U.S. Department of the Interior Cooperative Agreement

Minerals Management Service Coastal Marine Institute

Gulf of Mexico OCS Region Louisiana State University

OCS Study

MMS 2003-018

Coastal Marine Institute

Modeling the Economic Impacts

of Offshore Oil and Gas Activities

in the Gulf of Mexico:

Methods and Applications

Authors

David E. Dismukes

Williams O. Olatubi

Dmitry V. Mesyanzhinov

Allan G. Pulsipher

July 2003

Prepared under MMS Contract

14-35-0001-30660-19967 and

14-35-0001-30951-16803

by

Center for Energy Studies

Louisiana State University

Baton Rouge, Louisiana 70803

Published by
iii

DISCLAIMER

This report was prepared under contract between the Minerals Management Service

(MMS) and Louisiana State University’s Center for Energy Studies. This report has been

technically reviewed by MMS. Approval does not signify that the contents necessarily 

reflect the view and policies of the Service, nor does mention of trade names or

commercial products constitute endorsement or recommendation for use. It is, however,

exempt from review and compliance with MMS editorial standards.

REPORT AVAILABILITY

Extra copies of the report may be obtained from the Public Information Office (Mail Stop 

5034) at the following address:

U.S. Department of the Interior

Minerals Management Service

Gulf of Mexico OCS Region

Public Information Office (MS 5034)

1201 Elmwood Park Boulevard

New Orleans, Louisiana 70123-2394

Telephone Number: 1-800-200-GULF

CITATION

Suggested citation:

Dismukes, D.E., W.O. Olatubi, D.V. Mesyanzhinov, and A.G. Pulsipher. 2003. 

Modeling the Economic Impacts of Offshore Oil and Gas Activities in the Gulf of 

Mexico: Methods and Applications. Prepared by the Center for Energy Studies,

Louisiana State University, Baton Rouge, La. U.S. Department of the Interior,

Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, La.

OCS Study MMS 2003-018. 88 pp.
v

ACKNOWLEDGMENTS

The authors would like to acknowledge the financial assistance of the Minerals

Management Service in funding a portion of this study through the Coastal Marine

Institute program at the Louisiana State University. Additional matching financial

support for this study was provided by the Center for Energy Studies, Louisiana State

University and its Industry Associates Advisory Board. We would like to thank Kim

Coffman, Stephanie Gambino, Vicki Zatarain, and Richard Desalles, all with the MMS,

for their comments, suggestions, assistance, and advice. We would also like to thank

Barbara Kavanaugh and Ric Pincomb at CES/LSU, for their research assistance.

During the course of our investigation, we received important and helpful input from a

number of individuals. They have been listed below.

Marion Ashton, American Petroleum Institute

David Cheshire, Exxon Mobil

Steve Crookshank, American Petroleum Institute

Jeffrey Falzarano, UNO School of Marine and Naval Architecture

Jimmy Gilbert, Bay Offshore

Paul Hillard, Badger Oil Company

Keith Long, Petroleum Technology Transfer Council

Buddy Manuel, Century Exploration

Buster McKenzie, Applied Technology Research, Inc.

Bob Moran, National Ocean Industries Association

Robert Mott, Independent Energy Consultant

Kellie Nuetter, Mustang Engineering

Ralph Pike, LSU Minerals Processing Institute

Chip Riemer, Vastar Resources

Ralph Russell, U.S. Department of Energy, Energy Information Administration

Carter Tannehill, Purvin & Gertz, Inc.

Earl Sims, Vastar Resources

Frank Smith, J. Ray McDermott

Larry Wall, Louisiana Mid-Continent Oil and Gas Association
vii

ABSTRACT 

Recent changes in oil and gas activities on the Gulf of Mexico (GOM or Gulf) Outer

Continental Shelf (OCS) have sparked interest in the economic impact that these

activities have on coastal regions. Over the past several years, the MMS has initiated a

number of different research projects of increasing degrees of sophistication, attempting

to examine the relationship between OCS activity and the socioeconomic environment of 

coastal regions on the GOM. Recent MMS approaches have included the use of a

common methodology known as Input-Output (I-O) modeling. I-O models examine 

relationships between industries and other economic agents within an economy. The

mathematical formulae used to construct an I-O allow a researcher to simulate the effects 

that a change in one or several economic activities has on the entire economy.

A shortcoming with most I-O analysis is that the impact drivers (or multipliers) in the

model are typically taken from sampled, nation-wide survey data. One primary driver in 

these models is the production function (or cost function) matrix that is an industryspecific calculation dividing commodity-specific input expenditures by total commodity

input expenditures. These ratios are generally calculated from nationally, rather than

regionally, relative production expenditure profiles. Such an approach assumes that

industries in any given area will use inputs in the same proportion as the national average. 

For oil and gas firms operating on the Gulf OCS, this assumes that input expenditures are 

made in the same proportion as the national oil and gas industry average. Such an

approach averages production costs shares from such varied regions as Alaska to the

offshore GOM.

This report addresses a number of methodological shortcomings in the application of I-O 

analysis to the oil and gas industry. Our report presents examples of how the two

approaches present differing empirical conclusions and why some modifications are in

order. We offer a number of practical and applied alternatives to existing methods, as

well as suggestions on improving production function and other standardized input data,

to improve the understanding of how the oil and gas industry impacts coastal

communities. We use coastal Louisiana as a case study for examining the implications of 

our work.
ix

TABLE OF CONTENTS

 Page

List of Figures........................................................................................................................xi

List of Tables .........................................................................................................................xiii

Section 1 Introduction: Why Examine Economic Impacts? ..........................................1

1.1 The Role of the Minerals Management Service.......................................1

1.2 Examination of Past Economic Impact Studies and Methods.................2

1.3 Purpose of This Study..............................................................................3

Section 2 How Are Economic Impacts of Offshore Activities Modeled? .....................5

2.1 Defining Offshore Expenditure Profiles..................................................5

2.2 Defining Offshore Activity Phases ..........................................................6

2.3 Defining Relevant Water Depths.............................................................7 

2.4 Defining the Onshore Allocation of Offshore Activities.........................8

2.5 Data Collection Issues and Challenges....................................................8 

Section 3 Alternative Methods and Approaches to Modeling Economic Impacts ........11 

3.1 Exploratory Drilling.................................................................................11

3.2 Development Drilling ..............................................................................13 

3.3 Production Costs......................................................................................14 

3.4 Platform Fabrication ................................................................................15

 3.5 Pipeline Construction and Operation.......................................................16

 3.6 Gas Processing and Storage Construction and Operation........................18

 3.7 Workovers................................................................................................18

 3.8 Oil Spills..................................................................................................18

 3.9 Abandonment...........................................................................................19

 3.10 Onshore Allocations of Cost..................................................................20

Section 4 An Application: Modeling the Impacts of Offshore Activities on Coastal 

Louisiana........................................................................................................21

4.1 Introduction..............................................................................................21

4.2 Review of Impact Analysis Methodologies.............................................22

4.3 Inter-Industry Economy Wide Models.....................................................23

4.4 Data Methods...........................................................................................24

4.5 Regional Multipliers and Impact Analysis...............................................25

4.6 The Coastal Louisiana Economic Impact Model.....................................26

4.7 Regional Purchasing Coefficient .............................................................26

4.8 Sectoral Aggregation................................................................................27

4.9 Empirical Results for the Base Model Scenario ......................................30

4.10 Empirical Results for New Offshore Oil and Gas Activities.................31

4.11 Summary and Conclusion of Impact Analysis.......................................37
x

Section 5 Conclusions and Suggestions for Future Research ........................................39

5.1 Onshore Allocations................................................................................39

5.2 Cost Functions By Technology...............................................................40

5.3 Contractor Expenditure Profiles .............................................................40

5.4 Public Finance.........................................................................................41

 5.5 Interregional Analysis.............................................................................42

 5.6 Project Summary and Conclusions.........................................................42

References............................................................................................................................. 45

Appendix A Industry Cost Tables ......................................................................................49

Appendix B Coastal Impact Tables....................................................................................65 

Appendix C Discussion of Input-Output Structure ............................................................83 

C.1 The Basic Structure of Theoretical Input-Output Models......................85 

C.2 The Basic Structure of Theoretical SAM Models..................................87

C.3 Common Accounts of an I-O or SAM Model........................................89 

C.3.1 Expenditure (Column) Accounts.............................................89

C.3.2 Production (Intermediate Demand) Accounts.........................89 

C.3.3 Factors Expenditure Accounts ................................................89 

C.3.4 Institutional Expenditure Accounts.........................................89

C.3.5 Household Expenditure Accounts...........................................90

C.3.6 Federal Government Expenditure Accounts ...........................90

C.3.7 State/Local Government Expenditure Accounts.....................90

C.3.8 Investment (Capital) Accounts................................................90 

C.3.9 Rest of the World (Trade) Expenditure Account ....................91

C.3.10 Receipts (Rows) Accounts.....................................................91 

C.3.11 Production (Intermediate Sales) Accounts.............................91

C.3.12 Value-Added Revenue Accounts ...........................................91

C.3.13 Institutional Income Accounts................................................91 

C.3.14 Household Income Accounts..................................................91

C.3.15 Federal Government Revenue Accounts................................92 

C.3.16 Capital (Savings) Account .....................................................92 

C.3.17 Rest of the World (ROW) Account........................................93 
xi

LIST OF FIGURES

Figure Description Page

2.1 MMS Gulf of Mexico Coastal Areas.........................................................................8
xiii

LIST OF TABLES

Table Description Page

2.1 Offshore Expenditure Categories............................................................................... 6 

2.2 Expenditure Profiles for Development Drilling by Water Depth .............................. 7

3.1 Comparison of Water Depth and Exploratory Drilling Depth...................................13

3.2 Comparison of Water Depth and Development Drilling Depth ................................14

4.1 Demographic, Social, and Economic Indicators of Louisiana

 Coastal Areas (1996)..................................................................................................21

4.2 Louisiana Model Aggregation Industry and IMPLAN Included Sectors...................28

4.3 Aggregated RPCs and SDPs......................................................................................29

4.4 Economic Impact Results of Oil and Gas Development in the Gulf of Mexico

1997-2031: LA1 Annual per Well Impacts................................................................32

4.5 Economic Impact Results of Oil and Gas Development in the Gulf of Mexico

1997-2031: LA2 Annual per Well Impacts................................................................33

4.6 Economic Impact Results of Oil and Gas Development in the Gulf of Mexico

1997-2031: LA3 Annual per Well Impacts................................................................33

4.7 Income Distribution Impacts: LA1 Area....................................................................34

4.8 Income Distribution: LA2 Area .................................................................................34

4.9 Income Distribution: LA3 Area .................................................................................35

4.10 Impact Result versus Base Model Result...................................................................36

5.1 Estimated Economic Impacts for Exploratory Drilling, LA-2 Region ......................43

A.1 Production Functions for Exploratory Drilling in the Gulf of Mexico by Major

Water Depth...............................................................................................................51 

A.2 Production Functions for Development Drilling in the Gulf of Mexico ...................52 

A.3 Production Functions for Offshore Production in the Gulf of Mexico......................53 

A.4 Production Functions for Platform Fabrication in the Gulf of Mexico......................54

A.5 Production Functions for Pipeline Construction in the Gulf of Mexico....................55 

A.6 Production Functions for Pipeline O&M in the Gulf of Mexico ...............................56

A.7 Production Functions for Gas Processing & Storage Construction in the Gulf of

Mexico .......................................................................................................................57

A.8 Production Functions for Gas Processing & Storage O&M in the Gulf of Mexico ..58 

A.9 Production Functions for Workovers in the Gulf of Mexico.....................................59

A.10 Production Functions for Oil Spills in the Gulf of Mexico .......................................60 

A.11 Production Functions for Platform Abandonment in the Gulf of Mexico .................61

A.12 Onshore Allocation of Offshore Expenses ................................................................62 

A.13 Total Cost Analysis: Summary of Total Costs by Offshore Activity and Water

Depth .........................................................................................................................63

B.1 Socioeconomic and Demographic Indicators.............................................................67 

B.2 Selected Socioeconomic and Demographic Indicators, All Louisiana ......................69 

B.3 Commodities With Modified Regional Purchasing Coefficient................................70

B.4 Adjusted RPC and State Domestic Product Ratio for Selected Commodities...........72

B.5 Onshore Allocation Ratios/Profile for LA1, LA2, LA3 in Gulf of Mexico ..............74
xiv

LIST OF TABLES (continued)

Table Description Page

B.6 Expenditure Allocation

B.6.1 LA Model Exploratory Drilling Expenditure Distribution by Water Depth..75

B.6.2 LA Model Development Drilling Expenditure Distribution by Water 

Depth..............................................................................................................75 

B.6.3 LA Model Production Drilling Expenditure Distribution by Water Depth ...76 

B.7 Implan Exogenous Shock Vector by Water Depth and Activity, and LA Area 

Activity

B7.1 LA1: Exploratory Wells.................................................................................77

B7.2 LA1: Development Wells..............................................................................77 

B7.3 LA1: Production Wells..................................................................................78 

B7.4 LA2: Exploratory Wells.................................................................................78

B7.5 LA2: Development Wells..............................................................................79

B7.6 LA2: Production Wells..................................................................................79 

B7.7 LA3: Exploratory Wells.................................................................................80

B7.8 LA3: Development Wells..............................................................................80 

B7.9 LA3: Production Wells..................................................................................81 
1

Section 1: Introduction: Why Examine Economic Impacts?

The impact of oil and gas activities on communities surrounding the Gulf of Mexico (GOM) has 

become increasingly more pervasive since offshore activities began in earnest in 1947. While

there have been numerous intermittent studies of the economic impacts these offshore activities

have had over the years, no regular, comprehensive approach has been developed by either

government, industry, or academia. The purpose of this research has been to assist the MMS in

developing a new and inclusive approach for understanding the economic impacts of offshore oil 

and gas activities on GOM coastal communities.

This research has three goals. First, to compile information on per unit costs associated with a

host of different OCS oil and gas activities over a number of different water depths. Second, and 

most importantly, to develop an industry-specific expenditure profile for a number of different

OCS oil and gas activities, over a number of different water depths. Third, to develop a general 

onshore allocation mapping for expenditures, by industry classification, to various GOM coastal

communities. Before discussing the issues associated with industry costs, this introduction will

outline the importance and role of the MMS in examining economic impacts of coastal

communities. This discussion is followed by an overview of past economic impact studies on

offshore activities, followed by a discussion of the methods used to estimate offshore industry

cost characteristics and impacts.

1.1 The Role of the Minerals Management Service: The economic impact of offshore

activities has become an increasingly important issue to the Department of Interior, Minerals

Management Service (MMS). A very large portion of this research is subsumed within the

agency’s Environmental Studies Program (ESP) and defined in its National Strategic Plan (NSP).

The ESP Strategic Plan addresses a wide variety of environmental concerns and issues on a

national scale by identifying emerging and ongoing program areas. It complements and builds

upon broader strategic plans that set agency-wide policies and directions. Within these broad

issues or themes, multi-disciplined studies will be developed, as budget allocations allow (LTG

Associates, Inc., 2000).

The socioeconomic studies component of the program: 

• Provides information essential to understanding the consequences of OCS-related 

activities for the populations, economies, and social and cultural systems in areas where 

the activities occur;

• Supports the MMS’s planning and management processes; and

• Provides information essential for effective interaction with the public about the effects 

of OCS activities (LTG Associates, Inc., 2000).

MMS’ primary legal mandate to analyze the socioeconomic impacts of natural resource

management issues is provided in both the Outer Continental Shelf Lands Act, as amended in
2

1978 (OCSLAA), and the National Environmental Policy Act of 1969 (NEPA). Section 18 of

the OCSLAA mandates that MMS management of the OCS shall consider the “economic, social, 

and environmental values of the renewable and nonrenewable resources contained in the Outer

Continental Shelf, and the potential impact of oil and gas exploration on other resource values of 

the marine, coastal, and human environments” (43 USC 1344). “Human environment” includes

“the physical, social, and economic components, conditions, and factors which interactively

determine the state, condition, and quality of living conditions, employment, and health of those 

affected, directly or indirectly, by activities occurring on the Outer Continental Shelf...”(43 USC 

1333).

NEPA requires federal agencies engaged in significant land actions to assess impacts, including

those on the human environment, through the process of conducting Environmental Impact

Statements (EIS) (MMS, 1996). The Council on Environmental Quality’s (CEQ) Regulations for 

Implementing the Procedural Provisions of NEPA state that the human environment is to be

“interpreted comprehensively” to include “the natural and physical environment and the

relationship of people with that environment” (40 CFR 1508.14). An action’s “aesthetic, historic, 

cultural, economic, social, or health” effects must be assessed, “whether direct, indirect, or

cumulative” (40 CFR 1508.8). CEQ regulations state that when “economic or social and natural

or physical environmental effects are interrelated, the EIS will discuss all of these effects on the

human environment” (40 CFR 1508.14). 

Over the past several years, the ESP has become increasingly engaged in the socioeconomic

research of coastal communities in support of its EIS mission for the GOM Region (GOMR). In 

the past 10 years, the quantity of research funded under this program has tripled. While one

cannot predict funding levels in years to come, a recent meeting of social scientists and

researchers indicated that interest and commitment to these issues will continue to be strong. 

Of the three major MMS regions (Alaska, Pacific, and Gulf of Mexico), the Gulf of Mexico 

appears to have a pressing need for continued socioeconomic impact analyses. The Gulf, in

addition to providing a significant number of reserves and production, is also undergoing unique 

developments in both deepwater activity (900 meters and deeper) and the potential development

of frontier areas in the eastern Gulf off the coast of Florida. In addition, drilling moratoria and

uncertainties in the Pacific and Alaska make GOMR the only place where significant action is

envisioned over the next several years.

1.2 Examination of Past Economic Impact Studies and Methods: As early as the mid-1980s, 

the GOMR began its efforts to model the implications that offshore development had on coastal

communities. For close to 10 years, however, a good portion of these regional modeling

initiatives focused more on past consequences of OCS oil and gas development than on

predictive or forecasting methods. These initiatives could be broken into two general categories: 

(1) individual historic “consequences” analyses; and (2) the development of baseline analyses

(Luton and Cluck, 2000). Information from both types of studies was regularly used as a basis

for understanding economic impacts to local communities for EIS purposes.

This study employs an Input-Output (I-O) modeling framework. Such an approach attempts to

shift the direction of analysis away from historical consequences and towards more forward-
3

looking impacts. Over the past several years, there has been a concerted effort by the MMS to

develop increasingly more sophisticated modeling approaches that incorporate both quantitative

rigor and applied realism. One of the first studies to examine offshore activities from a more

rigorous and applied perspective was conducted by Foster Associates (FA Study) for the federal

waters off the coast of Alabama (Kelley and Wade, 1999; Wade and Mott, 1998). The FA

Study revealed a number of unique expenditure patterns that were required to support production 

of caustic (high H2S) natural gas. The results of the FA Study help move MMS in the direction

of: (1) employing I-O models as a basis for measuring the economic impact of all offshore

activities and (2) incorporating real-world differences in the production characteristics of

particular offshore areas.

The FA Study also highlighted one of the major advantages of moving forward with the use of IO models – their ability to allow a researcher to simulate the effects that a change in one or

several economic activities would have on the entire regional economy. It is predictive in the

sense that the economic impacts associated with hypothetical events, like the opening of several

new offshore blocks in the Gulf of Mexico, can be quantitatively modeled. The approach is also 

comprehensive since the I-O structure allows researchers to understand how exogenous shocks

impact entire regional economic systems, and not just the limited impacts on particular sectors

like only oil and gas activities.

In addition to breadth, these studies also provide depth of quantitative information. I-O 

techniques offer the advantage of measuring the direct, indirect, and induced impacts associated

with offshore activities. The indirect and induced impacts are commonly referred to as

“multiplier impacts” associated with a direct economic shock. These multiplier impacts quantify

the idea that a dollar impact has ripple effects throughout a regional economy.

1.3 Purpose of This Study: As noted earlier, a common shortcoming with most I-O analysis is 

that the impact drivers (or multipliers) in the model are typically taken from national, as opposed 

to regional trends and industries. Such an approach assumes, among other things, that industries 

in any given area will use inputs in the same proportion as the national average. For oil and gas

firms operating on the Gulf OCS, this assumes that input expenditures are made in the same

proportion as the national oil and gas industry average. Not only does such an approach assume

regional similarities, but it also assumes that onshore and offshore production functions are

similar. It is this last problem that causes the most difficulty in using existing regional I-O 

models to examine the economic impacts of offshore activities. The purpose of this research is

to discuss methodological and data collection methods that can help remedy this potential

problem and results of specialized data collection.

There are a number of methodological issues associated with modeling something as

complicated and multifaceted as the offshore oil and gas industry. The research goal here is not

to address every methodological issue, but concentrate on four of the more important issues that

were identified by MMS. These four research issues include:

(1) Defining unique offshore expenditures, and their relevant industry

classifications/sectors, and incorporating these into a standard economic inputoutput framework;
4

(2) Defining expenditure profiles for specific offshore activity phases and water

depths;

(3) Allocating activity-specific offshore expenditures to onshore areas; and

(4) Identifying the total costs associated with each of the “typical” activities in each

respective water depth category.

