Study

Note

2007-02

Army SRB Program: Estimates of

Effects on Retention (Revised) and

Length of Reenlistment

Flora Tsui, Paul Hogan, Jeff Chandler,

Javier Espinosa

Lewin Group, Inc.

Patrick Mackin

SAG Corporation

Peter Greenston

U.S. Army Research Institute

United States Army Research Institute

for the Behavioral and Social Sciences

November 2006

Approved for public release; distribution is unlimited.

20070111113
U.S. Army Research Institute

for the Behavioral and Social Sciences

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Authorized and approved for distribution:

STANLEY M. HALPIN MICHELLE SAMS

Acting Technical Director Acting Director

Research accomplished under contract

for the Department of the Army

Human Resources Research Organization

Technical Review by

Daniel Houser, George Mason University

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4. TITLE AND SUBTITLE 5a. CONTRACT OR GRANT NUMBER

Army SRB Program: Estimates of Effects on Retention (Revised) and DASWO1-98-D-0047 (D.O. 0044)

Length of Reenlistment 5b. PROGRAM ELEMENT NUMBER

65803

6. AUTHOR(S) 5c. PROJECT NUMBER

Flora Tsui, Paul Hogan, Jeff Chandler, Javier Espinosa (Lewin Group, D730

Inc.), Patrick C. Mackin (SAG Corporation), and Peter M. Greenston 5d. TASK NUMBER

(U.S. Army Research Institute) 265

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14. ABSTRACT (Maximum 200 words):

In this study the effects of Selective Reenlistment Bonuses (SRBs) on Army reenlistments over the 1990-2000

period at Zones A, B, and C at three levels of occupational aggregation - all Army, career management field (CMF),

and military occupational specialty (MOS) - were re-estimated to explicitly control for the drawdown in the mid1990s as well as labor market conditions. In general, the results for Zone A at all levels of occupational aggregation

indicate that reenlistment bonuses have a positive and statistically significant effect on Zone A reenlistments. A

one-level increase in SRB at Zone A typically increases the reenlistment rate by 3 to 7 percentage points,

depending upon the occupation. The results for Zone B are also solid at both the CMF and MOS levels. Results for

Zone C, where reenlistment rates are typically very high, were reasonably solid but not quite as good as the Zone A

and B results. The results provide the Army with estimates of reenlistment responsiveness to bonus changes for all

three zones for all MOS.

We also estimated the effect of SRBs on the reenlisting Soldier's choice of length of reenlistment. Increases in

the SRB level not only increase reenlistments, but also increase the length of reenlistment. The length of

reenlistment effects were incorporated into the SRB Management System to better predict program costs and the

additional staff years of contracted service provided by the bonus program.

15. SUBJECT TERMS

Personnel, Retention, Compensation

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ABSTRACT OF PAAGES

16. REPORT 17. ABSTRACT 18. THIS PAGE Ellen Kinzer

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ii
Study Note 2007-02

Army SRB Program: Estimates of Effects on Retention

(Revised) and Length of Reenlistment

Flora Tsui, Paul Hogan,

Jeff Chandler, and Javier Espinosa

Lewin Group, Inc.

Patrick Mackin

SAG Corporation

Peter Greenston

U.S. Army Research Institute

Selection and Assignment Research Unit

Michael G. Rumsey, Chief

U.S. Army Research Institute for the Behavioral and Social Sciences

2511 Jefferson Davis Highway, Arlington, Virginia 22202-3926

November 2006

Army Project Number Personnel and Training

665803 Analysis Activities

Approved for public release; distribution is unlimited.

iii
iv
ARMY SRB PROGRAM: ESTIMATES OF EFFECTS ON RETENTION (REVISED) AND

LENGTH OF REENLISTMENT

EXECUTIVE SUMMARY

Research Requirement:

The Selective Reenlistment Bonus (SRB) program is the primary way the Army provides

financial reenlistment incentives that vary by occupational specialty. Under the SRB program,

the Army sets an SRB level (ranging from zero to eight) by military occupational specialty

(MOS) for Soldiers at a first reenlistment point (Zone A), second reenlistment point (Zone B),

and third reenlistment point (Zone C). The Soldier is then offered a cash bonus equal to the

award level multiplied by the member's monthly basic pay and by the number of years (between

3 and 6) that the member chooses to reenlist. For the period of analysis, half of the bonus was

paid to the member at the time of reenlistment, while the remaining half was paid in equal

anniversary payments over the term of reenlistment.

Efficient allocation of reenlistment bonuses requires the ability to estimate the effect that

the bonus will have on reenlistments in an occupational specialty. The purpose of the research

reported in this paper is to provide revised estimates of the effect of reenlistment bonuses (by

occupations and reenlistment zone) upon retention, and to examine the relationship between size

of bonus and contract length. The resulting parameter estimates are to be incorporated into the

Army's SRB Management System (HRC/EPMD/Force Alignment Division).

Procedure:

In the analysis of the effect of selective reenlistment bonuses on Army enlisted retention,

we modeled the decision as a rational choice by the Soldier to remain in the Army or to leave

based on the benefits and costs associated with the alternatives. We applied the Annualized Cost

of Leaving Model (ACOL) to estimate the financial incentive to stay. This model estimates the

financial incentive to stay as the difference in annualized military and civilian pay, computed

from the decision point to an optimal time horizon. The SRB was included in the ACOL

computation. The econometric model was estimated as a logistic regression.

The Army provided data on reenlistment decisions made in FY1990 through FY2000.

We received annual extracts of the Enlisted Master File (EMF) for September 1989 through

September 2000 and extracts of the Enlisted Loss File for the 11 fiscal years in the study. We

used these data to identify Soldiers eligible to make stay/leave decisions, characterize their

decisions, and generate explanatory variables for the estimation. We generated individual records

for each reenlistment decision observed in the analysis period.

Findings:

.We estimated the effects of SRBs on reenlistments at Zones A, B, and C at three levels of

occupational aggregation-all Army, career management field (CMF), and MOS. After out-ofv
sample testing indicated that the original (2002) model could be improved, we re-estimated the

model. In particular, the revised model explicitly controlled for the mid-I 990s drawdown period

and facilitated detection of labor market effects in the retention model estimation. In general, the

results for Zone A at all levels of occupational aggregation indicate that reenlistment bonuses

have a positive and statistically significant effect on Zone A reenlistments. The magnitude of the

effect varied by occupation, but a one-level increase in SRB at Zone A typically increases the

reenlistment rate by 3 - 7 percentage points, depending upon the occupation. The results for Zone

B are also solid at both the CMF and MOS levels. Results for Zone C, where reenlistment rates

are typically very high, were reasonably solid but not quite as good as the Zone A and B results.

We were unable to obtain positive, statistically significant ACOL parameter estimates for a small

number of CMF/MOS. The reason is probably the lack of variation in bonuses at this zone.

Nevertheless, we provided the Army with estimates for all three zones for all MOS. In the case

of Zone C, however, we sometimes relied on higher-level occupational aggregations to obtain

estimates.

In addition, we estimated the effect that SRB has on the reenlisting Soldier's choice of

length of reenlistment. We found the increase in the SRB level will not only increase

reenlistments, but also increase the length of reenlistment. The estimated effects of the bonus on

length of reenlistment were incorporated into the SRB Management System to better predict the

costs of the program, and to estimate the additional staff years of contracted service provided by

the bonus program.

Utilization and Dissemination of Findings:

These results will be used to update the embedded parameters in the SRB Management

System, which assists the Army plan and execute its SRB program. The SRB Management

System estimates the effects on reenlistments, and calculates the bonus costs, associated with

alternative plans.

vi
TABLE OF CONTENTS

In tro d u ctio n ..................................................................................................................................... 1

R eenlistm ent M odels ...................................................................................................................... 1

The Theory of Reenlistment Behavior ................................................................................ 1

Reenlistment Model Estimation Results ........................................................................ 2

Models of the Length of Reenlistment (LOR) ............................................................................. 8

D ata ..................................................................................................................................... 8

M o d els ................................................................................................................................. 8

Summary of the Estimation Results ............................................................................... 9

What Do These Models Predict? ............................................ .............. ........ .. .. .. ........ . . . 14

R eferen ces ..................................................................................................................................... 17

Appendix: ACOL Coefficients ................................................................................................. 19

List of Tables

Table 1. All-Army Results of the Reenlistment Model ............................................................ 3

Table 2. ACOL Coefficients of the Largest 19 CMF ................................................................. 4

Table 3. Effect of One-Level Increase in SRB, CMF Level ...................................................... 4

Table 4. ACOL Coefficients of the Largest 20 MOS ................................................................. 5

Table 5. Effect of One-Level Increase in SRB, MOS Level ..................................................... 5

Table 6. Summary Comparison of the ACOL Coefficients from the Revised Model and the

O rig in al M o d el ..................... I .................................................................................................. 6

Table 7. Prediction Residuals from the Revised Model and from the Original Model (Zone A

o n ly ) ........................................................................................................................................ 6

Table 8. Unemployment Coefficients of the Largest 19 CMF ................................................... 7

Table 9. Unemployment Coefficients of the Largest 20 MOS ................................................... 7

Table 10. Results from the OLS Regression Model of Length of Reenlistment (Dependent

Variable = Length of Reenlistment in Months) ............................................................... 10

