Thomas and Kocher (1993) described the need for longitudinal research using survey and
personnel data. Over time, "leavers" and "stayers" could be tracked beyond their turnover
decision points to update personal, financial, and work-related data. In addition, research
comparing civilian to reserve turnover can shed light on individual differences between these
groups that may affect tumover. The research presented below focuses on a narrower set of
variables to address turnover intentions among Army reservists.

Demographics

Grissmer and Kirby (1985) found that age and the number of dependents negatively predicted
reenlistment decisions while marriage positively predicted reenlistment decisions. This suggests
that single reservists have higher retention rates than married reservists, but married reservists
with dependents have higher retention rates than single or married and childless reservists.
Results showed that higher retention rates were found among African-Americans and people
with some college education. Grissmer and Kirby (1985) stated that these results may reflect a
preference for reserve service among these groups or more uncertain civilian economic prospects
for African-Americans and less educated people. Phillips et al. (1992) stated that minorities are
more likely to remain in the Army than whites. For example, African- Americans reenlist after
their first term at about a rate of 50 percent higher than whites.

Attitudes

Lakhani and Fugita (1993) used a sociological theory to explain how spouse attitudes toward
reserve participation affected reserve reenlistment. Results showed that family earnings as well
as a spouses’ favorable attitude toward the reservists’ career plans increased the probability of
reenlistment. Lakhani (1995) found that spouses’ favorable attitude toward reenlistment was
positively related to reservists' reenlistment decision. Reservists’ satisfaction with military life
and job satisfaction were also positively associated with the probability of reenlisting. Lakhani
(1995) suggested that attitudinal and affective variables enter the reenlistment decision making
process, and economists should include these variables in analyses on retention intentions.

Military Experience

Reserve retention rates also show strong dependence on military experience variables.
Grissmer and Kirby (1985) reported that higher pay grades positively predicted retention rates.
In addition, reservists in noncombat jobs were more likely to reenlist at higher rates than those in
combat jobs. Holding risk constant, it may be that the skills acquired in combat jobs cannot be
easily transferred to civilian jobs.

Burright, Grissmer, and Doering (1982) advanced research on reserve retention by including
reserve-specific variables in their analysis. They concluded that variables such as prior active
military service, pay grade, civilian employer's attitude toward the reserves, and prior
reenlistment in the reserves had a positive and significant effect on reenlistment. In contrast,
years of service and assignment to a combat position were negatively related to reenlistment.

10



Table 31

Descriptive Statistics of Variables Used in Regression Equations

Variables N

M

Std.
Dev.

Minimum

Maximum

Dependent

Intent to Stay,
Training 433

Intent to Stay,
Deployment 330

Independent

Financial

Gain/Loss,

Training 357
$/month

Financial

Gain/Loss, 320
Deployment

$/month

Army 363
Satisfaction

Basic 328
Monthly Pay

Education* 481

2.25

1.83

174.74

97.50

3.23

1,442.08

4.23

0.56

0.70

1,024.72

362.56

1.15

514.61

2.11

1.0

1.0

-3,666.7

-750.0

1.0

957.6

1.0

3.0

3.0

3900.0

750.0

5.0

4,313.1

10.0

* J=some high school, no diploma; 10=graduate or professional degree.

31



Table 25

Home Ownership and Marital Status of AC and RC during Training

AC RC
Response Freq. % Freq. %
Do you own a home?
Yes 26 29.2 57 15.6
No 63 70.8 309 84.4
Total (N) 89 100.0 366 =: 100.0

Are you currently married?

Yes 52 58.4 101 27.7
No 33 37.1 249 68.2
Yes, Separated 4 45 15 41
Total (N) 89 100.0 365 100.0
Table 26

Self-Reported Impact of Volunteering by AC and RC on Army Career Intentions during Training

AC RC

Change in Career

Intentions Freq. % Freq. = %
Increased 11 12.2 117 31.8
Decreased 10 11.1 14 3.8
Unchanged 61 67.8 194 52.7
Don't Know 8 8.9 43 11.7
Total (N) 90 100.0 368 100.0

Comparative Statistics between Training and Deployment Phases

Economic variables. Table 27 shows that the summed average financial gain of all soldiers
(AC and RC) was greater during the training phase than corresponding gains during the
deployment phase ($599.45/month vs. $319.91/month). This table also shows that AC soldiers
were net losers (by $102.31/month) for the overall mission because they gained $147.09 ($45.40
+ $101.69) during the training phase, but lost $249.40 ($200.29 vs. $49.11) during the
deployment phase. On the other hand, RC soldiers were net gainers (by $335.68/month) during

27



where
RRSS = restricted residual sum of squares obtained from a pooled regression of the

entire data;
URSS = unrestricted residual sum of squares obtained from sub-samples of AC and RC
data;

k = number of predictors;
nl = sample size of subset 1; and
n2 = sample size of subset 2.

To obtain RRSS, we estimated the overall model, excluding the force component variable.
By dropping the force component variable, the sample size and regression coefficients in the re-
estimated pooled regression changed slightly from the original model. RRSS constrains the
parameters to be the same for the AC and RC. URSS allows the parameters to differ across the
sub-samples.

Results for the test of stability are reported in Table 6. Using the training phase data, we find
that the regression coefficients for the two sub-samples (RC and AC) are significantly different
from each other. Therefore, we conclude that the behavioral patterns of these two soldier groups
are significantly different during the training phase and should be treated separately for the
analysis. Using the deployment phase data, we find that the regression coefficients for the two
sub-samples are stable. Therefore, we fail to reject the hypothesis that the coefficients are equal.
This finding is compatible with results of the overall model reported earlier. The AC and RC
soldiers behavioral responses that were related to reenlistment intentions were similar during the
deployment phase. In view of this stability, we conclude that it is reasonable to combine these
two samples to infer their behavioral responses.

In summary, our analysis of equality of regression coefficients revealed that the Ac and RC
soldiers were different groups during the training phase, but the were not significantly different
during the more critical deployment phase. Therefore, we conclude that one can consider the
pooled data analysis for deployment phase to be representative of the sub-groups of soldiers.

Conclusions and future research on career commitment and earnings. The model explained
variance in career intentions during the training phase (R2=.125, p < .05) and the deployment
phase (R2=.153, p <.05). However, we are less interested in the total variance explained because
we did not have a complete model with several other relevant variables. Other variables could
explain greater variance in career commitment, but were not included in the study because we did
not have the required data. We are specifically interested in the regression coefficients of
existing variables used in the model.

The preceding results indicate that the financial gains perceived by the soldiers were directly
related to the career intentions of the soldiers to stay in the Reserve or the Active component
until their retirement. This result was confirmed for both the training phase and the deployment
phases. In addition, during the deployment phase, satisfaction with Army life predicted career
intention above and beyond the effect of financial gain. This result indicates that Army
commitment can also be increased by non-financial means such as job or family satisfaction.

36



and earnings (Matthews, 1995). Francis (1992) reported that reservists deployed in Operation
Desert Storm lost civilian income, health, and other benefits, as well as facing reduced
promotional opportunities in civilian occupations. As a result, more soldiers planned to leave the
Amy after their return (26%) than when they joined (18%) (Lakhani, 1995).

The required growth of the reserve force to adequately support the active force component can
be maintained by increasing reenlistment of reservists. However, retention can be problematic
because the overall annual attrition rate in reserve services is 25% (Lakhani, 1995). Wong,
Bliese, and Halverson (1995) examined the effects of multiple deployments on soldier well-being
and on soldier retention intentions using hierarchical regression. Survey responses were analyzed
using a sub-sample of 911 AC junior enlisted soldiers in infantry units deployed to Haiti. Data
were collected in November and December, 1994. Independent variables were multiple
deployments (i.e., Persian Gulf, Somalia, Grenada, Florida-Hurricane Andrew, Panama, forest
fire fighting, or Vietnam) and marital status. Results showed that marital status was not
significantly related to positive retention intentions, but multiple deployments were negatively
related to retention intentions. There was also a significant interaction between marital status,
previous deployments, and retention intentions. Single soldiers with previous deployments were
less likely to remain in the Army. Previous deployments were not significantly related to
retention intentions for married soldiers. These findings illustrate the Army's concern about the
impact of "activated" reservists on future reenlistment intentions.

Our research addresses some of the Army's concerns regarding deployment of reserve forces.
In this paper, we assess the economic impact on reservists being deployed to active duty missions
compared to the impact on their active-duty counterparts. Both groups were deployed to the
same mission. The second focus of our research is to determine how demographic and economic
variables affect Army career intentions. We draw on the economic and military literatures to
provide an overview of current research.

Veteran Status and Civilian Earnings

Our research targets reservist soldiers in peacekeeping operations. While most research
investigates the macro-economics of peacekeeping, we are interested in micro-economic effects
such as financial gains or losses due to deployment. Little economic research is drawn from
reservist samples to specifically address our research questions. Instead, these studies tend to
compare Army veterans to non-veterans.

Each year, thousands of young men enlist in the Armed Forces and most are discharged after a
few years and re-enter the civilian labor force (Bryant et al., 1993). A body of literature has
developed suggesting that military service positively influences civilian socioeconomic patterns.
The general hypothesis is that civilian earnings of military veterans are affected by military
experience, military training, and many social, economic, and demographic variables.



Sandler, T., & Hartley, K. (1995). Military manpower. In The economics of defense (pp. 153-
176). New York: Cambridge University Press.

Schroyer, C. J., Hansen, L. A., & Benedict, M. E. (1990). The 1990 ARI survey of employers:
Technical manual/codebook (ARI Research Product 91-04). Alexandria, VA: U.S. Army
Research Institute for the Behavioral and Social Sciences. (AD A231 740)

Schwartz, S. (1986). The relative earnings of Vietnam and Korean-era veterans. Industrial and
Labor Relations Review, 39, 564-572.

Segal, D. R., Segal, M. W., & Eyre, D. P. (1992). The social construction of peacekeeping in
America. Sociological Forum, 7, 121-135.

Sticht, T. G., Armstrong, W. B., Hickey, D. T., & Caylor, J. S. (1987). Cast-off youth: Policy and
training methods from the military experience. New York: Praeger.

Thomas, G. W., & Kocher, K. M. (1993). Gender differences in turnover among U.S. Army
reservists. Defence Economics, 4, 339-352.

U.S. Department of the State. (1995). Annual report to Congress on the activities of the
Multinational Force and Observers, 1994-1995. Washington, DC: Author.

U.S. General Accounting Office. (1991, April). Reserve components: Factors related to personnel
attrition in the selected reserve. Washington, DC: Author.

U.S. General Accounting Office. (1995a). Peacekeeping--Assessment of U.S. participation in the
Multinational Force and Observers (Report GAO/NSIAD-95-113, August). Washington,
DC: Author.

U.S. General Accounting Office. (1995b). Peace operations--DOD’s incremental costs and
funding for fiscal year 1994 (Report GAO/NSIAD-95-119BR). Washington, DC: Author.

U.S. Joint Chiefs of Staff. (1995). National military strategy of the United States of America,
1995--A strategy of flexible and selective engagement. Washington, DC: U.S.
Government Printing Office.

Villamez, W. J., & Kasarda, J. D. (1976). Veteran status and socioeconomic attainment. Armed
Forces & Society, 2, 407-420.

Welch, F. (1979). Effects of cohort size on earnings: The baby boom babies’ financial bust.
Journal of Political Economy, 87, $65-98.

46



Fligstein, C. R. (1976). The G.I. Bill: Its effects on the educational and occupational attainment of
US. males 1940-1973 (Working Paper 76-9). Madison, WI: Center for Demography and
Ecology.

Francis, B. D. (1992). Effects of mobilization on employment, income, and education. In B. C.
Harris, T. W. Elig, & L. W. Oliver (Eds.), 1991 survey of mobilized reservists: Attitudes
and experiences during Operation Desert Storm (ARI Research Report 1623). Alexandria,
VA: U.S. Army Research Institute for the Behavioral and Social Sciences. (AD A255
201)

Freeman, R. (1979). The effects of demographic factors on age-earnings profiles. Journal of
Human Resources, 14, 289-318.

Gade, P. A., Lakhani, H., & Kimmel, K. (1991). Military service: A good place to start? Military
Psychology. 3(4), 251-267.

Goldberg, M. S., & Warner, J. T. (1987). Military experience, civilian experience, and the
earnings of veterans. Journal of Human Resources, 22, 62-81.