Over the past several years MMS has moved toward more quantitative, forward looking

economic impact models. The purpose of the study is to assist in moving this initiative several

steps further. In addition, a case study is developed that examines the implications of offshore

activities, using the new methods identified above, for coastal Louisiana.
5

Section 2: How Are Economic Impacts of Offshore Activities Modeled?

2.1 Defining Offshore Expenditure Profiles: The exploration, development, operation and

eventual decommissioning of offshore facilities is a considerable logistic challenge. These

challenges are often revealed in the types of expenditures that are made by offshore operators. 

Thus, the first step in an analysis of this sort is to define a relevant set of expenditure categories

taking into account many of the unique offshore oil and gas activities. Some of the expenditure

categories that have unique implications for offshore oil and gas activity phases include:

Water and Air Transportation: Modes of transportation that are important in moving

both personnel and equipment from onshore supply and staging bases to areas supporting 

offshore activities;

Food and Catering Services: Often food and catering services are contracted by offshore 

operators to feed crews supporting exploration, development, and production activities;

Water Supply: Potable water for drinking, as well as water for certain types of drilling

muds, lubricants, and fluids, have to be transported to offshore areas;

Waste Disposal: While this activity is important to both onshore and offshore activities,

transportation and onsite storage can create a number of unique logistical challenges to

offshore activities; 

Turbines and Fuel: Most offshore platforms have both primary and secondary power

generation equipment as well as primary, and in some cases secondary, fuel to operate

these generators; and

Communications, Instrumentation and SCADA (supervisory control and data acquisition) 

Systems: Digital and mobile technologies have had a growing importance for offshore

activities.

During the course of this research, MMS was provided with a comprehensive listing of the

unique expenditure categories, and their IMPLAN sector identifications. The categories used in

modeling the economic impacts of offshore activities have been provided in Table 2.1.
6

Table 2.1: Offshore Expenditure Categories

IMPLAN Sector Description IMPLAN Sector Description

Sectors Sectors

38 Oil & Gas Operations 399 Transportation Equipment, NEC

50 New Gas Utility Facilities 401 Lab Equipment

53 Msc Nat Resource Facility Construct 403 Instrumentation

56 Maintenance and Repair, Other Facilities 435 Demurrage & /Motor Freight

57 Other Oil & Gas Field Services 436 Water Transport

160 Office Furniture and Equipment 437 Air Transport

178 Maps and Charts (Msc Publishing) 441 Communications

206 Explosives 443 Electric Services

209 Chemicals, NEC 444 Gas Production/Distribution

210 Petroleum Fuels 445 Water Supply

232 Hydraulic Cement 446 Waste Disposal

258 Steel Pipe and Tubes 454 Eating/Drinking

284 Fabricated Plate Work 455 Msc Retail

290 Iron and Steel Forgings 459 Insurance

307 Turbines 462 Real Estate

311 Construction Machinery & Equipment 469 Advertisement

313 O&G Field Machinery 470 Other Business Services

331 Special Industrial Machinery 473 Msc. Equipment Rental and Leasing

332 Pumps & Compressors 490 Doctors & Veterinarian Services

354 Industrial Machines, NEC 494 Legal Services

356 Switchgear 506 Environmental/Engineering Services

374 Communication Equipment, NEC 507 Acct/Msc Business Services

392 Shipbuilding and Ship Repair 508 Management/Consulting Services

509 Testing/Research Facilities

2.2 Defining Offshore Activity Phases: Another important area of examination is defining the 

relevant offshore activity phases. Most I-O models, as well as National Income and Product

Accounts (NIPA), treat oil and gas activities in a highly aggregated manner. As noted before,

onshore and offshore activities are rarely separated, and even then, are aggregated into either

drilling or production activities. MMS, however, must consider a range of offshore oil and gas

activity phases over relatively long periods of time.

The activity phases that were defined by MMS as being important for socioeconomic modeling

purposes include: Exploratory Drilling; Development Drilling; Platform Fabrication and

Installation; Pipeline Fabrication and Installation; Pipeline Operation and Maintenance (O & M); 

Gas Processing Installation O & M; Production; Workovers; Oil Spills; and Platform Removal & 

Abandonment. 

For typical EIS analyses, socioeconomic analyses will begin with a forecast of activities (in

units) for each of the above activity phases. These forecasts are developed independently by the

GOMR Office of Resource Evaluation Division within MMS. These units, when multiplied by

total costs, yield the total potential economic shock resulting from that activity. Thus, if a given 

potential lease sale is forecasted to yield five (5) new exploratory wells at an average total cost of 
7

$4 million per well, then the total direct economic shock would be $20 million. The next step in 

the process is to allocate this $20 million impact by the expenditure profile developed for

exploratory drilling.

It is important for impact modeling to develop different expenditure profiles by activity phase

given their tendency for variability and substantial compositional differences. In addition, there

is a tendency for expenditure patterns, and their relative compositions, to shift as the

development of a potential lease matures. This has implications for economic impacts since

many expenditures can move from more capital intensive, construction-oriented activities in the

exploration, development, pipeline, and gas processing construction phase, to more labor

intensive, maintenance oriented activities in the production, workover, gas processing and

transportation activities.

For instance, steel pipe expenditures can represent anywhere between 35 to 59 percent of total

expenditures during platform fabrication activities yet represent only three percent of total

expenditures during the production phase. Likewise, instrumentation costs can represent close to 

three percent of total expenditures during production but could be a relatively insignificant cost

during all other offshore activity phases.

2.3 Defining Relevant Water Depths: Another methodological challenge rests with modeling

variations in expenditure profiles across water depths. For instance, should, or do, expenditure

profiles change as offshore activities move into deeper waters? One might think that there is a

positive relationship between certain relative costs and water depth. Water transportation costs

comes to mind as being a relative cost that should increase as water depth, and hence distance,

increases. However, the unique realities of offshore activities, coupled with inconsistencies in

data collection and (internal) reporting, can lead to significant challenges in what should appear

to be an obvious conclusion. Table 2.2 presents an example of expenditures for development

drilling where shifts in expenditure trends are obvious for Sector 38 (oil and gas operations).

Table 2.2: Expenditure Profiles for Development Drilling by Water Depth

Sectors Sector Description 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters

38 Oil & Gas Ops 0.65341 0.52344 0.64192 0.69198

57 Other Oil & Gas Svc 0.03447 0.02107 0.04069 0.03348

210 Petroleum Fuels 0.02746 0.03349 0.03049 0.02664

232 Hydraulic Cement 0.06566 0.11871 0.07490 0.06410

258 Steel Pipe and Tubes 0.07104 0.15527 0.06077 0.05149

313 O&G Field Machinery 0.01545 0.01524 0.01039 0.00947

403 Instrumentation 0.04110 0.04222 0.04375 0.03817

436 Water Transport 0.08355 0.08276 0.08873 0.07739

437 Air Transport 0.00787 0.00780 0.00836 0.00729

Total 1.00000 1.00000 1.00000 1.00000
8

2.4 Defining the Onshore Allocation of Offshore Activities: The allocation of expenditures to 

onshore areas is probably one of the more important factors for determining the region-specific 

economic impacts associated with offshore activities. These break-outs are important because

they define the localities that are most affected by what happens offshore. There are historic

tendencies for certain onshore support activities to be concentrated in particular geographic 

areas. This concentration has historically been primarily in Louisiana and Texas, and has

continued despite the movement of offshore activities into deeper water and into the CentralEastern portions of the Gulf of Mexico.

Part of this research included the development of allocations for offshore expenditures, by

commodity categories outlined in Table 2.1, to the 10 major onshore regions defined by MMS

that has been presented in Figure 2.1. Additional areas included in the analysis include the noncoastal Gulf of Mexico, and Rest of US/World (ROW). 

Figure 2.1: MMS Gulf of Mexico Coastal Areas.

2.5 Data Collection Issues and Challenges: During the course of this analysis, two data

collection issues became particularly important:

(1) How to identify, locate, and secure reliable sources of information that did not

require the use of survey instruments; and
9

(2) How to reconcile reported accounting information to economic factors examined

in traditional input-output modeling.

The first issue was the more problematic of the two and one that can confound time-sensitive 

MMS social science research. This research needed to find a way to collect information that did 

not use survey or survey-type instruments. Therefore, mailing survey questionnaires to

numerous companies operating offshore was not allowed. This restriction on data collection is

placed on MMS, and other federal agencies by the Paper Work Reduction Act of 1980, which

was reauthorized in 1995. 

This purpose of the Act is to minimize the paperwork burden the federal government places on

the public and to improve the quality and use of federal information (Lauterbach, 2000). The

Act also requires each federal agency to seek and obtain approval from the Office of

Management and Budget (OMB) before requesting information from ten or more persons.

Furthermore, any reporting, record-keeping, or disclosure requirement contained in a rule is

deemed to involve ten or more persons. OMB approval is also needed to continue a collection

for which OMB’s approval and the validity of the OMB Control Number are about to expire.

OMB usually approves a collection for a maximum of three years.

In order to use a survey-based approach for this research project, a survey instrument review

process would have been initiated that, under the best of situations, would have taken six to eight 

months. Another four to six months probably would have been required to execute the survey,

assuming the best of luck on survey responses and data collection. This project, like many

MMS-funded research projects, was time sensitive, and needed for immediate use. OMB survey

requirements, in this instance, seemed too onerous to use as a vehicle for collecting this type of

information.

An alternative approach was to compile the required information from a variety of different

sources, which varied by offshore activity phase. In general, secondary source information was

scoured. This included a review of all relevant government, industry, trade, and academic

publications, periodicals, and databases. Some of these publications were readily available and

straightforward. For instance, there is considerable information on drilling expenditures and

patterns in the Joint Association Survey of the U.S. Oil and Gas Producing Industry compiled

annually and published (jointly) by the American Petroleum Institute (API), the Independent

Petroleum Association of America (IPAA), and the Mid-Continent Oil and Gas Association. 

Likewise, there is considerable information on pipeline construction costs and expenditures that

are required filings regularly made before the Federal Energy Regulatory Commission (FERC).

When direct “secondary” sources of published information were unavailable, the research was

forced to turn to information requests from industry, or to rely on trade association information

and surveys previously (and independently) compiled. These requests were limited and did not

violate the spirit or intent of the Paperwork Reduction Act. Information gathered in this process 

was simply used to “fill-in-the-blanks” from the search of secondary sources of information.

An additional data issue associated with this project was reconciling disparate documents and

information, most of which were provided in accounting-based formats, into economic
10

information for modeling purposes. Accounting information, for instance, rarely makes

distinctions between fixed and variable costs or clear cut differentiations between capital and

labor. Likewise, expenditures are made by types which may not have a readily apparent or even

mixed-industry classification. Thus, a painstaking process of reviewing accounting information

on a line by line basis was required. Because both accounting entries and the economic

classifications included in Appendix Table B.5 are limited, judgment calls were required to

separate a limited amount of information into limited classifications.

The process of utilizing judgment on some classifications was most apparent in dealing with

contracted services. Many costs associated with offshore activities would appear as contracted

services from one firm to another, although both were engaged in the same activity. For

instance, a company developing an exploratory well(s) would often, particularly in shallow

water, contract drilling services out to a separate company. This company, in turn, would have

direct expenditures for labor, materials, equipment, and other items that would “escape” the data 

collection process. The data received for this research, usually from the E & P Company

initiating a drilling project, recognized a drilling contractor was utilized, but was unable, from

that point, to identify subsequent expenditure allocation. Admittedly, this has led to slight biases 

(overstatements) in general categories such as IMPLAN sector 38 (oil and gas operations) or

Implan sector 57 (other oil and gas field services).
11

Section 3: Alternative Methods and Approaches to Modeling Economic Impacts

The previous section of this report outlined the main methodological issues associated with

developing unique offshore production function, total cost, and allocation information. This

section, divided into two parts, will discuss the actual mechanics of compiling information in

each area. First, the production function and total cost information analysis, per activity phase, is 

discussed. Second, the collection and results from the onshore allocation analysis is described.

3.1 Exploratory Drilling: The first task undertaken was a comprehensive search for

information that decomposed costs into specific cost categories for exploratory drilling activities. 

Such information would facilitate the development of an expenditure profile. This research

canvassed a number of areas that included trade journals and magazines, technical reports,

government research and analysis, and the academic literature. The research revealed little to no 

publicly available information. The only source identified was a drilling cost survey conducted

by the Independent Petroleum Association of America (IPAA) in the early 1990s. The purpose

of this IPAA survey was twofold: it examined cost allocations (expenditure profiles) for typical

drilling activities, and it attempted to track cost inflation, by component, across time. This

survey, unfortunately, suffered from two shortcomings. First, it examined only onshore drilling

and equipping wells. Second, the survey was discontinued for cost reasons in 1994, and even

here was aggregate continental United States data. 

Given the lack of available information, the research turned to alternative information sources. 

The first alternative source of information that was relied upon came from industry. A number

of industry sources offered accounting information on booked annual expenditures for

exploratory wells. These accounting reports are referred to as either Allowances for

Expenditures (AFE) or “Post Well Critiques.” The information is provided in an accounting

format, and more specifically, in the accounting format of any given company providing the

information. The challenge in using this data was to take identified expenditure categories and

reconcile them to standard Implan codes.

The second source of information relied upon was a type of engineering project cost estimation

software known as Fieldplan Pro. This software, developed by Brown and Root, is regularly

used by the MMS GOMR Office of Resource Evaluation for a variety of purposes. This

software is developed in a manner that allows users to “price-out” a particular oil and gas project 

under different drilling and/or production configurations in the Gulf of Mexico. In this portion

of the analysis, a number of hypothetical projects in the Gulf were developed and run through the 

Fieldplan Pro software. The Fieldplan output was then compared to expenditure profiles that

were provided by industry. The output from Fieldplan served as both a data input, and “sanity

check” for industry provided information. Other studies of offshore activities have facilitated a

similar approach.1

The use of the Fieldplan software was instrumental for three reasons. First, and foremost, the

Fieldplan software can provide information on a number of “blanks” when publicly available

information was missing. Second, Fieldplan provides a different engineering-oriented 

 

1

 See MMS Royalty Relief Study (p. 10). The approach is similar in many respects to that taken in a recent National 

Energy Technology Lab (NETL) study on marginal properties in the GOM.
12

perspective in understanding the difference in cost and expenditure allocations. Third, Fieldplan 

breaks costs into categories without any assumption on who performs those functions. This

helps avoid the problem associated with contracting services. All costs are “internalized.”

Appendix Table A.1 presents a breakout of the estimated exploratory drilling expenditure

profiles. Expenditure profiles for each water depth have been presented in a column. The far

right column presents a simple average across all water depths. The overwhelming proportion of 

expenditures for exploratory drilling falls into Implan Sector 38: Oil & Gas Operations. This

sector classification is essentially a “catch-all” category for a number of different activities that

includes technical engineering work, drilling work, mobilization, site preparation, rig moving

expenses, among others. After consultation with industry sources, it was concluded that a large

portion of shallow water drilling costs were allocated to contractor services. As operations

moved into deeper waters, more of these activities tended to be performed by more in-house 

personnel, hence the relative decrease in Implan Sector 38 activities. The remaining expenditure

categories include: oil and gas field services; instrumentation; and transportation (air and water). 

Deviations across water depth were relatively minimal since the output from Fieldplan Pro was

relied upon quite heavily. This is particularly true for Implan Sector 38 expenditures, which is

the main cost driver. Such trends were not true with our industry-specific data, which showed

considerable leaps across water depths. For instance, the information that was provided by

industry data showed higher percentages, 72.5 percent for sector 38 expenditures in the lower

water depth category (0-60 meters) as opposed to deeper water depths (900 meters and deeper)

where expenditures were only 51.7 percent. Clearly this was a problem of both cost/accounting

categorization, as well as the fact that the “sample” of companies, from which actually

information was collected, was limited.

The next major task was to gather estimates of the total costs for exploratory drilling on a per

well basis. Total cost estimates serve as the mechanism for creating the direct shock associated

with exploratory drilling. Thus, if the cost for any given exploratory well is $4 million, then the 

addition of 4 new exploratory wells will generate a $16 million direct shock or impact on coastal 

economies.

Total cost information comes from total cost survey data generated through the American

Petroleum Institute’s (API) Joint Industry Association Survey for the year 1999. API made total 

annual costs, associated offshore drilling, available to our project. The next step in examining

these total costs was to reconcile water depths associated with the survey to those used by MMS. 

As seen in Appendix Table A.13 there is a minor anomaly associated with drilling costs in the

60-200 meter category. Costs per well fell from $4.2 million in 0-60 meters to $3.2 million in

60-200 meters. Such a trend is counter to the expectation that drilling costs should increase as

water depth increases. 

There may be a reasonable explanation for this result. First, this information is collected from

survey data, and the number of wells in the 60-200 category is substantially lower than any of the 

other sample categories. Second, and more importantly, the average total drilling depth (sub

surface) is much shallower for wells located in 60-200 meters of water than in other water depth 
13

categories. These drilling depths, and their associated water depth categories are presented

below.

Table 3.1: Comparison of Water Depth and Exploratory Drilling Depth

Water Depth

(Meters)

Survey Number 

(Wells)

Total Drilling Depth

(Feet)

0-60 36 9,898

60-200 21 7,705

200-900 48 10,846

900 and deeper 88 13,031

3.2 Development Drilling: Research associated with development drilling proceeded along

virtually the same lines as that was discussed in exploratory drilling. Publicly available

information was queried yielding no sources that separated offshore development spending

profiles. The estimation, therefore, turned to the use of a combination of informally provided

industry sources and Fieldplan Pro simulations. Industry sources, in development drilling

activity, were comprised of one major oil company and one independent (for shallower water

depths).

The results from the estimated expenditure profile are presented in Appendix Table A.2. The

results, like exploratory drilling, are relatively stable, however there are a few areas of interest 

that should be pointed out. The first is that there is a noticeable drop in expenditure percentages 

corresponding to the more generalized oil and gas activity sectors (Sector 38 and Sector 57) in

the 60-200 meter water depth category. This shift is offset by relative increases in mud (Sector

232) and piping (Sector 258). This shift could be a reflection of changes in total drilling depth

that are substantially more noticeable in development drilling than in exploratory drilling.

Another noticeable development is the expected shift in expenditures, from exploratory to

development drilling, as wells are prepared for production activities. There is a noticeable shift,

for instance, towards greater relative expenditures in mud (Sector 232), piping and tubes (Sector 

258), and oil and gas field machinery (Sector 313).

Total development drilling costs also came from the 1999 API Joint Industry Association

Survey. These costs have been provided in Appendix Table A.13. Like exploratory drilling,

there is a noticeable drop in unit costs at the 60-200 meter water depth level. The rationale for

these decreases are similar in nature to the ones identified in exploratory drilling. In addition to

the smaller sample sizes in the 60-200 meter category, there were significant differences in total

drilling depth associated with development wells in the 60-200 meter water depth. Development 

drilling depths fall in the 60-200 meter category, relative to other water depths: hence, the

paradoxical shift in drilling costs for this water depth category. Both of these statistics have been 

presented below.
14

Table 3.2: Comparison of Water Depth and Development Drilling Depth

Water Depth

(Meters)

Survey Number 

(Wells)

Total Drilling Depth

(Feet)

0-60 86 8,868

60-200 72 5,438

200-900 117 11,128

900 and deeper 137 15,255

3.3 Production Costs: The analysis of offshore oil and gas production costs started with a

survey of publicly available information. The API Joint Industry Association Survey is perhaps

the most readily available and recognized source of information on total cost. However, there is 

little recognized work that examines production expenditure profiles. In this investigation,

however, an existing source of information was available. This source, published by the U.S.

Department of Energy, Energy Information Administration (EIA), is entitled Cost and Indices

for Domestic Oil and Gas Field Equipment and Production Operations. As noted in the

publication, several past efforts in measuring production cost (by component) no longer exist. 

The annual DOE report represents the sole source of information on oil and gas production cost

components. During the course of this research, EIA made a number of the detailed workpapers 

associated with calculating production costs available.

The EIA approach in estimating production costs is based upon a “price-out” approach to

production at an offshore lease. In order to “price-out” a typical operation, EIA analysts spend

the better part of 12 months collecting cost information from vendors supporting all types of

activities from workovers to communications to catering. These surveys are conducted annually

prior to report publication. In addition to vendor information, other service and equipment costs

are collected and tabulated. EIA engineers then use a typical offshore configuration to add-up all 

equipment and service costs. These cost components are relatively constant over time allowing

for cost indices to be developed.

EIA workpapers made available to this research were decomposed in a number of different ways. 

First, EIA cost information was to match the existing Implan Sector codes. Data was adjusted to 

remove the costs associated with well workovers, that were examined separately, and will be

discussed in a later section of this report. The second step in the analysis was to take the

adjusted EIA expenditure profile and calculate the relative percentages associated with the

remaining cost data.

Appendix Table A.3 provides the breakout of the estimated expenditure profile for oil and gas

production. The relative breakouts are stable enough to not warrant any considerable alarm, yet
15

there are some differences worthy of note. First, Sector 38: Oil & Gas Field Operations, which

consists primarily of engineering functions, is stable in absolute value across water depths. On a 

relative basis, however, these activities decrease in the deep-water categories since a number of

other activities are strongly influenced by water depth. This is most notable in both air (water

decreases as a percentage) transportation and insurance costs, which increase dramatically as

operating water depth is increased.

