Organic Crops: Revised Written Rating Report 

Organic Crops Deliverable 5.5.1.1.1: 

Revised Written Rating Report 

Contract Number: AG-645S-C-09-0003 

Submitted to:

United States Department of Agriculture

Risk Management Agency

 

Submitted by:

Watts and Associates, Inc.

4331 Hillcrest Road 

Billings, Montana 59101 

twatts@wattsandassociates.com

DUNS # 112960633 

RMA has modified this report for Section 508 Compliance 

February 1, 2010 

Watts and Associates, Inc., as a Contractor, has developed this material under contract with the United States Department of 

Agriculture and has exclusive ownership rights in part or all of its format and content. No material presented in any format, 

including orally, in print, or electronically, or that has been viewed, disseminated, or heard, may be further disseminated to 

any unauthorized person or entity. “Unauthorized person or entity” may i nclude, but i s not ne cessarily restricted to, any 

person who or entity that has no official connection to this project under the Federal government, or has not been authorized 

by Watts and Associates, Inc. to review a portion or all of this material. This material is protected by law.
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

i

Table of Contents 

Section I. Executive Summary ......................................................................................................... 1

Section II. Introduction and Overview ............................................................................................. 7

Section III. Organic Crop Yield Data Sources............................................................................... 15

Section IV. Literature Addressing Organic and Conventional Crop Yield Variability ................. 20

Section V. RMA Underwrtiting and Insurance Experience for Organic Crops ............................ 39

Section VI. Rating Analysis for Organic and Conventional Crops Based on Insurance 

Experience Data ........................................................................................................ 103

Section VI. Discussion ................................................................................................................. 125

Section VII. Recommendations ................................................................................................... 128

List of Tables

TABLE 1. 2008 Organic Crops Insured Under FCIC Plans of Insurance ....................................... 12

TABLE 2. States, Acreage, and FCIC Policies Earning Premium for Insured U.S. Organic 

Production ....................................................................................................................... 13

TABLE 3. Crops Named in the NASS Organic Production Survey and also Insured under 

Named-crop FCIC Programs .......................................................................................... 16

TABLE 4. Crops Named in the NASS Organic Production Survey but Not Insured under 

Named-crop FCIC Programs .......................................................................................... 16

TABLE 5. Number of Policies Earning Premium by Crop and Location with Five or More 

Producer Records for Organic Production Each Year from 2005 through 2008 ........... 19

TABLE 6. Parameters Illustrating the Potential Effects of Changes in 2006 Crop Year Rice 

Underwriting Lowering Premium Rates ........................................................................ 44

TABLE 7. Codes Specified for the Type 11 Record with Respect to Reporting Organic Data, 

1999-2008 ....................................................................................................................... 46

TABLE 8. Credible Crop/State Combinations at the 271 Indemnities per Crop/State Level .......... 47

TABLE 9. Credible Crop/State Combinations at the Adjusted Indemnities per Crop/State Level . 48

TABLE 10. Written Agreements issued by Type and Performance, 2001 through 2005 ................ 50

TABLE 11. Non-Organic Crops in Counties in Which a Written Agreement was Issued for 

Organic Practice, 2001 through 2005 ........................................................................... 52

TABLE 12. Organic Acreage Insured Under the OC and OT Common Option Code, 

2004 through 2008* ...................................................................................................... 54

TABLE 13. Number of Type 15 Records for Rice by State and Number of Actual Yields, 

2008 Type 15 File ......................................................................................................... 56

TABLE 14. Average Ratio of Actual Yields to Organic Reference Yield for Rice, 

by State and Number of Actual Yields, 2008 Type 15 File ......................................... 57

TABLE 15. Average Ratio of Actual Yields to Non-Organic Reference Yield for Rice, 

by State and Number of Actual Yields, 2008 Type 15 File ......................................... 58

TABLE 16. Average Multiplier of Base Premium Rate with Organic Reference Yield 

for Rice, by State and Number of Actual Yields, 2008 Type 15 File .......................... 58

TABLE 17. Rice: Number of Actual Yields by Organic Practice, 2008 Type 15 File .................... 59

TABLE 18. Use of Actual Yields and Ratio of Average Actual Yield to Reference Yield, 

All Crops and States ..................................................................................................... 60

TABLE 19. Wheat: Use of Actual Yields and Ratio of Average Actual Yield to 

Reference Yield, by State ............................................................................................. 61
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

ii

TABLE 20. Corn: Use of Actual Yields and Ratio of Average Actual Yield to 

Reference Yield, by State ............................................................................................. 62

TABLE 21. Soybeans: Use of Actual Yields and Ratio of Average Actual Yield to 

Reference Yield, by State ............................................................................................. 63

TABLE 22. Non-Organic Acreage of Same Crops Insured in Counties with a 

Common Option Code for Organic Practice, 2004 through 2008 ................................ 65

TABLE 23. Experience in Counties with Organic Practice Versus all Additional 

Coverage in the United States, 2004 through 2008 ..................................................... 67

TABLE 24. Top 15 Counties with Net Underwriting Gain and Top 15 Counties with 

Net Underwriting Loss, 2004 through 2008 ................................................................. 69

TABLE 25. Insurance Experience for Principal Crops Insured with Organic Common 

Option Codes, 2004 through 2008 ................................................................................ 71

TABLE 26. Insurance Experience for Same Crops Insured Without Organic Common 

Option Codes, 2004 through 2008 ................................................................................ 72

TABLE 27. Top Ten Organic Crops with Net Underwriting Gain and Top Ten Crops 

with Net Underwriting Loss, 2004 through 2008 ......................................................... 74

TABLE 28. Top Ten States with Acreage Insured Under Organic Common Option Codes, 

2004 through 2008 ........................................................................................................ 76

TABLE 29. Top Ten States with Net Underwriting Gain and Top Ten States with 

Net Underwriting Loss, 2004 through 2008 ................................................................. 77

TABLE 30. Contribution of Coverage Level to Realized Loss Ratios for Acreage 

with and without an Organic Code ............................................................................... 78

TABLE 31. Contribution of Coverage Level to Realized Loss Ratios for Acreage 

with and without an Organic Code with Loss Ratios Interchanged ............................. 79

TABLE 32. Crops with No Reported Indemnities (for either Conventional or Organic 

Production) in Counties with Insured Organic Production between 2001 and 2008 ... 80

TABLE 33. Crops with Aggregate Loss Ratios for Insured Conventional Production 

Greater than for Insured Organic Production between 2001 and 2008 in 

Counties with Insured Organic Production .................................................................. 81

TABLE 34. Summary of Insurance Performance of Organic and Non-organic Production 

by Crop in all Counties with Organic Production for that Crop ................................... 98

TABLE 35. Summary of APH Insurance Performance of Organic and Non-organic 

Production by Crop in all Counties with Organic Production for that Crop .............. 101

TABLE 36. Type 15 Record Counts .............................................................................................. 105

TABLE 37. Type 15 Policy Counts – 4 or More Actual Yields .................................................... 106

TABLE 38. Crop Policy Counts .................................................................................................... 107

TABLE 39. Paired Observations Standard Deviation Ratio (Organic/Conventional) 

Summary Statistics ..................................................................................................... 113

TABLE 40. Paired Observations Standard Deviation Ratio (Conventional/Organic) 

Summary Statistics ..................................................................................................... 114

TABLE 41. Log-Transformed Data Summary Statistics – Paired Yield Data .............................. 114

TABLE 42. Paired Observations Average Mean Yield Ratio (Organic/Conventional) 

Summary Statistics ..................................................................................................... 115

TABLE 43. Variance Homogeneity Test Results .......................................................................... 117

TABLE 44. Variance Ratio by Crop and Risk Region Summary Statistics .................................. 118
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

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restrictions on the title page of this report.

iii

TABLE 45. Paired Loss Experience Relative Loss Ratio Summary Statistics 

(Organic/Conventional) .............................................................................................. 119

TABLE 46. Log-Transformed Data Summary Statistics – Paired Experience Observations ........ 122

TABLE 47. Summary Statistics for Loss Ratio Differences ......................................................... 122

List of Figures

FIGURE 1. Tomato Yields under Four Different Management Practices* ..................................... 25

FIGURE 2. Tomato Yields Under Two Different Management Practices* ..................................... 27

FIGURE 3. Apple Yields in a New Grove under Three Different Management Practices* ............ 28

FIGURE 4. Corn Yields in the Iowa State Crop System Comparisons 1998 through 2008* .......... 30

FIGURE 5. Soybean Yields in the Iowa State Crop System Comparisons 1998 through 2008* .... 31

FIGURE 6. Corn Yields by Plot in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008*....................................................................................................... 32

FIGURE 7. Average Corn Yields in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008*....................................................................................................... 33

FIGURE 8. Soybean Yields by Plot in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008*....................................................................................................... 34

FIGURE 9. Average Soybean Yields in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008*....................................................................................................... 35

FIGURE 10. Wheat Yields in the Mid-Atlantic Region Crop System Comparisons 

1997 through 2008* ..................................................................................................... 36

FIGURE 11. Wheat Yields in the Mid-Atlantic Region Crop System Comparisons 

1998 through 2008 ....................................................................................................... 37

FIGURE 12. Comparison of Organic and Non-organic Insurance Experience for 

All Crops by Crop during the Period from 2001 through 2008 (each 

point represents one year for one crop) at the State, Risk Region, County, 

and Paired Unit Levels* .............................................................................................. 82

FIGURE 13. Comparison of Organic and Non-organic Insurance Experience for Wheat 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, County, and Paired Unit Levels* ....................................... 84

FIGURE 14. Comparison of Organic and Non-organic Insurance Experience for Corn 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, County, and Paired Unit Levels* ....................................... 85

FIGURE 15. Comparison of Organic and Non-organic Insurance Experience for Soybeans 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, County, and Paired Unit Levels* ....................................... 86

FIGURE 16. Comparison of Organic and Non-organic Insurance Experience for Rice 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, County, and Paired Unit Levels* ....................................... 88

FIGURE 17. Comparison of Organic and Non-organic Insurance Experience for Barley 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, and County Levels, by Year .............................................. 89

FIGURE 18. Comparison of Organic and Non-organic Insurance Experience for Apples 

during the Period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, County, and Paired Unit Levels * ...................................... 90
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

iv

FIGURE 19. Comparison of Organic and Non-organic Insurance Experience for All 

Fruits Except Apples during the Period from 2001 through 2008 (each point 

represents one year for one crop) at the Crop, State, Risk Region, County, 

and Paired Unit Levels* .............................................................................................. 91

FIGURE 20. Comparison of Organic and Non-organic Insurance Experience for All 

Vegetables during the Period from 2001 through 2008 (each point represents 

one year for one crop) at the Crop, State, Risk Region, County, and Paired 

Unit Levels* ................................................................................................................ 93

FIGURE 21. Comparison of Organic and Non-organic Insurance Experience for All 

Vegetables Except Potatoes during the Period from 2001 through 2008 

(each point represents one year for one crop) at the Crop, State, Risk Region, 

County, and Paired Unit Levels* ................................................................................ 94

FIGURE 22. Comparison of Organic and Non-organic Insurance Experience for Potatoes 

during the period from 2001 through 2008 (each point represents one year) 

at the State, Risk Region, and County Levels* ........................................................... 95

FIGURE 23. Yield Data All Observations County Map* .............................................................. 108

FIGURE 24. Yield Data Paired Observations County Map* ......................................................... 110

FIGURE 25. Loss Ratio Scatter Plot* ............................................................................................ 120

FIGURE 26. Relative Loss Ratio Histogram* ............................................................................... 121

FIGURE 27. Loss Ratio Difference Histogram* ............................................................................ 123

List of Appendices

Appendix A. Insured Organic Crops 2004 through 2007 

Appendix B. Referenced RMA Bulletins

Bulletin MGR-01-004 

Bulletin MGR-02-001 

Bulletin MGR-02-015 

Bulletin MGR-03-009 

Bulletin MGR-04-004

Appendix C. Loss Units by State and Crop

Appendix D. Reference and T-Yield Data

Appendix E. Insurance Experience Data for All State/County Combinations 

Appendix F. Insurance Experience Data by Crop

Appendix G. Organic Crop Underwriting Gain (Loss) 

Appendix H. Comparison of Organic and Non-organic Percentage Loss by Crop 

Appendix I. Samples of Type 11, 15, and 21 Data Used in the Rating Analysis 
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

1

SE CT ION I. E XE CUT IVE SUMMAR Y

The United States Department of Agriculture (USDA) Risk Management agency (RMA) 

awarded Contract Number AG-645S-C-09-0003 for a “review of the actuarial appropriateness of 

RMA’s organic rates and organic pricing arrangements.”1 “The objective of this contract [was]

to develop improvements in Federal crop insurance policies covering commodities produced in 

compliance with standards issued by the Department of Agriculture under the national organic 

program established under the Organic Foods Production Act of 1990 (7 U.S.C. 6501 et seq.), in 

accordance with the requirements of the Food, Conservation, and Energy Act of 2008.”2 The 

focus of this report on rating was to “review risk and loss experience of organic commodities

covered by RMA, as compared with the same crops produced in the same counties and during 

the same crop years using nonorganic [sic] methods.”3 “The review and [resulting] 

recommendation [are to] either confirm or refute the existence of significant, consistent, and

systemic variations in loss history between organic and non-organic production.”4 This report 

contains eight sections, including: this executive summary; an introduction and overview 

(Section II); an assessment of available data (Section III); a review of the academic literature 

(Section IV); an evaluation of insurance experience data (Section V); a premium rate analysis 

(Section VI); and discussions of findings and recommendations (Sections VII and VIII, 

respectively). 

Organic Production and Available Production Risk Data (Sections II and III). 

The Organic Foods Production Act, Title XXI of the 1990 Farm Bill, established Federal 

standards for the production of organic crops. The Title also identified processes for 

implementation of these standards through the United States Department of Agriculture (USDA) 

National Organic [Production] Program (NOP). Natural (non-synthetic) substances are generally 

allowed in organic production under these regulations and synthetic substances are generally 

prohibited. The 2007 USDA Census of Agriculture (Census) documented 20,437 farms engaged 

in organic production on 2,577,418 acres, with organic crops harvested from 1,288,088 acres. 

The Contractor initially made exhaustive efforts to gather available organic yield data from 

USDA sources, state resources addressing organic crops, producers and producer organizations, 

and the academic literature. These data were used in the review of risk and loss experience. 

Academic Reports of Yield and Yield Variability (Section IV)

There are numerous academic studies comparing organic and conventional yields and corollary 

studies comparing organic and conventional yield variability. Although some statistically 

significant differences exist between yields in some circumstances, there is no consistent or 

systemic pattern in these relationships. Generally, corn managed under organic practices has 

lower yields than corn managed under conventional practices. This relationship deteriorates over 

time (i.e., organic yields improve) as producers experience with organic production practices 

increases and as the locale is affected by these practices. Yields for soybean under organic 

practices with long rotational cycles are often comparable and occasionally higher than yields 

under conventional practices. The relationships of yields of crops under organic and 

conventional practices vary with the crop, the locale, and specific environmental conditions. 

 

1 USDA, RMA, 2009, Contract Number AG-645S-C-09-0003, Section 5.3 Scope of Work. 2 USDA, RMA, 2009, Contract AG-645S-C-09-0003, Statement of Work: 5.1. Contract Objective. 3 USDA, RMA, 2009, Contract Number AG-645S-C-09-0003, Section 5.4.1.1. 4 Ibid.
Organic Crops: Revised Written Rating Report 

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2

Evaluation of the Experience Data (Section V) 

The Contractor also conducted an extensive analysis of the FCIC risk and loss experience of 

organic crops as compared with the same crops produced in the same counties and during the 

same crop years using non-organic methods. The Contractor initially compared the underwriting, 

risk, and loss experiences of organic and non-organic crops from an underwriting perspective. 

The report on this analysis includes 

(1) An extensive evaluation of the experience data accumulated by RMA and consideration 

of rate structure for organic crops in light of the causes of loss reported for those crops; 

(2) A rate analysis conducted using the same RMA data; and

(3) Additional evidence about organic and non-organic production from alternative sources, 

primarily academic reports of yield and yield variability of organically and 

conventionally produced crops. 

Inasmuch as the purpose of the review is to “either confirm or refute the existence of significant, 

consistent, and systemic variations in loss history exist between organic and conventional 

commodities, either collectively or on an individual crop basis,”5

 the Contractor has explored a 

wide variety of mechanisms to consider the risk and loss experience in the context of the 

underwriting requirements for the organic production. The underwriting review is comprised of 

three elements: underwriting procedures, insurance experience, and causes of loss in crops 

insured with the organic codes. The results of the underwriting analysis do not provide sufficient 

statistical evidence that organic and conventional production methods result in significant, 

consistent, and systemic differences in insurance experience. The data indicate a wide range of 

relationships between conventional and organic production. 

As the analysis reveals, the aggregate insurance experience for organic production has been very 

different from that of conventional production over the observations captured in the available 

data. Although the data provide a noisy picture and are not well suited to aggregate analysis (as 

evidenced by substantially different implied surcharges in the data), the overall weight of the 

aggregate performance is too great to dismiss. The Contractor notes that the aggregate insurance 

performance of organic crops has been inferior to that of conventional crops. The data currently 

available are too sparse and noisy to draw sound actuarial/statistical conclusions to support 

premium rate revisions at any acceptable level of aggregation. It is clear from the aggregate loss 

cost ratios and loss ratios that “organic” is different from “non-organic.” Unfortunately the data 

at less than national aggregate becomes very unstable. The organic and conventional experience 

comparison at the national crop level suggests considerable deviations from non-organic rates in 

many cases, with both substantial discounts and increases in the rates, if the data are to be 

believed. The Contractor does not believe such substantial departures from non-organic rates are 

justified, and does not believe the data is reliable enough or representative of the true underlying 

distributions to support these substantial deviations from rates for non-organic production. 

However, this comparison ignores other important aspect of the organic insurance offer such as 

loss ratios, T-yields, and reference yields, which play a crucial role in creation of a sustainable, 

actuarially sound program. Assuming insurable conditions for organic crops are appropriately 

captured in the available RMA data, an increase in premiums of the magnitude implied by the 

ratio of loss cost ratios would make the program much less attractive to organic producers and 

 

5 Ibid.
Organic Crops: Revised Written Rating Report 

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3

likely encourage only the riskiest of organic producers to participate in the program. 

Furthermore, when examined from a wide variety of perspectives, this pattern is neither 

consistent nor systemic. For some crops, regions, and years, organic crops have lower losses than 

their conventional counterparts. This is true even at the risk region and state levels of 

aggregation. In many crops, conventional crops have a higher level of loss than organic crops in 

extreme risk circumstances (very high losses, as established by the loss ratio or loss cost ratio for 

the conventional production), but a lower level of losses when responding to lower levels of risk. 

The approach applied to organic rating to date, a flat surcharge applied uniformly across all crops 

and geographies, was a logical starting point for insurance development, especially considering 

the public policy goals, the required timeframe for action, and the paucity of available data. The 

variations in performance at all levels of aggregation suggest that substantial adjustments will 

need to be made to establish equitable and sustainable programs for individual organic crops and 

geographies. Such adjustments may include changes to the reference yields, T-yields, rate 

structure, underwriting, and pricing. The challenges are the breadth of adjustments that will 

likely need to be made over time and the likely interaction of the factors in the performance of 

the resulting product. 

Rate Analysis (Section VI) 

A review of premium rate adequacy and appropriateness was undertaken by the Contractor’s 

Rating Department. Data used to test the null hypothesis that organic and conventional 

production face the same insurance risk (expected loss cost) in a given locale on a per acre basis 

were gathered from RMA Type 11 (acreage record), Type 15 (yield record), and Type 21 (loss 

line record) datasets from crop years 2001 through 2008. In addition to consideration of 

historical loss experience, this element of the rate analysis also examined the Type 11 and 21 

files to evaluate insurance experience and the Type 15 files to compare historical short-run yield 

variability between conventional and organic production. The experience and yield datasets were 

grouped by policy into two non-mutually exclusive groups, first of paired observations (policies 

which insured units in which the acreage was either all organic or all non-organic) and then of all 

observations. The paired datasets allow outcomes (insurance experience and yield variability) 

from acreage insured under the same policy grown under conventional and organic methods to 

be directly compared Due to potential asymmetries in the “sampling” that produces the “all 

observations conventional” and “ all observations organic” groups, and because of the 

“matching” of elements of practices (i.e., soil types, experience, microclimate, etc.) in the paired 

dataset that focus the analysis primarily on the differences between non-organic and organic 

production practices, the paired dataset is the preferred dataset for the analysis. Unfortunately, 

the breadth and depth of the paired dataset is extremely limited. The second grouping includes all 

units in a county for each crop/county combination for which there was organic production. 

Attributes were evaluated across policies (producers) to compare organic production and 

conventional production in total, without the benefits of the paired sampling. 

Organic data available for the “all observations” exercise are limited, although more robust than 

the data in the paired dataset. The results of the rating analysis do not provide sufficient 

statistical evidence to reject the null hypothesis that organic and conventional production 

methods face the same insurance risk. While there are differences in yield, loss ratios, and loss 

cost ratios of non-organic and organic production, the differences are not generally statistically 
Organic Crops: Revised Written Rating Report 

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4

significant.

6 Furthermore, the data show a wide range of relationships between conventional and 

organic production, especially in the crops where data are sparse. This diversity of responses is 

evident at all levels of aggregation, but is less conspicuous as data from larger areas and across 

crops are aggregated. The data are not robust enough to dig deep into specific situations for crop 

by crop or state by state results. The high degree of variability in the results leads to a failure to 

reject the null hypothesis that organic and conventional production face the same insurance risk 

(expected loss cost). Currently, RMA typically uses a multiplicative load of 1.05 on organic 

contracts (with a few minor exceptions) and it is important to note the analysis presented in this 

section did not directly test if 1.05 is appropriate. Furthermore, it should be noted the failure to 

reject the null hypothesis that production risks are the same does not imply that 1.05 is an 

actuarially unsound value. With available data it is not currently possible to develop an 

appropriate multiplicative rate adjustment factor for all organic crops. Further study is 

recommended as more data become available.

There is not proof of a significant, consistent, and systemic difference in insurance experience or 

yield variability between organic and conventional production. Nonetheless, within the RMA 

dataset there are specific cases where data exist to identify substantial differences in yield 

variability between organic and non-organic practices. In those instances, as sufficient data 

become available, further analysis will indicate whether the crop grown under organic practices 

is simply an element of the larger set grown under good farming practices or if the organic 

practice requires an independent rate structure (or discount or surcharge). 

Discussion and Conclusions (Sections VII and VIII)

The review exposes some challenges in analyzing the insurance experience data comparing 

organic and conventional commodities, either collectively or on an individual crop basis. In most 

cases, where patterns might have been thought to exist, it was also possible to identify where 

those patterns break down. With the limited data available, artifacts of aggregation and sampling 

have the potential to lead to potentially dangerous generalizations. The Contractor has attempted 

to avoid this pitfall and identify where it has occurred in other analyses. 

The Contractor’s review refutes the existence of significant, consistent, and systemic variations 

in loss history between organic and non-organic commodities on an individual crop basis. When 

data for all crops in all areas are aggregated, the collective insurance experience for organic 

production has been very different from the insurance experience for non-organic production 

over the observations captured in the available data. Although the data provide a noisy picture 

and are not well suited to aggregate analysis, the overall weight of the aggregate performance is 

too great to dismiss. Public policy precludes the option simply to maintain the existing surcharge. 

Based on Contractor research, it appears that the organic insurance pool is subject to adverse 

selection by a subset of unusually high-risk producers. If the premium rates were raised by the 

value implied by the available aggregate data, the most likely outcome would be to assure this 

adverse selection would be exacerbated in future years. Rating, pricing, reference yields, T-

 

6 It should be noted that tests of statistical significance are highly dependent on the number of observations available in the applicable data. Given 

the small overall dataset, the differences in performance between organic and conventional observations would have had to have been relatively 

large and consistent to meet statistical significance at high levels of confidence. In this circumstance, the failure to demonstrate statistical 

significance does not necessarily indicate that differences do not exist in the underlying population but rather, that the data available are not 

adequate to verify these relationships to a high degree of confidence.
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5

yields, and good farming practices need to be addressed collectively on a regional/crop basis, and 

cannot be addressed effectively until more representative data become available. 

Blanket recommendations for all crops cannot be supported given the inconsistency of the data, 

and there are limited data to support specific recommendations for any given crop. However, 

there are a number of examples that demonstrate the T-yields are generally too high. In both the 

aggregate and for the major crops the average of actual organic yields certified by producers is 

approximately 65 percent of the reference yield. The risk analysis clearly indicates that 

inappropriate transitional yields are a significant source of the higher loss costs observed for the 

organic practice. There is substantial variation among states within crops and among crops as 

evidenced in this and other information contained in the report. Since the data at lower levels of 

aggregation is noisy and inconsistent, the remaining assessment focuses on the aggregate data. 

Nonetheless, the Contractor’s recommendations are formulated to address different risk profiles 

and insurance structures. 

The Contractor recommends RMA impose no premium differential for crops for which the Crop 

Provisions specify a very limited set of causes of loss that clearly are independent of 

management or other variable circumstances (These crops include those insurable under the 

Florida Citrus Fruit Crop Provisions (09-026); the Texas Citrus Tree Crop Provisions (99-025); 

the Macadamia Tree Crop Provisions (99-024); the Nursery Crop Provisions (08-073); the 

Florida Fruit Tree Provisions (08-0014); the Hawaii Tropical Trees Pilot Crop Provisions (09-

0265); all crops included under the Common Group Risk Plan (GRP), Basic Provisions. 09-102; 

all crops included under the Group Risk Income Protection Basic Provisions (05-GRIP-BASIC; 

and all acreage included under the Pasture, Forage, and Rangeland programs). For the crops for 

which the guarantee is not based on APH procedures (plan codes 50, 51, and 55), the Contractor 

recommends RMA make no adjustments to rates until a threshold value of organic units is 

represented in the experience dataset. For those crops for which the guarantee is not based on 

APH procedures and which meet the threshold, the Contractor recommends a premium 

differential (increase or decrease) based on the implicit differential (surcharge or discount) as 

illustrated in the report. The Contractor further recommends that the maximum reference amount 

of insurance for organic crops insured under the plans that do not use APH guarantees be 

reduced by one-third. 

Because of the confounding effects of T-yields on insurance experience for crops whose 

guarantee is based on APH procedures, these crops need to be treated by an alternate approach. 

Regardless of the extent of the experience data, for all plan code 25 (Revenue Assurance); plan 

code 42 (Income Protection); plan code 44 (Crop Revenue Coverage); plan code 45 (Indexed 

Income Protection); and plan code 90 (Actual Production History) crops, the Contractor 

recommends transitional yields be reduced by 35 percent and that no rate differentials between 

organic and conventional production be implemented until sufficient data under this new 

approach are available. The effect of this will be to insure organic production at the same 

premium rate and cost as that charged for non-organic practices for the same yield. These 

recommendations are based specifically on the role T-yields have played in the experience data 

collected to date. 
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6

The Contractor further recommends that the organic practice be established as a separate 

type/practice to facilitate the reduction in the transitional yields. To achieve the greatest ability to 

accrue relevant data, Crop Provisions should be modified to allow organic practice as a separate 

insurance unit. 

These adjustments are intended to reduce the impact of adverse selection going forward. The 

emphasis would then be on examining and explaining the ongoing insurance experience of 

organic practice and making appropriate adjustments as that experience is accrued. Judgmental 

rate increases (or discounts), limited to 10 percent to support the accumulation of data going 

forward, may be warranted for those crops afforded new price election until credible loss-costbased rate determinations by crop/region are possible. 
Organic Crops: Revised Written Rating Report 

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7

SE CT ION II. INT R ODUCT ION AND OV ERVIEW

Prior to the industrial revolution, most agricultural production worldwide was based primarily on 

on-farm produced inputs. As transportation systems improved and chemical manufacturing was 

industrialized, substantial changes in crop production practices, especially in the Western 

Hemisphere, occurred. Monoculture, the cultivation of a single crop on a farm or in a region, 

allowed significant mechanization of many labor-intensive farming activities. Use of off-farm 

inputs (including seed, mineral nutrients, and pesticides) became more common. Late in the 19th

Century, as consumers became aware of these changes in agricultural practices, the concept of 

organic farming, farming eschewing synthetic inputs, developed. However, the term “organic 

farming” was not generally applied to the practices for an additional half century.7

In most developed economies, organic practices were largely abandoned during the period 

between the two World Wars. This was a period of rapid developments in synthetic organic 

chemistry and plant breeding. Synthetic nitrogen fertilizers produced using Haber-Bosch

synthesis of ammonium nitrate replaced guano and manure as sources of nitrogen for agricultural 

applications. Use of these synthetic fertilizers generally increased crop yields, especially when 

monoculture and limited rotations were the predominant approach.

8

During the same period, crop breeding programs identified the potential benefits of heterosis on 

yields. Shull defined heterosis as “the interpretation of increased vigor, size, fruitfulness, speed 

of development, resistance to disease and to insect pests, or to climatic rigors of any kind, 

manifested by crossbred organisms as compared with corresponding inbreds, as the specific 

results of unlikeness in...the parental gametes.” The “hybrid vigor” characterizing heterosis led 

to the development of the commercial seed production industry. The development of proprietary 

hybrid seed lines, first for corn, and eventually for most major and minor crops, introduced a 

substantial genetic component affecting yields.

9

 Soon after World War II, the use of synthetic 

pesticides and hybrid seed in the United States became prevalent practices. These practices 

increased farm yields far beyond pre-World War II levels.10 Subsequently, in the 1990s, 

genetically modified crops11 (GMOs) were added to the repertoire of technologies that affected 

crop yields. Corn,12 cotton, and rice13 are among the major crops whose yields are reported to 

have improved most substantially through specific transgenic modifications. 

Increased environmental awareness and growing demand for organic foods fueled the growth of 

organic farming in the 1970s. At the time, there was general agreement on a philosophical 

approach for the organic farming concept, but no accepted standards defining the practices. 

Initially, state certification programs developed standards based on regional production practices. 

Eventually, a movement to develop a national organic standard led to the Organic Foods 

 

7 Walter Ernest Christopher James (Lord Northbourner), 2002 (first published 1940), Look to the Land, Sophia Perennis Books, Hillsdale, NY. 8 Zandstra, H. G., R. H. Anderson and W. K. Dawley, 1969, Effects of fertilizer on yield and quality of Norland potatoes in northeastern 

Saskatchewan, American Journal of Potato Research, 46: 1099-209X.; Erisman, J.W., M.A. Sutton, J. Galloway, Z. Klimont and W. Winiwarter, 

2008, How a century of ammonia synthesis changed the world, Nature Geoscience 1, 636 - 639 (2008) 9 Basra, A.S., 2000,, Heterosis and Hybrid Seed Production in Agronomic Crops, Food Products Press, Binghamton, NY. 10 University of California, San Diego, undated, Bacillus thuringiensis: Synthetic Fertilizers, http://www.bt.ucsd.edu/synthetic_pesticide.html, 

accessed, June 1, 2009.

11 Organisms whose genetic information has been altered using genetic engineering techniques known as recombinant DNA technology. 12 Rice, M.E., 2004, Transgenic Rootworm Corn: Assessing Potential Agronomic, Economic and Environmental Benefits, Plant Health Progress 

doi:10.1094/PHP-2004-0301-01-RV, http://www.plantmanagementnetwork.org/pub/php/review/2004/rootworm/, accessed June, 2009. 13 Raney, T., 2006, Economic Impact of Transgenic Crops in Developing Countries. Current Opinion in Biotechnology 2006, 17:1-5, 

http://www.agbioworld.org/pdf/raney.pdf, accessed June, 2009.
Organic Crops: Revised Written Rating Report 

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8

Production Act (OFPA), Title XXI of the 1990 Farm Bill.14 OFPA provided for the 

establishment of Federal standards for production of organic crops. OFPA was incorporated into 

the United States (U.S.) Code as Chapter 94 of Title 7.15 The language of OFPA also identified 

processes for oversight of Federal organic standards by the USDA National Organic Program 

(NOP), which “develops, implements, and administers national production, handling, and 

labeling standards for organic agricultural products.”16 

Use of natural (non-synthetic) substances in organic production is generally allowed under NOP 

regulations, while use of synthetic substances is prohibited. Consequently, organic crops are 

produced without employing most conventional pesticides17 or petroleum-based and sewagesludge-based fertilizers. Furthermore, the NOP regulations prohibit the use of GMOs and 

ionizing radiation in organic production and handling. 

In 2005, organic farmland in all 50 states was certified under NOP. Nonetheless, in 2007, 

certified organic cropland and pasture comprised less than 0.5 percent of total U.S. cropland.18

The 2007 USDA Census of Agriculture (Census) documented 20,437 farms engaged in organic 

production on 2,577,418 acres, with organic crops harvested from 1,288,088 acres on 16,778 

farms and 975,380 acres of organic pasture on 7,268 farms. The Census data indicate 12.2 

percent of the acreage (313,950 acres) managed under organic practices was neither harvested 

nor used as pasture, but instead may have been in summer fallow or similar conservation use.

Comparable values for all production are 2,204,792 farms engaged in production on 922,095,840 

acres, with crops harvested from 309,607,601 acres on 1,328,004 farms and 408,832,116 acres of 

pastureland on 1,132,606 farms, with 203,656,123 acres (22.1 percent) managed under 

conventional practices that were neither harvested cropland nor pastureland. 

As a follow-up to the 2007 Census, the USDA National Agricultural Statistics Service (NASS) is 

conducting a wide-scale survey of organic producers and producers transitioning to organic 

practices. Organic Production Survey (Survey) instruments were mailed in early May, 2009. 

Results are expected to be available in early 2010.19 Questions in the survey address all aspects 

of the practices, ranging from production and marketing activities to income and expenses. The 

survey results will provide the most comprehensive snapshot of organic production in the United 

States to date. The responses to the survey will substantially increase virtually every type of data 

available on commercial U.S. organic production practices, production, and acreage. 20

 

14 Federal Organic Foods Production Act of 1990, 2004, http://www.sarep.ucdavis.edu/Organic/complianceguide/national6.pdf, accessed March, 

2009.

 It is 

likely these survey data, in conjunction with Census data, will provide a basis for further 

15 U.S. Code, Title 7, Chapter 94, 2007, http://www.law.cornell.edu/uscode/7/usc_sup_01_7_10_94.html, accessed March, 2009. 16 USDA, AMS, National Organic Program: Program Overview, 2009, 

http://www.ams.usda.gov/AMSv1.0/ams.fetchTemplateData.do?template=TemplateA&navID=NationalOrganicProgram&leftNav=NationalOrga

nicProgram&page=NOPNationalOrganicProgramHome&acct=nop, accessed April, 2009.

17 Pesticides like pyrethrins, derived from natural sources, can be used on organic crops. 18 The distribution of cropland and organic farmland are illustrated in Census maps found at 

http://www.nass.usda.gov/research/2007mapgallery/album/Farms/Land_in_Farms_and_Land_Use/slides/Acres%20of%20Total%20Cropland.ht

ml and 

http://www.nass.usda.gov/research/2007mapgallery/album/Farms/Land_in_Farms_and_Land_Use/slides/Acres%20Used%20for%20Organic%20

Production.html, respectively. 19 The original release date was late 2009. This was modified in May 2009 to early 2010. USDA, NASS, 2009, Organic Production Survey FAQs, 

http://www.agcensus.usda.gov/Surveys/Organic_Production_Survey/FAQs/index9.asp. 20 To assist readers using this report as a stand-alone document, some information in the introduction speaks to issues also addressed in the report 

on pricing for FCIC insurance of crops produced under NOP approved practices.
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9

exploration of yield relationships between organic and non-organic production for some crops. 

Further study is recommended to determine how these data affect the agency’s treatment of crops 

produced under organic practices. 

While much of the organic production occurs in areas where growers participate actively in 

Federal Crop Insurance Corporation (FCIC) programs in 200721 the proportion of organic 

acreage insured under FCIC programs was about half the proportion insured for conventional 

production.22 Insurance of organic crops has been influenced substantively by Federal 

legislation. The Agricultural Risk Protection Act of 2000 (ARPA) required RMA to address

certified organic farming practices as good farming practices and to provide insurance coverage 

for crops produced under these practices. Federal crop insurance coverage for organic producers 

was initially provided through written agreements and subsequently through standard crop

insurance policies, using standard policy terms, but with an additional five percent rate load to 

account for the limited available insurance experience for the practices, RMA’s producer yieldsbased rate theory, and uncertainty related to the organic practices.23 Testimony from organic 

producers and representatives of organic producer organizations suggests those producers 

perceive the 5 percent rating surcharge applied to all organic crops is unfair, in spite of the fact a 

Federal subsidy covers approximately 67 percent of the premium.

Section 12023 of the Food, Conservation, and Energy Act of 2008 requires RMA to contract for 

“a review of the underwriting, risk, and loss experience of organic crops covered by the 

Corporation, as compared with the same crops produced in the same counties and during the 

same crop years using nonorganic24 methods ...as established using data collected and 

maintained by the Secretary [of Agriculture] or from other sources.”25 To the maximum extent 

practicable, the review is to “allow the Corporation to determine whether significant, consistent, 

or systemic variations in loss history exist between organic and nonorganic production.” 

RMA awarded Contract AG-645S-C-09-0003, Organic Crops: Review of Risk and Loss 

Experience and Development of Additional Price Election Procedures, to support research to 

develop this review. It is important to note the objective of the contracted work on rating, as 

described in the solicitation. 

“The objective of this contract is to develop improvements in Federal crop 

insurance policies covering commodities produced in compliance with standards 

issued by the Department of Agriculture under the national organic program 

established under the Organic Foods Production Act of 1990 (7 U.S.C. 6501 et 

 

21 See the Census map on organic production referenced earlier and the Census map on Federally insured crop land at 

http://www.nass.usda.gov/research/2007mapgallery/album/Farms/Land_in_Farms_and_Land_Use/slides/Acres%20Enrolled%20in%20Crop%20

Insurance%20Programs.html), 22 Based on 2007 Census of Agriculture total crop production data and RMA Summary of Business as compiled by the Contractor. 23 USDA, RMA, 2008, Organic Crops: Review of Risk and Loss Experience and Development of Additional Price Election Procedures, 

Statement of Work, Section 5.2.

24 For the purposes of this report, the words “nonorganic” [sic], “non-organic,” and “conventional” are both used. While the Crop Insurance 

Handbook defines “nonorganic farming practice” as “a practice commonly recognized in a conventional farming operation by which synthetic 

pesticides and fertilizers are used” and “conventional farming practice” as “a system or process for producing an agricultural commodity, 

excluding organic farming practices, that is necessary to produce the crop that may be, but is not required to be generally recognized by 

agricultural experts for the area to conserve or enhance natural resources and the environment.” Conventional and non-organic both effectively 

exclude organic production practices. 25 USDA, RMA, 2009, Contract AG-645S-C-09-0003, Section 5.2. Background. 
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10

seq.), in accordance with the requirements of the Food, Conservation, and Energy 

Act of 2008.”26

An additional RMA objective identified in the solicitation is to facilitate the eventual 

establishment of unique organic practice rating components as research is completed and more 

insurance experience is accumulated. Furthermore, the contract requires: 

 

“The review and recommendation should either confirm or refute the existence of 

significant, consistent, and systemic variations in loss history between organic 

and conventional commodities, either collectively or on an individual crop basis.” 

[emphasis added by the Contractor] 27

“Significant,” as a statistical term, means occurring not merely by chance, but rather as a result 

of actions or outcomes that are closely linked (i.e., that are connected by strong correlations or 

by a causal relationship). Statistical significance measures the likelihood of a statistical test

obtaining the same result repeatedly, or the likelihood that the relationship described by the 

sample data accurately reflects the underlying population and was not the product of chance in 

sampling. In the context of such testing, significance levels (equated to the Greek letter α) are 

chosen by the researcher. Commonly used significance levels are 0.05, 0.01, and 0.001 (5 

percent, 1 percent, and 0.1 percent respectively). Type I errors (false positives) are minimized 

with lower significance levels. Type II errors (false negatives) become less likely with higher

significance levels, so the significance levels are often chosen with the potential impacts of 

Type I and Type II errors in mind. Researchers may examine more than one α level in the 

course of an analysis. After an α level is chosen, it is then compared against the probability 

level determined through an appropriate statistical test. If the probability level of an event 

occurring by chance is less than the chosen significance level, the event is deemed statistically 

significant. If an α level of 0.01 is chosen, an event must occur less than 1 percent of the time 

due to the effect of chance to be considered significant. Regarding a comparison of organic and 

conventional yields, yield variability, and insurance experience, the challenge is identifying 

data where it is possible to make any appropriate test of significance.

“Consistent” has a similar meaning when applied to both meta-data analysis28

 

26 USDA, RMA, 2008, Organic Crops: Review of Risk and Loss Experience and Development of Additional Price

 and descriptive 

statistics. The term consistent means free from substantial variation or contradiction. 

Statistically, consistency can imply a small standard deviation or coefficient of variation. 

Consistency is also often associated with statistical estimators; consistent statistical estimators 

grow closer and closer to the parameter they are estimating as the sample size grows larger.

Logically, if there is a consistent relationship between conventional crops and organic crop 

yield variability, exceptions to that pattern would be limited and sporadic, particularly in large 

samples. In the context of crop insurance, inconsistency in the yield of a particular crop can

lead to higher coefficients of variation, which generally equate to higher rates. However, the 

rates would be expected to be consistently higher if the yield variability is consistently higher

and, conversely, to be lower where yields have consistently lower coefficients of variation.

Election Procedures Solicitation, and USDA, RMA, 2009, Contract AG-645S-C-09-0003, Statement of Work: 5.1. 27 USDA, RMA, 2008, Organic Crops: Review of Risk and Loss Experience and Development of Additional Price Election Procedures 

Solicitation, and USDA, RMA, 2009, Contract AG-645S-C-09-0003, Statement of Work: 5.4.1.1. 28 Metadata are values and/or other documentation that describes objects in a formalized way. They provide information on data and about 

processes of producing and using data. Metadata describe statistical data and, to some extent, processes and tools involved in the production and 

usage of statistical data. Consequently, data collected using different sampling methods, though having similar values, may not be considered 

consistent unless there are appropriate tests of the sampling methods themselves. 
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11

“Systemic” means of a system, relating to a system, or common to a system. In this instance, 

the system is a system of organic and conventional crop production. If there is a systemic 

difference between performance of crops under these practices, that difference would be 

expected to exist for different crops, in different regions, and at different times. Furthermore, 

“systemic variations” can be expected to be similar across disparate observations (i.e., if the 

conventional practice consistently results in a 15 percent higher yield in a crop, it would be 

expected to result in a similarly consistent elevated yield in another crop if the differences are

to be considered systemic). In addition, there is a system of crop insurance experience. If there 

is a systemic difference between the insurance experience for crops under the organic and 

conventional practices, that difference would be expected to exist for different crops, in 

different regions, and at different times. 

Consequently, the contract establishes very high standards for the comparison of organic and 

conventional risk and loss experience. To identify the existence of significant, consistent, and 

systemic variations in loss history between organic and conventional commodities, either 

collectively or on an individual crop basis, requires sufficient data for an appropriate analysis 

of these crucial characteristics. 

There are three possibilities that each require different amounts of data for evaluation. First, the 

risk characteristics of organic production may simply be a subset within the risk characteristics 

of the same crop within the larger population of all good farming practices. Second, organic 

production of a crop may track conventional production of the same crop, but with yields 

modified by an additive or multiplicative factorial relationship. Finally, the organic crop may 

be so different from the conventional crop that it is best treated entirely independently. Data 

requirements in each case will be influenced by the consistency of the yield relationship 

between the two practices. A single organic producer in a region cannot provide a basis for any 

statistical test of significance, even if his or her data covers a number of years of production. 

Furthermore, a large number of producers with one or two years of data also provide a very 

limited basis for testing of yield differences. The sample size greatly influences whether a 

hypothesis “the yield risks associated with the practices are not different” can be tested, and if 

it can be tested, whether the hypothesis can be rejected.

While the contract indicates RMA would provide insurance experience for the 2004, 2005, 

2006, and 2007 crop years, the Contractor also obtained data for 2001 through 2003 and for 

2008 from RMA, and incorporated those data into the review when appropriate. The 

Contractor identified no biases resulting from the incorporation of these additional data. 

However, incorporation improves the analysis by increasing both the depth (i.e., the period 

considered) and breadth (i.e., locations and crops considered) of the dataset. Yet even with the 

inclusion of these additional data, the insurance experience dataset for most crops is thin. The 

crop by crop differences in yields and yield variability, as well as the regional and temporal 

differences in insurance experiences, argue against treating all organic production identically 

or in aggregate. However, for a limited number of crops and states, sufficient losses to meet 

RMA’s credibility standard for counties have been accrued at the state level. The Contractor 

believes an additional two to three years of experience will likely supply sufficient data for 

credibility-weighted adjustment of rating for additional crops grown organically. 
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12

To further address the question of “significant, consistent, and systemic variations” in insurable 

risks between organic and conventional commodities, either collectively or on an individual 

crop basis, the Contractor made extensive efforts to identify and collect available organic and 

non-organic crop yield comparisons and comparisons of yield variability data from a wide 

variety of sources. The Contractor then examined the available data, with special attention to 

the context provided by the limited Federal organic crop data and by the role of yield and yield 

variability in establishing crop insurance rates. The Contractor believes this approach addresses 

the requirements that the review “include the widest available range of data collected by the 

Secretary and other outside sources of information; and ...not be limited to loss history under 

existing crop insurance policies.”29 

The work encompassed under Contract AG-645S-C-09-0003 is demanding due to the breadth of 

organic crops produced. In 2008, there was a wide range of crops produced organically and 

insured under FCIC programs (Table 1 and Appendix A). The insured crops ranged from a single 

unit of filler tobacco on half an acre to 1,788 units of wheat (0.3 percent of all insured wheat 

units in 2008) comprising almost 200,000 acres (0.4 percent of all insured wheat acres in 2008). 