Table 11. Results of the Heckman Model ..................................................................................... 11

Table 12a. Results from Multinomial Model (LOR=36 months) ............................................. 12

Table 12b. Results from Multinomial Model (LOR=60 months) ............................................. 13

Table 12c. Results from Multinomial Model (LOR=72 months) ............................................. 13

Table 13. Results from Ordered Logit Model ........................................................................... 14

Table 14. Probabilities of Each Choice Based on OLOGIT Estimates ................................... 14

List of Figures

Figure 1. Average length of reenlistment with different SRB level predicted by different

m o d els . .......................................................................................................................... 16

Figure 2. Average length of reenlistment with different percentage in lump sum payment

predicted by different m odels .................................................................................... 16

vii
viii
ARMY SRB PROGRAM: ESTIMATES OF EFFECTS ON RETENTION (REVISED) AND

LENGTH OF REENLISTMENT

Introduction

The U.S. Army Research Institute for the Behavioral and Social Sciences (ARI), together

with its contractor team of HumRRO, SAG Corporation, and the Lewin Group, has been

working with Human Resources Command to assist Selective Reenlistment Bonus (SRB)

managers in the management of the SRB program. Toward this end a web-based Army SRB

Management System has been designed and developed (Mackin and O'Brien, 2005). There are

two key components to the System. The first component is the mathematical modeling system

that incorporates the structure and logical relationships of the SRB program, databases and data

flow logic, and a user-friendly interface for planning and policy analysis. The second component

consists of quantitative estimates of the behavioral relationships between selective reenlistment

bonuses, contract length, reenlistments, and program costs. These estimated relationships provide

the empirical foundation of the SRB Management System.

The purpose of this paper is to present revised econometric estimates of the effects of

selective reenlistment bonuses on reenlistments, and new results for the effects on contract

length. Hogan et al. (2005) describes the original (2002) econometric estimates of the effect of

SRB on reenlistments. In addition, we analyze the effect of SRB and other factors on the choice

of contract length that, in addition to the decision to reenlist, is another important policy

consequence of the SRB program. Other things being equal, the Army would prefer Soldiers to

commit to reenlist for longer periods. Because the amount of reenlistment bonus a Soldier

receives increases with length of reenlistment, the SRB program provides an incentive for

Soldiers to reenlist for longer periods. We present estimates of the effect that various bonus

levels have on contract length using different econometric models. The selected model estimates

are incorporated as parameters into the SRB Management System itself, permitting more

accurate estimates of the cost of alternative SRB programs, and estimates of one dimension of

the benefits--contracted staff years.

Reenlistment Models

The Theory of Reenlistment Behavior

In the theory underlying the reenlistment model, the decision to reenlist is a rational

decision based on the benefits and costs associated with the alternatives. The most important

explanatory variable is the Annualized Cost of Leaving (ACOL) variable that represents the

maximum of annualized differences between military and civilian pay for each Soldier. In

addition, the model includes Soldiers' demographic characteristics including gender, race,

education, Armed Forces Qualification Test (AFQT) score, and marital status.

The data consist of individual observations of Soldiers at Zone A, B, and C reenlistment

points, by MOS, over the years FY1990 through FY2000. To improve the original model, we

added the national unemployment rate as well as dummy variables that control for the effect of

I
the armed forces drawdown (which occurred around 1992-1996.)' By controlling for the period

of the drawdown, during which Soldiers may have been encouraged not to reenlist, we were able

to estimate the effects of the economy on voluntary reenlistment decisions.

When the civilian job market is tight (characterized by a low unemployment rate) there

will be better civilian opportunities for Soldiers, inducing some to leave. Conversely, when the

civilian economy is weak (characterized by high unemployment rates) more Soldiers will choose

to reenlist. However, this relationship may have been obscured by the drawdown, during which

some Soldiers were encouraged not to reenlist. By controlling for this period, the relationship

between the reenlistment decision and the state of the economy could be estimated.

The rationale is that when the civilian economy was poor, more Soldiers would choose to

stay with the Army and sign up for reenlistment. On the other hand, the drawdown is similar to

downsizing, with the organization indicating that many employees are no longer as valued as

they once were. In the Army, this will have a negative effect on the number of voluntary

reenlistments, especially for those Soldiers that have reasonably attractive civilian alternatives.

Reenlistment Model Estimation Results

The estimation results of the revised model were noticeably improved compared to those

of the original model. With the inclusion of the drawdown dummy variables and the

unemployment rates, we obtained statistically significant and correctly signed coefficients for the

ACOL variables in a greater number of equations, and we also obtained significant results for the

unemployment rate in many cases. At the all-Army level, as Table 1 indicates, almost all

explanatory variables are significant in the equations for all three zones. These results appear to

be an improvement over the original model where the significance of the ACOL variable was

sensitive to the inclusion of demographic variables.

We calculated the responsiveness of the reenlistment rate to the change in SRB, based on

the following equation:

aR _ a R ACOL

aSRB -ACOL &SRB

where R is the reenlistment rate, SRB is the selective reenlistment bonus award level, and ACOL

is the annualized cost of leaving. Recall that, for a logit, aR

ACOL -R*(1-R)*B

Where R is the reenlistment rate evaluated at the mean and B is the ACOL coefficient.

'Controlling for the effects of the drawdown with dummy variables was necessary to estimate the effect of the

unemployment rate on reenlistments.

2
Table 1. All-Army Results of the Reenlistment Model

Zone A Zone B Zone C

Estimate SE Estimate SE Estimate SE

Intercept -2.2968*** 0.0734 -0.7931*** 0.082 3.5492*** 0.1243

ACOL 0.000361*** 0.000007537 0.000209*** 0.000006901 0.000075*** 0.000008343

Unemp. Rate 0.0299*** 0.00525 0.0145** 0.00689 -0.3517*** 0.0112

AFQT -0.00535*** 0.000157 -0.00047** 0.000229 -0.00392*** 0.000403

Female 0.2513*** 0.00845 0.00248 0.0126 -0.0283 0.0235

Non-white 0.5625*** 0.00618 0.3586*** 0.00915 0.2076*** 0.0166

Separated -0.07*** 0.0205 -0.1012*** 0.0189 -0.2035*** 0.0273

Single -0.495*** 0.00633 -0.1786*** 0.0102 -0.1632*** 0.0252

GED 0.508*** 0.0245 -0.2955*** 0.0335 -0.4353*** 0.0528

HS Grad 0.2323*** 0.0197 -0.1734*** 0.0277 -0.3202*** 0.0448

Non-HSG 0.4358*** 0.0332 -0.4694*** 0.068 -1.1724*** 0.1242

Some College 0.2329*** 0.0213 0.1819*** 0.0291 0.1957*** 0.0458

Post-drawdown 0.5818*** 0.0138 0.4245*** 0.0172 -0.4688*** 0.0292

Pre-drawdown 0.2318*** 0.012 0.8596*** 0.0155 0.5742*** 0.025

Percentage point

change in reenlistment 6.4 4.5 1.8

rate from a one-level

increase in SRB

**p <.05, *** p <.01

The responsiveness of reenlistment to SRBs at the all-Army level, as reported in the

bottom row of Table 1, is somewhat greater than the original estimate. The average effect of a

one-level increase in SRB in the all-Army model is to increase the first term reenlistment by

about 6.4 percentage points, the second term by about 4.4 percentage points, and the third term

by about 1.8 percentage points, calculated at the respective mean reenlistment rates. The results

for the unemployment rate and drawdown dummies are generally as expected. Higher

unemployment rates are associated with higher reenlistment rates. The reenlistment rate was

significantly lower at Zone A and Zone B during the drawdown period, though this was not the

case for Zone C. The effects of the demographic variables are similar to the original estimates for

Zone A. (Demographic variables were not included in the original estimates for Zone B or C.)

Women, non-whites, and married members have higher propensity to reenlist, while college

graduates have the lowest propensity to reenlist. However, the effect of education is different for

Zone B and Zone C, compared to Zone A, where college graduates and members with "some

college" are more likely to reenlist.

We also estimated the model and calculated SRB effects on the reenlistment rate at the

CMF level and the MOS level. Table 2 presents the estimates of the ACOL coefficient for the

largest 19 CMF, and Table 3 reports the effect of a one-unit increase in the SRB on reenlistment

rates. Similarly, Table 4 and Table 5 show the ACOL coefficients and one-unit SRB effects for

the largest 20 MOS, respectively. We omit the coefficient if the ACOL coefficient was negative.

Note that this occurred in very few cases.

Finally, we compare the new results with the original 2002 results in Table 6. The revised

results suggest significant improvement, compared to the original estimates, at both the CMF and

MOS level and across all zones.