Clearly, transportation costs increasing as water depth, and hence, distance, increases probably

comes as no surprise. What is interesting, however, is the increase in insurance costs. Theory

suggests that insurance premiums should increase as the net expected value of a loss increases. 

This can change by either higher probabilities of a loss, or increased value of lost equipment,

production, property, and life associated with deeper water activities, ceteris paribus. 

Total costs were developed using the EIA price-out approach. These total (annual) costs have

been presented in Appendix Table A.13. These costs appear to be reasonable and follow

relatively stable trends. Costs are increasing over water depth, but in a fashion that seems to

account for strictly depth-specific costs such a transportation (deeper water translates roughly to

further distances) and insurance (deeper water translates into higher expected value of a loss

associated with an offshore accident).

3.4 Platform Fabrication: Publicly available information on platform fabrication is sparse. 

Some recent media reports, for instance, have been known to cite total cost estimates for

constructing platforms, yet these reports are usually sporadic, isolated, and focus on the more

recent (deepwater) projects. In addition, these reported figures can often clutter total project cost 

information with total platform-specific costs.

Early in the project, some generalized, but highly subjective information, from the University of

New Orleans School of Naval Architecture was secured. The opinion oriented nature of the

information, along with the lack of breadth in its scope led to searches for supplementary and

corroborating information. Given the lack of published alternative information, this research

turned to the Fieldplan simulation tool as a source for verification and to supplement the

information provided by UNO.2

Fieldplan runs examined three different construction options within each different water depth. 

Each option, however, was limited to a “typical” type of platform/offshore structure. In the 0-60 

meter water depth, for instance, three different fixed platform structure configurations were

examined. The 60-200 meter category also examined fixed structures of a much larger scope

than those employed in shallow water. In the 200-900 meter category, the

fabrication/installation of three different types of tension leg platforms (TLP) were examined. In 

the 900 meter and deeper category, three different configurations of a Spar were used as the

typical platform technology. 

The next step in the analysis was to classify each of the engineering cost components to Implan

codes. Subsequently, a set of blended estimates was developed based upon the three simulations. 

 

2

 UNO was sent a table of likely platform fabrication cost components and asked to “populate” the table based upon 

subject matter expertise across various water depths.
16

The blended estimates from Fieldplan were compared to those provided by UNO. Fieldplan

estimates were selected over the UNO estimates since these estimates tended to be more detailed, 

and appeared to have less of a subjective composition.

The production function for platform fabrication has been included in Appendix Table A.4. An

examination of this table shows a number of interesting trends as water depths are increased. 

Most noticeable is the fact that the percentage of expenditures in shipbuilding and ship repair

(Sector 392) falls as depth increases. This suggests that a good amount of shipbuilding and ship 

repair is increasing at a rate that is less than other components as operations move across deeper 

water depth categories.

The relative cost share of steel pipe and tubes (Sector 258) increases. Unsurprisingly,

transportation costs associated with placing the structures (air and water) increase with water

depth, and hence distance, increases. Most of the other remaining categories, reflecting

expenditures on equipment, machinery, pumps and turbines, are relatively constant.

For consistency purposes, total platform fabrication costs were developed from the Fieldplan

simulation tool. These total cost estimates were generated by blending (or averaging) the three

different platform configurations for each water depth category. This is a reasonable approach in 

developing total platform fabrication costs since total cost simulation is ultimately one of the

primary purposes of the Fieldplan software. 

3.5 Pipeline Construction and Operation: The original research design for this project 

anticipated having one category for all pipeline activities. However, early in the process, it

became apparent that there should be some differentiation between construction-oriented 

activities and operation-oriented activities associated with pipelines. Construction-oriented 

activities, for instance, tend to have relatively larger, but one-time, economic impacts on local

communities. Impacts associated with operations, while longer term in nature, have minimal

employment and direct economic impacts. Thus it is important to separate pipeline activities, so 

that future MMS modeling would be able to minimize potential modeling errors and biases on a

forward going basis. This could become an increasingly important problem as MMS EIS’ focus

on the impacts of deeper water development where there is less developed pipeline

infrastructure.

Offshore pipelines that are not gathering systems are regulated by the Federal Energy Regulatory

Commission (FERC), under the Natural Gas Act (NGA), as well as the Outer Continental Shelf

Lands Act (OCSLA). Because of their regulated status, offshore pipelines are required to file

annual reports with the FERC. The FERC requires all cost and capital expenditure information

to be reported in a consistent manner. For natural gas pipelines, this information is required to

be filed in what is referred to as the FERC Form 6.

Given the detailed and highly reliable nature of the FERC Form 6 data, we used this information 

as the basis of the analysis of pipeline construction and operation expenditure. However, before 

discussing how this information is utilized, it should be noted that FERC information is not

without its potential limitations as well. First, like other information collected in this project,

FERC data is accounting oriented by nature and was not collected with economic impact
17

modeling in mind. Second, FERC information could have certain biases since major

transportation companies, that have both onshore and offshore operations, will dominate the

sample.

In terms of using the FERC information, the initial challenge was to separate the important from 

unimportant information. The first report examined was the balance sheet, or capital asset

composition, for each offshore pipeline company. In examining this information, the analysis

concentrated on only those companies with offshore assets that file a FERC Form 6. The second 

report we examined was the income statement, that highlights major annual expenditures

associated with output, or in this case, through-put. 

The first task was to remove companies from both reports (balance sheet and income statement)

that did not have offshore assets. The second step was to segregate companies by the primary

water depths in which they operate. This was a required step since data is filed with the FERC

on a “per-company,” as opposed to a “per-pipeline,” basis. Companies were assigned to water

depths based upon the miles of pipeline segments they owned/operated within certain water

depths. Pipeline segment ownership statistics were compiled from the Foster Associates survey

on offshore pipelines, that is actually generated from data collected by the MMS.

The next step in the analysis was to map the cost and asset categories into Implan sectors. 

Fortunately, costs for all offshore pipeline companies are required to be filed under a FERCdefined Uniform System of Accounts (USOA). Our job was to map these USOAs into Implan

Codes. After the relevant sectors were identified, two sets of allocations/profiles were developed: 

one associated with capital expenditures, and the other associated with operational expenditures.

The capital and operation expenditure profiles can be found on Appendix Table A.5 and

Appendix Table A.6, respectively. Both of these profiles tend to be more erratic than most all of 

the other expenditure profiles developed during the course of this project. For the pipeline

capital expenditures, a good portion of the allocation was concentrated in Sector 50 (New

Natural Gas Facilities). The next most significant category was in Sector 313 (Oil and Gas

Machinery).

The operational expenditures were concentrated heavily in Implan Sector 444 (Natural Gas

Utility Operations). The next closest expenditure percentage was concentrated in Sector 56 that

represents maintenance and repair of generally unclassified infrastructure investments. In

general, both Sector 444 and Sector 56 are generalized “catch-all” categories for utility activities. 

This seemed to be the appropriate delegation of costs since these assets are primarily utilityoriented in nature.

Total costs for pipeline construction and operation were developed from two different sources. 

Construction costs were taken from the annual survey of pipeline construction costs reported in

the Oil and Gas Journal. These construction costs are summaries of reported costs provided to

the FERC in the Certificate of Need and Convenience filings that are required to certify pipeline 

construction operations. Operational costs, however, were developed from the FERC Form 6. 

The same method of allocating offshore pipeline companies to water depth, and then calculating

costs, was facilitated.
18

3.6 Gas Processing and Storage Construction and Operation: The process of estimating gas 

processing costs followed lines that were similar to that utilized in examining gas pipelines. Gas 

processing costs for pipeline companies are reported in the FERC Form 6. This analysis

essentially separated these gas processing costs from other pipeline-related costs, to estimate

expenditure profiles for both capital (construction) and gas processing and storage operations. 

The unique difference in the analysis of gas processing costs, as opposed to gas transportation

costs, is that construction and operation of these facilities occurs completely onshore. 

Construction and operation are a function of processing capacity, and technology, not water

depth. Thus, total cost estimates and operating cost expenditure profiles are constant across

water depths. These estimates have been presented on Appendix Table A.7.

Total costs for gas processing were developed from two different sources. Total gas processing

construction costs were gathered from recently announced projects published in the Oil and Gas 

Journal. Total gas processing operation costs were calculated from information provided by gas 

transportation companies that provide gas processing services and report such costs in their

respective FERC Form 6 annual reports. Estimated production functions for gas processing

O&M have been presented on Appendix Table A.8. 

3.7 Workovers: Estimates of both workover costs expenditure profiles and total costs were

taken from the DOE-EIA publication of production and equipment costs and indices. These

publications included costs associated with workovers, and were developed on a similar “priceout” approach discussed in our section on production costs. These price-outs included estimates 

from three major types of workovers: recompletions; major workovers; and wireline. Our

estimates of workovers are based on an expected value approach. Expected values are

determined by the probability of a well having to undergo each of the three types of workovers

we discussed above. These probabilities are: 20 percent per well per year for recompletion; 10

percent per well per year for a major workover; and 40 percent per well per year for wireline

service. Our workover costs are the average of each of these expected workover types.

There is very little relative variation in expenditure profiles for workovers. About half of the

costs associated in this function are in oil and gas operations (Sector 38) and oil and gas field

services (Sector 57). Equipment costs (Sector 313) are about 5 percent of total costs. 

Transportation of work crews for this function is another important cost component. Production 

functions for workovers are presented on Appendix Table A.9.

Total costs for workovers were also developed using the expected value approach. Most of the

costs for workovers were relatively constant over water depth. Transportation costs were one of 

the more significant drivers of these total costs as water depth was increased. The source for

workover-related costs came from the price-out estimates produced in the annual DOE-EIA 

survey. These total costs are included in Appendix Table A.13.

3.8 Oil Spills: There is a paucity of information expenditure profiles for oil spills. This is

because oil spill costs are affected by so many factors that include size, location, weather, and

type of spill. Thus, developing a “typical” cost or expenditure profile, is a difficult task and

requires a number of assumptions. Nevertheless, we were able to generate some reflective
19

estimates of typical spill costs and expenditure profiles based upon past spill information that has 

been collected for the Gulf of Mexico.

Three main sources of information were consulted in the development of total oil spill costs and

cost expenditure profiles. These included: the Oil Spills Intelligence Report (1998); the Oil 

Spills Analysis: Destin Dome Development and Production Plans (1998); and the U.S. Coast

Guard (Etkin, 1998).

The strategies to develop a usable expenditure profile for oil spills were based upon a three step

process. First, major cost categories for expenditures in a typical oil spill were matched to

Implan sector codes. Second, recently reported cost information from near-shore and offshore

oil spills in the Gulf were examined. Third, the size, location, and cost structure for each of the

spills were examined to determine average costs and relative differences in cost distributions. 

Using information from the Oil Spills Intelligence Report, the expenditure breakout for our

estimated “typical” oil spill was developed and has been presented in Appendix Table A.10.

One of the more difficult parts of the analysis was estimating the costs of oil spills by water

depth. This is problematic since there are no well-established estimates of clean-up costs by

water depth. Therefore, estimates were developed based on (1) limited information from

published work cited above and (2) some judgment based upon the cited information about the

more common types of methods that would be used in different water depth/shore distance

combinations. 

3.9 Abandonment: Like workovers, there are a number of different types of processes that can 

be facilitated for abandoning a platform. We examined four major methods of removing

platform structures: bulk explosives (standard practice); bulk explosives topple in place; abrasive 

cutting; and mechanical cutting. We developed a weighted average for overall abandonment

costs based on the probability of the given technique being implemented in any given water

depth. In general, explosives tend to be the preferred method as water depth increases. We

assumed that the explosive method would be facilitated in the very deep (900 meters and deeper) 

water depth.

Our total costs and production functions were developed from previous work compiled by the

LSU Center for Energy Studies on platform abandonment. This work can be found in two

different sources. One published by National Research Council (National Research Council,

1996) and the other by the LSU Center for Energy Studies (Pulsipher, 1996). This work

examined a number of issues associated with platform abandonment methods including the costs 

associated with different abandonment techniques.

The estimated expenditure profiles for platform abandonment have been provided in Appendix

Table A.11. The changes in costs across water depth show how the increasing complexities of 

abandonment methods change. Overall costs associated with oil and gas operations (Sector 38)

increase across water depth and represent between 16 percent and 20 percent. A number of

disposal oriented activities are classified into the miscellaneous natural resources facility

construction category (Sector 53). These costs, in relative terms, are higher in shallow waters

than in the deeper water categories. One of the most significant cost categories, however, is
20

water transportation. Transportation is needed not only for moving crews in and out of the Gulf 

to remove structures, but also for removing the structure themselves.

Total costs were taken directly from sources provided in the CES-LSU report. These costs come 

from surveys of actual industry experience, and expectations for the types of costs that will be

increased in the future. We extrapolated some of the past experiences, for instance, to develop

very deep-water costs. This extrapolation was developed using a statistical estimation of the

relationship between costs and water depth for past industry abandonment experiences. Given

the lack of experience in deepwater abandonment, this was our only objective means for

estimation.

3.10 Onshore Allocations of Cost: Our on-shore allocation of costs to various regions in the

GOM was done in aggregate. Aggregate, in this context, entails that the allocation is by all

expenditures, across all offshore activities, and across all water depths. Developing allocations

that were disaggregated by either water depth or activity phase would have been a research

project of similar size and scope to our current investigation. Our research examined all publicly

available information in order to examine the onshore allocation of costs associated with

offshore activities. We were unable to secure any source of publically available information

regarding onshore allocations comparable to the format needed in this research.

Despite the lack of publicly available surveys, there was one private survey, conducted by the

Louisiana Mid-Continent Oil and Gas Association (LMOGA) that was made available to this

study. This survey examined all of the onshore businesses that were supporting offshore

activities. This survey was developed from vendor lists of several LMOGA member companies, 

that include most offshore major oil and gas companies. This vendor list included company name 

and physical location. A limited, redacted version of this survey information was provided to

our project by LMOGA. Companies in this survey were matched to Implan sectors to develop

sectoral allocations. These companies were matched to Implan codes by using a combination of

descriptive information in the survey database, or through matching companies to the Gulf Coast 

Oil and Gas Directory and identifying their activities as listed in the directory. The onshore

allocations have been presented on Appendix Table A.12. Each onshore area is defined as a

MMS region. We have also identified allocations made within the Gulf States, but not onshore 

(Gulf-Other), as well as the US and rest of the world (US-Other). This table identifies the

concentration of activities in each region by Implan Sector.
21

Section 4: An Application: Modeling the Impacts of Offshore Activities on Coastal 

Louisiana

4.1 Introduction: The primary purpose of our work has been to develop estimates for the cost

characteristics of offshore oil and gas operations. Our secondary objective has been to develop

estimates of the economic impacts of offshore activities on coastal Louisiana. This analysis will 

serve as a case study, and test for reasonableness, for our estimates of offshore expenditure

profiles, activity costs, and onshore allocations.

The impacts that have been simulated in this study are based on the MMS proposed lease

program for oil and gas well developments in the Gulf of Mexico regions for the period 1997-

2031. Our analysis was limited to an investigation of the economic impacts associated with

exploration, development, and production activities. Exploration wells are wells drilled in search 

of new oil and/or gas resources usually to find and produce oil or gas in an unproved area; find a 

new reservoir in a previously productive field in another reservoir; or expand the limit of an

existing reservoir. Development wells are drilled within the proved area of an oil or gas reservoir 

to the depth of a productive stratigraphic horizon, and they are used for potential production or to 

increase the production of a hydrocarbon accumulation discovered and delineated by previous

drilling. Production wells are successful and completed wells that currently produce oil and/or

gas. Important indicators of levels of economic and social aspect development in the designated 

coastal communities are presented below. 

Table 4.1 Demographic, Social, and Economic Indicators of Louisiana Coastal Areas (1996)

Region

Area

(sq miles) Population Employment

Number of 

Households

Total Personal 

Income ($000)

Income per 

Household ($)

LA1 4,403 492,449 284,040 177,916 9,833,829 55,272

LA2 6,078 1,019,205 565,810 368,226 20,269,121 55,045

LA3 2,821 1,202,640 705,545 434,499 26,933,920 61,988

All LA 43,567 4,350,579 2,304,531 1,571,810 85,552,280 54,429

Table 4.1 provides overview statistics for each of the major Louisiana coastal regions. In terms

of geographic area, LA2 is the largest area followed by LA1 and LA3, respectively. While the

combined areas encompass only about 30 percent of the landmass of the entire state, these areas

account for close to 62 percent of the state’s total population, 67 percent of its total employment, 

and 62 percent of its total households. The average income per household in these communities

is between $616 and $7,600 above the statewide average. More detailed socioeconomic

information on these areas and the entire state is provided in Appendix B. The above average

household income levels are in part due to the higher concentration of higher paying oil and gas 

industry jobs in these communities. Appendix Tables B.1 and B.2 show that mining

employment forms a relatively high percentage of total employment in these economies. 
22

4.2 Review of Impact Analysis Methodologies: Impact analysis in a region focuses on the

interaction between economic policy changes and the implications that these changes have on the 

local economy. This type of analysis can estimate the effect that a change in economic policy, or 

shift in major industry decision, can have on a variety of agents within the local economy, such

as specific socioeconomic groups, specific sectors, or specific locations. Changes in the level

and distribution of local employment, income, sales, and wealth are often the target of analysis in 

the context of regional planning (Shaffer, 1989). The academic literature is filled with numerous 

models that have been developed for impact analysis at the regional level. The most common

among these models includes econometric, export-base, benefit-cost analysis, and inter-industry 

models.

Export-base models (EBM) are based on the premise that regional income is determined by

exports (i.e. sales of goods and services both foreign and domestic) outside the region. The

economy is conceptualized as comprising two sectors, export industries and local service

industries. The export sector is comprised of local firms that bring funds into the community by

meeting external demand for their goods and services. The other sector (the non-export, nonbasic, or residentiary sector) sells its products within the boundaries of the region and exists to

support the export sector (Shaffer, 1989). EBM’s strong limitation lies in its emphasis on export

only as the sources of regional development and the fact that it is a very restrictive theory more

appropriate for smaller, less complex economies. 

Benefit-Cost models (BCM) represent an alternative approach in estimating the economic

impacts of public policy proposals. BCM models are premised on the concept of potential Pareto 

improvement. This concept applies to the premise that resources in a society may be re-allocated 

such that the resulting gains make everyone better off. Based on Kaldor-Hicks compensation

principle, gainers are able to compensate losers at least to the full extent of their losses. BCM

derives the net economic benefits or ratio of benefits to costs of proposal, policy, program, or

project alternatives. BCM has the disadvantage of reliance on a single criterion to determine

choice that limits its usefulness as an economy-wide analytic tool. 

Regional econometric models are similar to economic base models in that such models are

usually based on a Keynesian (demand-driven) picture of an economy. However, regional

econometrics models employ a different approach to implement and measure structural

relationships in a regional economy. Regression analysis is applied to time series data to

estimate the assumed relationship. Regional econometrics models are used to forecast future

levels of activity in the regional economy as a whole with model dependent variables as output,

employment and endogenous prices. The limitation of econometric models is typically

associated with their data-intensive nature, and a number of potential statistical problems

associated with endogeneity and parameter instability problems.

Although many of these regional analysis tools have been constructed to examine only the

effects of changes in demand, others are more encompassing in formulation and use. However,

most of these models are limited to examining the effect of change on a particular sector only. As 

a result, these models can be thought of as “partial-equilibrium” models that hold changes in

other sectors of the economy constant when examining a direct economic shock in a particular

sector. 
23

Models that can be used to examine direct, indirect and feedback effects of exogenous policy

shocks are more useful for forecasting change and making policy decisions than are models that

can only show direct impacts. This is because, in reality, the workings of a local economy shows 

inter-sectoral linkages, implying that the effects of a particular policy will not only be felt by the 

sectors directly impacted but also by other sectors directly or indirectly linked to that sector

(Shaffer, 1989). Examples of such encompassing models constitute the class of inter-industry 

models. It is this type of model that is employed here. Hence, the choice in this model is to use

inter-industry analysis models because of their general equilibrium holistic treatment of the

economy.

4.3 Inter-Industry Economy Wide Models: Most of the sectoral, partial equilibrium models

previously discussed have a number of limitations for long-run regional economic impact

analysis. Model use may also be limited due to a lack of detail when accounting for linkages in

the local economy. For example, in most open economies, investment dollars from outside the

region may be far more important than basic industries. Also, in open economies, inter-industry 

transactions, household incomes, and spending patterns, as well as government transfer payments 

and expenditures are becoming increasingly more important than single-industry transactions. 

Specifically, the level of aggregation in sectoral models may limit their usefulness in policy 

decision-making. Perhaps the most conceptual limitation is the implicit capacity constraints

imposed by most sectoral models as an underlying feature of the local economy. While capacity

constraint may be relevant in some cases, in broader perspective, a local economy is often more

open than closed. 

Input-output or I-O analysis, however, is an empirical analytical framework formalized by

Wassily Leontief in the late 1930s that collects, categorizes, and analyzes data on the interindustry structure and examines interdependencies of the economic activity of a country, region,

or state (Miller and Blair, 1985; Shaffer, 1989). The models focus on interrelationships of the

producing and consuming units in an economy. In addition, it depicts the interrelations among

different sectors that purchase goods and services from different sectors within a regional

economy.

