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Spillover effects from government employment
Economics Letters North-Holland
101
39 (1992) 101-104
Spillover effects from government employment * Joyce P. Jacobsen Rhodes College, Memphis TN, USA Received Accepted
2 December 14 February
1991 1992
The indirect effects of government employment on hourly examined using Census data. The proportion of employment earnings regressions.
earnings for workers in both the public and private in an occupation that is governmental is significantly
sector are positive in
Researchers are in general agreement that wage-determination processes vary between the public and private sectors [see, e.g., Katz and Krueger (199111, and that federal jobs in particular pay higher wages than comparable private-sector jobs [see, e.g., Moulton (199O)l. However, measurement of the public-private wage differential may understate the full effect that government has on wages. Government hiring at wages above the private sector level may push wages up in the private sector as well for occupations which experience heavy governmental demand. Regression analysis is used to test for significance of PCTG, the proportion of each occupation consisting of government employees, on earnings in both the public and private sectors. Alternatively, this variable may be measuring an innate characteristic of the particular occupation, such as indexing the desirability of the job, or it may be capturing a feature of the nature of employers or of members of that occupation. The interpretations are a priori indistinguishable. Nevertheless, it is useful to see if there is any relationship between this variable and earnings, as a lack of such a relationship would imply that governmental involvement in the labor force as an employer has no readily measurable effect on overall earnings. Results are calculated using the l/100 C sample of microdata from the 1980 U.S. Census of Population and Housing. From this set are extracted all wage or salary earners, ages 25-64, who did not work in a farming-related occupation and who reported working an average of thirty or more hours per week in the previous year, for a total of 577,192 workers. Equations are estimated Correspondence to: Joyce P. Jacobsen, Department of Economics and Business Administration, Rhodes College, 2000 North Parkway, Memphis, TN 38112, USA. * Full results for all regressions reported in this paper are available from the author upon request. The data utilized in this paper were made available by the Interuniversity Consortium for Political and Social Research. The data for the 1960, 1970, and 1980 Censuses of Population and Housing and the March 1986 and 1990 Current Population Surveys were originally collected and prepared by U.S. Dept. of Commerce, Bureau of the Census. Neither the collector of the original data nor the Consortium bears any responsibility for the analyses or interpretations presented here. Helpful comments from Victor Fuchs, Tom MaCurdy, and John Pencavel are gratefully acknowledged. 0165-1765/92/$05.00
0 1992 - Elsevier
Science
Publishers
B.V. All rights reserved
102
J. P. Jacobsen / Spillol,er ejjkts from golwnmmt
employmrnl
separately for four race-sex groups - white men, white women, nonwhite men, and nonwhite women, and for the four race-sex groups for private and public sector workers. The dependent variable throughout the regression analysis is the natural log of estimated hourly earnings for each individual. This estimate is constructed using three reported variables: total wage or salary income for 1979; weeks worked in 1979; and usual hours worked per week in 1979. Total yearly hours, obtained by multiplying the latter two variables together, is capped at 3500. The variables used as regressors besides PCTG are: _ controls for human capital, personal characteristics, and geographical variation: Age, age-squared, education, education-squared, experience (a dummy variable = 1 if person was working five years ago), three city-size dummies, marital status, veteran status (if male), and number of children ever born (if female); - controls for direct effects of government employment: Indication of federal (FED), state (STATE), or local (LOCAL) government worker status; _ controls for other