3
Table 2. ACOL Coefficients of the Largest 19 CMF

Zone A Zone B Zone C

CMF Estimate SE Estimate SE Estimate SE

11 0.000397*** 0.00002 0.000302*** 0.000023 0.000128*** 0.000029

12 0.000247*** 0.00004 0.000224*** 0.000047 0.000108* 0.000059

13 0.000399*** 0.000026 0.000254*** 0.000028 0.000076** 0.000035

14 0.000197*** 0.000051 0.000196*** 0.000056

19 0.00051*** 0.00003 0.000253*** 0.000036 0.000129*** 0.000041

31 0.000305*** 0.000029 0.000183*** 0.000026 0.000088*** 0.00003

51 0.000374*** 0.000059 0.000193*** 0.000054 0.000095 0.0.0066

63 0.00027*** 0.000021 0.000172*** 0.00002 0.000053** 0.000026

67 0.000387*** 0.000064 0.000321*** 0.00003 0.000104** 0.000045

71 0.000448*** 0.000034 0.000109*** 0.000026

76 0.000644*** 0.000064 0.000277*** 0.00005 0.000035 0.000049

77 0.000124*** 0.000045 0.000243*** 0.000049

88 0.000239*** 0.000039 0.000196*** 0.000036

91 0.000458*** 0.00003 0.000154*** 0.000022 0.000079*** 0.000028

92 0.000178*** 0.000028 0.000178*** 0.000028 0.000043 0.000038

94 0.000688*** 0.000068 0.000258*** 0.000059 0.000186** 0.000072

95 0.000291 *** 0.000039 0.000206*** 0.000032 0.000136*** 0.000036

96 0.00017** 0.000067 0.000161*** 0.000054 0.000203*** 0.000059

98 0.00027*** 0.000059 0.000153*** 0.000054 0.000177*** 0.000054

*p <.10, **p <.05, ***p <.ol

Table 3. Effect of One-Level Increase in SRB, CMF Level

CMF Zone A Zone B Zone C

11 0.066410 0.064266 0.029539

12 0.041708 0.050370 0.024924

13 0.003961 0.056037 0.017539

14 0.033767 0.042633

19 0.085555 0.052423 0.029770

31 0.052871 0.040373 0.019709

51 0.064296 0.042579 0.021633

63 0.046996 0.037946 0.012231

67 0.067146 0.076370 0.019229

71 0.074034 0.024047

74 0.105396 0.061111 0.008077

77 0.021791 0.051067

88 0.041980 0.043241

91 0.080047 0.033718 0.029719

92 0.029131 0.039270 0.007105

94 0.119665 0.056919 0.041587

95 0.050578 0.045447 0.030218

96 0.029576 0.035226 0.044230

98 0.045653 0.036316 0.043657

4
Table 4. ACOL Coefficients of the Largest 20 MOS

Zone A Zone B Zone C

MOS Estimate SE Estimate SE Estimate SE

JIB 0.000387*** 0.000028 0.000302*** 0.000031 0.000171*** 0.00004

IIC 0.000306*** 0.000059 0.000296*** 0.000072

IIM 0.000415*** 0.000038 0.000269*** 0.000043 0.000095* 0.000056

12B 0.000215*** 0.000043 0.000205*** 0.000052 0.000084 0.000067

13B 0.000589*** 0.000036 0.00026*** 0.000039 0.00007 0.000049

19D 0.000678*** 0.000051 0.00023*** 0.000059 0.000124* 0.000073

19K 0.000419*** 0.000038 0.000292*** 0.000046 0.000093* 0.000052

31U 0.000274*** 0.000063 0,000209*** 0.000058 0.00016* 0.000086

52D 0.00026*** 0.000068 0.000124** 0.000059 0.000061 0.000086

54B 0.000364*** 0.000072 0.000222*** 0.000063 0.00001 0.000059

63B 0.000195*** 0.000042 0.000189*** 0.000041 0.00000003646 0.000048

71L 0.000463*** 0.000055 0.00009** 0.000042

76Y 0.000679*** 0.000107 0.000327*** 0.000083 0.00009 0.000075

77F 0.000108** 0.000047 0.00024*** 0.000053

88M 0.00024*** 0.000047 0.000201*** 0.000042

91B 0.000323*** 0.000041 0.000018 0.000039

92A 0.000198*** 0.000047 0.000229*** 0.000042

92Y 0.00023*** 0.000051 0.000158** 0.000066

94B 0.000697*** 0.000068 0.000261*** 0.000059 0.000185** 0.000072

95B 0.000253*** 0.000041 0.000196*** 0.000033 0.000108*** 0.00004

*p<. 10 ,**p<. 0 5 , ***p<.0 1

Table 5. Effect of One-Level Increase in SRB, MOS Level

MOS Zone A Zone B Zone C

IIB 0.064748 0.065294 0.029304

IIC 0.051022 0.061568

1IM 0.069357 0.058595 0.016742

12B 0.036598 0.045557 0.015686

13B 0.100719 0.054406 0.013071

19D 0.113579 0.047179 0.023155

19K 0.070678 0.060736 0.017366

31U 0.046976 0.043734 0.034515

52D 0.045198 0.025947 0.011391

54B 0.063700 0.042812 0.001867

63B 0.034125 0.039549 0.000007

71L 0.076102 0.018833

76Y 0.118651 0.068426 0.016806

77F 0.018900 0.050221

88M 0.041953 0.040961

91B 0.056525 0.003767

92A 0.033946 0.047919

92Y 0.048128 0.022906

94B 0.121975 0.054615 0.034546

95B 0.043826 0.041014 0.024341

5
Table 6. Summary Comparison of the ACOL Coefficients from the Revised Model and the

Original Model

Specification No. of results statistically significant and positive

CMF level MOS level

Zone A B C Zone A B C

Rev. Has unemployment rate& All 19 All 19 12 19 19 8

model drawdown year dummies

Orig. No unemployment rate or year 17 6 5 17 4 2

model dummies

We also predicted the reenlistment rate for each year group using estimates from the

revised model and estimates from the original model. Subtracting the predicted rates from the

actual rates (calculated using the same data) yields the residuals of the prediction. We did this for

Zone A because-while both models seem to have yielded reasonably good results for Zone Athe original model did not produce many useful results for Zone B and C. Hence, to the extent

that this experiment indicates the improvement of the revised model, this improvement is likely

to be greater were Zones B and C considered. Table 7 summarizes the residuals and indicates

that out of the 11 years, the revised model provided better predictions for 7 years while the

original model provided better predictions for 4 years. The revised model's performance is more

consistent over the years, as the range of the residual is much smaller (-6.7%, 5.3%) compared to

original model (-11.8%, 9%).

Table 7. Prediction Residuals from the Revised Model and from the Original Model (Zone A

only)

FY Actual reenlistment (%) Prediction (%) Residual (%)

Orig. model Rev. model Orig. model Rev. model

1990 39.0 41.8 40 2.8 1.0

1991 40.8 40.7 39.2 -0.1 -1.7

1992 36.4 45.4 41.7 9.0 5.3

1993 47.0 45.8 42.8 -0.5 -4.1

1994 48.9 49.6 46.6 0.7 -2.3

1995 45.5 49.5 46 4.0 0.4

1996 46.2 49.9 45.8 3.8 -0.4

1997 54.4 45.9 52.6 -8.6 -1.9

1998 53.3 41.5 46.6 -11.8 -6.7

1999 52.1 49.4 58.1 -2.7 6.0

2000 55.7 50.1 58.2 -5.5 2.5

The unemployment rate is an important variable in the revised model. We report the

estimated coefficients for the largest 19 CMF and 20 MOS in Table 8 and Table 9, respectively.

Again we omitted the coefficient if the unemployment coefficient was negative. Other estimation

results are available upon request.

6
Table 8. Unemployment Coefficients of the Largest 19 CMF

Zone A Zone B Zone C

CMF Estimate SE Estimate SE Estimate SE

11 0.0889*** 0.0138 0.0447** 0.0226

12 _

13

14 _

19 0.1065*** 0.0235

31 0.0406** 0.02 0.0292 0.025

51 _

63 0.0121 0.0149

67 0.3127*** 0.0316

71 0.0816*** 0.0236 0.0456* 0.0259

76 0.1621*** 0.0357

77 _

88 _

91 0.0151 0.0198 0.0724*** 0.0247

92 0.2554*** 0.0426 0.1065* 0.0559 0.139 0.1039

94 0.1439"** 0.0346

95 0.0204 0.0284 0.214*** 0.0313 0.0462 0.0535

96 0.1316** 0.0577

98 0.1546*** 0.041 0.0199 0.0523

*p <.10, **p< .05, ***p< .01

Table 9. Unemployment Coefficients of the Largest 20 MOS

Zone A Zone B Zone C

MOS Estimate SE Estimate SE Estimate SE

IIB 0.1323*** 0.0186 0.066** 0.0302

IIC 0.0217 0.0394 0.1719** 0.072

IiM 0.0788*** 0.0283

12B ___

13B 0.0281 0.0249 0.0627 0.0394

19D 0.1855*** 0.0392

19K 0.0748** 0.03

31U 0.2506*** 0.0836 0.3701** 0.1122 0.2889 0.2373

52D 0.0339 0.0456 _

54B _ _

63B 0.0102 0.0278 0.0204 0.0397

71L 0.2033*** 0.0381 0.1029** 0.0411

76Y 0.145** 0.0598 _

77F _

88M _

91B 0.00632 0.0446

92A 0.3552*** 0.0689 0.016 0.154-

92Y 0.2732*** 0.1019 0.3388* 0.187

94B 0.1482*** 0.0345 _

95B 0.0181 0.0293 0.2229*** 0.0331 0.0326 0.5806

7
Models of the Length of Reenlistment (LOR)

While the primary purpose of the SRB program is to induce Soldiers who otherwise

might leave to reenlist, it has a second benefit in that it induces those who reenlist to choose

longer reenlistment periods. It is important to be able to predict the contract length effect of

reenlistment bonuses both for better force planning and to provide a more precise estimate of the

cost of a given SRB program.2

Data

To estimate the length of reenlistment model, we used the FYI 990-2000 data set that was

constructed for the SRB study. We included the national unemployment rate published by BLS and

three dummy variables that represent pre-drawdown years (FY1990-1991), drawdown years (1992-

1996), and post-drawdown years (1997-2000). To expedite the model runs, we used a 20% random

sample containing 208,298 observations, of which 123,074 chose to reenlist.4

For estimating the length of reenlistment, we constructed several additional variables: the

SRB bonus for a 4-year contract (bonus4), the present value of the bonus, the real present value of

the bonus, and a set of dummy variables indicating if the SRBfirst reached the ceiling under a 3-, 4-,

5-, or 6-year contract.5 We used bonus4 as a proxy for the level of SRB bonus because the most

frequently chosen contract length is 4 years. We calculated "bonus4" based on each individual's pay

grade, years of service, and the SRB award level for which the Soldier is qualified in a given year.