Recent extensions of I-O models have included the Social Accounting Matrix (SAM) model and 

the Competitive General Equilibrium (CGE) model. Our economic impact analysis of coastal

Louisiana will employ a SAM model. The SAM model, originally developed in 1961 by Stone,

was developed to reflect a snapshot of a regional economy that included the traditional circular

flow of commodities and money during a given time period (the base year) in a balanced fashion. 

It is essentially an accounting record for a whole economy, and not just transactions among

producers like a traditional I-O model (Bulmer-Thomas, 1982). Thus, a SAM extends beyond

producer-producer, producer-consumer and producer-factor relationships to include a broader

realm of institutions in a regional economy. These institutions are defined as entities having the

legal right of ownership and as a consequence, are able to accumulate and provide services (Pyatt 

and Roe 1977). 

Similar to I-O, institutions in a SAM usually include households, enterprises (firms), and

government. However, unlike an I-O, SAM generally accounts for all market flows and for non-
24

market income and transfers, and SAM explicitly accounts for all monetary flows in the

economy. Therefore, SAM provides a consistent picture of the flow-of-funds accounts of the

separate institutions or “actors” in the economy that one may wish to distinguish. The SAM is

a square matrix with each row and column reflecting separate accounts for a given entity. 

Expenditures represented by matrix columns, and receipts represented matrix rows, must

balance. The SAM models are therefore part of the general equilibrium framework of economic 

analysis. Within this general approach, fixed-price models are seen to be systems in which

supply prices are independent of the scale of production. With regard to prices, the circular flow 

of income within the macroeconomy can be interpreted in terms of fixed-price multiplier effects 

(Pyatt, 1988). 

Since the SAM model includes a more comprehensive view of the circular flow of income than

does the standard I-O model, it requires the extension of the fixed coefficients assumption to the 

coefficients of all endogenous accounts.3 The fixed coefficient assumption, which in I-O models 

is a fixed technology assumption, now must include the assumption that various expenditure

coefficients are fixed once those sectoral variables are treated as endogenous (Holland and

Wyeth, 1993). For example, if households’ variables are treated as endogenous, then the various 

household expenditure coefficients are fixed. Within an I-O there is an explicit specification of

the linkages between household income and household spending, whereas the linkage between

government revenue and expenditure of these sectors may be endogenous in a SAM. 

A SAM is particularly suitable for assessing impacts of programs and policies such as exogenous 

changes resulting from oil industry’s activities in a region because of the SAM’s relative

flexibility. For example, the distributional effects of a change in final demand across income

groups can be assessed. Analysis of an income redistribution policy may include the

disaggregation of income groups into high, medium and low-income classes, and the government 

sector may be broken down to the three layers of governments. 

4.4 Data Methods: The construction of regional impact models, regardless of methods, requires 

that a choice be made as to how data on some or all of the component elements of the models are 

to be secured and utilized. The three methods of underlying data for regional models are the

survey, ready-made, and hybrid approaches (Jensen, 1980; Brucker et. al., 1987). 

Construction of a model based on survey data involves obtaining information on the sectoral

distribution of regional purchases and sales to final demand of every modeled sector of the

economy and on the imports purchased and exports sold by each sector. Survey approaches rely

heavily on data availability in the individual establishments, industrial censuses, regulatory

commissions, tax authorities, trade associations, and expert opinions. National coefficients are

rarely used and only used when regional data resources are unavailable (Bourque, 1990). The

amount of data needed to construct a survey-based table and the associated time, cost, and

technical skill requirements are thus, considerable.

 

3Endogenous accounts refer to those accounts that hold variables that are determined within the model and in the I-O 

tables and to those accounts that are made part of the inter-industry matrix. Those accounts that are not part of the 

A-matrix are exogenous. 
25

Regional impact models based upon survey methods are sparse given the significant costs

associated with their creation. In contrast to the survey-based models, there are non-survey-based 

models, or the so-called “ready-made” approaches. Strictly non-survey techniques attempt to

depict regional transactions without recourse to detailed primary data, using procedures that have 

been described as essentially mechanical. In non-survey models, national coefficients, a region’s

share of national production of goods and services, are modified based on aggregate regional

data to produce estimates of regional coefficients using a variety of approaches including RAS,

location quotients, supply-demand pool, or some other statistical methods (West, 1990).

These types of non-survey based models are very common, particularly in the U.S. Some of the

popular ones include ADOTMATR, RIMS, RSRI, GRIT (for Australia), and Professional

(IMPLAN). The IMPLAN modeling system, originally developed by the U.S. Forest Service, is

by far the most popular of the ready-made approaches. These models are very tractable in cost

and time to utilize, especially with rapid advances in computer technology. Evaluation of the

impact studies’ results using these models seems to suggest no significant differences in

aggregate estimates obtained for output and income, but large differences were observed with

respect to employment (Brucker, et al., 1987).

Between the extremes of survey and non-survey models lie those models that combine survey

and non-survey data to depict regional economic structures. These are called the regional hybrid

models, and they combine information from a field survey with a ready-made format such as the 

IMPLAN. Econometrics, linear programming, published data, or budget approaches may be

used to generate the required coefficient from data collected from surveys. These coefficients

are incorporated into the standard models in existence to simulate policy impacts in the region(s) 

concerned. In current practice, especially in the U.S, ready-made models are the preferred

approach by regional analysts, because they seem to combine the advantage of cost-effectiveness 

with timeliness desired by decision makers (West and Jensen, 1993). 

This study relies on IMPLAN for our basic model construction. However, our study can be

described as a hybrid approach to economic impact modeling since we have incorporated

industry-specific information on offshore oil and gas activities, by water depth, into the

IMPLAN framework. Such an approach allows us to specifically model those sectors of the

coastal Louisiana economy for which we are most interested. For other sectors, we will facilitate 

the more generalized default information provided within the IMPLAN model.

4.5 Regional Multipliers and Impact Analysis: The concept of multipliers is central in the

understanding of regional economic models, because it defines and forms the basis of impact

analysis. Multipliers are based on the fundamental notion that one person’s expenditure is

another’s income, and since consumption usually increases when income increases, any extra

expenditure feeds through into further expenditure. These effects become smaller and smaller

through each spending round due to leakages. 

The idea of multipliers hinges upon the difference between the initial effect of an exogenous

(final demand) change and the total effects of the change. The total effects can either be captured 

in terms of direct, indirect, and induced effects. Direct effects are the changes in the industries to 
26

which a final demand change was affected; indirect effects measure the changes in inter-industry 

purchases resulting from the new demands of the directly affected industries. Induced effects are 

those changes in spending from households as income or population increases or decreases due

to changes in production (Miller and Blair, 1985). 

Multipliers can be constructed in terms of output, income, employment, or value-added with

different policy implications. There are four different multipliers commonly used in predictive

modeling: Type I, Type II, Type III, and Type IV. Type I multipliers measure the direct and

indirect effects of a change in economic activity. Type II captures both direct and indirect effects 

while taking into account the income and expenditures of households in addition to the interindustry effects. Type III uses the Type I results to generate further economic activity by

focusing the effect of the change on employment. Type IV (Madden and Batey, 1983) is based

on patterns of spending between local residents and currently unemployed local residents.

4.6 The Coastal Louisiana Economic Impact Model: A typical non-survey or ready-made 

regional model such as IMPLAN is, in effect, a stepped-down national model. As explained

previously, in such models available regional data can be used to improve model accuracy and

validity. The basic foundation of the SAM models of the Louisiana economy is the IMPLAN

database. In keeping with general practice, modifications have been made to this IMPLAN data

to ensure a more realistic picture of the region’s economy. These include modifications of

regional purchase coefficients (RPC), regional supply-demand pool (SDP), transportation and

marketing margins, and production functions based on primary or secondary data. Also, the

production sectors in the basic IMPLAN-based models were aggregated into major industry

groups. Aggregation may be justified on the grounds of resource limitation such as

computational time. This consideration is important when the loss of additional information due 

to aggregation is not critical to the problem under consideration. 

4.7 Regional Purchasing Coefficient: A regional purchase coefficient (RPC) represents the

proportion of a region’s total supply of a given commodity used to meet regional intermediate

(industry) and final demand for that commodity. For example, an RPC of 0.25 for the natural

gas sector means that local producers meet 25 percent of all demand for natural gas. Hence, 75

percent of regional natural gas demand is satisfied by regional imports. 

RPCs are important in regional models since they represent the direction and magnitude of

regional trade flows. Another potential measure for regional trade flows can be calculated

through the use of SDPs, or supply-demand percentages. An SDP is the maximum amount of a

regional supply that is available to meet regional demand. It is the ratio of regionally produced

net commodity supply to gross regional demand. An SDP of less than one implies that the

commodity will have to be imported even if none of the regional supply is exported domestically

(Hughes and Litz, 1996). 

RPCs, however, are more productive than SDP because they allow for cross-hauling (the

simultaneous important export of the same commodity), which may result from such factors as

brand differentiation. Ignoring cross-hauling in an I-O/SAM model may result in a bias of

regional impacts resulting from an exogenous change in final demand. The use of RPC

represents one way to reduce the possible bias in using ready-made national models in a regional 
27

context. In addition to issues associated with cross-hauling, the use of RPCs has the added

advantage of improving the accuracy of multiplier impacts. The 59 selected commodities with

modified RPCs that have been used in our model have been presented in Appendix Table B.3. 

The modifications to these RPCs have been based upon expert opinions and available regional

data used in other studies of the Louisiana economy (Olatubi, 1998). Attempting to reconcile

biases in RPCs is an important issue in economic impact modeling. 

Like production expenditure profiles, an RPC can be biased given that its primary base is from 

stepped-down national information. This bias can be important because RPCs, to a very large

extent, condition the leakages in a regional model. The greater the RPC, the less the leakage

from the local economy, and the greater the indirect and induced effects associated with an

exogenous shock. An example of why it is important to consider adjustments to the RPCs can be 

discerned from an analysis of the default RPC for Petroleum Refining (Sector 210). The original 

default RPC for this sector is 0.8543, indicating that about 15 percent of petroleum refining

demand in Louisiana is met by imports. Given the large amount of petroleum refining that is

currently within the state, a 15 percent import level seems high. In addition, since this is a sector 

related to the overall Louisiana energy economy, it would be prudent to make the appropriate

adjustments where possible.

4.8 Sectoral Aggregation: Sectoral Aggregation is the process by which two or more industrial 

sectors in IMPLAN, or any I-O model, are re-grouped into fewer industrial sectors for the

purpose of impact analysis. The choice of sectors to aggregate depends on the particular study

and sectoral compatibility (a function of underlying production technology), size of the

industries in question, other factors such as computational expense and feasibility, and

availability of data. However, since aggregation bias may result in biased multiplier estimates,

care must be taken in aggregating industrial sectors. There are 27 aggregated sectors used in this 

study from the original 528 sectors in IMPLAN for each of the three Louisiana area models. 

These 27 sectors were considered to meet the goals of this study in terms of its focus on oil and

gas related industries and in terms of presenting a valid broad representation of the Louisiana

regional economies. Our emphasis of the oil and gas industry has resulted in more detailed,

disaggregated sectors. The 27 aggregated sectors and the sectors that were combined to form

those aggregates are indicated in Table 4.2. The SDP and RPC values resulting from the 27-

sector aggregation are shown in Table 4.3.
28

Table 4.2: Louisiana Model Aggregation Industry and IMPLAN Included Sectors

Industry 

Code Industry Description IMPLAN Sectors Included

1 Farming 1--27

38 Natural Gas &Crude Petroleum 38

39 Natural Gas Liquids 39

28 Other Mining 28--37,40--47

50 New Utility Structures 50

53 New Mineral Extraction Facility 53

48 Other Construction 48,49, 51, 52,54--56

57 Maintenance &Repair: Oil & Gas wells 57

82 Food Processing 58--103

104 Natural Resource Processing 104--173

174 Printing & Publishing 174--185

186 Chemical & Allied Products 186--209

210 Petroleum Refining 210

211 Other Refining & Coal Products 211--214

215 Rubber and Misc. Plastics 215--220

313 Oil and Field Machinery 313

393 Transportation Equipment 384--399

221 Other Manufacturing 221--312, 314--383,400--432,528

436 Water Transportation 436

444 Gas Production & Distribution 444

433 Other Transportation & Public Utilities 433--435, 437--443,445,446

447 Wholesale Trade 447

451 Automotive Dealers & Service Stations 451

448 Other Retail Trade 448--450,452--455

456 FIRE 456--462

473 Services 463--509, 525

510 Government 510--524, 526,527
29

Table 4.3: Aggregated RPCs and SDPs

LA1 LA2 LA3

Sector Description SDP RPC SDP RPC SDP RPC

1 Farming 0.5440 0.1592 0.4424 0.1892 0.2631 0.0188

28 Other Mining 0.5318 0.5000 0.1264 0.0002 1.0000 0.0009

38 Natural Gas & Crude Petroleum 0.5924 0.3669 0.1952 0.1952 1.0000 0.3524

39 Natural Gas Liquids 0.5803 0.3559 0.1938 0.1938 1.0000 0.5000

48 Other Construction 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

50 New Utility Structures 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

53 New Mineral Extraction Facilities 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

57 Maintenance and Repair Oil and Gas Wells 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

82 Food Processing 0.7964 0.0479 0.7954 0.1236 0.7067 0.3415

104 Natural Resource Processing 0.2124 0.2124 0.2804 0.0326 0.2181 0.2181

174 Printing & Publishing 0.2899 0.1173 0.3515 0.1323 0.4887 0.1452

186 Chemical & Allied Products 1.0000 0.8465 1.0000 0.8227 0.5650 0.5650

210 Petroleum Refining 1.0000 0.8543 1.0000 0.8543 1.0000 0.8543

211 Other Refining & Coal Products 1.0000 0.9210 1.0000 0.8842 1.0000 0.9702

215 Rubber & Misc. Plastics 0.2858 0.0011 0.2606 0.0008 0.2466 0.0012

221 Other Manufacturing 0.3559 0.0036 0.4188 0.0029 0.2955 0.0045

313 Oil Field Machinery 0.6321 0.6216 0.6423 0.4447 0.6262 0.2780

393 Transportation Equipment Manufacturing 0.3670 0.0164 0.4516 0.0108 0.5964 0.0004

433 Other Transportation & Public Utilities 0.7698 0.6737 0.7283 0.7283 1.0000 0.6895

436 Water Transportation 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

444 Gas Production and Distribution 0.8091 0.8091 0.3965 0.3965 0.6931 0.6931

447 Wholesale Trade 0.8818 0.6114 0.8185 0.6114 1.0000 0.6114

448 Other Retail Trade 1.0000 0.9067 0.9318 0.9083 1.0000 0.9043

451 Automotive Dealers & Service Stations 1.0000 0.9487 0.9530 0.9487 1.0000 0.9487

456 FIRE 0.5418 0.5418 0.6386 0.6204 0.7622 0.6344

473 Services 0.9363 0.8074 0.7909 0.7909 1.0000 0.8159

510 Government 0.8363 0.8363 0.7811 0.7811 0.8652 0.8652
30

4.9 Empirical Results for the Base Model Scenario: In Table 4.10, column 1, we present the 

general results of IMPLAN’s run for the empirical structure of the coastal communities’

economies based on IMPLAN data for 1996.4 The results indicate that the total size of the LA1's 

economy is about $92.6 billion. Of these, industry output accounts for 29.6 percent or $27.4

billion, factor incomes represent 15 percent, or $13.5 billion, and household income is 12

percent, or $11.3 billion. The size of the federal government is estimated at 3 percent or $2.9

billion, and state and local governments are 3 percent or $2.8 billion. Businesses and enterprises 

also account for 2 percent or $1.7 billion, while capital investment and trade account for 5

percent or $4.9 billion and 13 percent and $11.7 billion, respectively.

For LA2, the results indicate the total size of the economy is approximately $180.6 billion. This

total is comprised of industry output of 29 percent or $52.2 billion, factor incomes of 14 percent, 

or $25.6 billion, and household income of 13 percent or $23.3 billion. In addition, the federal

government accounts for 3 percent or $6.2 billion, and state and local governments account for 4 

percent, or $6.4 billion of economic activity. Businesses and enterprises contribute 2 percent or

$2.9 billion, capital investment accounts for 6 percent, or $10.1 billion, and trade accounts for 

11 percent, or $20.6 billion of regional economic activity.

Similarly for LA3, the results estimate a 1996 economy of $213.6 billion. The economy is

composed of industry output of $54.2 billion (25 percent), factor incomes, $32.2 billion (15

percent), and household income of $29.6 billion (14 percent). The size of federal government

economic activity is estimated to be $13.3 billion (6 percent), and the state and local

governments are $8.2 billion (4 percent). Businesses and enterprises also account for $3.5 billion 

(2 percent), while capital investment and or $13.3 billion (11 percent) and trade amounts to $23.4 

billion (6 percent).

Having established the base year structure of the respective LA economies, a vector of the

potential exogenous changes or shocks must be determined. However, available data for

subsequent simulation purposes as provided by the MMS are usually aggregated for larger

planning areas indicated in Figure 2.1. Hence, onshore allocation of these offshore activities is

necessary. The allocation of activities or expenditures to onshore areas is probably one of the

more important factors for determining the region-specific economic impacts associated with

offshore activities. These breakouts are important, because there are tendencies for certain

onshore support activities to be concentrated in particular geographic areas. This concentration

has tended to occur in Louisiana and Texas and has continued despite the movement of offshore

activities into deeper water and into the Central-Eastern portions of the Gulf of Mexico. The

allocated ratios used for the relevant sectors and regions are as given in Appendix Table B.5. 

In addition to determining onshore allocations, we needed to identify specific expenditure

allocations for the direct shocks we were going to examine in our economic impact analysis. 

The expenditure profiles for exploratory and development drilling, as well as production, that

were developed in the first phase of our investigation, are facilitated. Direct costs that were

developed for these activities were also used to estimate a direct shock associated with new

offshore oil and gas activities.

 

4

 Minnesota IMPLAN group, the owners of IMPLAN, update their database annually. 1996 data was the most recent 

at the beginning of this study.
31

4.10 Empirical Results for New Offshore Oil and Gas Activities: In Table 4.4 we present the 

results of the impact simulation for LA1. Detailed impacts by water depth, sectors, and activity

phase have been presented in Appendix Table B.7. Subtables have been created to examine each 

subregional impact by water depth. In general, the results show that whether we consider direct, 

indirect, induced, or even total impact for output, labor income, value-added and taxes, the effect 

of the proposed exploratory wells development on LA1 economy is greater than development

wells, which, in turn, is smaller than production wells. In terms of employment, both exploratory 

and development wells have similar impacts in LA1, with only three additional jobs per well. 

The employment effects of production wells are far less with about 0.328 jobs created per well,

annually. Hence, as the industry adage notes, “it’s the drill-bit that creates the jobs.” It is noted 

that out of the components of value-added (TVA), labor income represents less than half of TVA 

for exploratory and development well activities, whereas it is greater than half of TVA for

production wells. 

A similar analysis for the LA2 economy is presented in Table 4.5. In total, probably due to the

greater leakage in LA2 or greater linkage in LA1’s economy compared to LA2, the levels of

impact are generally lower in LA2. This is in spite of the fact that LA2 economy is quite larger

than LA1’s. Following similar trends as in LA1, the results show that direct, indirect, induced,

or even total impact for output, labor income, value-added and taxes, the effect of the proposed

exploratory wells development on LA2 economy is greater than development wells, which is

also greater than production wells. In terms of employment both exploratory and development

wells have similar impact to LA1 but slightly smaller per well impact of only 2 jobs per well

drilled, and for production wells of 0.320 jobs per well.

The results in Table 4.6 show the impact effects in LA3 economy. In terms of trends among

exploratory, development, and production wells, the distribution of impacts are similar to LA1

and LA2. However, the levels of impacts are quite close to LA1 even though LA1 economy is

smaller in size to LA3. This result might be due to the extent of sectoral linkages in the

economy, as well as potential leakage levels out of the economy. Employment levels are the

same for LA1 and LA3 for exploratory and development wells activity but slightly lower for

LA3 production wells’ effects–0.314 jobs per well, annually. It is also noted that total tax impact 

in LA3 is higher than LA2 or LA1, probably due in part to the fact that LA3 workers earn a

higher average wage than the other regions.