Graham, B. (1995, March 9). Responsibilities of U.S. military expanded. The Washington Post,
p. A36.

Greene, W. H. (1993). Econometric analysis. New York: MacMillan.

Grissmer, D. W., & Kirby, S. N. (1985). Attrition and retention in the Army Reserve and National
Guard: An empirical analysis. In C. L. Gilroy (Ed.), Army manpower economics (pp. 169-
197). Boulder, CO: Westview.

Johnson, W. R. (1980). Vintage effects in the earnings of White American men. Review of
Economics and Statistics, 62, 399-407.

Lakhani, H. (1995). Reenlistment intentions of citizen soldiers in the U.S. Army. Armed Forces
and Society, 22, 117-130.

Lakhani, H., & Fugita, S. S. (1993). Reserve/guard retention: Moonlighting or patriotism?
Military Psychology, 5, 113-125.

Laurence, J. H., & Ramsberger, P. G. (1990, June). Long-term effects of military service on low-
aptitude recruits. Paper presented at the 65th Annual Western Economic Association
International Conference, San Diego, CA.

Little, R. D., & Fredland, J. E. (1979). Veteran status, earnings, and race. Armed Forces &
Society, 5, 244-260.

44



¢ RC soldiers reported greater career commitment than AC soldiers during the
training phase, but no significant difference was found between these groups
during the deployment phase.

© Career commitment for both AC and RC was enhanced significantly (p < .05)
by financial gains and satisfaction with Army life.

¢ The financial gains of RC soldiers were reduced significantly by losses to their
civilian earnings.

© The control group of non-volunteers had higher individual and family earnings
than corresponding earnings of RC volunteers.

42



$100/month=$50, $100-$200/month=$150, $201-$300/month=$250, $301-$400/month=$350,
$401-$500/month=$450, $500+=$750. These mid-values were combined to create a variable
that ranged from losses to gains. The variable reflected change in financial status during
deployment with values ranging from negative $750 (indicating loss) to positive $750 (indicating
gain).

Army satisfaction was also an independent variable and was measured in response to the
question, "Overall, how satisfied are you with the Army as a way of life?" Likert-type responses
ranged from "very dissatisfied"=1 to "very satisfied"=5. This question was not asked during the
training phase survey.

Control Group

To compare the study group with a control group, a survey was administered to soldiers in the
29th Light Infantry Division who did not volunteer to go to the Sinai. The economic questions in
this survey were similar to the questions in the survey of the study group. The control group
survey was mailed to 120 senior soldiers in ranks E5 and above. The response rate was
approximately 84% with 101 returned surveys.

Design and Analysis

Survey data collected during waves one and two were used to analyze financial gains/losses
and their effect on career intentions. We used summary statistics to describe demographic,
economic, and psychological variables of the RC and AC. We also compared financial variables
between training and deployment phases. Finally, we compared results of the study group to a
control group.

To determine the financial impact of the deployment experience on RC soldiers, hierarchical
regression equations were used for training and deployment wave data. This regression
procedure is appropriate because it controls for multicollinearity due to causal ordering among
variables by partialling out shared variance (Nie, Hull, Jenkins, Steinbrenner, & Bent, 1975). In
our data, the monthly basic pay variable (calculated from rank and years of service) was related
to variables of financial gain/loss and Army satisfaction (see Appendix A). All variables were
tested for normality, outliers, and linearity. No variables violated these assumptions.

Wave one variables included career intention during the training phase as the dependent
variable, and financial status, force component, race, marital status, and education as independent
variables. Financial status during the training phase referred to the perceived gain/loss in
finances compared to their financial status prior to volunteering for the MFO. Therefore, for the
AC, this variable represented military pay and allowances at the time of data collection; for the
RC, this variable represented the change in financial status from civilian earnings plus drill pay
received from the pre-training to the training phase. We hypothesized that financial gain is
positively associated with the intention to stay in the AC or RC until retirement, while
statistically controlling for the effects of other explanatory variables (e.g., Army satisfaction,
marital status, and education).

14



Table 32

Regression Results for Career Intentions during Training and Deployment Phases

Independent Variables Training Phase Deployment Phase
(N = 209) (N= 187)
Block 1 R? = 036, F(1,207) = 7.732* R? = 073, F(1,185) = 14.639*
Financial Status B =.190, t= 2.781 = .271,t = 3.826*
Block 2 NA AR? = .047, F(1,184) = 9.781*
Army Satisfaction NA B =.219, t=3.127*
Block 3 AR? = .072, F(2,205) = 8.273* AR? = 017, n.s.
RC B =.275, t= 4.027* B =.132, ns.
Monthly Pay B =.102, ns. B =-.005, ns.
Block 4 AR? = 017, ns. AR? = 015, ns.
Race B =.043, ns. B =-.030, n.s.
Marital Status B =-.131, ns. B = .040, ns.
Education B =.016, ns. 6B =.141, ns.
R 125, F(7,201) = 4.797* .153, F(6,180) = 4.606*

Note. Standardized regression coefficients are shown.

*p <.05.

NA = Not applicable, question not asked during the training survey.

32



FOREWORD

The Organization and Personnel Resources Research Unit (OPRRU) of the U.S. Army
Research Institute for the Behavioral and Social Sciences conducts research in the areas of soldier
retention, readiness, organizational change, family factors, and peacekeeping operations.
Questions have recently arisen about the economic benefits of peacekeeping expenditures to
individual soldiers deployed for the Multinational Force and Observers (MFO) mission in the
Sinai.

This report identifies and quantifies the financial gains and losses perceived by soldiers
deployed for the 28th Rotation in the Sinai. The relationship of these gains or losses to their
career commitment in respective components is also analyzed.

This research was sponsored by the Chief of Staff, Army (CSA) as part of a larger project
on the 28th Rotation. Results of this and other research were briefed to U.S. Army Deputy Chief
of Staff for Personnel (DCSPER) and CSA by the project Task Group Leader, Dr. Ruth Phelps.

ZITA M. SIMUTIS EDGAR M. JOHNSON
Technical Director Director



Table 20

Self-Reported Hazard Duty Pay (HDP) of AC and RC during Training

AC RC
HDP $/Month Freq. _% Freq. _%
$0 - $100 27 84.4 148 87.1
$101 - $200 4 12.5 13 7.6
$201 - $300 - - 4 2.4
$301 and above 1 3.1 5 2.9
Total (N) 32 100.0 170 ~=—:100.0
Table 21
Self-Reported Special Pay (SP) of AC and RC during Training
AC RC
SP $/Month Freq. _% Freq. _%
$0 - $25 23 62.2 122 73.5
$26 - $100 10 27.0 22 13.3
$101 - $150 3 8.1 7 4.2
$151 - $200 1 2.7 7 4.2
$201 and above - - 8 48
Total (N) 37 100.0 166 100.0
Table 22

Self-Reported "Other Monthly Pay" (OMP) of AC and RC during Training

AC RC

OMP $/Month Freq. _% Freq. _%

$0 - $25 15 50.0 Wt 77.1
$26 - $50 0 0.0 0 0.0
$51 - $75 9 30.0 10 6.9
$76 - $100 2 6.7 7 49
$101 and above 4 13.3 160 11.1
Total (N) 30 100.0 144 = 100.0

25



The US General Accounting Office (1991) found that reserve attrition rates increased in two
cases. First, attrition rates were higher for reservists who lost overtime pay opportunities.
Second, attrition rates were higher when a reservist's primary military occupational specialty
(PMOS) mismatched their duty occupation. Based on these results, they recommended more
flexible training requirements and further analysis of matching PMOS with duty occupations.

Economics

Some researchers analyzed the role of economic variables in predicting retention intentions.
Grissmer and Kirby (1985) found that reservists who live in areas with relatively high
unemployment and low per capita income have relatively higher retention rates. This implies
that reserve service may be economically motivated by supplementing income. In this study,
Grissmer and Kirby (1985) also tested the effects of Selective Reenlistment Bonuses (SRBs) on
reenlistment decisions. Results showed that SRBs were significantly related to retention rates.
Reservists receiving bonuses extended or reenlisted more frequently than those in a control
group. The estimated coefficient of .11 for military bonuses suggested that separation decisions
may be weakly sensitive to pay increases.

Mehay (1991) tested whether the decision by civilians to join the reserves is equivalent to the
decisions by civilians to moonlight. Results showed two distinct models for reservists and
moonlighters, suggesting the decision to join the reserves is not equivalent to the decision to
moonlight. Results showed that participation in the reserves is a labor force decision which is
strongly influenced by individual and family economic status and local employment conditions.
These findings are consistent with research related to reservists’ intention to remain in the Army.

Finally, Lakhani (1995) found that reenlistment increased with an increase in reserve pay and
decreased with increases in civilian moonlighting wages. In addition, reenlistment intentions
correlated positively and significantly with actual reenlistment behavior. Thus, both variables are
appropriate for analyzing turnover.

Summary

Research has shown that demographic, attitudinal, military, and economic variables explain
important aspects of the reenlistment decision. The literature revealed that turnover intentions
were positively associated with age at entry into the RC, school attendance, current financial
benefits, and retirement benefits. In addition, reserve retention was positively associated with
military pay grades, noncombat jobs, prior active military service, civilian employers' positive
attitude toward reserve service, and the similarity of civilian and reserve jobs. As Lakhani
(1995) states these variables "occupy an important place in the reenlistment analysis" (p. 126)
and "should not be excluded from the reenlistment equation" (p. 124). Therefore, to increase
reserve reenlistment, the US Congress should increase reserve pay to match or surpass civilian
moonlighting wages.

11



Table 3

Self-Reported Basic Allowance for Subsistence (BAS) during Training (N = 221)

BAS $/Month Freq. %

$0 - $100 138 62.4
$101 - $200 52 23.5
$201 - $300 26 11.8
$301 and above 5 2.3
Table 4

Self-Reported Hazard Duty Pay (HDP) during Training (N = 210)

HDP $/Month Freq. %

$0 - $100 183 87.1
$101 - $200 17 8.1
$201 - $300 4 19
$301 and above 6 2.9
Table 5

Self-Reported Special Pay (SP) during Training (N =214)

SP $/Month Freq. %
$0 - $25 155 72.4
$26 - $100 32 15.0
$101 - $150 10 47
$151 - $200 9 42
$201 and above 8 3.7

17



Wave One: Training Phase

The survey instrument, 1994/95 Questionnaire of Socioeconomic Impact of Deployment in
Multinational Force and Observers (MFO) Task Force, was administered, in person, to a
population of approximately 500 soldiers during pre-deployment training at Fort Bragg, NC in
August and October, 1994. The response rate varied between 66% and 90% for most of the 28
items in the survey. The survey consisted of demographic and financial items. Financial items
included military and civilian pay and allowances, self-estimated financial gains or losses from
volunteering for the MFO assignment, civilian and military employment experience, spouse
employment experience and earnings, and Army career intentions prior to and subsequent to
deployment for the mission. The specific variables of interest for this paper are described below.

The dependent variable, career intention, was measured in response to the question, "Has your
likelihood of staying in the Guard/Reserve or Regular Army until retirement increased,
decreased, or remained the same due to deployment in the MFO?" Responses were coded as
follows: decreased=1, remained the same=2, increased=3. Responses for "don't know" and
missing values were excluded from the analysis by listwise deletion.

The quantitative independent variables were self-reported financial gains and losses, monthly
pay, civilian earnings, and education. Respondents estimated the values of financial gain and
loss to open ended items. We calculated the soldiers' monthly salaries based on the 1995 Army
Times Pay Chart using individual data on rank and years of service. Years of service was
defined as the aggregated total number of years in active and reserve duty. Education was
defined as a continuous variable with the following values: some high school, no diploma=1;
GED or equivalent=2; high school diploma=3; 1-2 years college=4; Associate's Degree,
occupational program=5; Associate's Degree, academic program=6; 3-4 years college, no
degree=7; Bachelor's Degree=8; graduate credit, no degree=9; Graduate or Professional
Degree=10. Variables for categorical data were dummy coded. These variables included race
(white=1; else=0), marital status (married=1; else=0), and force component (Reserve=1;
Active=0).

Wave Two: Deployment Phase

The deployment phase survey was administered, in person, to the population of about 500
Active and Reserve Component soldiers in the Sinai Peninsula during May 1995. The survey
consisted of 41 items of both financial and family impact variables. The subset of financial and
non-financial variables used for the analyses in this paper is specified below.