T ABLE 1. 2008 Organic Crops Insured Under FCIC Plans of Insurance

Alfalfa Seed Citrus - Florida (continued) Corn, Popcorn Peaches, Fresh Freestone 

Almonds Citrus IV - Navel Oranges Corn, Sweet Peas, Dry

Apples Tangelos, and Tangerines Cotton Peas, Green

Apricots, Fresh Citrus V - Murcott and Temple Cotton - Extra Long Staple Peanuts

Apricots, Processing Oranges Cranberries Pears

Avocados Citrus VII - Grapefruit and Figs Plums

Barley Late Oranges Flax Potatoes

Beans, Processing Citrus - Texas Forage Production Prunes

Beans, Dry Grapefruit Forage Seeding Rice

Blueberries Citrus Trees - Florida Grain Sorghum Rye

Cherries Grapefruit Trees Grapes Safflower

Citrus - California and 

Arizona Orange Trees Grapes, Table Soybeans

Lemons All Other Citrus Trees Macadamia Nuts Strawberries

Mineola Tangelos Citrus Trees - Texas Macadamia Trees Sunflowers

Mandarins Citrus Trees I - Early and Millet Tobacco, Burley

Grapefruit Midseason Orange Trees Mustard Tobacco, Cigar Filler 

Oranges, Valencia Citrus Trees IV - Rio Red and Nectarines, Fresh Tobacco, Cigar Binder 

Oranges, Navel Star Ruby Grapefruit Trees Oats Tobacco, Flue Cured 

Oranges, Sweet Citrus Trees V - Ruby Red Onions Tomatoes

Citrus - Florida Grapefruit Trees Peaches Walnuts

Citrus I - Early and 

Midseason Corn Peaches, Cling Processing Wheat

Oranges Corn, Hybrid Seed Peaches, Freestone Processing Wild Rice, Cultivated

Source: The Contractor’s analysis of RMA Summary of Business Data, June, 2009 

A number of favorable and unfavorable preconceptions concerning organic production add to the 

challenge of evaluating differences in the performance of crops under conventional and organic 

 

29 Section 12023 of the Food, Conservation, and Energy Act of 2008, 122 STAT. 2147.
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13

practices. Due to the increased production that accompanied the introduction of synthetic 

fertilizers and pesticides, there is a general assumption that yields under organic practices will 

necessarily be lower than those under conventional practices. Based on a review of the literature

and RMA data, this is not always the case. Furthermore, while the NOP regulations prohibit the 

use of genetically modified organisms30 and ionizing radiation in organic production and 

handling, many other technologies have contributed to substantial increases in productivity of 

organic crops. These include, but are not limited to, development of better seed through 

conventional breeding, advances in irrigation, developments in tillage/bedding technologies, 

substantial improvements in data management and analysis, and a better understanding of the 

effects of extended crop rotations. Under some conditions, organic crop yields may exceed those 

for crops produced under conventional practices, especially when longer rotations are used and 

conditions under the two practices are matched as much as the management practices allow. 

The wide range of locations involved in organic production (Table 2) and the relatively limited 

data available in each area add to the complexity of the required analysis of insurance 

experience. Examination of patterns on a fine scale simultaneously introduces the possibility of 

sampling errors (which are more likely in smaller samples) on the one hand and poorly matched 

samples for comparison on the other. Due to the limited data and the challenges in creating a 

well-designed comparison, analysts are reluctant to disregard poorly matched data in the absence 

of a perfect match.

T ABLE 2. States, Acreage, and FCIC Policies Earning Premium 

for Insured U.S. Organic Production 

Year States Acres

Policies 

Earning 

Premium

2001 26 27,938 145 

2002 25 72,789 445

2003 26 77,767 578

2004 33 225,539 1,520

2005 34 280,942 1,898 

2006 36 368,909 2,576

2007 37 439,451 3,110

2008 38 479,668 3,565

Source: The Contractor’s analysis of RMA Summary of Business Data,

December, 2008

The Contractor’s assessment of insurance experience and the yield and loss data address the 

questions raised in the “Scope of Work” as described in the solicitation and the ensuing contract.

The remainder of this report documents: 

• An assessment of available data;

• The literature addressing organic and conventional yield variability;

• RMA underwriting and insurance experience for organic crops; 

 

30 These are organisms whose genetic information has been altered using genetic engineering techniques known as recombinant DNA technology. 
Organic Crops: Revised Written Rating Report 

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14

• An actuarial analysis of RMA yield and loss for organic crops; 

• A discussion focused on the implications of available data on the current rating paradigm; 

• A discussion of the implications of available data on establishing yield relationships; and 

• The Contractor’s recommendations.
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15

SE CT ION III. OR GANIC CR OP Y IE L D DATA SOUR CE S

In 2007, the Census documented 16,778 farms harvesting organic crops on 1,288,088 acres. As a 

follow-up to the organic data collection in the Census, NASS is gathering additional data through 

the Survey. 

The Survey is the first wide-scale survey of organic farming in the United States conducted by 

the USDA, and represents a scale of data collection that has not been, and likely cannot be, 

duplicated privately. The Survey was sent to all respondents to the Census who indicated they 

had organic production (including those who reported production of only organic livestock, 

dairy, eggs, and forage) and also allows participation by organic producers who did not 

participate in the Census.31

The Survey is collecting comprehensive information about organic acreage, production, and 

production value for numerous named insured (Table 3) and uninsured (Table 4) organic crops. 

The Survey instrument also allows entry of crop data for crops not listed by NASS. The Survey 

is collecting, using a uniform instrument and procedure, essential data to evaluate the production 

and valuation of insured organic crops. The broad-ranging and comprehensive scope of the 

Organic Production Survey is well beyond the scope of data collection anticipated in Contract 

AG-645S-C-09-0003. Unfortunately, none of the data collected under the Survey will be 

available until after the completion of this study.

 

31 USDA, NASS, 2009, Organic Production Survey FAQs: What if I want to participate in the survey but didn’t get one in the mail?, 

http://www.agcensus.usda.gov/Surveys/Organic_Production_Survey/FAQs/index11.asp, accessed May, 2009.
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16

T ABLE 3. Crops Named in the NASS Organic Production Survey

and also Insured under Named-crop FCIC Programs

Almonds Mint, peppermint, and spearmint Safflower

Apples Oats for grain or seed Snap beans, for processing

Avocados Onions, dry Sorghum for grain or seed,

Barley for grain or seed Oranges, all Sorghum for silage or greenchop

Dry Beans Peaches, all Soybeans for beans

Blueberries, tame Peanuts for nuts Squash, all (Winter Squash)

Cabbage, all Pears, all Strawberries

Canola Peas, dry peas and lentils Sugarcane for sugar

Cherries, sweet Peas, green Sunflower seed (Sunflowers)

Corn for grain or seed Peas Sweet corn

Corn for silage or 

greenchop Pecans, all Sweet potatoes

Cotton, all Peppers, bell Tangerines

Cranberries Plums and prunes Tomatoes (in the open)

Figs Popcorn Walnuts, English

Flaxseed (Flax) Potatoes Watermelons

Grapefruit Proso millet Wheat, Winter for grain or seed

Grapes Rice Wheat, Durum for grain or seed

Lemons Rye for grain or seed. Wheat, Other spring for 

grain/seed

Source: Compiled from the USDA NASS Organic Production Survey Instrument and USDA RMA 2009 Crop 

Policies and Pilot Program Lists 

T ABLE 4. Crops Named in the NASS Organic Production Survey

but Not Insured under Named-crop FCIC Programs

Beans, snap (fresh) Garlic

Blackberries and Dewberries Hazelnuts/Filberts

Broccoli Herbs, dried

Buckwheat Herbs, fresh-cut

Cantaloupes and muskmelons Honeydew melons

Carrots Lettuce

Cauliflower Peas, green (fresh)

Celery Pistachios

Cherries, tart Raspberries

Dates Spinach

Source: Compiled from the USDA NASS Organic Production Survey Instrument 

and USDA RMA 2009 Crop Policies and Pilot Program Lists 

Historically, organic data have been difficult to collect and assess. Organic production represents 

a small fraction of the total agricultural production in the United States. Much of the data is 

proprietary, and in many cases the data provide tools for marketing and market development. 

Furthermore, organic production is widely scattered across the continent. 
Organic Crops: Revised Written Rating Report 

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17

The Contractor made exhaustive efforts to gather available organic yield data through USDA 

sources, including NASS, Agricultural Marketing Service (AMS), Economic Research Service 

(ERS), and from extension offices and similar state resources addressing organic crops yields. 

The Contractor also collected additional data from academic and private sources. In developing 

the protocol for collection of additional data, the Contractor considered the constraints imposed 

by the Paperwork Reduction Act on the Government and its contractors. The Contractor 

conducted an extensive review of academic, trade, and popular literature to glean any appropriate 

information and identify potential data sources. Internet sources were searched to identify 

potential data sources and to gain insight into organic practices and production risks; the 

producer and marketing communities; and economics of organic regulation, production, and 

marketing. In this context, the Contractor identified resources for an initial data request and 

instituted a process designed to flow through the organic industry at all levels. The expectation 

was, due to the integrated nature of the organic community, the data request would reach 

audiences that could not otherwise be identified. 

The Organic Trade Association (OTA)

32 was established in 1985, initially to promote organic 

food production and eventually to support trade across the organic supply chain. The Contractor 

worked with OTA to identify potential sources among their membership for organic yield

datasets. The Contractor also worked closely with crop experts, producer organizations, 

advocacy organizations, consultants, cooperatives, and individuals within the organic community 

to obtain access to data. Attempts were made to gather data from as many sources as possible.

The Organic Crop Insurance Conundrum

As noted earlier, insurance of organic crops has been influenced substantively by legislation. 

When ARPA required certified organic farming practices to be treated as good farming practices 

for insurance purposes, crop insurance coverage was initially provided through written 

agreements. The agreements were based on a comprehensive underwriting review of the 

particulars of each request by RMA’s Regional Offices. Premium rates for these written 

agreements were determined either by using county rates for the crops under conventional 

practices from actuarial tables and applying a factor determined by the RMA Regional Office or 

by calculating individualized rates based on producer data. This was a remarkable attempt to 

provide appropriate individualized coverage. However, these written agreements placed a 

substantial administrative burden on RMA Regional Offices and insurance providers, and were 

perceived by producers as burdensome. 

Subsequently, Federal insurance of organic crops was provided through standard crop insurance 

policies, using standard policy terms, but with an additional five percent rate load to account for 

the limited available insurance experience for the practices, RMA’s producer yields-based rate 

theory, and uncertainty related to the organic practices. This was an attempt to provide a general 

simplified mechanism for structuring Federal insurance of organic crops. 

Development of actuarially sound crop insurance products requires considerable amounts of data 

consistent with actuarial principles of credibility. For example, under one approach, farm-level 

data provided by several producers for a period not less than 4 years is combined with county-

 

32 Formerly the Organic Foods Production Association of North America.
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18

level data for 10 to 40 years. This allows risks associated with individual production to be 

coupled with longer term risks associated with the locale, crop, and practices. Analysis of 

insurance experience, like the development efforts, also requires considerable breadth and depth 

in the data. The approach currently used to establish premiums rates for organic production (i.e., 

a surcharge on conventional rates) appropriately assumes data for organic crops are limited, but 

also assumes performance of the organic crop will basically be similar to the conventional crop 

performance. 

Among the RMA data there are only two (2) crop-county combinations with ten (10) or more 

producer records (policies/units earning premium for organic production) for four (4) years of 

organic production: apples in Grant County, Washington, and flax in Kidder County, North 

Dakota (Table 5). There are only 143 crop-county combinations with five (5) or more producer 

records (policies) for four (4) years of organic production. In these counties, there are an 

additional 89 policies/units with 2 to 3 years of insurance experience data. All totaled, of the 

3,140 counties in the United States, only 191 have one or more organic crop production records 

with four or more years in the RMA dataset. Generally, due to these limitations, organic yields 

appear to be a set within the larger set of yields produced under good farming practices. Of the 

5,742 crop-county-year organic yield averages that can be calculated from RMA data, only 621 

are statistically significantly different (at the 95 percent confidence level) from the yield average

for the same crop in the same county grown under conventional practices. 
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19

T ABLE 5. Number of Policies Earning Premium by Crop and Location with Five or More 

Producer Records for Organic Production Each Year from 2005 through 2008 

Crop State County Four 

Years

Two to 

Three 

Years

Almonds California Merced 8 3 

Apples Washington Grant 11 11 

Yakima 7 9

Cotton Texas Borden 5 0

Dry Peas Montana Sheridan 5 0 

Flax North Dakota Kidder 10 9 

Grapes

California

Madera 5 5 

Mendocino 5 7

Napa 6 4 

Washington Benton 8 2 

Yakima 8 5 

Pears Washington Chelan 6 2 

Yakima 6 7

Prunes California Sutter 6 3

Wheat

Colorado Logan 5 1 

Montana 

Blaine 6 2 

Daniels 5 3 

Sheridan 8 0

Valley 7 8 

North Dakota Kidder 7 8 

Utah San Juan 9 5 

Source: The Contractor’s Underwriting Department using RMA insurance experience data.
Organic Crops: Revised Written Rating Report 

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restrictions on the title page of this report.

20

SE CT ION IV. L IT E R AT UR E ADDR E SSING OR GANIC AND CONV E NT IONAL CR OP 

Y IE L D V AR IABIL IT Y

In light of the data limitations in the insurance experience data, the Contractor made an 

exhaustive search of the academic literature to identify potential sources of comparative data for 

organic and conventional production. Lampkin33 identified a number of difficulties in making 

such comparisons. First is an issue of definitions. While the NOP standards provide a limit to the 

range of practices that can be considered organic, it is clear that within this range there are wide 

variations in the levels of inputs, years of rotation, and species incorporated into the rotation. 

Furthermore, varietal differences affect both yields and income. Similar differences can be seen 

in conventionally produced crops, accounting for some of the differences in yield evident in 

Government and academic data. Lampkin also identifies “normative” effects derived from the 

values and prejudices of the individuals and institutions supporting the research comparing 

conventional and organic production. Objectives and performance measures can bias the results 

of research, both by limiting data collected and the analysis of those data. The time course of the 

comparison is also crucial.34 As early as the 1940s, Walter James identified the need to examine 

the effects of organic practices over a long term.35 Yet the logistics of such studies are 

complicated by financial and staffing considerations and by the evolution of technology. The 

changing meaning of “best management practices” over time and by region complicates any 

study designed to compare organic and conventional yields and yield variability. 

Comparisons of farming systems are most effective when they are conducted on a large scale. 

Comparisons conducted after the organic system has completed the transition from conventional 

to organic are more effective than studies that capture the variability inherent in the transition 

period. Some studies show more than five years are required for this transition to eliminate any 

residual effects of previous conventional practices. Comparisons also need to be made over a 

period that captures data from several rotational cycles. Replicating comparisons improve the 

validity of the studies. Finally, any study design needs to be flexible enough to reflect the 

dynamic nature of farm-level management.36

Yield variability between farms and/or plots is one factor affecting comparisons between organic 

and conventional production. This variability may result from differences in soil composition, 

rotational design, time since conversion, and management.37 These differences make it 

particularly difficult to make comparisons of aggregate data. In Denmark and Switzerland, 

differences between organic and conventional productivity are generally greater for crops than 

for livestock, with organic grains and potatoes yielding 50 to 85 percent of their conventional 

counterparts.38

 

33 Lampkin, N.H., 1994, Researching Organic Farming Systems, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK.

 In a survey study of Canadian producers, yields of organic grains are reported to 

be more stable than those under conventional practices, implying less variability and lower 

expected loss ratios. In one study with 2 organic and 2 matched conventional farms, the 5 year 

34 Ibid.. 35 Walter Ernest Christopher James (Lord Northbourner), 2002 (first published 1940), Look to the Land, Sophia Perennis Books, Hillsdale, NY. 36 Lampkin, N.H., 1994, Researching Organic Farming Systems, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK 37 Lampkin, N.H., 1994, Economics of Organic Farming in Britain, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK.

38 Dubgaard, A., 1994, Economics of Organic Farming in Denmark, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK; Muhlebach, I., and J. Muhlebach, 1994, Economics of Organic Farming in Switzerland, The Economics of 

Organic Farming, N.H. Lampkin and S. Padel, eds., CAB International, Wallingford, UK.
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21

average yields for the organic crops were higher than the conventional yields by 14 (winter 

wheat) to 16 percent (maize). Nonetheless, throughout Canada, average organic yields, both 

higher and lower than the conventional averages, are reported.39

Extrapolating farm-level yield results beyond the locale of the farm is problematic, especially in 

a country as large as the United States. Yields are influenced by localized climate variables, 

unmanageable pest problems, soil qualities, and other localized characteristics. Furthermore, if 

the studies cover a short period, differential weather effects on plants grown under different 

practices and stages of transition can mask the underlying yield potential and exaggerate the 

difference in yield variability. These patterns were evident in a study of 4 pairs of matched farms 

in Australia over a 35 year period. Organic yields of wheat tended to be higher than expected in 

exceptionally poor years and lower than expected in exceptionally good years.40 This damping of 

yield variability is evident primarily in long term studies. 

Crop yields reflect both the potential of the crop system and the impact of environmental factors. 

The potential is defined by the collective attributes of the cropping system, such as the soil 

quality, the genetics of the seed employed, the climate of the production region, the management 

practices utilized, and the ability of the operator. The potential defines a set of possible outcomes 

(e.g., the minimum and maximum possible yields). Specific environmental factors, such as 

nutrient availability, pests, precipitation, and insolation41 determine how much of the potential is 

actually realized during the crop year. These specific environmental factors acting on the 

potential vary from year to year. In one year production might be limited by precipitation. In 

another it might be limited by disease. In a third year the limitations may be available nitrogen or 

soil pH. Consequently, since the potential of the crop system and the specific environmental 

factors interact to establish yield, yield variability also reflects these two constituents.

The literature documents substantial differences in yields between crops grown under organic 

and conventional practices, but is rife with conflicting results and interpretations.42 Most early 

studies were conducted over a short term (four to ten years) and documented initial yields for 

many crops grown under organic practices that were lower than those for the same crop grown 

under conventional practices. 

There are three important issues with these early studies. First, the definitions of organic 

practices are vague and varied depending on the producer and the researcher. Second, many of 

the studies focus on energy requirements and therefore focus on organic practices that 

substantially limited energy inputs. In many commercial organic operations, energy intensive 

operations substitute for chemical applications, particularly for weed control. Therefore, limiting 

 

39 Henning, J., 1994, Economics of Organic Farming in Canada, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB

International, Wallingford, UK.

40 Wynen, E., 1994, Economics of Organic Farming in Australia, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK.

41 A measure of the sunlight reaching the Earth’s surface in a specific area during a given period. 42 Smolik, J.D., and T.L. Dobbs, 1991, Crop yields and economic returns accompanying the transition to alternative farming systems, Journal of 

Production Agriculture 4:153-161; Bernardi, G.M., 1978, Organic and conventional wheat production: examination of energy and economics, 

Agro-ecosystems, 4:367-376; Klepper, R., W. Lockeretz, B. Commoner, M. Gertler, S. Fast, D. O’Leary, and R. Blobaum, 1977, Economic 

performance and energy intensiveness on organic and conventional frams in the Corn Belt, American Journal of Agricultural Economics, 59:1-

12; United States Department of Agriculture, Study Team on Organic Farming, 1980, Report and Recommendations on Organic Farming: 

Productivity in Organic Farming, pp. 52-56; Dobbs, T. and J.D. Smolik. 1996. Productivity and profitability of conventional and alternative 

farming systems: A long-term on-farm paired comparison. Journal of Sustainable Agriculture 9:63–77.
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restrictions on the title page of this report.

22

energy inputs can limit yields. Finally, many of these early studies focus on paired farms. While 

this is a logical approach to examine differences in yield, environmental factors even within a 

field can cause substantial differences in yield. On non-irrigated land, in a wet year a low lying 

area may have substantially reduced yields as compared to nearby elevated areas. The same area 

in a dry year may show much higher productivity than the elevated acreage. 

Longer-term studies with careful experimental design show organic yields generally increase 

over time. These increases are often attributed to improved soil quality resulting from the organic 

management practices.43 To some extent, this period of conditioning is reflected in the 

conventional to organic transition period defined in the NOP, but the amount of time required for 

the full transition may be much longer. 

Variation in yields is an inherit risk of crop production. Under most conventional practices, 

growers use substantial mechanical and/or chemical inputs to limit the impact of unpredictable 

environmental conditions. Smith et al. assessed average crop yields and temporal yield 

variability over a 14 year period under conventional, no-till, low-input, or organic practices at the 

W. K. Kellogg Biological Station Long Term Ecological Research site in southwestern 

Michigan. The research focused on corn, soybean, and winter wheat in a three-year rotation. 

Yields were measured annually and yield variability was estimated using the coefficient of 

variation for each crop phase. Yield variability differed among management practices and 

rotational phases and was highest in the organic system. Yields under conventional and no-till

practices were similar for all crops. Yields under organic practices were lower for corn and 

winter wheat, however yields for soybeans were not significantly different under any of the 

practices.44 

The smaller effect of management practices on yield variability for soybeans is a pattern reported 

in a variety of studies in different parts of the United States. However, these differences are not 

consistent from region to region or from year to year. During one 9 year trial, soybean yield 

averaged 19 percent lower (2.88 metric tons per hectare) in the 3 organic systems studied than in 

the conventional systems (3.57 metric tons per hectare).45 Based on the analysis in the report, 

weed competition alone accounted for this difference. There were no consistent differences in 

wheat yield among cropping systems.46 Under conventional high-input management, soybeans 

have been shown to have higher temporal yield variability than either corn or sorghum.47

 

43 Jonsson, S., 2002, Crop yields in organic and conventional production – studies from the Öjebyn project, Proceedings of the UK Organic 

Research 2002 Conference, Powell, J. et al., eds., pp. 43-46; Pimentel, D., P. Hepperly, J. Hanson, D. Douds, and R. Seidel, 2005, Environmental, 

Energetic, and Economic Comparisons of Organic and Conventional Farming Systems, Bioscience, 55:573-582; Delate, K., M. Duffy, C. Chase, 

A. Holste, H. Friedrich, and N. Wantate, 2002, An economic comparison of organic and conventional grain crops in a long-term agroecological 

research (LTAR) site in Iowa, American Journal of Alternative Agriculture 18:59–69.

In a 

rotation including corn, soybean, cotton, oats, black oats (Avena strigosa), wheat, rye, rice, and 

green manure, the factors affecting variability of yield differ from one crop to another. 

44 Smith, R.G., Menalled, F.D., Robertson, G. 2007. Yield and Temporal Yield Variability under Conventional and Alternative Management 

Systems. Agronomy Journal.99:1629-1634. 45 Assuming 60 lbs per bushel for soybeans, 2.88 metric tons per hectare is roughly equivalent to 42.7 bushels per acre for organic production and 

3.57 metric tons per hectare is roughly equivalent to 53.3 bushels per acre for conventional production.

46 Cavigelli, M.A., J.R. Teasdale and A.E. Conklin, 2008, Long-Term Agronomic Performance of Organic and Conventional Field Crops in the 

Mid-Atlantic Region, Agronomy Journal 100:785-794 47 Eghball, B., and G.E. Varvel, Fractal Analysis of Temporal Yield Variability of Crop Sequences: Implications for Site-Specific Management, 

Agronomy Journal, 89:851-855.
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restrictions on the title page of this report.

23

Furthermore, relative changes in yield from one year to another suggest the causes of yield 

variability may change over time.48 

Soil structure and quality introduce an important source of variation in crop yield.49 Changes in 

soil characteristics, including both availability of mineral nutrients and organic composition of 

the soils, appear to account for some of the temporal and species yield variability.50 In a study 

examining cereal yields in China from 1949 through 1998, the average yield variability of rice 

and other grain crops was very significantly and negatively correlated with the cropland soil 

organic matter level. Furthermore, the correlation between soil organic matter and cereal 

productivity was significant in most cases, but the relationship degraded as production practices 

incorporated new technologies.51

Increased yields during the transitional period to organic production have been attributed to 

improved soil quality. However, there was no difference in tomato yields between established 

organic and first-year transitional plots in one study. Yet the organic systems had higher yields 

than the comparable conventional system. Benefits from a winter legume cover crop may have 

contributed to the yield improvements of the organic production relative to conventional 

practices. It may also be that improvements in organic yields result from increases in experience

with organic management practices.

52

A carefully managed experiment in Oklahoma examined yield during the transition to organic 

production of vegetables. The transitional crops were sweet corn, bell pepper, and cucumber. By 

the third year, yields of the rotation, bell pepper, but not of cucumber and sweet corn, were as 

productive under organic practices as under conventional.53 Duram reports that in comparing 

farm-level productivity, organic yields were lower than conventional yields in 15 cases, were 

higher in 13 cases, and were equal in 2 cases. In these studies, organic productivity was less 

variable and produced higher yields in stressful growing conditions, particularly during periods 

of drought.54 For the last 10 years of a 21 year comparison of organic and conventional 

production in Pennsylvania, organic corn yields were only 3 percent less than conventional 

yields. The organic yields were higher than the conventional yields in drought years.55

 

48 Viera, S.R.; J.L. Hatfield, D.R. Nielsen, and J.W. Biggar, 1983,Geostatistical theory and application to variability of some agronomical 

properties, Hilgardia, 51:pp. 1-75; Viera, S.R. and A. Paz Gonzalez, 2003, Analysis of the spatial variability of crop yield and soil properties in 

small agricultural plots, Bragantia, 62: pp. 127-138, http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-

87052003000100016&lng=en&nrm=iso, accessed May 2009.

These 

results suggest the organic practice would have lower loss cost ratios due to the ability of the 

organic crops to overcome stressful conditions. 

49 A.U. Bhatti, 2005, Using Geostatistics to Find Optimum Plot Size for Field Research Experiments, Communications in Soil Science and Plant 

Analysis, 35:2299 – 2310. 50 Viera, S.R.; J.L. Hatfield, D.R. Nielsen, and J.W. Biggar, 1983,Geostatistical theory and application to variability of some agronomical 

properties, Hilgardia, 51:pp. 1-75; Viera, S.R. and A. Paz Gonzalez, 2003, Analysis of the spatial variability of crop yield and soil properties in 

small agricultural plots, Bragantia, 62: pp. 127-138, http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-

87052003000100016&lng=en&nrm=iso, accessed May 2009. 51 Pan, G., Pete Smith, and W. Pan, 2009, The role of soil organic matter in maintaining the productivity and yield stability of cereals in China, 

Agriculture, Ecosystems & Environment, 129: p344-348. 52 Martini, E.A., J.S. Buyer, D.C. Bryant, T.K. Hartz, and R.F. Denison, 2004, Yield increases during the organic transition: improving soil 

quality or increasing experience?, Field Crops Research 86:225-266. 53 Russo, V.M., and M. Taylor, 2006, Soil amendments in transition to organic vegetable production with comparison to conventional methods: 

yields and economics. HortScience, 41:1576-1583. 54 Duram, L.A., 2005, Organic Farmers in the U.S.: Opportunities, Realities and Barriers, Symposium Proceedings: Organic Agriculture: 

Innovations in Organic Marketing, Technology, and Research

55 Pimentel, D., P. Hepperly, J. Hanson, D. Douds,, and R. Seidel, 2005, Environmental, energetic, and economic comparisons or organic and 

conventional farming systems, BioScience 55:7:573-582.
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contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

24

Ten year production trials in Minnesota evaluated a corn–soybean rotation and a corn–soybean–

oat/alfalfa–alfalfa rotation under four management strategies. One trial was on land with a 

history of conventional fertilizer and pesticide application; another was on land which had not 

been treated with synthetic fertilizers or pesticides. Chemical inputs under the four management 

practices included organic chemical inputs, low and high levels of conventional inputs, and 

replicates managed without external inputs. In this experiment, relative yields of organic corn 

were reduced to a lower extent than those of organic soybeans compared to the conventional 

counterpart. This study showed beneficial effects of a longer crop rotation on yields, which are

often masked by external inputs in conventional production.56 Furthermore, the patterns of yields 

under the high-input conventional production and the organic management using a four year 

rotation were similar, especially in the last six or seven years of the trials.

The effects of management practices on variability of crop yields were assessed in a four year

study in Michigan. Practices included continuous corn and a corn–corn–soybean–wheat rotation

under both conventional and organic production. Yield variability was assessed using the 

coefficient of variation and a multivariate dissimilarity index (Bray-Curtis). Corn yields in the 

organic rotation were not significantly different from those in the conventional monoculture. 

Variability in corn yield was highest under conventional monoculture.57

Another study reported the yield of winter rapeseed grown organically as lower and more 

variable than the yields of rapeseed grown conventionally. A study of 19 fields in 4 regions of 

France over 2 years showed competition with weeds in early winter explained much of the crop 

variation, while pest damage in the spring explained a smaller portion of variation.58 However, 

as producers develop strategies to deal with these limiting factors, organic yields increase and 

variability decreases. This has been a recurring theme in the literature on crop yields under 

organic production practices. 

The Long-Term Research on Agricultural Systems experiment has been monitoring the effects of 

conventional and alternative practices in California on crop yields since 1993; the planned 

duration of the project is 100 years. One study follows two-year rotations with multiple

replicates including irrigated conventional and organic corn-tomato rotational systems. For years 

three through nine of the experiment, average yields of the organic system for corn were 

significantly lower than those for conventional corn, and the organic corn yields had significant 

negative trends. Yet there were no significant differences in average yields of tomato between 

conventional and organic practices, and organic tomato yields showed a significant positive 

trend.59 Furthermore, on “average, yields were not significantly different between the two 

systems, but there was less year-to-year variation in the organic systems.”60

 

56 Porter, P.M., D.R. Huggins, C.A. Perillo, S.R. Quiring, and R.K. Crookstone, 2003, Organic and Other Management Strategies with Two- and 

Four-Year Crop Rotations in Minnesota, Agronomy Journal 95:233-244. 57 Smith, R.G., and K.L. Gross, 2006, Weed community and corn yield variability in diverse management systems, Weed Science 54: pp. 106-

113. 

58 Valantin-Morison, M., and ,J. M. Meynard, 2008, Diagnosis of limiting factors of organic oilseed rape yield. A survey of farmers' fields, 

Agronomy for Sustainable Development, 28: pp. 527-539. 59 Denison, R.F., D.C. Bryant, and T.E. Kearney, 2004. Crop yields over the first nine years of LTRAS, a long-term comparison of field crop 

systems in a Mediterranean climate. Field Crops Res., 86:267-277. 60 Denison, R.F., D.C. Bryant, and T.E. Kearney, 2004. Crop yields over the first nine years of LTRAS, a long-term comparison of field crop 

systems in a Mediterranean climate. Field Crops Res., 86:267-277.
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restrictions on the title page of this report.

25

A four year comparison of conventional, low-input, and organic yields for tomatoes in 

California’s Sacramento Valley evaluated the importance of weeds, nitrogen, and water as yieldlimiting factors. Tomato yields ranged from about 55 metric tons per hectare to over 90 metric 

tons per hectare (Figure 4). Significant treatment differences were observed in the first two years

of the study, but were not evident thereafter.

FIGUR E 1. Tomato Yields under Four Different Management Practices* 

*Alternative text descriptions of figures in this report are provided to assure access to the information contained in 

those figures consistent with guidance available from the USDA Office of the Chief Information Officer Web-site, 

including a section entitled “Web-based Intranet and Internet Information and Applications (1194.22),” which states 

“The standards do not prohibit the use of web site graphics or animation. Instead, the standards aim to ensure that 

such information is also available in an accessible format. Generally, this means use of text labels or descriptors for 

graphics” (http://www.access-board.gov/sec508/summary.htm) and the section entitled “Providing Appropriate

Alternative Text” under “Principles of Accessible Design” found in the WebAim (Web Accessibility in Mind) Website (http://webaim.org/intro/#implementin).

Figure 1 illustrates a four year comparison (1994 through 1997) of conventional, low-input, and organic yields for 

tomatoes in California’s Sacramento Valley. Tomato yields ranged from about 55 metric tons per hectare to over 90 

metric tons per hectare. Statistically significant treatment differences in yield were observed in the first two years of 

the study, with conventional and low input yields exceeding those of the organic crop, but were not evident in 1996 

and 1997, the last two years of the study.

0

20

40

60

80

100

120

1994 1995 1996 1997

Crop Year

Yield (tons/hectare)

Conventional 2-year rotation

Conventional 4-year rotation

Low Input 4-year rotation

Organic 4-year rotation

Source: After Clark, M.S., W.R. Horwath, C. Shennan, K.M. Scow, W.T. Lantni and H. Ferris, 1999, Nitrogen, weeds and water as yield-limiting 

factors in conventional, low-input, and organic tomato systems, Agriculture, Ecosystems & Environment 73:257-270. (Figure 1 Data)

Multivariate analysis indicates weeds, nitrogen, and water all influenced yields in this study, but 

the relative importance of each was dependent upon the management practices. The findings 

indicate organic and low-input tomato systems in this region can produce yields similar to those 

of conventional systems. Nitrogen availability was most important in limiting yields in the 

organic system and water availability was more important under conventional management.61

 

61 Clark, M.S., W.R. Horwath, C. Shennan, K.M. Scow, W.T. Lantni and H. Ferris, 1999, Nitrogen, weeds and water as yield-limiting factors in 

conventional, low-input, and organic tomato systems, Agriculture, Ecosystems & Environment 73:257-270.
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restrictions on the title page of this report.

26

Yield variability was lowest in the low impact system and essentially equal in the conventional 

and organic systems.

A long-term, cropping systems comparison at the Center for Integrated Farming Systems at 

Russell Ranch near the University of California – Davis focuses on the sustainability and 

environmental impact of agriculture. The experiment was inspired by results from other longterm experiments showing short-term trends can be poor predictors of long-term sustainability. 

The project compared organic and conventional irrigated corn/tomato production in multiple one 

acre replicates (Figure 2). Conventional plots received synthetic pesticides as needed, while the

organic crops received only organically approved pesticides, such as sulfur and Bt compounds. 

Crop yields and total biomass were measured annually. The authors report within year variability 

is generally lower under conventional practices, while between year yield variability is lower 

under organic practices. On average, yields are not significantly different between the two 

systems.62

 

62 Kaffka, S.R.; D.C. Bryant, and R.F. Denison, 2005, Comparison of organic and conventional maize and tomato cropping systems from a longterm experiment in California, Proceedings of the First Scientific Conference of the International Society for Organic Farming Research, 

U.Koepke, D.Neuhoff, P. Cornish, W. Lockeretz, and H.Wiler, eds.; Institute of Organic Agriculture, 218-221; Mitchell, A.E., Y-J. Hong, E. 

Koh, D.M. Barrett, D.E. Bryant, R.F. Denison, and S. Kaffka, 2007. Ten-Year Comparison of the Influence of Organic and Conventional Crop 

Management Practices on the Content of Flavonoids in Tomatoes Journal of Agricultural and Food Chemistry, 55: 6154-6159. 
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27

FIGUR E 2. Tomato Yields Under Two Different Management Practices* 

* Figure 2 illustrates a twelve year comparison (1994 through 2005) of conventional and organic yields for tomatoes 

in California’s Sacramento Valley. Organic yields ranged from about 50 metric tons per hectare to over 70 metric 

tons per hectare, while conventional yields ranged from about 30 metric tons per hectare to over 80 metric tons per 

hectare. On average, over the 12 years, yields are not significantly different between the two systems.

0

10

20

30

40

50

60

70

80

90

1994 1996 1998 2000 2002 2004

Crop Year

Yield (metric tons/hectare)

Conventional Organic

Source: After Mitchell, A.E., Y-J. Hong, E. Koh, D.M. Barrett, D.E. Bryant, R.F. Denison, and S. Kaffka, 2007. Ten-Year Comparison of the 

Influence of Organic and Conventional Crop Management Practices on the Content of Flavonoids in Tomatoes Journal of Agricultural and Food 

Chemistry, 55: 6154-6159. (Figure 2 Data)

In a five year study on apple yields in new orchards, conventional yields exceed organic yields in 

the first two years of the study and in the fifth year (Figure 3). Practices integrating elements of 

both conventional and organic practices appear to provide some yield benefits under varying 

conditions. Yields are not significantly different between the two systems.63 Yet the pattern of 

yields over time shows some of the challenges in studying yield and yield variability, particularly 

in long lived perennials. 

 

63 Reganold, J.P., J.D. Glover, P.K. Andrews and H.R. Hinman, 2001, Sustainability of three apple production systems, Nature, 410:926-930.
Organic Crops: Revised Written Rating Report 

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contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

28

FIGUR E 3. Apple Yields in a New Grove under Three Different Management Practices* 

* Figure 3 illustrates a five year comparison (1995 through 1999) of conventional and organic yields for apples in a 

newly established orchard in Washington State, as well as yields under integrated practices incorporating elements 

of both the organic and conventional procedures. Yields under all three approaches increased during the first three 

years. In the third through fifth years, the organic yields exceeded the conventional yields twice, while the 

conventional yield was greater than the organic yield once. The five-year cumulative yields under the three systems 

of management were not significantly different.

0

50

100

150

200

250

300

1995 1996 1997 1998 1999 1995-

1999

Year

Yield (Metric Tons per Hectare)

Organic

Conventional

Integrated

Source: After Reganold, J.P., J.D. Glover, P.K. Andrews and H.R. Hinman, 2001, Sustainability of three apple production 

systems, Nature, 410:926-930. (Figure 3 Data)

After more than 110 years, the Old Rotation experiment at Auburn University continues to 

document the long-term effects of crop rotation and winter legume cover crops on sustainable 

cotton (Gossypium hirsutum L.) production in the southeastern United States. Long-term yields 

indicate winter legumes are as effective as nitrogen fertilizers in producing maximum cotton 

yields and increasing soil organic carbon (SOC). Higher SOC results in higher cotton yields. 

However, rotating cotton with corn (Zea mays L.) in a two-year rotation or rotating corn, winter 

wheat (Triticum aestivum L.), and soybeans [Glycine max. (L.) Merr.] in a three-year rotation 

produced little long-term cotton yield advantage beyond that associated with just the 

improvements in SOC. Cotton yields over 110 years have hardly increased in plots without 

winter legumes or without the application of synthetic or natural nitrogen fertilizers. Corn yields 

in dryland rotations with cotton are generally low for the region where the trials are being 

maintained.

64

The effects of technological advances can be seen in crops grown in the Old Rotation under 

almost every practice. In the 1950s, yields of all crops increased with increasing rates of 

application of potassium and phosphorus. Since adoption of subsoil applications of fertilizers 

(whether organic or synthetic), high-residue (conservation) tillage, and genetically modified 

cultivars in 1997, all non-irrigated crops have produced their highest recorded yields since the 

study began. 

 

64 Mitchell, Charles C., Delaney, Dennis P., Balkcom, Kipling S. A Historical Summary of Alabama's Old Rotation (circa 1896): The World's 

Oldest, Continuous Cotton Experiment. Agronomy Journal, 2008; 100 (5): 1493 DOI: 10.2134/agronj2007.0395.
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

29

Based on the large investment in breeding and genetically modifying varieties used in 

conventional practices as compared to the rather recent and relatively modest investment in 

selection of varieties for organic practices, some differences in yield potential are expected. The 

highest yielding winter wheat varieties under conventional practices are often not the highest 

yielding under organic practices. An analysis of variance for yield among 35 genotypes in paired 

organic and conventional systems showed highly significant (P < 0.001) interactions between 

genotype and management practices in 4 of 5 locations. Selection of varieties specifically 

targeting organic practices produced yields 15 percent, 7 percent, 31 percent, and 5 percent

higher in 4 locations than the yields resulting from selection for conventional practices. Varieties 

bred in and adapted to organic practices will allow organic production to approach the yield 

potential for the crop, location, and practice.65 

Iowa State University has maintained a crop system comparison for approximately three 

decades. The original system included a wide variety of conventional and organic rotations that 

were modified over time. A conventional corn-soybean (C-S) rotation was added in 1998 to 

assess the benefits of both the price premium for soybeans and the soil nitrogen credit from the 

soybean crop. The conventional rotations receive herbicides, insecticides, and commercial

fertilizer as determined by soil analysis. In the organic corn-soy-oat/alfalfa (C-S-O/A) rotation, 

alfalfa is seeded as a companion crop with oats. The annual, non-dormant alfalfa, is used as a

“green manure.” An additional corn-soy-oats/alfalfa-alfalfa (C-S-O/A-A) provides a second year 

of alfalfa growth, increasing the nitrogen credits in the rotation. The corn stubble is fall chisel 

plowed, the soybean stubble is spring field cultivated, and the alfalfa is moldboard plowed after a 

fall application of dry livestock manure. Organic corn and soybeans are rotary hoed prior to 

emergence (weather permitting) followed by three cultivations, the last with hillers attached to 

the cultivator to bury more weeds.

The Contractor extracted yield data for corn and soybean from the annual published reports of 

the Iowa State crop system comparisons. Early in the trials, conventional corn yields were 

significantly better than organic yields. Over time, the organic yields improved and, particularly 

in the case of the longer term rotational system, were comparable to the yields under 

conventional practices (Figure 4).

 

65 Murphy, K.M., K.G. Campbell, S.R. Lyon and S.S. Jones, 2007, Evidence of varietal adaptation to organic farming systems, Field Crops 

Research, 102:172-177.
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contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

30

FIGUR E 4. Corn Yields in the Iowa State Crop System Comparisons 1998 through 2008* 

* Figure 4 illustrates an 11 year comparison (1998 through 2008) of corn yields from conventional corn-soybean 

rotations and organic corn-soybean-oats/alfalfa and corn-soybean-oats/alfalfa-alfalfa rotations in an Iowa study. 

Over time there was a tendency for yields under all practices to increase. During the first two years of the study the 

conventional yields were substantially greater than the organic yields. This pattern was not maintained after the third 

year. The longer organic rotation had the highest yields in four of the last five years of the study. 

0

50

100

150

200

250

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year

Yield (bushels per acre)

C-S conventional

C-S-O/A organic

C-S-O/A-A organic

Source: The Contractor’s Research Department using Iowa State University Comparison of Organic and Conventional Crops at the Neely-Kinyon 

Long-term Agroecological Research (LTAR) Station:66 (Figure 4 Data)

The differences between conventional and organic yields seen in corn are less evident for 

soybeans grown under those practices (Figure 5). While small differences in yields, sometimes 

significant, are seen, there is no consistent pattern of yield differences and over time, yields and 

yield variability of the conventional and organic soybeans are comparable. 

 

66 http://extension.agron.iastate.edu/organicag/researchreports/n-kltar98.pdf

http://extension.agron.iastate.edu/organicag/researchreports/n-kleopold99.pdf

http://extension.agron.iastate.edu/organicag/researchreports/n-kleopold00.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk01ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/orgeconomics.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk02ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk03ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/04nkltarl.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk05ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk06ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk07ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk08ltar.pdf
Organic Crops: Revised Written Rating Report 

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restrictions on the title page of this report.

31

FIGUR E 5. Soybean Yields in the Iowa State Crop System Comparisons 1998 through 2008* 

* Figure 5 illustrates an 11 year comparison (1998 through 2008) of soybean yields from conventional corn-soybean 

rotations and organic corn-soybean-oats/alfalfa, corn-soybean-oats/alfalfa-alfalfa, and soybean-wheat rotations in an 

Iowa study. Over time there was a tendency for yields under all practices to increase. While small differences in 

yields, sometimes significant, are evident, there is no consistent pattern of yield differences and over time, yields 

and yield variability of the conventional and organic soybeans are comparable. 

0

10

20

30

40

50

60

70

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year

Yield (bushels per acre)

C-S conventional

C-S-O/A organic

C-S-O/A-A Organic

S-W Organic

Source: The Contractor’s Research Department using Iowa State University Comparison of Organic and Conventional Crops at the 

Neely-Kinyon Long-term Agroecological Research (LTAR) Station:67 (Figure 5 Data)

The Contractor obtained unpublished plot-level data for a similar crop system comparison in the 

Mid-Atlantic region. The comparison, performed under the auspices of the Sustainable 

Agricultural Systems Laboratory of the Animal and Natural Resources Institute of the 

Agricultural Research Service of the USDA, focuses on differences in long-term performance of 

organic and conventional crops.68 It is instructive to examine these data at both the plot level 

(Figures 6, 8 and 10) and the aggregate level (Figures 7, 9, and 11). Some patterns observed in 

other studies are also evident in these data. However, plot by plot differences can be masked 

when simple averages of organic and conventional performance are reported. Furthermore, the 

importance of outliers that dramatically affect insurance performance is more evident in these 

charts (e.g., the disparate performance of the conventional no-till corn in 2000). 

 

67 http://extension.agron.iastate.edu/organicag/researchreports/n-kltar98.pdf

http://extension.agron.iastate.edu/organicag/researchreports/n-kleopold99.pdf

http://extension.agron.iastate.edu/organicag/researchreports/n-kleopold00.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk01ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/orgeconomics.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk02ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk03ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/04nkltarl.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk05ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk06ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk07ltar.pdf

http://extension.agron.iastate.edu/organicag/researchreports/nk08ltar.pdf

68 Cavigelli, M.A., B.L. Hima, J.C. Hanson, J.R. Teasdale, A.E. Conklin, and Y-C Lu, 2009, Long-term economic performance of organic and 

conventional field crops in the mid-Atlantic region, Renewable Agriculture and Food Systems: 24:102–119.
Organic Crops: Revised Written Rating Report 

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32

FIGUR E 6. Corn Yields by Plot in the Mid-Atlantic Region Crop System Comparisons 1996 

through 2008* 

* Figure 6 illustrates a 12 year comparison (1996 through 2008) of corn yields from individual plots in a study of 2 

conventional and 3 organic management practices. Yields were quite variable within treatments and between 

treatments. Longer organic rotations tended to perform better than shorter organic rotations. Corn yields and yield 

variability under conventional practices tended to be greater than those under organic practices.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

1994 1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric tons per hectare)

Conventional - no till Conventional - chisel till Organic - 2 crop rotation

Organic - 3 crop rotation Organic - 4+ crop rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 6 Data)
Organic Crops: Revised Written Rating Report 

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33

FIGUR E 7. Average Corn Yields in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008* 

* Figure 7 illustrates the average values by treatment and year for the same 12 year comparison of corn yields as in 

Figure 6. Average conventional yields were generally higher than average organic yields, but much of the within 

treatment yield variability (from individual plots) under conventional practices is masked by graphing only the 

average the yields.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

1994 1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric tons per acre)

Conventional - no till Conventional - chisel till Organic - 2 crop rotation

Organic - 3 crop rotation Organic - 4+ crop rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 7 Data)
Organic Crops: Revised Written Rating Report 

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34

FIGUR E 8. Soybean Yields by Plot in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008* 

* Figure 8 illustrates a 12 year comparison (1996 through 2008) of soybean yields from individual plots in a study of 

2 conventional and 3 organic management practices. Soybean yields were somewhat less variable within treatments 

than corn yields in the same study. The length of rotation seemed to have less effect on soybean yields than on corn 

yields. Differences between organic and conventional yields were less substantial and less consistent than for corn.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

1994 1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric tons per hectare)

Conventional - no till Conventional - chisel till Organic - 2 crop rotation

Organic - 3 crop rotation organic - 4+ crop rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 8 Data)
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

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35

FIGUR E 9. Average Soybean Yields in the Mid-Atlantic Region Crop System Comparisons 

1996 through 2008* 

* Figure 8 illustrates a 12 year comparison (1996 through 2008) of soybean yields from individual plots in a study of 

2 conventional and 3 organic management practices. Soybean yields were somewhat less variable within treatments 

than corn yields in the same study. The length of rotation seemed to have less effect on soybean yields than on corn 

yields. Differences between organic and conventional yields were less substantial and less consistent than for corn.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

1994 1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric tons per hectare)

Conventional - no till Conventional - chisel till Organic - 2 crop rotation

Organic - 3 crop rotation Organic - 4+ crop rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 9 Data)
Organic Crops: Revised Written Rating Report 

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36

Figure 10. Wheat Yields in the Mid-Atlantic Region Crop System Comparisons 

1997 through 2008* 

* Figure 10 illustrates comparison of wheat yields from individual plots in a study of two conventional and two 

organic management practices (1997 through 2008). Wheat yields were somewhat less variable within treatments 

than corn yields in the same study. The length of rotation seemed to have less effect on wheat yields than on corn 

yields. Differences between organic and conventional yields were less substantial and less consistent than for corn.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric Tons per Hectare)

Conventional - no till Conventional - Chisel Till

Organic - 3 Crop Rotation Organic 4+ Crop Rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 10 Data)
Organic Crops: Revised Written Rating Report 

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37

FIGUR E 11. Wheat Yields in the Mid-Atlantic Region Crop System Comparisons 

1998 through 2008 

* Figure 11 illustrates the average values by treatment and year for the comparison of wheat yields in Figure 8. 