One of the key advantages of extending an I-O framework is to examine potential distributional

effects of a proposed activity or project. Income distribution effect is particularly important for

rural communities, or frontier areas where oil and gas development is envisaged because of the

potential negative effects of disrupting current income patterns, and hence the existing social

milieu. In Tables 4.7-4.9, we present the income distribution pattern resulting from oil and gas

wells development in these three regions.
32

Table 4.4: Economic Impact Results of Oil and Gas Development in the Gulf of Mexico 

1997-2031: LA1 Annual per Well Impacts

Exploratory Development Production

Impact Item Direct Indirect Induced Total Direct Indirect Induced Total Direct Indirect Induced Total

Output ($) 714,423 101,698 53,234 869,355 623,045 94,511 50,095 767,651 28,701 9,713 4,703 43,118

Labor 

Income ($) 57,627 30,283 19,944 107,854 53,743 29,010 18,768 101,522 4,169 3,573 1,762 9,504

Total Value 

Added ($) 170,751 54,004 32,364 257,119 147,895 50,586 30,455 228,936 8,610 5,313 2,859 16,783

Employment 

(Jobs) 1 1 1 3 1 1 1 3 0.128 0.124 0.076 0.328

Taxes ($) N/A N/A N/A 60,773 N/A N/A N/A 54,461 N/A N/A N/A. 4,303
33

Table 4.5: Economic Impact Results of Oil and Gas Development in the Gulf of Mexico 

1997-2031: LA2 Annual per Well Impacts

Exploratory Development Production

Impact Item Direct Indirect Induced Total Direct Indirect Induced Total Direct Indirect Induced Total

Output ($) 716,297 73,474 37,625 827,395 623,569 67,773 34,568 725,911 28,615 9,238 4,618 42,472

Labor Income 

($) 37,825 23,706 14,094 75,625 51,422 33,382 19,424 104,227 4,098 3,443 1,730 9,271

Total Value 

Added ($) 103,906 39,436 23,021 166,364 89,014 36,528 21,151 146,693 8,500 5,140 2,825 16,466

Employment 1 1 1 2 1 1 1 2 0.128 0.119 0.073 0.320

Taxes ($) N/A N/A N/A 42,826 N/A N/A N/A 37,946 N/A N/A N/A 4,470

Table 4.6: Economic Impact Results of Oil and Gas Development in the Gulf of Mexico 

1997-2031: LA3 Annual per Well Impacts

Exploratory Development Production

Impact 

Item Direct Indirect Induced Total Direct Indirect Induced Total Direct Indirect Induced Total

Output ($) 715,396 93,816 55,308 864,520 623,501 84,324 49,160 756,985 28,682 9,296 5,059 43,038

Labor 

Income ($) 57,314 29,136 21,237 107,687 50,057 26,774 18,876 95,707 4,357 3,529 1,942 9,829

Total Value 

Added ($) 168,392 52,081 34,619 255,093 140,720 47,041 30,771 218,532 9,035 5,316 3,166 17,518

Employment 1 1 1 3 1 1 1 3 0.121 0.114 0.079 0.314

Taxes ($) N/A N/A N/A 66,731 N/A N/A N/A 57,430 N/A N/A N/A 4,876
34

Table 4.7: Income Distribution Impacts: LA1 Area

Annual Impact Per Well ($)

Household Income

Category Exploratory Development Production

< $5,000 199 188 17

$5,000---$10,000 1,024 964 90

$10,000---$15,000 2,767 2,605 243

$15,000---$20,000 4,024 3,788 354

$20,000---$30,000 13,416 12,628 1,182

$30,000---$40,000 16,986 15,988 1,496

$40,000---$50,000 17,006 16,007 1,498

$50,000---$70,000 26,126 24,592 2,302

> $70,000 26,306 24,762 2,318

Table 4.8: Income Distribution: LA2 Area

Annual Impact Per Well ($)

Household Income

Category Exploratory Development Production

< $5,000 172 237 21

$5,000---$10,000 612 844 75

$10,000---$15,000 1,702 2,346 208

$15,000---$20,000 2,682 3,696 328

$20,000---$30,000 8,961 12,350 1,098

$30,000---$40,000 11,867 16,355 1,454

$40,000---$50,000 11,766 16,216 1,442

$50,000---$70,000 19,892 27,415 2,438

> $70,000 17,971 24,768 2,203
35

Table 4.9: Income Distribution: LA3 Area

Household Annual Impact Per Well ($)

Income

Category Exploratory Development Production

< $5,000 248 220 22

$5,000---$10,000 832 739 75

$10,000---$15,000 2,371 2,107 216

$15,000---$20,000 3,675 3,266 335

$20,000---$30,000 12,730 11,314 1,162

$30,000---$40,000 15,616 13,878 1,425

$40,000---$50,000 15,170 13,482 1,384

$50,000---$70,000 26,489 23,542 2,417

> $70,000 30,556 27,157 2,789

Generally, to provide more detail we use a 9-income category version of the U.S. Bureau of 

Economic Analysis (BEA) Consumption Expenditure Survey (CES) income group. In terms of

the previously used three income groups of low (< $20,000), medium ($20,000-$50,000), and

high income (>$50,000), the medium and higher income household benefits the most from oil

and gas development in the three regional economies. 

Our results indicate that the distribution of the economic benefits of offshore activities is

relatively balanced between high income and low income households. Within the three groups

we have examined, about 50 percent goes to those households with incomes that are greater than 

$50,000 per year. The other 50 percent is strongly distributed towards medium income

households, with between 6 to 8 percent going to the poorest households. 

The relative potential contribution of each oil and gas well type to their respective regional

coastal economies is depicted in Table 4.10. In each case, we examined the proportional

contribution of the impact of a well relative to the total size of the economy with regard to

output, value-added, and employment. 

 
36

Table 4.10: Impact Result versus Base Model Result

(Annual Per Well Basis)

LA1

Item Total Base

Annual

Total Per Well 

Impact

Per Well Impact 

as a Percent of 

Regional 

Economy

Output ($000) 27,393,500 44 0.00163379

Value Added ($000) 13,482,700 17 0.00128084

Employment Number 284,040 3.34 0.00117589

LA2

Item Total Base

Annual

Total Per Well 

Impact

Per Well Impact 

as a Percent of 

Regional 

Economy

Output ($000) 52,183,200 44 0.00084368

Value Added ($000) 25,565,600 16 0.00065633

Employment Number 565,810 3.24 0.00057263

LA3

Item Total Base

Annual

Total Per Well 

Impact

Per Well Impact 

as a Percent of 

Regional 

Economy

Output ($000) 54,181,200 44 0.00082427

Value Added ($000) 32,172,600 17 0.00055924

Employment Number 705,545 3.20 0.00045355

All Areas

Item Total Base

Annual

Total Per Well 

Impact

Per Well Impact 

as a Percent of 

Regional 

Economy

Output ($000) 133,757,900 133 0.00099763

Value Added ($000) 71,220,900 52 0.00073069

Employment Number 1,555,395 9.78 0.00062878
37

The results show that oil and gas development has more impact in the LA1 economy than the

other two economies, which share similar relative impacts. Exploratory, development, and

producing wells contribute about twice as much (on a per well basis) more than the contribution

to the economies in LA2 and LA3. In addition, exploratory and development drilling create the 

biggest impact in all three regional economies.

4.11 Summary and Conclusion of Impact Analysis: The purpose of this section of our report 

has been to examine the economic impacts of offshore activities by incorporating two new

methodological approaches. The first is the use of a Social Accounting Matrix, or SAM, to look 

at the full range of economic impacts across all regional economic agents and institutions. The

second was to incorporate our considerable work in developing offshore industry cost drivers for 

economic impact modeling purpose. These cost drivers included offshore industry activity

expenditure profiles, total unit costs, and onshore cost allocation factors.

Although there are varieties of economic activities undertaken by oil and gas industries in the

Gulf of Mexico OCS region, our simulation was based on the basic industry activities of

exploration, development, and production wells spanning the period 1997-2031 as forecast by

the MMS. Our results show that in terms of aggregate output, labor income, value added,

employment, and tax base in all three economies, production activities add the most value to

these onshore regional economies. Exploration and development, or overall drilling activities,

tend to have a less substantial impact. Exploration and development activities add about 3 jobs

per drilled well annually. Production activities, however, increase total local employment by 200 

jobs for every production well in operation. 

Although these regional economies are of varying sizes, our analysis reveals that the impacts of

offshore activities are not directly correlated with size. For example, while LA1 economy is

clearly smaller than LA2, the relative impact of offshore activities in LA1 is considerably higher 

than in LA2. Likewise, our analysis shows that the relative impact on the LA2 and LA3

economies are very similar despite the fact that the LA3 economy is much larger. Thus, it is

important to recognize the importance of the structure of the economy in terms of inter-industry 

linkages and potential levels of leakages out of the economy when examining the economic

impacts of large construction and infrastructure projects or any type of major public policy

initiative.

Income distribution effects are an additionally important consideration in the policy analysis of

how industries impact local communities. Our analysis shows that while all income groups

benefit from an increase in offshore activities, the benefits are skewed more toward the upper

income households. In all three coastal Louisiana economies, we found that as much as 50

percent of the income gains that are created by increased offshore activities accrues to

households with annual incomes greater than $50,000, while another 50 percent goes to those

under $50,000. Such a result would tend to support the fact that the distribution of benefits

associated with offshore activities is relatively balanced.
39

Section 5: Conclusions and Suggestions for Future Research

The research encompassed in this report has expanded the opportunities for a more detailed and

industry-specific approach to modeling the economic impacts of offshore activities. However, it 

would be a display of hubris to suggest that we have come even close to developing a

comprehensive approach of understanding the complete economic impact of these oil and gas

industry activities. At best, this work can claim to have at least successfully developed a

framework upon which future research can move forward.

There are at least five generalized areas where these approaches could be expanded and 

improved:

(1) Customizing onshore allocations

(2) Developing cost functions for specific technologies

(3) Developing labor and value added implications

(4) Understanding the implications of activities on public finance

(5) Developing a model that incorporates interregional linkages

5.1 Onshore Allocations: The onshore allocations used in our report were generalized across 

all offshore activities and water depths. This aggregation however, can generalize economic

impacts. Further disaggregation could result in a more refined understanding of how those

impacts accrue across specific (county/parish) coastal regions. There are a number of ways these 

onshore allocations could be improved, however, the two most readily available opportunities for 

disaggregation includes: (a) developing specific onshore allocations for each activity type and (b) 

developing on-shore allocations for each water depth.

As noted earlier in this report, each offshore activity phase is unique. Not only are the

expenditure patterns of these activities unique, but in many instances, particular areas supporting

these activities can be concentrated in a certain locale. For instance, as the industry has become

more consolidated, certain activities can also become more consolidated in particular regions as

the number of firms becomes more concentrated. For instance, there has been a notable

tendency for platform fabrication and shipbuilding to become concentrated in particular areas. 

While our current allocations reflect some of this concentration – the current framework does not 

provide a dynamic approach of how these concentrations are changing.

Another area of improvement within the allocation process is related to water depth. In

particular, attempting to understand if there are unique onshore allocations associated with

offshore production in varying water depths. Do deepwater activities tend to have different

onshore allocations than shallow water activities? There is at least some anecdotal evidence that 

would suggest there is a greater out-of-area impact associated with deepwater activity than

shallow water. In particular, deepwater activity has often been characterized as more “global” in 
40

nature, and as such, deepwater activities in the Gulf more than likely pull resources from

deepwater producing basins around the world. 

5.2 Cost Functions By Technology: One of the other limitations of the current approach is

that there has been an aggregation of cost functions across technologies used in each activity

phase. This analysis assumed that within each activity phase, and within each water depth, there 

was a “typical” technology that was being facilitated. Thus, in the pipeline construction phase, a 

“typical” pipeline diameter is assumed, over a typical area, facilitating a particular pipeline

laying process. However, one of the first points many offshore professionals would make today

is that there is no such thing as a “typical” offshore approach – this is particularly true with

deepwater activities.

Thus, this lane of research could be improved by disaggregating offshore activities by a range of 

feasible technologies. The advantage of conducting such methods in a straightforward,

disaggregated manner will hopefully provide more accurate understanding of the impacts of

changing technology on local communities. For instance, conventional wisdom would tend to

support the notion that technological innovation, with its greater reliance on computer-driven 

automation and remote applications, can only be bad for labor – it results in less labor demand,

higher unemployment, and a lower quality of living for households directly associated with

offshore activities. 

Furthermore, consider the offsetting impacts that these technologies can also have. Recent

emphasis on computer applications and SCADA systems are changing a number of production

processes. These are streamlining communications and creating greater emphasis on

communications related expenditures, fiber optic cable installation, switching equipment,

broadband wireless equipment, to name a few. This has the direct effect of increasing and

changing our allocations. 

Another interesting aspect of incorporating technology-specific approach is that, on a forward

going basis, it will allow for the direct economic modeling of a shift in technologies that will

require MMS approval. Consider, for instance, the recent approval process for Floating 

Production, Storage and Offloading (FPSO) vessels. Using a direct technology allocation and

production function would allow for the direct economic impact modeling of this technology and 

an understanding of the economic impacts that this shift in technology would have on

community relative to other types of technology use – for instance, what are the relative

economic impacts of using FPSO versus constructing and operating a major pipeline?

5.3 Contractor Expenditure Profiles: As alluded to earlier, a good deal of activities over time 

have become offered out to subcontractors. This is especially true in shallow water activities.

The problem with the presence of contractor information for this project was that it has the

tendency to aggregate a considerable amount of expenditures into one economic sector category. 

For instance, in both the exploratory and development drilling activities, owners relied heavily

upon drilling contractors. These expenditure entries, presented in accounting format, were

allocated to one general category for oil and gas sector work (there are no separate accounts for

drilling as opposed to other activities). This is problematic because: (1) the approach treated all
41

contractor expenditures as a lump sum, or as one contractor, when many could have been used,

in different places on the Gulf; and (2) these contractors hire labor and purchase equipment,

tools, services and other things that have unique expenditure profiles of their own. One

important limitation with the current work is that these types of expenditures are missing.

In the future, in order to gain a more accurate representation of these allocations, a contractor

allocation profile will need to be developed. Such an approach will require two things. First, to 

determine the typical types of activities that tend to be contracted – for instance, what are the

common types of contractor services that are employed and do these vary by activity or by water 

depth. Second, after identifying the types of activities that are contracted, a survey of contractors 

will need to be developed on the types of expenditures they make related to internal operators.

An alternative to this approach, however, could consist of a more “whole-phase” nature. Such an 

approach would consider all types of expenditures within an activity based upon the nature of the 

activity, and not the party engaged in the process. Such an approach, however, while appealing,

is clearly more difficult.

5.4 Public Finance: An additional area of investigation that would be important for future

economic impact analyses is understanding the public expenditure profile. This analysis did not

consider the impact that offshore activities have on public expenditures, and how the public

sector reacts to changes in offshore activities. Clearly, the composition of these public

expenditures will change given overall changes in the types of offshore activities that are

occurring across different water depths. This is a complicated area of inquiry that to date has

been explored in little quantitative depth. 

The issues associated with public sector activities abound:

(1) Do public expenditures vary by activity type? In other words, do particular types of

offshore activities have unique impacts on public sector economics. An interesting

question to consider is whether construction oriented activities tend to have bigger

public sector impacts than traditional operations/production activities.

(2) What are the expenditure profiles of public sector activities that arise in response to

offshore oil and gas activities? The government sector, like others, is a consuming

unit in regional economies. It is an interesting research question to understand how

public sector expenditures evolve and the impacts they have on regional economies. 

A recent study funded by the MMS examined the impacts that overall offshore

activities have had on one particular community (Port Fourchon). This study

interestingly noted that offshore activities generated more revenues for this local

community than it required in expenditures on public infrastructure.

(3) How are offshore royalty revenues (benefits) distributed across onshore

communities? While the MMS develops an equitable sharing approach, it is not

entirely clear how royalty revenues are distributed within coastal states, and in turn,

how different economic impacts arise from those differing distributions.
42

5.5 Interregional Analysis: Another limitation of the current research, and in the more recent

approaches of modeling the economic impacts of offshore activities, is the lack of linkages

between offshore areas. The economic impact framework used in this study examines onshore

communities in aggregate blocks across an expansive area in the Gulf. There may be, however,

substantial linkages between the areas in terms of their potential mutual support for differing

activities. Future analysis should examine the degree of linkages between these defined areas. 

One might anticipate, for instance, that expenditures in localized areas may spill over into

neighboring regions to help support offshore activities. Conventional wisdom might lead one to

expect that these linkages may become stronger during boom periods when some local

economics could become saturated. In addition, there is some evidence that particular activities, 

particularly those associated with deepwater activities, have highly specialized functions that are

“pulled-together” from throughout the Gulf region. Future research should explore the

magnitude and extent of such potential spill-over effects.

5.6 Project Summary and Conclusions: This study is the first of its kind to comprehensively

examine the cost structures of offshore activities in the Gulf of Mexico. No other research has

examined total costs, activity-specific costs, and the allocation of costs to onshore areas in the

manner presented here. As noted earlier, there are a number of areas where this research can be

improved. We are confident that this report has made a significant contribution to the literature. 

Nevertheless, we believe that, in conjunction with the work of our colleagues at the MMS, we

have started the process of developing analytic tools that quantify the links between the offshore

industry and onshore communities. 

We believe that the results of our research have yielded benefits that go beyond intellectual

curiosity. The process of creating real world models for offshore oil and gas activities in the

Gulf of Mexico can yield meaningful differences when compared to standardized, secondary I-O 

models. We believe the MMS motivation for moving forward with creating these customized

approaches appears to be justified. 

In conclusion, we would like to present estimates that compare the standardized results from the

IMPLAN modeling approach to the customized results for exploratory drilling in the 0-60 meter 

water depth for the LA-2 region. Table 5.1 presents two sets of analyses that result from

shocking both the generalized IMPLAN model and the IMPLAN model using our specialized

expenditure profiles and onshore allocations. The first analysis is the generalized, standard

IMPLAN results, while the second analysis comes from our Gulf-specific analysis. The table

shows considerable percent differences between the two types of analyses.
43

 Table 5.1: Estimated Economic Impacts for Exploratory Drilling, LA-2 Region

Estimated Annual Impact -- Standard Analysis (1998 Dollars)

Direct Indirect Induced Total

Output 179,502,016 16,454,092 15,543,905 211,500,011

Labor Income 14,524,824 3,839,397 5,936,279 24,300,500

Total Value Added 49,131,317 8,382,280 9,560,596 67,074,189

Employment (Number) 273 111 246 629

Estimated Annual Impact -- Modified, Gulf-Specific Analysis (1998 Dollars)

Direct Indirect Induced Total

Output 178,219,407 29,111,563 21,800,854 229,131,826

Labor Income 17,490,114 8,875,273 8,325,832 34,691,221

Total Value Added 47,687,687 15,538,328 13,409,060 76,635,075

Employment (Number) 391 278 345 1,014

The differences in output, for instance, are 8 percent lower using our revised method of

measuring economic impacts, than the canned approach included in IMPLAN. Labor income,

however, is about 42 percent higher in our analysis relative to standard approaches. Value added 

is 14 percent higher in our model, while employment opportunities, represented by the number of 

jobs created by new exploratory wells, is 62 percent higher in our model than the standardized

approach. These results, at minimum, support the notion that there are unique economic

differences in the offshore industry and that further research should be conducted to better

understand those differences and the impacts they have on human communities of the Gulf of

Mexico.
45

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Appendix A:

Industry Cost Tables
51

Table A.1: Production Functions for Exploratory Drilling in the Gulf of Mexico

by Major Water Depth

EXPLORATORY DRILLING

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.6773 0.6741 0.7331 0.7322 0.7042

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.0343 0.0342 0.0292 0.0292 0.0317

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels 0.0283 0.0283 0.0242 0.0241 0.0262

232 Hydraulic Cement 0.0669 0.0695 0.0580 0.0593 0.0634

258 Steel Pipe and Tubes 0.0619 0.0628 0.0441 0.0438 0.0531

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation 0.0408 0.0407 0.0346 0.0346 0.0377

435 Demurrage/Warehousing/Motor Freight

436 Water Transport 0.0828 0.0827 0.0701 0.0701 0.0764

437 Air Transport 0.0078 0.0078 0.0066 0.0066 0.0072

441 Communications

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail

459 Insurance

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.0000 1.0000 1.0000 1.0000 1.0000
52

DEVELOPMENT DRILLING

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.65341 0.52344 0.64192 0.69198 0.62769

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.03447 0.02107 0.04069 0.03348 0.03243

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels 0.02746 0.03349 0.03049 0.02664 0.02952

232 Hydraulic Cement 0.06566 0.11871 0.07490 0.06410 0.08084

258 Steel Pipe and Tubes 0.07104 0.15527 0.06077 0.05149 0.08464

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.01545 0.01524 0.01039 0.00947 0.01264

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation 0.04110 0.04222 0.04375 0.03817 0.04131

435 Demurrage/Warehousing/Motor Freight

436 Water Transport 0.08355 0.08276 0.08873 0.07739 0.08311

437 Air Transport 0.00787 0.00780 0.00836 0.00729 0.00783

441 Communications

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Disposal

454 Eating/Drinking

455 Msc Retail

459 Insurance

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.2: Production Functions for Development Drilling in the Gulf of Mexico
53

PRODUCTION , OPERATIONS

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.29058 0.27271 0.26142 0.25126 0.26899

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.07158 0.07020 0.07018 0.07018 0.07054

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes 0.03560 0.03324 0.03171 0.03033 0.03272

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.04846 0.04526 0.04317 0.04129 0.04455

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation 0.02755 0.02573 0.02454 0.02347 0.02532

435 Demurrage/Warehousing/Motor Freight

436 Water Transport 0.35196 0.32868 0.31353 0.29987 0.32351

437 Air Transport 0.05306 0.07260 0.07581 0.07832 0.06995

441 Communications 0.00843 0.01023 0.01043 0.01057 0.00991

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Disposal

454 Eating/Drinking 0.03637 0.03396 0.03240 0.03099 0.03343

455 Msc Retail

459 Insurance 0.07641 0.10739 0.13681 0.16372 0.12108

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.3: Production Functions for Offshore Production in the Gulf of Mexico
54

PLATFORM FABRICATION

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.02500 0.02500 0.02650 0.02750 0.02600

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes 0.36377 0.42526 0.48000 0.56312 0.45804

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines 0.01312 0.01250 0.01250 0.01250 0.01266

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.00125 0.00125 0.00125 0.00125 0.00125