Data were collected for the dependent variable, career intention, during the deployment phase
survey administration. The item and its response options were identical to the career intention
item included in the training survey. Data for financial gains and losses were also collected as
independent variables, but did not reflect open ended responses as in the training phase survey.
Instead, responses were framed in terms of value ranges to reflect the ranges in the training wave
data. The midpoint of each range was used as an item response. Midpoint values for financial
gain/loss were computed as follows: did not gain/lose financially=$0, less than

13



Table 23

Self-Reported Total Military Earnings of AC and RC during Training

AC RC
Total Mil. $/Month Freq. % Freq. %
$0 - $200 2 2.5 132 43.1
$201 - $400 1 13 98 32.0
$401 - $1,000 4 5.0 50 16.3
$1,001 - $1,500 19 23.8 8 2.6
$1,501 - $2,000 24 30.0 8 2.6
$2,001 - $3,000 27 33.8 6 2.0
$3,001 and above 3 3.8 4 1.3
Total (N) 80 100.0 306 100.0
Table 24

Self-Reported Financial Gain and Loss of AC and RC during Training

—AC__ —RC__
$/Month Freq. _% Freq. _%
Financial Gain
$0 - $200 50 94.3 107 43.0
$201 - $400 - - 11 44
$401 - $1,000 1 19 25 10.0
$1,001 - $1,500 - - 9 3.6
$1,501 - $2,000 - - 5 2.0
$2,001 and above 2 3.8 92 36.9
Total (N) 53. 100.0 249 100.0
Financial Loss
$0 - $200 32 46.4 158 70.5
$201 - $400 8 11.6 6 2.7
$401 - $1,000 6 8.7 12 5.4
$1,001 - $1,500 11 15.9 2 0.9
$1,501 - $2,000 2 2.9 7 3.1
$2,001 and above 10 14.5 39 17.4
Total (N) 69 100.0 224 100.0

26



negative impact of about five months in the military. These results suggest that military training
differentially impacts veterans’ subsequent civilian wages.

Goldberg and Warner (1987) examined the effects of military and civilian experience on
veterans’ earnings. In support of the theory of general human capital, results showed that military
earnings are a close substitute for civilian experience in occupational groups where training
appears to be most transferable (e.g., medical, electrical/mechanical equipment repair). In
occupational groups where training is least transferable (e.g., combat), civilian experience has a
substantially larger effect on civilian earnings than does military experience. This research
supports the specific human capital theory and illustrates how military experience moderates the
relationship between veteran status and civilian earnings.

Summary

The positive effects of military service were substantive for World War I veterans, but
declined somewhat for Korean War veterans and were negative for Vietnam War veterans. In
addition, the impact of demographic factors on civilian earnings revealed that members of
minority groups realized greater financial gains as veterans than members of non-minority
groups. The literature of the effects of military training versus military experience revealed that
the training was more beneficial for life course development than experience. Military
experience is useful in occupations with civilian counterparts.

The preceding studies appear to have three limitations. First, the studies do not include a
comparable statistical control group of non-veterans. Some studies employ non-veterans of
similar age or similar formal educational levels as statistical controls. However, the growing
literature on the effects of cohort size on earning profiles show that it is.the year of entry into the
labor market that affects earnings rather than year of birth (Easterlin, 1980; Freeman, 1979;
Johnson, 1980; Welch, 1979). In addition, formal educational level is not an appropriate control
variable because it does not account for the quality of education which varies by geographic
regions.

The second limitation of these studies is that economic studies typically concentrate on
earnings of individuals and neglect family earnings. With the rise in dual-income families in
society today, it becomes necessary to examine family earnings. This is particularly of interest
for military members whose spouses are unemployed or underemployed during periods of active
military service (Payne, Warner, & Little, 1992).

The third limitation is that the research is compartmentalized by discipline: economists tend
to concentrate on economic variables and sociologists and psychologists analyze variables of
their own discipline. Therefore, there is a substantial case for inter-disciplinary research that
encompasses variables across these disciplines.



CONTENTS (Continued)

Table 31.

32.

33.

34.

35.

36.

37.

38.

Page

LIST OF TABLES (Continued)
Descriptive Statistics of Variables Used in Regression Equations ............:..00::0:+ 331
Regression Results for Career Intentions during Training and Deployment Phases......32
Comparison of Regression Coefficients in RC and AC Data Subsets .............0:0 34

Regression Results for Predicting Financial Status during Training ................0.--.00-+ 38

Logit Model Results of Home Ownership ..

Comparison of Control Group and Study Group Civilian Earning$S .............0.-000e 40
1994 Earnings of Control Group and Study Group by Rank...........0.::eeeneieee 40
Comparison of Spouse Earnings of Control Group and Study Group ...........:0:::0 41

xii



Base pay and allowances. Table 17 shows that while the typical monthly basic pay of the AC
and RC was in the $1,001-$1,500 range, most AC soldiers earned more than this amount and RC
soldiers earned much less. 22% of the AC earned $1,501 to $2,000 per month compared to 7%
of the RC in this range. This is because, as noted earlier, AC soldiers were more senior in rank
than RC soldiers.

A similar pattern of results was found with the BAQ variable. The reported BAQ values were
higher for the AC than the RC. For example, Table 18 shows that most RC soldiers (41%)
reported getting the lowest (up to $100) BAQ whereas most AC soldiers (56%) reported being in
the highest bracket ($401 and above). Table 19 shows that typical BAS values were greater for
the AC than the RC ($101-$200 range vs. $0-$100). In contrast, Hazard Duty Pay and Special
Pay values appear more evenly distributed for the two groups (Tables 20 and 21). Values for
"Other Monthly Pay," shown in Table 22, are small (less than $100) and most RC soldiers
reported this pay in the smallest bracket (less than $25).

Table 23 shows that total military earnings of AC soldiers are considerably higher than
military earnings of RC soldiers because of seniority in rank. 91% of AC soldiers reported
$1,001 and above but only 26% of RC soldiers reported earnings at this level. Table 24 shows
the distribution of financial gains and losses from training. These results reveal that the number
of gainers (N=302) during the training wave exceeded the number of losers (N=293) and gains
were greater for the RC than the AC. For example, most AC soldiers (94%) were concentrated in
the lowest gain bracket of $0-$200 compared to 43% of RC soldiers in this bracket. On the other
hand, many (37%) RC soldiers reported gaining $2,001 or more and approximately 4% of AC
soldiers reported being in this bracket. The RC volunteers who reported gains from training are
likely to be those who were unemployed and were looking for civilian jobs. In addition, most
RC volunteers (70%) lost the smallest amounts ($0-$200) whereas most AC soldiers lost the
larger amounts ($201 and above). To sum up, the RC gained more and lost less relative to the
AC.

Home ownership and marital status. The upper panel of Table 25 shows that home ownership
was greater for the AC than the RC (29% vs. 16%). The lower panel of this table shows that a
greater percentage of AC soldiers were married relative to RC soldiers (58% vs. 28%). These
statistics correspond to demographic variables such as the age distribution of RC and AC
soldiers.

Career commitment, Table 26 shows that the probability of career intentions for most
respondents during the training phase remained unchanged (68% of the AC and 53% of the RC).
However, the probability of increased retention was greater for the RC than the AC (32% vs.
12%). The probability of decreased retention was greater for the AC than the RC (11% vs. 4%).
Therefore, RC soldiers perceived that they were more likely to stay in the Army after their Sinai
experience relative to AC soldiers.

23



Table 10

1993 Civilian Unemployment of RC Soldiers (N = 328)

Employment Status Freq. %

Employed (N = 168)

Had job through 1993 127 75.6
Not looking for job 41 24.4

Unemployed (N = 160)

Less than 2 weeks 98 61.3

3-4 weeks 18 11.3
5 - 6 weeks 7 44
7-8 weeks 6 3.8
9 - 10 weeks 4 2.5
11 - 12 weeks 7 44
13 or more weeks 20 12.5
Table 11

1993 Civilian Hours Worked Per Week of RC Soldiers (N = 367)

Hours/Week Freq. %
0-20 39 10.6
21-30 24 6.5
31-40 142 38.7
41-50 96 26.2
51-60 43 11.7
61 and above 23 6.3

20



ECONOMIC LIFE COURSE ANALYSIS OF PEACEKEEPING DEPLOYMENT IN THE
SINAI

CONTENTS

Page
INTRODUCTION ......sesssssstessesssesssessssesssesssessscsssesssesssecsesssessecsseesnessnecsueesnecsneesuecanecsnecsncesneeneesnees 1
CONCEPTUAL FRAMEWORK
LITERATURE REVIEW ........ssess00e0

Veteran Status and Civilian Earnings .
Positive Effects of Military Service
Negative Effects of Military Service .
War Cohorts ...
Demographics
Military Training and Experience
Summary ........

Tumover Intentions .
Demographics .... 10
Attitudes 0... 10
Military Experience 10
Economics ......4++0+04 11
SUMMALY .......eeeeeeeeeseeeeee 11

RESEARCH OBJECTIVES

METHOD
Data Collection
Wave One: Training Phase
Wave Two: Deployment Phas:

Control Group .... 14
Design and Analysis .. 14
RESULTS AND DISCUSSION

Study Group Descriptive Statistics ..
Economic, Demographic, and Psychological Variables
Comparative Statistics between the AC and RC .......
Comparative Statistics between Training and Deployment Phases ..

Study Group Regression Results .
Career Commitment
Civilian Earnings ...

ix



ECONOMIC LIFE COURSE ANALYSIS OF PEACEKEEPING DEPLOYMENT IN THE
SINAI

EXECUTIVE SUMMARY

Research Requirement:

The U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) conducts
research on manpower, personnel, training, and peacekeeping of significance and interest to the
U.S. Army. Questions have been raised about the economic benefits of peacekeeping in the Sinai,
as part of Rotation 28 of the Multinational Force and Observers, to the individual soldiers.

Procedure:

The authors reviewed literature and analyzed data (N = 500) for Active Component (AC)
(20%) and Reserve Component (RC) (80%) soldiers who volunteered for the 28th Rotation for
service in the Sinai. Survey data were collected during the training phase at Fort Bragg in August
and October 1994 and during deployment at South Camp in the Sinai in May 1995. Descriptive
statistics and regression equations (step-wise, hierarchical, and logit) were estimated to analyze
changes in financial status from the predeployment training phase to the deployment phase. The
effects of these changes on career commitment of the soldiers in their respective component were
also analyzed. Data for a control group of RC soldiers who did not volunteer for the mission
were also collected and analyzed.

Findings:

The literature review revealed that there was no difference in the cost of deployment of a
100% AC battalion, as in the 27th Rotation, and a composite battalion of 20% AC and 80% RC,
as in the 28th Rotation. The regression results for the 28th Rotation revealed that the RC soldiers
realized an average net financial gain ($335 per month) and the AC soldiers incurred a net
financial loss ($102 per month) from the overall mission. Career commitments of both the groups
to their respective component was, however, enhanced significantly by financial gains and their
satisfaction with Army life.

Utilization of Findings:
The cost of an active and a composite battalion is about the same, but the economic
benefits appear to be greater for the RC component. Bases on this result, the Chief of Staff,

Army might be able to use this information for future deployment of composite battalions in the
Sinai, ceteris paribus.

vii



Turover Intentions

This section reviews the literature on demographic and economic variables that affect Army
career intentions. In this review, we primarily draw from the psychological and military
literatures to provide an overview of current research.

Many turnover models emphasize intervening variables of job satisfaction, commitment,
intention to quit, and search behavior (e.g., Mobley, Griffeth, Hand, & Meglino, 1979; Price &
Mueller, 1981). While these models identify causal paths in making a turnover decision, the
relative importance of other determinants has been neglected. For example, the direct effects of
demographic and economic variables have received limited attention (Thomas & Kocher, 1993).

Cotton and Tuttle (1986) conducted a meta-analysis on the correlates of turnover and found that
type of industry moderated the relationship between turnover and pay, job satisfaction, and
gender. In addition, they found that individual perceptions about economic or possible
employment alternatives are consistently related to individual turnover. The authors suggest that
these variables significantly impact turnover findings and need to be studied in the future.