Average conventional yields were higher than average organic yields for all treatments in four years, while average 

organic yields for all treatments were higher than average conventional yields in two years.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

1996 1998 2000 2002 2004 2006 2008 2010

Year

Yield (metric tons per hectare)

Conventional - no till Conventional - chisel till

Organic - 3 crop rotation Organic 4+ Crop rotation

Source: The Contractor’s Research Department using data supplied by M.A. Cavigelli, USDA ARS. (Figure 11 Data)

Crop yields in the Mid-Atlantic crop system comparison varied between years, largely due to 

differences in precipitation. There were no statistically significant differences in average grain 

yields between the two conventional systems. Average corn and soybean yields in these 

conventional systems were generally greater than in the three organic systems, but not in any 

consistent pattern. Among organic systems, corn yields increased with increasing crop rotation 

length. There were no consistent effects of crop rotation length on soybean or wheat yields. 

Although on an annual basis there may be significant differences in organic and conventional 

yields, there is no consistent practice which has the higher yield; nor is there consistency in the 

significance of differences; and the patterns between crops are not consistent. Annual yields in 

these trials are influenced by changing technologies, temperature, precipitation patterns, and a 

host of other factors. 

Soil quality is often considered a primary source of yield variability. Crop productivity is 

affected by soil organic matter, nutrient availability, soil water capacity, soil aggregate stability, 

and soil biology.69

 

69 Millar, J., 2007, Soil Variability, Carbon Variability, Nutrient Variability, USDA on-line publication, 

Management practices affect all these soil characteristics. While soil quality 

differences have been implicated in some of the disparity between organic and conventional 

http://www.sdnotill.com/2007/Soil%20Variability-Millar.htm, accessed May, 2009.
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38

yields, as well as differences in yield variability under particular practices, differences in yield 

and yield variability can not be explained by soil quality alone. The evidence is increasing that 

more diverse cropping systems, whether organic or conventional, have fewer pest problems. 

Variation in crop yield is likely to be lower in a system with greater biological diversity. In the 

transition from a high input monoculture system to a more diverse cropping system, yield may 

drop and variance in yield may increase drastically at the early stages of the transition. As the 

transition progresses, the variance may decrease as pest populations come under increased 

natural control and yields increase.70

 

70 Maxwell, B.D., 1999, A Perspective On Ecologically Based Pest Management, Weed Science 47:129. 

http://weedeco.msu.montana.edu/WeedEdu/EBPM%20Perspectives.htm, accessed May, 2009.
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39

SE CT ION V. RMA UNDE R W R T IT ING AND INSUR ANCE E XPE R I E NCE FOR 

OR GANIC CR OPS

This section of the report responds to elements of Section 5.2. of the Contract addressing “a 

review of the underwriting, risk, and loss experience of organic crops covered by the Corporation 

and loss experience of organic crops covered by the Corporation, as compared with the same 

crops produced in the same counties and during the same crop years using nonorganic 

methods.”71 Inasmuch as the purpose of the review is to “either confirm or refute the existence of

significant, consistent, and systemic variations in loss history exist between organic and 

conventional commodities, either collectively or on an individual crop basis,”72

(1) A discussion of the administrative and underwriting procedures addressing crops 

produced under organic management practices; 

 the Contractor 

has explored a wide variety of approaches to consider the risk and loss experience in the context 

of the underwriting requirements for the organic production. The review is comprised of three 

elements, including: 

(2) An evaluation of the experience data accumulated by RMA for organic practice versus 

non-organic practice of the same crops in the same county; and 

(3) Consideration of the relationship of the rate surcharge for organic crops in light of the 

causes of loss reported for those crops. 

V .A. A Brief History of Underwriting Organically Produced Crops by FCIC 

References to organically grown crops can be found in various documents related to 

underwriting on the RMA website. The Contractor reviewed various documents to provide a 

summary of the contents and identify the changes to policy as these changes occurred. 

Underwriting Practices Addressing Organically Produced Crops 

Prior to 2001, acreage of organically produced crops was required to be insured if the producer 

also insured conventional production, provided the acreage and the crop met the conditions of 

insurability as stated in the Basic Provisions and the various Crop Provisions. However, as stated 

in Bulletin MGR-01-00473

In the past, crop insurance policies may not have covered production losses when 

organic insect, disease, and weed control measures were used and such measures 

were not effective. Such determinations were made because the insured had not 

complied with the definition of good farming practices contained in the Basic 

Provisions. 

Organic Farming Practices-Implementation of the Section 123 of 

Agricultural Risk Protection Act of 2000 (ARPA) (January 17, 2001):

Thus, although losses due to drought, excess precipitation, or similar cause beyond the control of 

the producer could be covered and indemnified under the crop insurance policies, losses due to 

failure to use non-organic pesticides were not covered if the loss adjuster determined that such 

losses could have been avoided had those products been used. Use of such pesticides would be 

contrary to the organic regimen; hence, for practical purposes, such losses were not covered by 

the crop insurance policies in force at that time. There was no reduction in premium although the 

 

71 Section 5.4.1.1 of the Contract 72 Ibid. 73 Bulletins referenced in this report are compiled in Appendix B.
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40

scope of the crop insurance for organically produced crops was limited compared to the scope of 

insurance for conventionally produced crops. 

MGR-01-004 further stated that “Section 123 of the Agricultural Risk Protection Act of 2000 

(ARPA) now requires that organic farming practices be recognized as good farming practices.”

This legislation reversed the standard that losses resulting from the failure to use non-organic 

pesticides were not covered if the loss adjuster determined that such losses could have been 

avoided had those conventional products been used. To implement this new standard, since it 

was not possible to revise the Basic Provisions and all other crop insurance documents under the 

procedures of the Administrative Procedures Act in a timely manner, the Bulletin extended 

insurance coverage for organically produced crops via written agreements.74 The Bulletin 

applied to all crops with a sales closing date of March 15, 2001 or later. Thus, the Corporation 

began to offer coverage under written agreements for crops planted in the spring of 2001, while 

the approach was not effective for crops with sales closing dates earlier than March 15 until the 

2002 crop year.75 

Producers of organic crops who failed to request the written agreement were subject to the 

interpretation of the Basic Provisions that losses due to failure to use non-organic pesticides were 

not covered if the loss adjuster determined that such losses could have been avoided had 

conventional products been used. Furthermore, coverage was not made available for “... 

catastrophic risk, income protection, and revenue assurance plans of coverage and for pilot 

program crops unless permitted by the crop provisions.” 

The written agreements authorized by MGR-01-004 were governed by the standards established 

by the 2001 Written Agreement Handbook (FCIC-24020) (11-00) “Standards and Instructions 

for Processing of Actuarial Requests and Written Agreements.” Organically produced crops are 

not mentioned specifically in this document. The Handbook “... allows the flexibility to provide 

insurance coverage for land or persons involved in the production of insurable crops and to 

amend the terms and condition of insurance provided in the insurance policy when specifically 

permitted by the regulation, policy, actuarial documents, or special provisions.” Requests for 

written agreements were required to contain “...all information required to establish insurance 

coverage in accordance with the policy and actuarial documents.” 

Written agreements were to be based on a comprehensive underwriting review of the particulars 

of each request. RMA’s Regional Offices were responsible for issuing these agreements. The 

conditions for approval of a request for a written agreement as stated in the 2001 Written 

Agreement Handbook were: 

(1) RMA determines that adequate information is available for the individual and/or county 

to establish an actuarially sound premium rate and insurance coverage for the insurable 

crop; 

(2) The crops, types, practices, or varieties are adapted to prevalent production conditions of 

the county; 

(3) All required information was received by the specified deadlines;

 

74 Written agreements are documents issued by the RMA Regional Offices (or approved insurance providers if authorized) and accepted in 

writing by the insured to modify the terms of coverage stated in the Basic Provisions, the Crop Provisions, and the actuarial documents. 75 Due to the extended insurance period, citrus crops generally were not covered until the 2003 crop year.
Organic Crops: Revised Written Rating Report 

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41

(4) Individual requests are submitted for each insured; 

(5) The crop is commercially grown in the county and viable markets for the crop are 

available (applicable for counties without actuarial documents); 

(6) The requested change to the terms of insurance is determined by RMA to conform to 

sound insurance principles; 

(7) The requested change is a significant variation (as determined by RMA) from the terms 

and conditions established by the policy, and/or actuarial documents or special 

provisions, and is authorized by such documents, or other RMA issuances; 

(8) The requested changes to the terms and conditions of insurance are not prohibited by the 

Federal Crop Insurance Act, as amended, or by the insurance policy; and 

(9) It is the result of an appeal or mediation decision RMA is required to implement.

The Regional Offices were instructed to “deny requests that do not meet any of these 

conditions” and to provide an explanation to the Insurance Provider for denied requests. 

When a request for a written agreement was denied, the original terms and conditions of 

the contract (if applicable) were to remain in force.

Premium rates for written agreements were to be determined as follows:

(1) [The rate] Shown on the county actuarial documents for the reference county. (The rate 

tables for the reference state and county may be attached for this purpose. Any exceptions 

must be noted.);76

(2) Determined by applying a factor to rates from the reference county actuarial documents; 

(3) Determined by quoting individualized rates at the 75 percentage coverage. Differential 

factors for the crop will be used to determine the premium rate for other coverage 

percentages; or 

(4) Determined by using an add-on rate to the preliminary base rate.

Under the law in effect in 2004, rates were to be established with the goal of achieving and 

maintaining a cumulative national loss ratio of 1.075.77,78 MGR-01-004 was to remain active 

until its contents were incorporated into the Crop Insurance Handbook and the Written 

Agreement Handbook, with a projected disposal date of December 31, 2002. 

Bulletin MGR-02-001 “Written Agreements – 2002 Crop Year” (2-22-02) announced additional 

procedures for approval of written agreements due to excessive loss ratios on certain written 

agreements. These additional procedures required disapproval of requests for written agreements 

on acreage on which two or more indemnities had been paid (there is no reference to a base 

period for this determination) or that had a cumulative loss ratio of 3.00 or greater for all years 

for which the written agreement was in effect. The justification for this action was Section 

508(c)(9) of the Act: “The Board may limit the availability of additional coverage under this 

subsection in any county or area, or on any farm, on the basis of the insurance risk involved.” 

The terms of MGR-01-004 remained in effect. 

 

76 Regional Offices were authorized to use actuarial data for the crop either from the county where the land was located or from a county deemed 

to be more representative of the production conditions for which the written agreement was requested. For example, if only non-irrigated practice 

was specified in a county whereas the written agreement requested coverage for irrigated practice, the actuarial data for a county with irrigated 

practice for the crop might be referenced instead.

77 This applies to ALL written agreements that establish a rate. 78 Note the Food, Conservation, and Energy Act of 2008 changed this target loss ratio to 1.000.
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42

Bulletin MGR-02-015 “Written Agreements – 2003 Crop Year” (July 16, 2002) directed that “... 

information relating to written agreements found in the 2003 Crop Insurance Handbook, the 

2001 Written Agreement Handbook, and MGR-02-001 shall provide the experience criteria and 

procedures to be used in requesting, reviewing, and approving or rejecting written agreements. 

The 2003 Crop Insurance Handbook will control if conflicts exist between it and the 2001 

Written Agreement Handbook.” 

The 2003 Crop Insurance Handbook (FCIC-18010-01) (June 2002) added a procedure to 

recognize organic practices as “good farming practices” via written agreements. The issuance 

primarily identified the application deadline, the approval authority, and the required 

documentation. It referred the user to the Organic Crop Insurance Underwriting Guide (FCIC24140) (03-2001) for specific reporting requirements and instructions. That issuance provided 

these specific provisions, among others: 

• Organic acreage [under written agreement] was to be reported with the appropriate 

production practice and type that would pertain to conventional practice and type 

(irrigated, non-irrigated, etc.). 

• Producers were required to follow good organic farming practices and any conventional 

farming practices not in conflict with the organic practice.

• Acreage on which an organic practice was followed, but for which a producer did not 

request a written agreement, was to be insured under the conventional practice and was 

subject to uninsured cause of loss appraisals for losses due to weeds, insects, and disease 

that were deemed to have been avoidable.

• The insured was required to provide at least three years of acceptable records that 

documented organic production (not necessarily insurable crops in all years) for organic 

certified acreage and all available records for organic transitional acreage. 

Bulletin MGR-03-009 “Written Agreements – 2004 Crop Year” (08/28/03) directed that “... 

information relating to written agreements found in the 2004 Crop Insurance Handbook, the 

2001 Written Agreement Handbook, and MGR-02-001 shall provide the experience criteria and 

procedures to be used in requesting, reviewing, and approving or rejecting written agreements. 

The Crop Insurance Handbook will control if conflicts exist between it and the 2001 Written 

Agreement Handbook.” The 2004 Crop Insurance Handbook contained the same information as 

did the 2003 Handbook with regard to written agreements with the exception that definitions 

contained in the Organic Crop Insurance Underwriting Guide were included. 

Bulletin MGR-04-004 “Written Agreement Experience Criteria – 2004 and Succeeding Crop 

Years” (March 12, 2004) allowed persons previously denied written agreements under the terms 

of MGR-02-001 to apply for a written agreement if the producer: 

(1) executed an actual production history form, and 

(2) provided supporting documentation to demonstrate that no loss would have occurred in at 

least two years since the written agreement was denied. The provisions of MGR-03-009 

remained in effect otherwise.

A fundamental change in the underwriting of organic practices occurred with the publication of a 

final rule (68 FR 37723, June 25, 2003) to promulgate the 2004 Common Crop Insurance 

Regulations. This regulation amended the definition of good farming practice to include organic 

practices as “... those generally recognized by the organic agricultural industry for the area or 
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43

contained in the organic plan.” With this amendment, a factor (1.05) to adjust the premium rate 

for certified organic acreage was added to the actuarial documents for 2004 crops with a contract 

change date of November 30, 2003 or later (primarily crops planted in the spring of 2004). The 

factor was added to the actuarial documents for crops with earlier contract change dates effective 

for the 2005 crop year, along with a factor (also 1.05) for organic transitional acreage. This 

change meant producers no longer were required to submit detailed justification before acreage 

could be insured as organic. It instead shifted the burden of proof of organic practice to situations 

when loss or damage was claimed.

Under the rules established beginning the 2004 crop year for crops with an organic factor on the 

actuarial tables, the insured person was required to have in his or her possession, on the date the 

acreage was reported, a written certification from the certifying agent that specific acreage 

qualified as certified or transitional. The documentation was required to specifically identify 

fields and acreage to which the certification applied and those to which it did not. Proof of this 

evidence was not required at the time the acreage was reported, but the 2004 Loss Adjustment 

Manual (FCIC-25010) (1-2004) directed the loss adjuster to request the records and verify the 

information. Acreage with an organic certification, on which an organic practice was being 

followed, and for which a premium rate was shown on the actuarial documents was required to 

be insured as organic. If there was no organic factor on the actuarial tables and no written 

agreement was requested or approved, the acreage would be insured under the conventional 

practice and be subject to the uninsurable cause of loss provisions for weeds, insects, and 

disease. However, in March 2004, the 2004 Loss Adjustment Manual was clarified to state that 

acreage on which an organic practice was being followed was UNINSURABLE whenever there 

was no premium rate on the actuarial table, no written agreement was in effect on such acreage, 

and the acreage was certified as organic certified or transitional acreage.

The 2006 Loss Adjustment Manual added a provision that “The ‘Organic farming practice’ (as 

defined in the Basic Provisions) does not apply (including an insured’s exemption from the 

National Organic Program requirement of an organic certification to sell a commodity as 

organic) when the insured has no organic plan in effect from a certifying agent.” Under this 

provision, producers who sell less than $5,000 a year in organic products are not allowed to 

insure acreage as organic even if they follow organic practices. A certification is mandatory 

under the crop insurance program although it is not required under NOP. Under NOP, qualifying 

producers must abide by the national standards for organic products and may label their product 

as organic. However, the acreage on which the crop is produced may not be insured as organic. 

Effective for the 2006 crop year, the actuarial documents for rice were amended to add Organic 

(Transitional) and Organic (Certified) as specified insurable practices rather than labeling such 

acreage as an option (as continues to be the case for all other crops). This change in approach 

allowed RMA to adjust the reference yields, the base premium rate, and the T-yields for the 

organic practice in each county. Both the reference yields and the T-yields were reduced by 50 

percent. The base premium rate was increased by the 5 percent organic factor previously 

assessed for the organic practice. The actual change in the base premium rate differed slightly 

from 5 percent due to rounding of the surcharge. The values of the exponent and of the fixed rate 

load were not changed.
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The purpose of this action was to reduce the transitional yields to levels that evidence suggested 

were more appropriate for organic rice. The change could only be made in this manner, since 

transitional yields are associated with a type and practice on the actuarial documents, and the 

option code does not permit this treatment. If this were the only change made, the premium rates 

for organic production based in whole or in part on transitional yields would have risen 

substantially since the premium rate is negatively associated with the yield ratio. By reducing the 

reference yield, the yield ratio remains at 1.00 and the insured would pay the same premium rate 

on the unit (but with the 5 percent load) as previously if the approved yield were based entirely 

on transitional yields and the transitional yield and the reference yield are equal, or if the 

average actual yields were 50 percent lower than the original reference yield.

The effect of these changes is much more complex and depends on the number and magnitude of 

actual yields certified for a unit. A lower rate than paid originally is one potential outcome. The 

rate might also be much lower than the premium rate charged for conventional practice. This 

would occur if actual yields had less than the assumed 50 percent “yield drag” compared to 

conventional yields. Consider the example illustrated in Table 6: 

Table 6. Parameters Illustrating the Potential Effects of Changes in 2006 Crop Year Rice 

Underwriting Lowering Premium Rates

Conventional Organic

Base Premium Rate 0.051 0.055

Exponent -1.8 -1.8

Fixed Rate Load 0.031 0.031

Reference Yield 5,000 2,500

With these parameters, the premium rate for an approved yield of 5,000 lbs. for conventional 

practice is 8.2 percent and the rate for an approved yield of 2,500 lbs. for organic practice is 8.6 

percent. However, if the organic “yield drag” is only 25 percent relative to the conventional 

yield, the average yield for the organic practice would be 3,750 pounds. This would result in a 

premium rate of 5.7 percent for average organic production. The premium rate for the average 

organic practice is less than the rate charged for an average yield of conventional practice. The 

difference is that a yield of 3,750 pounds is 50 percent better than the reference yield for organic 

practice, whereas that yield is 25 percent worse than the reference yield for conventional 

practice. Consequently, the setting of an appropriate reference yield is crucial to the success of 

this approach to addressing issues with the insurance for organic crops. Additional discussion of 

the effect of this change is provided in the section of this report entitled “Use of Transitional 

Yields and Relationship of Actual Yields to Reference Yields.” 

Changes to Procedural Documents that Affected Organically Produced Crops

The 2001 Organic Crop Insurance Underwriting Guide (FCIC-24140) (03-2001) provided 

detailed definitions of organic production and details for issuing written agreements to insure 

crops produced using organic practices. MGR-01-004 had announced that “RMA will issue 

coverage and rate rules, underwriting guidelines, and procedures to establish coverage for 

organic producers through written agreements. These materials will be issued in the near future.” 

FCIC-24140 was released approximately two months later, but the Contractor could not find any 
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45

Manager’s or Product Management Bulletin to announce its availability. Subsequent issuances as 

documented above never referenced FCIC-24140 as a source of information for underwriting 

organically produced crops. 

The 2003 Crop Insurance Handbook (FCIC-18010-01) (6-02) modified Section 4, which dealt 

with Written Agreements, by adding a reference to organically produced crops recognized as 

good farming practices. The information referenced FCIC-24140 as a source document for 

underwriting such agreements. 

The 2004 Crop Insurance Handbook (FCIC-18010) (6-03) added definitions concerning 

organically produced crops that also were contained in FCIC-24140. It did not change the 

material in Section 4 that had been added in the 2003 Handbook. 

The 2005 Crop Insurance Handbook (FCIC-18010) (6-04) replaced FCIC-24140 as well as other 

issuances. Information from FCIC-24140 is included as Exhibit 38 to the 2005 Crop Insurance 

Handbook. 

Beginning with the 2005 crop year, for Crop Provisions with filing dates on or after November 

30, 2004, a provision for organically produced crops was added to the actuarial documents. Any 

organic acreage was made insurable by including the appropriate code in the Record Type 11 

(acreage). A five percent surcharge is automatically added to the premium rate when the 

appropriate code is entered. As noted earlier, no written agreements for organically produced 

crops were found in the experience data once this information was included on the actuarial 

documents. 

V .B. Documentation of the Insurance Experience for Organically Produced Crops

A review of the Data Acceptance System Handbook (known as Manual 13 or Appendix III to the 

Standard Reinsurance Agreement (SRA)) reveals provision for capture of data related to 

insurance of organically produced crops beginning in the 2001 crop year. Beginning that year, 

written agreements for organically produced crops were specifically recognized with an explicit 

set of codes. 

Table 7 identifies the coding of the organic data processed under the Record Type 11 (Acreage) 

by year as specified in the Data Acceptance System Handbook. The codes are interpreted as 

follows: 

RC Certified Organic Acreage with a location or reference county. 

RT Transitional Organic Acreage with a location or reference county. 

NC Certified Organic Acreage with no reference county. 

NT Transitional Organic Acreage with no reference county. 

OC Organic Certified Acreage

OT Organic Transitional Acreage

 702 Organic Certified (rice only)

 712 Organic Transitional (rice only) 

The difference in the alphabetic coding was based on the source of the premium rate and other 

insurance information: whether it was from the county where the land was located (no reference 
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46

county) or whether the written agreement data referenced another county for that information 

(with a location or reference county). Information in Table 7 identifies the data fields in which 

the codes appeared for each year. The 2007-2008 data are the same as 2005-2006. Due to 

reformatting of the record, the location changed but the nature of the information did not. 

T ABLE 7. Codes Specified for the Type 11 Record with Respect to Reporting Organic Data, 

1999-2008 

Year Field 26 Written 

Agreement Type

Field 28 Written 

Agreement Processing 

Flag

Field 49 Common 

Option Codes

Field 23 Written 

Agreement Type

Field 25 Written 

Agreement Processing 

Flag

Field 46 Common 

Option Codes

Field 11 *

2008 OC RC, RT, NC, NT OC, OT 702, 712

2007 OC RC, RT, NC, NT OC, OT 702, 712

2006 OC RC, RT, NC, NT OC, OT 702, 712

2005 OC RC, RT, NC, NT OC, OT N/A

2004 OC, OT RC, RT, NC, NT OC N/A

2003 OC, OT RC, RT, NC, NT Blank N/A

2002 OC, OT RC, RT, NC, NT Blank N/A

2001 OC, OT RC, RT, NC, NT Blank N/A

2000 ← No references to organic →

1999 ← No references to organic →

*These codes in Field 11 apply only to rice 702 (certified) and 712 (transitional)

Source: The Contractor’s Underwriting Department using USDA, RMA data.

W&A reviewed the document “Actuarial Documentation of Multiple Peril Crop Insurance 

Ratemaking Procedures”79 (Actuarial Procedures). This document provides a detailed description 

of the procedures followed by RMA to establish premium rates. Premium rates are based on 

experience to the extent this is practical, with an experience period beginning in 1975 if data 

from that period are available at the county level for a crop (page 16). The data at the 

county/crop level (all practices and types combined) are assigned a credibility score based on the 

number of units indemnified during the experience period. The credibility score is based on 271 

paid indemnities during the experience period (page 21). If there are 271 or more paid 

indemnities, the credibility score is 1.00. If the number of paid indemnities is fewer than 271, the 

credibility score is formed by taking the square root of the ratio of the number of paid 

indemnities to 271. For example, if the number of paid indemnities is 100, the credibility score is 

the square root of (100/271), which is approximately 60 percent. This means the data from the 

county/crop level are weighted only 60 percent in the ratemaking process. Data from surrounding 

counties then receive a greater weight.

Type/practice data are treated differently.80

 

79 http://www.rma.usda.gov/pubs/2000/mpci_ratemaking.pdf

 According to the Actuarial Procedures, 

“Type/Practice factors are derived from MPCI data that is aggregated at a level greater than the 

county level. This is appropriate, since the county data would likely lack sufficient credibility. In 

addition, we would not expect that the relative impact of specific practices would vary 

80 The organic practice (with the exception of rice) is treated as an option under the actuarial procedures of RMA, and can be considered to 

generally conform to treatment of a type/practice. 
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47

significantly from one county to the next (although the impact could vary across broader 

regions)” (page 32). This statement implies, but does not specifically state, that the same 

standard for credibility (a minimum of 271 losses) applies to type/practice data as to the 

county/crop data. Accordingly, under the Actuarial Procedures, it is appropriate to aggregate the 

organic data to a higher level of aggregation than the county. The first level to consider might be 

a grouping of counties having similar characteristics (an RMA risk region). The Contractor first 

aggregated data to the state/crop level to determine the number of such combinations that might 

meet the credibility standard established by RMA. The Contractor is not aware that aggregation 

to a level greater than a state is practiced in the ratemaking procedures, and notes this is not 

discussed in the Actuarial Procedures. The parenthetical comment about variability in “broader 

regions” included above raises a caution about aggregation. In addition, aggregation across crops 

is likely to be problematic. This aggregation is not discussed in the Actuarial Procedures since 

RMA’s ratemaking procedures are applied crop by crop. 

With the credibility standard of 271 losses, the following crop/state combinations (Table 8) are 

fully credible at the state level for type/practice determinations (number in parentheses is number 

of units indemnified).81

T ABLE 8. Credible Crop/State Combinations at the 271 Indemnities per Crop/State Level 

Crop State

Wheat Colorado (311), Montana (747), and North Dakota (455) 

Flax North Dakota (463) 

Corn Iowa (353), Minnesota (404), Wisconsin (445)

Soybeans Iowa (391), Minnesota (643), Wisconsin (313)

The process described in Actuarial Procedures can be applied directly to these crop/state 

combinations. However, recall that the experience period for ratemaking begins in 1975 for 

crops with that much experience. It would not be reasonable to expect some crops to accrue 271 

losses in only 5 years compared to the totality of the loss history considered in a ratemaking 

exercise. If the standard were relaxed to state that the number of losses in the organic experience 

period must be proportional to the length of the experience period for the crop, fewer years 

would be necessary to ascribe a reasonable credibility to the data. Although this is not discussed 

in the Actuarial Procedures, it might be an appropriate adjustment to recognize the recent 

introduction of capture for organic data. Assuming this adjustment is acceptable, the number of 

losses for 5 years would be 41 (5 years divided by 33 years times 271). In this case, the 

following crop/state combinations (Table 9) could be considered to have a reasonable degree of 

credibility:

 

81 These state/crop combinations are ranked as fully credible based on the simplifying assumption that 271 indemnity records at the state level 

provides the same level of credibility as 271 records at the county level.
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T ABLE 9. Credible Crop/State Combinations at the Adjusted Indemnities per Crop/State 

Level

Crop State

Wheat Minnesota (98), Nebraska (76), Oklahoma (58), South Dakota (43), Texas (58), Utah (94), and Wyoming (164)

Oats Minnesota (44) and North Dakota (129)

Millet Colorado (62) and Nebraska (84)

Rice Arkansas (77) and Texas (48)

Cotton Texas (142)

Almonds California (76)

Corn Illinois (88), Michigan (168), Ohio (48), and South Dakota (49)

Dry Beans Michigan (51)

Grain Sorghum Kansas (67)

Grapes California (52)

Apples California (218)

Dry Peas Montana (159) and North Dakota (79)

Sunflowers North Dakota (47)

Soybeans Illinois (92), Missouri (65), Nebraska (103), and North Dakota (69)

Potatoes Colorado (65)

Barley Montana (64) and North Dakota (138)

The group of crop/state combinations that is fully credible with the standard of 271 loss 

observations constitutes slightly less than one-half of all organic units indemnified during 2004-

2008. By reducing the standard on a pro-rata basis, slightly more than three-fourths of the loss 

units are included. The complete table of crop/state combinations and number of losses is 

included as Appendix C.

In the foreseeable future, it is unlikely organic production of any commodity crop will represent 

more than a small percentage of the total production of the crop. In 2007, the percentage of 

insured organic acreage approached 40 percent of the NASS reported organic acreage from the 

Census. If the insurance for the organic production adequately and appropriately addresses the 

risks the crop faces, it is easier to foresee comparable relative levels of participation between 

organic production and non-organic production. Data available as a result of the increase in 

insured organic acreage will support development of appropriate yield differentials and yield

variability analyses when appropriate time series are available. The Contractor believes RMA 

will need to apply the procedures it has established to determine a differential for a practice when 

data are relatively scarce compared to the totality of data for a crop/state combination. Organic 

experience data for most crops do not yet meet the standard of credibility established by RMA 

unless the assumption that geography does not affect the performance can be supported. 

Written Agreement History and Performance

Data for written agreements for organic crops from the 2001 crop year to the 2005 crop year 

were compiled. Data for 2005 represent the limited number of crops for which there was no 

organic factor (1.05) on the actuarial tables (primarily citrus, for which the contract change date 

was November 2003). The NC code (organic certified acreage where the written agreement used 
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county actuarial data where the land was located) accounted for over 70 percent of the activity 

with written agreements, and the RC code (organic certified acreage where the written agreement 

used another county’s actuarial data) accounted for about 25 percent of the activity with written 

agreements. Transitional acreage was less than three percent of the activity with written 

agreements. The number of units or acres for which producers sought a written agreement was 

negligible. The perception of a relatively small chance of an uninsured cause of loss appraisal for 

certain causes of loss and the burden of applying for a written agreement may have been barriers 

to participation in the organic coverage by organic producers during this period. Table 10 

displays written agreement performance by type for the years 2001 through 2005. 
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T ABLE 10. Written Agreements issued by Type and Performance, 2001 through 2005 

Written Agreement 

Code Units Acres (1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio \1 

Loss Cost

Ratio

NC 2,267 170 29,217 3,596 12.3 1,066 47.0 5,036 1.400 0.172

NT 66 5 928 116 12.5 25 37.9 138 1.183 0.148

RC 823 42 8,466 951 11.2 341 41.4 1,036 1.090 0.122

RT 12 0 67 12 18.6 8 66.7 33 2.608 0.485

Total 3,168 217 38,679 4,676 12.1 1,440 45.5 6,242 1.335 0.161

NC Percent of Total

71.6 78.5 75.5 76.9 74.0 80.7

Transitional Percent 

of Total

2.5 2.3 2.6 2.8 2.3 2.7 

Source: The Contractor’s Underwriting Department after USDA, RMA data.
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It is not possible to compare non-organic insurance experience in a manner that corresponds to 

the four codes for written agreements since more than one type of written agreement may have 

been issued in a particular county. Thus, matching non-organic business to the business 

addressed under individual written agreement codes would result in double-counting in some 

cases. Hence, for a comparison of organic and conventional experiences, only the grand total of 

the non-organic business is shown. However, as seen in Table 10, the majority of this activity is 

associated with the NC code. The non-organic business represents the same crops for which at 

least one written agreement to cover organic production was issued in a county for the same crop 

year.

Crops insured under written agreements constituted about one half percent of the units, acres, 

liability, and premium in the same counties where the written agreements were issued. However, 

the organic share of the loss data is about twice as large, about one percent. The percentage of 

units indemnified, the loss ratio, and the loss cost ratio are 2 up to almost 3 times greater for the 

organic practice even though the earned premium rate was 36 percent greater. 82 Since these 

contracts were individually underwritten by RMA Regional Offices, there is no systematic 

underlying structure to the insurance offers that were made under this system. Each office was 

directed to follow a specific process utilizing specified information to develop the parameters of 

the insurance offer. However, a certain amount of judgment was allowed. In addition, applicants 

were required to submit a significant amount of information, a task some producers found 

onerous. This may have discouraged some producers from applying for coverage. This raises the 

question of reliability and comparability of this information with data generated when organic 

acreage became generally insurable as an option. Since these data are much worse than the later 

data, the Contractor recommends it be used for setting premium rates for the organic practice 

with caution. Greater weight should be given to the much more standardized data developed 

beginning in crop year 2005. 

Table 11 demonstrates the magnitude of various variables with respect to the organic practice, 

when considered in conjunction with Table 10. Table 10 contains data regarding transitional and 

certified organic acreage insured during 2001-2005. Table 11 contains the non-organic data for 

the same counties for those years. For example, the organic practice represented 3,168 organic 

units insured compared to 636,164 non-organic units insured, which indicates organic units 

represented only 0.497 percent of the non-organic units insured. 

 

82 The data in the row labeled “Organic Share” represent the absolute percentage share of the variable (such as acres insured) or the relative level 

of a percentage variable such as percent of unit indemnified. A value greater than 100 percent in the latter case indicates that units insured under 

the organic practice were more likely to be involved in a loss situation relative to non-organic units based purely on an assessment of the 

numbers.
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T ABLE 11. Non-Organic Crops in Counties in Which a Written Agreement was Issued for Organic Practice, 2001 through 2005 

 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

NonOrganic 636,164 47,637 9,145,122 813,281 8.9 133,717 21.0 562,517 0.692 0.062

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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Common Option Code History and Performance 

Use of a common option code for organic acreage is found in the data beginning with the 2004 

crop year. Acreage included under an organic practice increased substantially once it no longer 

was necessary to apply for a written agreement. Even after acknowledging the difference in the 

number of years in each dataset, it still is clear that producers were more likely to insure acreage 

as organic during 2004 through 2008 when there were common option codes on the actuarial 

documents. Under the rules in effect for most of this period, such acreage was required to be 

insured under the organic practice if a certificate was in effect on the acreage and the organic 

practice was followed. The organic share of the acreage tripled, but still remained at less than 

two percent of insured acres for common counties and crops. 

As was the case under written agreements, almost all the insured acreage was certified organic 

acreage; only limited acreage is classified as transitional organic acreage (Table 12). Aggregate 

loss performance of acreage insured under the organic code improved relative to written 

agreements, but only marginally. The percent of units indemnified, the loss ratio, and the loss 

cost ratio continued to be substantially higher than the same measures of performance for 

acreage insured under non-organic practices. This pattern is consistent at the highest level of 

aggregation, but is not statistically significant at that level. Nor is it consistent between crops, by 

county, or temporally, or systemic as experience is aggregated to a lower level. Nonetheless, 

from the perspective of an insurance construct, the losses associated with organic production 

need to be addressed in an appropriate manner. Differences in risk associated with different 

crops need to be addressed as data become available, while the insurance structure should not 

distort participation patterns in ways that result in adverse selection. As additional data become 

available, it should be possible to establish statistically valid yield differentials, differences in 

yield variability, and corresponding differences in T-yields and rates. In the meantime, RMA 

should apply its ratemaking methodology as it normally would when data for a type/practice 

represent only a small share of the total insurance experience for a crop.
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T ABLE 12. Organic Acreage Insured Under the OC and OT Common Option Code, 2004 through 2008* 

 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

OC 21,964 1,503 394,824 50,133 12.7 8,480 38.6 55,753 1.112 0.141

OT 2,404 158 54,959 5,253 9.6 826 34.4 6,294 1.198 0.115

Total 24,368 1,661 449,783 55,386 12.3 9,306 38.2 62,047 1.120 0.138

Transitional Percent 

of Total

10.9 10.5 13.9 10.5 9.7 11.3 

* The unique actuarial approach for rice and the resulting insurance experience is described earlier in the report.

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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55

Use of Transitional Yields and Relationship of Actual Yields to Reference Yields

The Contractor analyzed the Type 15 records in the 2008 experience file to determine 1) use of 

transitional yields and 2) the relationship of actual yields certified by the producer to the 

reference yield. This relationship determines the rate that is charged for a particular yield in a 

particular county. First, it was necessary to resolve a discrepancy in the data.

The Contractor’s review of the procedures set forth in Appendix 38 of the Crop Insurance 

Handbook led to the set of rules set forth as follows: 

(1) Whenever a unit or portion thereof is being converted to organic production, two 

databases are established: one to capture actual organic yields on the acreage as long as it 

remains in transitional organic status (Database A) and the second to accrue actual 

organic yields from transitional and certified organic acreage (Database B).83

(2) The initial entries into Database A are appropriate transitional yields (either adjusted or 

unadjusted according to the rules of APH). For most crops, these are the standard Tyields and for rice, the special T-yields established for this crop. 

 

(3) Once production begins on the transitional organic acreage, actual yields are entered into 

this database with a flag of “G” (actual transitional organic yield). “This yield type can be 

combined with up to nine years of any other yield type (except S, SX, A, AY, NA, PA, 

PP, PW) for a minimum of four years” (DAS Type 15 record Exhibits).84

(4) Database B also is populated initially with the appropriate T-yields. The T-yields are 

replaced by the actual transitional organic yields with a flag of “G” until the acreage 

attains the status of organic certified.

Each actual 

year of production thus replaces one of the T-yields included at the initiation of the 

database.

(5) Once the acreage has attained the status of organic certified, the actual organic certified 

yields, identified with a flag of “V,” are entered in the database. As these enter the 

database, the oldest of the four “T” or “G” yields is eliminated. Once four years of “V” 

yields are available, the database builds to ten years. As in the case of a “G” flag, “This 

yield type can be combined with up to nine years of any other yield type (except S, SX, 

A, AY, NA, PA, PP, PW) for a minimum of four years” (DAS Type 15 record 

Exhibits).85 

The Type 15 data do not conform entirely to the data structure as described. Numerous records 

contain a flag of “A,” which is inconsistent with the guidance in the Crop Insurance Handbook 

that conventional actual yields are not entered into an organic database. The Contractor found 

that records with an “A” flag for yields did not contain either “V” or “G” flags. The “A” flags 

were combined with “T” and other flags. When the Contractor examined the records for rice, all 

records that contained one of more “T” flags did contain the organic T-yield from the FCI-35 

specific for that crop. Thus, it appears the records with “A” type yields were edited with the 

requirement: “Can be combined with up to 9 years of any yield type other than S for a minimum 

of 4 years.” In contrast, the records that contained a “V” or “G” were edited with the requirement 

stated earlier in this section. But, the Contractor notes, the Crop Insurance Handbook specifically 

prohibits use of conventional yields in the organic databases. Thus, the “A” type code or any of 

 

83 The terms “Database A” and “Database B” do not appear in the procedures. The nomenclature is adopted in this report for convenience. 84 http://www.rma.usda.gov/data/m13/aprvd2006.html 85 http://www.rma.usda.gov/data/m13/aprvd2006.html
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56

its relatives should not appear in these data. Based on these findings, the Contractor concluded 

that records containing “A” flags really were intended to be “G” or “V” flags.

Rice Type 15 Data 

The rice Type 15 data for the 2008 crop year are considered first for two reasons: 1) it is a 

relatively small dataset and 2) the Contractor’s earlier observations about the potential the 

premium rate could be lower on organic acreage than would be charged for the same yield on 

non-organic acreage.

There were a total of 472 records for rice produced under organic practices in the 2008 crop year 

Type 15 dataset. The distribution of those records by state and by number of actual yields is 

shown in Table 13. California and Texas each accounted for around one-half these organic Type 

15 records. Only about one-third of the records had more than one actual yield. An actual yield 

includes all yield types “A,” “G,” and “V.”

T ABLE 13. Number of Type 15 Records for Rice by State and Number of Actual Yields, 

2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas Grand 

Total Percent

None 53 1 150 204 43 

1 79 35 114 24

2 24 14 38 8

3 14 1 6 21 4

4 16 3 19 4 

5 1 13 1 15 3

6 12 12 3

7 14 1 15 3

8 5 5 1 

9 1 9 1 11 2

10 13 5 18 4

Grand Total 2 252 1 1 216 472

Table 14 shows the ratios of the average actual yield to the reduced reference yield that applies 

to organic practices for rice. Data for Arkansas, Louisiana, and Mississippi provide no 

meaningful information. The reduced reference yield clearly is much lower than the average of 

the actual yields in California regardless of the number of actual yields included in the Type 15 

records. The reduced reference yield is too high in Texas for virtually all cases, but the number 

of observations above two actual yields per record is extremely small. However, where there are 

larger numbers of observations, the ratio of the average actual yield to the organic reference yield 

tends to be larger. This may indicate a difference in short-term results and longer-term 

relationships. 
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T ABLE 14. Average Ratio of Actual Yields to Organic Reference Yield for Rice, by State 

and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

None N/A N/A N/A N/A N/A

1 1.53 0.83

2 1.41 1.03

3 1.44 2.56 0.75

4 1.50 0.72 

5 2.60 1.56 0.56

6 1.39

7 1.46 0.75

8 1.31 

9 2.03 1.32 0.84

10 1.55 1.30

Average 2.32 1.45 2.56 0.85

Table 15 reports the average ratio of the average actual yield to the non-organic reference yield. 

The data reveal the same characteristics as does Table 14. However, the table does demonstrate 

the percentage the average actual yield represents of the original reference yield. In California, 

the organic practice tends to be about 25 percent lower than the non-organic practice at most 

numbers of yields per record. Texas, on the other hand, is very variable, with an average yield 

drag of organic to non-organic of around 58 percent. However, the range is large due to the low 

numbers of observations in some instances. 
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58

T ABLE 15. Average Ratio of Actual Yields to Non-Organic Reference Yield for Rice, by 

State and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

None N/A N/A N/A N/A N/A

1 0.76 0.42

2 0.70 0.51

3 0.72 1.28 0.38

4 0.75 0.36 

5 1.30 0.78 0.28

6 0.70

7 0.73 0.37

8 0.66 

9 1.02 0.66 0.42

10 0.78 0.65

Average 1.16 0.72 1.28 0.42

Table 16 simply indicates the average multiplier of the base premium rate assuming an exponent 

of -1.800 in all cases. This is intended merely to demonstrate a range of the multipliers. All yield 

ratios were individually cupped at -0.50 and capped at 1.50 consistent with practice for 

calculating this value.

T ABLE 16. Average Multiplier of Base Premium Rate with Organic Reference Yield for 

Rice, by State and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

1 0.768 1.980

2 0.712 1.356

3 0.694 0.482 2.043

4 0.642 1.901 

5 0.482 0.556 2.810

6 0.685

7 0.702 1.689

8 0.754 

9 0.482 0.680 1.383

10 0.522 0.770

Average 0.482 0.672 0.482 1.741

Table 17 shows the numbers of actual yields by organic practice. Virtually all the data were 

reported as certified organic when the organic flag is included. Differences in the average actual 
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59

yield by practice are not reported due to the scarcity of yields flagged as transitional organic 

practice.

T ABLE 17. Rice: Number of Actual Yields by Organic Practice, 2008 Type 15 File 

Number of 

Actual 

Yields

Certified 

Organic

Transitional 

Organic

0 116 88

1 105 9

2 35 3 

3 21 

4 19

5 13 2

6 12 

7 15 

8 5

9 11

10 17 1 

Conclusions Regarding Rice 

The data indicate the across the board adjustment to the rice reference yields and transitional 

yields for organic practice was inappropriate. It appears California reference yields were reduced 

more than appropriate and Texas reference yields may not have been reduced enough. However, 

the data for Texas are less conclusive than the data for California, since so few units reported 

more than one or two actual yields when any actual yields were reported. The status for 

Arkansas, Louisiana, and Mississippi cannot be determined due to the lack of data. The 

adjustments to the T-yields were affected similarly. In some cases, the reference yield and the Tyield are not identical; however, in all cases the Contractor examined, the differences were not 

large. Hence, the inference from the comparisons of the ratios of the average actual yield to the 

reference yield that they apply to transitional yields as well. 

All Crops Results

Table 18 reports the number of Type 15 records in the 2008 dataset along with certain 

characteristics of those records for each crop for which an organic practice was reported and that 

are either Type B or Type C crops for the purposes of Actual Production History. About onethird of all records consisted exclusively of T-yields, a value that is relatively constant for corn, 

soybeans, and wheat. Several other crops also had about one-third of all records composed only 

of t-yields. There is a wide variation in use of T-yields among the remaining crops. 
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T ABLE 18. Use of Actual Yields and Ratio of Average Actual Yield to Reference Yield, All 

Crops and States

Crop Total 

Records

Records with no Actual 

Yield

Percent No Actual 

Yield

Total Actual 

Yields

Average per Record 

1/

Ratio Actual Yield to Reference 

Yield

11 5,507 1,835 33 15,450 4.2 0.63

12 18 9 50 42 4.7 0.57

13 31 13 42 28 1.6 0.39

15 27 17 63 21 2.1 0.45

16 974 320 33 2,305 3.5 0.71

17 342 120 35 712 3.2 0.59

18 472 204 43 900 3.4 0.90

21 185 94 51 565 6.2 1.11

22 7 0 0 16 2.3 0.89

28 70 10 14 323 5.4 0.71

29 29 5 17 150 6.3 1.17

31 688 101 15 2,100 3.6 0.66

33 130 42 32 428 4.9 0.67

34 2 0 0 9 4.5 0.31

36 24 3 13 127 6.0 1.04

39 2 2 100 0 0.0 0.00

41 3,319 1,252 38 8,104 3.9 0.65

42 110 31 28 188 2.4 0.44

43 69 45 65 76 3.2 0.47

46 18 5 28 44 3.4 0.45

47 847 438 52 1,202 2.9 0.57

49 73 28 38 102 2.3 0.37

51 178 83 47 357 3.8 0.40

52 65 9 14 271 4.8 1.18

53 274 39 14 1,476 6.3 1.05

54 600 143 24 1,800 3.9 0.87

55 3 1 33 10 5.0 1.41

58 9 2 22 40 5.7 0.38

60 18 3 17 85 5.7 1.55

64 85 23 27 97 1.6 0.43

67 528 130 25 905 2.3 0.38

69 3 2 67 1 1.0 0.42

75 150 114 76 94 2.6 0.47

78 565 277 49 798 2.8 0.45

81 3,074 984 32 8,789 4.2 0.67

84 172 47 27 348 2.8 0.54

87 117 13 11 574 5.5 0.94

89 150 34 23 664 5.7 0.78

91 987 328 33 1,975 3.0 0.64

92 45 8 18 232 6.3 1.02

94 69 11 16 187 3.2 0.79

107 1 0 0 1 1.0 0.06

218 18 5 28 70 5.4 1.08

219 4 0 0 29 7.3 0.92

220 65 24 37 244 6.0 0.78

221 7 0 0 33 4.7 1.00

222 1 0 0 1 1.0 0.71

223 83 10 12 453 6.2 0.91

229 43 35 81 10 1.3 0.28

231 2 0 0 2 1.0 0.95

234 1 1 100 0 0.0 0.00

235 1 1 100 0 0.0 0.00

256 1 0 0 6 6.0 0.86

Total 20,263 6,901 34 52,444 3.9 0.68

1/ Average for all records containing at least one actual yield.

When actual yields were reported, the typical record contained nearly four actual yields, 

indicating insurance typically is based on a relatively long history of organic practice. An 

interesting comparison is the ratio of the average of the actual yields certified to the reference 

yield, the value of which is about two-thirds. All the major crops – corn, soybeans, and wheat – 

that collectively account for a large share of the organic acreage also have an average actual 
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61

yield that is about two-thirds of the reference yield. These three crops also had about four 

certified yields on average for each unit with actual certified yields. Thus, it would appear that 

the reference yields, on average, tend to exceed the production potential of acreage used for 

organic production by about 50 percent (reference yield should be reduced by one-third on 

average).