occupational characteristics: Proportion female (PCTF), nonwhite (PCTNW), and those working 30 hours or less per week (PCTPT). PCTG, PCTF, PCTNW and PCTPT are calculated at the three-digit occupational level for the 496 nonfarming Census occupational classes. A point of concern is the omission of significant variables which may be correlated with PCTG. However, many omitted variables which may have an effect on earnings, including plant size, firm size, and job characteristics such as physical strength required, are correlated with PCTF and PCTNW. In the case of PCTPT, it is likely that occupations with a large percentage of part-time workers and nonwhite workers would also pay less for a variety of reasons. Part-time workers lead to higher quasi-fixed costs for employers, may be less productive, and employees may be willing to forego higher pay in exchange for greater flexibility. While it is possible that these omitted variables might exert some influence through PCTG as well, the inclusion of these occupational-level variables may diminish the omitted variable effect on the coefficient of PCTG. The simple correlation coefficients between these variables and PCTG indicate orthogonality (0.04 for PCTF, -0.12 for PCTNW, and 0.16 for PCTPT), so their relative effects on hourly earnings should be separable. Tables 1 and 2 display coefficients on the direct and indirect measures of government influence. In table 1, the coefficients on FED, STATE, and LOCAL are consistent with the work of other researchers, showing a positive federal premium for all groups; negative returns for men and positive returns for women in the state and local sectors relative to the private sector. The coefficient on the measurement of indirect effects, PCTG, is significantly positive for all groups of
Table 1 1980 Census,
coefficients
on government
variables
White men FED STATE LOCAL
0.09 a -0.11 i1 -0.13 “
PCTG
0.06 a
LNHREARN N “ Statistically
2.06 303,527 significant
at the 0.95 confidence
from log of hourly
White women 0.16 i1 0.04 a 0.05 a 0.18 a 1.58 189.73 1 level.
earnings Nonwhite 0.12 I - 0.06 .’ - 0.06 “ 0.14 i1 1.78 44,616
equations. men
by race-sex
group.
Nonwhite 0.18 >’ 0.03 I 0.04 a 0.23 .’ 1.49 39.318
women
J.P. Jacobsen / Spillocer effects from government employment Table 2 1980 Census,
coefficients
on government
variables
from log of hourly
Public
Private
Private
Public
Private
equations,
Nonwhite
White women
White men
earnings
103
by race-sex
group
Nonwhite
men Public
Private
FED STATE
_
0.23 a 0.01
_ _
0.14 = 0.01
_ -
0.19 a 0.00
_ _
PCTG
0.10 a
0.06 a
0.15 a
0.20 B
0.14 a
0.16 a
0.25 ”
Dep. mean N a Statistically
2.05 248,723 significant
2.07 54,804
1.52 144,549
at the 0.95 confidence
1.75 45,182
1.76 34,123
1.86 10,493
and sector.
women Public 0.15 >’ - 0.01 0.21 a
1.41 26,934
1.66 12,384
level.
workers, both overall (table l), and in the private and public sectors taken separately (table 2). The effect of this variable is larger for women than for men, and larger for nonwhites than for whites by sex. To determine the stability over time of this result, the analysis was repeated using microdata samples from the 1960 and 1970 Censuses of Population, and the March 1986 and March 1990 Current Population Surveys. The regression specifications vary between the samples due to differing availability of variables noncentral to the analysis. However, PCTG follows roughly the same patterns as in 1980, again affecting male earnings less than female earnings. The magnitude of the effect declines over time for women (coefficient of 0.29 and 0.59 in 1960 for white and nonwhite women respectively, compared to coefficients of 0.04 and 0.10 in 1990). Finally, specifying the overall effect of governmental demand in particular labor markets as a continuous variable does not allow for nonlinearities. One alternative hypothesis is that until PCTG is quite large, the effects of governmental participation in the labor market might not be noticeable. To check for the existence of such nonlinearities, two alternative dummy variable specifications for level of governmental share in total occupational employment were used. The first specification uses three dummies to denote the percentage of employment in the occupation
Table 3 1980 Census, sector.