When the SRB award level increases, the present value of the bonus over a 4-year contract increases.

It is the relationship between bonus value and length of reenlistment that we attempted to measure.

However, the highest value of bonus4 is $20,000 because that was the SRB ceiling for the period of

our analysis. That is, if the computed value of the bonus, based on grade, award level, and contract

length exceeds $20,000, we set the value equal to the ceiling value of $20,000. In the calculation of

the present value of SRB, we assumed an individual discount rate of 10% and discounted the annual

installment of SRB payments to the value at the beginning year.6 The real present value of SRB

further adjusted the present value by the consumer price index (CPI) to constant, 1990 dollars.

Models

There has been only one (unpublished) study on the length of reenlistment and SRB in

the literature. Warner and Goldberg (1984) estimated a linear regression model and a logit model

2 Recall that the bonus is equal to the product of (monthly) basic pay, bonus award level, and the length of

reenlistment (in years). 3 For data description and variable construction of the other variables, see Hogan et al. (2005).

"To ensure that the sampling did not introduce bias or reduce efficiency, we estimated several models with both the

entire data set and the sample. The results were very similar.

5 The Army has established a "ceiling" for the total bonus that can be paid that supersedes the value calculated from

the formula. The ceiling, however, is binding only in rare cases where there is a very high bonus award level. 6 Recall that the discount rate used in calculating the ACOL variable for the stay/leave decision was 16%. There is

no evidence on the appropriate discount rate to use in analyzing contract length choices. The 10% rate is used for

convenience. Because the observed choices of contract length are conditional on reenlisting, one would expect

that the average discount rate for those who reenlist is someone lower than the unconditional average. The reason

for this expectation is that those who choose to reenlist probably discount future retirement payments less than

those who do not choose to reenlist.

8
consisting of three log-odds equations.7 They found that LOR decisions are positively and

significantly related to bonus levels and to the form of the bonus payment. However, the results

from both the linear regression model and the multinomial model may be subject to bias because

they do not take into account the selection process (i.e., we only observe LOR for members who

chose to reenlist). There has been no other empirical research on this issue.8

We estimated four models that seem plausible for modeling the choice of LOR: (1) an

ordinary least square (OLS) regression model, (2) a Heckman selection model, (3) a maximumlikelihood multinomial logistic (mlogit) model, and (4) a maximum likelihood ordered logit

(ologit) model: 9

LOR =f(Bonus (real present value of the bonus under a 4-year contract), gender, AFQT,

race, education, marital status, military drawdown, reenlistment zone),

where the functional form,J( .... ), varies among the four models.

The unemployment rate and the ACOL variable are in the reenlistment model but not in

the LOR equation. ACOL is not in the LOR equation because we assume that once people decide

to reenlist after considering the annualized cost of leaving, it is the bonus itself that will largely

determine the length of reenlistment. We also assume that the state of the economy is not likely

to have a significant impact on the length of reenlistment. This is based on the presumption that

the contract length constrains the Soldier from leaving. The Soldier believes that he or she can

always extend a reenlistment or reenlist in the future. Hence, the Soldier prefers short contracts

to longer contracts, all else being equal. It is not assumed that the Soldier believes that the

contract length is a form of job security for which a longer contract is preferred to a shorter

contract.

Once an SRB amount reaches the Army's ceiling level-the maximum total amount it

will pay-the incentive for additional contract length is eliminated. To control for and estimate

the effect of SRB ceiling on LOR, we estimated the models with a set of dummy variables

indicating whether the SRB ceiling was binding under a 3-, 4-, 5-, or 6-year contract. However,

less than 1% of the observations ever reached the SRB ceiling. Because of this, we did not obtain

significant results for the "cap" dummies included in the models. Therefore, we proceeded with

the models without these dummy variables.

Summary of the Estimation Results

All four models yielded significant results for all our explanatory variables except for

some education dummy variables and AFQT in the Heckman model and MLOGIT model. The

directions of the effects of the explanatory variables are generally consistent across models. ' 0 To

7 The equations were similar to a multinomial logit.

8 One cannot reenlist for more than 72 months. Hence, the dependent variable is censored. We do not believe that

this significantly affects the results. Moreover, the discrete choice models do not suffer from this problem.

9 In the case of the Heckman model, this is the second step equation.

10 Note that the interpretation of the signs for results of MLOGI model is different from that under the other models.

See discussion in the sections on MLOGIT model for details.

9
demographic characteristics such as male, white, married, pre- and post-drawdown years, Zone

B, and Zone C. The only exceptions are "married" and "post-drawdown" in the Heckman model

and the drawdown variables in the MLOGIT model. In the Heckman model, "married" and

"post-drawdown" exhibit positive signs in the reenlistment equation, but have negative signs in

the LOR equation after having been adjusted for the selection effect. As for the drawdown

variables in the MLOGIT model, both the probability of contracts shorter than 48 months and the

probability of contracts longer than 48 months rise in pre-drawdown and post-drawdown years.

This counter-intuitive result is probably caused by an important property of the MLOGIT model

- it does not take into account the fact that the choices of LOR are rank-ordered. The following

subsections discuss each model's results in more detail.

The OLS Model

We started with this simple model that neglects certain econometric problems. However,

the results may still offer insight on the relationship between LOR and the explanatory variables.

The results also serve as a backdrop from which to compare results from the other, more

sophisticated models.

We summarize the OLS results in Table 10. According to Table 10, the bonus has a

significant and positive effect on the length of reenlistment. Females and non-whites, although

more likely to reenlist according to the reenlistment model, tend to reenlist for shorter terms. On

the other hand, those with lower AFQT scores and those who are married are more likely to both

reenlist and to reenlist for a longer time. Drawdown again has a negative impact on LOR.

Members in Zone A tend to commit for shorter reenlistment periods than their counterparts in

Zone B and Zone C.

Table 10. Results from the OLS Regression Model of Length of Reenlistment (Dependent

Variable = Length of Reenlistment in Months)

Independent variable Coefficient t-stat

Bonus 0.0014755*** 69.83

Female -2.026536*** -16.68

AFQT -0.0134057*** -5.70

Non-white -0.7380958*** -8.06

Non-high school graduate -0.5968151 -1.03

GED -0.4543827 -1.36

High school graduate -1.370816*** -4.98

Some college 0.5130197* 1.79

College graduate Omitted variable

Single/separated -1.250486* ** -13.76

Married Omitted variable

Pre-drawdown 5.262623*** 47.92

Post-drawdown 0.5271567*** 5.63

Drawdown Omitted variable

Zone B 2.827503*** 28.68

Zone C 8.912168*** 72.91

Zone A Omitted variable

Constant 39.85984*** 117.92

Adjusted R-squared 0.1079

10
Heckman Selection Model

We observe the reenlistment lengths only for those who reenlist. However, a higher

bonus award level will both increase the average length of reenlistment for those who would

have reenlisted at a lower SRB award level and induce additional reenlistments. The reenlistment

period chosen by the induced reenlistments may not be the same as that for those who would

have reenlisted anyway. Hence, imputing the length of reenlistment for those induced to reenlist

based on the reenlistment choices of those who would have reenlisted even without the bonus

increase may overstate the average effect of bonuses on reenlistment length.

To correct for this potential selection effect, we estimated a Heckman 2-step selection

model in which the first stage is a probit model of reenlistment such that:

Probability of reenlistment =f(ACOL, unemployment, gender, AFQT, race, education,

marital status, military drawdown, reenlistment zone).

The second equation is the OLS regression model for LOR as specified above. The

inverse Mills ratio, calculated from the first equation, is included as an explanatory variable in

the linear regression to control for selection. The inverse Mills ratio controls for selection

because it captures the omitted factors that affect contract length choice."I

We summarize the Heckman model results in Table 11. The bonus still has a significant

positive effect. The effect is slightly smaller than the OLS estimate, but is unchanged to a first

approximation.