Differences among states exist. Tables 19, 20, and 21 report data by state for wheat, corn, and 

soybeans, respectively. The variable of greatest interest is the ratio of certified actual yields to 

the reference yield, a value that shows variation among states. This difference in some cases is 

based on few observations. But, it is difficult to make generalizations among states on the basis 

of these data. Are differences in the ratio due to differences in the average yield on organic acres 

or to differences in the basis of the reference yield? Since the Contractor must accept the 

reference yield as a given, it appears the potential yield on organic acres is not consistent among 

states, a characteristic that also was evident with the rice data considered earlier.

T ABLE 19. Wheat: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records with 

No Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average 

per Record 

1/ 

Ratio Actual 

Yield to 

Reference Yield

06 29 16 55 31 2.4 0.50

08 515 211 41 1,335 4.4 0.83

16 59 15 25 187 4.3 0.63

17 32 5 16 112 4.1 0.98

19 9 2 22 10 1.4 1.08

20 273 76 28 1,104 5.6 0.77

26 192 89 46 173 1.7 0.71

27 493 252 51 629 2.6 0.49

30 1,616 413 26 4,730 3.9 0.61

31 352 126 36 1,107 4.9 0.83

34 1 1 100 0 0.0 0.00

36 3 0 0 21 7.0 1.07

38 930 243 26 2,987 4.3 0.67

39 15 7 47 35 4.4 0.45

40 51 14 27 116 3.1 0.84

41 16 14 88 2 1.0 0.14

46 230 67 29 840 5.2 0.62

48 90 36 40 219 4.1 0.63

49 219 110 50 496 4.6 0.47

53 27 13 48 25 1.8 0.30

55 57 36 63 36 1.7 0.50

56 298 89 30 1,255 6.0 0.81

Grand Total 5,507 1,835 33 15,450 4.2 0.63

1/ Average for all records containing at least one actual yield.
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62

T ABLE 20. Corn: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records with 

No Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average per 

Record 1/ 

Ratio Actual 

Yield to 

Reference Yield

06 1 0 0 2 2.0 1.26 

08 20 6 30 29 2.1 0.54

09 2 2 100 0 0.0 0.00

16 8 3 38 7 1.4 0.50

17 122 42 34 318 4.0 0.61 

18 10 4 40 20 3.3 0.54

19 609 155 25 2,167 4.8 0.81

20 81 19 23 312 5.0 0.73

23 17 2 12 38 2.5 0.65 

24 7 4 57 3 1.0 0.99

26 393 183 47 639 3.0 0.68

27 619 260 42 1,316 3.7 0.72

29 40 6 15 101 3.0 0.70 

31 341 152 45 716 3.8 0.68

33 1 1 100 0 0.0 0.00

34 3 0 0 5 1.7 0.54

36 55 15 27 163 4.1 0.58 

37 11 3 27 14 1.8 0.48

38 125 56 45 156 2.3 0.59

39 65 19 29 131 2.8 0.51

41 2 1 50 2 2.0 0.52 

42 35 16 46 104 5.5 0.34

46 107 28 26 474 6.0 0.51

48 14 11 79 7 2.3 0.19

50 29 15 52 57 4.1 0.55 

51 29 6 21 100 4.3 0.88

53 9 4 44 7 1.4 0.77

55 533 218 41 1,204 3.8 0.67

56 31 21 68 12 1.2 0.22 

Grand Total 3,319 1,252 38 8,104 3.9 0.65

1/ Average for all records containing at least one actual yield.
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T ABLE 21. Soybeans: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records 

with No 

Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average per 

Record 1/ 

Ratio Actual 

Yield to 

Reference Yield

13 2 1 50 2 2.0 1.40 

17 131 32 24 498 5.0 0.74 

18 8 3 38 17 3.4 0.37 

19 621 174 28 2,137 4.8 0.76 

20 70 21 30 174 3.6 0.61 

24 7 5 71 3 1.5 1.03 

26 456 190 42 999 3.8 0.60 

27 744 201 27 2,109 3.9 0.63 

29 82 6 7 408 5.4 0.82 

31 252 108 43 550 3.8 0.75 

34 2 0 0 3 1.5 0.44 

36 30 8 27 111 5.0 0.56 

37 11 0 0 15 1.4 0.88 

38 120 49 41 196 2.8 0.47 

39 56 9 16 183 3.9 0.75 

42 6 1 17 17 3.4 0.65 

46 115 32 28 459 5.5 0.66 

48 5 4 80 2 2.0 0.25 

51 15 3 20 66 5.5 0.78 

55 341 137 40 840 4.1 0.53 

Grand Total 3,074 984 32 8,789 4.2 0.67 

1/ Average for all records containing at least one actual yield.

Additional disaggregation of data by state is not included in this report; however, the data on 

which Tables 18 through 21 are based is included in Appendix D. The general indications 

provided in Tables 18 through 21 are similar for all crops and states that have a reasonable 

amount of data. 

Organic Acreage Under Common Option Code Relative to Non-Organic Acreage of the 

Same Crops in the Same Counties

Units insured with a common option code for organic practice represented only about 1.5 percent 

of the total units, acres, liability, and premium of the same crops in the same counties (Table 22). 

The aggregate indemnities, however, were nearly three percent of the total for these crops and 

counties. The earned premium rate for acreage insured with an organic code was about 27 

percent greater than for the same crops in the same counties. In spite of this higher premium rate, 

both the loss ratio and the loss cost ratio were substantially higher in the aggregate than for 
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acreage insured without an organic common option code. While this pattern is consistent at the 

highest level of aggregation, it is not statistically significant at that level. Differences in risk 

associated with different crops need to be addressed as data become available and the insurance 

structure should not distort participation patterns in any way that can result in adverse selection. 

As additional data become available, it should be possible to establish statistically valid yield 

differentials, differences in yield variability, and corresponding differences in T-yields and rates.

In the meantime, RMA should apply its ratemaking methodology as it normally would when data 

for a type/practice represent only a small share of the total insurance experience for a crop. 

As will be demonstrated later, there are major differences among crops and states with regard to 

the performance of organic acreage relative to non-organic acreage. Tables 12 and 22 are to be 

interpreted in the same manner as Tables 10 and 11. 
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T ABLE 22. Non-Organic Acreage of Same Crops Insured in Counties with a 

Common Option Code for Organic Practice, 2004 through 2008 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

NonOrganic 1,497,444 113,694 34,590,732 3,348,387 9.7 343,418 22.9 2,280,253 0.681 0.066

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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Significance of Counties with an Organic Code, 2004 through 2008 

The contract requires comparisons of organic and non-organic insurance performance in the 

same counties. However, this raises the question: “How representative are counties with organic 

coverage relative to all counties in which insurance was written during these years?” Counties in 

which at least 1 unit with organic coverage was reported during 2004 through 2008 represented 

slightly more than 10 percent of units and acres, and about 13 percent of premium and liability 

for all eligible insurance plans in the United States during those years (Table 23).86 Interestingly, 

the earned premium rate, the loss ratio, and the loss cost ratio for the counties with at least one 

unit insured with organic practice was lower than the U.S. average for all additional coverage. 

These data may indicate that organic practice was more prevalent in counties with relatively 

lower premium rates than the national average. As will be shown later, the dominance of 

California with regard to liability and premiums likely biases the earned premium rate. But, 

when examined solely within the counties with an organically insured practice, the organic 

practice in the aggregate had higher than average premium rates and worse than average loss 

experience.

 

86 Insurance plan codes such as GRP and GRIP for which organic codes are not offered are excluded from the All U.S. data. These plan codes 

automatically would not have been included in the county/crop combinations with an organic practice code.
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T ABLE 23. Experience in Counties with Organic Practice Versus all Additional Coverage 

in the United States, 2004 through 2008 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium

Rate (%)

Units 

Indemnified

Units 

Indemnified (%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

With Organic 

Code 1/ 1,521,812 115,355 35,040,514 3,403,773 9.7 352,724 23.2 2,342,300 0.688 0.067

All U.S. 2/ 14,695,151 1,062,958 265,839,212 26,826,649 10.1 3,356,644 22.8 19,677,272 0.733 0.074

Percent Organic 10.4 10.9 13.2 12.7 95.9 10.5 100.4 11.9 NA NA

Source: The Contractor’s Underwriting Department using USDA, RMA data.

1/ With organic code = at least one unit was insured in a county using an organic code during 2004 through 2008

2/ All U.S. indicates all counties in the United States but excluding insurance plans without organic option codes.
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T ABLE 9. Credible Crop/State Combinations at the Adjusted Indemnities per Crop/State 

Level

Crop State

Wheat Minnesota (98), Nebraska (76), Oklahoma (58), South Dakota (43), Texas (58), Utah (94), and Wyoming (164)

Oats Minnesota (44) and North Dakota (129)

Millet Colorado (62) and Nebraska (84)

Rice Arkansas (77) and Texas (48)

Cotton Texas (142)

Almonds California (76)

Corn Illinois (88), Michigan (168), Ohio (48), and South Dakota (49)

Dry Beans Michigan (51)

Grain Sorghum Kansas (67)

Grapes California (52)

Apples California (218)

Dry Peas Montana (159) and North Dakota (79)

Sunflowers North Dakota (47)

Soybeans Illinois (92), Missouri (65), Nebraska (103), and North Dakota (69)

Potatoes Colorado (65)

Barley Montana (64) and North Dakota (138)

The group of crop/state combinations that is fully credible with the standard of 271 loss 

observations constitutes slightly less than one-half of all organic units indemnified during 2004-

2008. By reducing the standard on a pro-rata basis, slightly more than three-fourths of the loss 

units are included. The complete table of crop/state combinations and number of losses is 

included as Appendix C.

In the foreseeable future, it is unlikely organic production of any commodity crop will represent 

more than a small percentage of the total production of the crop. In 2007, the percentage of 

insured organic acreage approached 40 percent of the NASS reported organic acreage from the 

Census. If the insurance for the organic production adequately and appropriately addresses the 

risks the crop faces, it is easier to foresee comparable relative levels of participation between 

organic production and non-organic production. Data available as a result of the increase in 

insured organic acreage will support development of appropriate yield differentials and yield

variability analyses when appropriate time series are available. The Contractor believes RMA 

will need to apply the procedures it has established to determine a differential for a practice when 

data are relatively scarce compared to the totality of data for a crop/state combination. Organic 

experience data for most crops do not yet meet the standard of credibility established by RMA 

unless the assumption that geography does not affect the performance can be supported. 

Written Agreement History and Performance

Data for written agreements for organic crops from the 2001 crop year to the 2005 crop year 

were compiled. Data for 2005 represent the limited number of crops for which there was no 

organic factor (1.05) on the actuarial tables (primarily citrus, for which the contract change date 

was November 2003). The NC code (organic certified acreage where the written agreement used 
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county actuarial data where the land was located) accounted for over 70 percent of the activity 

with written agreements, and the RC code (organic certified acreage where the written agreement 

used another county’s actuarial data) accounted for about 25 percent of the activity with written 

agreements. Transitional acreage was less than three percent of the activity with written 

agreements. The number of units or acres for which producers sought a written agreement was 

negligible. The perception of a relatively small chance of an uninsured cause of loss appraisal for 

certain causes of loss and the burden of applying for a written agreement may have been barriers 

to participation in the organic coverage by organic producers during this period. Table 10 

displays written agreement performance by type for the years 2001 through 2005. 
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50

T ABLE 10. Written Agreements issued by Type and Performance, 2001 through 2005 

Written Agreement 

Code Units Acres (1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio \1 

Loss Cost

Ratio

NC 2,267 170 29,217 3,596 12.3 1,066 47.0 5,036 1.400 0.172

NT 66 5 928 116 12.5 25 37.9 138 1.183 0.148

RC 823 42 8,466 951 11.2 341 41.4 1,036 1.090 0.122

RT 12 0 67 12 18.6 8 66.7 33 2.608 0.485

Total 3,168 217 38,679 4,676 12.1 1,440 45.5 6,242 1.335 0.161

NC Percent of Total

71.6 78.5 75.5 76.9 74.0 80.7

Transitional Percent 

of Total

2.5 2.3 2.6 2.8 2.3 2.7 

Source: The Contractor’s Underwriting Department after USDA, RMA data.
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51

It is not possible to compare non-organic insurance experience in a manner that corresponds to 

the four codes for written agreements since more than one type of written agreement may have 

been issued in a particular county. Thus, matching non-organic business to the business 

addressed under individual written agreement codes would result in double-counting in some 

cases. Hence, for a comparison of organic and conventional experiences, only the grand total of 

the non-organic business is shown. However, as seen in Table 10, the majority of this activity is 

associated with the NC code. The non-organic business represents the same crops for which at 

least one written agreement to cover organic production was issued in a county for the same crop 

year.

Crops insured under written agreements constituted about one half percent of the units, acres, 

liability, and premium in the same counties where the written agreements were issued. However, 

the organic share of the loss data is about twice as large, about one percent. The percentage of 

units indemnified, the loss ratio, and the loss cost ratio are 2 up to almost 3 times greater for the 

organic practice even though the earned premium rate was 36 percent greater. 82 Since these 

contracts were individually underwritten by RMA Regional Offices, there is no systematic 

underlying structure to the insurance offers that were made under this system. Each office was 

directed to follow a specific process utilizing specified information to develop the parameters of 

the insurance offer. However, a certain amount of judgment was allowed. In addition, applicants 

were required to submit a significant amount of information, a task some producers found 

onerous. This may have discouraged some producers from applying for coverage. This raises the 

question of reliability and comparability of this information with data generated when organic 

acreage became generally insurable as an option. Since these data are much worse than the later 

data, the Contractor recommends it be used for setting premium rates for the organic practice 

with caution. Greater weight should be given to the much more standardized data developed 

beginning in crop year 2005. 

Table 11 demonstrates the magnitude of various variables with respect to the organic practice, 

when considered in conjunction with Table 10. Table 10 contains data regarding transitional and 

certified organic acreage insured during 2001-2005. Table 11 contains the non-organic data for 

the same counties for those years. For example, the organic practice represented 3,168 organic 

units insured compared to 636,164 non-organic units insured, which indicates organic units 

represented only 0.497 percent of the non-organic units insured. 

 

82 The data in the row labeled “Organic Share” represent the absolute percentage share of the variable (such as acres insured) or the relative level 

of a percentage variable such as percent of unit indemnified. A value greater than 100 percent in the latter case indicates that units insured under 

the organic practice were more likely to be involved in a loss situation relative to non-organic units based purely on an assessment of the 

numbers.
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52

T ABLE 11. Non-Organic Crops in Counties in Which a Written Agreement was Issued for Organic Practice, 2001 through 2005 

 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

NonOrganic 636,164 47,637 9,145,122 813,281 8.9 133,717 21.0 562,517 0.692 0.062

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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53

Common Option Code History and Performance 

Use of a common option code for organic acreage is found in the data beginning with the 2004 

crop year. Acreage included under an organic practice increased substantially once it no longer 

was necessary to apply for a written agreement. Even after acknowledging the difference in the 

number of years in each dataset, it still is clear that producers were more likely to insure acreage 

as organic during 2004 through 2008 when there were common option codes on the actuarial 

documents. Under the rules in effect for most of this period, such acreage was required to be 

insured under the organic practice if a certificate was in effect on the acreage and the organic 

practice was followed. The organic share of the acreage tripled, but still remained at less than 

two percent of insured acres for common counties and crops. 

As was the case under written agreements, almost all the insured acreage was certified organic 

acreage; only limited acreage is classified as transitional organic acreage (Table 12). Aggregate 

loss performance of acreage insured under the organic code improved relative to written 

agreements, but only marginally. The percent of units indemnified, the loss ratio, and the loss 

cost ratio continued to be substantially higher than the same measures of performance for 

acreage insured under non-organic practices. This pattern is consistent at the highest level of 

aggregation, but is not statistically significant at that level. Nor is it consistent between crops, by 

county, or temporally, or systemic as experience is aggregated to a lower level. Nonetheless, 

from the perspective of an insurance construct, the losses associated with organic production 

need to be addressed in an appropriate manner. Differences in risk associated with different 

crops need to be addressed as data become available, while the insurance structure should not 

distort participation patterns in ways that result in adverse selection. As additional data become 

available, it should be possible to establish statistically valid yield differentials, differences in 

yield variability, and corresponding differences in T-yields and rates. In the meantime, RMA 

should apply its ratemaking methodology as it normally would when data for a type/practice 

represent only a small share of the total insurance experience for a crop.
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54

T ABLE 12. Organic Acreage Insured Under the OC and OT Common Option Code, 2004 through 2008* 

 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

OC 21,964 1,503 394,824 50,133 12.7 8,480 38.6 55,753 1.112 0.141

OT 2,404 158 54,959 5,253 9.6 826 34.4 6,294 1.198 0.115

Total 24,368 1,661 449,783 55,386 12.3 9,306 38.2 62,047 1.120 0.138

Transitional Percent 

of Total

10.9 10.5 13.9 10.5 9.7 11.3 

* The unique actuarial approach for rice and the resulting insurance experience is described earlier in the report.

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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55

Use of Transitional Yields and Relationship of Actual Yields to Reference Yields

The Contractor analyzed the Type 15 records in the 2008 experience file to determine 1) use of 

transitional yields and 2) the relationship of actual yields certified by the producer to the 

reference yield. This relationship determines the rate that is charged for a particular yield in a 

particular county. First, it was necessary to resolve a discrepancy in the data.

The Contractor’s review of the procedures set forth in Appendix 38 of the Crop Insurance 

Handbook led to the set of rules set forth as follows: 

(1) Whenever a unit or portion thereof is being converted to organic production, two 

databases are established: one to capture actual organic yields on the acreage as long as it 

remains in transitional organic status (Database A) and the second to accrue actual 

organic yields from transitional and certified organic acreage (Database B).83

(2) The initial entries into Database A are appropriate transitional yields (either adjusted or 

unadjusted according to the rules of APH). For most crops, these are the standard Tyields and for rice, the special T-yields established for this crop. 

 

(3) Once production begins on the transitional organic acreage, actual yields are entered into 

this database with a flag of “G” (actual transitional organic yield). “This yield type can be 

combined with up to nine years of any other yield type (except S, SX, A, AY, NA, PA, 

PP, PW) for a minimum of four years” (DAS Type 15 record Exhibits).84

(4) Database B also is populated initially with the appropriate T-yields. The T-yields are 

replaced by the actual transitional organic yields with a flag of “G” until the acreage 

attains the status of organic certified.

Each actual 

year of production thus replaces one of the T-yields included at the initiation of the 

database.

(5) Once the acreage has attained the status of organic certified, the actual organic certified 

yields, identified with a flag of “V,” are entered in the database. As these enter the 

database, the oldest of the four “T” or “G” yields is eliminated. Once four years of “V” 

yields are available, the database builds to ten years. As in the case of a “G” flag, “This 

yield type can be combined with up to nine years of any other yield type (except S, SX, 

A, AY, NA, PA, PP, PW) for a minimum of four years” (DAS Type 15 record 

Exhibits).85 

The Type 15 data do not conform entirely to the data structure as described. Numerous records 

contain a flag of “A,” which is inconsistent with the guidance in the Crop Insurance Handbook 

that conventional actual yields are not entered into an organic database. The Contractor found 

that records with an “A” flag for yields did not contain either “V” or “G” flags. The “A” flags 

were combined with “T” and other flags. When the Contractor examined the records for rice, all 

records that contained one of more “T” flags did contain the organic T-yield from the FCI-35 

specific for that crop. Thus, it appears the records with “A” type yields were edited with the 

requirement: “Can be combined with up to 9 years of any yield type other than S for a minimum 

of 4 years.” In contrast, the records that contained a “V” or “G” were edited with the requirement 

stated earlier in this section. But, the Contractor notes, the Crop Insurance Handbook specifically 

prohibits use of conventional yields in the organic databases. Thus, the “A” type code or any of 

 

83 The terms “Database A” and “Database B” do not appear in the procedures. The nomenclature is adopted in this report for convenience. 84 http://www.rma.usda.gov/data/m13/aprvd2006.html 85 http://www.rma.usda.gov/data/m13/aprvd2006.html
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56

its relatives should not appear in these data. Based on these findings, the Contractor concluded 

that records containing “A” flags really were intended to be “G” or “V” flags.

Rice Type 15 Data 

The rice Type 15 data for the 2008 crop year are considered first for two reasons: 1) it is a 

relatively small dataset and 2) the Contractor’s earlier observations about the potential the 

premium rate could be lower on organic acreage than would be charged for the same yield on 

non-organic acreage.

There were a total of 472 records for rice produced under organic practices in the 2008 crop year 

Type 15 dataset. The distribution of those records by state and by number of actual yields is 

shown in Table 13. California and Texas each accounted for around one-half these organic Type 

15 records. Only about one-third of the records had more than one actual yield. An actual yield 

includes all yield types “A,” “G,” and “V.”

T ABLE 13. Number of Type 15 Records for Rice by State and Number of Actual Yields, 

2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas Grand 

Total Percent

None 53 1 150 204 43 

1 79 35 114 24

2 24 14 38 8

3 14 1 6 21 4

4 16 3 19 4 

5 1 13 1 15 3

6 12 12 3

7 14 1 15 3

8 5 5 1 

9 1 9 1 11 2

10 13 5 18 4

Grand Total 2 252 1 1 216 472

Table 14 shows the ratios of the average actual yield to the reduced reference yield that applies 

to organic practices for rice. Data for Arkansas, Louisiana, and Mississippi provide no 

meaningful information. The reduced reference yield clearly is much lower than the average of 

the actual yields in California regardless of the number of actual yields included in the Type 15 

records. The reduced reference yield is too high in Texas for virtually all cases, but the number 

of observations above two actual yields per record is extremely small. However, where there are 

larger numbers of observations, the ratio of the average actual yield to the organic reference yield 

tends to be larger. This may indicate a difference in short-term results and longer-term 

relationships. 
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57

T ABLE 14. Average Ratio of Actual Yields to Organic Reference Yield for Rice, by State 

and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

None N/A N/A N/A N/A N/A

1 1.53 0.83

2 1.41 1.03

3 1.44 2.56 0.75

4 1.50 0.72 

5 2.60 1.56 0.56

6 1.39

7 1.46 0.75

8 1.31 

9 2.03 1.32 0.84

10 1.55 1.30

Average 2.32 1.45 2.56 0.85

Table 15 reports the average ratio of the average actual yield to the non-organic reference yield. 

The data reveal the same characteristics as does Table 14. However, the table does demonstrate 

the percentage the average actual yield represents of the original reference yield. In California, 

the organic practice tends to be about 25 percent lower than the non-organic practice at most 

numbers of yields per record. Texas, on the other hand, is very variable, with an average yield 

drag of organic to non-organic of around 58 percent. However, the range is large due to the low 

numbers of observations in some instances. 
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58

T ABLE 15. Average Ratio of Actual Yields to Non-Organic Reference Yield for Rice, by 

State and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

None N/A N/A N/A N/A N/A

1 0.76 0.42

2 0.70 0.51

3 0.72 1.28 0.38

4 0.75 0.36 

5 1.30 0.78 0.28

6 0.70

7 0.73 0.37

8 0.66 

9 1.02 0.66 0.42

10 0.78 0.65

Average 1.16 0.72 1.28 0.42

Table 16 simply indicates the average multiplier of the base premium rate assuming an exponent 

of -1.800 in all cases. This is intended merely to demonstrate a range of the multipliers. All yield 

ratios were individually cupped at -0.50 and capped at 1.50 consistent with practice for 

calculating this value.

T ABLE 16. Average Multiplier of Base Premium Rate with Organic Reference Yield for 

Rice, by State and Number of Actual Yields, 2008 Type 15 File 

Number of 

Actual 

Yields

Arkansas California Louisiana Mississippi Texas

1 0.768 1.980

2 0.712 1.356

3 0.694 0.482 2.043

4 0.642 1.901 

5 0.482 0.556 2.810

6 0.685

7 0.702 1.689

8 0.754 

9 0.482 0.680 1.383

10 0.522 0.770

Average 0.482 0.672 0.482 1.741

Table 17 shows the numbers of actual yields by organic practice. Virtually all the data were 

reported as certified organic when the organic flag is included. Differences in the average actual 
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59

yield by practice are not reported due to the scarcity of yields flagged as transitional organic 

practice.

T ABLE 17. Rice: Number of Actual Yields by Organic Practice, 2008 Type 15 File 

Number of 

Actual 

Yields

Certified 

Organic

Transitional 

Organic

0 116 88

1 105 9

2 35 3 

3 21 

4 19

5 13 2

6 12 

7 15 

8 5

9 11

10 17 1 

Conclusions Regarding Rice 

The data indicate the across the board adjustment to the rice reference yields and transitional 

yields for organic practice was inappropriate. It appears California reference yields were reduced 

more than appropriate and Texas reference yields may not have been reduced enough. However, 

the data for Texas are less conclusive than the data for California, since so few units reported 

more than one or two actual yields when any actual yields were reported. The status for 

Arkansas, Louisiana, and Mississippi cannot be determined due to the lack of data. The 

adjustments to the T-yields were affected similarly. In some cases, the reference yield and the Tyield are not identical; however, in all cases the Contractor examined, the differences were not 

large. Hence, the inference from the comparisons of the ratios of the average actual yield to the 

reference yield that they apply to transitional yields as well. 

All Crops Results

Table 18 reports the number of Type 15 records in the 2008 dataset along with certain 

characteristics of those records for each crop for which an organic practice was reported and that 

are either Type B or Type C crops for the purposes of Actual Production History. About onethird of all records consisted exclusively of T-yields, a value that is relatively constant for corn, 

soybeans, and wheat. Several other crops also had about one-third of all records composed only 

of t-yields. There is a wide variation in use of T-yields among the remaining crops. 
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T ABLE 18. Use of Actual Yields and Ratio of Average Actual Yield to Reference Yield, All 

Crops and States

Crop Total 

Records

Records with no Actual 

Yield

Percent No Actual 

Yield

Total Actual 

Yields

Average per Record 

1/

Ratio Actual Yield to Reference 

Yield

11 5,507 1,835 33 15,450 4.2 0.63

12 18 9 50 42 4.7 0.57

13 31 13 42 28 1.6 0.39

15 27 17 63 21 2.1 0.45

16 974 320 33 2,305 3.5 0.71

17 342 120 35 712 3.2 0.59

18 472 204 43 900 3.4 0.90

21 185 94 51 565 6.2 1.11

22 7 0 0 16 2.3 0.89

28 70 10 14 323 5.4 0.71

29 29 5 17 150 6.3 1.17

31 688 101 15 2,100 3.6 0.66

33 130 42 32 428 4.9 0.67

34 2 0 0 9 4.5 0.31

36 24 3 13 127 6.0 1.04

39 2 2 100 0 0.0 0.00

41 3,319 1,252 38 8,104 3.9 0.65

42 110 31 28 188 2.4 0.44

43 69 45 65 76 3.2 0.47

46 18 5 28 44 3.4 0.45

47 847 438 52 1,202 2.9 0.57

49 73 28 38 102 2.3 0.37

51 178 83 47 357 3.8 0.40

52 65 9 14 271 4.8 1.18

53 274 39 14 1,476 6.3 1.05

54 600 143 24 1,800 3.9 0.87

55 3 1 33 10 5.0 1.41

58 9 2 22 40 5.7 0.38

60 18 3 17 85 5.7 1.55

64 85 23 27 97 1.6 0.43

67 528 130 25 905 2.3 0.38

69 3 2 67 1 1.0 0.42

75 150 114 76 94 2.6 0.47

78 565 277 49 798 2.8 0.45

81 3,074 984 32 8,789 4.2 0.67

84 172 47 27 348 2.8 0.54

87 117 13 11 574 5.5 0.94

89 150 34 23 664 5.7 0.78

91 987 328 33 1,975 3.0 0.64

92 45 8 18 232 6.3 1.02

94 69 11 16 187 3.2 0.79

107 1 0 0 1 1.0 0.06

218 18 5 28 70 5.4 1.08

219 4 0 0 29 7.3 0.92

220 65 24 37 244 6.0 0.78

221 7 0 0 33 4.7 1.00

222 1 0 0 1 1.0 0.71

223 83 10 12 453 6.2 0.91

229 43 35 81 10 1.3 0.28

231 2 0 0 2 1.0 0.95

234 1 1 100 0 0.0 0.00

235 1 1 100 0 0.0 0.00

256 1 0 0 6 6.0 0.86

Total 20,263 6,901 34 52,444 3.9 0.68

1/ Average for all records containing at least one actual yield.

When actual yields were reported, the typical record contained nearly four actual yields, 

indicating insurance typically is based on a relatively long history of organic practice. An 

interesting comparison is the ratio of the average of the actual yields certified to the reference 

yield, the value of which is about two-thirds. All the major crops – corn, soybeans, and wheat – 

that collectively account for a large share of the organic acreage also have an average actual 
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61

yield that is about two-thirds of the reference yield. These three crops also had about four 

certified yields on average for each unit with actual certified yields. Thus, it would appear that 

the reference yields, on average, tend to exceed the production potential of acreage used for 

organic production by about 50 percent (reference yield should be reduced by one-third on 

average).

Differences among states exist. Tables 19, 20, and 21 report data by state for wheat, corn, and 

soybeans, respectively. The variable of greatest interest is the ratio of certified actual yields to 

the reference yield, a value that shows variation among states. This difference in some cases is 

based on few observations. But, it is difficult to make generalizations among states on the basis 

of these data. Are differences in the ratio due to differences in the average yield on organic acres 

or to differences in the basis of the reference yield? Since the Contractor must accept the 

reference yield as a given, it appears the potential yield on organic acres is not consistent among 

states, a characteristic that also was evident with the rice data considered earlier.

T ABLE 19. Wheat: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records with 

No Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average 

per Record 

1/ 

Ratio Actual 

Yield to 

Reference Yield

06 29 16 55 31 2.4 0.50

08 515 211 41 1,335 4.4 0.83

16 59 15 25 187 4.3 0.63

17 32 5 16 112 4.1 0.98

19 9 2 22 10 1.4 1.08

20 273 76 28 1,104 5.6 0.77

26 192 89 46 173 1.7 0.71

27 493 252 51 629 2.6 0.49

30 1,616 413 26 4,730 3.9 0.61

31 352 126 36 1,107 4.9 0.83

34 1 1 100 0 0.0 0.00

36 3 0 0 21 7.0 1.07

38 930 243 26 2,987 4.3 0.67

39 15 7 47 35 4.4 0.45

40 51 14 27 116 3.1 0.84

41 16 14 88 2 1.0 0.14

46 230 67 29 840 5.2 0.62

48 90 36 40 219 4.1 0.63

49 219 110 50 496 4.6 0.47

53 27 13 48 25 1.8 0.30

55 57 36 63 36 1.7 0.50

56 298 89 30 1,255 6.0 0.81

Grand Total 5,507 1,835 33 15,450 4.2 0.63

1/ Average for all records containing at least one actual yield.
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62

T ABLE 20. Corn: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records with 

No Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average per 

Record 1/ 

Ratio Actual 

Yield to 

Reference Yield

06 1 0 0 2 2.0 1.26 

08 20 6 30 29 2.1 0.54

09 2 2 100 0 0.0 0.00

16 8 3 38 7 1.4 0.50

17 122 42 34 318 4.0 0.61 

18 10 4 40 20 3.3 0.54

19 609 155 25 2,167 4.8 0.81

20 81 19 23 312 5.0 0.73

23 17 2 12 38 2.5 0.65 

24 7 4 57 3 1.0 0.99

26 393 183 47 639 3.0 0.68

27 619 260 42 1,316 3.7 0.72

29 40 6 15 101 3.0 0.70 

31 341 152 45 716 3.8 0.68

33 1 1 100 0 0.0 0.00

34 3 0 0 5 1.7 0.54

36 55 15 27 163 4.1 0.58 

37 11 3 27 14 1.8 0.48

38 125 56 45 156 2.3 0.59

39 65 19 29 131 2.8 0.51

41 2 1 50 2 2.0 0.52 

42 35 16 46 104 5.5 0.34

46 107 28 26 474 6.0 0.51

48 14 11 79 7 2.3 0.19

50 29 15 52 57 4.1 0.55 

51 29 6 21 100 4.3 0.88

53 9 4 44 7 1.4 0.77

55 533 218 41 1,204 3.8 0.67

56 31 21 68 12 1.2 0.22 

Grand Total 3,319 1,252 38 8,104 3.9 0.65

1/ Average for all records containing at least one actual yield.
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63

T ABLE 21. Soybeans: Use of Actual Yields and Ratio of Average Actual Yield to Reference 

Yield, by State 

State Total 

Records

Records 

with No 

Actual 

Yield

Percent No 

Actual Yield

Total 

Actual 

Yields

Average per 

Record 1/ 

Ratio Actual 

Yield to 

Reference Yield

13 2 1 50 2 2.0 1.40 

17 131 32 24 498 5.0 0.74 

18 8 3 38 17 3.4 0.37 

19 621 174 28 2,137 4.8 0.76 

20 70 21 30 174 3.6 0.61 

24 7 5 71 3 1.5 1.03 

26 456 190 42 999 3.8 0.60 

27 744 201 27 2,109 3.9 0.63 

29 82 6 7 408 5.4 0.82 

31 252 108 43 550 3.8 0.75 

34 2 0 0 3 1.5 0.44 

36 30 8 27 111 5.0 0.56 

37 11 0 0 15 1.4 0.88 

38 120 49 41 196 2.8 0.47 

39 56 9 16 183 3.9 0.75 

42 6 1 17 17 3.4 0.65 

46 115 32 28 459 5.5 0.66 

48 5 4 80 2 2.0 0.25 

51 15 3 20 66 5.5 0.78 

55 341 137 40 840 4.1 0.53 

Grand Total 3,074 984 32 8,789 4.2 0.67 

1/ Average for all records containing at least one actual yield.

Additional disaggregation of data by state is not included in this report; however, the data on 

which Tables 18 through 21 are based is included in Appendix D. The general indications 

provided in Tables 18 through 21 are similar for all crops and states that have a reasonable 

amount of data. 

Organic Acreage Under Common Option Code Relative to Non-Organic Acreage of the 

Same Crops in the Same Counties

Units insured with a common option code for organic practice represented only about 1.5 percent 

of the total units, acres, liability, and premium of the same crops in the same counties (Table 22). 

The aggregate indemnities, however, were nearly three percent of the total for these crops and 

counties. The earned premium rate for acreage insured with an organic code was about 27 

percent greater than for the same crops in the same counties. In spite of this higher premium rate, 

both the loss ratio and the loss cost ratio were substantially higher in the aggregate than for 
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64

acreage insured without an organic common option code. While this pattern is consistent at the 

highest level of aggregation, it is not statistically significant at that level. Differences in risk 

associated with different crops need to be addressed as data become available and the insurance 

structure should not distort participation patterns in any way that can result in adverse selection. 

As additional data become available, it should be possible to establish statistically valid yield 

differentials, differences in yield variability, and corresponding differences in T-yields and rates.

In the meantime, RMA should apply its ratemaking methodology as it normally would when data 

for a type/practice represent only a small share of the total insurance experience for a crop. 

As will be demonstrated later, there are major differences among crops and states with regard to 

the performance of organic acreage relative to non-organic acreage. Tables 12 and 22 are to be 

interpreted in the same manner as Tables 10 and 11. 
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65

T ABLE 22. Non-Organic Acreage of Same Crops Insured in Counties with a 

Common Option Code for Organic Practice, 2004 through 2008 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

NonOrganic 1,497,444 113,694 34,590,732 3,348,387 9.7 343,418 22.9 2,280,253 0.681 0.066

Source: The Contractor’s Underwriting Department using USDA, RMA data.
Organic Crops: Revised Written Rating Report 

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restrictions on the title page of this report.

66

Significance of Counties with an Organic Code, 2004 through 2008 

The contract requires comparisons of organic and non-organic insurance performance in the 

same counties. However, this raises the question: “How representative are counties with organic 

coverage relative to all counties in which insurance was written during these years?” Counties in 

which at least 1 unit with organic coverage was reported during 2004 through 2008 represented 

slightly more than 10 percent of units and acres, and about 13 percent of premium and liability 

for all eligible insurance plans in the United States during those years (Table 23).86 Interestingly, 

the earned premium rate, the loss ratio, and the loss cost ratio for the counties with at least one 

unit insured with organic practice was lower than the U.S. average for all additional coverage. 

These data may indicate that organic practice was more prevalent in counties with relatively 

lower premium rates than the national average. As will be shown later, the dominance of 

California with regard to liability and premiums likely biases the earned premium rate. But, 

when examined solely within the counties with an organically insured practice, the organic 

practice in the aggregate had higher than average premium rates and worse than average loss 

experience.

 

86 Insurance plan codes such as GRP and GRIP for which organic codes are not offered are excluded from the All U.S. data. These plan codes 

automatically would not have been included in the county/crop combinations with an organic practice code.
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67

T ABLE 23. Experience in Counties with Organic Practice Versus all Additional Coverage 

in the United States, 2004 through 2008 

Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium

Rate (%)

Units 

Indemnified

Units 

Indemnified (%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

With Organic 

Code 1/ 1,521,812 115,355 35,040,514 3,403,773 9.7 352,724 23.2 2,342,300 0.688 0.067

All U.S. 2/ 14,695,151 1,062,958 265,839,212 26,826,649 10.1 3,356,644 22.8 19,677,272 0.733 0.074

Percent Organic 10.4 10.9 13.2 12.7 95.9 10.5 100.4 11.9 NA NA

Source: The Contractor’s Underwriting Department using USDA, RMA data.

1/ With organic code = at least one unit was insured in a county using an organic code during 2004 through 2008

2/ All U.S. indicates all counties in the United States but excluding insurance plans without organic option codes.
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68

At least 1 unit with an organic code was reported in each of 670 counties during the 2004 

through 2008 time period. The average number of units with an organic code per county for the 

entire time period was 36.5 and the median was 11 units. On an annualized basis, the numbers 

are considerably smaller. In comparison, there was an average of 949 units without an organic 

code per county during these years. 

The Contractor examined the data on a county basis by calculating the net underwriting gain 

(loss) of acreage insured under an organic code and compared the percentage gain (loss) to 

acreage of the same crops insured without the organic code in the same county.87 Table 24 shows 

the 15 counties with the greatest underwriting gain and the 15 with the greatest underwriting 

loss. Acreage with an organic code performed better in the aggregate in the counties with 

underwriting gains than did acreage of the same crops in the same counties produced 

conventionally. Conversely, in the counties with underwriting losses on acreage with an organic 

code, performance was worse than the performance for crops produced conventionally. Six of 

the best performing counties are in California, but so are four of the worst performing counties. 

Eight of the 15 best performing counties had 10,000 acres or more insured under organic codes 

during this period whereas only 3 of the worst performing counties had this much acreage. This 

may indicate that greater acreage insured under the organic code led to more favorable insurance 

experience. There is no other pattern evident in these data. The complete experience data for 

each state/county combination is included in Appendix E in alphabetical order. A table similar to 

Table 24 also is included for all state/county combinations.

 

87 Gain (loss) is the difference of the total premium and total indemnity.
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69

T ABLE 24. Top 15 Counties with Net Underwriting Gain and Top 15 Counties with Net 

Underwriting Loss, 2004 through 2008 

State County

With Organic Codes Without Organic Codes

Number of AcresGain (Loss)LiabilityPercent of LiabilityNumber of AcresGain (Loss) Liability Percent of Liability

Washington Douglas 5 840 13,572 6.2 192 2,536 84,297 3.0

Washington Yakima 9 699 17,814 3.9 338 6,918 518,346 1.3

Arizona Graham 3 645 6,314 10.2 0 83 546 15.3

California Napa 3 573 10,402 5.5 93 11,702 306,412 3.8

Washington Grant 27 497 24,777 2.0 440 11,826 472,082 2.5

Michigan Shiawassee 29 423 7,788 5.4 304 4,921 85,178 5.8

Wyoming Laramie 42 421 3,250 12.9 302 1,416 26,352 5.4

California Madera 13 381 11,015 3.5 342 11,424 303,743 3.8

California Kings 7 364 9,576 3.8 177 2,805 55,419 5.1

California Kern 10 333 12,609 2.6 520 22,634 660,263 3.4

California Ventura 3 311 5,593 5.6 137 8,335 270,372 3.1

Washington Benton 20 296 15,301 1.9 279 8,614 271,456 3.2

Colorado Arapahoe 31 288 1,599 18.0 59 8 4,681 0.2

Colorado Lincoln 30 257 1,640 15.6 134 (365) 13,934 -2.6

California Mendocino 6 253 6,499 3.9 24 1,373 33,198 4.1

Total / Average 237 6,582 147,749 4.5 3,342 94,230 3,106,278 3.0

North Dakota Dunn 9 (218) 748 -29.2 716 (20,122) 81,029 -24.8

Nebraska Rock 3 (219) 1,459 -15.0 17 309 8,098 3.8

Montana Roosevelt 31 (235) 2,296 -10.2 1,180 399 85,348 0.5

Wisconsin Chippewa 3 (244) 727 -33.5 302 (2,364) 86,360 -2.7

Wisconsin Jackson 5 (247) 1,331 -18.5 101 1,307 32,960 4.0

California Sonoma 4 (248) 3,167 -7.8 151 14,286 370,338 3.9

Iowa Winneshiek 8 (251) 2,031 -12.4 626 5,061 219,462 2.3

Utah Box Elder 41 (255) 2,774 -9.2 159 (137) 17,547 -0.8

Wisconsin Dunn 3 (295) 795 -37.1 316 (2,448) 84,004 -2.9

California Merced 3 (325) 3,628 -8.9 291 15,316 480,371 3.2

Texas Matagorda 2 (331) 799 -41.4 5 (12) 1,632 -0.7

California Butte 4 (465) 3,164 -14.7 206 2,363 153,826 1.5

Minnesota Freeborn 5 (486) 1,556 -31.2 866 17,922 329,145 5.4

California Fresno 27 (685) 23,727 -2.9 1,586 38,878 1,218,801 3.2

Colorado Alamosa 6 (759) 4,494 -16.9 80 581 67,504 0.9

Total / Average 154 (5,263) 52,698 -10.0 6,603 71,339 3,236,424 2.2

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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70

Principal Crops with Organic Common Option Organic Code, 2004 through 2008 

The principal crops insured with the organic option code during 2004 through 2008 were not 

specialty crops as some might suspect. Instead, wheat, corn, and soybeans occupied the top three 

positions in terms of acres, liability, and premium. These three crops represented about twothirds of all activity with regard to organic insurance. The remaining one-third of activity with 

regard to organic insurance represented 78 crop codes. 

The prominence of the top three crops perhaps can be explained by their importance in the 

standard diet. Organic wheat flour most likely is used to produce organic bakery products either 

commercially or at home. Organic corn flour would occupy a similar position for use in organic 

ethnic products (such as Mexican) and also for home use. Similarly, organic soybeans would be 

used to produce oil for commercial production of fried organic foods and for home use. Organic 

corn and soybean meal would be fed to animals raised organically. These applications represent 

a large volume of use for the three crops, and even a tiny share of the total market by organic 

uses would be a larger volume than can be attained by other crops. 

The top ten crops insured with an organic code are shown in Table 25. Table 26 contains the 

insurance experience for the same crops in the same counties that were insured without the 

organic common option code. Data for all 81 crops is included in Appendix F. 
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71

T ABLE 25. Insurance Experience for Principal Crops Insured with Organic Common Option Codes, 2004 through 2008 

Crop Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%) 

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

Wheat 6,028 655 57,700 14,455 25.1 2,224 36.9 14,006 0.969 0.243

Corn 4,274 236 71,165 9,450 13.3 1,897 44.4 12,914 1.367 0.181

Soybeans 3,976 235 42,834 6,788 15.8 2,058 51.8 12,042 1.774 0.281

Apples 1,137 35 79,141 6,168 7.8 232 20.4 2,991 0.485 0.038

Grapes 715 26 30,793 1,853 6.0 57 8.0 542 0.293 0.018

Tomatoes 197 18 23,752 1,414 6.0 22 11.2 849 0.600 0.036

Almonds 199 10 14,419 1,377 9.6 63 31.7 1,362 0.989 0.094

Flax 871 59 4,622 1,081 23.4 528 60.6 1,784 1.650 0.386

Potatoes 231 10 9,757 970 9.9 82 35.5 1,292 1.333 0.132

Barley 706 51 4,274 909 21.3 333 47.2 827 0.910 0.194

Top Ten 18,334 1,335 338,457 44,465 13.1 7,496 40.9 48,610 1.093 0.144

All other crops 6,549 384 136,431 12,455 9.1 1,851 28.3 14,617 1.174 0.107

* Totals derived by adding whole dollar values and then rounding

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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72

T ABLE 26. Insurance Experience for Same Crops Insured Without Organic Common Option Codes, 2004 through 2008 

Crop Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned Premium 

Rate (%)

Units 

Indemnified

Units Indemnified 

(%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

Wheat 392,323 38,069 4,354,668 732,403 16.8 100,820 25.7 547,782 0.748 0.126

Corn 527,854 37,726 14,466,069 1,266,692 8.8 104,654 19.8 698,958 0.552 0.048

Soybeans 506,380 34,184 8,079,585 795,669 9.8 132,132 26.1 678,795 0.853 0.084

Apples 10,928 627 1,285,670 62,447 4.9 1,152 10.5 49,767 0.797 0.039

Grapes 27,489 1,358 1,516,957 82,517 5.4 1,606 5.8 20,066 0.243 0.013

Tomatoes 4,923 467 478,623 22,074 4.6 309 6.3 8,708 0.395 0.018

Almonds 12,755 939 1,508,695 89,012 5.9 1,532 12.0 29,742 0.334 0.020

Flax 6,239 454 34,813 5,082 14.6 2,194 35.2 6,607 1.300 0.190

Potatoes 3,129 383 380,135 28,435 7.5 650 20.8 16,089 0.566 0.042

Barley 16,413 2,050 158,375 21,844 13.8 5,275 32.1 23,298 1.067 0.147

Top Ten 1,508,433 116,257 32,263,591 3,106,175 9.6 350,324 23.2 2,079,812 0.670 0.064

All other crops 176,385 21,270 5,193,119 443,424 8.5 42,206 23.9 397,687 0.897 0.077

* Totals derived by adding whole dollar values and then rounding 

Source: The Contractor’s Underwriting Department using USDA, RMA data.
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73

Net indemnities (premium minus indemnity) for the insured organic production were negative 

$6.3 million for these years. Corn and soybeans had net indemnities of negative $8.7 million. 

Grapes and apples accounted for $4.5 million of the gains. The total of the negative net 

indemnities was $13.8 million, while the crops with positive net indemnities produced a surplus 

of $7.8 million. Thirty-two of the 81 crops had negative net indemnities, leaving 49 with positive 

net indemnities (see Appendix F, Table F1). This reinforces the earlier indications of any lack of 

consistency in the data. 

The top ten organically insured crops with gains and the top ten with losses are shown in Table 

27. The amount of the gain (loss) and its percent of liability are also shown along with the same 

data for acreage insured without the organic code. Of the crops with gains on the organic 

acreage, only oats had negative net indemnities on acreage insured without the organic codes. 

For eight of the ten crops, the percentage gain relative to the liability exceeded the comparable 

percentage gain on the acreage without an organic code.