To investigate broader categories of turnover antecedents, Thomas and Kocher (1993)
adopted Cotton and Tuttle's (1986) categorization of tumover correlates in their research. Cotton
and Tuttle (1986) summarized the correlates of turnover from numerous studies and reported
three factors that affect turnover intention: external market (e.g., alternative employment
opportunities), personal (e.g., demographic, work experience), and work-related (e.g., job
characteristics).

Thomas and Kocher (1993) were specifically interested in determining a broad range of
factors likely to influence recruiting and retention policies. They tested hypotheses about the
relative contribution of external market, personal, and work-related factors to an Army reservist's
decision to remain in the Army. A logistic regression model was used with a dichotomous
dependent variables (turnover decision). Independent variables were civilian labor force status
(external variable); race, family status, average length of service, school attendance (personal
variables); travel time to drill and retirement benefits (work-related variables). The initial
turnover model was run for all reservists and results showed a significant gender effect.
Different models predicting turnover were found for males and females. Subsequent analyses
were performed using gender specific models. We report the male model because it is consistent
with the sample in our study. Results showed that logistic regression coefficients for age at
reserve entry, school attendance, current financial benefits, and retirement benefits positively
predicted turnover decision. Race did not significantly impact the turnover decision.

Based on these results, Thomas and Kocher (1993) evaluated policy approaches. They
suggested that policy should target older individuals in reserve recruiting (e.g., ages 20-22).
Attention to compensation policy and retirement policy appear to be important predictors of male
reserve retention, as would a policy focusing on non-monetary aspects of the reserve job such as
intrinsic job characteristics.



CONTENTS (Continued)

Table 13

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

30.

Page
LIST OF TABLES (Continued)

1993 Civilian Earnings of RC Soldiers..........0...cccccceetee teres eens eseee tees nenseeeeceeees 21
1993 Civilian Weekly Earnings of RC Soldiers..............cccccecsesseeet et reeeeeeeeenesiees 21
Marital Status and Home Ownership during Training ...............0cccccsteeereereeieeeee 22
Self-Reported Impact of Deployment on Changes in Career Intentions
during Training... cesses eessecseesseeseeeseeeneesneeonecsnssensnsecarecesssesesssssenessceeacsesennetss 22
Self-Reported Basic Monthly Pay of AC and RC during Training............0:ccceeee 24
Self-Reported Basic Allowance for Quarters (BAQ) of AC and RC
during Traiming.....0......cecccsecsessesseesseesseesseesneesneeseeennesneeesecssenessserenssesetesseesstensetntsy 24
Self-Reported Basic Allowance for Subsistence (BAS) of AC and RC
during Traiming 0.0... ccccecsceeseesecssesseesseesseessecssecssecsecseeenieeneesneeeissseceeesereraneesessencetas 24

Self-Reported Hazard Duty Pay (HDP) of AC and RC during Training.
Self-Reported Special Pay (SP) of AC and RC during Training ...........0.-0ceeneee 25

Self-Reported “Other Monthly Pay” (OMP) of AC and RC during Training............... 25

Self-Reported Total Military Earnings of AC and RC during Training ...
Self-Reported Financial Gain and Loss of AC and RC during Training ...........0...0 26
Home Ownership and Marital Status of AC and RC during Training ..........0..00-00 27

Self-Reported Impact of Volunteering by AC and RC on Army Career Intentions
during Training............cccscesccecscesstessecsseesseeseesneceneenecesessneeeeeeseensesesesesseeesnsensatsneeentss 27

Comparison of Mean Gains and Losses during Training and Deployment Phases.
Comparison of Monthly Financial Gains during Training and Deployment Phases....... 29

Comparison of Changes in Army Career Intentions during Training and Deployment
PHASES oo. seccccscscscscscscscsesceseseseseseseecevseseeeseceseeseasseesscssscsssesesnseeeeneasieaseeseseseseseessneeees 30



Wave two variables included career intention during the deployment phase as the dependent
variable and change in financial status and Army satisfaction as independent variables. Other
independent variables included force component, race, marital status, and education. These
demographic data were previously collected during wave one and were match-merged with wave
two data by social security numbers.

RESULTS AND DISCUSSION
Study Group Descriptive Statistics

Summary statistics for the study group are organized into three sections: 1) analysis of
economic, psychological, and demographic variables, 2) comparison of AC and RC data, and 3)
comparison of training and deployment data. Please note that percentages listed in the tables
may not sum to 100% due to rounding error.

Economic, Demographic, and Psychological Variables

Base pay and allowances. Table 1 shows that the soldiers’ typical basic monthly pay was
between $1,000 and $1,500. The typical values of Basic Allowance for Quarters (BAQ), Basic
Allowance for Subsistence (BAS), Hazard Duty Pay (HDP), Special Pay (SP), and "Other
Monthly Pay" (OMP) were up to $100 per month (Table 2, 3, 4, 5 and 6). Table 7 shows that
typical total military earnings were up to $200 per month. These amounts were earned as drill
pay by the RC prior to their volunteering for the Sinai duty.

More soldiers (N=320) reported that they gained from volunteering for deployment compared
to those (N=314) who perceived an overall loss from volunteering for deployment. The typical
value of gain and loss was up to $200 (Table 8).

Civilian employment. The data on civilian employment status revealed that 45% of RC
volunteers were employed full-time and the remaining 55% were either unemployed,
underemployed (employed for 20 hours or fewer per week), or were attending school.
Specifically, 20% of the soldiers were unemployed, 13% were employed part-time, and 22%
were in school at the time they decided to volunteer for the Sinai mission.

Analysis of civilian job experience suggested that most of the RC (72%) had worked for fewer
than two years and only a few (3%) had worked for 10 or more years prior to deployment in the
Sinai (Table 9). This low level of civilian employment experience is supported by the extent of
civilian unemployment among the volunteers. For example, Table 10 shows that almost 49% or
160 of the 328 responding RC volunteers were unemployed and looking for civilian jobs in 1993
(the year prior to volunteering for the mission). Of those who were unemployed, most (61%)
were unemployed for fewer than two weeks; some (approximately 12%) were unemployed for 13
or more weeks.

Table 11 shows that the typical civilian hours worked by RC soldiers were in the 31-40 range
(39%), followed by those soldiers who worked 41-50 hours (26%). The civilian job tenure of the

15



Technical Report 1054

Economic Life Course Analysis of
Peacekeeping Deployment in the Sinai

Hyder Lakhani
U.S. Army Research Institute

Elissa Tartak-Abod
George Mason University

January 1997

United States Army Research Institute
for the Behavioral and Social Sciences

Approved for public release; distribution is unlimited.

cD



Table 34

Regression Results for Predicting Financial Status during Training

Independent Variables Regr. Coeff. (N = 56)
Block 1

Basic Monthly Pay b= 545
Other Mo. Pay b= 560
Mo. Hazard Pay b= 4.273
Mo. Allow. for subsistence b=  .922
Basic Allow. for Quarters b= .677
Special Pay b= 1.014
Block 2

Total Civilian Earnings b= -.030*
Years of Military Service b= 19.180
Rank b =-312.046
Block 3

Education b= -12.352
Marital Status b= -12.284
R? .210

E 1.068

Note. Raw regression coefficients are shown in this table.
*p<.05.

Table 35

Logit Model Results of Home Ownership (N=313)

Independent Variables Coefficient Probability
Financial gain/loss 000043 775
Family earnings .0005 .001
RC -.8004 018
Soldier's education 0438 528
Constant -2.0558 .001

38



but little is known about the micro economic effects of expenditures on the soldiers and their
families (Brinkerhoff & Horowitz, 1995; US General Accounting Office, 1995a, 1995b). For
example, the US General Accounting Office (1995a) estimated the total US incremental cost of
deploying the AC (the 27th rotation) for Fiscal Year 1993 at $18.6 million. Similarly,
Brinkerhoff and Horowitz (1995) of the Institute for Defense Analyses report the cost of the
combined AC and RC battalion in the 28th rotation at $21 million, with $18 million accounting
for pay and allowances. They note, "this is about the same cost that would be incurred by using
an AC battalion for the mission" (Brinkerhoff & Horowitz, 1995, p. 7). Therefore, an objective
of this report is to analyze the micro-economic life course benefits to US soldiers who were
deployed for 28th rotation of the peacekeeping mission in the Sinai.

CONCEPTUAL FRAMEWORK

The life course theory holds that experiences earlier in our lives shape the short-term and
long-term paths our lives will follow. Active military service is a prime example of a life-
shaping experience that has enduring effects across the life-span. Therefore, economists,
sociologists, and psychologists are interested in the effects of active military service on soldiers’
post-service life course developments. Economists concentrate on earnings, sociologists focus
on educational and occupational attainment, and psychologists deal with socio-psychological life
course aspects. Both the theoretical underpinnings and variables of interest vary by discipline.
The research presented below illustrates this divergence.

Economists consider military training and experience as investment in human capital that may
yield returns after active military service. They use the theory of human capital to predict future
earnings of veterans. This theory has two competing hypotheses related to the effects of human
capital on subsequent earnings: the theory of "general" human capital versus the theory of
"specific" human capital.

The hypothesis of "general" human capital suggests that military training enhances general
human capital which can be readily transferred to civilian occupations and results in an increase
in civilian earnings. A number of economic studies have found support for this hypothesis
(Villamez & Kasarda, 1976; Little & Fredland, 1979; Martindale & Poston, 1979; Sticht,
Armstrong, Hickey, & Caylor, 1987; Magnum & Ball, 1989; Phillips, Andrisani, Daymont, &
Gilroy, 1992; Xie, 1992; Bryant, Samaranayake, & Wilhite, 1993). These studies concluded that
gains in civilian earnings were significantly higher for World War II veterans, somewhat smaller
for Korean War veterans, and the smallest for Vietnam War veterans compared to non-veterans.

The hypothesis of "firm specific" human capital suggests that military training imparts firm-
specific capital that is not transferrable to the civilian sector. Military service taps soldiers’
capacities during the prime of their lives at the expense of college education or civilian
experience. Economists contend that the interruption in education and/or civilian work
experience is not conducive to continued increases in earnings. The result is lower civilian
earnings reported for veterans compared to non-veteran civilians (Rosen & Taubman, 1982;
Berger & Hirsch, 1983; Schwartz, 1986; Crane & Wise, 1987; Angrist, 1989, 1990; Laurence &
Ramsberger, 1990; Angrist & Krueger, 1994).



ECONOMIC LIFE COURSE ANALYSIS OF PEACEKEEPING DEPLOYMENT IN THE SINAI

INTRODUCTION
"Money is like a sixth sense without which you cannot make complete use of the other five."
Somerset Maugham

During the post-Cold War era, multinational peacekeeping operations have become
increasingly more important for both the United Nations Organization (UN) and the United
States (US). Changes in international peacekeeping doctrine and Russian support of collective
security under the United Nations auspices have contributed to the status of peacekeeping as a
“prominent military mission" (Segal, Segal, & Eyre, 1992). The US Joint Chiefs of Staff (1995)
noted for the first time that the principal roles of American troops are no longer limited to
fighting wars and deterring aggression, but also include sustaining peace.

The level of increased peacekeeping efforts directly impacts two significant areas, personnel
and financial resources. For example, the US Joint Chiefs of Staff (1995) report added that
"Reserve component elements will take on increased responsibility for participating in and
supporting peacekeeping missions" (p. 9). In addition, peacekeeping activities require substantial
revenue and resource allocation. An obvious rationale for US spending on peacekeeping efforts
is that prevention of war is better than the cure. The rationale for deployment of the Reserve
Component (RC) is to reduce the strain on the Active Component (AC) and also to integrate the
two components in a true sense of the term "total force policy."

The UN peacekeeping budget increased from $233 million with 20,000 employees in Fiscal
Year 1987 to $3.6 billion with 70,000 employees in Fiscal Year 1995. In fact, the UN spent
more on peacekeeping in 1993 than in the previous 48 years of its existence (Mathews, 1995).
The US share of the UN peacekeeping budget accounts for approximately 31% and amounted to
$1 billion in Fiscal Year 1995 (Preston, 1995).

The US peacekeeping expenditures for the Multinational Force and Observers (MFO)
operation in the Sinai are excluded as part of the US share in the UN peacekeeping budget. The
US provides one-third of the annual operating costs for maintaining the MFO (US Department of
the State, 1995) and has provided about one-half of the total force required for this mission (US
General Accounting Office, 1995). US involvement in the MFO operation consists of supplying
military personnel and civilian observers and providing financial contributions. Apart from the
US, the MFO includes ten other countries: Australia, Canada, Colombia, Fiji, France, Hungary
(replaced The Netherlands in 1995), Italy, New Zealand, Norway, and Uruguay.