Table 11. Results of the Heckman Model

LOR equation (2"d step) Reenlistment equation (Ist step)

Independent variable Coefficient z-stat Coefficient z-stat

Bonus 0.0014698*** 70.48

ACOL 0.0002992*** 81.78

Unemployment 0.0353769*** 7.46

Female -2.485818*** -19.09 0.1292082*** 14.35

AFQT -0.0008897 -0.35 -0.002509*** -15.25

Non-white -2.099457*** -17.50 0.2935858*** 44.73

Non-high school graduate 0.4425854 -0.73 -0.0370479 -0.96

GED -0.9045859*** -2.57 0.0963936*** 3.96

High school graduate -1.224573*** -4.23 -0.00087385 -0.44

Some college -0.0824854 -0.27 0.1444354*** 6.89

College graduate Omitted variable

Single/separated 0.6446092*** 4.66 -0.2611867*** -39.63

Married Omitted variable

Pre-drawdown 5.362511*** 46.58 0.3700707*** 40.22

Post-drawdown -0.2659317** -2.49 0.4033406*** 34.07

Drawdown Omitted variable

Zone B 1.868715*** 17.08

Zone C 6.26882*** 34.28

1 Selection bias in a linear regression is equivalent to omitted variable bias. The inclusion of the inverse Mills ratio,

calculated from the first equation, captures otherwise omitted factors that are correlated both with other

explanatory variables and contract length, reducing the potential bias in the explanatory variables.

11
LOR equation (2 d step) Reenlistment equation (Ilt step)

Independent variable Coefficient z-stat Coefficient z-stat

Zone A Omitted variable

Constant 45.39956*** 99.56 -1.812698*** -36.18

Inverse Mill's ratio -8.466624*** -19.14

p -0.55160

Prob > X 2 0.0000

Multinomial Logit Model

The multinomial procedure estimates the relative probabilities of multiple (more than

two) discrete choices or outcomes as a function of a set of independent variables. To be

parsimonious in the number of equations we have to estimate, we collapsed the lengths of

reenlistment into four choices (36, 48, 60, and 72 months) by rounding the LOR to the nearest of

these four choices. We set the most frequent choice, 48 months, as the base case and obtained the

results summarized in Table 12a (for the choice of 36 months), Table 12b (for the choice of 60

months), and Table 12c (for the choice of 72 months). These results show that, other things being

equal, as the bonus increases, the relative probability (or the relative risk ratio) of people

choosing a shorter term contract (36 vs. 48 months) decreases and the relative probabilities of

choosing a longer term contract (60 or 72 months vs. 48 months) increases. Longer reenlistment

terms are also associated with certain demographic factors. Other factors remaining constant,

members who are male, white, married, and have lower AFQT scores choose longer contract

lengths than others. Finally, those who are in Zones B or C tend to choose longer contract

lengths than those in Zone A.

Table 12a. Results from Multinomial Model (LOR=36 months)

Independent variable Coefficient z-stat

Bonus -.0001408*** -30.48

Female 0.1883301*** 8.45

AFQT 0.0035804*** 8.30

Non-white 0.0553763*** 3.31

Non-high school graduate -0.3189131 *** -2.99

GED 0.0795627 1.23

High school graduate 0.0327615 0.61

Some college -0. 1194836* -2.12

College graduate Omitted variable

Single 0.0736387*** 4.51

Married Omitted variable

Pre-drawdown 0.2160763*** 10.38

Post-drawdown 0.229404*** 13.45

Drawdown Omitted variable

Zone B -0.5186359*** -28.73

Zone C -0.8164958*** -34.57

Zone A Omitted variable

Constant 0.0074112 0.11

12
Table 12b. Results from Multinomial Model (LOR=60 months)

Independent variable Coefficient z-stat

Bonus 0.0001579*** 26.09

Female -0.1885473*** -3.44

AFQT -0.0002038 -0.22

Non-white -0.1118356*** -3.00

Non-high school graduate 0.1871566 0.91

GED 0.0776206 0.62

High school graduate -0.1207198 -1.13

Some college -0.2165567* -1.94

College graduate Omitted variable

Single -0.1095936*** -2.94

Married Omitted variable

Pre-drawdown 1.003847*** 24.21

Post-drawdown 0.4219925*** 10.65

Drawdown Omitted variable

Zone B 0.4153536*** 10.23

Zone C 0.653715*** 13.18

Zone A Omitted variable

Constant -2.782946*** -20.90

Table 12c. Results from Multinomial Model (LOR=72 months)

Independent variable Coefficient z-stat

Bonus 0.0001947*** 41.73

Female -0.263057*** -7.54

AFQT -0.0004527 -0.76

Non-white -0.1017128*** -4.25

Non-high school graduate -0.438795*** -2.73

GED -0.3143119*** -4.08

High school graduate -0.496712*** -7.88

Some college -0.2432595*** -3.75

College graduate Omitted variable

Single -0.2268228*** -8.91

Married Omitted variable

Pre-drawdown 1.436714*** 53.36

Post-drawdown 0.6427517*** 25.01

Drawdown

Zone B 1.235115*** 40.49

Zone C 2.149697*** 63.76

Zone A Omitted variable

Constant -2.319184*** -28.01

Pseudo R2 0.0846

Prob> >2 0.0000

Ordered Logit Model

The ordered logit model differs from MLOGIT in that it treats values of the dependent

variable as inherently rank-ordered while MLOGIT, motivated by a random utility model, treats

them as merely different choices or outcomes. In our case, OLOGIT seems more appropriate as

13
the length of reenlistment is ordered in length.' 2 Again we collapsed the lengths of reenlistment

into four choices (36, 48, 60, and 72 months) and set 48 months as the base case. Table 13

reports the estimation results including the "cut points" and Table 14 gives the probabilities of

each choice. From Table 13, we can see that bonus is positive significant. The same set of

demographic features that are associated with higher relative probability of longer LOR are also

associated with longer LOR in this model (i.e., male, white, lower AFQT, married, predrawdown, post-drawdown, Zone B, and Zone C).

Table 13. Results from Ordered Logit Model

Independent variable Coefficient z-stat

Bonus 0.0001933*** 62.20

Female -0.2728039*** -14.12

AFQT -0.0033216*** -9.25

Non-white -0.0895837*** -6.36

Non-high school graduate 0.0441664 0.50

GED -0.1897568*** -3.66

High school graduate -0.2912972*** -6.75

Some college -0.0834035* -1.86

College graduate Omitted variable

Single -0.1511815*** -10.78

Married Omitted variable

Pre-drawdown 0.6154351*** 36.77

Post-drawdown 0.0893996*** 6.16

Drawdown Omitted variable

Zone B 0.8469606*** 54.87

Zone C 1.655362*** 86.17

Zone A Omitted variable

Pseudo R2 0.0667

Prob > X2 0.0000

cut] -0.0925123

_cut2 1.906766

cut3 2.264168

Table 14. Probabilities of Each Choice Based on OLOGIT Estimates

LOR Probability Observed

36 Pr ( -oo < xb+u <_cut1) 0.4032

48 Pr (_cutl < xb+u <_cut2) 0.3963

60 Pr (_cut2< xb+u <_cut3) 0.0458

72 Pr (cut3<xb+u< +oo ) 0.1547

What Do These Models Predict?

Although comparing the level of significance and the signs of the estimated parameters

across the four models is straightforward, comparing the estimated magnitude of the effect is not.

The difficulty arises because the estimated coefficients from MLOGIT and OLOGIT models are

not the marginal effects. To compare effects across models, we could simply calculate the

12 Another desirable feature of OLOGIT is that, unlike the ordinary regression, assigning different values to

choices/ outcomes (e.g., 1, 5, 10, 15, instead of 1, 2, 3, 4) will not change the parameter estimates as long as it

preserves the rank order.

14
marginal effects of each parameter. However, it would be more useful for understanding if we

generate predictions for a common population for each model, under a variety of scenarios, and

compare the prediction results. For example, we could predict expected average LOR for a

common population with different levels of SRB or with different percentages of the SRB's

lump sum payment.

To facilitate comparison across models, we drew a representative group from our data

based on the frequency distribution of various personal characteristics. In most cases, we chose

the category that is the "mode" (i.e., that with the highest frequency). As a result, individuals

with the following characteristics are "representative": male, white, married, AFQT=57, highschool graduate, grade=E4, years of service (YOS)=4, in Zone A, and in FY 1996. Although

characteristics such as grade, YOS, and FY are not in the models, they are taken into account to

ensure that the "representative" cases obtain the same real present value of bonus with the same

LOR when we predict under different levels of SRB. When we predicted under different

percentages of lump sum payment, we had to specify SRB-award level to be used. The SRBaward level in this case is 0.5, and it is also the most frequent (modal) SRB.

We present the prediction results in Figure 1 and Figure 2. Figure 1 shows the predicted

average LOR under different SRB award levels by different models. We observe that the

predictions of all four models are very close and imply similar LOR effects with regard to the

SRB level. Although OLOGIT seems to consistently generate the largest effects, the differences

among the models are modest, 3.5 months at most. The Heckman selection model did seem to

adjust downward the predictions from OLS, presumably by accounting for the selection process.

But again, the difference in prediction is very small. One should also notice that all the

relationships dissipate after SRB level 4. That is because the bonus for our "representative" case

hits the ceiling of $20,000 at that level.

Figure 2 shows that the impact from changing the lump sum proportion of the payment is

relatively small and again that the models' predictions are similar. However the lump sum

payment effect depends on the assumption about the personal discount rate. If the personal

discount rate is greater than 10%, we would observe a greater effect on contract length. If a

higher discount rate were used, such as the 16% rate used in the calculation of the original

ACOL variables, one would expect the slope of the lines to be slightly greater. This is because

the future installments, to be received 4 or 5 years from the reenlistment decision, would be

discounted at a higher rate. Individuals, at the margin, would choose lower reenlistment contract

lengths to lessen this effect.