Five of the ten crops with the largest net losses for organic codes also had negative net 

indemnities for the acreage insured without the organic codes. With the exception of prunes, the 

percentage loss on the acreage insured with an organic code exceeded the percentage loss on 

acreage insured without the organic codes. In a number of cases, the percentage loss on the 

acreage insured with an organic code was much greater than the percentage loss on acreage 

insured without the organic codes. Data for all crops are included in Appendix G. 
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T ABLE 27. Top Ten Organic Crops with Net Underwriting Gain and Top Ten Crops with 

Net Underwriting Loss, 2004 through 2008 

Crop

With Organic Code Without Organic Code

Gain (Loss)LiabilityPercent of LiabilityGain (Loss) Liability Percent of Liability

Apples 3,177 79,141 4.01 12,680 1,285,670 0.99

Grapes 1,311 30,793 4.26 62,452 1,516,957 4.12

Tomatoes 565 23,752 2.38 13,365 478,623 2.79

Wheat 449 57,700 0.78 184,620 4,354,668 4.24

Raisins 353 5,712 6.17 17,347 288,569 6.01

Avocados 337 4,699 7.17 11,397 202,382 5.63

Pears 154 5,076 3.04 3,469 125,226 2.77

Oats 153 2,680 5.72 (613) 19,045 -3.22

Plums 147 1,939 7.57 1,819 48,480 3.75

Fresh Nectarines 93 1,853 5.03 3,295 75,085 4.39

Cotton Ex Long Staple (228) 510 -44.69 (547) 67,071 -0.82

Valencia Oranges (297) 3,671 -8.10 (317) 94,924 -0.33

Sweet Corn (303) 5,014 -6.04 1,053 35,439 2.97

Potatoes (323) 9,757 -3.31 12,346 380,135 3.25

Prunes (469) 5,596 -8.39 (18,711) 137,167 -13.64

Rice (589) 4,386 -13.43 795 129,108 0.62

Flax (702) 4,622 -15.20 (1,524) 34,813 -4.38

Navel Oranges (703) 6,247 -11.25 (4,043) 554,061 -0.73

Corn (3,464) 71,165 -4.87 567,735 14,466,069 3.92

Soybeans (5,254) 42,834 -12.27 116,874 8,079,585 1.45

Source: The Contractor’s Underwriting Department using USDA, RMA data.

Principal States with Common Option Organic Code, 2004 through 2008 

Acreage with the organic common option code was reported in 39 states during 2004 through 

2008 (Appendix H). The location of organically insured acreage corresponds to the major 

production locations for the principal crops insured under organic codes (Table 28). Montana, 

Minnesota, and North Dakota were the top 3 states with organically insured acreage, accounting 

for slightly less than 40 percent of all acres insured under organic codes but only about 16 

percent of the liability. This reflects the relatively low value per acre of wheat in particular and 

the major commodity crops in general. California and Colorado were the only other states to 

report more than 100,000 acres for organic insurance coverage during 2004 through 2008. In 

terms of the insured liability, California was far and away the leader with nearly 30 percent of 

the total. Washington occupied second place, with about 20 percent of the total liability. 

With the exception of Washington, the loss ratio for acreage insured under the organic code in 

the top ten states exceeded the loss ratio for acreage without the organic code. Among all 39 

states, the loss ratio on organic acreage was lower in 10 of the states, most of which had very 

small acreage under the organic code (Appendix H, Table H1). Among the 39 states, the organic 
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75

loss ratio was more than double the non-organic in 11 states. However, once the comparisons are 

beyond the top ten states in terms of acres, the thinness of the data become even more evident. 
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T ABLE 28. Top Ten States with Acreage Insured Under Organic Common Option Codes, 2004 through 2008 

State Organic Net 

Acres

Non-Organic 

Net Acres

Organic 

Liability

Non-Organic 

Liability

Organic 

Premium

Non-Organic 

Premium

Organic 

Indemnity

Non-Organic 

Indemnity

Organic 

Loss Ratio

NonOrganic 

Loss Ratio

Organic:NonOrganic Ratio

Montana 238,347 16,781,863 19,193 1,534,302 4,396 256,856 5,171 199,886 1.176 0.778 1.511

Minnesota 203,677 25,496,953 37,922 7,023,349 5,993 718,043 9,018 455,235 1.505 0.634 2.373

North Dakota 179,984 14,140,803 17,235 1,985,784 4,236 331,136 5,622 281,443 1.327 0.850 1.562

Colorado 132,099 2,389,744 17,426 399,402 4,770 63,002 4,722 57,001 0.990 0.905 1.094

California 127,698 5,713,354 129,449 6,072,665 9,872 364,466 9,533 191,265 0.966 0.525 1.840

Nebraska 96,998 9,960,420 19,118 2,706,171 2,697 264,835 2,603 130,940 0.965 0.494 1.952

Utah 95,179 306,351 4,522 23,279 1,153 3,752 1,410 3,943 1.223 1.051 1.164

Iowa 84,830 19,308,444 23,858 7,050,279 2,457 520,938 4,286 336,274 1.745 0.646 2.703

Washington 76,891 1,787,562 95,172 1,883,006 5,967 93,890 3,031 66,839 0.508 0.712 0.713

Michigan 62,981 1,916,713 14,672 465,555 2,652 52,796 2,524 38,415 0.952 0.728 1.308

Top Ten 1,298,683 97,802,206 378,567 29,143,793 44,193 2,669,714 47,920 1,761,239 1.084 0.660 1.644

All Other States 365,978 28,338,792 82,162 7,832,212 11,766 855,618 14,210 700,855 1.208 0.819 1.474

Source: The Contractor’s Underwriting Department using USDA, RMA data.
Organic Crops: Revised Written Rating Report 

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77

Table 29 shows the top ten states in terms of underwriting gain and the worst ten in terms of 

underwriting loss. With the exception of Arizona, Florida, and Oklahoma, the percentage rate of 

gain on acreage with an organic code is far smaller than the rate of gain for the same county/crop 

combinations without the organic code. The percentage rate of loss on organic acreage in the 

worst performing states is far higher than the rate of loss for the same county/crop combinations 

without the organic code in the states with underwriting losses.

T ABLE 29. Top Ten States with Net Underwriting Gain and Top Ten States with Net 

Underwriting Loss, 2004 through 2008 

State

With Organic Code Without Organic Code

Gain (Loss)LiabilityPercent of LiabilityGain (Loss) Liability Percent of Liability

Washington 2,936 95,172 3.1 27,051 1,883,006 1.4

Arizona 637 6,347 10.0 74 14,304 0.5

Wyoming 352 4,411 8.0 1,497 54,123 2.8

California 337 139,192 0.2 173,200 6,368,692 2.7

Florida 155 6,406 2.4 (2,852) 320,854 -0.9

Michigan 128 14,672 0.9 14,381 465,555 3.1

Nebraska 93 19,118 0.5 133,895 2,706,171 4.9

Hawaii 59 4,704 1.3 372 174,407 0.2

Colorado 49 17,426 0.3 6,002 399,402 1.5

Oklahoma 32 551 5.7 (2,154) 18,647 -11.5

Missouri (157) 1,791 -8.8 4,626 169,724 2.7

South Dakota (192) 5,821 -3.3 54,312 1,063,111 5.1

Ohio (250) 1,918 -13.0 (650) 415,221 -0.2

Utah (258) 4,522 -5.7 (191) 23,279 -0.8

Texas (831) 15,676 -5.3 (4,190) 958,716 -0.4

Montana (774) 19,193 -4.0 56,970 1,534,302 3.7

North Dakota (1,387) 17,235 -8.0 49,693 1,985,784 2.5

Iowa (1,830) 23,858 -7.7 184,664 7,050,279 2.6

Wisconsin (1,993) 12,304 -16.2 5,050 1,263,387 0.4

Minnesota (3,024) 37,922 -8.0 262,808 7,023,349 3.7

Source: The Contractor’s Underwriting Department using USDA, RMA data.

Influence of Coverage Level

The Contractor attempted to determine if differences in the coverage level had any influence on

the performance of acreage insured with an organic code relative to acreage insured without the 

organic code. Table 30 provides the percentage distribution of business by coverage level 

percentage for acreage with and without an organic code as well as the loss ratio for each 

coverage level. Generally, acreage with an organic code had a greater proportion of the premium 

at coverage levels between 50 to 60 percent. Acreage with organic codes had 21 percent of the 

premium in this range whereas acreage without an organic code had 12 percent. With the 

exception of the 55 percent and 60 percent coverage levels, loss ratios by coverage level are 
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78

consistently higher for the acreage with an organic code. Weighted loss ratios by coverage level 

are consistently higher for the acreage with an organic code, although the significance of some of 

the differences is questionable considering sample size for some of the coverage level categories.

T ABLE 30. Contribution of Coverage Level to Realized Loss Ratios for Acreage with and 

without an Organic Code

Coverage 

Level (%)

Organic Code Non-Organic Code 

Share of 

Premium 

(%)

 Loss Ratio Weighted 

Loss Ratio 

Share of 

Premium 

(%)

 Loss Ratio Weighted 

Loss Ratio 

50 12.6 0.585 0.073 8.2 0.444 0.037 

55 2.3 0.329 0.007 0.1 0.522 0.000 

60 5.9 0.722 0.043 3.8 0.873 0.033 

65 16.2 1.294 0.209 14.2 0.789 0.112

70 23.1 1.293 0.299 33.3 0.722 0.240 

75 32.2 1.115 0.359 31.0 0.695 0.216 

80 4.9 1.517 0.074 7.3 0.527 0.038 

85 2.9 1.552 0.045 2.1 1.038 0.022

Total 100.0 1.110 100.0 0.698 

Source: The Contractor’s Underwriting Department using USDA, RMA data.

Although superficially it appears differences in choices of coverage level most likely had no 

bearing on the performance between practices, the Contractor attempted to develop a more 

robust test. At the aggregate level, the Contractor interchanged the loss ratios (i.e., the actual loss 

ratios for coverage levels with organic code were assigned to coverage levels without the organic 

codes and vice-versa). This comparison does not account for differences in coverage levels 

among counties or crops, but is intended only as an approximation to performance that might 

have been observed if the units with organic code experienced, in the aggregate, had the same 

loss ratios as did the units with non-organic codes at the same coverage level. Results are shown 

in Table 31. The aggregate loss ratio for acreage with the organic code would have been the 

same as was actually observed for units without the organic codes. Conversely, the loss ratio 

would have increased for the acreage without the organic codes when the loss ratios by coverage 

level for organic acreage are used.
Organic Crops: Revised Written Rating Report 

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contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

79

T ABLE 31. Contribution of Coverage Level to Realized Loss Ratios for Acreage with and 

without an Organic Code with Loss Ratios Interchanged

Coverage 

Level (%)

Organic Code Non-Organic Code 

Share of 

Premium 

(%)

 Loss Ratio Weighted 

Loss Ratio 

Share of 

Premium 

(%)

 Loss Ratio Weighted 

Loss Ratio 

50 12.6 0.444 0.056 8.2 0.585 0.048 

55 2.3 0.522 0.012 0.1 0.329 0.000 

60 5.9 0.873 0.052 3.8 0.722 0.027

65 16.2 0.789 0.128 14.2 1.294 0.184 

70 23.1 0.722 0.167 33.3 1.293 0.430 

75 32.2 0.695 0.224 31.0 1.115 0.346 

80 4.9 0.527 0.026 7.3 1.517 0.111

85 2.9 1.038 0.030 2.1 1.552 0.032 

Total 100.0 0.693 100.0 1.179 

Source: The Contractor’s Underwriting Department using USDA, RMA data.

The Contractor concludes that any differences in distribution of business among coverage levels 

were not important in explaining the differences in the aggregate loss ratios between the two 

categories of acreage. The acreage insured with the organic codes performed worse (had higher 

losses) overall.

The preceding analysis shows some challenges in analyzing the insurance experience data to 

“either confirm or refute the existence of significant, consistent, and systemic variations in loss 

history exist between organic and conventional commodities, either collectively or on an 

individual crop basis.” In most cases, where patterns might have been thought to exist, it was 

also possible to identify exceptions to those patterns. With the limited data available, artifacts of 

aggregation and de facto sampling errors have the potential to lead to potentially dangerous 

generalizations. It is also challenging to examine tabular data at a range of scales that reveals 

patterns pertinent to the objective of confirming or refuting significant, consistent, and systemic 

variations in loss history between organic and conventional production. The Contractor therefore 

explored the potential of alternative approaches to expose patterns that may have not been 

evident in the preceding quantitative insurance performance analysis. 

The Contractor initially calculated the loss ratios by crop from data for the counties where 

organic production for the crop was insured, using aggregate indemnities and premiums in those 

counties for the years when organic production was reported during the period from 2001 

through 2008. For 15 crop codes for a variety of specialty crops, the loss ratios were 0 for both 

the conventional and the organic insurance (Table 32). The Crop Provisions for many of these 

crops define specific causes of loss such as wind, excess precipitation, freezes or other events 

that seemingly are independent of the decision to follow organic practices. Unless organic 

practices result in a tree that is weaker than a tree resulting from non-organic practices, it is 

difficult to justify a load on the premium rate for losses due to wind, excess precipitation, freeze, 

and similar perils.
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

80

T ABLE 32. Crops with No Reported Indemnities (for either Conventional or Organic 

Production) in Counties with Insured Organic Production between 2001 and 2008

Crops Codes

Citrus

Citrus II (FL) 246

Citrus III (FL) 247 

Orlando Tangelos 

(AZ/CA) 237

Citrus trees

Citrus Trees I (TX) 240 

Citrus Trees IV (TX) 243 

Citrus Trees V (TX) 244

Grapefruit Trees (FL) 208

Orange Trees (FL) 207 

All Other Citrus Trees 

(FL) 211

Processing Freestone 

Peaches 222

Strawberries 110 

Tobacco

Burley Tobacco 231

Cigar Filler Tobacco 234

Cigar Binder Tobacco 235 

Vegetable crops 256

Source: The Contractor’s Underwriting Department using USDA, RMA data.

 

There were also data reported under 14 crop codes with loss ratios for conventional production 

greater than the loss ratios for the crop produced under organic practices (Table 33). Several of

the crops produced organically had no indemnities during these years (i.e., a loss ratio of zero). 
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

81

T ABLE 33. Crops with Aggregate Loss Ratios for Insured Conventional Production Greater 

than for Insured Organic Production between 2001 and 2008 in Counties with Insured 

Organic Production

Crop

Conventional 

Loss

Ratio

Organic 

Loss 

Ratio

Citrus IV 2.44 0.00

Citrus I 1.65 0.00

Peppers 0.64 0.00

Processing Cling Peaches 0.17 0.00 

Sugarcane 0.11 0.00

Mineola Tangelos 0.11 0.00

Cultivated Wild Rice 0.08 0.00

Macadamia Trees 0.06 0.00 

Forage Production 0.71 0.51

Pears 0.31 0.26

Citrus VII 4.82 4.04

Sugar Beets 0.37 0.32 

Forage Seeding 0.61 0.55

Millet 0.76 0.72

Source: The Contractor’s Underwriting Department using USDA, RMA data.

However, in general, the crops that had losses at any time during these years were more likely to 

have a higher loss ratio for organic production than for conventional production. 

The Contractor then graphed the relationship of loss cost ratios for conventional and organic 

production and loss ratios for conventional and organic production by crop and year, for all crops 

combined, at a variety of different aggregation levels. In the following figures resulting from this 

exercise, the red line illustrates a one to one relationship between the conventional loss cost ratio 

(loss ratio) and the organic loss cost ratio (loss ratio). Any data points falling on this line 

represent equivalence of the elements with and without the organic code. Data points above this 

blue line represent worse performance (in terms of loss cost ratio or loss ratio) of organic crops 

relative to non-organic crops and points below the line represent better performance. The blue 

line is an ordinary least squares regression of the relationship between loss cost ratio (or loss 

ratio) for a crop (or crops) with the organic code and without the organic code. 

In the following figures, comparing the loss cost ratios and loss ratios for crops that had both 

organic and conventional experience over the period 2001 to 2008, many of the points are above 

the blue line, indicating almost the organic crops performed worse in terms of losses relative to 

non-organic crops. However, it is important to note that as the risk to non-organic production 

increases, the regression generally predicts better performance for organic production relative to 

conventional production. 
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

82

FIGUR E 12. Comparison of Organic and Non-organic Insurance Experience for All Crops 

by Crop during the Period from 2001 through 2008 (each point represents one year for one 

crop) at the State, Risk Region, County, and Paired Unit Levels* 

* Figure 12 includes ten scatter diagrams, five for loss cost ratio and five for loss ratio, showing the range of 

relationships between values for organic and non-organic insured crops at the crop, state, risk region, county and 

paired unit level. In general there are more cases where the organic value exceeds the non-organic value, however 

there are numerous instances where the organic value is lower than the non-organic value at all levels. In all cases, a 

simple regression line starts above the origin (0, 0) and eventually drops below the x=y line. (Figure 12 Data)

Loss Cost Ratio Loss Ratio 

County

Crop

State

Risk Region

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

83

FIGUR E 12. Comparison of Organic and Non-organic Insurance Experience for All Crops 

by Crop during the Period from 2001 through 2008 at the State, Risk Region, County, and 

Paired Unit Levels (continued)

Loss Cost Ratio Loss Ratio 

Paired Unit

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

The Contractor then examined the organic crops with the most substantial production (i.e., 

wheat, corn, and soybean) to determine if the patterns observed for all crops were reflected in the 

performance of each of the major crops (Figures 13 to 15). While the slopes of these 

comparisons for wheat, corn, and soybean, did in fact reflect the relationship that much of the 

organic crops performance was worse than the performance of the same crops grown under nonorganic practices, again as the risk (defined here as likelihood of severe loss) to non-organic 

production increases, the regression predicts better performance for organic production relative 

to conventional production. 

One interpretation of this pattern is that the issues with performance of insurance for organic 

crops cannot be resolved by a simple, across the board increase in insurance premiums (a fixed 

surcharge), since such an increase would have the effect of lowering the regression line with 

minimal impact on the slope (i.e., if the premium for organic production is raised across the 

board, the premium for organic crops in extreme conditions would be excessive relative to the 

premium for the same crop grown conventionally). Another inference is that while organic 

guarantees may be too high in some cases, a change to the guarantee structure would not 

necessarily align the historic performance with the ideal one to one line. 

Instead, it is likely a number of factors are interacting to create the performance pattern observed 

for organic crops relative to their non-organic counterparts. These could include potential rating 

issues, issues with guarantees including T-yields used for organic production, underwriting 

issues related to experience with the crop and with organic practices, loss adjustment issues 

related to uninsurable causes of loss (i.e., poor farming practices), or yield differentials due to 

practice being adjusted as an insurable loss. 
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

84

FIGUR E 13. Comparison of Organic and Non-organic Insurance Experience for Wheat 

during the Period from 2001 through 2008 (each point represents one year) at the State, 

Risk Region, County, and Paired Unit Levels* 

* Figure 13 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic wheat at the state, risk region, county and paired unit 

level. In general there are more cases where the organic value exceeds the non-organic value; however there are 

numerous instances where the organic value is lower than the non-organic value at all levels. A simple regression 

line starts above the origin (0, 0) and eventually drops below the x=y line at the state, risk region, and county level. 

At the paired unit level the regression line starts at or very near the origin and stays below the x=y line. (Figure 13 Data)

Loss Cost Ratio Loss Ratio 

Paired Unit

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

85

FIGUR E 14. Comparison of Organic and Non-organic Insurance Experience for Corn 

during the Period from 2001 through 2008 (each point represents one year) at the State, 

Risk Region, County, and Paired Unit Levels* 

Figure 14 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic corn at the state, risk region, county and paired unit level. 

In general there are more cases where the organic value exceeds the non-organic value; however there are numerous 

instances where the organic value is lower than the non-organic value at all levels. A simple regression line in each 

scatter diagram starts above the origin (0,0) in every case and eventually drops below the x=y line at the state, risk 

region, and county level for both loss cost ratio and loss ratio. At the risk region and paired unit levels for the loss 

cost ratio the simple regression line is slightly above the x=y line starts at or very near the origin and stays above the 

x=y line. At the paired unit level for loss ratio, the regression starts above the origin and drops below the x=y line.

(Figure 14 Data)

Loss Cost Ratio Loss Ratio 

Paired Unit

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

86

FIGUR E 15. Comparison of Organic and Non-organic Insurance Experience for Soybeans 

during the Period from 2001 through 2008 (each point represents one year) at the State, 

Risk Region, County, and Paired Unit Levels* 

* Figure 15 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic soybean at the state, risk region, county and paired unit 

level. In general there are more cases where the organic value exceeds the non-organic value; however there are 

numerous instances where the organic value is lower than the non-organic value at all levels. At the paired unit 

level, a simple regression line overlies x=y for loss cost ratio and starts at or very near the origin and stays below the 

x=y line for loss ratio. (Figure 15 Data)

Loss Cost Ratio Loss Ratio 

Paired Unit

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

87

Differentiating between the potential contributors to the insurance performance patterns by crop 

and year is a task outside the scope of this contract. Rating issues, guarantees, underwriting 

issues, and loss adjustment create a range of interactions that cannot be revealed through the 

analysis of historical performance over a relatively short period, regardless of the percentage of 

total U.S. organic production insured in the most recent year. Furthermore, if organic producers 

are choosing to insure only if they believe their risk is high and not participating if they perceive 

their risk is low (regardless of the insurance premium subsidy), then that producer behavior adds 

another potential complication to the assessment of the cause underlying the differences in 

insurance performance between organic and conventional production. 

Nonetheless, the Contractor expanded the examination of the insurance experience patterns to 

include a variety of other crops, including rice (Figure 16), barley (Figure 17), apples (Figure 

18), all fruits collectively except apples (Figure 19), all vegetables collectively (Figure 20), all 

vegetables collectively except potatoes (Figure 21), and potatoes (Figure 22). The all fruits 

except apples group includes production insured as fresh apricots, processing apricots, avocado, 

blueberries, cranberries, cherries, figs, grapes, table grapes, raisins, grapefruit, lemons, fresh 

nectarines, peaches, processing cling peaches, processing freestone peaches, fresh freestone 

peaches, pears, plum, prunes, strawberries, mandarin oranges, Mineola tangelos, sweet oranges, 

Valencia oranges, and as California citrus, Citrus I, Citrus II, Citrus III, Citrus IV, Citrus V, and 

Citrus VII. No single fruit predominated in this assemblage. The all vegetables except potatoes 

group includes production insured as onions, sweet corn for canning and processing, green peas, 

peppers, fresh market tomatoes, and processing tomatoes. No single vegetable predominated in 

this assemblage.
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

88

FIGUR E 16. Comparison of Organic and Non-organic Insurance Experience for Rice during 

the Period from 2001 through 2008 (each point represents one year) at the State, Risk 

Region, County, and Paired Unit Levels* 

* Figure 16 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic rice at the state, risk region, county and paired unit level. 

In general there are more cases where the organic value exceeds the non-organic value; however there are numerous 

instances where the organic value is lower than the non-organic value at all levels. A simple regression line starts 

above the origin (0, 0) and eventually drops below the x=y line at the risk region and county level. At the paired unit 

level the regression line starts at or very near the origin and stays below the x=y line. (Figure 16 Data)

Loss Cost Ratio Loss Ratio 

Paired Unit

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

89

FIGUR E 17. Comparison of Organic and Non-organic Insurance Experience for Barley 

during the Period from 2001 through 2008 (each point represents one year) at the State, 

Risk Region, and County Levels, by Year 

* Figure 17 includes six scatter diagrams, three for loss cost ratio and three for loss ratio, showing the range of 

relationships between values for organic and non-organic barley at the state, risk region, and county levels (there are 

not sufficient data to create the diagrams at the paired unit level). In general there are more cases where the organic 

value exceeds the non-organic value; however there are numerous instances where the organic value is lower than 

the non-organic value at all levels graphed. A simple regression line starts above the origin (0, 0) and eventually 

drops below the x=y line at the state, risk region, and county level. (Figure 17 Data)

Loss Cost Ratio Loss Ratio 

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

90

FIGUR E 18. Comparison of Organic and Non-organic Insurance Experience for Apples 

during the Period from 2001 through 2008 (each point represents one year)at the State, 

Risk Region, County, and Paired Unit Levels * 

* Figure 18 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic apples at the state, risk region, county and paired unit 

level. In general there are more cases where the organic value exceeds the non-organic value; however there are 

numerous instances where the organic value is lower than the non-organic value at all levels. A simple regression 

line for the scatter diagrams at the state, risk region, and county level starts above the origin (0, 0) and eventually 

drops below the x=y line. At the paired unit level the regression lines essentially overly the x=y line. (Figure 18 Data)

Loss Cost Ratio Loss Ratio 

Paired Unit

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

91

FIGUR E 19. Comparison of Organic and Non-organic Insurance Experience for All Fruits 

Except Apples during the Period from 2001 through 2008 (each point represents one year 

for one crop) at the Crop, State, Risk Region, County, and Paired Unit Levels* 

* Figure 19 includes ten scatter diagrams, five for loss cost ratio and five for loss ratio, showing the range of 

relationships between values for organic and non-organic fruit (except apples) at the crop, state, risk region, county 

and paired unit level. In general there are more cases where the organic value exceeds the non-organic value; 

however there are numerous instances where the organic value is lower than the non-organic value at all levels. A 

simple regression line for the scatter diagrams at the crop, state, risk region, and county level starts above the origin 

(0, 0) and eventually drops below the x=y line. At the paired unit level the regression lines essentially overly the x=y

line. (Figure 19 Data)

Loss Cost Ratio Loss Ratio 

County

Crop

State

Risk Region

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

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5

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Non-organic

Organic

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Non-organic

Organic

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Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

92

Figure 19. Comparison of Organic and Non-organic Insurance Experience for All Fruits 

Except Apples during the Period from 2001 through 2008 at the Crop, State, Risk Region, 

County, and Paired Unit Levels (continued)

Loss Cost Ratio Loss Ratio 

Paired Unit

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

93

FIGUR E 20. Comparison of Organic and Non-organic Insurance Experience for All 

Vegetables during the Period from 2001 through 2008 (each point represents one year for 

one crop) at the Crop, State, Risk Region, County, and Paired Unit Levels* 

* Figure 20 includes ten scatter diagrams, five for loss cost ratio and five for loss ratio, showing the range of 

relationships between values for organic and non-organic vegetables at the crop, state, risk region, county and paired 

unit level. While there are more cases where the organic value exceeds the non-organic value, there are numerous 

instances where the organic value is lower than the non-organic value at all levels. A simple regression line for the 

scatter diagrams at the state, risk region, and county level starts above the origin (0, 0) and eventually drops below 

the x=y line in seven instances, while for the state level in both cases and at the risk region level for loss cost ratio 

the regression line lies above the line x=y. (Figure 20 Data)

Loss Cost Ratio Loss Ratio 

County

Crop

State

Risk Region

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

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0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

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5

6

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8

9

10

0 2 4 6 8 10

Non-organic

Organic

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0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

94

Figure 21. Comparison of Organic and Non-organic Insurance Experience for All 

Vegetables Except Potatoes during the Period from 2001 through 2008 (each point 

represents one year for one crop) at the Crop, State, Risk Region, County, and Paired Unit 

Levels*

* Figure 21 includes eight scatter diagrams, four for loss cost ratio and four for loss ratio, showing the range of 

relationships between values for organic and non-organic vegetables except potatoes at the crop, state, risk region, 

and county level. While there are more cases where the organic value exceeds the non-organic value, there are 

numerous instances where the organic value is lower than the non-organic value at all levels. A simple regression 

line for the scatter diagrams at the state, risk region, and county level starts above the origin (0, 0) and eventually 

drops below the x=y line in six instances, while for the loss cost ratio at the state and risk region level the regression 

line lies above the line x=y. (Figure 21 Data)

Loss Cost Ratio Loss Ratio 

County

Crop

State

Risk Region

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

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0.4

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0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

95

Figure 22. Comparison of Organic and Non-organic Insurance Experience for Potatoes 

during the period from 2001 through 2008 (each point represents one year) at the State, 

Risk Region, and County Levels* 

* Figure 22 includes six scatter diagrams, three for loss cost ratio and three for loss ratio, showing the range of 

relationships between values for organic and non-organic potatoes at the state, risk region, and county levels. While 

there are more cases where the organic value exceeds the non-organic value, there are instances where the organic 

value is lower than the non-organic value at all levels. A simple regression line for the scatter diagrams at the state, 

risk region, and county level lies above the line x=y in every case. (Figure 22 Data)

Loss Cost Ratio Loss Ratio 

State

Risk Region

County

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic

0

0.2

0.4

0.6

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1

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Non-organic

Organic

0

1

2

3

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5

6

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8

9

10

0 2 4 6 8 10

Non-organic

Organic

0

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0.8

1

0 0.2 0.4 0.6 0.8 1

Non-organic

Organic

0

2

4

6

8

10

0 2 4 6 8 10

Non-organic

Organic
Organic Crops: Revised Written Rating Report 

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restrictions on the title page of this report.

96

It is important to remember this graphical analysis is a tool to envision a wide-ranging and 

disparate dataset. There is a great deal of “noise” in these data. There is a potential of cluster 

sampling, both geographically and by the insureds’ perception of potential risk. At the county 

level, when organic and conventional yields are compared by crop and year, of the more than 

5,500 cases, more than 31 percent have insufficient data to run even simple statistical tests of 

differences such as Student’s or Welch’s T-tests. Of those yields that can be compared using 

these tests, 84 percent cannot be demonstrated to be statistically significantly different at the 95 

percent confidence level. In the cases where there are significant differences (just 10.8 percent of 

all the potential comparisons at the county level), there is a predominance of cases where the 

organic yield is significantly lower than the conventional yield.

There is no question the insurance for organic production is not functioning ideally. In aggregate 

analyses, the differences in risk responses between organic production and conventional 

production generally favor conventional production in the lowest risk situations and organic 

production in the higher risk situations. The organic producers receive a disproportionate amount 

of the indemnities paid at lower risk levels (as defined by the risk for conventional production). 

This response to risk levels likely explains some of the bias toward higher yields for 

conventional production in the crop-county-year combinations having significantly different 

yields under the two practices. The number of samples of production under lower relative risk 

levels would be expected to exceed number of samples of production under high risk scenarios. 

What can not be explained using this logic is the relative responses to risk in the paired unit 

comparisons. 

In the comparison of loss ratios and loss cost ratios at the paired unit level, the intercept of the 

regression between units with the different codes is generally very close to 0, and the regression 

line generally lies near or below the one to one line throughout the range of loss ratios and loss 

cost ratios. This pattern is consistent across crops and crop sectors. However the sample size is 

limited, with very few observations relative to the magnitude of all insurance experience for the 

crop during these years. Furthermore, there is a high degree of scatter in the data. Nonetheless, 

the consistency of this observation when the most precise comparisons possible are made is 

notable. 

Causes of Loss on Acreage with an Organic Code 

The primary benefit of insuring qualifying acreage under organic codes (as opposed to insuring it 

as a conventional crop) is to obtain the coverage for losses due to insects, disease, and weeds. 

With the insurance in place, acreage on which one of these causes of loss occurs will be covered 

(if an allowed pesticide88

 

88 The term pesticide is used herein in the same manner as it is used by the Environment Protection Agency. It includes all chemicals commonly 

referenced as pesticides, fungicides, rodenticides, and related terms.

 was applied and was not effective due to an adverse weather condition 

and it could not be reapplied either due to label limitations or continuation of the adverse weather 

conditions). In addition, a condition for which there is no pesticide labeled for use on the crop 

and/or causative agent, similarly, would be covered. These are the same conditions that apply to 

conventional acreage. The only difference is the type of pesticide that is considered in making 

the determination. Losses due to all other causes – drought, wind, excess precipitation, and so 

forth – are covered exactly the same for crops insured under the organic code as these conditions 

would be covered under conventional practices. 
Organic Crops: Revised Written Rating Report 

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97

During 2004 through 2008, indemnities for causes of loss 71 (insects) and 81 (plant disease) on 

acreage insured with an organic code amounted to $0.994 million. Producers paid approximately 

$2.6 million for the organic coverage. Acreage of the same crops insured without the organic 

code in the same counties paid $12.5 million in indemnities for these causes of loss during this 

period. The loss cost on the acreage without an organic code was 0.00036 percent. Thus, for the 

liability on acreage with the organic code, expected indemnities under the conventional coverage 

would have been $450 million89 times 0.00036, or $0.162 million. Thus, acreage with an organic 

code received excess indemnities of $0.831 million relative to conventional practice. Based on 

these assumptions and relationships, the current rate premium factor for acreage with an organic 

code resulted in an over-charge of approximately $1.8 million during these years. 

Consequently, while the insurance experience does show in aggregate a pattern of higher losses 

for organic crops than for conventional crops, this pattern is neither consistent nor systemic. It is 

difficult to defend a uniform rate premium surcharge, especially in light of the limited added risk 

associated with use of organic practices to control disease, insects, and weeds.

Relationships of Organic and Non-organic Loss Cost Ratios by Crop and in the Aggregate 

This report considers the available data at all levels of aggregation to determine if the data reflect 

a systemic, consistent, and significant bias between conventional and organic loss experience. 

This section addresses the analysis at the highest level of aggregation. Table 34 compiles 

summary statistics for each crop for which an organic code was reported during 2004 through 

2008. The table compares loss cost ratios by crop, as well as the respective loss ratios, earned 

premium rates, for the organic and non-organic practices for the years 2004 through 2008. In 

addition, the number of units insured for each crop under the organic and non-organic practices 

for the years 2004 through 2008 is reported. In the case of rice, three comparisons are presented: 

2004 through 2005 and 2006 through 2008 as well as the aggregate data for 2004 through 2008, 

to address the actuarial changes that were made for that crop. The earned premium rate for the 

organic practice is net of the five percent surcharge.

90

 

89 $450 million is the approximate liability on acreage with an organic code. See Table 7. 90 The earned premium rate divided by 1.05 to eliminate the effect of the historic 5 percent surcharge applied over the period during which these 

observations were collected.
Organic Crops: Revised Written Rating Report 

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contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

98

Table 34. Summary of Insurance Performance of Organic and Non-organic Production by 

Crop in all Counties with Organic Production for that Crop 

Crop

All Organic Units All Non-Organic Units Ratios

Implied 

Surcharge

Total

Number of 

Units

Net Earned 

Premium 

Rate*

Loss 

Ratio

Loss 

Cost 

Ratio

Total 

Number of 

Units

Earned 

Premium 

Rate

Loss 

Ratio

Loss 

Cost 

Ratio

Earned 

Premium 

Rate

Loss 

Cost 

Ratio

Wheat 6,028 0.239 0.969 0.243 397,088 0.168 0.750 0.126 1.422 1.930 0.36

Blueberries 15 0.092 1.344 0.130 141 0.075 0.428 0.032 1.221 4.025 2.30

Onions 86 0.151 0.905 0.143 590 0.106 0.810 0.086 1.421 1.668 0.17

Oats 886 0.205 0.734 0.158 7,532 0.183 1.176 0.215 1.122 0.735 -0.34

Millet 419 0.281 0.722 0.213 9,842 0.198 0.963 0.191 1.422 1.119 -0.21

Rice 04-05 123 0.095 2.349 0.234 3,576 0.033 0.813 0.027 2.878 8.733 2.03

Rice 06-08 447 0.063 1.158 0.077 6,741 0.038 0.636 0.024 1.662 3.179 0.91

Rice All 570 0.071 1.540 0.114 10,317 0.037 0.676 0.025 1.927 4.606 1.39

Avocado 106 0.113 0.655 0.078 2,979 0.115 0.646 0.074 0.985 1.048 0.06

Cotton 331 0.225 1.149 0.272 52,026 0.250 1.082 0.271 0.901 1.004 0.11

Cotton Ex Long Staple 6 0.106 5.012 0.558 476 0.042 1.195 0.050 2.531 11.151 3.41

Macadamia Nuts 6 0.022 0.771 0.018 403 0.020 1.549 0.031 1.086 0.568 -0.48

Macadamia Trees 8 0.013 0.000 0.000 281 0.011 0.000 0.000 1.203 N/A N/A

Almonds 199 0.091 0.989 0.094 12,755 0.059 0.334 0.020 1.542 4.793 2.11

Walnuts 72 0.037 3.853 0.151 1,927 0.033 0.102 0.003 1.122 44.422 38.58

Flax 871 0.223 1.650 0.386 6,239 0.146 1.300 0.190 1.526 2.033 0.33

Forage Seeding 77 0.126 0.493 0.065 1,351 0.136 0.489 0.066 0.927 0.980 0.06

Forage Production 120 0.111 0.459 0.054 2,855 0.114 0.639 0.073 0.972 0.734 -0.24

Peaches 3 0.185 0.000 0.000 82 0.177 0.135 0.024 1.044 0.000 -1.00

Prunes 94 0.147 1.542 0.239 2,186 0.142 1.960 0.279 1.037 0.856 -0.17

Raisins 64 0.070 0.160 0.012 5,264 0.079 0.243 0.019 0.882 0.611 -0.31

Corn 4,274 0.126 1.367 0.181 529,179 0.087 0.554 0.048 1.445 3.744 1.59

Sweet Corn, C&P 112 0.046 2.249 0.109 522 0.035 0.162 0.006 1.297 18.903 13.57

Popcorn 43 0.104 1.526 0.167 230 0.058 0.107 0.006 1.785 26.622 13.92

Beans, Processing 27 0.149 2.182 0.341 195 0.104 0.768 0.080 1.432 4.269 1.98

Beans, Dry 400 0.161 1.290 0.217 8,692 0.138 0.823 0.113 1.165 1.917 0.65

Safflower 51 0.145 1.267 0.193 208 0.106 0.949 0.100 1.371 1.922 0.40

Grain Sorghum 133 0.275 1.600 0.462 7,589 0.175 1.109 0.194 1.573 2.384 0.52

Table Grapes 159 0.059 1.260 0.079 3,294 0.049 0.371 0.018 1.223 4.358 2.56

Grapes 715 0.057 0.293 0.018 30,692 0.057 0.287 0.016 1.007 1.079 0.07

Apples 1,137 0.074 0.485 0.038 10,975 0.049 0.795 0.039 1.526 0.978 -0.36

Cultivated Wild Rice 9 0.039 0.000 0.000 39 0.041 0.097 0.004 0.959 0.000 -1.00

Cherries 135 0.064 1.249 0.084 4,465 0.104 1.121 0.117 0.617 0.722 0.17

Cranberries 23 0.087 0.836 0.076 746 0.029 0.222 0.006 2.976 11.767 2.95

Figs 47 0.056 0.642 0.038 76 0.067 0.296 0.020 0.841 1.914 1.28

Hybrid Corn Seed 31 0.108 0.503 0.057 116 0.051 0.832 0.042 2.122 1.347 -0.37

Peas, Green 92 0.085 1.060 0.094 349 0.068 0.522 0.036 1.239 2.645 1.13

Peas, Dry 490 0.227 1.393 0.332 7,785 0.144 1.189 0.171 1.578 1.941 0.23

Mustard 3 0.104 3.029 0.332 3 0.100 0.249 0.025 1.039 13.296 11.79

Peanuts 183 0.070 0.991 0.073 3,019 0.050 0.469 0.023 1.413 3.134 1.22

Sunflowers 278 0.212 1.066 0.238 6,504 0.182 0.769 0.140 1.168 1.701 0.46

Soybeans 3,976 0.151 1.774 0.281 507,750 0.098 0.853 0.084 1.533 3.348 1.18

Potatoes 231 0.095 1.333 0.132 3,165 0.075 0.559 0.042 1.265 3.167 1.50

Tomatoes, Fresh Market & GP 4 0.110 0.000 0.000 9 0.139 0.472 0.066 0.794 0.000 -1.00

Tomatoes, Processing 197 0.057 0.600 0.036 4,923 0.046 0.395 0.018 1.229 1.964 0.60

Pears 328 0.040 0.268 0.011 5,065 0.034 0.187 0.006 1.160 1.746 0.50

Barley 706 0.203 0.910 0.194 16,448 0.138 1.066 0.147 1.470 1.317 -0.10

Plum 123 0.112 0.356 0.042 2,212 0.109 0.655 0.071 1.030 0.588 -0.43

Rye 27 0.163 1.024 0.175 13 0.174 0.145 0.025 0.935 6.932 6.42

Alfalfa Seed 3 0.064 6.312 0.426 1 0.058 7.512 0.432 1.116 0.985 -0.12

Strawberries 16 0.023 0.000 0.000 333 0.025 0.000 0.000 0.942 N/A N/A

Grapefruit 14 0.047 3.683 0.182 102 0.044 1.055 0.047 1.062 3.893 2.67

Lemons 36 0.057 1.357 0.081 1,226 0.040 0.552 0.022 1.423 3.671 1.58

* Net Earned Premium Rate = Actual Earned Premium Rate divided by 1.05.

N/A = Organic Loss Cost Ratio is 0.00.
Organic Crops: Revised Written Rating Report 

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

99

Table 34. Summary of Insurance Performance of Organic and Non-organic Production by 

Crop in all Counties with Organic Production for that Crop (continued)

Crop

All Organic Units All Non-Organic Units Ratios

Implied 

Surcharge Total 

Number of 

Units

Net Earned 

Premium 

Rate*

Loss 

Ratio

Loss 

Cost 

Ratio

Total 

Number of 

Units

Earned 

Premium 

Rate

Loss 

Ratio

Loss 

Cost 

Ratio

Earned 

Premium 

Rate

Loss 

Cost 

Ratio

Mandarins 11 0.069 0.265 0.019 76 0.074 0.354 0.026 0.930 0.730 -0.22

Mineola Tangelos 8 0.062 0.000 0.000 86 0.070 1.140 0.080 0.884 0.000 -1.00

Orange Trees 1 0.018 0.000 0.000 57 0.019 0.000 0.000 0.921 N/A N/A

Grapefruit Trees 1 0.018 0.000 0.000 6 0.016 0.000 0.000 1.093 N/A N/A

All Other Citrus Trees 1 0.018 0.000 0.000 4 0.019 0.000 0.000 0.958 N/A N/A

Navel Oranges 86 0.061 3.414 0.220 7,925 0.055 1.538 0.084 1.122 2.615 1.33

Sweet Oranges 3 0.075 5.082 0.399 13 0.080 1.091 0.087 0.938 4.591 3.89

Valencia Oranges 78 0.066 2.923 0.204 2,333 0.069 1.373 0.095 0.961 2.147 1.24

Fresh Apricots 45 0.109 1.512 0.173 170 0.107 0.798 0.085 1.023 2.034 0.99

Processing Apricots 13 0.096 1.303 0.131 172 0.106 1.490 0.158 0.905 0.830 -0.08

Fresh Nectarines 145 0.082 0.416 0.036 1,922 0.059 0.260 0.015 1.386 2.333 0.68

Processing Cling Peaches 18 0.036 0.000 0.000 323 0.036 0.744 0.026 1.006 0.000 -1.00

Processing Freestone Peaches 1 0.052 0.000 0.000 1 0.052 0.000 0.000 0.999 N/A N/A

Fresh Freestone Peaches 144 0.069 0.903 0.065 1,600 0.047 0.064 0.003 1.475 21.821 13.79

Flue Cured Tobacco 28 0.053 3.353 0.185 1,592 0.059 2.552 0.151 0.889 1.226 0.38

Burley Tobacco 3 0.092 0.000 0.000 7 0.087 1.194 0.103 1.063 0.000 -1.00

Cigar Filler Tobacco 1 0.061 0.000 0.000 3 0.045 0.000 0.000 1.371 N/A N/A

Ciger Binder Tobacco 2 0.065 0.000 0.000 4 0.058 10.564 0.614 1.114 0.000 -1.00

Citrus Trees I 4 0.034 0.000 0.000 876 0.036 0.000 0.000 0.941 N/A N/A

Citrus Trees IV 4 0.045 0.000 0.000 1,461 0.048 0.000 0.000 0.944 N/A N/A

Citrus Trees V 6 0.045 0.000 0.000 138 0.043 0.000 0.000 1.061 N/A N/A

Citrus I 13 0.036 0.000 0.000 281 0.030 7.101 0.214 1.190 0.000 -1.00

Citrus II 7 0.039 0.000 0.000 153 0.041 0.078 0.003 0.953 0.000 -1.00

Citrus III 2 0.035 0.000 0.000 1 0.035 0.000 0.000 0.997 N/A N/A

Citrus IV 23 0.057 0.000 0.000 344 0.039 2.817 0.109 1.486 0.000 -1.00

Citrus V 6 0.066 3.376 0.234 100 0.048 3.420 0.163 1.386 1.436 0.04

Citrus VI 9 0.036 4.039 0.155 208 0.030 17.461 0.526 1.209 0.294 -0.76 

Coffee 1 0.020 0.000 0.000 13 0.019 0.000 0.000 1.061 N/A N/A

All Crops 24,628 0.116 1.121 0.136 1,690,128 0.095 0.707 0.067 1.212 2.019 0.67

* Net Earned Premium Rate = Actual Earned Premium Rate divided by 1.05.

N/A = Organic Loss Cost Ratio is 0.00. 

Three ratios are presented in the final columns of the table. The penultimate column, which is the 

ratio of the non-organic loss cost ratio to the organic loss cost ratio, indicates the loss cost 
Organic Crops: Revised Written Rating Report 

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restrictions on the title page of this report.

100

experience of the organic practice was two times higher in aggregate than the non-organic. The 

ratio of earned premium rate compares the average rates the producers paid for the organic 

production (again eliminating the historic five percent surcharge) to that of the non-organic 

production. On average, organic producers paid 21 percent higher premium rates in the same 

counties where an organic practice code was reported (net of the five percent surcharge). Thus, 

on average, the existing rating systems are increasing the premium rates for organic practice 

exclusive of the surcharge, based often on lower average yields for organic production and the 

impacts of yield ratio and exponent in the existing rating systems. The implied surcharges 

included in the final column exhibit substantial variation, with some indicating a 100 percent 

discount for organic because there were no losses for the organic practice for these crops in the 

available data. This is simply an artifact of the data representing very few years and very few 

insured units for those crops. An entry of N/A indicates no losses were reported for either 

practice. In several cases, these are “disaster” type crops such as citrus trees that have limited 

causes of loss.

Mathematically, the net surcharge implied by the available loss cost ratio data, if the organic 

practice were to be continued under the existing actuarial structure (i.e., with a flat surcharge 

across all crops and geography), would be 2.02 divided by 1.21, or approximately 67 percent (i.e. 

the factor on actuarial table for organic would be 1.67, not 1.05). At the same time, the aggregate 

loss ratio for insured organic crops from 2004 to 2008 was 1.121. Assuming insurable conditions 

for organic crops are appropriately captured in the available RMA data, an increase in premiums 

of the magnitude implied by the ratio of loss cost ratios would drive the insurance performance 

so the loss ratio for organic crops would be much less than 1.00, implying that under this 

approach the organic practice would be over-rated. Furthermore, the implied surcharges by crop 

shown in the final column exhibit substantial variation, including cases where the organic crop 

would receive a discount (a negative implied surcharge) over crops grown conventionally.91

It is also important to consider, these data represent an average of distinctly different rating 

systems. Table 35 is a subset of Table 34 containing only the APH-based rating system crops.92 

This subset of crops had an average loss cost ratio that was 185 percent greater than the loss cost 

ratio for the non-organic practice. The premium rating system generated a premium rate that was 

52 percent greater on average; hence, the net surcharge under the existing actuarial structure for 

all crops insured under plan code 90 would be 88 percent considering all data in the aggregate. 

Experience from the 2009 crop year and additional crop years (when available) will likely 

modify these estimates.

 

91 The variation in observations is striking, with some indicating a 100 percent discount for organic because there were no losses for the organic 

practice for these crops in the available data. This is simply an artifact of the data representing very few years and very few insured units for those 

crops. An entry of N/A indicates no losses were reported for either practice.