331 Special Industrial Machinery 0.05380 0.05750 0.05750 0.05750 0.05658

332 Pumps & Compressors 0.03205 0.03625 0.03625 0.03625 0.03520

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair 0.43063 0.35395 0.27625 0.21337 0.31855

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport 0.01266 0.01714 0.02275 0.01972 0.01807

437 Air Transport 0.01250 0.01250 0.01250 0.01250 0.01250

441 Communications

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal

454 Eating/Drinking 0.00377 0.00364 0.00425 0.00375 0.00385

455 Msc Retail

459 Insurance

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services 0.05145 0.05501 0.07025 0.05254 0.05731

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.4: Production Functions for Platform Fabrication in the Gulf of Mexico
55

PIPELINES: CONSTRUCTION

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.00209 0.01330 0.01560 0.00000 0.00775

50 New Gas Utility Facilities 0.78299 0.81386 0.78306 0.96255 0.83562

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services

160 Office Furniture and Equipment 0.00508 0.00358 0.00587 0.00000 0.00363

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.19694 0.14566 0.18518 0.03629 0.14102

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC 0.00228 0.00226 0.00435 0.00000 0.00222

356 Switchgear

374 Communication Equipment, NEC 0.00456 0.01054 0.00397 0.00116 0.00506

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC 0.00433 0.00614 0.00115 0.00000 0.00290

401 Lab Equipment 0.00088 0.00008 0.00001 0.00000 0.00024

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport

437 Air Transport

441 Communications

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail

459 Insurance

462 Real Estate 0.00085 0.00457 0.00080 0.00000 0.00156

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.5: Production Functions for Pipeline Construction in the Gulf of Mexico
56

PIPELINES: OPERATIONS & MAINTENANCE

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities 0.162247 0.125630 0.129560 0.024087 0.110381

57 Other Oil & Gas Field Services

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery

331 Special Industrial Machinery

332 Pumps & Compressors 0.004091 0.118562 0.127545 0.008342 0.064635

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport

437 Air Transport

441 Communications 0.002782 0.005693 0.004815 0.038740 0.013007

443 Electric Services 0.028229 0.000000 0.000000 0.007096 0.008831

444 Gas Production/Distribution 0.420153 0.414360 0.410597 0.454391 0.424875

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail 0.040800 0.071190 0.012592 0.017434 0.035504

459 Insurance 0.034591 0.020910 0.045459 0.000605 0.025391

462 Real Estate

469 Advertisement 0.000000 0.000089 0.000000 0.000000 0.000022

470 Other Business Services 0.002744 0.054240 0.028815 0.120269 0.051517

473 Msc. Equipment Rental and Leasing 0.013041 0.027807 0.031880 0.030699 0.025857

490 Doctors & Veterinarian Services

494 Legal Services 0.141174 0.066919 0.089409 0.005405 0.075727

506 Environmental/Engineering Services 0.027406 0.027624 0.041986 0.292933 0.097487

507 Acct/Msc Business Services 0.042891 0.002233 0.000000 0.000000 0.011281

508 Management/Consulting Services 0.079852 0.064742 0.077341 0.000000 0.055484

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.6: Production Functions for Pipeline O&M in the Gulf of Mexico
57

GAS PROCESSING & STORAGE: CONSTRUCTION

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.58415 0.58415 0.58415 0.58415 0.58415

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction 0.04208 0.04208 0.04208 0.04208 0.04208

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.37186 0.37186 0.37186 0.37186 0.37186

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC 0.00000 0.00000 0.00000 0.00000 0.00000

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport

437 Air Transport

441 Communications

443 Electric Services

444 Gas Production/Distribution 0.00000 0.00000 0.00000 0.00000 0.00000

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail

459 Insurance

462 Real Estate 0.00192 0.00192 0.00192 0.00192 0.00192

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.7: Production Functions for Gas Processing & Storage Construction in the Gulf of Mexico
58

GAS PROCESSING & STORAGE: OPERATIONS & MAINTENANCE

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.05635 0.05635 0.05635 0.05635 0.05635

50 New Gas Utility Facilities 0.00000 0.00000 0.00000 0.00000 0.00000

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities 0.06933 0.06933 0.06933 0.06933 0.06933

57 Other Oil & Gas Field Services

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing) 0.00007 0.00007 0.00007 0.00007 0.00007

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery

331 Special Industrial Machinery

332 Pumps & Compressors 0.10274 0.10274 0.10274 0.10274 0.10274

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation 0.00216 0.00216 0.00216 0.00216 0.00216

435 Demurrage/Warehousing/Motor Freight 0.00000 0.00000 0.00000 0.00000 0.00000

436 Water Transport

437 Air Transport

441 Communications 0.00000 0.00000 0.00000 0.00000 0.00000

443 Electric Services 0.10139 0.10139 0.10139 0.10139 0.10139

444 Gas Production/Distribution 0.25144 0.25144 0.25144 0.25144 0.25144

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail 0.06783 0.06783 0.06783 0.06783 0.06783

459 Insurance 0.01348 0.01348 0.01348 0.01348 0.01348

462 Real Estate

469 Advertisement 0.00052 0.00052 0.00052 0.00052 0.00052

470 Other Business Services 0.23464 0.23464 0.23464 0.23464 0.23464

473 Msc. Equipment Rental and Leasing 0.05566 0.05566 0.05566 0.05566 0.05566

490 Doctors & Veterinarian Services

494 Legal Services 0.04236 0.04236 0.04236 0.04236 0.04236

506 Environmental/Engineering Services

507 Acct/Msc Business Services 0.00199 0.00199 0.00199 0.00199 0.00199

508 Management/Consulting Services

509 Testing/Research Facilities

Total 0.99999 0.99999 0.99999 0.99999 0.99999

Table A.8: Production Functions for Gas Processing & Storage O&M in the Gulf of Mexico
59

WORKOVERS

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.06899 0.06543 0.06455 0.06375 0.06568

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.37196 0.35280 0.34804 0.34373 0.35413

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery 0.04905 0.04652 0.04589 0.04532 0.04669

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport 0.47569 0.49167 0.49529 0.49857 0.49030

437 Air Transport 0.02361 0.03282 0.03544 0.03781 0.03242

441 Communications 0.00214 0.00264 0.00278 0.00291 0.00261

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal

454 Eating/Drinking 0.00857 0.00812 0.00801 0.00792 0.00816

455 Msc Retail

459 Insurance

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.9: Production Functions for Workovers in the Gulf of Mexico
60

OIL SPILLS

Total

Average Average Average Average Average

Production Production Production Production Production

IMPLAN Sector Description Function Function Function Function Function

Sectors 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations 0.00230 0.00119 0.00352 0.00352 0.00263

50 New Gas Utility Facilities

53 Misc Natural Resource Facility Construction

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services 0.00210 0.00147 0.00178 0.00178 0.00178

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC 0.00399 0.00454 0.00444 0.00444 0.00435

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair 0.00536 0.00832 0.01409 0.01409 0.01047

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight 0.00132 0.00088 0.00099 0.00099 0.00104

436 Water Transport

437 Air Transport

441 Communications 0.00012 0.00005 0.00000 0.00000 0.00004

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal 0.00178 0.00018 0.00020 0.00020 0.00059

454 Eating/Drinking 0.00247 0.00148 0.00167 0.00167 0.00182

455 Msc Retail 0.00273 0.00104 0.00117 0.00117 0.00153

459 Insurance

462 Real Estate

469 Advertisement 0.00189 0.00109 0.00000 0.00000 0.00075

470 Other Business Services

473 Msc. Equipment Rental and Leasing 0.01409 0.00903 0.01079 0.01079 0.01118

490 Doctors & Veterinarian Services 0.04327 0.04437 0.04387 0.04387 0.04384

494 Legal Services 0.67255 0.70237 0.77443 0.77443 0.73094

506 Environmental/Engineering Services 0.15935 0.14437 0.14287 0.14287 0.14736

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities 0.08669 0.07963 0.00019 0.00019 0.04167

Total 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.10: Production Functions for Oil Spills in the Gulf of Mexico
61

Total

Average Average Average Average Average

FA Production Production Production Production Production

IMPLAN Sector Description Platform Function Function Function Function Function

Sectors Abandonment 0-60 Meters 60-200 Meters 200-900 Meters 900 + Meters (All Depths)

38 Oil & Gas Operations NA 0.14855 0.16929 0.17309 0.20139 0.17308

50 New Gas Utility Facilities NA 0.03732 0.04683 0.05043 0.05972 0.04858

53 Misc Natural Resource Facility Construction NA 0.05050 0.03210 0.01563 0.01667 0.02872

56 Maintenance and Repair, Other Facilities

57 Other Oil & Gas Field Services NA 0.17102 0.11066 0.10253 0.01389 0.09952

160 Office Furniture and Equipment

178 Maps and Charts (Msc Publishing)

206 Explosives

209 Chemicals, NEC

210 Petroleum Fuels

232 Hydraulic Cement

258 Steel Pipe and Tubes

284 Fabricated Plate Work

290 Iron and Steel Forgings

307 Turbines

311 Construction Machinery & Equipment

313 O&G Field Machinery

331 Special Industrial Machinery

332 Pumps & Compressors

354 Industrial Machines, NEC

356 Switchgear

374 Communication Equipment, NEC

392 Shipbuilding and Ship Repair

399 Transportation Equipment, NEC

401 Lab Equipment

403 Instrumentation

435 Demurrage/Warehousing/Motor Freight

436 Water Transport NA 0.58534 0.62886 0.64319 0.69028 0.63692

437 Air Transport

441 Communications

443 Electric Services

444 Gas Production/Distribution

445 Water Supply

446 Waste Disposal

454 Eating/Drinking

455 Msc Retail

459 Insurance

462 Real Estate

469 Advertisement

470 Other Business Services

473 Msc. Equipment Rental and Leasing

490 Doctors & Veterinarian Services

494 Legal Services

506 Environmental/Engineering Services NA 0.00728 0.01226 0.01513 0.01806 0.01318

507 Acct/Msc Business Services

508 Management/Consulting Services

509 Testing/Research Facilities

Total NA 1.00000 1.00000 1.00000 1.00000 1.00000

Table A.11: Production Functions for Platform Abandonment in the Gulf of Mexico

PLATFORM ABANDONMENT
62

IMPLAN Definition TX-1 TX-2 LA-1 LA-2 LA-3 MA-1 FL-1 FL-2 FL-3 FL-4 Gulf-Other US-Other

Sectors

38 Oil & Gas Operations 0.00 0.34 0.09 0.06 0.15 0.00 0.00 0.00 0.00 0.00 0.25 0.12

50 New Gas Utility Facilities 0.07 0.38 0.05 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.13 0.07

53 Misc Natural Resource Facility Construction 0.03 0.21 0.23 0.15 0.30 0.02 0.00 0.00 0.00 0.00 0.06 0.03

56 Maintenance and Repair, Other Facilities 0.06 0.31 0.04 0.08 0.09 0.08 0.00 0.00 0.00 0.00 0.22 0.11

57 Other Oil & Gas Field Services 0.00 0.30 0.26 0.12 0.16 0.00 0.00 0.00 0.00 0.00 0.11 0.05

160 Office Furniture and Equipment 0.15 0.54 0.00 0.00 0.08 0.23 0.00 0.00 0.00 0.00 0.00 0.00

178 Maps and Charts (Msc Publishing) 0.12 0.59 0.02 0.06 0.11 0.10 0.00 0.00 0.00 0.00 0.00 0.00

206 Explosives 0.50 0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

209 Chemicals, NEC 0.03 0.64 0.04 0.10 0.04 0.04 0.00 0.00 0.00 0.00 0.08 0.04

210 Petroleum Fuels 0.11 0.50 0.09 0.16 0.09 0.05 0.00 0.00 0.00 0.00 0.00 0.00

232 Hydraulic Cement 0.00 0.10 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.50 0.30

258 Steel Pipe and Tubes 0.00 0.50 0.31 0.05 0.07 0.00 0.00 0.00 0.00 0.00 0.08 0.04

284 Fabricated Plate Work 0.04 0.63 0.06 0.09 0.05 0.14 0.00 0.00 0.00 0.00 0.00 0.00

290 Iron and Steel Forgings 0.00 0.81 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.14 0.00

307 Turbines 0.05 0.65 0.00 0.10 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00

311 Construction Machinery & Equipment 0.06 0.42 0.00 0.06 0.19 0.11 0.00 0.00 0.00 0.00 0.11 0.06

313 O&G Field Machinery & Equipment 0.03 0.18 0.27 0.18 0.22 0.00 0.00 0.00 0.00 0.00 0.08 0.04

331 Special Industrial Machinery 0.00 0.00 0.00 0.38 0.54 0.00 0.00 0.00 0.00 0.00 0.05 0.03

332 Pumps & Compressors 0.04 0.30 0.17 0.22 0.09 0.00 0.00 0.00 0.00 0.00 0.12 0.06

354 Industrial Machines, NEC 0.05 0.66 0.06 0.10 0.06 0.06 0.00 0.00 0.00 0.00 0.00 0.00

356 Switchgear 0.00 0.63 0.00 0.07 0.11 0.07 0.00 0.00 0.00 0.00 0.11 0.00

374 Communication Equipment, NEC 0.13 0.50 0.00 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.13 0.00

392 Shipbuilding and Ship Repair 0.09 0.24 0.05 0.24 0.18 0.19 0.00 0.00 0.00 0.00 0.00 0.00

399 Transportation Equipment, NEC 0.00 0.78 0.06 0.11 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00

401 Lab Equipment 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

403 Instrumentation 0.01 0.13 0.39 0.27 0.08 0.00 0.00 0.00 0.00 0.00 0.08 0.04

435 Demurrage/Warehousing/Motor Freight 0.11 0.37 0.21 0.09 0.09 0.01 0.00 0.00 0.00 0.00 0.12 0.00

436 Water Transport 0.02 0.27 0.10 0.25 0.22 0.04 0.01 0.00 0.01 0.00 0.08 0.00

437 Air Transport 0.03 0.42 0.11 0.11 0.08 0.02 0.00 0.00 0.00 0.01 0.22 0.00

441 Communications 0.09 0.51 0.07 0.11 0.11 0.11 0.00 0.00 0.00 0.00 0.00 0.00

443 Electric Services 0.13 0.36 0.06 0.15 0.12 0.18 0.00 0.00 0.00 0.00 0.00 0.00

444 Gas Production/Distribution 0.10 0.54 0.08 0.07 0.05 0.03 0.00 0.00 0.00 0.00 0.08 0.04

445 Water Supply 0.08 0.43 0.08 0.12 0.05 0.11 0.00 0.00 0.00 0.00 0.12 0.01

446 Waste Treatment/Disposal 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

454 Eating/Drinking 0.00 0.24 0.28 0.08 0.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00

455 Msc Retail 0.09 0.48 0.06 0.10 0.15 0.11 0.00 0.00 0.00 0.00 0.00 0.00

459 Insurance 0.04 0.47 0.07 0.12 0.09 0.00 0.00 0.00 0.00 0.00 0.18 0.03

462 Real Estate 0.09 0.47 0.04 0.08 0.11 0.08 0.00 0.00 0.00 0.00 0.12 0.01

469 Advertisement 0.06 0.45 0.06 0.08 0.15 0.08 0.00 0.00 0.00 0.00 0.12 0.01

470 Other Business Services 0.00 0.60 0.11 0.09 0.06 0.00 0.00 0.00 0.00 0.00 0.10 0.05

473 Msc. Equipment Rental and Leasing 0.09 0.26 0.22 0.10 0.10 0.01 0.00 0.00 0.00 0.00 0.20 0.03

490 Doctors & Veterinarian Services 0.09 0.53 0.06 0.09 0.14 0.08 0.00 0.00 0.00 0.00 0.00 0.00

494 Legal Services 0.07 0.48 0.07 0.11 0.19 0.08 0.00 0.00 0.00 0.00 0.00 0.00

506 Environmental/Engineering Services 0.06 0.38 0.11 0.08 0.08 0.03 0.01 0.00 0.02 0.00 0.21 0.01

507 Acct/Msc Business Services 0.06 0.46 0.05 0.09 0.13 0.07 0.00 0.00 0.00 0.00 0.12 0.01

508 Management/Consulting Services 0.04 0.54 0.04 0.09 0.11 0.05 0.00 0.00 0.00 0.00 0.12 0.01

509 Testing/Research Facilities 0.00 0.38 0.14 0.14 0.05 0.00 0.00 0.00 0.00 0.00 0.22 0.11

Table A.12: Onshore Allocation of Offshore Expenses
63

Table A.13: Total Cost Analysis: Summary of Total Costs by Offshore Activity and Water Depth

Category 0-60 Meters 60-200 Meters 200-900 Meters 900+ Meters

Exploratory Drilling

Annual Total Cost Per Well (1998, $000) 4,245 3,240 6,897 10,577

Development Drilling

Annual Total Cost Per Well (1998, $000) 4,231 2,774 5,045 9,779

Production Costs

Annual Total Cost Per Well (1998) 240,908 253,764 263,152 271,070

Platform Installation Costs

Total Cost Per Platform (1999, $ Million) 19.101 74.376 124.566 131.115

Installed Costs: Pipelines

Total Costs Per Mile 541,315 891,654 1,509,284 3,850,385

O&M Costs: Pipelines

Total Costs Per MMBTU (1998 Dollars) 0.0520 0.0642 0.0660 0.0767

Total Costs Per BCF (1998 Dollars) 53.3296 65.8886 67.6846 78.7038

Installed Cost: Gas Processing and Storage

Total Costs per BCF/d Capacity (2000 $ Millions) 136 136 136 136

O&M Cost: Gas Processing and Storage

Total Costs per BCF (1998) 36.9373 36.9373 36.9373 36.9373

Workover Costs

Total Costs Per Workover Per Well (1998) 13,704 14,385 14,566 14,566

Oil Spill Costs

Total Costs Per Gallon Spilled (1998) 107.19 67.88 45.45 45.45

Platform Abandonment and Removal Costs

(Costs Per Platform)

4-Pile Platform (By Method)

Bulk Explosives (Topple) -- (1994) 572,500 1,236,435 6,128,504 10,032,703

Bulk Explosives (Std Practice) -- (1994) 707,500 1,676,685 10,108,047 17,421,039

Abrasive Cutting -- (1994) 880,000 1,991,857 8,403,445 13,536,319

Mechanical Cutting -- (1994) 976,750 2,172,751 9,120,996 14,678,739

Weighted Average (1994) 800,988 1,582,313 8,132,202 10,032,703

8-Pile Platform (By Method)

Bulk Explosives (Topple) -- (1994) 835,000 2,030,700 10,869,108 17,931,115

Bulk Explosives (Std Practice) -- (1994) 987,500 2,473,299 15,377,140 26,629,383

Abrasive Cutting -- (1994) 1,221,250 2,842,409 11,950,378 19,253,528

Mechanical Cutting -- (1994) 1,435,750 3,263,999 13,572,417 21,837,837

Weighted Average 1,131,832 2,413,015 13,129,364 17,931,115
65

Appendix B:

Coastal Impact Tables 
67

 Appendix Table B.1:

Socioeconomic and Demographic Indicators

Project Area Mean

LA1 Average earnings per job (dollars), 1997 25,810.60

LA2 Average earnings per job (dollars), 1997 27,712.00

LA3 Average earnings per job (dollars), 1997 27,999.80

LA1 Civilian labor force (BLS), number, 1996 47,883.80

LA2 Civilian labor force (BLS), number, 1996 44,441.00

LA3 Civilian labor force (BLS), number, 1996 112,520.80

LA1 Civilian labor force (BLS),unemployment rate, 1996 5.72

LA2 Civilian labor force (BLS),unemployment rate, 1996 7.27

LA3 Civilian labor force (BLS),unemployment rate, 1996 6.12

LA1

Educational attainment, percent of persons 25 years and over 

college graduates, 1990 12.58

LA2

Educational attainment, percent of persons 25 years and over 

college graduates, 1990 11.84

LA3

Educational attainment, percent of persons 25 years and over 

college graduates, 1990 15.82

LA1

Educational attainment, percent of persons 25 years and over 

high school graduates, 1990 64.46

LA2

Educational attainment, percent of persons 25 years and over 

high school graduates, 1990 65.72

LA3

Educational attainment, percent of persons 25 years and over 

high school graduates, 1990 69.24

LA1 Farm employment, 1997 4,567.00

LA2 Farm employment, 1997 5,163.00

LA3 Farm employment, 1997 911

LA1 Farm income (thousands of dollars), 1997 8,742.20

LA2 Farm income (thousands of dollars), 1997 5,751.09

LA3 Farm income (thousands of dollars), 1997 799

LA1 Mining Employment, 1997 21,977.00

LA2 Mining Employment, 1997 12,393.00

LA3 Mining Employment, 1997 15,938.00

LA1 Nonfarm employment, 1997 294,089.00

LA2 Nonfarm employment, 1997 552,095.00

LA3 Nonfarm employment, 1997 700,815.00

LA1 Nonfarm personal income (thousands of dollars), 1997 2,102,038.20

LA2 Nonfarm personal income (thousands of dollars), 1997 1,926,348.64

LA3 Nonfarm personal income (thousands of dollars), 1997 5,612,477.80

LA1 Nonfarm personal income (thousands of dollars), 1997207,660.00

LA2 Nonfarm personal income (thousands of dollars), 1997 35,108.36

LA3 Nonfarm personal income (thousands of dollars), 1997 183,412.60

LA1 Per Capita Personal Income (dollars), 1997 19,565.80

LA2 Per Capita Personal Income (dollars), 1997 19,600.09

LA3 Per Capita Personal Income (dollars), 1997 22,064.00

LA1 Per capita transfer payments, 1997 3,643.20

LA2 Per capita transfer payments, 1997 3,785.73

LA3 Per capita transfer payments, 1997 4,545.40
68

Project Area Mean

LA1 Population (number of persons), 1997 99,280.80

LA2 Population (number of persons), 1997 93,160.27

LA3 Population (number of persons), 1997 239,516.40

LA1 Population, 65 years and over, 1996 10,408.40

LA2 Population, 65 years and over, 1996 8,642.00

LA3 Population, 65 years and over, 1996 27,425.00

LA1 Population, percent American Indian, Eskimo, or Aleut, 1996 0.2

LA2 Population, percent American Indian, Eskimo, or Aleut, 1996 0.92

LA3 Population, percent American Indian, Eskimo, or Aleut, 1996 0.66

LA1 Population, percent Asian or Pacific Islander, 1996 1.1

LA2 Population, percent Asian or Pacific Islander, 1996 0.74

LA3 Population, percent Asian or Pacific Islander, 1996 1.98

LA1 Population, percent Hispanic (maybe of any race), 1996 1.74

LA2 Population, percent Hispanic (maybe of any race), 1996 1.75

LA3 Population, percent Hispanic (maybe of any race), 1996 4.72

LA1 Population, Percent Black, 1996 20.3

LA2 Population, Percent Black, 1996 29.03

LA3 Population, Percent Black, 1996 25

LA1 Poverty, percent below poverty, 1993 20

LA2 Poverty, percent below poverty, 1993 20.95

LA3 Poverty, percent below poverty, 1993 21.38

LA1 Private nonfarm establishments, percent retail trade, 1995 24.34

LA2 Private nonfarm establishments, percent retail trade, 1995 24.36

LA3 Private nonfarm establishments, percent retail trade, 1995 24.02

LA1 Private nonfarm establishments, percent service, 1995 33.48

LA2 Private nonfarm establishments, percent service, 1995 31.84

LA3 Private nonfarm establishments, percent service, 1995 35.6

LA1 Total full- and part-time employment, 1997 59,731.00

LA2 Total full- and part-time employment, 1997 50,660.00

LA3 Total full- and part-time employment, 1997 140,345.00

Source: REIS, U.S. BEA, and Government Information Sharing Project

(Http://govinfo.kerr.orst.edu)

(Continued)
69

Appendix Table B.2:

Selected Socioeconomic and Demographic Indicators, All Louisiana

Indicator Description Estimate

Average earnings per job (1996 dollars) 26,798.00

Civilian labor force (BLS), number, 1996 19,997,300.00

Civilian labor force (BLS),unemployment rate, 1996 6.7

Educational attainment, percent of persons 25 years and over college graduates, 

1990

16.1

Educational attainment, percent of persons 25 years and over high school 

graduates, 1990

68.3

Farm employment, 1996 37,476.00

Farm income, 1996 497,478.00

Mining Employment, 1996 58,023.00

Nonfarm employment, 1996 2,258,496.00

Nonfarm personal income ($1000) , 1996 88,569,068.00

Oil and gas extraction earnings ($1000) , 1996 3,049,679.00

Per capita personal income (dollars) , 1996 20,458.00

Per capita transfer payments, 1996 4,326.00

Population (number of persons) , 1996 4,351,769.00

Population, 65 years and over, 1996 496,606.00

Population, percent white, 1996 66.3

Population, percent American Indian, Eskimo, or Aleut, 1996 0.4

Population, percent Asian or Pacific Islander, 1996 1.2

Population, percent Hispanic (maybe of any race), 1996 2.5

Population, percent Black, 1996 32

Poverty, percent below poverty, 1993 23.9

Private nonfarm establishments, percent retail trade, 1995 24.3

Private nonfarm establishments, percent service, 1995 36.5

Total full- and part-time employment, 1996 2,295,972.00

Source: REIS, U.S. BEA, and Government Information Sharing Project 

(http://govinfo.kerr.orst.edu)
70

Appendix Table B.3:

Commodities With Modified Regional Purchasing Coefficient

IMPLAN 

Code

Commodity Net Commodity 

Supply

Total Gross 

Commodity 

Demand

Domestic 

SDP

Average 

RPC

1 Dairy Farm Products 130.32 177.59 0.7300 0.1900

13 Hay and Pasture 98.65 70.36 1.0000 0.0900

19 Sugar Crops 134.94 121.33 1.0000 0.9800

23 Greenhouse and Nursery Products 34.33 181.16 0.1900 0.0700

24 Forestry Products 416.00 401.36 1.0000 0.0100

38 Natural Gas & Crude Petroleum 6362.35 10775.30 0.5900 0.3600

45 Chemical- Fertilizer Mineral 

Mining- N.E.C.

0.00 50.28 0.0000 0.0000

60 Poultry Processing 495.19 446.04 1.0000 0.9800

69 Pickles- Sauces- and Salad 

Dressings

123.90 123.16 1.0000 0.0500

74 Rice Milling 163.57 71.75 1.0000 0.1000

95 Bottled and Canned Soft Drinks & 

Water

686.49 460.59 1.0000 0.1300

98 Prepared Fresh Or Frozen Fish Or 

Seafood

334.26 119.01 1.0000 0.1000

99 Roasted Coffee 539.98 101.61 1.0000 0.9000

162 Paper Mills- Except Building Paper 1109.05 422.75 1.0000 0.0000

163 Paperboard Mills 715.08 178.49 1.0000 0.0000

164 Paperboard Containers and Boxes 374.65 364.55 1.0000 0.9800

168 Bags- Paper 69.74 39.21 1.0000 0.0000

174 Newspapers 100.08 148.54 0.6700 0.1600

179 Commercial Printing 229.15 411.62 0.5600 0.1800

189 Inorganic Chemicals N.E.C. 980.76 665.76 1.0000 0.4400

191 Plastics Materials and Resins 1486.43 266.36 1.0000 0.8800

192 Synthetic Rubber 414.81 33.90 1.0000 0.8400

204 Agricultural Chemicals- N.E.C 259.26 159.84 1.0000 0.2800

210 Petroleum Refining 14599.54 3784.42 1.0000 0.8500

213 Lubricating Oils and Greases 498.39 110.92 1.0000 1.0000

214 Petroleum and Coal ProductsN.E.C.0.00 18.04 0.0000 0.0000

220 Miscellaneous Plastics Products 634.74 1366.61 0.4600 0.0000

243 Concrete Products- N.E.C 140.29 284.89 0.4900 0.0100

244 Ready-mixed Concrete 262.71 261.77 1.0000 0.0100

254 Blast Furnaces and Steel Mills 222.06 698.94 0.3200 0.0600

261 Primary Aluminum 201.17 62.35 1.0000 0.0200

265 Aluminum Rolling and Drawing 88.66 101.14 0.8800 0.0200

282 Fabricated Structural Metal 583.53 334.91 1.0000 0.0900

284 Fabricated Plate Work (Boiler 

Shops)

159.69 134.04 1.0000 0.0400

301 Industrial and Fluid Valves 355.59 288.24 1.0000 0.3300

303 Pipe- Valves- and Pipe Fittings 1.26 156.53 0.0100 0.0100

309 Farm Machinery and Equipment 100.55 153.42 0.6600 0.6600

313 Oil Field Machinery 94.92 148.68 0.6400 0.5300

314 Elevators and Moving Stairways 9.01 38.15 0.2400 0.2400

354 Industrial Machines N.E.C. 378.03 305.17 1.0000 0.0000
71

(Continued)

IMPLAN

Code

Commodity Net Commodity 

Supply

Total Gross 

Commodity 

Demand

Domestic 

SDP

Average 

RPC

369 Lighting Fixtures and Equipment 209.83 264.61 0.7900 0.0000

392 Ship Building and Repairing 1114.65 482.23 1.0000 0.0800

393 Boat Building and Repairing 154.05 110.61 1.0000 0.0200

441 Communications- Except Radio and 

TV

2638.85 3697.48 0.7100 0.5500

442 Radio and TV Broadcasting 49.96 50.90 0.9800 0.4200

456 Banking 3503.09 4880.19 0.7200 0.5600

457 Credit Agencies 453.91 571.53 0.7900 0.5600

460 Insurance Agents and Brokers 1094.68 615.82 1.0000 0.5200

461 Owner-occupied Dwellings 5193.65 7647.46 0.6800 0.6800

462 Real Estate 4020.84 8567.45 0.4700 0.4700

467 Funeral Service and Crematories 189.45 169.26 1.0000 0.9000

482 Miscellaneous Repair Shops 541.96 461.39 1.0000 0.6900

488 Amusement and Recreation ServicesN.E.C.1940.41 768.92 1.0000 0.8500

495 Elementary and Secondary Schools 383.69 408.37 0.9400 0.8000

497 Other Educational Services 320.74 299.64 1.0000 0.8000

503 Business Associations 234.10 196.80 1.0000 0.6000

504 Labor and Civic Organizations 239.34 271.48 0.8800 0.6000

513 U.S. Postal Service 734.14 742.65 0.9900 0.5100

515 Other Federal Government 

Enterprises

90.28 53.42 1.0000 0.5100

Source: IMPLAN, Minnesota Implan Group, Inc.
72

Appendix Table B.4:

Adjusted RPC and State Domestic Product Ratio for Selected 

Commodities

IMPLAN 

Code

Commodity SDP Ratio Modified RPC

1 Dairy Farm Products 0.7339 0.7000

13 Hay and Pasture 1.0000 1.0000

19 Sugar Crops 1.0000 1.0000

23 Greenhouse and Nursery Products 0.1895 0.0837

24 Forestry Products 1.0000 0.6000

38 Natural Gas & Crude Petroleum 0.5905 0.3200

39 Natural Gas Liquids 0.5919 0.3500

45 Chemical- Fertilizer Mineral Mining- N.E.C. 1.0000 0.5000

60 Poultry Processing 1.0000 0.3000

69 Pickles- Sauces- and Salad Dressings 1.0000 0.5000

74 Rice Milling 1.0000 0.3000

95 Bottled and Canned Soft Drinks & Water 1.0000 0.9000

98 Prepared Fresh Or Frozen Fish Or Seafood 1.0000 0.2000

99 Roasted Coffee 1.0000 0.6000

162 Paper Mills- Except Building Paper 1.0000 0.5000

163 Paperboard Mills 1.0000 0.7500

168 Bags- Paper 1.0000 0.5000

174 Newspapers 0.6738 0.6000

179 Commercial Printing 0.5567 0.5500

189 Inorganic Chemicals Nec. 1.0000 0.7000

191 Plastics Materials and Resins 1.0000 0.8000

192 Synthetic Rubber 1.0000 0.7000

204 Agricultural Chemicals- N.E.C 1.0000 0.5500

210 Petroleum Refining 1.0000 0.7500

213 Lubricating Oils and Greases 1.0000 0.7500

214 Petroleum and Coal Products- N.E.C. 1.0000 0.7500

220 Miscellaneous Plastics Products 0.4645 0.2000

243 Concrete Products- N.E.C 0.4925 0.4500

244 Ready-mixed Concrete 1.0000 1.0000

254 Blast Furnaces and Steel Mills 0.3177 0.1000

261 Primary Aluminum 1.0000 0.5000

265 Aluminum Rolling and Drawing 0.8766 0.2500

282 Fabricated Structural Metal 1.0000 0.5000

284 Fabricated Plate Work (Boiler Shops) 1.0000 0.2500

301 Industrial and Fluid Valves 1.0000 0.5000

303 Pipe- Valves- and Pipe Fittings 0.9400 0.5000

309 Farm Machinery and Equipment 0.6554 0.6000

313 Oil Field Machinery 0.6384 0.5500

354 Industrial Machines N.E.C. 1.0000 0.5000

369 Lighting Fixtures and Equipment 0.7930 0.5000

392 Ship Building and Repairing 1.0000 0.3000
73

 (Continued)

IMPLAN

Code

Commodity SDP Ratio Modified RPC

393 Boat Building and Repairing 1.0000 0.5000

441 Communications- Except Radio and TV 0.7137 0.6500

442 Radio and TV Broadcasting 0.9816 0.7500

456 Banking 0.7178 0.6000

457 Credit Agencies 0.7942 0.7500

460 Insurance Agents and Brokers 1.0000 0.9000

461 Owner-occupied Dwellings 0.6791 1.0000

467 Funeral Service and Crematories 1.0000 1.0000

482 Miscellaneous Repair Shops 1.0000 0.9000

488 Amusement and Recreation Services- N.E.C. 1.0000 0.9500

495 Elementary and Secondary Schools 0.9396 0.9000

496 Colleges- Universities- Schools 0.9550 0.9000

497 Other Educational Services 1.0000 0.9500

503 Business Associations 1.0000 0.7500

504 Labor and Civic Organizations 0.8816 0.7500

513 U.S. Postal Service 0.9885 0.9000

515 Other Federal Government Enterprises 1.0000 1.0000

Source: IMPLAN, Minnesota Implan Group, Inc.
74

Appendix Table B.5:

Onshore Allocation Ratios/Profile for LA1, LA2, LA3 in Gulf of Mexico

IMPLAN 

Sector

Description LA1 LA2 LA3

38 Oil & Gas Operations 0.0900 0.0600 0.1500

50 New Gas Utility Facilities 0.0500 0.1000 0.1000

53 Misc. Natural Resource Facility Construction 0.2300 0.1500 0.3000

56 Maintenance and Repair, Other Facilities 0.0400 0.0800 0.0900

57 Other Oil & Gas Field Services 0.2600 0.1200 0.1600

160 Office Furniture and Equipment 0.0000 0.0000 0.0800

178 Maps and Charts (Misc. Publishing) 0.0200 0.0600 0.1100

206 Explosives 0.0000 0.0000 0.0000

209 Chemicals, NEC 0.0400 0.1000 0.0400

210 Petroleum Fuels 0.0900 0.1600 0.0900

232 Hydraulic Cement 0.0000 0.0000 0.0000

258 Steel Pipe and Tubes 0.3100 0.0500 0.0700

284 Fabricated Plate Work 0.0600 0.0900 0.0500

290 Iron and Steel Forgings 0.0000 0.0000 0.0500

307 Turbines 0.0000 0.1000 0.2000

311 Construction Machinery & Equipment 0.0000 0.0600 0.1900

313 O&G Field Machinery & Equipment 0.2700 0.1800 0.2200

331 Special Industrial Machinery 0.0000 0.3800 0.5400

332 Pumps & Compressors 0.1700 0.2200 0.0900

354 Industrial Machines, NEC 0.0600 0.1000 0.0600

356 Switchgear 0.0000 0.0700 0.1100

374 Communication Equipment, NEC 0.0000 0.0000 0.2500

392 Shipbuilding and Ship Repair 0.0500 0.2400 0.1800

399 Transportation Equipment, NEC 0.0600 0.1100 0.0000

401 Lab Equipment 0.0000 0.0000 0.0000

403 Instrumentation 0.3900 0.2700 0.0800

435 Demurrage/Warehousing/Motor Freight 0.2100 0.0900 0.0900

436 Water Transport 0.1000 0.2500 0.2200

437 Air Transport 0.1100 0.1100 0.0800

441 Communications 0.0700 0.1100 0.1100

443 Electric Services 0.0600 0.1500 0.1200

444 Gas Production/Distribution 0.0800 0.0700 0.0500

445 Water Supply 0.0800 0.1200 0.0500

446 Waste Treatment/Disposal 0.0000 0.0000 0.0000

454 Eating/Drinking 0.2800 0.0800 0.4000

455 Misc. Retail 0.0600 0.1000 0.1500

459 Insurance 0.0700 0.1200 0.0900

462 Real Estate 0.0400 0.0800 0.1100

469 Advertisement 0.0600 0.0800 0.1500

470 Other Business Services 0.1100 0.0900 0.0600

473 Misc. Equipment Rental and Leasing 0.2200 0.1000 0.1000

490 Doctors & Veterinarian Services 0.0600 0.0900 0.1400

494 Legal Services 0.0700 0.1100 0.1900

506 Environmental/Engineering Services 0.1100 0.0800 0.0800

507 Acct/Misc. Business Services 0.0500 0.0900 0.1300

508 Management/Consulting Services 0.0400 0.0900 0.1100

509 Testing/Research Facilities 0.1400 0.1400 0.0500

 Source : IMPLAN, Minnesota Implan Group, Inc.
75

Appendix Table B.6:

Expenditure Allocation

Appendix Table B.6.1:

LA Model Exploratory Drilling Expenditure Distribution by Water 

Depth

IMPLAN

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+ All Depths

38 Oil & Gas Operations 0.6773 0.6741 0.7331 0.7322 0.7042

57 Other Oil & Gas Field 

Services

0.0343 0.0342 0.0292 0.0292 0.0317

210 Petroleum Fuels 0.0283 0.0283 0.0242 0.0241 0.0262

232 Hydraulic Cement 0.0669 0.0695 0.0580 0.0593 0.0634

258 Steel Pipe and Tubes 0.0619 0.0628 0.0441 0.0438 0.0531

403 Instrumentation 0.0408 0.0407 0.0346 0.0346 0.0377

436 Water Transport 0.0828 0.0827 0.0701 0.0701 0.0764

437 Air Transport 0.0078 0.0078 0.0066 0.0066 0.0072

Total: 1.0000 1.0000 1.0000 1.0000 1.0000

Appendix Table B.6.2:

LA Model Development Drilling Expenditure Distribution by Water 

Depth

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+ All Depths

38 Oil & Gas Operations 0.6534 0.5234 0.6419 0.6920 0.6277

57 Other Oil & Gas Field 

Services

0.0345 0.0211 0.0407 0.0335 0.0324

210 Petroleum Fuels 0.0275 0.0335 0.0305 0.0266 0.0295

232 Hydraulic Cement 0.0657 0.1187 0.0749 0.0641 0.0808

258 Steel Pipe and Tubes 0.0710 0.1553 0.0608 0.0515 0.0846

313 O&G Field Machinery 

& Equipment

0.0155 0.0152 0.0104 0.0095 0.0126

403 Instrumentation 0.0411 0.0422 0.0438 0.0382 0.0413

436 Water Transport 0.0836 0.0828 0.0887 0.0774 0.0831

437 Air Transport 0.0079 0.0078 0.0084 0.0073 0.0078

Total: 1.0000 1.0000 1.0000 1.0000 1.0000
76

Appendix Table B.6.3:

LA Model Production Drilling Expenditure Distribution by Water 

Depth

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+ All Depths

38 Oil & Gas Operations 0.2906 0.2727 0.2614 0.2513 0.2690

57 Other Oil & Gas Field 

Services

0.0716 0.0702 0.0702 0.0702 0.0705

258 Steel Pipe and Tubes 0.0356 0.0332 0.0317 0.0303 0.0327

313 O&G Field Machinery 

& Equipment

0.0485 0.0453 0.0432 0.0413 0.0446

403 Instrumentation 0.0276 0.0257 0.0245 0.0235 0.0253

436 Water Transport 0.3520 0.3287 0.3135 0.2999 0.3235

437 Air Transport 0.0531 0.0726 0.0758 0.0783 0.0700

454 Eating/Drinking 0.0364 0.0340 0.0324 0.0310 0.0334

459 Insurance 0.0764 0.1074 0.1368 0.1637 0.1211

Total: 1.0000 1.0000 1.0000 1.0000 1.0000
77

Appendix Table B.7:

Implan Exogenous Shock Vector by Water Depth and Activity, 

and LA Area Activity

Appendix Table B.7.1:

LA1: Exploratory Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 691,730 525,388 1,216,429 1,863,125

57 Other Oil & Gas Field 

Services

34,994 26,637 48,417 74,255

210 Petroleum Fuels 28,933 22,052 40,080 61,448

232 Hydraulic Cement 68,314 54,147 96,313 150,993

258 Steel Pipe and Tubes 63,181 48,907 73,233 111,408

403 Instrumentation 41,635 31,736 57,441 87,993

436 Water Transport 84,526 64,443 116,317 178,409

437 Air Transport 7,961 6,072 10,968 16,833

Total: 1,021,275 779,384 1,659,198 2,544,464

Appendix Table B.7.2:

LA1: Development Wells

($000)

IMPLAN 

Sector

Description Water 

Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 996,742 523,483 1,167,414 2,439,502 

57 Other Oil & Gas Field 

Services

 52,575 21,071 74,004 118,035 

210 Petroleum Fuels 41,894 33,492 55,457 93,924 

232 Hydraulic Cement 100,157 118,719 136,210 225,973 

258 Steel Pipe and Tubes 108,366 155,282 110,522 181,517 

313 O&G Field Machinery & 

Equipment

 23,566 15,238 18,897 33,375 

403 Instrumentation 62,694 42,227 79,559 134,572 

436 Water Transport 127,446 82,763 161,365 272,829 

437 Air Transport 12,012 7,798 15,204 25,707 

Total: 1,525,452 1,000,073 1,818,631 3,525,434 
78

Appendix Table B.7.3:

LA1: Production Wells

($000)

IMPLAN 

Sector

Description Water 

Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 20,441,559 20,207,687 20,088,158 19,887,889