15
Figure 1. Average length of reenlistment with different SRB level predicted by different models.

5.5

5 -

45 _______________ 5-OLS "4.5 A Heckman

"0 4 X molgit

-* ologit

3.5 -

0 1 2 3 4 5 6

SRB level

Figure 2. Average length of reenlistment with different percentage in lump sum payment

predicted by different models.

5.

S4.5 

OL

"4 -- Heckman

0 ---- molgit

-.-. o logit

4 3.5 4 .L A A .

X X( X X -X

50% 60% 70% 80% 90%

Up front lump sum payment

A significant finding from comparing the models' prediction is that they all provide

similar, reasonable predictions. This, together with the earlier finding that all models yielded

significant and similar parameter estimates, suggest that the choice of which model to

incorporate into the Army's SRB Management System to predict contract length can be based on

which is the most convenient to code. No model appears to be significantly different from, or

superior to, the others. There are some theoretical defects in some of the models. For example,

OLS neglects the selection process and its associated effect. The Heckman model, on the other

hand, takes the selection effect into account but might be flawed in assuming that the relationship

between bonus and contract length is linear.

16
References

Hogan, P. F., Espinosa, J., Mackin, P., & Greenston, P. (2005). A Model ofArmy Reenlistment

Behavior: Estimates of the Effects ofArmy's Selective Reenlistment Bonus on Retention

by Occupation (Study Report 2005-02). Arlington, VA: U. S. Army Research Institute for

the Behavioral and Social Sciences.

Mackin, P., & O'Brien, K. (2005). Army Selective Reenlistment Bonus Management System:

Functional and User Documentation (Study Note 2005-04). Arlington, VA: U. S. Army

Research Institute for the Behavioral and Social Sciences.

Warner, J., & Goldberg, M. (1984, March). The Bonus Ceiling and the Length of Navy

Reenlistment Contracts. Unpublished manuscript.

17
18
Appendix: ACOL Coefficients

ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

00B 0.0003741 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

O0D 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

O0E 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

0OR 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

OOU 0.0004481 0.000109f 0.000075* 0.0816t 0.0456t 0.0000*

OOZ 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

01H 0.000458f 0.000154f 0.0000791 0.0299* 0.07241 0.0000*

02A 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02C 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02E 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02F 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02G 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02H 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02J 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02K 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02L 0.000361 * 0.000209* 0.000075* Q.0299* 0.0145* 0.0000*

02M 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02N 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02S 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02T 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02U 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

02Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09C 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09S 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09T 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

09W 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

11B 0.000387t 0.0003021 0.0001715 0.1323* 0.0660t 0.0000*

11C 0.000306f 0.0002961 0.000128t 0.08891 0.17191 0.0000*

11H 0.0003971 0.000302t 0.000128t 0.0889t 0.0447t 0.0000*

11M 0.000415t 0.0002691 0.000095$ 0.07881 0.0447t 0.0000*

lix 0.000397t 0.000302f 0.0001 281 0.0889f 0.0447t 0.0000*

11z 0.0003971 0.000302t 0.0001 281 0.08891 0.04471 0.0000*

12B 0.000215T 0.000205T 0.000108t 0.0299* 0.0145* 0.0000*

12C 0.0002471 0.0002241 0.0001081 0.0299* 0.0145* 0.0000*

12F 0.0002471 0.0002241 0.0001081 0.0299* 0.0145* 0.0000*

12Z 0.0002471 0.0002241 0.0001081 0.0299* 0.0145* 0.0000*

13B 0.0005891 0.0002601 0.0000761 0.0299* 0.0145* 0.0000*

13C 0.0003991 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

13D 0.0003991 0.0002541 0.000076t 0.0299* 0.0145* 0.0000*

13E 0.0003991 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

13F 0.0003991 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

13M 0.0003991 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

13N 0.0003991 0.000254t 0.0000761 0.0299* 0.0145* 0.0000*

13P 0.0003991 0.000254t 0.0000761 0.0299* 0.0145* 0.0000*

13R 0.0003991 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

19
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

13S 0.0003991 0.0002541 0.000076t 0.0299* 0.01 45* 0.0000*

13T 0.000399t 0.0002541 0.000076t 0.0299* 0.0145* 0.0000*

13W 0.000399t 0.000254f 0.000076t 0.0299* 0.0145* 0.0000*

13X 0.000399t 0.000254t 0.000076t 0.0299* 0.0145* 0.0000*

13Z 0.000399t 0.000254t 0.000076t 0.0299* 0.0145* 0.0000*

14D 0.0001 97t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

14E 0.000197t 0.000196f 0.000075* 0.0299* 0.0145* 0.0000*

14J 0.000197t 0.0001 96t 0.000075* 0.0299* 0.0145* 0.0000*

14L 0.000197t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

14M 0.0001 97t 0.000196t 0.000075* 0.0299* 0.01 45* 0.0000*

14R 0.000197t 0.0001 96t 0.000075* 0.0299* 0.0145* 0.0000*

14S 0.000197t 0.000196t 0.000075* 0.0299* 0.01 45* 0.0000*

14T 0.000197t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

14Z 0.000197t 0.0001 96t 0.000075* 0.0299* 0.0145* 0.0000*

15B 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15D 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15E 0.000399t 0.000254f 0.000076t 0.0299* 0.0145* 0.0000*

1SF 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15G 0.000361 * 0.000209* 0.QQQQ75* 0.0299* 0.0145* 0.0000*

15H 0.000361 * 0.000209* 0.000076* 0.0299* 0.0146* 0.0000*

15J 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15K 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15M 0.000361 * 0.000209* 0.00QQ75* 0.0299* 0.0145* 0.0000*

15N 0.000361 * 0.000209* QQQQQ075* 0.0299* 0.0145* 0.0000*

15P 0.000361 * 0.000209* 0.000075* 0.0299* 0.0146* 0.0000*

15Q 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15S 0,000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15T 0.000361 * 0.000209* 0.00007S* 0.0299* 0.0145* 0.0000*

15U 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15V 0.000361 * 0.000209* 0.00007S* 0.0299* 0.0145* 0.0000*

15SX 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

15Y 0.00361* 0.000209* 0.00007S* 0.0299* 0.0145* 0.0000*

15Z 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

16D 0.000197t 0.000196t 0.000075* 0.0299* 0.01 45* 0.0000*

16E 0.0001 97t 0.000196t 0.00007S* 0.0299* 0.014S* 0.0000*

16F 0.000197t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

16J 0.0001 97t 0.0001 96t 0.00007S* 0.0299* 0.0145* 0.0000*

16P 0.000197t 0.000196t 0.000075* 0.0299* 0.01 45* 0.0000*

16R 0.000197t 0.000196t 0.00007S* 0.0299* 0.014S* 0.0000*

16S 0.000197t 0.0001961 0.00007S* 0.0299* 0.014S* 0.0000*

16T 0.0001 971 0.0001 961 0.000075* 0.0299* 0.0145* 0.0000*

16X 0.0001 971 0.0001961 0.000075* 0.0299* 0.0145* 0.0000*

16Z 0.000197t 0.000196t 0.00007S* 0.0299* 0.0145* 0.0000*

17B 0.000399t 0.000254t 0.000076t 0.0299* 0.014S* 0.0000*

1 8B 0.000361 * 0.000209* 0.00007S* 0.0299* 0.0145* 0.0000*

180 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

18D 0.000361 * 0.000209* 0.00007S* 0.0299* 0.0145* 0.0000*

18E 0.000361 * 0.000209* 0.000076* 0.0299* 0.0146* 0.0000*

18F 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

18X 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

18Z 0.000361 * 0.000209* 0.000076* 0.0299* 0.0146* 0.0000*

19D 0.000678f 0.000230$ 0.0001 24T 0.1 855T 0.0145* 0.0000*

20
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

19E 0.00051lOt 0.000253t 0.000129t 0.1065t 0.0145* 0.0000*

19K 0.000419f 0.000292f 0.000093f 0.0748T 0.01 45* 0.0000*

19Z 0.000510Ot 0.000253t 0.0001 29t 0.1065t 0.0145* 0.0000*

21B 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

.210 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

21 D 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21E 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21F 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 G 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

21 H 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21J 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 K 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21L 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 M 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 N 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 P 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21Q 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21S 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

21 T 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 U 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21W 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

21 X 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21 Y 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

21Z 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

23R 0.000197t 0.0001 96t 0.000075* 0.0299* 0.01 45* 0.0000*

24C 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

24G 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

24H 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

24K 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

24M 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

24N 0.0001 97t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

24R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

24T 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

25B 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25C 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25D 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

2SF 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

25L 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

25M 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25P 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

25Q 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0146* 0.0000*

25S 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25T 0.000361 * 0.000209* 0.00007S* 0.0299* 0.01 45* 0.0000*

25U 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25V 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25W 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

25X 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25Y 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

25Z 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27B 0.000361 * 0.000209* 0.000075* 0.0299* 0.01 45* 0.0000*

21
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

27D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27E 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27F 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27G 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27H 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27J 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27K 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27L 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27M 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27N 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27X 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

27Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29E 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29F 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29J 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29M 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29N 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29P 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29S 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29W 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29X 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29Y 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

29Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

31B 0.000305t 0.000183f 0.000088t 0.0406t 0.0145* 0.0000*

31C 0.000305t 0.000183t 0.000088t 0.0406f 0.0145* 0.0000*

31D 0.000305t 0.000183t 0.000088f 0.0406t 0.0145* 0.0000*

31E 0.0003051 0.000183t 0.0000881 0.0406t 0.0145* 0.0000*

31F 0.0003051 0.000183t 0.0000881 0.0406t 0.0145* 0.0000*

31G 0.0003051 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

31K 0.000305t 0.000183f 0.000088t 0.0406t 0.0145* 0.0000*

31L 0.0003051 0.0001831 0.000088t 0.04061 0.0145* 0.0000*

31M 0.000305t 0.0001831 0.0000881 0.0406t 0.0145* 0.0000*

31N 0.0003051 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

31P 0.0003051 0.000183f 0.0000881 0.04061 0.0145* 0.0000*

31Q 0.000305t 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

31R 0.0003051 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

31S 0.0003051 0.000183f 0.0000881 0.0406t 0.0145* 0.0000*

31T 0.0003051 0.000183f 0.0000881 0.0406t 0.0145* 0.0000*

31U 0.000274f 0.0002091 0.000160t 0.2506t 0.3701f 0.0000*

31V 0.0003051 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

31W 0.0003051 0.000183t 0.0000881 0.0406t 0.0145* 0.0000*

31Y 0.0003051 0.000183t 0.0000881 0.0406t 0.0145* 0.0000*

31Z 0.0003051 0.0001831 0.0000881 0.0406t 0.0145* 0.0000*

33M 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33P 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33Q 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

22
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

33W 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33Y 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

33Z 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35A 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35C 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35E 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35F 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35G 0.000458f 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

35H 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35J 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35K 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35L 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35M 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35N 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35P 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35Q 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35R 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35S 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35U 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

35V 0.000361 * .0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35W 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35Y 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

35Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

36L 0.000305t 0.000183t 0.000088t 0.0406t 0.0145* 0.0000*

36M 0.000305t 0.000183t 0.000088t 0.0406t 0.0145* 0.0000*

37F 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

38A 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39B 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39C 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39E 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39G 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39L 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39W 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39X 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

39Y 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

41C 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

42A 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

42C 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

42D 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

42E 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

42F 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

42L 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

42R 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

42S 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

43E 0.000178t 0.000178t 0.000075* 0.2554t 0.1065t 0.0000*

43M 0.000178t 0.000178t 0.000075* 0.2554t 0.1065t 0.0000*

44B 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

44C 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

23
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

44E 0.000270f 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

45B 0.0002701 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

45D 0.000270f 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

45E 0.000270t 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

45G 0.000270t 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

45K 0.000270t 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

45L 0.0002701 0.000172f 0.000053t 0.0299* 0.0145* 0.0000*

45N 0.000270t 0.0001721 0.000053t 0.0299* 0.0145* 0.0000*

45T 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

45Z 0.0002701 0.000172t 0.0000531 0.0299* 0.0145* 0.0000*

46N 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

46Q 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

46R 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

46Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

51B 0.000374t 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

51G 0.000374t 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

51H 0.000374t 0.000193f 0.000075* 0.0299* 0.0145* 0.0000*

51 K 0.000374t 0.000193f 0.000075* 0.0299* 0.0145* 0.0000*

51 M 0.000374t 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

51R 0.000374t 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

51T 0.000374t 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

51Z 0.000374t 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

52C 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

52D 0.000260t 0.000124f 0.000053t 0.0299* 0.0145* 0.0000*

52E 0.000374t 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

52F 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

52G 0.000374t 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

52X 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

54B 0.000364f 0.000222$ 0.000075* 0.0299* 0.0145* 0.0000*

55B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

55D 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

55G 0.000361 * 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

55R 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

55X 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

55Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

56M 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

57E 0.0001781 0.000178t 0.000075* 0.2554f 0.10651 0.0000*

57F 0.000178t 0.0001781 0.000075* 0.25541 0.1065f 0.0000*

62B 0.000270t 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

62E 0.0003741 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

62F 0.0003741 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

62G 0.0003741 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

62H 0.0003741 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

62J 0.0003741 0.0001 931 0.000075* 0.0299* 0.0145* 0.0000*

62N 0.0003741 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

63A 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

63B 0.000195T 0.000189f 0.0000531 0.0299* 0.0145* 0.0000*

63D 0.0002701 0.0001 721 0.0000531 0.0299* 0.0145* 0.0000*

63E 0.0002701 0.0001721 0.000053t 0.0299* 0.0145* 0.0000*

63G 0.0002701 0.0001721 0.000053t 0.0299* 0.0145* 0.0000*

63H 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

63J 0.0002701 0.0001 721 0.000053t 0.0299* 0.0145* 0.0000*

63M 0.0002701 0.0001721 0.0000531 0.0299* 0.0145* 0.0000*

24
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

63N 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

63S 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

63T 0.000270f 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

63W 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

63X 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

63Y 0.000270t 0.000172f 0.000053f 0.0299* 0.0145* 0.0000*

63Z 0.000270t 0.000172t 0.000053t 0.0299* 0.0145* 0.0000*

67B 0.000387f 0.000321t 0.000104t 0.0299* 0.31271 0.0000*

67G 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67H 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67N 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67R 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67S 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67T 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67U 0.000387t 0.0003211 0.000104f 0.0299* 0.3127f 0.0000*

67V 0.000387f 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67X 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

67Y 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

67Z 0.000387f 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

68B 0.000387t 0.000321t 0.0001041 0.0299* 0.3127t 0.0000*

68D 0.000387t 0.0003211 0.0001041 0.0299* 0.3127t 0.0000*

68F 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

68G 0.000387t 0.000321t 0.000104f 0.0299* 0.3127t 0.0000*

68H 0.0003871 0.0003211 0.000104t 0.0299* 0.3127t 0.0000*

68J 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

68K 0.000387t 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

68L 0.000387t 0.0003211 0.0001041 0.0299* 0.3127t 0.0000*

68N 0.000387t 0.000321 0.0001041 0.0299* 0.3127f 0.0000*

68P 0.000387t 0.0003211 0.000104t 0.0299* 0.3127t 0.0000*

68Q 0.000387f 0.0003211 0.000104t 0.0299* 0.3127t 0.0000*

68R 0.000387f 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

68S 0.000387t 0.000321t 0.0001041 0.0299* 0.3127t 0.0000*

68X 0.000387t 0.000321f 0.000104t 0.0299* 0.3127t 0.0000*

68Y 0.000387f 0.000321t 0.000104t 0.0299* 0.3127t 0.0000*

71C 0.0004481 0.000109t 0.000075* 0.08161 0.0456f 0.0000*

71D 0.000448f 0.000109t 0.000075* 0.08161 0.0456t 0.0000*

71E 0.000448t 0.000109t 0.000075* 0.0816t 0.0456t 0.0000*

71G 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

71L 0.000463t 0.000090t 0.000075* 0.2033T 0.1029t 0.0000*

71M 0.000448t 0.0001091 0.000075* 0.0816t 0.0456t 0.0000*

72E 0.000305t 0.000183t 0.000088t 0.0406t 0.0145* 0.0000*

72G 0.0003051 0.0001831 0.000088t 0.0406t 0.0145* 0.0000*

73C 0.000448t 0.000109t 0.000075* 0.08161 0.0456t 0.0000*

73D 0.000448t 0.000109t 0.000075* 0.0816f 0.0456t 0.0000*

73Z 0.0004481 0.0001 09t 0.000075* 0.0816t 0.0456t 0.0000*

74B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

74C 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

74D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

74F 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

74G 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

74Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

75B 0.0004481 0.0001091 0.000075* 0.0816t 0.0456t 0.0000*

75C 0.000448t 0.0001 09t 0.000075* 0.0816t 0.0456t 0.0000"