92 Certain crops, such as dry beans or dry peas, were rated under the yield-dependent plan code 90 system in some parts of the country and under 

the flat rated plan code 86 in other areas for at least part of this time period. These crops have not been included in the table.
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101

Table 35. Summary of APH Insurance Performance of Organic and Non-organic 

Production by Crop in all Counties with Organic Production for that Crop 

Crop

All Organic Units All Non-Organic Units Ratios

Implied 

Surcharge Total 

Number of 

Units

Net Earned 

Premium 

Rate*

Loss 

Ratio

Loss Cost 

Ratio

Total 

Number 

of Units

Earned 

Premium 

Rate

Loss 

Ratio

Loss 

Cost 

Ratio

Earned 

Premium 

Rate

Loss Cost 

Ratio

Wheat 6,028 0.239 0.969 0.243 397,088 0.168 0.750 0.126 1.422 1.930 0.36

Oats 886 0.205 0.734 0.158 7,532 0.183 1.176 0.215 1.122 0.735 -0.34

Millet 419 0.281 0.722 0.213 9,842 0.198 0.963 0.191 1.422 1.119 -0.21

Rice A 123 0.095 2.349 0.234 3,576 0.033 0.813 0.027 2.878 8.733 2.03

Rice B 447 0.063 1.158 0.077 6,741 0.038 0.636 0.024 1.662 3.179 0.91

Rice All 570 0.071 1.540 0.114 10,317 0.037 0.676 0.025 1.927 4.606 1.39

Cotton 331 0.225 1.149 0.272 52,026 0.250 1.082 0.271 0.901 1.004 0.11

Macadamia Nuts 6 0.022 0.771 0.018 403 0.020 1.549 0.031 1.086 0.568 -0.48

Almonds 199 0.091 0.989 0.094 12,755 0.059 0.334 0.020 1.542 4.793 2.11

Flax 871 0.223 1.650 0.386 6,239 0.146 1.300 0.190 1.526 2.033 0.33

Corn 4,274 0.126 1.367 0.181 529,179 0.087 0.554 0.048 1.445 3.744 1.59

Sweet Corn, C&P 112 0.046 2.249 0.109 522 0.035 0.162 0.006 1.297 18.903 13.57

Popcorn 43 0.104 1.526 0.167 230 0.058 0.107 0.006 1.785 26.622 13.92

Safflower 51 0.145 1.267 0.193 208 0.106 0.949 0.100 1.371 1.922 0.40

Grain Sorghum 133 0.275 1.600 0.462 7,589 0.175 1.109 0.194 1.573 2.384 0.52

Cranberries 23 0.087 0.836 0.076 746 0.029 0.222 0.006 2.976 11.767 2.95

Mustard 3 0.104 3.029 0.332 3 0.100 0.249 0.025 1.039 13.296 11.79

Sunflowers 278 0.212 1.066 0.238 6,504 0.182 0.769 0.140 1.168 1.701 0.46

Soybeans 3,976 0.151 1.774 0.281 507,750 0.098 0.853 0.084 1.533 3.348 1.18

Barley 706 0.203 0.910 0.194 16,448 0.138 1.066 0.147 1.470 1.317 -0.10

Rye 27 0.163 1.024 0.175 13 0.174 0.145 0.025 0.935 6.932 6.42

APH Crops 18,909 0.157 1.260 0.208 1,565,381 0.104 0.705 0.073 1.520 2.853 0.88

* Net Earned Premium Rate = Actual Earned Premium Rate divided by 1.05.

N/A = Organic Loss Cost Ratio is 0.00.

These comparisons of loss cost ratios provide a basis for assessing three potential treatments of 

the organic practice. The first is the continuation of the current practice of including a flat, 

across-the board surcharge on the actuarial tables. The variability in the crop-by-crop loss ratios 

and loss cost ratios makes this approach untenable. The second is the inclusion of a surcharge on 

the actuarial tables, the amount of which is the implied surcharge (derived from the ratio of the 

two identified columns less one [to reflect the assumed ratio if the crops perform identically 

under the two practices]). This approach will “force a balance” between the loss cost ratios of 

organic and conventional production, but only if the historic data accurately reflects the relative 

risks of the two practices and if the future participation and experience mirrors the past. The 

Contractor does not believe the first conditions have been met or that the second will be met. The 

last is treating the organic practice as a separate type/practice with its own base premium rate, 

based on whatever historical yield data may be available. It also implies other adjustments to the 
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102

actuarial structures such as reduced transitional yields or reference yields, or imposing additional 

underwriting constraints. 

As the analysis clearly reveals, the aggregate insurance experience for organic production has 

been very different from that of conventional production over the observations captured in the 

available data. Although the data provide a noisy picture and are not well suited to aggregate 

analysis as evidenced by the substantially different implied surcharge, the overall weight of the 

aggregate performance is too great to dismiss.

The approach applied to organic rating to date, a flat surcharge applied uniformly across all crops 

and geographies, was a logical starting point for insurance development, especially considering 

the public policy goals, the required timeframe for action, and the paucity of available data. The 

variation in performance at all levels of aggregation suggest substantial adjustments will need to 

be made to establish equitable and sustainable programs for individual organic crops and 

geographies, which will likely include independent rate assessment (as sufficient data become 

available) as well as adjustments to the reference yields, T-yields, underwriting, and pricing. A 

flat increase in organic premium rates based on aggregate insurance experience over a brief 

period is not appropriate. Organic production is diverse, encompassing a vast array of regions, 

crops, and risk profiles. Economic theory would postulate that a flat premium rate increase 

across organic crops, without corresponding equitable adjustments to other components of 

organic programs, will undermine the insured pool; poor producers may opt into the insurance 

scheme and better producers will opt out. 
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103

SE CT ION V I . R AT ING ANAL Y SIS FOR OR GANIC AND CONV E NT IONAL CR OPS 

BASE D ON INSUR ANCE E XPE R IE NCE DAT A

This section of the report addresses portions of Section 5.4.1.1. of the Statement of Work in the 

contract requiring the Contractor to determine “an actuarially-sound rate or rate differential for 

organic commodities relative to the same commodities grown under conventional non-organic 

practices,” and contributes to the analysis that “... will either confirm the existence of 

significant, consistent, and systemic variations in loss history between organic and conventional 

commodities (collectively or on an individual crop basis) or refute such variation” required in 

that same section of the contract. It also addresses the requirement the Contractor “provide all 

datasets used for the analysis as well as documentation of the sources of those data, necessary

formulas for the analysis, and logic used to compute the final results and reach any conclusions. 

The data and methods will be sufficiently detailed and complete so that RMA can reapply the 

methodology over time using current and updated data.” 

V .A. Introduction

The analysis presented herein evaluates whether significant, consistent, and systemic variations 

in yield risk and/or loss history experience between organic and conventional commodities 

(collectively or on an individual crop basis) exist. The null hypothesis is that organic and 

conventional production face the same insurance risk (expected loss) in a given locale on a per 

acre basis. The null hypothesis does not test whether the current RMA organic adjustment of 5 

percent (premium multiplied by 1.05) is appropriate. Data available for this exercise are limited 

and therefore the conclusions of the actuarial analysis should be considered tentative and further 

study is recommended as more data become available.

Data used to test the null hypothesis were gathered from RMA Type 11 (acreage record), Type 

15 (yield record), and Type 21 (loss line record) datasets from crop years 2001 through 2008 

(Appendix I). The Type 11 and 21 files were utilized to evaluate insurance experience and the 

Type 15 files were used to compare yield variability between conventional and organic 

production. The experience and yield datasets were grouped by policy into two non-mutually 

exclusive groups: (1) paired observations, policies which insured both conventional and organic 

units,93 and (2) all observations. The paired datasets allow outcomes (insurance experience and 

yield variability) from both conventional and organic acreage grown under the same policy, 

which is presumably located relatively close together and tended in a similar manner while 

experiencing similar growing conditions, to be directly tested. 

Ideally, in assessing the impact of production practices on yields and yield variability, all 

variables other than the practices being studied would be controlled. Variables controlled would 

include, but not be limited to, factors such as soil mineral content, soil quality, slope, aspect, 

temperature, precipitation, planting date, yield potential of the seed, etc. To the extent possible, 

this is the approach taken in published studies comparing organic and conventional production. 

The ‘all observations’ dataset in this study introduces potential asymmetries in the sampling94

 

93 This group consists of the policies included in the discussion of the previous section.

that generates the all conventional and organic groups. In contrast the paired dataset “matches” 

94 Since all observations are included, the “sampling” is a result of a producer’s decision to participate in the insurance program. This is 

influenced by the producers perception of the cost and efficacy of the program.
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104

elements of practices (i.e., soil types, experience, microclimate, etc.) that help to focus the 

analysis primarily on the differences between non-organic and organic production practices. 

Consequently, a paired dataset of sufficient size is the preferred dataset for the analysis. 

Unfortunately, the breadth of the paired dataset is limited. The second grouping includes all units 

in a given county for each crop for which there was organic production. In other words, if there 

were organic wheat production in a county, then all organic and conventional units would be 

included, but if there were no organic corn insured in a county, conventional corn units would be 

excluded. Analysis is focused on insurance experience and yield variability. 

The paired insurance experience data are used to compare the loss ratio of conventional and 

organic units insured under the same policy. The datasets are parsed to evaluate the frequency 

and severity of indemnity payments across all units based on production practice and to compare 

loss ratios when both types of units (conventional and organic) under the policy receive an 

indemnity payment in a given year. The analysis of the “all observation” loss history data looks 

at differences in expected loss ratios (organic loss ratio minus conventional loss ratio) across 

crop and state combinations. 

The analysis of yield variability focuses on the expected temporal standard deviation of yield 

across producers for a given crop and region. The RMA Actual Production History (APH) 

continuous rating function for major commodities has a negative non-zero exponent which 

means premium rates are inversely related with yield magnitude. This result is consistent with 

expected temporal standard deviation of yields being independent of expected yield. Previous 

research by the Contractor has also found that for major commodity crops in major production 

areas, standard deviation tends to be independent of expected yield. Therefore, if organic and 

conventional have similar expected temporal standard deviations, the RMA continuous rate 

function presumably handles additional risk due to differences in expected yield. The paired 

yield dataset is used to evaluate the ratio of temporal standard deviation across producers and the 

all observation dataset is used to look at pooled risk estimates by crop and risk region. 

Analysis of yield standard deviation and expected loss history indicates an extremely wide range 

of outcomes across crops and regions. This result, compounded by the sparse data, given the task 

at hand, leads the Contractor to conclude there are not significant, consistent, and systemic 

variations in yield risk and/or loss history experience between organic and conventional 

production methods. However, there is also no indication the current five percent load for 

organic production is not actuarially sound. 

V .B. Data Description and Discussion 

Appropriate data handling is essential to performing credible analysis. In this section, the 

Contractor provides a detailed discussion of data collection, assessment procedures, and quality 

control measures employed in organizing datasets for the analysis of organic and conventional 

insurance risk. Research was conducted to identify and explore existing sources of regional and 

farm-level data. Production and experience data were identified at the farm level.

Data used to test the null hypothesis were gathered from RMA Type 11 (acreage record), Type 

15 (yield record), and Type 21 (loss line record) datasets from crop years 2001 through 2008. 

The Type 11 and 21 files were utilized to evaluate insurance experience and the Type 15 files 
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105

were used to compare yield variability between conventional and organic production. RMA 

historical record files have been used by the Contractor for many research efforts in the past and 

the data have proven to be reliable and robust. The yield data are discussed next followed by the 

loss experience data.

Historical Yield Data

The Contractor split RMA Type 15 records into two datasets depending on whether they are 

coded as conventional or organic. Table 7 provides the database fields and corresponding entries 

that were used to identify organic records by crop year. In all, 34,706 organic records were found 

based on the following organic coding criteria that if any of the three fields has an organic entry, 

the record is collected in the organic dataset. Conventional (non-organic) yield records were 

extracted for matching county/crop/crop year combinations. For conventional, roughly 6.9 

million records were identified. Record counts by crop year for organic and conventional 

production are provided in Table 36. 

T ABLE 36. Type 15 Record Counts95

Year Organic Conventional

2001 777 165,392

2002 2,093 477,739

2003 2,656 558,127

2004 1,768 216,652 

2005 4,349 919,632

2006 6,313 1,268,279

2007 7,749 1,534,780

2008 9,001 1,723,366 

Total 34,706 6,863,967

Source: The Contractor’s Rating Department using

RMA data.

Datasets were kept separate but cleaned and aggregated in the same fashion. Quality control 

procedures were applied to the Type 15 data files. The first step was to identify and remove 

duplicate records.96 Next, reported crop years from each file are limited to a range of 20 years. 

For example, for the 2008 file crop, reported years are limited to 1988 through 2007. For this 

formal rate analysis, the total number of actual yields reported (yield observations) is counted for 

each record and only records with four or more actual yield observations are utilized.

97 Further 

data quality assurance procedures were then implemented on qualifying records to identify data 

entry errors. Entry errors that are outliers can skew results if not handled appropriately. Entry 

errors were removed from the dataset. One screening method involves calculating yield standard 

deviation across years for a particular record. If the record’s yield standard deviation is less than 

one, the record is removed. 

 

95 While the counts for Organic did not include the uniquely coded 702 entries for rice, a follow-up review of insurance experience showed no 

substantive or significant effects of this exclusion the rating analysis. 96 The most likely cause of duplicate records is duplication of production history as a basic unit is disaggregated into optional units. 97 An “actual yield” is a yield reported by a producer, i.e., a yield that actually “occurred,” as opposed to a transitional or proxy yield.
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106

Record-level data were aggregated to the policy level using an acreage weighted average and the 

resultant data are policy-level yield histories with at least four years of reported yields.98 Pooling 

the data spatially and across crops both may obfuscate differences between organic and 

conventional data. However, the Contractor believes geographic pooling is more likely to hide 

differences between practices than pooling across crops, particularly given the use of relative risk 

measures which account for unit of measure differences across crops. It is likely there are 

policies which include the same historical yields across multiple crop year files. The presence of 

this situation reduces the degrees of freedom in the statistical results and could bias results. 

Previous research by the Contractor has indicated cross-year merging on RMA Type 15 files is 

difficult and not certain to produce correct results due to procedures private companies use to 

report data to RMA and the procedures RMA uses to mask (randomize) policy numbers before 

sending the data to the Contractor. However, it is likely the duplicates are not exact, for example, 

the 2005 file may include yields from 2000 through 2004 while the 2006 crop year file includes 

2000 through 2005. No efforts were taken to remove policies which show up in multiple crop 

year data files for the paired dataset (the bias should apply equivalently to organic and 

conventional) but exact yield observation duplicates were removed in the analysis of the all 

observations dataset as detailed later. Table 37 includes counts of policies with four or more 

actual yields by crop year.

T ABLE 37. Type 15 Policy Counts – 4 or More Actual Yields

Year Organic Conventional

2001 68 34,583 

2002 262 101,976

2003 399 112,672

2004 381 41,029

2005 234 179,798 

2006 246 237,413

2007 305 278,277

2008 334 308,998

Total 2,229

1,294,74

6

Source: The Contractor’s Rating Department 

using RMA data.

Table 38 includes the number of policies with four or more actual yields by crop. 

 

98 A minimum of four actual values was used to provide a reasonable sample size for estimation of mean and standard deviation. Ideally, a 

minimum of six actual values would have been implemented, but the four actual value cut-off was used to increase the number of paired

observations.
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T ABLE 38. Crop Policy Counts 

Crop Policy Count

Organic Conventional

Wheat 460 245,394

Soybeans 407 400,818

Corn 380 429,109

Apples 173 9,419

Oats 93 13,818

Grapes 70 26,608

Pears 64 6,633

Barley 56 29,229

Flax 51 3,621

Millet 40 5,087

Almonds 38 13,084

Rice 37 2,528

Plums 32 3,259

Dry Beans 31 10,069

Sunflowers 30 17,458

Cotton 28 23,719

Grain Sorghum 25 11,767

Table Grapes 22 3,964

Tomatoes 19 2,051

Fresh Apricots 16 187

Fresh Freestone Peaches 15 2,046

Navel Oranges 14 7,747

Fresh Nectarines 14 1,855

Walnuts 14 1,980

Valencia Oranges 10 4,545

Potatoes 10 2,532

Processing Apricots 9 142

Forage Production 8 976

Peanuts 8 1,181

Avocados 6 3,509

Figs 6 407

Onions 5 595

Processing Cling Peaches 4 649

Prunes 4 1,021

Fresh Market Tomatoes 4 12

Rye 4 9

Peaches 3 91

Cultivated Wild Rice 3 36

Dry Peas 3 1,422

Lemons 2 504

Mandarins 2 31

Sugar Beets 2 241

Cranberries 2 947

Minneola Tangelos 1 219

Macadamia Nuts 1 32

Sweet Corn 1 311

Popcorn 1 346

Safflower 1 416

Source: The Contractor’s Rating Department using RMA data.
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Figure 23 indicates which counties in the Type 15 dataset contained an organic policy with at 

least four years of reported actual yields.

FIGUR E 23. Yield Data All Observations County Map* 

* Figure 23 shows a map of the Unites States divided into states and then subdivided into counties. Counties 

containing at least one organic policy with at least four years of reported actual yields are colored green. California 

has the largest land area colored green. Iowa has the largest number of counties colored green. States west of the 

Mississippi River, except Arkansas, Nevada, and New Mexico all have at least one, county colored green, while east 

of the Mississippi River, only Illinois, Indiana, Michigan, Mississippi, New York, Ohio, Pennsylvania, and 

Wisconsin have at least one such county.

Source: The Contractor’s Rating Department using RMA data. (Figure 23 Data)

A specific policy will be in both conventional and organic datasets for a given crop year if the 

policy had both types of production and sufficient historical observations. 

Historical Experience Data

The Type 11 and 21 files are joined to merge indemnity, liability, and premium information at 

the unit level and then aggregated so insurance experience can be evaluated at a policy 

(enterprise unit) level. Organic records were extracted from the 2001 through 2008 Type 11 files. 

In all, 32,384 organic records were found99

 

99 Numbers of records do not match numbers from the Type 15 files since not all units in the Type 15 file are reported for insurance.

. Conventional (non-organic) yield records were also 

extracted for matching county/crop/year combinations and added in with the organic records 

with the two being flagged separately. For conventional, roughly 6.0 million records were found. 
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Type 21 indemnity records were also gathered for all county/crop/year combinations found in the 

organic records. Records were flagged as organic based on the same criteria as the Type 11 

records. There were 10,427 organic records and just under 1.2 million conventional records. At 

this point, all units with both organic and conventional records in the same year at the type and 

practice level were eliminated from the Type 11 and Type 21 dataset due to an issue that can 

arise when a loss occurs for such a unit (a record is in effect a component of a unit). There is no 

allowance that permits organic practice to be defined as a unit separate from the non-organic 

practice. In addition, there is no requirement the production to count on any particular record be 

tagged identically to a quantity insured. Therefore, when a loss occurs and the loss adjuster often 

times has only a total quantity of harvested production, the production to count must be allocated 

to the multiple Type 11 records. This process introduces the possibility for error. Any Type 21 

organic record from a unit with conventional acreage may contain conventional data also. Thus, 

there is no certainty whether the loss data on a record with an organic code really is limited to the 

production from the organic acreage. However, for units comprised entirely of either 

conventional or organic production records, there is a high degree of certainty the corresponding 

production to count is from the same production method. In total, 3,628 records were eliminated 

from the Type 11 data with 1,589 being coded organic and 2,039 being coded as conventional. 

From the Type 21 data, 592 records were eliminated with 263 being coded as organic and 329 

being coded conventional. The raw Type 11 and Type 21 records formed the basis of the policy 

loss data. In this context, a policy was defined to include crop, crop year, insurance plan, type, 

practice, and coverage level. Organic units and/or organic acreage within a policy were 

segregated from conventional units/acreage. 

Policy-level (including crop, year, plan, type, practice, and coverage level) acreage, liability, and 

premium were calculated from the Type 11 records while policy-level indemnity was calculated 

from the Type 21 records. The policy-level Type 11 data was then joined to the policy-level 

Type 21 data. The resultant data was a policy loss record flagged as conventional or organic 

including policy acreage, liability, premium, and indemnity. If a policy had both conventional 

and organic units, it would be in the data twice with the production methods segregated. Loss 

ratios (indemnity/premium) and loss cost ratios (indemnity/liability) were also calculated. 

Once the policy-level loss records were calculated, policies (including crop, year, plan, type, 

practice, and coverage level) with both organic and conventional data were identified and subset. 

The total number of policies with both organic and conventional data was 2,820. 

Policies identified from Type 11 data as having both conventional and organic production in a 

given crop year were used to develop a subset of the Type 15 yield history files to create the 

paired yield history dataset. Policies included in the paired yield dataset were also merged so the 

paired observations had historical yields reported from the same years. For example, the crop 

year 2008 yield history file included a policy with multiple units where at least one unit was 

conventional and at least one unit was organic. After separation of the unit data into the 

conventional and organic data and aggregation to the policy level, the policies in each file are 

required to have reported at least four years of data and to have reported for the same years. If 

the conventional aggregated unit(s) had records for 2002 through 2007 but the organic 

aggregated unit(s) only had records for 2003 through 2007, the 2002 conventional observation 

was dropped in the paired dataset. 
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110

Figure 24 illustrates which counties had policies with both conventional and organic units as well 

as having both units report at least four years of actual yields.

FIGUR E 24. Yield Data Paired Observations County Map* 

* Figure 24 shows a map of the Unites States divided into states and then subdivided into counties. Counties 

containing at least one policy with an organic unit reporting actual yields and a non-organic unit reporting actual 

yields in the same year for the same crop? are colored green. California has the largest land area colored green 

followed by Washington. Only 53 counties have at least one or more such policies, including counties in California, 

Idaho, Illinois, Iowa, North and South Dakota, Minnesota, Michigan, Missouri, Nebraska, New York, Ohio, Oregon,

Texas, Washington, and Wisconsin. 

Source: The Contractor’s Rating Department after RMA data. (Figure 24 Data)

The next section discusses the methods used to evaluate the yield and loss experience datasets to 

determine if conventional and organic have significant, consistent, and systemic differences in 

production risk. 

V .C. Actuarial Methods

Yield variability is evaluated by looking at the temporal variability of paired historical 

observations as well as the pooled risk across producers in a risk region for a particular crop. 

Loss experience data are evaluated by looking at the typical loss ratio for conventional and 

organic producers for a given crop in a given state and the frequency and severity of loss as well 

as the relative loss amounts given both the conventional and organic units had a loss for a given 

policy. The analysis is based on confidence intervals derived from the empiric data. The 

distributions evaluated in this analysis tend to be strongly non-normal. Some distributions are 
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censored at zero and positively skewed (median < mean). Due to non-normality, standard 

confidence interval tests may not produce reliable results. The APH premium rates are a function 

of expected temporal variability. Therefore, comparing temporal variability is relevant as an 

element of this analysis. Incorporating information about localized historical weather variation 

into this analysis is beyond the scope of this project. The next section discusses how confidence 

intervals on the non-normal datasets were performed. 

Confidence Interval Estimation Procedures

Confidence intervals on the non-normal datasets were estimated through a log-transform on the 

original data X where Y = log(X).100

E X[ ] = θ

The data are log-transformed and a confidence interval is 

estimated for the transformed distribution mean and the confidence interval is then backtransformed (anti-log) to form an interval for the original dataset. Let , 

E XY   log ( ) =   , and the sample variance of Y be 2

s .

101 The confidence interval for log ( ) θ is 

estimated as

( )

2 24

2 21

s ss Y z

n n

+ ±⋅ + α − (V.C.1) 

where z is the area under the standard normal distribution with α significance.102

X(1)

The log-normal 

transformation is used to improve confidence interval estimates given left censored, positively 

skewed datasets. Another approach which minimizes the influence of outliers is focusing on the 

distribution median rather than the mean. The median is the point at which 50 percent of 

observations are greater than the value. Order statistics can be used to form a robust, nondistribution specific, and computationally straight forward confidence interval about the median. 

Assuming the data are independently and identically distributed, an exact confidence in an 

interval about the median can be determined. Sort the data such that is the smallest 

observation and X(2) is the next smallest etc.

(1) (2) ( ) , ,..., XX X n (V.C.2) 

The probability the median, θ , is between the th k observation from each end of the distribution is 

( ) 1 1 ( ) ( ) ( ) 1 Pr X X Pr X Pr X k n k k n k θ θθ + − + −  ≤ ≤ =− < − >          (V.C.3) 

 

100 The standard confidence interval around a sample mean, assuming normality, is calculated as / 2 x z

n α

σ ± ⋅

101 Recall [ ]

[ ] [ ] ( ) 2

Var Y

E Y

EX e

+

=

102 The confidence interval estimation procedures were taken from “Confidence Intervals for the Mean of a Log-Normal Distribution” by Ulf 

Olsson, published in the Journal of Statistics Education Volume 13, Number 1 (2005), www.amstat.org/punlications/jse/v13n1/olsson.html
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The component Pr X( ) k 1 θ +   <  is the probability that there are no more than k observations less 

than the median. Since the median is the 50th percentile Pr X( ) k 1 θ +   <   can be re-written as a 

binomial cumulative distribution function with the probability of success equal to one half. A 

confidence interval defined by the k + 1 and n – k observations has confidence level equal to 

1 1 2 , ,0.5 2n Binomial k  − − ⋅     (V.C.4) 

where Binomial is the binomial distribution function. The result is a confidence interval with an 

exact confidence level which is distribution independent. The implementation of the confidence 

interval procedures for the yield history data analysis is discussed next.

Yield Variability Analysis

Yield variability among the paired observations is evaluated by looking at the ratio of organic to 

conventional temporal yield variability. The null hypothesis is the expected value of the temporal 

standard deviation ratio is equal to one. Empiric data are used to form a 95 percent confidence 

interval around the sample mean ratio. If the confidence interval includes 1, then the null 

hypothesis cannot be rejected. In addition, if the median of the distribution is not significantly 

different from one, this implies half the observations show a ratio less than one and half show a 

ratio greater than one. A median equal to one indicates the ratios are not consistent. Yield 

variability among all observations is evaluated by first decomposing producer-level variability, 

then pooling producer residuals by crop and RMA risk region and testing for variance 

homogeneity between each group, and finally evaluating the distribution of variance ratios across 

groups. 

The RMA APH continuous rating function, which does not assume yields are normally 

distributed, has a non-zero negative exponent, which means premium rates are inversely related 

with yield magnitude. This result is consistent with expected temporal standard deviation of 

yields being independent of expected yield. Previous research by the Contractor has also found, 

for commodity crops in major production areas, standard deviation tends to be independent of 

expected yield.103 Therefore, if organic and conventional have similar expected temporal 

standard deviations, regardless of whether the mean yield (and therefore coefficient of variation) 

is the same, it is likely a rate difference of zero is appropriate because the continuous rate 

function presumably handles changes in risk due to differences in expected yield.

The procedures for evaluating temporal standard deviation differ by dataset. For the paired 

dataset (recall the paired dataset includes historical yield observations for both conventional and 

organic acreage insured under a common policy) the ratio of organic and conventional standard 

deviations is estimated for each policy. If 100 policies were identified with both conventional 

and organic units with at least 4 years of historical data, there would be 100 temporal standard 

deviation ratios. The all observations dataset variance comparison is performed by pooling 

policy-level residuals at the crop/risk region level and comparing the variability between 

 

103 In some arid areas there are substantial differences in variability and expected yield between dryland and irrigated acres.
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conventional and organic production methods as well as looking at the distribution of the ratio of 

the variances across state/crop combinations. Comparisons between production methods are 

performed using relative measures (i.e., ratios) to reduce the obfuscation of absolute differences 

due to the spatial and cross-crop aggregation. Modeling differences would be less problematic 

statistically than comparing ratio, but would force conclusions to be drawn from substantially 

smaller sample sizes, because spatial and cross-crop aggregation would be inappropriate in these 

comparisons due to disparities in yield magnitude.

Summary statistics for the paired dataset, including expected yield ratios, are provided in Tables 

39 though 41. Each observation is a policy which had two or more units and at least one unit was 

coded as organic and at least one unit was coded as conventional. Additionally, at least four 

years of actual yield observations from the same years were required for the conventional and 

organic units after aggregation to the policy level. The standard deviation ratios are presented as 

organic divided by conventional (Table 39) and as conventional divided by organic (Table 40). 

T ABLE 39. Paired Observations Standard Deviation Ratio (Organic/Conventional) 

Summary Statistics 

Year Minimum 1st 

Quantile MedianMean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

2001 0.989 0.993 0.998 0.998 1.002 1.007 0.013 2

2002 0.813 1.006 1.174 1.121 1.243 1.368 0.216 5 

2003 0.260 0.880 1.015 1.102 1.276 2.449 0.496 29

2004 0.097 0.744 1.048 1.264 1.740 3.438 0.862 34

2005 0.271 0.847 0.976 1.249 1.730 3.011 0.808 12

2006 0.214 0.725 0.953 1.263 1.606 2.961 0.870 13 

2007 0.636 0.868 1.129 1.190 1.408 2.450 0.493 14

2008 0.427 0.855 1.051 0.984 1.154 1.347 0.293 8

All Years 0.097 0.813 1.016 1.184 1.350 3.438 0.673 117

Source: The Contractor’s Rating Department using RMA data.
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T ABLE 40. Paired Observations Standard Deviation Ratio (Conventional/Organic) 

Summary Statistics

Year Minimum 1st 

Quantile Median Mean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

2001 0.993 0.998 1.002 1.002 1.007 1.011 0.013 2

2002 0.731 0.805 0.852 0.922 0.994 1.230 0.197 5 

2003 0.408 0.784 0.986 1.142 1.136 3.848 0.712 29

2004 0.291 0.575 0.954 1.627 1.345 10.300 2.096 34

2005 0.332 0.579 1.024 1.260 1.181 3.689 1.029 12

2006 0.338 0.623 1.049 1.310 1.379 4.665 1.157 13 

2007 0.408 0.711 0.891 0.965 1.153 1.572 0.355 14

2008 0.743 0.868 0.953 1.144 1.177 2.342 0.519 8

All Years 0.291 0.741 0.985 1.281 1.230 10.300 1.305 117

Source: The Contractor’s Rating Department using RMA data.

Notice the median value for all years in Tables 39 and 40 show organic production to be more 

variable than conventional while the mean value for all years shows organic to be more variable 

in Table 39 and conventional to be more variable in Table 40. The discrepancy in the mean value 

is due to the effect of positive tail outliers when a ratio truncated at zero is being evaluated. 

Confidence interval tests performed using all years of data and the summary statistics of the log 

transformed data are provided in Table 41. 

T ABLE 41. Log-Transformed Data Summary Statistics – Paired Yield Data

Minimum 1st 

Quantile MedianMean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

Organic -2.332 -0.207 0.016 -0.001 0.300 1.235 0.631 117

Conventional -1.235 -0.300 -0.016 0.001 0.207 2.332 0.631 117

Source: The Contractor’s Rating Department using RMA data.

The log-transformed confidence intervals for the organic to conventional and conventional to 

organic standard deviation ratios using all years of data are calculated as

( ) ( )

2 24 0.631 0.631 0.631 0.001 1.96 0.323,0.073 2 117 2 117 1

− + ±⋅ + = − (V.C.5) 

and 

( ) ( )

2 24 0.631 0.631 0.631 0.001 1.96 0.325,0.075 2 117 2 117 1

+ ±⋅ + = − (V.C.6) 

The anti-log of the confidence intervals produces intervals of (1.08, 1.38) which imply that the 

expected ratios are significantly different from 1.0 at a 95 percent confidence level. The results 
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directly conflict each other. With organic in the numerator it appears the organic standard 

deviation is significantly greater than the conventional but the results are the opposite when 

organic is in the denominator. Thus, due to the difficulty of modeling ratios, the log-transform 

might not suitably address the non-normality of the dataset. The Contractor investigated a 

number of alternative approaches and determined, in light of the available data, that the logtransformation was the most appropriate technique despite its shortcomings. 

The median values of the distribution are consistent and show a slight increase in variability for 

organic production. A non-parametric, distribution free estimate of the confidence intervals 

around the median values are calculated by finding the th k and ( )th n k − values which define a 

roughly 2.5 percent upper and lower tail. With organic in the numerator, a 95.85 percent 

confidence interval around the median of the all data sample is (0.981, 1.095), and with 

conventional in the numerator, the 95.85 percent confidence level is (0.913, 1.019). Both 

intervals indicate the median standard deviation ratio is not different from 1.0 with 95 percent 

confidence regardless of which production method is in the numerator. These results are 

consistent with each other and indicate that half the population of organic producers with both 

conventional and organic units experience higher variability on their organic acreage while half 

experience higher variability on their conventional acreage.

The ratio of mean yields for the paired dataset is provided in Table 42. 

T ABLE 42. Paired Observations Average Mean Yield Ratio (Organic/Conventional) 

Summary Statistics

Year Minimum 1st 

Quantile Median Mean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

2001 0.970 1.002 1.034 1.034 1.066 1.098 0.091 2 

2002 0.922 0.958 0.972 0.990 1.043 1.053 0.057 5 

2003 0.512 0.732 0.897 0.913 0.979 2.214 0.332 29 

2004 0.456 0.785 0.959 1.103 1.359 2.887 0.514 34 

2005 0.258 0.529 0.852 0.819 1.066 1.446 0.390 12 

2006 0.305 0.634 1.018 0.960 1.095 1.586 0.374 13 

2007 0.128 0.745 0.942 0.835 1.014 1.114 0.284 14 

2008 0.571 0.943 1.046 1.036 1.117 1.508 0.267 8 

All Years 0.128 0.769 0.946 0.968 1.085 2.887 0.394 117 

Source: The Contractor’s Rating Department using RMA data.

The paired data mean yield ratio summary statistics indicate organic tends to have lower yield 

than conventional but the 95 percent confidence interval around the mean for all years, 

calculated as

0.968 1.96 0.394 0.196,1.74 ±⋅ = ( ) (V.C.7) 

indicates the ratio of mean yields is not significantly different from 1. The confidence interval 

assumes the underlying data are normally distributed, which is not the case for the mean ratio 
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data. However, the confidence interval is so wide (due to variability) it is very likely improved 

confidence interval estimation procedures would still fail to reject the null hypothesis that the 

expected mean ratio is equal to 1.

Yield variability among all observations is evaluated by first decomposing producer-level 

variability then pooling producer residuals by crop and RMA risk region and testing for variance 

homogeneity between each group; then evaluating the distribution of variance ratios across 

groups. The Type 15 data include observations from the crop years 2001 through 2008. Since the 

same historical yield will be included for multiple crop years, e.g., the 2001 observation being 

included in the 2002 through 2008 yield history files, exact duplicates are removed from the 

datasets. Duplicates are identified by reporting organization, company, policy number, crop 

identification, state, county, type, practice, organic flag, and aggregated yield and acreage. 

Approximately 25 percent of the total yield observations were removed as duplicates. 

Producer yield variance is decomposed into two components: (1) regional variability, and (2) the 

remaining or residual farm-level variability. The decomposition removes variability due to 

region-wide events such as drought or excessive rain which affect both conventional and organic 

production. By removing a common component, regional variation, the statistical tests are likely 

to produce more reliable results. The variance decomposition is accomplished by subtracting the 

county yield from the farm yield. This generates a deviation from the region yield, dt

f , for each 

farm f and for each year t in the RMA yield history dataset. Farm f’s average deviation from the 

region, d f , can then be calculated for each farm. These expressions can be presented 

mathematically as:

f fC

t tt d yld Yld = − (V.C.8) 

and

1

1 Tf f f C f

t

t f

d d yld Yld T == = − ∑ (V.C.9) 

The county yield is calculated as an acre weighted average across all producers (both organic and 

conventional) in the dataset. After constructing dt

f and d f , the remaining farm variability can 

be constructed as:

( )( ) ffC f f f C t t t t t e d d yld yld Yld Yld =−= − − − (V.C.10) 

The remaining farm residual, et

f , can be viewed as the difference between the farm’s deviation 

from its average yield ( )f f

t yld yld − and the county’s deviation from its average yield 

( ) C C t Yld Yld t − over the same time period. Each farm’s deviation from its mean is adjusted by the 

amount by which the county deviated from its average. The total variation in farm yields has 
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117

been decomposed into variation that occurred at the county level and the remaining farm-level 

variation around the county yields. 

Farm residuals are pooled by production practice, crop, and risk region. Bartlett’s test for 

variance homogeneity is used to test the null hypothesis that the variability between the groups 

(conventional and organic) is the same.104 The Bartlett’s test assumes the underlying data are 

normally distributed and is sensitive to departures from normality. That is, if the samples are 

from non-normal distributions, Bartlett's test may simply be testing for non-normality. However, 

the variance decomposition procedure has a substantial normalizing effect on the residuals. 

In order for a crop/risk region combination to be included, data from at least five organic 

producers was required. This resulted in 99 crop/risk region combinations. Of those, 57 had a 

significant difference (95 percent confidence level) between the variability of the pooled 

conventional and organic residuals. The 57 combinations with a statistically significant 

difference can further be subset by whether the organic or conventional had the larger variability. 

Roughly half the combinations had a greater variability among the organic pooled residuals. 

These general results tend to hold as more organic producers were included in a given crop/risk 

region combination in order to be included in the analysis. When at least 20 organic producers 

are required, there are 10 combinations, 6 of which have a statistically significant difference in 

variability. Four show a larger conventional variability and two show a larger organic variability. 

A results summary is provided in Table 43. 

Table 43. Variance Homogeneity Test Results

Minimum 

Number of 

Organic 

Policies

Crop/Risk 

Region 

Combinations 

Number of Combinations 

with Significant 

Differences (95% 

Confidence) 

Conventional 

Variability

Significantly 

Greater

Organic 

Variability

Significantly 

Greater

5 99 57 27 30

10 40 24 13 11

15 22 14 8 6 

20 10 6 4 2

Source: The Contractor’s Rating Department using RMA data.

The variance homogeneity tests clearly indicate there is not a systemic or consistent difference in 

variability between conventional and organic production. Another approach to looking at the 

pooled dataset is to evaluate the distribution of the variance ratios across crop/risk region 

combination. For the group of crop/risk regions with a minimum of 5 organic policies there are 

99 variance ratios. The variance ratio distribution is estimated twice: once with organic in the 

numerator and then again with organic in the denominator. Summary statistics are provided in 

Table 44. 

 

104 Snedecor, George W. and Cochran, William G. (1989), Statistical Methods, Eighth Edition, Iowa State University Press.
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Table 44. Variance Ratio by Crop and Risk Region Summary Statistics 

Variance Ratio (Conventional/Organic)

Minimum 

Number of 

Organic 

Policies

Minimum 1st 

Quantile Median Mean 3rd Quantile Maximum Standard Deviation

5 0.252 0.632 1.005 1.246 1.381 9.910 1.193

10 0.333 0.665 1.012 1.175 1.354 5.649 0.916 

15 0.333 0.823 1.043 1.120 1.337 3.132 0.649

20 0.414 0.881 1.089 1.295 1.276 3.132 0.859

Variance Ratio (Organic/Conventional)

Minimum 

Number of 

Organic 

Policies

Minimum 1st 

Quantile Median Mean 3rd Quantile Maximum Standard Deviation

5 0.101 0.724 0.995 1.219 1.582 3.966 0.762

10 0.177 0.739 0.988 1.198 1.505 3.002 0.683

15 0.319 0.748 0.960 1.214 1.215 3.002 0.755 

20 0.319 0.784 0.918 1.117 1.142 2.414 0.730

Source: The Contractor’s Rating Department using RMA data.

The results are similar to those seen in Tables 39 and 40. The median of the distributions 

consistently show conventional production tends to be more variable but the means of the 

distributions contradict each other. The yield variability analysis did not produce consistent 

results; in one case implying conventional production is more variable than organic and in the 

other that organic is more variable than conventional. As noted earlier, modeling differences 

would be less problematic statistically than modeling ratios, but would force conclusions to be 

drawn from substantially smaller sample sizes, because spatial and cross-crop aggregation would 

be inappropriate. Loss experience analysis is discussed next.

Loss Experience Analysis

The paired insurance experience data are used to compare the loss ratio of conventional and 

organic units insured under the same policy. The datasets are parsed to evaluate the frequency 

and severity of indemnity payments across all units based on production method and to compare 

loss ratios when both units (conventional and organic) under the policy receive an indemnity 

payment in a given year. The analysis of the “all observation” loss history data looks at 

differences in expected loss ratios (organic loss ratio – conventional loss ratio) across crop and 

state combinations.

Paired data look at frequency and severity (relative to premium rate) of indemnity payments. 

There are 2,819 total paired observations. The frequency of an indemnity payment (LR > 0) for 

conventional and organic production methods are 0.398 and 0.319, respectively. Units insured as 

conventional are more likely to have received an indemnity payment between 2001 and 2008 
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relative to organic acreage grown by the same insured. The severity of indemnity payments, 

average loss ratio given the loss ratio was greater than zero, are 3.717 and 3.092 for conventional 

and organic, respectively. This means the expected indemnity amount is greater for conventional 

(measured as a percent of premium) than for organic. Another pertinent statistic is the percentage 

of organic/conventional units that had an indemnity payment when the paired 

conventional/organic unit also had an indemnity payment. The percent of organic observations 

receiving an indemnity when their paired conventional observation experienced a loss was 0.547 

and the percentage of conventional observations experiencing a loss when their paired organic 

observation received an indemnity payment was 0.681. These percentages are consistent with 

conventional having an overall higher indemnity frequency when grown by the same producer 

under presumably the same environmental conditions. 

The Contractor compared loss ratios for paired observations where both the conventional and 

organic observations had a loss. Summary statistics for the ratio of loss ratios (relative loss ratio) 

are provided in Table 45 and a scatter plot of the paired loss ratios is presented in Figure 25. 

T ABLE 45. Paired Loss Experience Relative Loss Ratio Summary Statistics 

(Organic/Conventional) 

Minimum 1st 

Quantile Median Mean 3rd Quantile Maximum Standard Deviation

Number of 

Observations

0.018 0.613 1.053 2.956 2.294 106.700 7.591 614 

Source: The Contractor’s Rating Department using RMA data.

The median of the relative loss ratios is approximately 1.0 while the mean of the distribution is 

substantially greater. In this case, greater than the 3rd quantile (75th percentile), indicating a 

heavily skewed distribution. The blue line in Figure 25 is a 45 degree line and observations 

located on that line had an organic loss ratio equal to the conventional loss ratio. If the data point 

lies above the blue line the organic observation had a greater loss ratio than the paired 

conventional observation. 
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FIGUR E 25. Loss Ratio Scatter Plot* 

* Figure 25 shows a scatter diagram of loss ratios for paired observations where both the conventional and organic 

observations had a loss. Most of the values fall below 5,5. Only about 25 of the more than 600 values are above 10 

for either the conventional or organic production. The median of the loss ratios is approximately one.

Source: The Contractor’s Rating Department using RMA data. (Figure 25 Data)

Outliers on both sides of the blue line in Figure 25 can be seen. A histogram of the relative loss 

ratios is provided in Figure 26. 
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FIGUR E 26. Relative Loss Ratio Histogram* 

* Figure 26 shows a histogram of the relative loss ratios for paired observations where both the conventional and 

organic observations had a loss. The histogram was truncated at a value of five to eliminate distortion of the plot 

from individual outliers with higher relative values. The histogram peaks for the class with relative values between 

0.8 and 1.0. The tail beyond a loss ratio value greater than 2.0 generally has values less than one fifth the value of 

the peak class value.

Source: The Contractor’s Rating Department using RMA data. (Figure 26 Data)

The heavily skewed distribution indicated by the summary statistics in Table 43 can be seen in 

Figure 29. To perform hypothesis tests on the mean, the data were log-transformed and 

additionally, the inverse of the ratio (conventional/organic) was tested. Summary statistics for the 

log-transformed relative loss ratios are provided in Table 46. 
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Table 46. Log-Transformed Data Summary Statistics – Paired Experience Observations

Numerator Minimum 1st 

Quantile MedianMean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

Organic -4.010 -0.490 0.051 0.179 0.830 4.670 1.238 614

Conventional -4.670 -0.830 -0.051 -0.179 0.490 4.010 1.238 614

Source: The Contractor’s Rating Department using RMA data.

Organic numerator anti-log confidence interval around the mean is (2.259, 2.93) and the 

conventional numerator anti-log confidence interval is (1.579, 2.048). These results contradict 

each other. The confidence interval about the median is (0.8725, 1.004) with conventional in the 

numerator and (0.9957, 1.146) with organic in the numerator. The tests do not provide evidence 

of a systemic, consistent, or significant difference in loss history. 

The all observations experience data were evaluated by examining the loss ratio from 2001 

through 2008 for conventional and organic practices at the crop/state level. Indemnities and 

premiums were summed across all observations by crop, state, and production practice. The 

difference in loss ratio between conventional and organic for each state/crop combination then 

was pooled and evaluated. In order for a state/crop combination to be included in the analysis, a 

minimum number of organic observations was required. Results were evaluated with the 

minimum sets of 5, 10, 25, and 50 observations. Summary statistics are provided in Table 47. 

Table 47. Summary Statistics for Loss Ratio Differences

Minimum Number 

of Organic Policies Minimum 1st Quantile MedianMean 3rd Quantile Maximum Standard Deviation

Number of 

Observations 

5 -4.071 -0.325 0.068 0.146 0.572 3.766 0.925 199

10 -4.071 -0.306 0.133 0.136 0.586 3.766 0.903 156

25 -1.405 -0.207 0.145 0.200 0.550 3.416 0.685 98

50 -1.126 -0.208 0.228 0.226 0.584 3.416 0.654 69 

Source: The Contractor’s Rating Department using RMA data.

Summary statistics presented in Table 47 indicate the distributions of loss ratio differences are 

reasonably symmetric (normality in all cases is strongly rejected by Anderson-Darling and 

Cramer-von-Mises tests) and standard confidence intervals around the mean indicate the means 

are not significantly different from zero in all cases. Figure 27 presents a histogram of the 

differences for the group with five or more organic policies in each state/crop combination. 
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Figure 27. Loss Ratio Difference Histogram* 

* Figure 27 shows a histogram of the loss ratio differences for each state/crop combination for the group with five or 

more organic policies for the state/crop combination. The distribution of loss ratio differences is relatively 

symmetric although not normal by Anderson-Darling and Cramer-von-Mises tests. Standard confidence intervals 

around the mean indicate the mean is not significantly different from zero. 

Source: The Contractor’s Rating Department using RMA data. (Figure 27 Data)

Analysis of the paired experience data indicate units without organic codes (conventional units) 

in paired observations were more likely to receive an indemnity payment and the average 

payment (measured as a percentage of the premium), given a payment was received, was higher. 

However, when both paired observations received an indemnity payment, the 50th percentile of 

that distribution indicated the payments were not significantly different. Furthermore, analysis of 

all observations shows organic to have a slightly higher loss ratio but the difference is not 

statistically significant.
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V .D. Concluding Remarks

The paired dataset is the preferred dataset for hypothesis testing since the observations are grown 

under presumably the same conditions, in the same year, in presumably relatively close

locations. The ‘all observations’ dataset is less reliable due to the generally large discrepancy 

between the number of producers growing conventional and the number of producers growing 

organic for a given crop/region combination. Exact confidence intervals require information 

regarding the underlying distribution, which is not known; hence the Contractor used accepted 

procedures to form intervals and acknowledges the reported intervals reflect those procedures 

more than any attribute of the data itself. However, the Contractor believes the confidence 

intervals are reliable enough to fail to reject the null hypothesis that production risk differences

are statistically significant, and found little evidence supporting suggestions they are consistent, 

or systemic.