57 Other Oil & Gas Field 

Services

5,035,185 5,202,146 5,392,425 5,555,373

258 Steel Pipe and Tubes 2,504,271 2,463,413 2,436,825 2,400,751

313 O&G Field Machinery 

& Equipment

3,409,248 3,353,624 3,317,429 3,268,318

403 Instrumentation 1,938,100 1,906,479 1,885,903 1,857,984

436 Water Transport 24,759,234 24,355,271 24,092,407 23,735,751

437 Air Transport 3,732,265 5,379,830 5,825,176 6,199,475

441 Communications 593,278 758,029 801,245 836,403

454 Eating/Drinking 2,558,454 2,516,711 2,489,549 2,452,694

459 Insurance 5,374,999 7,957,432 10,512,860 12,959,441

Total: 70,346,593 74,100,623 76,841,976 79,154,080

Appendix Table B.7.4:

LA2: Exploratory Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 461,153 350,258 810,953 1,242,083

57 Other Oil & Gas Field 

Services

23,330 17,758 32,278 49,503

210 Petroleum Fuels 19,288 14,701 26,720 40,965

232 Hydraulic Cement 45,543 36,098 64,209 100,662

258 Steel Pipe and Tubes 42,120 32,605 48,822 74,272

403 Instrumentation 27,757 21,158 38,294 58,662

436 Water Transport 56,351 42,962 77,545 118,939

437 Air Transport 5,308 4,048 7,312 11,222

Total: 680,850 519,589 1,106,132 1,696,310
79

Appendix Table B.7.5:

LA2: Development Wells

($000)

IMPLAN 

Sector

Description Water 

Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 664,495 348,988 778,276 1,626,335

57 Other Oil & Gas Field 

Services

35,050 14,047 49,336 78,690

210 Petroleum Fuels 27,929 22,328 36,971 62,616

232 Hydraulic Cement 66,772 79,146 90,807 150,649

258 Steel Pipe and Tubes 72,244 103,522 73,681 121,011

313 O&G Field Machinery 

& Equipment

15,710 10,159 12,598 22,250

403 Instrumentation 41,796 28,151 53,039 89,715

436 Water Transport 84,964 55,175 107,577 181,886

437 Air Transport 8,008 5,199 10,136 17,138

Total: 1,016,968 666,715 1,212,421 2,350,289

Appendix Table B.7.6:

LA2: Production Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 13,627,706 13,471,792 13,392,105 13,258,593

57 Other Oil & Gas Field 

Services

3,356,790 3,468,097 3,594,950 3,703,582

258 Steel Pipe and Tubes 1,669,514 1,642,275 1,624,550 1,600,501

313 O&G Field Machinery 

& Equipment

2,272,832 2,235,749 2,211,619 2,178,879

403 Instrumentation 1,292,067 1,270,986 1,257,268 1,238,656

436 Water Transport 16,506,156 16,236,848 16,061,605 15,823,834

437 Air Transport 2,488,176 3,586,553 3,883,451 4,132,983

441 Communications 395,519 505,353 534,163 557,602

454 Eating/Drinking 1,705,636 1,677,808 1,659,699 1,635,129

459 Insurance 3,583,332 5,304,955 7,008,573 8,639,627

Total: 46,897,729 49,400,415 51,227,984 52,769,386
80

Appendix Table B.7.7:

LA3: Exploratory Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 1,152,883 875,646 2,027,382 3,105,208

57 Other Oil & Gas Field 

Services

58,324 44,395 80,695 123,758

210 Petroleum Fuels 48,221 36,753 66,799 102,413

232 Hydraulic Cement 113,857 90,245 160,522 251,656

258 Steel Pipe and Tubes 105,301 81,512 122,055 185,680

403 Instrumentation 69,392 52,896 95,735 146,655

436 Water Transport 140,877 107,406 193,862 297,348

437 Air Transport 13,269 10,120 18,280 28,055

Total: 1,702,124 1,298,973 2,765,330 4,240,774

Appendix Table B.7.8:

LA3: Development Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 1,661,237 872,471 1,945,690 4,065,837

57 Other Oil & Gas Field 

Services

87,624 35,119 123,340 196,724

210 Petroleum Fuels 69,823 55,819 92,428 156,540

232 Hydraulic Cement 166,929 197,865 227,017 376,622

258 Steel Pipe and Tubes 180,610 258,804 184,203 302,529

313 O&G Field Machin. & 

Equipment

39,276 25,397 31,495 55,625

403 Instrumentation 104,489 70,379 132,598 224,286

436 Water Transport 212,411 137,939 268,942 454,716

437 Air Transport 20,021 12,997 25,340 42,844

Total: 2,542,420 1,666,788 3,031,052 5,875,723
81

Appendix Table B.7.9 :

LA3: Production Wells

($000)

IMPLAN 

Sector

Description Water Depth

0-60 m 60-200 m 200-900 m 900 m+

38 Oil & Gas Operations 34,069,265 33,679,479 33,480,263 33,146,482

57 Other Oil & Gas Field 

Services

8,391,975 8,670,244 8,987,374 9,258,956

258 Steel Pipe and Tubes 4,173,786 4,105,688 4,061,375 4,001,252

313 O&G Field Machinery 

& Equipment

5,682,080 5,589,373 5,529,048 5,447,197

403 Instrumentation 3,230,167 3,177,465 3,143,171 3,096,641

436 Water Transport 41,265,389 40,592,119 40,154,012 39,559,584

437 Air Transport 6,220,441 8,966,383 9,708,627 10,332,458

441 Communications 988,797 1,263,381 1,335,408 1,394,004

454 Eating/Drinking 4,264,090 4,194,519 4,149,248 4,087,824

459 Insurance 8,958,331 13,262,387 17,521,433 21,599,068

Total: 117,244,322 123,501,038 128,069,960 131,923,466
83

Appendix C:

Discussion of Input-Output Structure
85

Appendix C.1: The Basic Structure of Theoretical Input-Output Models

Let zij be noted as the sales of industry i to j. Assume an economy with n sectors, and let Xi 

be the total output (production) of sector i and Yi the total final demand for sector i’s

product, then 

 (1) Xi = zi1 + zi2 + zi3 + ....... + zii .....+ zin + Yi 

such that the z terms represent inter-industry sales by sector i , thus the right hand side of (1) 

is the sum of all sector i’s inter-industry sales and its sales to final demand. Also, the above 

equation represents the distribution of sector i’s output. For the entire economy, a system of

equations with the structure given above can be constructed. 

Value-added consists of returns to factors of production (labor and capital), and land as a

form of capital in some cases and indirect business taxes. Since not all local demand may be 

met by local production for all local activities, the I-O table also includes a trade row that

accounts for all imports into the region’s economy.

Given a Leontief production model, output to input relationship can be expressed such that

 (2) Xj = min[ z1j/a1j , z2j/a2j, ........, znj/anj] 

 Hence , the system of equation modeling the economy becomes

 (3) X1 = a11X1 + a12X2 +......+ a1iXi + .....+ a1nXn + Y1

 Xi = ai1X1 + ai2X2 +....+ aiiXi + ..... + ainXn + Yi

 Xn = an1X1 + an2X2 +....+ aniXi + ..... + annXn + Yi 

where aij is the intermediate requirements from sector i per unit of sector j, or I-O technical 

coefficients.

These equations serve to make explicit the interdependence of inter-industry flows on the

total outputs of each sector. Separate prices and quantity relationships are incorporated into

the accounts by letting Pi equal the price of output in sector i. Assume for now that there

are no exports and imports, the rows of the nominal input-output accounts can be written as 

(4) PiXi = PiXi + PiYi 
86

(5) aij = Xij/Xj 

The relationship between nominal intermediate flows to nominal output (expressed as ratios) 

is given by 

(6) Piaij /Pj = PiXi /PjXj 

Given a base-year, normalized units can be used where flows are in real units and all prices 

equal one. In this case, equation (5) and equation (6) above are equivalent. Dividing by the 

price and using the I-O coefficients, (4) above can be written as 

 (7) Xi = aijXj + Yi 

This is the material balance equation of the I-O model. In matrix notation, it is

 (8) X = AX +Y 

or, solving for X,

(9) X = (I-A)-1Y 

where, (I-A)-1 is the well known Leontief inverse. The most basic element in input-output 

analysis is estimating changes in output levels for particular sector(s) of an economy that is

required to achieve a final output (Hewings, 1985). Given exogenously specified final

demand, (yi) production requirements necessary to satisfy the demand can be estimated

using the Leontief inverse. That is,

(10) X = ( I-A )-1 Y 

Given final demand targets, the Leontief inverse (I-A)-1 allows for the estimation of the

implied targets for sectoral production. 

 
87

Appendix C.2: The Basic Structure of Theoretical SAM Models

Mathematically, an algebraic representation of SAM is essentially the same as an I-O. In

this case, the matrices and vectors are of higher dimensions since more variables are

considered and more issues may be analyzed. For example, the A-matrix may be expanded

to include households as producers and other institutions may be included as rows and

columns in highly disaggregated and explicit formulation (Holland and Wyeth, 1993;

Waters and Holland, 1996). 

Assume households, government revenue, and employments are treated as endogenous. 

Given this framework, various multipliers can be estimated. Hence, the total impact of a

policy change on the entire economy can be estimated. As an illustration, the result of

treating households endogenously is a partitioned SAM specified as follows:

 

Endogenous Institution

Value Added

Activities

O Y H

V O O

A O C

S -

ú

ú

ú

û

ù

ê

ê

ê

ë

é

= 

 

where: S is the matrix of SAM direct coefficients

A is the matrix of technical coefficients (analogous to the input-output coefficients), 

V is the matrix of value-added (VA) coefficients,

Y is the matrix of VA distribution coefficients,

C is the matrix of expenditure coefficients, and

H is the matrix of institutional and household distribution coefficients.

It is possible to represent demand and supply balance equations as 

 

 

 

ú

ú

ú

û

ù

ê

ê

ê

ë

é

+

ú

ú

ú

û

ù

ê

ê

ê

ë

é

=

ú

ú

ú

û

ù

ê

ê

ê

ë

é

ey

ev

ex

y

v

x

S

y

v

x

 

where: X is the vector of sector supply

V is the vector of value-added by categories

Y is the vector of household incomes

ex is the vector of exogenous commodity demand

ev is the vector of exogenous value-added, and 

ey is the vector of exogenous household incomes (Holland and Wyeth, 1993).

(11)

(12)
88

From (12), an (I-S) matrix can be constructed that when inverted is a matrix equation

showing the level of sectoral supply, value-added, and household income as a function of

exogenous variables or

 

ú

ú

ú

û

ù

ê

ê

ê

ë

é

= -

ú

ú

ú

û

ù

ê

ê

ê

ë

é

-

ey

ev

ex

(I S)

y

v

x

1

 

 

where (I - S)-1 represents the matrix of SAM inverse coefficients. Notice that (I - S)-1 is

similar to the (I - A)-1 in I-O models but now includes more endogenous accounts. Hence,

embodied in the matrix is the notion that the SAM provides a more complete flow in the

economy. The effect of a change in say agricultural output (i.e. changes in ex in equation 5) 

on the levels of sectoral supply, value-added, and household incomes can thus be examined. 

(13)
89

Appendix C.3: Common Accounts of an I-O or SAM Model

C.3.1 Expenditure (Column) Accounts: Expenditure accounts (read along a column in 

the tables) are payments made by the sector or institution represented in that column to

the receiving sectors or institution in the respective row. In the fixed-price models these

include payments made for intermediate goods and services by industries, payment made 

by industries to factors of production, payments to institutions such as households,

governments, or for investments. 

C.3.2 Production (Intermediate Demand) Accounts: Production accounts hold the

records of payments made by the industry in that column to other industries in the

corresponding row as inputs to its production to meet final demand in the economy

(Miller and Blair, 1985). The Louisiana models were based on the industry-by-industry 

format. The industry-by-industry format uses an industry-based technology approach,

which assumes that an industry has the same input structure, regardless of its output

product mix. 

C.3.3 Factors Expenditure Accounts: The traditional economic definition of factors of 

production includes land, labor and capital. In inter-industry models, capital and labor are 

designated as factors of production, with land included in the capital account. IMPLAN 

follows the conventional national accounts for the U.S. I-O table. Factor payments are

comprised of employee compensation (returns to labor), proprietary income (returns to

labor and capital), other property income (returns to capital), and indirect business taxes. 

Factor cost of each industry in the region, that is, wages and salaries, as well as benefits

such as health and life insurance, retirement payments, and non-cash items. Proprietary

income is made up of payments received by self-employed individuals as income. 

Hence, proprietary income is a return to both capital investment and labor by owneroperators. Other property income consists of payments individuals receive from rents,

royalties, and dividends and corporate profits, retained earnings, and depreciation by

corporations. Indirect business taxes (IBT) consist of excise and sales taxes paid by

individuals to businesses. That is, IBT are taxes that are imbedded (included) in prices. 

Factor account columns in the fixed price models represent factor expenditures in the

study period. Factor or value-added as expenditure accounts are absent in the Louisiana IO model, as is the case in most basic regional I-O models. In the SAM, these accounts

include expenditures made for factor income disbursements to institutions, taxes paid,

depreciation expenditures, and import expenditures for factor services or factor leakages

out of the region. 

 

C.3.4 Institutional Expenditure Accounts: Institutional expenditure accounts are

found only in the SAM, which represents one point of departure between I-O and SAM

based models. Institutions are defined to include households, government, investment

and savings accounts. In the Social Accounting Matrix, an institution category is often

included that serves as a bridge between factor accounts and households. The inclusion of 

specific institution accounts is justified on the grounds that households do not ordinarily

receive payment directly from factors. This particular formulation overcomes the familiar 
90

“brain-dead SAM” ordinarily constructed from social accounts of ready-made models

such as the IMPLAN. These SAMs are said to be brain-dead because there is no explicit 

correspondence between detailed sectoral value-added receipts by factors from industry

and the factor disbursement sub-matrix containing only aggregated allocations of factor

receipts by institutions (Sullivan, McCollum, and Alward, 1997). The Louisiana models

defined institutions to include labor, property, and enterprise institutions while also

explicitly designating the usual institutional categories of households, government, and

capital/savings accounts. Labor as an institution receives and disburses labor payments

to households (“owners” of labor); property as an institution receives and disburses land

income to landowners. The enterprise institution disburses capital income to owners of

capital in addition to accounting enterprise savings. 

C.3.5 Household Expenditure Accounts: Depending on the goals of a particular study, 

it is often convenient to group households in the region into two or more classes either

along income lines such as low, medium, and high income level groups, or along

functional lines such as urban and rural households. This study adopts the latest BEA

nine income classes, which is now standard in the latest IMPLAN SAMs. Household

expenditure accounts represent one of the final demand categories in both I-O and SAM

models. In the Louisiana I-O, these expenditures include personal consumption

expenditures on goods and services produced by the 27 industrial sectors, taxes paid by

households, household savings, and imports of goods and services by Louisiana

households. 

C.3.6 Federal Government Expenditure Accounts: The column values in these

accounts represent another category of final demand in the fixed price models. In the

IMPLAN framework, expenditures by the federal government in a region are divided into 

military and non-military purchases. In the Louisiana fixed-price models, these two

accounts are combined to form a single federal government expenditure account. In the

SAM, federal government expenditures include federal agencies’ purchase of goods and

services from the industrial sectors; transfers to institutions, households, and state/local

government; and imports purchases or income transfers out of the region. In the

Louisiana I-O, all the transfer accounts are absent. Thus, income transfers are not

explicitly mapped, which is a limitation in representing economic flows in a standard I-O 

model.

C.3.7 State/Local Government Expenditure Accounts: State and local government

expenditures in IMPLAN include purchases for educational and non-educational uses.

These categories are combined into a single state/local government purchases category in 

the Louisiana I-O and SAM models. The structure of these government accounts are

similar to the structure of the government account except that in the Louisiana I-O, unlike 

the Louisiana SAM, the state/local government accounts include savings and no intergovernmental transfers. 

C.3.8 Investment (Capital) Accounts: Capital (investment demand) accounts are also

part of the final demand categories in regional models. In IMPLAN, investment demand

accounts are defined to include inventory purchases and capital formation. For each

industry, inventory purchases are purchased commodities that are not used in the current
91

year production while capital formation are expenditures made on durable goods or

capital equipment. These two capital accounts categories are combined into a single

capital account in the Louisiana I-O and SAM models for the nine industrial sectors. 

C.3.9 Rest of the World (Trade) Expenditure Account: The rest of the world (ROW) 

account consists of exports out of the region and earned income received by regional

economic agents from out-of-the sources, such as dividend payments to residents from

outside of the state capital investments. In general, IMPLAN ROW expenditures consist

of foreign exports, which are the demand by regional consumers for goods and services

produced outside of the U.S., and domestic exports, which are the demands by regional

consumers for goods and services produced elsewhere in the U.S. These two accounts

are consolidated into a single export account in the Louisiana I-O and SAM models.

C.3.10 Receipts (Rows) Accounts: Revenue accounts (read across a row in the tables)

are income received (earned or transfers) by the sector or institution represented in that

row from the paying sector or institution in the respective column. In the fixed-price 

models these include income received for sales of intermediate goods and services to

industries, income received by factors as value-added from industries, income received

by institutions such as households, governments, or savings. 

C.3.11 Production (Intermediate Sales) Accounts: Intermediate sales accounts are the 

mirror image of the intermediate purchase accounts. In both the I-O and SAM models all 

purchases made by each of the nine industrial sectors from other regional sectors are sales 

revenues earned by the same nine sectors. Thus, the inter-industry matrix is always

square.

 

C.3.12 Value-Added Revenue Accounts: Value-added accounts show payments

(wages, interests, profits, and IBT) by industrial sector to the designated factors of

production. The value-added detail income received by designated categories of factors

from the nine industrial sectors as wages, taxes, interests, and profits. Value-added 

accounts are similar to the factor expenditure accounts. As indicated earlier, IMPLAN’s

four categories are realigned to follow economic theory and for consistency with the

goals of this study. 

C.3.13 Institutional Income Accounts: Institutional accounts are absent in the

Louisiana I-O but included in the SAM. Institutions in the Louisiana SAM received

payments from the corresponding factor categories. These accounts also receive transfer

payments from both federal and state/local governments.

C.3.14 Household Income Accounts: Except when models are closed with respect to

household income, explicit household income accounts are absent in I-O models. Hence, 

unlike the SAM, which maps income flows to expenditures in their entirety, the I-O 

shows only a partial mapping via the factor payments to labor. Because in an I-O table,

the flow of income to households and other institutions that is detailed in the institutional 

account in the SAM is missing, the multiplier estimate of an exogenous change in a

sector in the economy is different. In the I-O, the multiplier is usually restricted to the

inter-industry matrix (i.e. A-matrix). Thus, it is suggested that when, as is done in some
92

regional applications of I-O, households are endogenized, the result is a gross

overestimation of multiplier effects. This is because value-added is often used as a proxy

for household income in these studies and is a much larger figure than personal income in 

a SAM (Holland and Wyeth, 1993). On the other hand, the structure of the SAM as

constructed in this study allows for explicit mapping of household income from three

economic perspectives: value-added, non-household institutions, and households.

Therefore, the multiplier effects of an exogenous change in the SAM when closed with

respect to any or all of these perspectives, allows for both the open loop and close loop

effects5 often observed in the SAM. In the Louisiana SAM, payments received by each

household category include institutional income distribution, payments between the three

household income groups, government income transfers to households and enterprises,

and remittances from out of the region to households and governments. 

C.3.15 Federal Government Revenue Accounts: In most applications, a regional I-O 

does not include an explicit government income-receiving sector. A SAM includes a

government sector and also disaggregates it into each level of government. For I-O 

models with a government sector (Wolff and Howell, 1989), it is usually a single

consolidated account of all levels of government. In the Louisiana I-O, a single

consolidated government sector is used. The federal government sector in the SAM

receives income from businesses in the form of IBT, tax revenue from factor accounts,

corporate tax revenue, personal income tax revenue from household accounts, and out of

region remittances. For state/local government sector, a single consolidated government

account receives all income due to all levels of government in the SAM; revenue sources 

are similar to those of the federal government except that state/local government also

receives direct transfers from the federal government.

C.3.16 Capital (Savings) Account: Savings are usually treated as pure leakage in

regional I-O models and thus accounted for in the ROW account. Because of this

treatment of regional savings, a consolidated capital account is often constructed to

accommodate savings and ROW receipts. When capital income is also considered a pure 

leakage, the leakage account combines capital income, savings and ROW accounts

(Kraybill, 1994). The savings account is present in both the Louisiana I-O and the SAM

models. In the Louisiana I-O, the savings account includes household savings,

government savings, and net capital remittances from out of the region. In the Louisiana

SAM, these sources of savings are also present, but depreciation and retained earnings by

enterprises are now included. 

 

5Open loop multipliers describe the effects of an external shock that is transmitted to other blocks 

of the SAM matrix and end there, not been fed back to the sector where they originated. Close loop 

multipliers describe the effects that proceed outwards from the block in the SAM where they originated and 

then fed back to it (Holland and Wyeth, 1993).
93

C.3.17 Rest of the World (ROW) Account: The ROW account holds import of

industrial sector for production of local goods, household and government imports of

goods and services. It also includes income transfers out of the region by regional

economic agents such as remittances by Louisiana households living abroad or public

servants working abroad.