The US deploys soldiers to the Sinai Peninsula on six-month rotations to support the Camp
David Accord signed in 1979. Since the implementation of the Camp David Accord in 1982,
there have been 28 rotations. The 28th rotation initiated deployments in January, 1995 and
comprised a battalion of 80% RC and 20% AC soldiers. This was the first time the US deployed
a battalion of this type as part of the MFO.

The macro aspects of public expenditures for peacekeeping costs are relatively well known,

1



Using training data, the RC analysis showed that financial status (gain or loss) and basic
monthly pay variables account for a significant portion of variance in explaining career
intentions. In the original model, monthly pay was not a significant predictor. The AC analysis
did not result in significant predictors of career intentions. Note that while the coefficients and
overall R are larger than the RC analysis, the effect size is small (F = 1.814). The non-
significant results may be attributed to the small sample size in the AC analysis (n = 34). In the
original model, we aggregated the two components due to insufficient sample size for AC data
and created a dummy variable to represent force component.

Table 33

Comparison of Regression Coefficients in RC and AC Data Subsets

Independent Overall Model RC Model AC Model

Variables (N = 214) (n = 175) (n = 34)
Training Phase Analysis

Constant 2.074 2.026 1.947

Block 1 R?= 037% R’= .028* R’= .106

Financial Status B= .192* B= .168*

Block 2 AR? = .001 AR? = .025*

Monthly Pay B= .032 B= .158*

Block 3 AR? = .036* AR? = .012*

Race B= .074 B= .021

Marital Status B =-.185* B=-.115

Education B= .017 B = -.000

R .074* .065* 208

F F(5,208) = 3.324 —-F(5,169)=2.337. ——-F(5,28) = 1.467

Test of Stability

Std. Error 546 535 497

Residual Sum of Squares 61.917 48.370 6.922

34



Table 15

Marital Status and Home Ownership during Training

Response Freq. %

Marital Status (N = 485)

Not married 306 63.1
Currently married 159 32.8
Separated 20 41

Home Ownership (N = 486)

Yes, own home 86 17.7
No, do not own 400 82.3
Table 16

Self-Reported Impact of Deployment on Changes in Career Intentions during Training (N = 488)

Change in Career

Intentions Freq. %

Increased 133 27.3
Decreased 27 5.5
Unchanged 274 56.1
Don't Know 54 11.1

Comparative Statistics between the AC and RC

Military experience. The survey respondents included junior enlisted, noncommissioned
officers, and commissioned officers from both the AC and RC. The number of soldiers was 634,
with 80% RC soldiers and 20% AC soldiers. The rank structure revealed that 63% of the soldiers
were junior enlisted, 30% were Noncommissioned Officers (NCOs), and the remaining 7% were
officers. This distribution of ranks represents the population of all soldiers in the peacekeeping
assignment. While the officers and NCOs were equally divided between the RC and AC, junior
enlisted soldiers were drawn mostly from the RC (61% vs. 2% from the AC).

22



Control Group Descriptive Statistics

In this set of analyses, control group and study group summary statistics were compared for a
subset of variables. These descriptive results are reported below.

Demographics

Statistics show that the study group is further along in both family and career. More control
group soldiers were married compared to the study group (80.2% vs. 31.7%). The average
(arithmetic mean) number of children was also greater for control group soldiers (mean=1.35)
compared to study group soldiers (mean=.61). The control group has reached a higher average
educational level (mean of 6.85 equivalent to 3 or 4 years of college) relative to the study group
(mean of 4.13 equivalent to 1 or 2 years of college). Finally, all control group soldiers were
NCO or officers compared to 28.6% of the study group.

Civilian Earnings

Table 36 shows that most control group soldiers had considerably higher civilian earnings
compared to the earnings of the study group soldiers ($41,100/year vs. $16,670/year). Since
mean values are influenced by extreme earnings of a few soldiers, median earnings are more
representative of the groups. Median earnings indicate that one-half of the soldiers had income
higher than the median value and another one-half had earnings lower than the median. The
median earnings of the control and the study group was $36,944/year and $15,212/year,
respectively. The lower mean and median earnings of the study group reflect the fact that many
of these soldiers were either unemployed, underemployed, or in school.

Since the control group soldiers held higher ranks as noncommissioned officers, we sorted the
study group soldiers in these same ranks to compare their earnings. Table 37 shows that the
study group soldiers' earnings were lower for the same ranks of soldiers.

In future research, we will attempt to analyze growth rates of civilian earnings for volunteers
and non-volunteers. It is likely that the growth rate of earnings for volunteers would be higher
and consequently would surpass the earnings of non-volunteers over time.

Spouse Earnings

Table 38 shows that mean spouse earnings of the control group soldiers were also higher than
spouse earnings of the study group soldiers ($23,115 vs. $10,418). The information contained in
Table 38 does not include the unemployed. Similarly, median spouse earnings of the control and
the study group were $25,000 and $5,200, respectively. We conclude that the non-volunteer
group did not volunteer for the mission because their individual and family earnings were
substantially higher than corresponding values for the study group, and they would have lost
financially by volunteering.

39



Table 12

1993 Civilian Job Tenure of RC Soldiers (N = 333)

Weeks Worked/Year Freq.

%

0 - 26 67 20.1
27-52 256 76.9
53-78 9 2.7
79 and above 1 0.3
Table 13

1993 Civilian Earnings of RC Soldiers (N = 51)

Civilian $/Year Freq. %
$0 - $1,000 14 27.5
$1,001 - $2,000 13 25.5
$2,001 - $3,000 12 23.5
$3,001 - $4,000 5 9.8
$4,001 and above 7 13.7

Table 14

1993 Civilian Weekly Earnings of RC Soldiers (N = 339)

Civilian $/Week Freq. %
$0 - $100 17 5.0
$101 - $200 65 19.2
$201 - $300 86 25.4
$301 - $500 95 28.0
$501 - $800 42 12.4
$801 - $1,200 17 5.0
$1,201 and above 17 5.0

21



CONTENTS (Continued)

Financial Status....
Home Ownership.
Control Group Descriptive Statistic:
Demographics...
Civilian Earning
Spouse Earnings ..

SUMMARY AND CONCLUSIONS .0.00..0.00ccccccscscssessesc esses eeseeeeeesessneeesnessenssistenseesansinesntens 41
REFERENCES o0oo...cocecccccceccecceeeceececescscecesesesesesscssssesesessessesseseescsssesessssecavatieerseeseisesssssesessenes 43
APPENDIX A. CORRELATION MATRIX AMONG QUANTITATIVE PREDICTORS ........ 49
LIST OF TABLES
Table 1. Self-Reported Basic Monthly Pay during Training ..............0..ccceceeceeeee eects 16
2. Self-Reported Basic Allowance for Quarters (BAQ) during Training... 16
3. Self-Reported Basic Allowance for Subsistence (BAS) during Training................0...... 17
4. Self-Reported Hazard Duty Pay (HDP) during Training 00.00.0000. 17
5. Self-Reported Special Pay (SP) during Training ...0......0..0.0.0 cece eseeeeeseeeeeeteeeaees 17
6. Self-Reported “Other Monthly Pay” (OMP) during Training... cee 18
7. Self-Reported Total Military Earnings during Training ........0....0..0.cccccceteee eee 18
8. Self-Reported Financial Gain and Loss during Training .........0.0..0ccccceceesseeeteeeceeeee 19
9. Years of Civilian Service of RC Soldiers 0.0.0.0... ese eeeseeesesesseseseeeeseeeesees 19
10. 1993 Civilian Unemployment of RC Soldiers .........0.0..cccccceeceseeses cece eeesecseseeseeeeseees 20
11. 1993 Civilian Hours Worked Per Week of RC Soldiers .........0.ccccceceseeeeeeseeeee 20
12. 1993 Civilian Job Tenure of RC Soldiers.............cccceseseeseseseeeeeeeseteeeesenseeeereneneeies 21



RESEARCH OBJECTIVES

Some of the volunteering RC soldiers were confronted with a tradeoff between civilian
earnings and active duty military earnings. As such, it is necessary to determine whether the loss
of civilian earnings, plus drill pay received as a reservist, were offset by either financial gains or
losses due to active duty earnings associated with volunteering for the peacekeeping mission. In
addition, the component's average financial gain will be compared to its average financial loss to
determine the average net gain or loss associated with volunteering for the component. Career
intentions will be regressed on financial status (gains or losses) to determine whether financial
gains are associated with Army career commitment, while statistically controlling for other
variables affecting career commitment.

For this paper, career commitment is defined as "the intention to stay in the RC or AC until
retirement." In future research, career commitment will be defined as reenlistment behavior
during the post-deployment period. Future long-term earnings and reenlistment behavior will be
analyzed by follow-up surveys for three years upon the soldiers’ return (end of 1995, 1996, and
1997). Educational attainment, a sociological variable, will be assessed from educational levels
attained by the Sinai veterans from the post-deployment follow-up surveys.

This preliminary report is, however, limited to examining life course perceptions of financial
benefits of individual (not family earnings) volunteers during two points in time. For wave one,
we compare the change in reservists’ financial status during the pre-deployment training period
(from approximately July 1994 through December 1994) to their financial status prior to
volunteering for this mission. For wave two, we compare the change in financial status during
the deployment phase in the Sinai (from January 1995 through July 1995) to their status during
the training period. The third through the fifth waves will result in three annual follow-up
surveys from the end of 1995 to the end of 1997. The results of these last three waves will be
discussed in separate reports. Future research will determine whether RC soldiers with civilian
jobs prior to volunteering for the mission were reemployed in the same jobs, as required under
the 1994 Uniformed Services Employment and Reemployment Rights Act (USERRA).

METHOD
Data Collection

To determine the economic impact of deployment to the Sinai on the soldiers, data were
collected in two waves. Wave one data were collected during the MFO task force training phase
and wave two data were collected during deployment at the South Camp in the Sinai. Similar
surveys and methods were employed during both data collection waves. Most demographic
information was collected during wave one. However, these demographic data were used in both
wave one and wave two data analyses.

12



APPENDIX A

Pearson R Correlation Coefficients among Quantitative Predictors

T_FINANC D_FINANC MO_PAY EDUCAT ASATIS
T_FINANC 1.00 413* 030 .049 NA
D_FINANC 1.00 048 055 .137*
MO_PAY 1.00 .543* .286*
EDUCAT 1.00 .082
ASATIS 1.00
*p<.05

NA = Not applicable; T_FINANC = Financial gain/loss, training;

D_FINANC = Financial gain/loss, deployment, MO_PAY = Basic monthly pay; EDUCAT =

Education level completed; ASATIS = Amy satisfaction.

49



Table 28

Comparison of Monthly Financial Gains during Training and Deployment Phases

AC RC

Training Deploy. Training Deploy.

(n =55) (n = 36) (n = 449) (n = 195)
Gain $/Month % % % %
Less than $100 94.5 27.8 41.8 17.4
$101 - $500 0.0 55.6 8.4 43.6
$501 or more 5.5 8.3 49.8 6.7
Don't know * 8.3 * 32.3

amount/NA

* = Question not asked during training survey
NA = Not applicable

Table 29

Comparison of Monthly Financial Losses during Training and Deployment Phases

AC RC

Training Deploy. Training Deploy.

(n=71) (m= 54) (n = 224) (n = 203)
Loss $/Month % % % %
Less than $100 31.0 57.4 69.2 58.6
$101 - $500 26.8 35.2 5.2 19.8
$501 or more 42.3 0.0 25.4 3.4
Don't know * 7A 0.2 18.3

amount/NA

* = Question not asked during training survey
NA = Not applicable

Career commitment, Table 30 shows the data for career intentions of AC and RC soldiers.
The data for the training phase revealed that career intentions remained unchanged for most of
the soldiers (67.4% for the AC vs. 52.7% for the RC). During the training phase, RC soldiers
reported they were more likely to stay in the Army until retirement compared to AC soldiers
(31.9% vs. 12.0%). During the deployment phase, perceived career commitment decreased
considerably compared to the training phase for both components.

29



Table 30

Comparison of Changes in Army Career Intentions during Training and Deployment Phases

AC RC

Training Deploy. Training Deploy.