The paired yield data tests were performed on the median values of the distributions and 

indicated there is no consistent difference in temporal standard deviation. The all observation 

yield data analysis utilized Bartlett’s test of variance homogeneity and while the test 

demonstrated statistically significant differences in production risk, the differences showed 

conventional as more variable as often as they showed organic being more variable. Again, no 

consistent result was found. The paired loss ratio dataset showed conventional paired 

observations were more likely to receive an indemnity payment and the average payment 

(measured as a percentage of the premium), given a payment was received, was higher. 

However, when both paired observations received an indemnity payment, the 50th percentile of 

that distribution indicated the payments were not significantly different. Furthermore, analysis of 

all observations shows organic to have a slightly higher loss ratio, but the difference is not a 

statistically significant difference.

Currently, RMA typically uses a multiplicative load of 1.05 on organic contracts (there are a few 

minor exceptions) and it is important to note the analysis presented in this section did not directly 

test if 1.05 is appropriate. Furthermore, it should be noted the failure to reject the null hypothesis 

that production risks are the same does not imply that 1.05 is an actuarially unsound value. Based 

on the currently available data, it is not possible to develop an appropriate multiplicative 

adjustment rate factor that applies to all organic crops using a statistically rigorous approach. 

Further study is recommended as more data become available.
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SE CT ION VI. DISCUSSION

The Food, Conservation, and Energy Act of 2008 called for “a review of the underwriting, risk, 

and loss experience of organic crops covered by the Corporation and loss experience of organic 

crops covered by the Corporation, as compared with the same crops produced in the same 

counties and during the same crop years using nonorganic methods.” It specifies the review shall 

“to the maximum extent practicable, be designed to allow the Corporation to determine whether 

significant, consistent, or systemic variations in loss history exist between organic and nonorganic production.” Section 12023 of the Food, Conservation, and Energy Act further required 

RMA to contract for “a review of the underwriting, risk, and loss experience of organic crops 

covered by the Corporation, as compared with the same crops produced in the same counties and 

during the same crop years using nonorganic methods” RMA awarded Contract Number AG645S-C-09-0003 to address the review identified in the Food, Conservation, and Energy Act. 

In this report, the Contractor was charged with evaluating currently available data and 

their application to the rating paradigm currently used for organic crops. Specifically, the 

Contractor was required to 

• Provide RMA a risk analysis for organic producers that can be used to establish a risk 

relationship between organic and conventional practices (Statement of Work Section 

5.4.1.2.1.); 

• Include yield relationships between organic and conventional practices (Statement of

Work Section 5.4.1.2.2.); 

• Present, discuss, and defend the yield differential that merits establishment of a separate 

APH database (Statement of Work Section 5.4.1.2.3.); and

• Identify collectable information that would be beneficial for future annual reports which 

may be used to refine the risk relationship between organic and conventional practices as 

more data is collected (Statement of Work 5.4.1.2.4.); 

The Contractor conducted an analysis of the underwriting, risk, and loss experience of organic 

crops covered by FCIC as compared with the same crops produced in the same counties and 

during the same crop years using non-organic methods. The Contractor explored a wide variety 

of mechanisms to consider the risk and loss experience in the context of the underwriting 

requirements for the organic production. The review includes an extensive evaluation of the 

experience data accumulated by RMA.

The review exposes some challenges in analyzing the insurance experience data comparing 

organic and conventional commodities, either collectively or on an individual crop basis. In most 

cases, where patterns might have been thought to exist, it was also possible to identify significant 

exceptions to those patterns. With the limited data available, artifacts of aggregation and of 

sampling have the potential to lead to potentially dangerous generalizations. 

The Contractor also conducted a rating review using data for conventional and organic 

production in the same counties. Data used to test the null hypothesis that organic and 

conventional production are confronted by the same insurance risk (expected loss) in a given 

locale were gathered from RMA Type 11, Type 15, and Type 21 datasets from crop years 2001 

through 2008. The experience and yield datasets were grouped by policy into a set of paired 

observations and a set of all observations. The paired dataset allows outcomes from acreage 
Organic Crops: Revised Written Rating Report 

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126

insured under the same policy, which is presumably located relatively close together and 

otherwise managed similarly, but grown under both conventional and organic methods to be 

directly tested. The paired dataset is the preferred dataset for the analysis. However, the 

existence of policies with units managed under organic practices and units managed under nonorganic practices raises the question: “Why would a producer manage a crop under both 

practices?” It is possible the producer is not convinced organic farming would save on input 

costs, increase revenues, or provide appropriate risk management. It is also possible there are

differences in the land itself or crops grown nearby that effect this behavior. The producer may 

be new to organic production, which would increase the risk to the organic crop, or may have 

planted the conventional crop on marginal land, which would increase the risk to the 

conventional crop. Or, the behavior may simply recognize that the market for organic products is 

small and production using non-organic methods is a method for reducing total revenue risk. 

Such differences support Lampkin’s contention that comparisons of organic and non-organic 

production are challenging at best.105 Unfortunately, the breadth of the paired dataset is limited. 

The second grouping includes all units in a given county for each crop for which there was 

organic production. Attributes (mean and variance in the case of the yield dataset) were 

evaluated across all policies in order to compare “typical” organic production and “typical” 

conventional production. 

The results of the rating analysis do not provide sufficient evidence to reject the null hypothesis 

that organic and conventional production methods face the same insurance risk. There is not 

proof of a significant, consistent, and systemic difference in insurance experience or yield 

variability between organic and conventional production. The data indicate a wide range of 

relationships between conventional and organic production. The data are not robust enough to 

dig deep into specific situations for crop by crop or state by state results. The high degree of 

variability in the results leads to a failure to reject the null hypothesis statistically. 

RMA currently requires separate yield databases for organic and non-organic acreage but 

requires all acreage be insured within the same unit as defined by the Basic Provisions. However, 

the Basic Provisions require only that “[the insured] must: (1) Provide a complete harvesting and 

marketing record of each insured crop by unit including separate records showing the same

information for production from any acreage not insured.” The requirement is by unit, not by any 

characteristic that might affect the unit indemnity. Better data to evaluate the impact of the 

organic codes most likely will not be available until the system is converted to establish the 

organically certified or transitional acreage as a separate unit. When this is done, the data for a 

unit will clearly be distinguishable from other (non-organic) units. In the present system, acreage 

insured under an organic code may be commingled with acreage without such codes, and the 

utility of the experience data is compromised.

The organic surcharge is not appropriate for some crops insured under the Federal crop insurance 

programs. Table 32 includes several crops for which the loss ratio is zero for both organic and 

non-organic practice when compared in the same counties and years. In particular, damage to 

trees is not likely to differ materially between trees bearing a crop produced organically and trees 

 

105 Lampkin, N.H., 1994, Researching Organic Farming Systems, The Economics of Organic Farming, N.H. Lampkin and S. Padel, eds., CAB 

International, Wallingford, UK.
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127

bearing a crop produced non-organically. For example, the causes of loss stated in the Crop 

Provisions for Texas Citrus Trees are: 

(a) Excess precipitation;

(b) Excess wind;

(c) Fire, unless weeds and other forms of undergrowth have not been controlled or pruning 

debris has not been removed from the grove; 

(d) Freeze;

(e) Hail;

(f) Tornado; or 

(g) Failure of the irrigation water supply if caused by an insured peril or drought that occurs 

during the insurance period. 

The only justification for an organic surcharge for Texas Citrus Trees would be evidence that 

trees on acreage following organic practices are structurally weaker, or that organic producers 

are more likely to fail to clear weeds and other forms of undergrowth from the grove. The 

Contractor is not aware of any evidence supporting such a belief. Similar considerations should 

apply to other insured crops where the causes of loss are limited to very specific perils that occur 

rarely and are catastrophic when they do occur.

A universal surcharge for all organic production is not appropriate. The data demonstrate 

numerous instances in which the experience differs substantially among crops and states. 

Although experience in the aggregate displays higher losses for units with an organic code, there 

are many crops and many states where experience on units with organic practice is better than 

experience on non-organic units. This suggests the organic practice is not a consistent performer 

relative to non-organic practice. Surcharges, if deemed necessary, should be tailored to the 

state/crop combination, as can be supported by data. RMA should continue to apply its standard 

methodology for ratemaking to the organic practice data when evaluating rate adequacy. Any 

deviation from the Actuarial Procedures should be documented by an Addendum to that 

document so interested parties are aware of the process.

The Contractor and RMA agree the data for analyzing insurance performance for crops grown 

under organic practices at the county level are relatively thin, especially when compared to 

available data for crops produced under conventional practices; and both believe this pattern will 

not change substantially in the near future. 
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128

SE CT ION VII. R E COMME NDAT IONS

This section summarizes the detailed information in the report and organizes that summary

around the section of the contract calling for recommendations. The Contractor reviewed the risk 

and loss experience of organic commodities insured under RMA plans of insurance as compared 

with the risk and loss experience of the same commodities produced in the same counties and 

during the same crop years using non-organic methods. The Contractor’s review refutes the 

existence of significant, consistent, and systemic variations in loss history between organic and 

non-organic commodities on an individual crop basis. When data for all crops in all areas are 

aggregated, the collective insurance experience for organic production has been very different 

from the insurance experience for non-organic production over the observations captured in the 

available data. Although the data provide a noisy picture and are not well suited to aggregate 

analysis, the overall weight of the aggregate performance is too great to dismiss. 

The Contractor consequently considered approaches to develop a recommendation for actuarially 

appropriate rates based on the available data. Since the research refutes the existence of 

significant, consistent, and systemic variations in loss history between organic and non-organic 

commodities both collectively and on an individual crop basis, public policy precludes the option 

simply to maintain the existing surcharge.

Based on the Contractor’s research and analysis, it appears the organic insurance pool is subject 

to adverse selection by a subset of unusually high-risk producers. If the premium rates were 

raised by the value implied by the available aggregate data, the most likely outcome would be to 

assure this adverse selection would be exacerbated in future years, perpetuating and intensifying 

the current issues with the programs. It is clear from the literature and research completed for 

this report that issues such as pricing, reference yields, T-yields, and good farming practices need 

to be addressed collectively on a regional/crop basis, and cannot be addressed effectively until 

more representative data become available. 

The issues affecting loss performance in the organic program to date are more complex than a 

simple question of the appropriateness of rates or premium sufficiency. The report addresses the 

relationship of actual yields to reference yields by crop and for major crops by state, identifying 

a substantial range of discrepancies between the two variables. Obviously, this analysis also is 

data dependent; no conclusions can be reached if data are too sparse to support them. However, 

there are a number of examples that demonstrate the T-yields and reference yields are likely too 

high (or perhaps too low in certain circumstances). The data, while limited, are consistent with 

the findings of the literature review that there is no systemic and consistent relationship of 

organic to non-organic yields and yield variability. The analysis of the data and the literature 

review are compelling in one regard: there can be no consistent relationship of rates or of 

program yield components (reference yields and T-yields) for organic production relative to nonorganic production that applies to all crops and states. Blanket recommendations for all crops 

cannot be supported given the inconsistency of the data, and there are limited data to support 

specific recommendations for any given crop.

The Contractor notes again that the aggregate insurance performance of organic crops has been 

inferior to that of conventional crops. RMA has a statutory responsibility to maintain actuarial 

soundness of the crop insurance program. The data currently available are too sparse and noisy to 
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129

draw sound actuarial/statistical conclusions to support premium rate revisions at any acceptable 

level of aggregation. It is clear from the aggregate loss cost ratios and loss ratios that “organic” is 

different from “non-organic.” Unfortunately the data at less than national aggregate becomes 

very unstable. The organic and conventional experience comparison at the national crop level 

suggests considerable deviations from non-organic rates in many cases, with both substantial 

discounts and increases in the rates, if the data are to be believed. The Contractor does not 

believe such substantial departures from non-organic rates are justified, and does not believe the 

data is reliable enough or representative of the true underlying distributions to support these 

substantial deviations from rates for non-organic production. 

The Contractor notes that participation in organic coverage has shown steady growth in recent 

years. The Organic Survey will provide an important dataset for further analysis. If the Organic 

Survey yield data can substantiate the median yields evident in the experience dataset, reference 

and T-yields should be adjusted by crop/region as soon as practical. The additional experience 

data collected over the next two years is a second important data element. At the end of that 

period, it is likely rate adjustments for major crops in major production regions can be made 

using existing adjustment procedures by type/practice. Holding adjustments in abeyance during 

that period likely provides a least cost alternative for including “organic” in the safety net and at 

the same time supporting the collection of substantial data. 

Estimates of the ratio of the average actual yields certified by producers relative to the respective 

reference yields, by crop for all crops (Table 18) and by crop/state for those crops with the 

greatest number of observations (Tables 19 through 21) are provided. The reference yield is used 

since it is the basis of premium rates established for plan code 90 crops, which account for the 

majority of the organic experience. In both the aggregate and for the major crops insured with 

organic practice, the average of actual yields certified by producers is approximately 65 percent 

of the reference yield. There is substantial variation among states within crops and among crops 

as evidenced in this and other information contained in the report. Since the data at lower levels 

of aggregation is noisy and inconsistent, the remaining assessment focuses on the aggregate data 

contained in these tables.

The risk analysis clearly indicates inappropriate transitional yields are a significant source of the 

higher loss costs observed for the organic practice. About one-third of all unit type 15 records 

contained no actual yield (i.e., the guarantee is based solely on transitional yields), while a 

typical record containing any actual yields had at least one transitional yield. The average of the 

actual yields is lower than the reference yield, which is adopted as indicative of a “normal” yield 

for the non-organic practice. This observation addresses contract section 5.4.1.2.2 to address the 

yield relationships between the organic and conventional practices. 

These data also address contract section 5.4.1.2.3 in that they show yield differentials meriting 

establishment of separate APH databases for organic production currently exist. The average 

actual yield to date for the organic practice is lower than the reference yield by about one-third. 

Mixing of yields from organic and non-organic acreage within the same unit within the current 

reporting structure may have resulted in inappropriate average yields for both practices. Separate 

APH databases for organic production should address that issue. 
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130

The Contractor is not convinced the data reflect a consistent outcome that will exist for all time; 

merely that it exists currently. Hence, the Contractor recommends that, in the future, RMA 

continue to analyze and compare organic average yields with both the appropriate reference 

yields and the non-organic yields to determine if the relationship changes as producers become 

more adept at following organic processes and as the available inputs to sustain the practice 

change.

With regard to contract section 5.4.1.2.1 of the SOW, the Contractor makes five

recommendations, the first three of which specifically address the risk relationship. These 

recommendations were developed in the context of the data in aggregate by crop, a position that 

may be less supportable as the data are disaggregated to the state, risk region, and county levels. 

1. The Contractor recommends RMA impose no premium differential for crops for which 

the Crop Provisions specify a very limited set of causes of loss that clearly are 

independent of management or other variable circumstances, as well as all crop policies 

that are not based on individual coverage. For example, insured trees generally do not 

merit a premium differential. The Contractor was not able to identify any rationale or 

reasons why a tree grown with organic practices would not be able to withstand winds or 

be more susceptible to freeze than a tree grown with non-organic practices. These crops 

include those insurable under the Florida Citrus Fruit Crop Provisions (09-026); the 

Texas Citrus Tree Crop Provisions (99-025); the Macadamia Tree Crop Provisions (99-

024); the Nursery Crop Provisions (08-073); the Florida Fruit Tree Provisions (08-0014); 

the Hawaii Tropical Trees Pilot Crop Provisions (09-0265); all crops included under the 

Common Group Risk Plan (GRP), Basic Provisions. 09-102; all crops included under the 

Group Risk Income Protection Basic Provisions (05-GRIP-BASIC; and all acreage

included under the Pasture, Forage, and Rangeland programs. 

2. For the crops for which the guarantee is not based on APH procedures (dollar plans, etc.), 

the Contractor recommends RMA make no adjustments to rates until some threshold 

value of units is represented in the experience dataset. The Contractor recommends the 

threshold value be set at 500 organic units. For those crops for which the guarantee is 

not based on APH procedures and which meet the threshold, the Contractor 

recommends a premium differential (increase or decrease). Inasmuch as these plans do 

not use T-yields, the implicit differential (surcharge or discount) from Table 34 could be 

used initially as the initial rate differential, with further adjustment made as data permit. 

The crops included under this recommendation include all crops insurable under plan 

code 50 (Dollar Amount of Insurance); plan code 51 (Fixed Dollar Amount of 

Insurance); and plan code 55 (Yield Based Dollar Amount of Insurance). 

The Contractor further recommends the maximum reference amount of insurance for 

organic crops insured under plan codes 50 and 51 be reduced by one-third. The 

thresholds at which reductions in the guarantee are made under plan code 55 should be 

reviewed to determine if the “break-points” presently established are reasonably 

consistent with the one-third reduction on a county-crop basis. 
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131

3. As a result of the confounding effects of T-yields on insurance experience for crops 

whose guarantee is based on APH procedures, these crops need to be treated with an 

alternate approach. Regardless of the extent of the experience data, for plan code 25 

(Revenue Assurance); plan code 42 (Income Protection); plan code 44 (Crop Revenue 

Coverage); plan code 45 (Indexed Income Protection); and plan code 90 (Actual 

Production History) crops, the Contractor recommends transitional yields be reduced by 

35 percent. This recommendation is based specifically on the role T-yields have played 

in the experience data collected to date. In the short term, following this recommendation 

will result in continuing to use the same premium rating parameters as are established for 

non-organic practices. The effect of this will be to insure organic production at the same 

premium rate and cost as that charged for non-organic practices for the same yield. The 

Contractor believes it is critical that the transitional yields be reduced to a level consistent 

with the experience before any effort to adjust rates is made. This approach will sharply 

reduce the frequency and severity of losses for the organic practice and reduce loss ratios. 

It will also encourage participation with the consequent development of a richer, deeper 

dataset.

4. The Contractor further recommends the organic practice be established as a separate 

type/practice, as appropriate on the actuarial documents, to facilitate the reduction in the 

transitional yields. As data permit, on a continuing basis, other attributes of the insurance 

offer can be adjusted as experience indicates.

5. To achieve the greatest ability to accrue relevant data, Crop Provisions should be 

modified to allow organic practice as a separate insurance unit. Presently, if both organic 

and non-organic acreage are included within the same insurance unit (primarily because 

both are in the same section), there is a reasonable degree of doubt as to whether 

harvested production to count is assessed against the appropriate acreage within the unit 

on the Production Worksheet and hence on the type 21 record. In addition, the production 

from non-organic acreage may offset wholly or partially any losses on organic acreage 

(or vice-versa) such that the true risk relationship on such units cannot be identified. 

Organic acreage already can be designated as a separate optional unit in certain 

circumstances such as planting in a different section than plantings of non-organic 

acreage. There is no reason to restrict producers who happen to have acreage of both 

practices within the same section.

Based on the data guidelines provided in the contract, external data are much less likely to 

inform insurance program adjustments than are experience data generated by the program. 

Accordingly, information collected for such adjustments will be largely controlled by RMA

regulations, policies, and procedures. Nonetheless, the Contractor does recommend the data from 

the USDA NASS organic survey, when available, be analyzed to identify causal forces and 

factors in the insurance experience that may not be evident in the insurance data. However, since 

such data are not currently available, the Contractor is unable to specify the degree to which such 

information may be useful for future annual reports. Outside sources were used by the Contractor 

in the context of developing a base of knowledge about organic practices. However, outside 

sources were not specifically utilized for developing recommendations. Accordingly, there is no 

need for RMA to rely in the future upon the outside data sources used by the Contractor. For 
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132

future annual reports, the emphasis would be on examining and explaining the insurance 

experience of organic practice and making appropriate adjustments as that experience is accrued.

If the agency cannot hold rate adjustments in abeyance for the additional time required to collect 

further experience data, the Contractor suggests judgmental adjustments be made for those crops 

for which new and higher organic price elections are offered. The availability of more 

appropriate price elections will likely entice participation by a much less biased producer 

population, and major crops offer better organic experience datasets than other crops, lending 

potentially useful insight into judgmental rate adjustments.

However, the Contractor believes adverse selection in the experience pool by high risk producers 

may have distorted the loss experience data, which would strongly argues against simply using 

the loss-cost-ratio-implied surcharge to quantify any judgmental adjustments. An initial 

surcharge of 10 percent may be sufficient if action needs to be taken to maintain the integrity of 

the program while additional experiential data is gathered. Again, timing of the implementation 

of judgmental rates to lessen the impact on the adverse selection is important. Introduction of 

these rates at the same time as the new price elections are rolled out seem logical.

Delaying the introduction of a new rating structure, new reference yields, and new prices until 

sufficient data are available has the potential to reduce the impact of adverse selection going 

forward. As the agency adds price elections for other organic crops, a judgmental rate increase 

(or discount) may be warranted for those crops afforded the new price election until credible loss 

cost based rate determination is possible. 
Organic Crops: Revised Written Rating Report

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Appendix A

Insured Organic Crops 2004 through 2007
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restrictions on the title page of this report.

A1

T ABLE A1. 2004 Organic Crops Insured Under FCIC Plans of Insurance 

Barley Onions

Corn Peanuts

Cotton Popcorn

Dry Beans Potatoes

Dry Peas Processing Beans

Flax Raisins

Flue Cured Tobacco Rice

Forage Seeding Safflower

Grain Sorghum Soybeans

Green Peas Sunflowers

Hybrid Corn Seed Sweet Corn

Millet Wheat

Oats 

Source: The Contractor’s Underwriting Department using 

USDA, RMA data.
Organic Crops: Revised Written Rating Report

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A2

T ABLE A2. 2005 Organic Crops Insured Under FCIC Plans of Insurance 

Alfalfa Seed Grapes

Almonds Green Peas

Apples Hybrid Corn Seed

Barley Macadamia Trees

Cherries Millet

Citrus I Oats

Citrus IV Onions

Citrus Trees I Peaches

Citrus Trees IV Peanuts

Citrus Trees V Pears

Citrus V Plums

Citrus VII Popcorn

Corn Potatoes

Cotton Processing Apricots

Cranberries Processing Cling Peaches

Cultivated Wild Rice Prunes

Dry Beans Raisins

Dry Peas Rice

Figs Rye

Flax Safflower

Flue Cured Tobacco Soybeans

Forage Production Sunflowers

Forage Seeding Sweet Corn

Fresh Apricots Table Grapes

Fresh Freestone Peaches Tomatoes

Fresh Nectarines Walnuts

Grain Sorghum Wheat

Source: The Contractor’s Underwriting Department using USDA, RMA data.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

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A3

T ABLE A3. 2006 Organic Crops Insured Under FCIC Plans of Insurance

Almonds Lemons

Apples Macadamia Nuts

Avocados Macadamia Trees

Barley Mandarins

Blueberries Millet

Cherries Mineola Tangelos

Citrus I Mustard

Citrus II Navel Oranges

Citrus III Oats

Citrus IV Onions

Citrus Trees I Orlando Tangelos

Citrus Trees IV Peaches

Citrus Trees V Peanuts

Citrus VII Pears

Corn Plums

Cotton Popcorn

Cranberries Potatoes

Cultivated Wild Rice Processing Apricots

Dry Beans Processing Beans

Dry Peas Processing Cling Peaches

Figs Prunes

Flax Raisins

Flue Cured Tobacco Rice

Forage Production Safflower

Forage Seeding Soybeans

Fresh Apricots Strawberries

Fresh Freestone Peaches Sunflowers

Fresh Market Tomatoes Sweet Corn

Fresh Nectarines Table Grapes

Grain Sorghum Tomatoes

Grapefruit Valencia Oranges

Grapes Walnuts

Green Peas Wheat

Hybrid Corn Seed

Source: The Contractor’s Underwriting Department using USDA, RMA data.
Organic Crops: Revised Written Rating Report

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restrictions on the title page of this report.

A4

T ABLE A4. 2007 Organic Crops Insured Under FCIC Plans of Insurance

Alfalfa Seed Grapes

Almonds Green Peas

Apples Hybrid Corn Seed

Avocados Lemons

Barley Macadamia Nuts

Blueberries Macadamia Trees

Burley Tobacco Mandarins

Cherries Millet

Cigar Binder Tobacco Mineola Tangelos

Citrus I Mustard

Citrus II Navel Oranges

Citrus III Oats

Citrus IV Onions

Citrus Trees I Peanuts

Citrus Trees IV Pears

Citrus Trees V Plums

Citrus V Popcorn

Citrus VII Potatoes

Corn Processing Apricots

Cotton Processing Beans

Cotton Ex Long Staple Processing Cling Peaches

Cranberries Prunes

Cultivated Wild Rice Rice

Dry Beans Rye

Dry Peas Safflower

Figs Soybeans

Flax Strawberries

Flue Cured Tobacco Sunflowers

Forage Production Sweet Corn

Forage Seeding Sweet Oranges

Fresh Apricots Table Grapes

Fresh Freestone Peaches Tomatoes

Fresh Market Tomatoes Valencia Oranges

Fresh Nectarines Walnuts

Grain Sorghum Wheat

Grapefruit

Source: The Contractor’s Underwriting Department using USDA, RMA data.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

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restrictions on the title page of this report.

Appendix B 

Referenced RMA Bulletins

The text in the report provides the essential information concerning the research project; the full bulletin provides context for the 

referenced sections, but is not essential to the analysis of the report. The referenced bulletins are available on the USDA RMA Website. These bulletins are provided in portable document format (PDF). Links to these bulletins are provided below. 

• MGR-01-004 - Organic Farming Practices-Implementation of the Section 123 of Agricultural Risk 

Protection Act of 2000 (ARPA) 

• MGR-02-001 - Written Agreements – 2002 Crop Year

• MGR-02-015 - Written Agreements – 2003 Crop Year

• MGR-03-009 - Written Agreements – 2004 and Succeeding Crop Years

• MGR-04-004 - Written Agreement Experience Criteria – 2004 and Succeeding Crop Years
Organic Crops: Revised Written Rating Report

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Appendix C

Loss Units by State and Crop
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C1

TABLE C1. Number of Loss Units by State and Crop, 2004 through 2008 

State Wheat Onions Oats MilletRice AvocadoCotton Almonds Walnuts Flax

Forage 

Seeding

Forage 

Production Prunes Corn

Sweet 

Corn Popcorn

Beans, 

Processing

Beans, 

Dry Safflower

Grain 

Sorghum

California 12 2 77 25 76 19 2 40 0 0 

Colorado 311 11 62 11 30

Idaho 13 4 7 

Illinois 10 3 88 2

Indiana 24 1 

Iowa 4 11 353 3

Kansas 178 2 2 33 67

Michigan 40 0 17 168 1 51

Minnesota 98 44 0 9 3 4 404 2 4 15

Missouri 9 0 30 5 2

Montana 747 5 33 0 

Nebraska 76 15 84 113 9 1

New York 3 0 24 3 4 1 

North Dakota 455 129 0 463 2 6 36 37 2

Ohio 10 0 48

Oklahoma 58 0

South Dakota 43 18 5 23 0 0 49

Texas 58 10 48 142 3 1 0 2

Utah 94 1 13 17

Washington 6 0 0 23 0

Wisconsin 11 7 11 3 445 4 2 

Wyoming 164 21 6 7 21 12

Grand Total 2,400 21 274 159 125 25 142 76 19 528 18 21 40 1,854 32 20 12 167 19 71
Organic Crops: Revised Written Rating Report

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C2

T ABLE C1. Number of Loss Units by State and Crop, 2004 through 2008 

State

Table 

Grapes Grapes Apples Cherries

Peas, 

Green

Peas, 

Dry Peanuts Sunflowers Soybeans Potatoes

Tomatoes, 

Processing Pears Barley Plum Rye

Navel 

Oranges

Valencia 

Oranges

Fresh 

Nectarines

Fresh 

Freestone 

Peaches

Grand 

Total

California 38 52 218 0 1 22 0 5 15 33 27 14 16 694

Colorado 0 3 65 7 500

Idaho 0 0 22 46

Illinois 92 195

Indiana 13 38

Iowa 391 0 762

Kansas 9 21 17 329

Michigan 15 197 1 9 499

Minnesota 8 27 643 0 39 1,300

Missouri 65 111

Montana 159 64 1,008

Nebraska 26 103 4 431

New York 0 15 0 50

North Dakota 71 47 69 4 138 15 1,474

Ohio 45 103

Oklahoma 0 58

South Dakota 2 18 69 3 230

Texas 35 5 1 305

Utah 0 125

Washington 12 37 16 16 6 16 2 3 3 140

Wisconsin 6 313 1 21 824

Wyoming 5 236

Grand Total 38 64 270 16 30 232 35 130 2,041 79 22 16 336 15 15 33 27 17 19 9,458
Organic Crops: Revised Written Rating Report

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Appendix D

Reference and T-Yield Data
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D1

Table D1 contains the underlying data used for the analysis of T-yields and to compare average actual 

yields under organic practices with the reference yields for the same crops in the same counties. The 

column headers are crop code, state FIPS, county FIPS, practice (code), total records, number of records 

with no actuals, percent no actuals, total number of actuals, average number of actuals, average of actual 

yields, reference yield, ratio (of average of actual yields to reference yield) . There are more than 2,600 

rows of data. The ratio of the average of the actual yields to the reference yield overall is about twothirds. Corn, soybeans, and wheat, that collectively account for a large share of the organic acreage, also 

have an average actual yield that is about two-thirds of the reference yield. These three crops had about 

four certified yields on average for each unit with actual certified yields. While reference yields, on 

average, tend to exceed the production potential of acreage used for organic production by about 50 

percent (reference yield should be reduced by one-third on average), differences among states exist. 

However, it should be noted, this difference in some cases is based on a relatively small number of 

observations.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

D2

T ABLE D1. Data for Calculating Use of T-Yields and to Compare Reference Yield, by Crop, 

State, County, Practice, and Type; sample only below, see data link for full data set 

(Table D1 Data) 

Crop 

Code

State 

FIPS

County 

FIPS Practice Type Total Records

Number 

Records 

with No 

Actuals 

Percent 

No 

Actuals

Total 

Number 

of 

Actuals

Average 

Number 

of Actuals

Average 

of 

Actual 

Yields

Reference 

Yield Ratio

11 06 011 002 011 1 1 100% 0 0.0 0.0 76 0.00

11 06 013 002 011 1 1 100% 0 0.0 0.0 68 0.00

11 06 019 002 011 1 1 100% 0 0.0 0.0 73 0.00

11 06 019 003 011 1 0 0% 2 2.0 31.0 13 2.38

11 06 031 002 011 1 1 100% 0 0.0 0.0 75 0.00

11 06 049 002 012 2 0 0% 6 3.0 76.7 73 1.05

11 06 061 002 011 4 3 75% 2 2.0 91.5 75 1.22

11 06 065 003 011 4 4 100% 0 0.0 0.0 22 0.00

11 06 077 003 011 5 1 20% 8 2.0 0.0 35 0.00

11 06 093 002 012 4 1 25% 5 1.0 86.2 84 1.03

11 06 095 002 011 1 0 0% 1 1.0 33.0 75 0.44

11 06 095 003 011 1 0 0% 7 7.0 38.0 44 0.86

11 06 101 002 011 2 2 100% 0 0.0 0.0 73 0.00

11 06 113 002 011 1 1 100% 0 0.0 0.0 79 0.00

11 08 001 005 997 70 34 49% 79 2.0 14.8 28 0.53

11 08 003 002 012 9 7 78% 3 1.0 54.3 88 0.62

11 08 005 005 997 108 54 50% 220 4.0 12.6 25 0.50

11 08 021 002 012 5 2 40% 3 1.0 43.7 83 0.53

11 08 023 002 012 5 1 20% 4 1.0 92.5 83 1.11

11 08 033 003 011 16 2 13% 77 5.0 14.6 16 0.91

11 08 039 005 997 2 1 50% 3 3.0 15.0 29 0.52

11 08 069 002 997 16 0 0% 72 4.0 67.7 58 1.17

11 08 073 005 997 100 50 50% 183 3.0 15.8 31 0.51

11 08 075 002 997 4 2 50% 2 1.0 43.0 54 0.80

11 08 075 005 997 73 25 34% 363 7.0 27.9 29 0.96

11 08 105 002 012 3 2 67% 3 3.0 103.3 88 1.17

11 08 109 002 012 16 5 31% 31 2.0 83.0 88 0.94

11 08 113 003 011 5 0 0% 40 8.0 15.1 17 0.89

11 08 121 004 997 5 2 40% 3 1.0 22.3 24 0.93

11 08 121 005 997 38 13 34% 119 4.0 22.2 30 0.74

11 08 123 005 997 37 9 24% 129 4.0 14.9 25 0.60
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Appendix E 

Insurance Experience Data for All State/County 

Combinations 
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Ei

List of Tables

TABLE E1. Alphabetical State/County Insurance Experience for All Crops with an 

Organic Code, 2004-2008 ............................................................................................ E1

TABLE E2. Alphabetical State/County Insurance Experience for All Crops with a 

Non-organic Code, 2004-2008 ..................................................................................... E2

TABLE E3. Rank Ordered Listing of Counties with Net Underwriting Gains (Losses) 

for Crops Insured with the Organic Code, 2004-2008 ................................................. E3
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

E1

Table E1 contains the insurance experience data for organic production organized by state and county. 

The Contractor examined the data on a county basis by calculating the net underwriting gain (loss) of 

acreage insured under an organic code. The column headers are state (name), county (name), units 

(number), net acres (hundreds of), liability (thousands of dollars of), premium (thousands of dollars of) 

Units indemnified (number) indemnity (thousands of dollars of), gain or loss (thousands of dollars of), 

loss ratio, and loss cost ratio. There are almost 700 rows of data. While the data may indicate that greater 

acreage insured under the organic code led to more favorable insurance experience, there is no other 

pattern evident in these data.

TABLE E1. Alphabetical State/County Insurance Experience for All Crops 

with an Organic Code, 2004-2008; sample only below, see data link for full data set 

(Table E1 Data) 

Appendix Table E1. Alphabetical State/County Insurance Experience for All Crops with an 

Organic Code 2004-2008 

Appendix Table E1. Alphabetical State/County Insurance Experience for All 

Crops with an Organic Code 2004-2008 

State County Units

Net 

Acres 

(100) 

Liability 

($1,000) 

Premium 

($1,000) 

Units 

Indemnified

Indemnity 

($1,000) 

Gain (Loss) 

($1,000) 

Loss 

Ratio

Loss Cost 

Ratio

Arkansas Chicot 1 0.1 8.2 0.9 0 0.0 0.9 0.000 0.000 

Arkansas Craighead 1 0.5 8.3 0.2 0 0.0 0.2 0.000 0.000

Arkansas Drew 1 3.6 23.1 0.8 0 0.0 0.8 0.000 0.000 

Arkansas Independence 1 1.0 6.5 0.3 0 0.0 0.3 0.000 0.000 

Arizona Graham 29 3.3 6,313.8 1,411.1 9 765.8 645.3 0.543 0.121 

Arizona Yuma 3 0.2 32.8 1.4 1 9.2 (7.8) 6.775 0.279

California Butte 92 7.3 4,494.1 470.6 24 888.0 (417.4) 1.887 0.198 

California Colusa 114 9.8 5,638.4 312.6 9 70.2 242.4 0.225 0.012 

California Contra Costa 9 0.1 40.6 3.5 0 0.0 3.5 0.000 0.000 

California El Dorado 1 0.0 8.0 0.9 0 0.0 0.9 0.000 0.000

California Fresno 406 26.5 23,727.5 1,914.7 72 2,600.0 (685.3) 1.358 0.110 

California Glenn 61 4.8 1,061.9 44.4 4 68.9 (24.6) 1.554 0.065 

California Kern 130 10.3 12,609.3 811.7 17 479.1 332.6 0.590 0.038 

California Kings 185 6.9 9,576.4 625.6 15 261.5 364.1 0.418 0.027

California Lake 20 0.5 149.8 6.1 7 18.5 (12.3) 3.008 0.123 

California Madera 172 12.7 11,015.2 849.9 35 468.8 381.1 0.552 0.043 

California Mendocino 164 5.5 6,499.1 360.8 15 108.2 252.6 0.300 0.017 

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

E2

Table E2 contains the insurance experience data for non-organic production in the same counties and for 

the same crops in Table E1, organized by state and county. The Contractor examined the data on a 

county basis by calculating the net underwriting gain (loss) of acreage insured without an organic code. 

The column headers are state (name), county (name), units (number), net acres (hundreds of), liability 

(thousands of dollars of), premium (thousands of dollars of) Units indemnified (number) indemnity 

(thousands of dollars of), gain or loss (thousands of dollars of), loss ratio, and loss cost ratio. There are 

almost 700 rows of data. No pattern is immediately evident in the data.

TABLE E2. Alphabetical State/County Insurance Experience for 

All Crops with a Non-organic Code, 2004-2008; sample only below, see data link for full 

data set (Table E2 Data) 

TABLE E2. Alphabetical State/County Insurance Experience for All 

Crops with a Non-organic Code, 2004-2008 

TABLE E2. Alphabetical State/County Insurance Experience for All Crops with 

a 

Non-organic Code, 2004-2008 

State County Units Net Acres 

(100) 

Liability 

($1,000) 

Premium 

($1,000) 

Units 

Indemnif

ied

Indemnity 

($1,000) 

Gain 

(Loss) 

($1,000) 

Loss 

Ratio

Loss Cost 

Ratio

Arkansas Chicot 144 29.7 4,290.6 514.7 1 0.6 514.0 0.001 0.000 

Arkansas Craighead 286 345.5 7,664.8 236.4 3 15.9 220.5 0.067 0.002 

Arkansas Drew 63 67.7 1,053.5 37.6 1 0.8 36.7 0.022 0.001 

Arkansas Independence 91 70.5 950.7 84.6 0 0.0 84.6 0.000 0.000 

Arizona Graham 9 0.3 545.9 88.5 2 5.0 83.5 0.057 0.009 

Arizona Yuma 97 22.4 13,757.7 606.3 15 615.5 (9.2) 1.015 0.045 

California Butte 3,128 2,227.3 226,150.4 11,854.0 394 7,962.0 3,892.0 0.672 0.035 

California Colusa 3,915 3,198.5 222,187.5 8,275.3 150 2,419.1 5,856.2 0.292 0.011 

California Contra Costa 1 0.0 2.5 0.2 0 0.0 0.2 0.000 0.000 

California El Dorado 3 0.0 23.7 4.1 2 10.6 (6.6) 2.620 0.448 

California Fresno 20,564 1,585.7 1,218,801.2 74,584.3 1,933 35,706.3 38,877.9 0.479 0.029 

California Glenn 1,348 1,884.9 103,199.6 3,966.8 66 3,106.1 860.7 0.783 0.030 

California Kern 3,187 520.3 660,263.0 31,998.1 135 9,364.1 22,634.0 0.293 0.014 

California Kings 926 177.2 55,419.4 3,833.6 51 1,028.8 2,804.9 0.268 0.019 

California Lake 137 7.3 6,081.9 141.2 30 230.7 (89.5) 1.634 0.038 

California Madera 3,957 342.2 303,742.6 19,461.2 393 8,036.8 11,424.4 0.413 0.026 

California Mendocino 759 24.4 33,197.7 1,693.5 42 320.9 1,372.6 0.189 0.010 

California Merced 4,334 291.0 480,370.6 27,588.2 675 12,271.9 15,316.3 0.445 0.026 

California Modoc 131 15.3 13,934.1 1,563.0 14 157.0 1,405.9 0.100 0.011 

California Napa 3,533 93.4 306,411.5 14,261.7 176 2,559.8 11,701.8 0.179 0.008 

California Orange 6 2.9 5,307.0 313.1 0 0.0 313.1 0.000 0.000 

California Placer 154 125.1 7,777.5 696.9 43 1,403.6 (706.8) 2.014 0.180 

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

E3

Table E3 organizes the insurance experience from Tables E1 and E2 rank ordered by the net underwriting 

gain (loss) of acreage insured under an organic code. The column headers are state (name), county 

(name), units (number), then for units of crops with an organic code, net acres, gain or loss (dollars of) 

liability (thousands of dollars of), and percent of liability, and finally for the same crops without an 

organic code in the same counties net acres (hundreds of), gain or loss (thousands of dollars of) liability 

(thousands of dollars of), and percent of liability. Once again there are almost 700 rows of data. There is 

no obvious geographic pattern in these data. 

T ABLE E3. Rank Ordered Listing of Counties with Net Underwriting Gains (Losses) for 

Crops Insured with the Organic Code, 2004-2008; sample only below, see data link for full 

data set (Table E3 Data) 

TABLE E3. Rank Ordered Listing of Counties with Net Underwriting Gains (Losses) for 

Crops Insured with the Organic Code, 2004-2008 

TABLE E3. Rank Ordered Listing of Counties with Net Underwriting Gains 

(Losses) for Crops Insured with the Organic Code, 2004-2008 

State County

With an Organic Code With a Non-organic Code

Net 

Acres 

(100) 

Gain 

(Loss) 

($1,000) 

Liability 

($1,000) 

Percent 

of 

Liability 

Net Acres (100) Gain (Loss) 

($1,000) Liability ($1,000) Percent of Liability

Washington Douglas 5.4 840.0 13,572.0 6.2 192.2 2,535.6 84,296.6 3.0 

Washington Yakima 8.6 699.4 17,813.6 3.9 337.9 6,918.0 518,345.6 1.3

Arizona Graham 3.3 645.3 6,313.8 10.2 0.3 83.5 545.9 15.3 

California Napa 3.0 573.4 10,402.3 5.5 93.4 11,701.8 306,411.5 3.8 

Washington Grant 27.1 496.8 24,777.2 2.0 440.0 11,826.5 472,082.4 2.5 

Michigan Shiawassee 28.7 423.4 7,787.9 5.4 303.8 4,920.8 85,178.1 5.8

Wyoming Laramie 41.7 420.6 3,250.4 12.9 301.8 1,416.2 26,352.5 5.4 

California Madera 12.7 381.1 11,015.2 3.5 342.2 11,424.4 303,742.6 3.8 

California Kings 6.9 364.1 9,576.4 3.8 177.2 2,804.9 55,419.4 5.1 

California Kern 10.3 332.6 12,609.3 2.6 520.3 22,634.0 660,263.0 3.4

California Ventura 3.0 311.1 5,592.6 5.6 136.9 8,335.0 270,371.9 3.1 

Washington Benton 19.9 296.5 15,301.1 1.9 278.6 8,613.6 271,456.4 3.2 

Colorado Arapahoe 31.0 288.3 1,598.5 18.0 59.0 8.3 4,680.8 0.2 

Colorado Lincoln 30.0 256.6 1,639.8 15.6 133.9 (365.3) 13,933.5 -2.6

California Mendocino 5.5 252.6 6,499.1 3.9 24.4 1,372.6 33,197.7 4.1 

Kansas Wichita 17.7 226.8 3,332.3 6.8 698.0 (1,573.6) 129,624.9 -1.2 

Washington Walla Walla 2.5 216.4 5,365.0 4.0 139.7 (10,699.8) 166,403.9 -6.4 

Utah San Juan 34.7 183.4 1,017.2 18.0 137.2 (46.2) 5,425.5 -0.9

Nebraska Kimball 20.9 175.0 1,287.4 13.6 580.5 3,293.5 39,390.5 8.4 

Nebraska Dawson 6.7 163.8 2,017.5 8.1 602.6 10,355.5 255,693.5 4.0 

Washington Okanogan 1.9 160.4 4,158.6 3.9 64.1 5,543.0 112,010.1 4.9 

California Yolo 5.4 159.1 5,518.2 2.9 217.7 3,295.6 186,921.4 1.8

California Colusa 3.1 146.3 2,799.7 5.2 319.7 3,886.5 128,635.1 3.0 

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Appendix F

Insurance Experience Data by Crop
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

F1

TABLE F1. Insurance Experience for Crops Insured with 

Organic Common Option Codes, 2004-2008 

Crop Name Units 

Insured

Net acres 

(100)

Liability 

($1,000)

Premium 

($1,000)

Units 

Indemnified

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

Alfalfa Seed 3 2.3 112.0 7.6 2 47.7 6.312 0.426

All other Citrus Trees 2 0.0 57.9 0.9 0 0.0 0.000 0.000

Almonds 199 100.8 14,419.0 1,377.2 63 1,362.3 0.989 0.094

Apples 1,137 346.7 79,141.5 6,167.6 232 2,990.9 0.485 0.038

Avocado Trees (FL) 1 0.0 11.2 0.5 0 0.0 0.000 0.000

Avocados 166 34.9 4,699.2 542.9 25 206.2 0.380 0.044

Barley 706 511.8 4,273.5 909.1 333 827.1 0.910 0.194

Blueberries 15 5.5 607.1 58.7 3 78.9 1.344 0.130

Burley Tobacco 3 0.1 16.3 1.6 0 0.0 0.000 0.000

Cherries 135 16.9 3,576.9 241.0 18 300.9 1.249 0.084

Cigar Binder Tobacco 2 0.0 6.5 0.4 0 0.0 0.000 0.000

Cigar Filler Tobacco 1 0.0 0.8 0.1 0 0.0 0.000 0.000

Coffee 1 0.0 4.2 0.1 0 0.0 0.000 0.000

Corn 4,274 2,360.9 71,164.9 9,449.6 1,897 12,913.5 1.367 0.181

Cotton 331 218.6 3,700.3 875.9 138 1,006.0 1.149 0.272

Cotton Ex Long Staple 6 5.9 509.7 56.8 2 284.6 5.012 0.558

Cranberries 23 6.2 1,314.2 119.4 4 99.8 0.836 0.076

Cultivated Wild Rice 9 18.5 1,178.1 48.5 0 0.0 0.000 0.000

Dry Beans 400 223.7 4,263.8 718.7 167 927.2 1.290 0.217

Dry Peas 490 316.9 2,158.7 515.4 233 717.8 1.393 0.332

Early and Midseason Orange Trees (TX) 4 0.3 31.3 1.1 0 0.0 0.000 0.000

Early and Midseason Oranges (FL) 29 10.4 1,017.3 33.7 0 0.0 0.000 0.000

Figs 47 36.2 2,903.6 170.8 10 109.6 0.642 0.038

Flax 871 585.3 4,622.5 1,081.1 528 1,783.5 1.650 0.386

Flue Cured Tobacco 28 2.0 465.3 25.7 9 86.2 3.353 0.185

Forage Production 120 88.0 1,262.5 147.5 15 67.7 0.459 0.054

Forage Seeding 77 44.6 667.0 88.1 16 43.4 0.493 0.065

Fresh Apricots 45 5.2 796.3 91.2 9 137.8 1.512 0.173

Fresh Freestone Peaches 144 13.7 1,750.5 126.5 23 114.2 0.903 0.065

Fresh Market Tomatoes 4 0.3 139.2 16.1 0 0.0 0.000 0.000

Fresh Nectarines 145 12.3 1,852.6 159.8 17 66.5 0.416 0.036

Grain Sorghum 133 49.1 524.0 151.1 71 241.8 1.600 0.462

Grapefruit (CA) 23 8.5 652.1 31.5 4 77.5 2.462 0.119

Grapefruit (fresh) and Late Oranges (FL) 25 6.3 554.6 24.2 1 13.8 0.568 0.025

Grapefruit (Juice) (FL) 2 0.0 3.0 0.1 0 0.0 0.000 0.000

Grapefruit Trees (FL) 4 0.0 605.8 8.1 0 0.0 0.000 0.000

Grapes 715 264.9 30,792.8 1,853.4 57 542.4 0.293 0.018

Green Peas 92 137.5 6,844.6 607.7 31 644.3 1.060 0.094

Hybrid Corn Seed 31 18.2 1,040.8 117.9 6 59.3 0.503 0.057

Late Oranges (Juice) (FL) 24 8.5 781.5 28.4 0 0.0 0.000 0.000

Lemons 53 19.8 3,326.8 195.7 6 183.7 0.939 0.055

Macadamia Nuts 8 10.3 1,226.8 28.3 2 16.1 0.569 0.013

Macadamia Trees 8 10.3 3,473.3 47.2 0 0.0 0.000 0.000

Mandarins (CA) 18 2.5 193.1 14.0 2 2.2 0.155 0.011

Millet 419 225.0 988.2 291.9 158 210.7 0.722 0.213

Mineola Tangelos (CA) 13 4.1 447.3 27.7 0 0.0 0.000 0.000

Murcott and Temple Oranges (FL) 9 1.0 125.4 7.6 1 11.1 1.450 0.088

Mustard 3 2.8 63.9 7.0 1 21.2 3.029 0.332

Navel Oranges 125 49.8 6,246.5 426.1 33 1,128.8 2.649 0.181
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