coefficients
on percent
government
White men
dummies
from log of hourly
White women
earnings
Nonwhite
equations,
men
by race-sex
Nonwhite
Private
Public
Private
Public
Private
Public
Private
0.05 a - 0.04 a -0.18 a
0.02 = 0.06 a 0.04 a
0.10 a - 0.02 - 0.03 a
0.07 a 0.10 a 0.20 a
0.03 a 0.14 a -0.14
0.02 0.15 a 0.13 a
0.11 a 0.08 * 0.09 a
0.05 0.06 0.08 0.08
0.09 0.10 0.12 a 0.20 a
0.04 0.07 0.15 0.12
group
women Public
Specification 1 GOV1550 GOV5185 GOVGT85
0.10 a 0.13 :’ 0.22 n
Specification 2 GOV0207 GOV0816 GOVI 736 GOVGT36 a Statistically
0.08 0.10 0.12 0.08 significant
a a a a
0.08 0.11 0.11 0.15
a a a a
at the 0.95 confidence
0.07 0.11 0.16 0.11 level
a a ’ a
0.09 0.18 0.21 0.29
a a a a
a a a a
B a a a
- 0.09 0.01 0.10 a 0.15 a
and
104
J.P. Jacobsen /
Spilhw effectsfromgocwwnentemployment
which is governmental as being between 15 and 50 percent (GOVZ5501, 50 to 85 percent (GOV518.5), or greater than 85 percent (GOVGT85). The second specification uses four dummies for the ranges for 2 to less than 7 percent (GOVO207), 7 to less than 16 percent (GUVO7161, 16 to 36 percent (GOVl636), and greater than 36 percent (GOVGT36). The first specification was chosen to provide symmetrical numerical break points for the percentages. Sixty percent of occupations (and persons) are in the omitted class, while only 0.4 percent of occupations and 7.5 percent of the workers are in the category where government employment comprises over 85 percent of the occupation. The second specification was chosen so that about one-fifth of the sample of occupations, and of people, are in each category. Table 3 contains results for these specifications by race-sex group and sector. Some strong nonlinear patterns arise when these regressions are analyzed and the two regression specifications yield different results. For example, for white women in the private sector, the first specification yields a positive effect for GOVI550, but a negative coefficient for GOVGT85. In the second specification the coefficients increase through GOV1636, and then decline for GOVGT36, but are all positive. The magnitudes of the effects are still larger and positive in general for women than for men. In terms of affecting the overall fit of the regressions, these specifications do not differ from those regressions represented in table 2. However, it is difficult to find clear patterns in these results on how governmental presence affects overall wage levels in particular labor markets. In conclusion, while it is difficult to arrive at a clear-cut theoretical interpretation of this ‘spillover effect’, similar to the difficulty in interpreting the positive effect of percent unionized on earnings, the evidence presented in this paper supports the idea that governmental labor demand raises hourly earnings in both the public and private sectors.
References Katz, L.F. and A.B. Krueger, 1991, Changes in the structure of wages in the public and private sectors, Working Moulton, B.R., 1990, A reexamination of the federal-private wage differential in the United States. Journal Economics 8, 270-293.
paper. of Labor
101
39 (1992) 101-104
Spillover effects from government employment * Joyce P. Jacobsen Rhodes College, Memphis TN, USA Received Accepted
2 December 14 February
1991 1992
The indirect effects of government employment on hourly examined using Census data. The proportion of employment earnings regressions.