(n = 92) (n= 67) (n = 370) (n = 284)
Response % % % %
Increased 12.0 6.0 31.9 17.6
Decreased 12.8 38.8 3.8 28.9
Unchanged 67.4 49.3 52.7 43.3
Don't know 8.7 6.0 11.6 10.2

Study Group Regression Results
Career Commitment

Table 31 provides descriptive statistics of the independent variables used in the regression
analyses. Table 32 shows the results of two separate regression equations for predicting career
intentions--one for each phase of the MFO (i.c., training and deployment). These results are
discussed below.

Financial status (gain or loss) was entered in block one using the training phase data to predict
career intentions. The results reveal that financial gain accounts for a statistically significant
portion of variance in explaining career intentions. Thus, increases in financial gains from the
pre-training to training phase are associated with greater likelihood of remaining in the Army
until retirement.

Army satisfaction (Block 2 variable) was not included in the training phase regression
equation because this question was not asked as part of the training survey. To accurately
compare training and deployment phase results, the next set of variables are described as block
three variables. Independent variables entered in block three were basic monthly pay and force
component (RC=1; AC=0). Basic monthly pay was calculated from the Army Times pay tables
for 1995 by using two institutional variables, rank and years of service. We hypothesized that,
basic monthly pay, and hence experience, would impact on subsequent career commitment.
Block three variables added significant variance above and beyond the financial explanatory
variable in block one. However, only force component (i.e., RC) had a significant positive,
linear, relationship with career intentions. Thus, during the training phase, RC soldiers, but not
AC soldiers, reported that they were more likely to remain in the military until retirement. It is
important to note that the criterion variable in the equation refers to career intention, not
behavior, so that the results are only tentative until we examine data for career behavior. Career
behavior data will be collected in post-deployment surveys.

30



Magnum, S. L., & Ball, D. E. (1987. Military skill training: Some evidence of transferability.
Armed Forces and Society, 13, 425-441.

Magnum, S. L., & Ball, D. E. (1989). The transferability of military provided occupational
training in the post-draft era. Industrial and Labor Relations Review, 42(2), 230-245.

Maddala, G. S. (1977). Some further topics in multiple regression. In Econometrics (p. 198).
New York: McGraw Hill.

Martindale, M., & Poston, D. L. (1979). Variations in the veteran/non-veteran earnings patterns
among World War II, Korea, and Vietnam War cohorts. Armed Forces & Society, 5, 219-
243.

Mason, W. M. (1970). On the socioeconomic effects of military service. Unpublished doctoral
dissertation, University of Chicago, Chicago, IL.

Mathews, J. (1995, August 28). The U.N.’s next 50 years. The Washington Post.

Matthews, W. (1995, August 28). Guard and Reserve: Reserve forces in a new light. Army
Times, pp. 24-25.

Mehay, S. L. (1991). Reserve participation versus moonlighting: Are they the same? Defence
Economics, 2, 325-337.

Mobley, W. H., Griffeth, R. W., Hand, H. H., & Meglino, B. M. (1979). Review and conceptual
analysis of the employee turnover process. Psychological Bulletin, 36, 493-522.

Nie, N. H., Hull, C. H., Jenkins, J. G., Steinbrenner, K., & Bent, D. H. (1975). Statistical
packages for the social sciences (pp. 379-381). New York: McGraw Hill.

Payne, D. M., Warner, J. T., & Little, R. D. (1992). Tied migration and returns to human capital:
The case of military wives. Social Science Quarterly, 73(2), 324-339.

Phillips, R. L., Andrisani, P. J., Daymont, T. N., & Gilroy, C. L. (1992). The economic returns to
military service: Race-ethnic differences. Social Science Quarterly, 73(2), 340-360.

Preston, J. (1995, March 16). Funding cut seen threatening U.S. role in UN. The Washington
Post, p. A31.

Price, J. L., & Mueller, C. W. (1981). A causal model of turnover for nurses. Academy of
Management Journal, 24, 543-545.

Rosen, S., & Taubman, P. (1982). Changes in life-cycle earnings: What do social security data
show? Journal of Human Resources, 17, 321-338.

45



Table 6

Self-Reported "Other Monthly Pay" (OMP) during Training (N = 182)

OMP $/Month Freq. %
$0 - $25 133 73.1
$26 - $50 0 0.0
$51 - $75 20 11.0
$76 - $100 9 49
$101 and above 20 11.0
Table 7

Self-Reported Total Military Earnings during Training (N = 407)

Total Mil. $/Month Freq. %
$0 - $200 139 34.2
$201 - $400 107 26.3
$401 - $1,000 58 14.3
$1,001 - $1,500 27 6.6
$1,501 - $2,000 35 8.6
$2,001 - $3,000 33 8.1
$3,001 and above 8 2.0

18



46



Technical Report 1054

Economic Life Course Analysis of Peacekeeping
Deployment in the Sinai

Hyder Lakhani
U.S. Army Research Institute

Elissa Tartak-Abod
George Mason University

Multinational Force and Observers Task Force
Ruth H. Phelps, Leader

and

Organization and Personnel Resources Research Unit
Paul A. Gade, Chief

U.S. Army Research Institute for the Behavioral and Social Sciences
5001 Eisenhower Avenue, Alexandria, Virginia 22333-5600

Office, Deputy Chief of Staff for Personnel
Department of the Army

January 1997
Army Project Number Manpower and Personnel

20363007A792

Approved for public release; distribution is unlimited.

iii



Data for veteran volunteers who returned from the Sinai will be collected in post-deployment
follow-up surveys conducted at the end of 1995, 1996, and 1997. Future research will include
analyses of reenlistment behavior of the soldiers as well as their plans to stay in the RC until
retirement.

Civilian Earnings

To predict civilian earnings of RC soldiers, we estimated an equation with civilian earnings as
the dependent variable and explanatory variables such as civilian education of the soldier, marital
status, the number of dependents, years of service in the RC, age, and civilian experience. We
hypothesized that civilian earnings will increase with an increase in education, civilian job
experience, or age. Listwise deletion of missing data reduced the number of observations to only
80. The results revealed that the R-squared value was approximately .06 and none of the
regression coefficients was significant. Therefore, these results are not reported.

Financial Status

Table 34 shows regression results for predicting financial status during training. Hierarchical
regression was used to determine if any set of variables explained significant variance in
financial status (gain or loss). At level one, basic monthly pay, monthly hazard pay, basic
allowances for quarters, allowance for subsistence, special pay, and other monthly pay were
entered. This set of variables did not contribute significant variance in the dependent variable.
However, the signs for the betas showed that basic monthly pay and monthly hazard pay were
more strongly related to financial status than other "allowance" variables.

At level two, total civilian earnings, years of service, and rank were entered as predicted. A
significant, linear, negative relationship was found between total civilian earnings and financial
status. One unit increase in total civilian earnings is associated with a .03 decrease in financial
status. Therefore, RC soldiers who had civilian jobs appear to have lost financially by
volunteering for the mission. At level three, education and marital status were entered. No
significant relationships were found.

Home Ownership

Home ownership is the largest economic asset held by an individual or a family. Of the 313
soldiers who responded to the question on home ownership, only 21% of the soldiers owned their
homes. A greater percentage of AC soldiers owned homes than RC soldiers (30% vs. 16%)
because they were older, married, and had higher ranks relative to RC.

Home ownership was analyzed by estimating a logit model because the dependent variable
was binary (i.e., soldiers either owned homes or did not own homes). Table 35 shows that home
ownership was positively and significantly (p < .01) associated with family earnings (i.e.,
earnings of the soldier and his spouse). Also, RC soldiers were significantly less likely to own a
house relative to AC. An increase in soldier's earnings or his education was positively associated
with home ownership, but this relationship was not statistically significant.

37



Table 33 Continued

Comparison of Regression Coefficients in RC and AC Data Subsets

Independent Overall Model RC Model AC Model

Variables (N =214) (n = 175) (n = 34)
Deployment Phase Analysis

Constant 1.354 1.435 583

Block 1 R’= .081* R’= .083*

Financial Status B= .285* B= .288*

Block 2 AR’ = .049* AR? = .049*

Army Satisfaction B= .224* B= .224*

Block 3 AR’ = .002 AR’ = .003

Monthly Pay B =-.052 B = -.056

Block 4 AR? = 014

Race B =-.007

Marital Status B= .007

Education B= .136

R 146* .144* 357

E F(6,182) = 5.185 F(6,156) = 4.387 F(6,17) = 1.575

Test of Stability

Std. Error 673 684 537

Residual Sum of Squares 82.428 72.890 4.901

*p<.05

Using deployment data, the RC analysis showed that financial status and Army satisfaction
variables account for a significant portion of variance in explaining career intentions. These
results are consistent with the original model. The AC analysis did not result in significant
predictors of career intentions. The AC data set for the deployment phase also had a small sub-
sample size (n=24).

To determine the equivalence of the two regressions, we conducted a test of stability using the
Chow Test (1960; as cited in Maddala, 1977). This analysis tests the hypothesis that some or all
of the regression coefficients are different in subsets of the data. The formula for the F test is

F=(RRSS - URSS / (k + 1))/ (URSS / (n1 + 2 - 2k -2))
35



Positive Effects of Military Service

Mason (1970) analyzed the GI Bill benefits and concluded that many veterans obtained a
higher education because of these benefits. Fligstein (1976) concluded that higher educational
levels of World War II veterans were due to their greater motivation. Martindale and Poston
(1979) concluded that World War II, Korean War, and Vietnam War era veterans all showed
higher civilian earnings patterns than non-veterans, though these positive effects were less
substantial and more variable for Vietnam era veterans. Villamez and Kasarda (1976) also
observed a positive economic impact of military service, but found the impact to be the strongest
for World War II veterans and weakest for Vietnam era veterans. Xie (1992) concluded that
veterans earned slightly more than non-veterans in the civilian market after Statistically
controlling for age and education. Little and Fredland (1979) noted that there was a positive
economic impact of military service, with larger gains realized by non-white veterans than white
veterans.

The greater benefits to minority groups is often called the "bridging environment" provided by
the military to get them out of a low level equilibrium trap of poverty based on past
discrimination. Gade et al. (1991) analyzed the post-Vietnam data and concluded that Army
service had a positive impact not only in terms of socio-economic benefits, such as an increase in
employment, earnings, standard of living, and educational levels, but also in enhancing several
socio-psychological benefits. In this research, Gade et al. (1991) confirmed the bridging
hypothesis.

Negative Effects of Military Service

The studies that show negative effects of military service mostly pertain to veterans who were
drafted during the Vietnam War. Laurence and Ramsberger (1990) analyzed a small sample of
400 low ability veterans (those who scored in one of the lowest categories on the Armed Services
Vocational Aptitude Battery). They concluded that being a veteran did not provide much, if any,
advantage in post-military earnings. However, their results are not very useful for a number of
reasons. First, the sample consisted of low ability veterans recruited in the pre-all volunteer force
(AVF) era. Second, they had questionable control variables for a period prior to enlistment
instead of the more relevant post-service variables. Finally, they did not have a comparable
control group of non-veterans. The military has not recruited similar low ability recruits since the
AVE. Above all, other studies using a larger sample of substantially the same data reached
opposite conclusion (see Sticht et al., 1987).

Crane and Wise (1987) focused exclusively on the Vietnam era veterans and found that
veterans lost 11 percent of civilian earnings, while Berger and Hirsch (1983) found a smaller
penalty of 2 percent. Schwartz (1986) found no benefit for Korean War veterans and a penalty
for Vietnam era veterans. Angrist (1989) used National Longitudinal Survey data that were also
used by Phillips et al. (1992). In this study, Angrist (1989) concluded that white veterans had
lower hourly wages in 1981 than non-veterans and that Vietnam veterans had neither a premium
nora penalty. In 1990, Angrist used social security data and showed (ten years after discharge)
that white Vietnam veterans had an annual earnings loss of $3,500 or a penalty of 15 percent.

5



Wong, L., Bliese, P., & Halverson, R. (1995). Multiple deployments: Do they make a difference?
Paper presented at the biennial conference of the Inter-University Seminar on Armed
Forces and Society, Baltimore, MD.

Xie, Y. (1992). The socioeconomic status of young male veterans, 1964-1984. Social Science

Quarterly, 73(2), 379-396.

47



service on subsequent civilian wages differs with education and race. Minorities and high school
dropouts benefitted from a military stint while college graduates suffered a large wage penalty.