F2

TABLE F1. Insurance Experience for Crops Insured with 

Organic Common Options Codes, 2004-2008 (continued)

Crop Name Units 

Insured

Net acres 

(100)

Liability 

($1,000)

Premium 

($1,000)

Units 

Indemnified

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

Navel Oranges (FL) 7 0.9 96.3 4.2 0 0.0 0.000 0.000

Oats 886 424.0 2,679.8 576.7 276 423.3 0.734 0.158

Onions 86 18.2 2,060.0 326.3 21 295.2 0.905 0.143

Orange Trees (FL) 11 0.0 2,482.8 41.5 0 0.0 0.000 0.000

Peaches 3 0.2 41.5 8.1 0 0.0 0.000 0.000

Peanuts 183 150.2 4,723.9 347.1 37 343.9 0.991 0.073

Pears 328 36.9 5,076.2 210.7 13 56.4 0.268 0.011

Plums 123 15.6 1,938.9 228.1 15 81.3 0.356 0.042

Popcorn 43 28.4 750.4 82.1 20 125.3 1.526 0.167

Potatoes 231 104.7 9,756.7 969.6 82 1,292.2 1.333 0.132

Processing Apricots 13 3.7 206.9 20.8 5 27.1 1.303 0.131

Processing Beans 27 13.6 346.3 54.1 12 118.0 2.182 0.341

Processing Cling Peaches 18 2.7 321.3 12.0 0 0.0 0.000 0.000

Processing Freestone 1 0.1 7.2 0.4 0 0.0 0.000 0.000

Prunes 94 49.6 5,596.1 865.5 38 1,334.8 1.542 0.239

Raisins 64 116.7 5,711.6 420.0 8 67.3 0.160 0.012

Rice 570 681.2 5,783.3 1,362.6 125 2,097.9 1.540 0.363

Ruby Red and Star Grapefruit Trees (TX) 4 0.3 38.5 1.8 0 0.0 0.000 0.000

Ruby Red Grapefruit Trees (TX) 6 0.2 17.0 0.8 0 0.0 0.000 0.000

Rye 27 19.4 131.4 22.4 12 23.0 1.024 0.175

Safflower 51 155.7 431.2 65.5 19 83.0 1.267 0.193

Soybeans 3,976 2,345.8 42,834.4 6,788.2 2,058 12,042.5 1.774 0.281

Strawberries 16 8.8 2,919.9 71.7 0 0.0 0.000 0.000

Sunflowers 278 177.8 2,302.2 513.2 130 547.2 1.066 0.238

Sweet Corn 112 196.1 5,013.6 242.4 33 545.0 2.249 0.109

Sweet Oranges (CA) 5 0.3 40.3 3.0 1 8.6 2.836 0.214

Table Grapes 159 47.3 8,815.9 549.7 35 692.7 1.260 0.079

Tangelos and Tangerines (FL) 32 4.6 520.1 32.2 0 0.0 0.000 0.000

Tomatoes 197 179.5 23,752.0 1,413.7 22 848.6 0.600 0.036

Valencia Oranges 109 38.6 3,671.4 252.8 26 550.3 2.176 0.150

Walnuts 72 32.7 1,933.4 75.7 18 291.8 3.853 0.151

Wheat 6,028 6,554.2 57,699.8 14,455.1 2,224 14,006.4 0.969 0.243

Source: The Contractor’s Underwriting Department using USDA RMA data.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

F3

TABLE F2. Insurance Experience for the Same Crops Insured Without Organic Common 

Option Codes, 2004-2008 

Crop Name Units Net acres 

(100) 

Liability 

($1,000) 

Premium 

($1,000) 

Units 

Indemnified 

Indemnity 

($1,000) 

Loss 

Ratio

Loss Cost 

Ratio

Alfalfa Seed 1 0.6 27.0 1.6 1 11.7 7.512 0.432

All other Citrus Trees 49 0.0 2,532.0 46.7 0 0.0 0.000 0.000

Almonds 12,755 9,386.5 1,508,695.3 89,012.2 1,532 29,741.5 0.334 0.020

Apples 10,928 6,274.3 1,285,670.3 62,446.5 1,152 49,766.9 0.797 0.039

Avocado Trees (FL) 117 0.0 17,264.8 671.7 0 0.0 0.000 0.000

Avocados 3,999 1,238.8 202,382.0 22,837.4 627 11,440.9 0.501 0.057

Barley 16,413 20,499.5 158,375.3 21,844.2 5,275 23,298.3 1.067 0.147

Blueberries 141 79.3 13,774.1 1,038.5 9 444.6 0.428 0.032

Burley Tobacco 7 0.3 52.3 4.5 2 5.4 1.194 0.103

Cherries 4,465 769.2 159,550.2 16,589.4 850 18,590.6 1.121 0.117

Cigar Binder Tobacco 4 0.2 29.3 1.7 2 18.0 10.564 0.614

Cigar Filler Tobacco 3 0.1 25.1 1.1 0 0.0 0.000 0.000

Coffee 13 0.7 181.9 3.5 0 0.0 0.000 0.000

Corn 527,854 377,260.0 14,466,068.6 1,266,692.3 104,654 698,957.9 0.552 0.048

Cotton 51,495 34,199.4 584,437.7 147,886.7 17,943 158,583.1 1.072 0.271

Cotton Ex Long Staple 476 1,226.6 67,070.7 2,811.3 49 3,358.4 1.195 0.050

Cranberries 746 387.3 75,824.6 2,205.6 43 489.5 0.222 0.006

Cultivated Wild Rice 39 115.0 7,138.1 291.9 1 28.3 0.097 0.004

Dry Beans 8,663 4,946.6 101,550.4 14,007.1 2,420 11,531.1 0.823 0.114

Dry Peas 7,785 8,850.7 81,293.4 11,712.5 2,644 13,928.2 1.189 0.171

Early and Midseason Orange Trees (TX) 876 103.0 26,786.3 970.5 0 0.0 0.000 0.000

Early and Midseason Oranges (FL) 981 632.2 38,808.4 1,030.3 55 1,959.0 1.901 0.050

Figs 76 103.1 7,429.5 494.6 5 146.5 0.296 0.020

Flax 6,239 4,541.6 34,812.8 5,082.3 2,194 6,606.5 1.300 0.190

Flue Cured Tobacco 1,592 168.9 45,337.6 2,685.0 386 6,852.4 2.552 0.151

Forage Production 2,847 2,439.9 19,689.1 2,252.5 511 1,441.1 0.640 0.073

Forage Seeding 1,345 433.5 5,793.8 786.4 147 385.5 0.490 0.067

Fresh Apricots 170 40.4 5,966.2 636.2 36 507.7 0.798 0.085

Fresh Freestone Peaches 1,600 702.4 61,408.7 2,864.8 61 183.6 0.064 0.003

Fresh Market Tomatoes 4 2.1 1,001.2 110.3 1 15.9 0.144 0.016

Fresh Nectarines 1,922 768.7 75,085.0 4,450.7 140 1,155.6 0.260 0.015

Grain Sorghum 7,430 3,242.6 51,771.9 9,054.3 2,284 9,967.9 1.101 0.193

Grapefruit (CA) 150 87.3 10,285.5 449.0 15 322.5 0.718 0.031

Grapefruit (fresh) and Late Oranges (FL) 275 289.2 17,210.2 563.8 69 6,509.0 11.545 0.378

Grapefruit (Juice) (FL) 1 0.1 5.0 0.2 0 0.0 0.000 0.000

Grapefruit Trees (FL) 220 0.0 66,643.9 961.0 1 56.8 0.059 0.001

Grapes 27,489 13,582.4 1,516,957.0 82,517.4 1,606 20,065.9 0.243 0.013

Green Peas 349 562.0 12,671.7 864.5 37 451.0 0.522 0.036

Hybrid Corn Seed 114 65.4 5,375.0 262.4 4 231.7 0.883 0.043

Late Oranges (Juice) (FL) 277 145.5 15,543.9 511.3 2 30.0 0.059 0.002

Lemons 1,624 1,048.2 163,970.2 5,933.1 100 2,670.3 0.450 0.016

Macadamia Nuts 498 479.6 87,327.2 1,776.1 52 2,326.6 1.310 0.027

Macadamia Trees 248 249.4 86,897.8 919.5 0 0.0 0.000 0.000

Mandarins (CA) 113 128.8 21,913.1 1,672.8 7 567.3 0.339 0.026

Millet 9,842 5,429.2 29,301.5 5,798.7 3,597 5,584.0 0.963 0.191

Mineola Tangelos (CA) 121 32.8 2,769.5 183.7 11 143.5 0.781 0.052

Murcott and Temple Oranges (FL) 117 16.5 2,799.6 139.5 37 356.3 2.554 0.127

Mustard 3 8.4 167.5 16.8 1 4.2 0.249 0.025

Navel Oranges 10,241 4,020.4 554,061.3 31,562.3 1,284 35,605.4 1.128 0.064
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

F4

TABLE F2. Insurance Experience for the Same Crops Insured Without Organic Common 

Option Codes, 2004-2008 (continued)

Crop Name Units Net acres 

(100) 

Liability 

($1,000) 

Premium 

($1,000) 

Units 

Indemnified 

Indemnity 

($1,000) 

Loss 

Ratio

Loss Cost 

Ratio

Navel Oranges (FL) 22 4.8 518.4 22.7 0 0.0 0.000 0.000

Oats 7,529 3,493.2 19,045.4 3,480.5 2,299 4,093.4 1.176 0.215

Onions 590 428.3 57,302.4 6,082.3 149 4,923.8 0.810 0.086

Orange Trees (FL) 333 0.0 139,516.6 1,993.6 0 0.0 0.000 0.000

Peaches 82 4.7 1,462.6 259.1 10 34.9 0.135 0.024

Peanuts 3,019 2,045.5 72,717.7 3,600.9 134 1,689.2 0.469 0.023

Pears 5,065 979.7 125,226.1 4,266.3 147 797.5 0.187 0.006

Plums 2,212 434.2 48,479.7 5,273.3 405 3,454.0 0.655 0.071

Popcorn 230 144.6 6,539.3 381.6 10 41.0 0.107 0.006

Potatoes 3,129 3,831.4 380,135.4 28,434.6 650 16,088.7 0.566 0.042

Processing Apricots 172 63.4 6,163.2 652.1 53 971.9 1.490 0.158

Processing Beans 195 93.7 3,919.7 407.3 47 312.9 0.768 0.080

Processing Cling Peaches 323 68.4 7,320.0 259.9 29 193.4 0.744 0.026

Processing Freestone 1 0.0 4.3 0.2 0 0.0 0.000 0.000

Prunes 2,186 1,189.6 137,166.5 19,492.6 1,171 38,203.6 1.960 0.279

Raisins 5,264 5,152.5 288,568.8 22,913.2 767 5,565.7 0.243 0.019

Rice 10,317 18,206.0 507,219.2 18,613.4 559 12,586.0 0.676 0.025

Ruby Red and Star Grapefruit Trees (TX) 1,461 283.5 76,254.7 3,674.4 0 0.0 0.000 0.000

Ruby Red Grapefruit Trees (TX) 138 21.1 4,760.1 203.9 0 0.0 0.000 0.000

Rye 13 5.0 43.3 7.5 1 1.1 0.145 0.025

Safflower 208 232.8 1,259.3 132.9 32 126.1 0.949 0.100

Soybeans 506,380 341,836.6 8,079,585.5 795,669.2 132,132 678,795.3 0.853 0.084

Strawberries 333 294.9 106,681.1 2,650.5 0 0.0 0.000 0.000

Sunflowers 6,497 5,292.7 82,462.8 14,990.8 2,144 11,530.3 0.769 0.140

Sweet Corn 520 1,364.4 35,438.9 1,257.2 22 204.0 0.162 0.006

Sweet Oranges (CA) 26 1.8 349.6 27.8 1 13.6 0.488 0.039

Table Grapes 3,294 2,641.2 505,271.0 24,534.4 298 9,110.9 0.371 0.018

Tangelos and Tangerines (FL) 377 70.0 5,363.4 215.1 95 524.4 2.439 0.098

Tomatoes 4,923 4,673.2 478,622.8 22,073.6 309 8,708.4 0.395 0.018

Valencia Oranges 3,012 763.4 94,924.5 6,647.7 354 6,964.5 1.048 0.073

Walnuts 1,927 1,790.5 129,984.9 4,321.3 45 441.7 0.102 0.003

Wheat 392,323 380,685.4 4,354,667.5 732,402.6 100,820 547,782.3 0.748 0.126

Source: The Contractor’s Underwriting Department using USDA RMA data.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Appendix G

Organic Crop Underwriting Gain (Loss)
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

G1

TABLE G1. Organic Crop Net Underwriting Gain (Loss) and Comparable Values for the 

Non-organic Component of the Crop, 2004-2008 

Crop

With Organic Code Without Organic Code

Gain (Loss) 

($1,000)

Liability 

($1,000)

Percent of 

Liability

Gain (Loss) 

($1,000)

Liability 

($1,000)

Percent of 

Liability

Alfalfa Seed (40.1) 112.0 -35.8 (10.1) 27.0 -37.5

All other Citrus Trees 0.9 57.9 1.5 46.7 2,532.0 1.8

Almonds 14.9 14,419.0 0.1 59,270.6 1,508,695.3 3.9

Apples 3,176.7 79,141.5 4.0 12,679.7 1,285,670.3 1.0

Avocado Trees (FL) 0.5 11.2 4.9 671.7 17,264.8 3.9 

Avocados 336.7 4,699.2 7.2 11,396.6 202,382.0 5.6

Barley 82.1 4,273.5 1.9 (1,454.1) 158,375.3 -0.9

Blueberries (20.2) 607.1 -3.3 594.0 13,774.1 4.3

Burley Tobacco 1.6 16.3 9.7 (0.9) 52.3 -1.7

Cherries (59.9) 3,576.9 -1.7 (2,001.2) 159,550.2 -1.3

Cigar Binder Tobacco 0.4 6.5 6.8 (16.3) 29.3 -55.6

Cigar Filler Tobacco 0.1 0.8 6.4 1.1 25.1 4.5

Coffee 0.1 4.2 2.1 3.5 181.9 1.9

Corn (3,464.0) 71,164.9 -4.9 567,734.4 14,466,068.6 3.9

Cotton (130.1) 3,700.3 -3.5 (10,696.4) 584,437.7 -1.8

Cotton Ex Long Staple (227.8) 509.7 -44.7 (547.0) 67,070.7 -0.8

Cranberries 19.6 1,314.2 1.5 1,716.1 75,824.6 2.3

Cultivated Wild Rice 48.5 1,178.1 4.1 263.6 7,138.1 3.7

Dry Beans (208.5) 4,263.8 -4.9 2,476.0 101,550.4 2.4

Dry Peas (202.3) 2,158.7 -9.4 (2,215.7) 81,293.4 -2.7

Early and Midseason Orange Trees (TX) 1.1 31.3 3.6 970.5 26,786.3 3.6

Early and Midseason Oranges (FL) 33.7 1,017.3 3.3 (928.7) 38,808.4 -2.4

Figs 61.2 2,903.6 2.1 348.1 7,429.5 4.7

Flax (702.5) 4,622.5 -15.2 (1,524.3) 34,812.8 -4.4

Flue Cured Tobacco (60.5) 465.3 -13.0 (4,167.3) 45,337.6 -9.2

Forage Production 79.8 1,262.5 6.3 811.4 19,689.1 4.1

Forage Seeding 44.7 667.0 6.7 400.9 5,793.8 6.9

Fresh Apricots (46.6) 796.3 -5.9 128.5 5,966.2 2.2

Fresh Freestone Peaches 12.3 1,750.5 0.7 2,681.1 61,408.7 4.4

Fresh Market Tomatoes 16.1 139.2 11.6 94.4 1,001.2 9.4

Fresh Nectarines 93.3 1,852.6 5.0 3,295.2 75,085.0 4.4

Grain Sorghum (90.7) 524.0 -17.3 (913.5) 51,771.9 -1.8

Grapefruit (CA) (46.0) 652.1 -7.1 126.5 10,285.5 1.2

Grapefruit (fresh) and Late Oranges (FL) 10.5 554.6 1.9 (5,945.2) 17,210.2 -34.5

Grapefruit (Juice) (FL) 0.1 3.0 3.7 0.2 5.0 3.5

Grapefruit Trees (FL) 8.1 605.8 1.3 904.2 66,643.9 1.4

Grapes 1,311.0 30,792.8 4.3 62,451.5 1,516,957.0 4.1

Green Peas (36.6) 6,844.6 -0.5 413.5 12,671.7 3.3

Hybrid Corn Seed 58.7 1,040.8 5.6 30.7 5,375.0 0.6

Late Oranges (Juice) (FL) 28.4 781.5 3.6 481.3 15,543.9 3.1

Lemons 12.0 3,326.8 0.4 3,262.8 163,970.2 2.0

Macadamia Nuts 12.2 1,226.8 1.0 (550.5) 87,327.2 -0.6

Macadamia Trees 47.2 3,473.3 1.4 919.5 86,897.8 1.1

Mandarins (CA) 11.8 193.1 6.1 1,105.5 21,913.1 5.0

Millet 81.2 988.2 8.2 214.6 29,301.5 0.7

Mineola Tangelos (CA) 27.7 447.3 6.2 40.2 2,769.5 1.5

Murcott and Temple Oranges (FL) (3.4) 125.4 -2.7 (216.8) 2,799.6 -7.7

Mustard (14.2) 63.9 -22.2 12.6 167.5 7.5
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

G2

TABLE G1. Organic Crop Net Underwriting Gain (Loss) and Comparable Values for the 

Non-organic Component of the Crop, 2004-2008 (continued)

Crop

With Organic Code Without Organic Code

Gain (Loss) 

($1,000)

Liability 

($1,000)

Percent of 

Liability

Gain (Loss) 

($1,000)

Liability 

($1,000)

Percent of 

Liability

Navel Oranges (702.7) 6,246.5 -11.2 (4,043.2) 554,061.3 -0.7

Navel Oranges (FL) 4.2 96.3 4.3 22.7 518.4 4.4

Oats 153.4 2,679.8 5.7 (612.9) 19,045.4 -3.2

Onions 31.1 2,060.0 1.5 1,158.5 57,302.4 2.0

Orange Trees (FL) 41.5 2,482.8 1.7 1,993.6 139,516.6 1.4

Peaches 8.1 41.5 19.4 224.2 1,462.6 15.3

Peanuts 3.2 4,723.9 0.1 1,911.7 72,717.7 2.6

Pears 154.2 5,076.2 3.0 3,468.8 125,226.1 2.8

Plums 146.9 1,938.9 7.6 1,819.3 48,479.7 3.8

Popcorn (43.2) 750.4 -5.8 340.6 6,539.3 5.2

Potatoes (322.6) 9,756.7 -3.3 12,345.9 380,135.4 3.2

Processing Apricots (6.3) 206.9 -3.0 (319.8) 6,163.2 -5.2

Processing Beans (63.9) 346.3 -18.5 94.3 3,919.7 2.4

Processing Cling Peaches 12.0 321.3 3.7 66.5 7,320.0 0.9

Processing Freestone 0.4 7.2 5.5 0.2 4.3 5.2

Prunes (469.3) 5,596.1 -8.4 (18,711.0) 137,166.5 -13.6

Raisins 352.7 5,711.6 6.2 17,347.5 288,568.8 6.0

Rice (735.2) 18,355.9 -4.0 6,027.4 507,220.2 1.2

Ruby Red and Star Grapefruit Trees (TX) 1.8 38.5 4.8 3,674.4 76,254.7 4.8

Ruby Red Grapefruit Trees (TX) 0.8 17.0 4.8 203.9 4,760.1 4.3

Rye (0.5) 131.4 -0.4 6.4 43.3 14.9

Safflower (17.5) 431.2 -4.1 6.8 1,259.3 0.5

Soybeans (5,254.3) 42,834.4 -12.3 116,873.9 8,079,585.5 1.4

Strawberries 71.7 2,919.9 2.5 2,650.5 106,681.1 2.5

Sunflowers (34.0) 2,302.2 -1.5 3,460.5 82,462.8 4.2

Sweet Corn (302.6) 5,013.6 -6.0 1,053.2 35,438.9 3.0

Sweet Oranges (CA) (5.6) 40.3 -13.8 14.2 349.6 4.1

Table Grapes (143.0) 8,815.9 -1.6 15,423.5 505,271.0 3.1

Tangelos and Tangerines (FL) 32.2 520.1 6.2 (309.4) 5,363.4 -5.8

Tomatoes 565.1 23,752.0 2.4 13,365.3 478,622.8 2.8

Valencia Oranges (297.4) 3,671.4 -8.1 (316.8) 94,924.5 -0.3

Walnuts (216.1) 1,933.4 -11.2 3,879.6 129,984.9 3.0

Wheat 448.7 57,699.8 0.8 184,620.4 4,354,667.5 4.2

Source: The Contractor’s Underwriting Department using USDA RMA data.
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Appendix H

Comparison of Organic and Non-organic Percentage Loss 

by Crop
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

H1

TABLE H1. Organic and Non-organic Insurance Data 2005-2008: By State With Most 

Organic Insured Acres to Least (All Data Except Loss Ratio in 1,000 units) 

State Organic 

Acres 

Nonorganic 

Acres 

Organic 

Liability

Non-organic 

Liability

Organic 

Premium

Non-organic 

Premium

Organic 

Indemnity

Non-organic 

Indemnity

Organic 

Loss Ratio

Nonorganic 

Loss Ratio

Montana 238.3 16,781.9 19,193.0 1,534,302.2 4,396.2 256,856.0 5,170.6 199,885.5 1.176 0.778

Minnesota 203.7 25,497.0 37,922.3 7,023,348.8 5,993.4 718,042.6 9,017.9 455,234.9 1.505 0.634

North Dakota 180.0 14,140.8 17,235.4 1,985,783.7 4,235.5 331,136.0 5,622.0 281,442.9 1.327 0.850

Colorado 132.1 2,389.7 17,426.3 399,401.9 4,770.4 63,002.5 4,721.6 57,000.5 0.990 0.905

California 127.7 5,713.4 129,448.6 6,072,665.3 9,871.9 364,466.5 9,532.7 191,264.7 0.966 0.525

Nebraska 97.0 9,960.4 19,118.2 2,706,171.1 2,696.7 264,835.3 2,603.3 130,940.0 0.965 0.494

Utah 95.2 306.4 4,521.9 23,279.2 1,152.9 3,752.1 1,410.4 3,943.1 1.223 1.051

Iowa 84.8 19,308.4 23,858.1 7,050,279.0 2,456.8 520,937.8 4,286.4 336,273.6 1.745 0.646

Washington 76.9 1,787.6 95,171.5 1,883,006.3 5,967.1 93,889.8 3,030.8 66,838.9 0.508 0.712

Michigan 63.0 1,916.7 14,671.7 465,555.2 2,652.0 52,795.8 2,524.0 38,414.8 0.952 0.728

Texas 61.8 4,409.1 11,498.2 893,020.1 1,880.4 173,238.3 2,565.4 177,282.6 1.364 1.023

Wyoming 56.1 468.2 4,411.0 54,123.5 933.2 8,352.8 581.3 6,855.7 0.623 0.821

Wisconsin 49.0 4,035.1 12,303.5 1,263,386.8 2,151.2 140,454.3 4,143.8 135,404.6 1.926 0.964

Kansas 42.4 3,972.5 6,758.5 603,459.3 1,056.8 100,653.2 1,211.1 87,901.1 1.146 0.873

South Dakota 40.8 4,914.6 5,820.5 1,063,111.5 1,041.3 132,106.0 1,233.8 77,793.7 1.185 0.589

Illinois 19.5 5,540.8 5,754.1 2,130,470.3 614.1 158,306.3 759.4 60,554.3 1.237 0.383

Idaho 19.4 436.6 2,311.0 94,547.2 299.1 6,952.9 269.3 6,218.3 0.900 0.894

Missouri 12.3 878.0 1,791.0 169,724.4 393.1 22,718.3 550.2 18,092.3 1.399 0.796

New York 12.2 393.8 2,103.5 74,189.4 286.2 5,764.8 261.1 2,697.9 0.912 0.468

Oregon 10.3 563.5 4,125.4 166,449.6 235.7 15,878.9 309.6 34,686.7 1.313 2.184

Ohio 8.8 1,417.2 1,917.6 415,221.2 305.4 40,569.0 555.2 41,219.1 1.818 1.016

Oklahoma 8.1 217.4 550.9 18,647.1 186.1 3,888.4 154.5 6,041.9 0.830 1.554

Virginia 5.6 97.4 1,598.3 39,434.1 267.7 4,716.2 341.2 5,577.0 1.274 1.183

Arizona 3.4 22.7 6,346.6 14,303.6 1,412.4 694.7 775.0 620.5 0.549 0.893

Florida 3.3 121.1 6,405.5 320,854.0 192.7 6,749.4 37.3 9,601.2 0.193 1.423

Indiana 2.7 328.3 660.1 120,468.6 82.6 11,342.9 122.9 5,788.1 1.487 0.510

Hawaii 2.1 73.0 4,704.4 174,406.9 75.6 2,699.1 16.1 2,326.6 0.213 0.862

Maryland 1.8 118.5 531.1 32,075.9 74.7 4,076.1 47.8 2,330.9 0.640 0.572

New Mexico 1.8 15.7 513.7 3,580.9 41.8 322.7 36.7 101.4 0.880 0.314

North Carolina 1.5 51.7 496.3 51,106.3 51.2 5,206.6 59.6 13,238.8 1.163 2.543

Pennsylvania 0.9 91.3 245.2 23,476.9 34.1 3,219.0 31.0 1,622.0 0.908 0.504

Maine 0.6 50.1 155.8 42,476.8 16.6 4,010.0 20.9 2,320.2 1.257 0.579

Georgia 0.5 18.9 828.0 12,058.9 105.3 1,580.9 88.4 1,897.5 0.839 1.200

Vermont 0.4 42.1 87.6 8,143.2 8.7 532.7 7.3 330.1 0.847 0.620

New Jersey 0.3 5.9 49.4 1,362.4 8.0 209.7 17.6 93.3 2.207 0.445

Massachusetts 0.2 25.0 180.2 37,662.8 10.5 847.8 11.8 250.6 1.130 0.296

Arkansas 0.1 29.7 8.2 4,290.6 0.9 514.7 0.0 0.6 0.000 0.001

Connecticut 0.0 0.5 2.9 152.4 0.4 11.1 2.1 8.0 4.737 0.724

New Hampshire 0.0 0.0 3.0 7.1 0.2 0.6 0.0 0.0 0.000 0.000

Grand Total 1,664.7 126,141.0 460,728.7 36,976,004.6 55,959.1 3,525,331.7 62,130.0 2,462,093.9 1.110 0.698

Percent of Non-organic 1.32% 1.25% 1.59% 2.52%

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

H2

TABLE H2. Organic and Non-organic Insurance Data 2001-2004: By State with Most 

Organic Insured Acres to Least (All Data Except Loss Ratio in 1,000 units) 

State Organic 

Acres 

Nonorganic 

Acres 

Organic 

Liability

Non-organic 

Liability

Organic 

Premium

Non-organic 

Premium

Organic 

Indemnity

Non-organic 

Indemnity

Organic 

Loss 

Ratio

Nonorganic 

Loss 

Ratio

Montana 48.5 14,594.9 3,005.7 1,310,858.4 561.4 220,167.9 857.6 171,744.0 1.528 0.780

Minnesota 26.4 13,459.1 2,655.3 3,024,849.0 386.5 364,397.1 688.9 221,578.3 1.783 0.608

North Dakota 21.4 8,604.5 1,476.2 1,088,680.5 288.9 181,589.0 647.3 138,716.4 2.241 0.764

Utah 17.5 306.4 1,349.0 23,279.2 227.6 3,752.1 506.9 3,943.1 2.227 1.051

Nebraska 16.4 4,976.2 1,428.1 1,034,220.1 246.6 99,850.7 167.8 49,808.3 0.680 0.499

Colorado 11.4 1,655.8 748.0 204,246.5 122.0 32,791.9 171.2 30,913.5 1.403 0.943

Iowa 8.8 10,812.4 1,365.6 3,828,063.6 145.0 282,872.3 299.3 175,493.1 2.064 0.620

Washington 8.7 1,666.4 11,658.5 1,847,593.8 928.0 91,773.1 543.8 62,900.3 0.586 0.685

Wisconsin 8.0 2,846.7 1,442.6 867,684.0 174.8 93,743.8 479.1 92,817.1 2.741 0.990

Idaho 7.6 61.4 762.1 21,673.5 124.4 1,345.8 168.5 1,384.5 1.355 1.029

California 7.5 5,374.9 6,978.7 5,804,293.8 574.1 342,582.8 750.6 182,758.1 1.307 0.533

Texas 7.1 2,585.7 830.0 506,480.6 145.3 94,223.0 103.0 85,039.8 0.709 0.903

South Dakota 6.8 3,905.0 535.0 760,073.4 58.4 90,491.2 165.0 59,313.0 2.823 0.655

Michigan 5.7 1,525.1 611.6 343,906.2 101.8 39,536.0 244.7 23,830.8 2.405 0.603

Missouri 3.4 413.4 367.4 72,075.0 56.4 7,922.9 87.5 7,744.2 1.552 0.977

Wyoming 3.2 434.3 201.4 45,405.0 33.2 7,245.4 31.3 5,384.7 0.941 0.743

Kansas 2.8 1,855.1 287.6 291,633.9 40.0 41,851.1 127.4 40,398.8 3.182 0.965

Illinois 1.6 2,979.0 234.7 1,026,843.1 26.5 78,513.9 75.0 31,025.6 2.828 0.395

Ohio 1.3 696.0 187.1 178,182.4 18.8 17,545.8 20.5 17,410.2 1.088 0.992

Arizona 1.2 0.4 2,128.7 592.3 392.7 93.0 70.1 17.3 0.179 0.186

New York 1.0 213.2 111.3 39,201.6 10.4 3,148.8 4.9 1,559.9 0.472 0.495

Hawaii 0.3 73.0 214.7 174,406.9 4.1 2,699.1 1.9 2,326.6 0.461 0.862

New Jersey 0.1 1.3 13.2 160.6 1.9 14.7 3.5 29.1 1.893 1.976

Pennsylvania 0.1 57.9 16.9 13,175.0 2.6 1,968.8 8.3 1,345.5 3.157 0.683

Indiana 0.0 13.3 6.3 2,672.6 0.9 225.8 0.0 65.9 0.000 0.292

Oregon 0.0 23.9 38.5 24,776.5 2.4 852.7 8.1 543.8 3.349 0.638

Massachusetts 0.0 2.3 24.2 2,973.8 0.8 83.3 10.2 18.8 13.312 0.226

Grand Total 217.0 79,137.2 38,678.5 22,538,001.3 4,675.5 2,101,281.8 6,242.3 1,408,110.6 1.335 0.670

Percent of Non-organic 0.27% 0.17% 0.22% 0.44% 

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

H3

TABLE H3. Experience Data for Crops Insured Under Organic Codes 

and Non-organic Practice, 2001-2008 

Year Units Acres 

(1,000)

Liability 

($1,000)

Premium 

($1,000)

Earned 

Premium Rate

Units 

Indemnified

Units 

Indemnified (%)

Indemnity 

($1,000)

Loss 

Ratio

Loss Cost 

Ratio

Organic Codes

2001 193 15 1,305 190 0.145 96 49.7 275 1.45 0.21

2002 880 66 8,299 1,080 0.130 501 56.9 1,934 1.79 0.23

2003 1,130 68 10,775 1,338 0.124 585 51.8 2,528 1.89 0.23

2004 3,209 210 38,215 5,022 0.131 1,365 42.5 6,850 1.36 0.18

2005 3,931 281 57,082 6,800 0.119 1,173 29.8 5,750 0.85 0.10

2006 5,165 356 79,815 9,247 0.116 2,067 40.0 9,975 1.08 0.12

2007 6,070 419 121,999 14,211 0.116 1,973 32.5 12,908 0.91 0.11

2008 6,770 459 170,580 22,125 0.130 2,943 43.5 28,027 1.27 0.16

Total 27,348 1,874 488,070 60,012 0.123 10,703 39.1 68,247 1.14 0.14

 Non-organic

2001 24,337 1,846 219,556 20,293 0.092 6,998 28.8 28,700 1.41 0.13

2002 70,692 5,367 714,466 61,036 0.085 20,712 29.3 71,731 1.18 0.10

2003 79,348 5,737 1,006,831 82,591 0.082 21,001 26.5 86,565 1.05 0.09

2004 210,857 15,796 3,278,246 305,279 0.093 51,411 24.4 229,604 0.75 0.07

2005 265,780 19,903 4,237,676 382,835 0.090 39,597 14.9 191,315 0.50 0.05

2006 297,659 22,481 5,419,454 483,571 0.089 55,783 18.7 277,245 0.57 0.05

2007 337,572 25,734 8,326,062 770,589 0.093 46,067 13.6 345,527 0.45 0.04

2008 400,426 30,792 13,640,947 1,444,867 0.106 156,562 39.1 1,281,958 0.89 0.09

Total 1,686,671 127,655 36,843,239 3,551,061 0.096 398,131 23.6 2,512,645 0.68 0.07

Organic as Percent of Non-organic

2001 0.79 0.80 0.59 0.93 157.32 1.37 172.98 0.96 102.68 161.54

2002 1.24 1.22 1.16 1.77 152.26 2.42 194.31 2.70 152.47 232.16

2003 1.42 1.19 1.07 1.62 151.34 2.79 195.60 2.92 180.33 272.91

2004 1.52 1.33 1.17 1.65 141.12 2.66 174.46 2.98 181.35 255.91

2005 1.48 1.41 1.35 1.78 131.86 2.96 200.29 3.01 169.21 223.13

2006 1.74 1.58 1.47 1.91 129.85 3.71 213.54 3.60 188.14 244.29

2007 1.80 1.63 1.47 1.84 125.86 4.28 238.19 3.74 202.56 254.95

2008 1.69 1.49 1.25 1.53 122.45 1.88 111.18 2.19 142.77 174.83

Total 1.62 1.47 1.32 1.69 127.57 2.69 165.80 2.72 166.99 212.12

Source: The Contractor’s Underwriting Department using data from USDA, RMA
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

Appendix I

Samples of Type 11, 15, and 21 Data 

Used in the Rating Analysis
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

I1

Sample of A ll Y ield Obser vations (C leaned)

Table I1 below provides images of a sample of the “all yield observations” data for crop/county combinations which include units 

flagged as organic. The columns are labeled Rp_Org, Company (code), Stfips (state FIPS), Ctyfips (county FIPS), ID_num 

(identification number), year, RR (risk region), flag, type, prac (practice), AcWtdAvgYield_pol (actual weighted average yield for the 

policy, and Acres_pol (acres). The column labeled ID_num does not contain actual policy numbers but rather contain unique 

identifiers that allow policy level analysis. 

(Table I1 Data)

Data T able I 1

Rp_Org Company Stfips Ctyfips ID_num Cr_id theYear RR flag type prac AcWtdAvgYield_pol Acres_pol

MJ 951 6 111 1536330 19 2007 926 2 55 2 7372 78.8

MB 998 6 111 204800 19 2007 926 2 55 2 7490 5

MJ 951 6 111 37353 19 2007 926 2 55 2 8008 50

HL 30 6 111 7458023 19 2007 926 2 55 2 8607 65

MJ 951 6 111 1537323 19 2007 926 2 55 2 9927 4

MJ 951 6 111 6650215 19 2007 926 2 55 2 10976 74

OW 718 6 111 4005823 19 2007 926 2 55 2 10985 8.8

HB 349 49 3 3335484 33 2007 928 2 552 2 2.6 74

HB 349 49 3 3260592 11 2007 928 2 11 5 4.447427 268.2

OW 819 49 3 4122115 11 2007 928 2 11 5 11 251.3

OW 718 49 49 3234330 11 2007 928 2 11 3 12 1855.1

OW 819 49 3 3194700 11 2007 928 2 11 2 21 142

OW 819 49 3 4932030 11 2007 928 2 11 5 21 224.2

HB 349 49 3 2978100 11 2007 928 2 11 5 27 39.8

OW 819 49 3 4482438 11 2007 928 2 11 5 32 277.3

OW 718 49 49 3234330 11 2007 928 2 12 2 58 83.6

OW 819 49 3 4619453 11 2007 928 2 11 5 79.91 90

OW 819 49 3 4482484 11 2007 928 2 11 2 80 63

HB 349 49 3 3260684 11 2007 928 2 11 2 100 42

HB 349 49 3 3260800 11 2007 928 2 11 2 111 65

UB 601 49 3 5507146 49 2007 928 2 997 3 118 46.5

OW 819 49 3 3255076 11 2007 928 2 11 2 130 201.6
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

I2

Sample of Pair ed Y ield Obser vations

Table I2 below provides images of a sample of the “paired yield observations” data for crop/county combinations which include units 

flagged as organic. The columns are labeled Stfips (state FIPS), Ctyfips (county FIPS), cr_id (crop id), ip_code (insurance provider 

code), ID_num (identification number), type, prac (practice), Cavg (average yield under conventional practices), Cstdev (standard 

deviation of yield under conventional practices), Oavg (average yield under organic practices), Ostdev (standard deviation of yield 

under organic practices). The column labeled ID_num does not contain actual policy numbers but rather contain unique identifiers that 

allow policy level analysis. (Table I2 Data)

Data T able I 2 

"stfips" "ctyfips" "cr_id" "ip_code" "ID_num" "type" "prac" "Cavg" "Cstdev" "Oavg" "Ostdev"

28 51 21 44 79907 997 2 1066.290355 196.9691459 1170.990616 194.7530915

29 13 81 90 4476784 997 53 33.98383955 9.21042077 32.95236074 9.271758502

19 73 81 25 6959430 997 3 39.81236762 5.504405266 38.70983982 7.527726527 

27 125 11 44 217769 997 3 39.29485739 16.51636967 40.99287627 19.39345047

48 415 21 90 5418023 997 3 106.9534943 139.4881548 112.6574032 113.3851235

53 7 89 86 3321146 186 2 6.261304348 1.190518095 5.770910556 1.1976079

53 7 89 86 3321146 187 2 19.09076923 3.998055083 18.28874778 4.969112256 

6 11 18 90 4131100 997 2 8962.968553 550.367453 4839.04702 1347.821576

16 27 54 86 3879369 114 2 524.0750659 164.2550732 476.5142857 131.9927539

16 27 54 86 3879369 115 2 794.4630819 311.2677512 483.5 273.9300397

19 121 81 90 45500 997 3 35.89122724 2.949576241 26.0212275 3.519414911 

26 151 81 44 14307 997 53 35.70931234 12.17005329 32.71352941 12.21883792

27 120 81 90 4381953 997 3 23.74960077 9.710818709 27.64107929 6.196795051

27 125 81 90 217769 997 3 28.41027858 12.42764027 16.75892857 15.85349593

27 125 81 90 836792 997 3 23.92441601 9.947215063 21.45389596 11.54700538 

27 149 81 44 2128884 997 3 32.99880164 7.494632962 31.22096292 9.612025382

27 149 81 90 953769 997 3 22.29272073 10.26576755 49.35554342 5.366563146
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

I3

Sample of J oined T ype 11 and 21 A ll Obser vations (C leaned)

Table I3 below provides images of a sample of the joined “all observations” data for crop/county combinations which include units flagged as organic. The columns are labeled 

row 11, org_flag11 (yes or no), rp_org, stfips (state FIPS), company, ID_num (identification number), cr_year (crop year), cr_id (crop id), ip_code (insurance provider code), 

ctyfips (county FIPS), type, prac (practice), coverage_level11, acres, liability, subsidy, premium, indemnity, LR (loss ratio), and LCR (loss cost ratio). The column labeled ID_num 

does not contain actual policy numbers but rather contain unique identifiers that allow policy level analysis. 

(Table I3 Data)

Data T able I 3 row11 org_flag11 rp_org stfips company ID_num cr_year cr_id ip_code ctyfips type prac coverage_level11 acres liability subsidy premium row21 indemnity LR LCR

1531 No AJ 19 601 2321746 2001 41 90 27 16 3 0.5 84.05 5888 158 158 0 0

901 No AJ 19 601 2321746 2001 81 90 27 997 2 0.5 66.15 4028 79 79 0 0 

1532 No AJ 19 601 2321761 2001 41 90 27 16 3 0.5 84 6692 159 159 0 0 

902 No AJ 19 601 2321761 2001 81 90 27 997 3 0.5 84 5481 101 101 0 0

1533 No AJ 20 601 946569 2001 11 90 125 997 3 0.5 71.0622 4278 117 174 0 0

1 No AJ 20 601 946600 2001 11 90 125 997 3 0.65 60.606 1765 276 467 0 0 

903 No AJ 20 601 946615 2001 11 90 125 997 3 0.5 50.692 1879 101 151 0 0 

904 No AJ 20 601 946638 2001 11 90 125 997 3 0.5 485.8977 21741 1015 1515 0 0

91 No AJ 20 601 1359907 2001 11 90 125 997 3 0.65 60.606 2868 194 328 0 0

905 No AJ 20 601 1371400 2001 11 90 125 997 3 0.5 18.315 409 29 29 0 0 

1534 No AJ 29 601 102700 2001 41 44 45 16 3 0.7 90.45 15947 1724 2921 0 0 

906 No AJ 29 601 102700 2001 81 44 45 997 3 0.7 165.15 16733 2086 3536 0 0

92 No AJ 29 601 109669 2001 41 44 45 16 3 0.55 370.4 57271 4278 6683 437880 8033 1.202005 0.140262

907 No AJ 29 601 109669 2001 81 44 45 997 3 0.55 202.2 21342 918 1435 0 0 

1535 No AJ 29 601 109992 2001 41 44 45 16 3 0.7 13 2395 168 285 328232 198 0.694736 8.27E-02 

93 No AJ 29 601 109992 2001 81 44 45 997 3 0.7 22.45 2788 181 306 387062 168 0.549019 6.03E-02

1536 No AJ 29 601 111223 2001 81 25 3 997 3 0.75 510 65307 4098 7451 0 0

94 No AJ 29 601 111338 2001 41 90 3 16 3 0.75 63.5 10525 711 1292 0 0 

2 No AJ 29 601 111338 2001 81 90 3 997 3 0.75 91 14083 631 1147 0 0 
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

I1

Sample of T ype 11 and 21 J oined Pair ed Obser vations

Table I4 below provides images of a sample of the joined “all observations” data for crop/county combinations which include units 

flagged as organic. The columns are labeled rp_org, stfips (state FIPS), company, ID_num (identification number), cr_year (crop 

year), cr_id (crop id), ip_code (insurance provider code), ctyfips (county FIPS), type, prac (practice), coverage_level11, Orow11, 

Oacres, Oliability, Osubsidy, Opremium, Orow21, Oindemnity, OLR (loss ratio), OLCR (loss cost ratio), Crow11, Cacres, Cliability, 

Csubsidy, Cpremium, Crow21, Cindemnity, CLR (loss ratio), and CLCR (loss cost ratio) . The column labeled ID_num does not 

contain actual policy numbers but rather contain unique identifiers that allow policy level analysis. (Table I4 Data)

Data T able I 4

rp_org stfips company ID_num cr_year cr_id ip_code ctyfips type prac coverage_level11 Orow11 Oacres Oliability Osubsidy Opremium Orow21 Oindemnity OLR OLCR Crow11 Cacres Cliability Csubsidy Cp

AX 8 631 6941323 2005 17 90 75 50 3 0.5 2212333 83.05 2564 469 699 0 0 670 34.017 1007 155 

AX 26 631 7146323 2006 81 90 91 997 53 0.5 2212347 406.3 34844 1687 2518 0 0 17548 88.3 7504 283 

AX 39 631 7648123 2006 41 90 125 16 3 0.5 2337925 39.4 3684 101 101 0 0 56599 180.5 17771 440 

AX 48 631 7538992 2005 21 90 329 997 2 0.5 2523240 78 13669 1029 1536 0 0 52396 472.95 116890 8382 1

AX 48 631 7538992 2006 21 90 329 997 2 0.5 2337928 98.7 18745 1531 2285 0 0 58017 447.478 134672 10474 1

CA 6 30 6212830 2002 54 86 97 112 997 0.5 2212376 18 9576 324 483 0 0 31718 157.15 70906 2278 3

CA 6 30 6924738 2002 54 86 97 112 997 0.5 1862443 9.8 5577 175 260 292136 3805 14.634615 0.682266 32679 131.4 84998 2724 4

CA 6 30 7456553 2004 54 86 97 112 997 0.5 2212446 9.8 8523 259 387 0 0 33158 132 124177 3994 

CA 6 30 7472792 2004 87 90 113 997 66 0.5 1862451 375.5 336344 7983 11914 0 0 33310 633.498 630031 11638 1

CA 6 30 7472846 2004 87 90 113 997 66 0.5 2523260 87.261 65675 2005 2992 0 0 116472 739.53 674158 14099 2

CA 46 30 7303746 2004 41 90 127 16 3 0.5 2523330 22 2857 92 137 0 0 178000 291.6 49326 1326 

CA 53 30 7411753 2004 54 86 71 114 2 0.5 2212591 83.1 126965 4845 7232 0 0 181811 1377.5 5855463 212833 3

CA 53 30 7411753 2004 54 86 71 115 2 0.5 2338092 159.9 395592 15098 22534 0 0 107198 2544.1 8823976 320730 47

CU 48 101 7538992 2004 21 90 329 997 2 0.5 1862564 60.1 11720 798 1191 0 0 116421 398.478 92257 5979 

DX 31 445 7728630 2004 17 90 105 50 3 0.5 2338113 36.993 840 108 154 0 0 124763 112.233 2546 312 

ET 16 349 3334569 2006 11 90 71 12 3 0.5 2338116 339.2 8404 1303 1944 41003 3829 1.96965 0.455616 124901 10 425 29 

ET 31 445 7728630 2005 17 90 105 50 3 0.5 2523395 29.997 807 125 177 0 0 252310 132.534 3565 493 

HK 26 232 567353 2005 16 90 11 997 3 0.5 2212887 5.5 264 21 32 0 0 166202 50.1 3381 167 
Organic Crops: Revised Written Rating Report

Use or disclosure of information or data Risk Management Agency

contained on this sheet is subject to the Contract No: AG-645S-C-09-0003

restrictions on the title page of this report.

I2