earnings for workers in both the public and private in an occupation that is governmental is significantly
sector are positive in
Researchers are in general agreement that wage-determination processes vary between the public and private sectors [see, e.g., Katz and Krueger (199111, and that federal jobs in particular pay higher wages than comparable private-sector jobs [see, e.g., Moulton (199O)l. However, measurement of the public-private wage differential may understate the full effect that government has on wages. Government hiring at wages above the private sector level may push wages up in the private sector as well for occupations which experience heavy governmental demand. Regression analysis is used to test for significance of PCTG, the proportion of each occupation consisting of government employees, on earnings in both the public and private sectors. Alternatively, this variable may be measuring an innate characteristic of the particular occupation, such as indexing the desirability of the job, or it may be capturing a feature of the nature of employers or of members of that occupation. The interpretations are a priori indistinguishable. Nevertheless, it is useful to see if there is any relationship between this variable and earnings, as a lack of such a relationship would imply that governmental involvement in the labor force as an employer has no readily measurable effect on overall earnings. Results are calculated using the l/100 C sample of microdata from the 1980 U.S. Census of Population and Housing. From this set are extracted all wage or salary earners, ages 25-64, who did not work in a farming-related occupation and who reported working an average of thirty or more hours per week in the previous year, for a total of 577,192 workers. Equations are estimated Correspondence to: Joyce P. Jacobsen, Department of Economics and Business Administration, Rhodes College, 2000 North Parkway, Memphis, TN 38112, USA. * Full results for all regressions reported in this paper are available from the author upon request. The data utilized in this paper were made available by the Interuniversity Consortium for Political and Social Research. The data for the 1960, 1970, and 1980 Censuses of Population and Housing and the March 1986 and 1990 Current Population Surveys were originally collected and prepared by U.S. Dept. of Commerce, Bureau of the Census. Neither the collector of the original data nor the Consortium bears any responsibility for the analyses or interpretations presented here. Helpful comments from Victor Fuchs, Tom MaCurdy, and John Pencavel are gratefully acknowledged. 0165-1765/92/$05.00
0 1992 - Elsevier
Science
Publishers
B.V. All rights reserved
102
J. P. Jacobsen / Spillol,er ejjkts from golwnmmt
employmrnl
separately for four race-sex groups - white men, white women, nonwhite men, and nonwhite women, and for the four race-sex groups for private and public sector workers. The dependent variable throughout the regression analysis is the natural log of estimated hourly earnings for each individual. This estimate is constructed using three reported variables: total wage or salary income for 1979; weeks worked in 1979; and usual hours worked per week in 1979. Total yearly hours, obtained by multiplying the latter two variables together, is capped at 3500. The variables used as regressors besides PCTG are: _ controls for human capital, personal characteristics, and geographical variation: Age, age-squared, education, education-squared, experience (a dummy variable = 1 if person was working five years ago), three city-size dummies, marital status, veteran status (if male), and number of children ever born (if female); - controls for direct effects of government employment: Indication of federal (FED), state (STATE), or local (LOCAL) government worker status; _ controls for other occupational characteristics: Proportion female (PCTF), nonwhite (PCTNW), and those working 30 hours or less per week (PCTPT). PCTG, PCTF, PCTNW and PCTPT are calculated at the three-digit occupational level for the 496 nonfarming Census occupational classes. A point of concern is the omission of significant variables which may be correlated with PCTG. However, many omitted variables which may have an effect on earnings, including plant size, firm size, and job characteristics such as physical strength required, are correlated with PCTF and PCTNW. In the case of PCTPT, it is likely that occupations with a large percentage of part-time workers and nonwhite workers would also pay less for a variety of reasons. Part-time workers lead to higher quasi-fixed costs for employers, may be less productive, and employees may be willing to forego higher pay in exchange for greater flexibility. While it is possible that these omitted variables might exert some influence through PCTG as well, the inclusion of these occupational-level variables may diminish the omitted variable effect on the coefficient of PCTG. The simple correlation coefficients between these variables and PCTG indicate orthogonality (0.04 for PCTF, -0.12 for PCTNW, and 0.16 for PCTPT), so their relative effects on hourly earnings should be separable. Tables 1 and 2 display coefficients on the direct and indirect measures of government influence. In table 1, the coefficients on FED, STATE, and LOCAL are consistent with the work of other researchers, showing a positive federal premium for all groups; negative returns for men and positive returns for women in the state and local sectors relative to the private sector. The coefficient on the measurement of indirect effects, PCTG, is significantly positive for all groups of
Table 1 1980 Census,
coefficients
on government
variables
White men FED STATE LOCAL
0.09 a -0.11 i1 -0.13 “
PCTG
0.06 a
LNHREARN N “ Statistically
2.06 303,527 significant
at the 0.95 confidence
from log of hourly
White women 0.16 i1 0.04 a 0.05 a 0.18 a 1.58 189.73 1 level.
earnings Nonwhite 0.12 I - 0.06 .’ - 0.06 “ 0.14 i1 1.78 44,616
equations. men
by race-sex
group.