Browning, Lopreato, and Poston (1973) examined the effects of military service for three
ethnic groups: Mexican Americans, African Americans, and whites. Two related predictions
were made: 1) white veterans will earn less than non-veterans and 2) among minorities, veterans
will earn more than non-veterans. The goal of this research was to determine the average dollar
difference between veteran and non-veteran income while controlling for educational and
occupational attainment. The data supported prediction #1 that income differences between
veterans and non-veterans vary by race. Prediction #2 was also supported. For most
occupations, veterans had an income advantage over non-veterans for both minority groups.

Little and Fredland (1979) reported the long term effects of veteran status on civilian wages.
This research targeted veteran groups, disaggregated by race, approximately 20 years after their
military service in World War II. Results showed that the positive impact of military service on
civilian earnings was attributed to "general" training. Veteran status was a positive and
significant variable in explaining the earnings of ex-servicemen, regardless of race,
approximately 15 to 20 years after their military service. White veterans had earnings 5-10%
higher than non-veterans and minority veterans had even larger benefits. Limited evidence
suggested that veterans came from somewhat better socioeconomic backgrounds than non-
veterans and that veterans improved their status relative to non-veterans.

Military Training and Experience

The military is a major provider of on-the-job training. This training can be useful in the
civilian sector (e.g., motor vehicle driving, computer skills, and repairs and maintenance)
(Magnum & Ball, 1989; Sandler & Hartley, 1995). Other military training is not as transferable
to the civilian sector and includes missile operators, tank gunners, and parachutists (Sandler &
Hartley, 1995). Some researchers have suggested that approximately 80% of military
occupational specialties have civilian counterparts (Magnum & Ball, 1987). Magnum and Ball
(1987) conducted a study to determine the transferability of military skills training to civilian
occupations. Results showed that a significant amount of skills transferred to civilian
employment. Males were better able to transfer skills in occupations such as craft and equipment
repair and females were better able to transfer skills to occupations such as administrative
support.

In general, it is predicted that more general training is transferable and will result in higher
civilian wages for veterans. In contrast, soldiers receiving specific training will not benefit in the
civilian market. Bryant et al. (1993) provided empirical evidence suggesting that military
training is beneficial. Results showed that training increased civilian wages, but general military
experience was detrimental to subsequent civilian earnings. Bryant and Wilhite (1990) separated
military experience from military training. After controlling for several social, economic, and
demographic characteristics, military training exerted a positive influence on civilian wages.
Results showed that time in the military reduced civilian wages. Military training does not have
a direct impact on wages, but interacts with time in service. One month of training offsets the

1



REPORT DOCUMENTATION PAGE

1, REPORT DATE 2. REPORT TYPE 3. DATES COVERED (from. . . to)
1997, January Final May 1994-February 1996
4, TITLE AND SUBTITLE 5a, CONTRACT OR GRANT NUMBER

Economic Life Course Analysis of Peacekeeping Deployment in the 5b. PROGRAM ELEMENT NUMBER

Sinai 0603007A
6. AUTHOR(S) 5c. PROJECT NUMBER
A792
Hyder Lakhani (ARI) and Elissa Tartak-Abod (George Mason 5d. TASK NUMBER
University) 1124
Se. WORK UNIT NUMBER
HO1
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER
U.S. Amny Research Institute for the Behavioral and Social Sciences
ATTN: PERI-RP

5001 Eisenhower Avenue
Alexandria, VA 22333-5600

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. MONITOR ACRONYM

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

5001 Eisenhower Avenue

Alexandria, VA 22333-5600 11, MONITOR REPORT NUMBER

Technical Report 1054

12. DISTRIBUTION/AVAILABILITY STATEMENT
Approved for public release; distribution is unlimited.

13, SUPPLEMENTARY NOTES

14. ABSTRACT (Maximum 200 words):

This report has two objectives. The first objective is to estimate the extent of financial gains or losses of Active Component
(AC) and Reserve Component (RC) soldiers for the Multinational Force and Observers (MFO) peacekeeping mission in the
Sinai. The second objective is to estimate the effect of these gains/losses on soldiers’ intentions to remain in their respective
component until retirement. Data for a population of approximately 500 soldiers were collected during their predeployment
training at Fort Bragg, NC and during deployment at the South Camp in the Sinai. Results of these analyses revealed that AC
soldiers perceived a small financial loss ($102 per month) and RC soldiers perceived considerable financial gain ($335 per
month). Therefore, soldiers experienced net average financial gains ($233 per month). Regression results for change in
financial status revealed that civilian earnings were negatively related to financial gains of the RC. Regression results for
career commitment revealed that the soldiers’ likelihood of staying in their respective component until retirement increased
with financial gains, while statistically controlling for satisfaction with Army life and demographic variables.

15. SUBJECT TERMS
Peacekeeping Multinational Force and Observers Reserve Components
The Sinai 28th Rotation

‘SECURITY CLASSIFICATION OF 49. LIMITATION OF | 20. NUMBER | 21. RESPONSIBLE PERSON

ABSTRACT OF PAGES (Name and Telephone Number)
16. REPORT 17. ABSTRACT | 18. THIS PAGE

Unclassified | Unclassified | Unclassified | Unlimited 358 Hyder Lakhani
(703) 617-8104



the overall mission because they gained $722.27 ($554 + $218.22) during the training phase, but
lost $386.59 ($287.42 + $99.17) during the deployment phase.

Table 28 shows that perceived financial gains during training were greater for the RC than the
AC. For example, while only 5% of the AC reported monthly gains of $501/month or more,
almost 50% of the RC reported this level of gain. Greater gains made by the RC can be
attributed to receiving higher amounts of basic military pay and allowances compared to the drill
pay received as part of reserve status, plus civilian earnings. As noted earlier, 55% of RC
soldiers were either unemployed, underemployed, or in school so their civilian earnings losses
were not substantive. The preceding outcome was reversed during the deployment phase because
financial gains were greater for the AC than the RC. The incremental gains to the AC during
deployment were due to the receipt of additional allowances such as foreign duty pay by the
enlisted soldiers. These allowances were not paid to AC soldiers during training (prior to
deployment in the Sinai).

Table 29 shows the results of the perceived financial losses to AC and RC soldiers. The AC
reported greater losses during training compared to the RC (26.8% vs. 5.2% losses in the $101-
$500 range and 42.3% vs. 25.4% losses in the $501+ range). Greater financial losses to AC
soldiers are attributed to the loss of jump duty pay that was received by most of these soldiers
who were deployed from the 82nd Airborne. Losses to the RC are attributed to volunteers who
had civilian jobs which were lost when they volunteered for the mission. As noted earlier,
almost 45% of RC soldiers were employed full-time and an additional 13% were employed part-
time.

Calculation of the average (arithmetic mean) net effect of financial gains and losses revealed
that, during the training phase, the RC made a net gain (gain minus loss), and the AC had a net
loss. For example, the RC had a monthly average gain of $163.74 ($298.58 gain minus $134.84
loss) and the AC had an average loss of $122.61 ($30.91 gain minus $153.52 loss). During the
deployment phase, both components made average net financial gains. These were $119.05
($218.22 minus $99.17) for the RC and $52.58 ($101.69 minus $49.11) for the AC. Therefore,
the deployment phase was financially beneficial to both the groups of soldiers.

Table 27

Comparison of Mean Gains and Losses during Training and Deployment Phases

AC RC
Gain $ Loss $ Gain $ Loss $
Phase M n M n M n M n
Training 45.40 55 200.29 71 554.05 233 287.42 207
Deployment 101.69 59 49.11 56 218.22 225 99.17 241

28



RC was very low because almost 77% of the soldiers had worked for less than a year at their
current jobs (Table 12). Consequently, their civilian earnings were also low, with the typical
amount being only up to $1,000 in 1993 (Table 13). Similarly, their weekly civilian earnings
were low, with the typical value being in the $301-$500/week range (Table 14).

Demographics. The age distribution of the soldiers revealed that most of the RC soldiers
were very young, junior in rank (E1 to E4), and unmarried. AC soldiers were mostly NCOs,
older, married, and with dependent children. Approximately two-thirds of all soldiers were not
married (63% were not married and 4% were separated) and only one-third were married (Table
15). Home ownership of the soldiers suggested that most (82%) did not own their homes (Table
15). The average (arithmetic mean) educational level of the soldiers was 4.23 or | to 2 years of
college.

Career commitment. When asked about career intentions during deployment, most soldiers
(56%) reported that their intentions to stay in the Army remained unchanged from the training
phase. However, more soldiers said their intention to stay had increased (27%) than those who
reported a decline in career intentions (5%) (Table 16).

Table 1

Self-Reported Basic Monthly Pay during Training (N = 390)

Basic Pay $/Month Freq. %
$0 - $500 8 2.1
$501 - $1,000 45 11.5
$1,001 - $1,500 236 60.5
$1,501 - $2,000 60 15.4
$2,001 - $3,000 41 10.5
Table 2

Self-Reported Basic Allowance for Quarters (BAQ) during Training (N = 278)

BAQ $/Month Freq. %
$0 - $100 100 36.0
$101 - $200 12 43
$201 - $300 37 13.3
$301 - $400 50 18.0
$401 and above 79 28.4

16



U.S. ARMY RESEARCH INSTITUTE
FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency Under the Jurisdiction
of the Deputy Chief of Staff for Personnel

EDGAR M. JOHNSON
Director

ee .

Technical review by

Joan Harman
Abraham Nelson

NOTICES

I. Please addré

correspondenct ‘ Institute for the
Behavioral and SocialSei : PERI-STP, dist Ave., Alexandria, Virginia
22333-5600

FINAL DISPOSITION: This report may be destroyed when it is no longer needed. Please do not
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NOTE: The findings in this report are not to be construed as an official Department of the Army
position, unless so designated by other authorized documents.



Table 36

Comparison of Control Group and Study Group Civilian Earnings

Control Group Volunteer Group
(N = 85) (N = 285)
($/Year) Freq. % Freq.  %
$0 - $1,000 0 0.0 14 49
$1,000 - $3,000 0 0.0 25 8.8
$3,001 - $6,000 0 0.0 28 9.8
$6,001 - $10,000 2 24 31 10.9
$10,001 - $15,000 1 1.2 42 14.7
$15,001 - $25,000 17 20.0 88 30.9
$25,001 - $35,000 20 23.5 35 12.3
$35,001 - $45,000 16 18.8 15 5.3
$45,000 or more 29 34.1 7 2.5
M $41,100 $16,670
Median $36,944 $15,212
Table 37

1994 Earnings of Control Group and Study Group by Rank

Control Group Study Group
(N= 101) (N = 400)

($/Year) E1-E4 E5+ E1-E4 E5+
Mean
Civilian NA 40,035 14,320 23,314
Military NA 11,058 4,349 13,681
Median
Civilian NA 37,000 12,000 21,000
Military NA 7,000 2,366 10,000

NA = Not applicable, none in the group

40



Table 17

Self-Reported Basic Monthly Pay of AC and RC during Training

AC RC
Basic Pay $/Month Freq. _% Freq. %
$0 - $500 - - 7 24
$501 - $1,000 - - 43 14.9
$1,001 - $1,500 38 46.9 185 64.2
$1,501 - $2,000 25 30.9 32 11.1
$2,001 - $3,000 18 22.2 21 73
Total (N) 81 100.0, 288 100.0
Table 18

Self-Reported Basic Allowance for Quarters (BAQ) of AC and RC during Training

AC RC

BAQ $/Month Freq.  % Freq.  %

$0 - $100 9 14.8 8541.5
$101 - $200 - - 12 5.9
$201 - $300 4 6.6 33 16.1
$301 - $400 14 23.0 36 17.6
$401 and above 34 55.7 39 19.0
Total (N) 61 100.0 205 100.0

Table 19

Self-Reported Basic Allowance for Subsistence (BAS) of AC and RC during Training

AC RC
BAS $/Month Freq. % Freq. %
$0 - $100 14 25.0 118 76.6
$101 - $200 26 46.4 22 14.3
$201 - $300 14 25.0 11 TA
$301 and above 2 3.6 3 1.9
Total (N) 56 100.0 154 100.0

24



Independent variables entered in block four were demographic variables: race, marital status,
and level of educational attainment. This set of variables did not contribute significant variance
to the prediction of career intentions. Therefore, these demographic variables were not crucial in
explaining career intentions.