25
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

75D 0.000448t 0.000109t 0.000075* 0.0816t 0.0456t 0.0000*

75E 0.000448t 0.000109t 0.000075* 0.0816t 0.0456t 0.0000*

75F 0.000448t 0.000109f 0.000075* 0.0816t 0.0456t 0.0000*

75H 0.000448t 0.000109t 0.000075* 0.08161 0.0456t 0.0000*

75Z 0.000448t 0.000109t 0.000075* 0.0816t 0.0456t 0.0000*

76C 0.000644t 0.0002771 0.000075* 0.1621t 0.0145* 0.0000*

76J 0.000458t 0.000154f 0.000079t 0.0299* 0.0724t 0.0000*

76P 0.000644t 0.0002771 0.000075* 0.1621t 0.0145* 0.0000*

76V 0.000644t 0.000277t 0.000075* 0.1621t 0.0145* 0.0000*

76X 0.000644t 0.000277t 0.000075* 0.1621f 0.0145* 0.0000*

76Y 0.000679f 0.000327t 0.000075* 0.1450f 0.0145* 0.0000*

76Z 0.000644t 0.000277t 0.000075* 0.1621t 0.0145* 0.0000*

77F 0.000108t 0.000240t 0.000075* 0.0299* 0.0145* 0.0000*

77L 0.000124f 0.000243t 0.000075* 0.0299* 0.0145* 0.0000*

77W 0.000124t 0.000243t 0.000075* 0.0299* 0.0145* 0.0000*

79D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

79R 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

79S 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

79T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

79V 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

81B 0.000374f 0.000193t 0.000075* 0.0299* 0.0145* 0.0000*

81C 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

81L 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

81Q 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

81T 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

81Z 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

82B 0.000374f 0.0001931 0.000075* 0.0299* 0.0145* 0.0000*

82C 0.000399t 0.000254t 0.000076f 0.0299* 0.0145* 0.0000*

82D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

83E 0.000361* 0,000209* 0.000075* 0.0299* 0.0145* 0.0000*

83F 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

88H 0.0002391 0.000196f 0.000075* 0.0299* 0.0145* 0.0000*

88K 0.000239t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

88L 0.0002391 0.000196f 0.000075* 0.0299* 0.0145* 0.0000*

88M 0.000240t 0.000201f 0.000075* 0.0299* 0.0145* 0.0000*

88N 0.0002391 0.000196f 0.000075* 0.0299* 0.0145* 0.0000*

88P 0.000239t 0.000196f 0.000075* 0.0299* 0.0145* 0.0000*

88Q 0.000239t 0.0001 96t 0.000075* 0.0299* 0.0145* 0.0000*

88R 0.000239t 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

88S 0.0002391 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

88T 0.0002391 0.0001961 0.000075* 0.0299* 0.0145* 0.0000*

88U 0.0002391 0.0001 96f 0.000075* 0.0299* 0.0145* 0.0000*

88V 0.0002391 0.000196t 0.000075* 0.0299* 0.0145* 0.0000*

88W 0.0002391 0.0001961 0.000075* 0.0299* 0.0145* 0.0000*

88X 0.000239f 0.0001 96f 0.000075* 0.0299* 0.0145* 0.0000*

88Y 0.000239t 0.0001 96f 0.000075* 0.0299* 0.0145* 0.0000*

88Z 0.000239t 0.0001961 0.000075* 0.0299* 0.0145* 0.0000*

89B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

89D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

91A 0.0004581 0.0001541 0.000079t 0.0299* 0.0724t 0.0000*

91B 0.000323T 0.000018f 0.0000791 0.0299* 0.0724t 0.0000*

91C 0.0004581 0.0001 54t 0.000079f 0.0299* 0.0724t 0.0000*

91D 0.000458t 0.000154t 0.0000791 0.0299* 0.0724t 0.0000*

26
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

91E 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91F 0.000458t 0.000154t 0.0000791 0.0299* 0.0724t 0.0000*

91G 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91H 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91J 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91K 0.0004581 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91L 0.0004581 0.0001541 0.000079t 0.0299* 0.0724t 0.0000*

91M 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91 N 0.000458t 0.0001 54t 0.000079t 0.0299* 0.0724t 0.0000*

91P 0.0004581 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91Q 0.000458t 0.000154t 0.0000791 0.0299* 0.0724t 0.0000*

91R 0.000458t 0.0001541 0.000079t 0.0299* 0.0724t 0.0000*

91S 0.000458t 0.000154f 0.000079t 0.0299* 0.0724t 0.0000*

91T 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91U 0.0004581 0.0001 54t 0.000079t 0.0299* 0.0724t 0.0000*

91V 0.000458t 0.0001 54t 0.000079t 0.0299* 0.0724t 0.0000*

91W 0.000458t 0.000154t 0.000079t 0.0299* 0.0724t 0.0000*

91X 0.0004581 0.000154t 0.000079f 0.0299* 0.0724t 0.0000*

91 Y 0.000458t 0.0001 54t 0.000079t 0.0299* 0.0724f 0.0000*

91Z 0.000458t 0.000154t 0.000079t 0.0299* 0.0724f 0.0000*

92A 0.000198t 0.0002291 0.000075* 0.3552t 0.1065t 0.0000*

92B 0.0004581 0.0001 54t 0.000079f 0.0299* 0.07241 0.0000*

92E 0.000458f 0.000154t 0.0000791 0.0299* 0.0724t 0.0000-

92F 0.000178t 0.0001781 0.000075* 0.2554t 0.1065t 0.0000*

92G 0.000178t 0.0001 78t 0.000075* 0.2554t 0.1065t 0.0000*

92L 0.000178t 0.0001 78t 0.000075* 0.2554t 0.1065t 0.0000*

92M 0.000178t 0.000178t 0.000075* 0.2554t 0.1065t 0.0000*

92R 0.000178t 0.000178t 0.000075* 0.2554t 0.1065t 0.0000*

92S 0.0001781 0.000178t 0.000075* 0.2554t 0.1065t 0.0000*

92W 0.0001781 0.0001781 0.000075* 0.2554t 0.1065t 0.0000*

92Y 0.0001 78t 0.000230t 0.000158f 0.2554t 0.2732t 0.3388t

92Z 0.000178t 0.000178t 0.000075* 0.2554t 0.1065f 0.0000*

93B 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

93C 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

93D 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

93F 0.000399f 0.0002541 0.0000761 0.0299* 0.0145* 0.0000*

93P 0.000361* 0.000209* 0.000075* 0.0299* 0.0145* 0.0000*

94A 0.000688f 0.0002581 0.0001861 0.1439f 0.0145* 0.0000*

94B 0.000697f 0.000261T 0.000185t 0.1482T 0.0145* 0.0000*

94D 0.000688t 0.000258t 0.0001861 0.1439f 0.0145* 0.0000*

94E 0.000688t 0.0002581 0.0001861 0.1439t 0.0145* 0.0000*

94F 0.000688t 0.0002581 0.0001861 0.1439t 0.0145* 0.0000*

94H 0.000688t 0.0002581 0.0001861 0.1439t 0.0145* 0.0000*

94K 0.0006881 0.0002581 0.0001861 0.1439t 0.0145* 0.0000*

94L 0.000688t 0.0002581 0.000186t 0.1439t 0.0145* 0.0000*

94M 0.0006881 0.0002581 0.0001861 0.1439f 0.0145* 0.0000*

94P 0.000688t 0.0002581 0.0001861 0.1439f 0.0145* 0.0000*

94R 0.000688t 0.000258t 0.0001861 0.1439f 0.0145* 0.0000*

94S 0.000688t 0.0002581 0.000186t .0.1439f 0.0145* 0.0000*

94T 0.000688t 0.000258t 0.0001861 0.1439f 0.0145* 0.0000*

94V 0.0006881 0.000258t 0.0001861 0.1439t 0.0145* 0.0000*

94W 0.000688t 0.000258t 0.000186t 0.1439t 0.0145* 0.0000*

94Y 0.0006881 0.000258t 0.000186t 0.1439t 0.0145* 0.0000*

27
ACOL Coefficients Unemployment Coefficients

Zone Zone

MOS A B C A B C

94Z 0.000688f 0.000258t 0.000186t 0.1439t 0.0145* 0.0000*

95B 0.000253f 0.000196f 0.0001084 0.0299* 0.2229f 0.0000*

95C 0.0002914 0.000206t 0.000136t 0.0299* 0.2140t 0.0000*

95D 0.0002914 0.000206f 0.000136t 0.0299* 0.2140t 0.0000*

96B 0.000170t 0.0001614 0.0002034 0.0299* 0.1316f 0.0000*

96D 0.000170t 0.000161t 0.000203f 0.0299* 0.1316f 0.0000*

96F 0.0001704 0.000161f 0.000203f 0.0299* 0.1316f 0.0000*

96H 0.000170f 0.0001614 0.000203t 0.0299* 0.1316t 0.0000*

96R 0.000170f 0.000161f 0.000203f 0.0299* 0.1316t 0.0000*

96U 0.000170f 0.000161t 0.0002034 0.0299* 0.1316t 0.0000*

96Z 0.0001704 0.000161t 0.0002034 0.0299* 0.1316t 0.0000*

97B 0.000170t 0.000161t 0.0002034 0.0299* 0.1316t 0.0000*

97E 0.0001704 0.000161t 0.000203t 0.0299* 0.1316t 0.0000*

97G 0.0001704 0.0001614 0.0002034 0.0299* 0.1316t 0.0000*

97L 0.0001704 0.0001614 0.0002034 0.0299* 0.1316t 0.0000*

97Z 0.0001704 0.0001614 0.0002034 0.0299* 0.1316t 0.0000*

98C 0.0002704 0.0001534 0.0001774 0.1546t 0.0145* 0.0000*

98D 0.0002704 0.0001534 0.0001774 0.1546t 0.0145* 0.0000*

98G 0.0002704 0.0001534 0.0001774 0.15464 0.0145* 0.0000*

98H 0.0002704 0.0001534 0.0001774 0.15464 0.0145* 0.0000*

98J 0.0002704 0.0001534 0.0001774 0.15464 0.0145* 0.0000*

98K 0.0002704 0.0001534 0.0001774 0.1546t 0.0145* 0.0000*

98P 0.0002704 0.0001534 0.000177f 0.1546t 0.0145* 0.0000*

98X 0.0002704 0.0001534 0.0001774 0.1546t 0.0145* 0.0000*

98Y 0.0002704 0.0001534 0.0001774 0.1546t 0.0145* 0.0000*

98Z 0.0002704 0.0001534 0.000177t 0.1546t 0.0145* 0.0000*

* Coefficient based on all-Army model

t Coefficient based on CMF-specific model

Coefficient based on MOS-specific model

28