For the deployment phase analysis, the financial gain/loss variable was also entered in block
one to predict career intentions. The results reveal that this financial variable accounts for a
significant portion of variance in explaining career intention during deployment. Thus, increases
in financial gains during the deployment phase are associated with a greater likelihood of
remaining in the military until retirement.

Army satisfaction, entered in block two, explained significant variance in addition to the
financial independent variable in block one. This variable had a positive, linear relationship with
career commitment. Thus, during the deployment phase, soldiers satisfied with Army life
indicated they were more likely to remain in the Army until retirement.

Independent variables entered in block three were basic monthly pay and force component
(RC). Block three variables did not add significant variance in excess of the Army satisfaction
and change in financial status variables. During the deployment phase, force component does not
have a significant linear relationship with career intentions. This result differs from the result
obtained during the training phase. In the deployment data analysis, Army satisfaction was
included as an independent variable. To identify potential reasons for the different results, force
component and monthly pay were re-analyzed, excluding Army satisfaction from the second
equation. This structure parallels the training phase analysis. The results indicated that force
component did not have a significant relationship with career intentions. However, when Army
satisfaction was included in the equation, the regression coefficient for RC increased. It appears
that force component was suppressed by Army satisfaction and hence, does not predict career
intentions at the time of deployment. When RC soldiers faced the realities of deployment, their
career commitment declined substantially and was not different from career commitment levels
of AC soldiers.

The independent variables entered in block four were demographic variables of race, marital
status, and educational attainment. This set of variables did not contribute significant variance to
the prediction of career intentions.

Test of Equality of Regression Coefficients. Separate regression equations were estimated for
the RC and AC during the training and deployment phases to test the null hypothesis that the
parameters are not different for the AC and RC. Regression coefficients from each equation
were compared to the overall model to test for equivalence of the coefficients across the two
regressions. In the original model, force component was included as a dummy-coded variable.
Since we estimated separate equations for each component, this variable was no longer
appropriate. Therefore, the pooled equation was re-estimated by dropping the component
variable. Table 33 summarizes the results presented below.

33



Table 8

Self-Reported Financial Gain and Loss during Training (N = 634)

$/Month Freq. %
Gain (N = 320)
$0 - $200 165 51.6
$201 - $400 12 3.8
$401 - $1,000 28 8.8
$1,001 - $1,500 11 3.4
$1,501 - $2,000 6 19
$2,001 and above 98 30.6
Loss (N = 314)
$0 - $200 204 65.0
$201 - $400 14 45
$401 - $1,000 21 6.7
$1,001 - $1,500 15 48
$1,501 - $2,000 9 2.9
$2,001 and above 51 16.1
Table 9

Years of Civilian Service of RC Soldiers (N = 341)

Years of Service Freq. %

Less than 2 247 72.4
3-4 40 11.7
5-6 22 6.5
7-8 11 3.2
9-10 10 2.9
11 or more 11 3.2

19



Sociologists generally concentrate on the effects of military service on educational or
occupational attainment of soldiers. Educational attainment refers to higher levels of schooling;
occupational attainment refers to an index of prestige within an occupation. Mason (1970) and
Fligstein (1976) found that veterans of World War II and the Korean War had significantly
higher levels of occupational attainment than non-veterans. However, studies that sampled
Vietnam War veterans revealed that occupational or educational attainment was lower for this
group compared to non-veterans (Card, 1983; Cohen, Segal, & Temme, 1992). These results
support findings of economic studies which have concluded that earnings of Vietnam era
veterans were lower than non-veterans due to lower levels of educational attainment.

Gade, Lakhani, and Kimmel (1991) concluded that post-Vietnam era veterans obtained social-
psychological benefits such as self-pride, self-confidence, ability to work with others, self-
discipline, leadership ability, establishing independence, respect for authority, and the
development of new skills. Schroyer, Hansen, Lerro, and Benedict (1990) administered a survey
to American business executives regarding attitudes and perceptions of veterans in the civilian
work force. Results indicated that employers value the attributes that may be acquired by Army
veterans. In addition, survey results indicated that, in general, employers believe that Army
veterans possess greater levels of desired skills and abilities than nonveteran job applicants.

The research outlined above illustrates differing perspectives (i.e, economic, sociological, and
psychological) regarding the effects of active military service on post-service developments. In
addition, a theoretical framework is presented for organizing the literature in this domain.

LITERATURE REVIEW

The relative importance of reservist soldiers in the military is increasing given the rise in
military commitments and the greater drawdown of the active-duty force (Lakhani, 1995). The
Air Force has already implemented a plan that relies on reservists to fly cargo planes, aerial
tankers, and fighters around the world. The Army implemented a similar plan as part of the
MFO Task Force (Matthews, 1995).

A reserve job is a part-time volunteer assignment and is similar to a civilian part-time job in a
number of ways. Both groups of jobholders come from diverse backgrounds, select part-time
work for a variety of reasons, and fill jobs in different occupations (Thomas & Kocher, 1993).
The reserve job also differs substantially from civilian part-time jobs. The National Guard
component of the reserve force primarily involves combat infantry missions and is committed to
a specified length of service. Reservists must be interested in "military service, meet enlistment
standards, complete initial training, and adapt to the military environment" (Thomas & Kocher,
1993, p. 340). Most reservists accrue eligibility for retirement benefits, compared to less than
20% of part-time civilian workers (Blank, 1990, as cited in Thomas & Kocher, 1993).

Selected reservists may participate in missions that present family and/or job conflicts. As
recent events in the Middle East have shown, reserve participation may include the risk of
civilian job disruption and family separation if a reservist is "activated" (Thomas & Kocher,
1993). As such, officials are concerned about the impact on reservists’ families, civilian jobs,

3



Table 38

Comparison of Spouse Earnings of Control Group and Study Group

Control Group Study Group

(N=52) (N=128)
$/Year Freq. % Freq. %

$0 - $1,000 0 0.0 45 35.2

$1,001 - $3,000 2 3.8 11 8.6
$3,001 - $6,000 4 717 11 8.6
$6,001 - $10,000 5 9.6 14 10.9
$10,001 - $15,000 4 17 15 11.7
$15,001 - $25,000 11 21.2 15 11.7
$25,001 - $35,000 20 38.5 10 78
$35,001 - $45,000 4 V7 3 2.3
$45,001 and above 2 3.8 4 3.1
M $23,115 $10,418
Median $25,000 $ 5,200

SUMMARY AND CONCLUSIONS

In this report, we analyzed the impact of volunteering for the MFO peacekeeping mission on
the 28th rotation soldiers. We reviewed the literature on civilian earnings and retention
intentions of reservist soldiers. A survey of 28th rotation soldiers (N=500) was conducted during
training and deployment phases. A survey of non-volunteers (N=101) was also conducted to
compare their socio-economic status with the study group of RC volunteers. Analysis of these
data resulted in the following major conclusions:

© Based on a review of the literature, the costs of deployment of the AC versus
the rainbow battalion (80% RC and 20% AC) did not differ substantially.

e RC volunteers were mostly younger, junior in rank, unmarried, and were either
unemployed, underemployed, or in school.

e RC soldiers realized an average net financial gain ($335/month) and AC

soldiers realized an average net average loss ($102/month) from the overall
mission of the Sinai.

41



REFERENCES

Angrist, J. D. (1989). Using the draft lottery to measure the effects of military service on civilian
labor market outcomes. In R. Ehrenberg (Ed.), Research in labor economics (Vol. 10, pp.
265-310). Greenwich, CT: JAI Press.

Angrist, J. D. (1990). Lifetime earnings and the Vietnam ear draft lottery: Evidence from Social
Security Administration records. American Economic Review, 80, 313-336.

Angrist, J. D., & Krueger, A. B. (1994). Why do World War II veterans earn more than
nonveterans? Journal of Labor Economics, 12(1), 74-97.

Berger, M. C., & Hirsch, B. T. (1983). The civilian earnings experience of Vietnam-era veterans.
Journal of Human Resources, 18, 455-479.

Brinkerhoff, J. R., & Horowitz, S. A. (1995, May). Case studies in Reserve Component
volunteerism: A composite battalion task force for the U.S. Army element of the
multinational force and observers mission, Sinai (Report IDA Document D-1665, pp. 1-
11). Alexandria, VA: Institute for Defense Analysis.

Browning, H. L., Lopreato, S. C., & Poston, D. L. (1973). Income and veteran status: Variations
among Mexicans, Blacks, and Anglos. American Sociological Review, 38, 74-85.

Bryant, R., & Wilhite, A. (1990). Military experience and training effects on civilian wages.
Applied Economics, 22, 69-81.

Bryant, R. R., Samaranayake, V. A., & Wilhite, A. (1993). The effects of military service on the
subsequent civilian wage of the post-Vietnam veteran. Quarterly Review of Economics
and Finance, 33(1), 15-31.

Burright, B., Grissmer, D. W., & Doering, Z. D. (1982). A model of reenlistment decisions of
Army national Guardsmen (Report R-2866-MRAL). Santa Monica, CA: RAND.

Card, J. (1983). Lives after Vietnam. Lexington, MA: Lexington Books.

Cohen, J., Segal, D. R., & Temme, L. V. (1992). The impact of education on Vietnam-era
veterans’ occupational attainment. Social Science Quarterly, 73(2), 397-409.

Cotton, J. L., & Tuttle, J. M. (1986). Employee turnover: A meta-analysis and review with
implications for research. Academy of Management Review, 11, 55-70.

Crane, J. R.; & Wise, D. A. (1987). Military service and the civilian earnings of youths. In D. A.
Wise (Ed.), Public sector payrolls (pp. 119-137). Chicago: University of Chicago Press.

Easterlin, R. A. (1980). Birth and fortune. New York: Basic Books.

43



Cohen et al. (1992) analyzed occupational attainment of Vietnam era veterans and concluded that
lower occupational attainment was attributable to lower educational levels of veterans instead of
veteran status.

The explanations referred to above suggest that the observed correlation between veteran
status and civilian earnings is caused by military service. It is possible that other factors such as
war cohort, race, education, or type of training could moderate these effects (Martindale &
Poston, 1979). The sections below elaborate on this research.

War Cohorts

Some research has shown that World War II veterans benefitted from their military
experience, but Vietnam era veterans earn less than non-veterans in their cohort (Villamez &
Kasarda, 1976; Martindale & Poston, 1979; Sticht et al., 1987; Magnum & Ball, 1989; Phillips et
al., 1992; Xie, 1992; Bryant et al., 1993). Villamez and Kasarda (1976) provided descriptive
information on income differences between veterans and non-veterans, and income distributions
of veterans vs. non-veterans by race and war cohort (i.e., World War II, Korea, and Vietnam).
They conducted a path analysis postulating that income is a direct function of veteran status, age,
education, and occupation. They found that veterans generally reported higher incomes.
However, this pattern was reversed for the Vietnam cohort.

One hypothesis to explain civilian wage differences among war cohorts is that selection forces
are likely to induce a positive bias in estimates of the veteran premiums for World War II
veterans and a negative bias for Vietnam veterans (Angrist & Krueger, 1994). Mason (1970) and
Fligstein (1976) found that veterans of World War II and the Korean War had significantly
higher levels of occupational attainment than non-veterans. Studies that sampled Vietnam War
veterans revealed that occupational and educational attainment was lower for this group
compared to non-veterans (Card, 1983; Cohen et al., 1992). Demographic variables such as
education level may explain differences between cohort groups. Evidence suggests that college-
educated men from wealthy families avoided military service during the Vietnam period, while
low income men were unable to avoid the service.

Demographics

Demographic factors seem to play a significant role in explaining the relationship between
veteran status and civilian wages. For example, Martindale and Poston (1979) assessed race
differences from three war periods to determine economic effects on veterans vs. non-veterans.
In general, veterans had earnings (adjusted for inflation) advantages over non-veterans.
However, for whites and Mexican Americans, non-veterans fared better financially than veterans.

These findings are sustained among the World War II and Korean War cohorts. This suggests
that certain minorities may benefit from military experience once they rejoin the civilian
marketplace. Prior to military service, minority groups may be economically disadvantaged
compared to non-minorities in terms of jobs and salaries. Military experience for minority
groups may provide the skills to be more marketable than non-veterans with the same
backgrounds. Bryant et al. (1993) found similar results showing that the impact of military

6