Nonwhite 0.18 >’ 0.03 I 0.04 a 0.23 .’ 1.49 39.318
women
J.P. Jacobsen / Spillocer effects from government employment Table 2 1980 Census,
coefficients
on government
variables
from log of hourly
Public
Private
Private
Public
Private
equations,
Nonwhite
White women
White men
earnings
103
by race-sex
group
Nonwhite
men Public
Private
FED STATE
_
0.23 a 0.01
_ _
0.14 = 0.01
_ -
0.19 a 0.00
_ _
PCTG
0.10 a
0.06 a
0.15 a
0.20 B
0.14 a
0.16 a
0.25 ”
Dep. mean N a Statistically
2.05 248,723 significant
2.07 54,804
1.52 144,549
at the 0.95 confidence
1.75 45,182
1.76 34,123
1.86 10,493
and sector.
women Public 0.15 >’ - 0.01 0.21 a
1.41 26,934
1.66 12,384
level.
workers, both overall (table l), and in the private and public sectors taken separately (table 2). The effect of this variable is larger for women than for men, and larger for nonwhites than for whites by sex. To determine the stability over time of this result, the analysis was repeated using microdata samples from the 1960 and 1970 Censuses of Population, and the March 1986 and March 1990 Current Population Surveys. The regression specifications vary between the samples due to differing availability of variables noncentral to the analysis. However, PCTG follows roughly the same patterns as in 1980, again affecting male earnings less than female earnings. The magnitude of the effect declines over time for women (coefficient of 0.29 and 0.59 in 1960 for white and nonwhite women respectively, compared to coefficients of 0.04 and 0.10 in 1990). Finally, specifying the overall effect of governmental demand in particular labor markets as a continuous variable does not allow for nonlinearities. One alternative hypothesis is that until PCTG is quite large, the effects of governmental participation in the labor market might not be noticeable. To check for the existence of such nonlinearities, two alternative dummy variable specifications for level of governmental share in total occupational employment were used. The first specification uses three dummies to denote the percentage of employment in the occupation
Table 3 1980 Census, sector.
coefficients
on percent
government
White men
dummies
from log of hourly
White women
earnings
Nonwhite
equations,
men
by race-sex
Nonwhite
Private
Public
Private
Public
Private
Public
Private
0.05 a - 0.04 a -0.18 a
0.02 = 0.06 a 0.04 a
0.10 a - 0.02 - 0.03 a
0.07 a 0.10 a 0.20 a
0.03 a 0.14 a -0.14
0.02 0.15 a 0.13 a
0.11 a 0.08 * 0.09 a
0.05 0.06 0.08 0.08
0.09 0.10 0.12 a 0.20 a
0.04 0.07 0.15 0.12
group
women Public
Specification 1 GOV1550 GOV5185 GOVGT85
0.10 a 0.13 :’ 0.22 n
Specification 2 GOV0207 GOV0816 GOVI 736 GOVGT36 a Statistically
0.08 0.10 0.12 0.08 significant
a a a a
0.08 0.11 0.11 0.15
a a a a
at the 0.95 confidence
0.07 0.11 0.16 0.11 level
a a ’ a
0.09 0.18 0.21 0.29
a a a a
a a a a
B a a a
- 0.09 0.01 0.10 a 0.15 a
and
104
J.P. Jacobsen /
Spilhw effectsfromgocwwnentemployment
which is governmental as being between 15 and 50 percent (GOVZ5501, 50 to 85 percent (GOV518.5), or greater than 85 percent (GOVGT85). The second specification uses four dummies for the ranges for 2 to less than 7 percent (GOVO207), 7 to less than 16 percent (GUVO7161, 16 to 36 percent (GOVl636), and greater than 36 percent (GOVGT36). The first specification was chosen to provide symmetrical numerical break points for the percentages. Sixty percent of occupations (and persons) are in the omitted class, while only 0.4 percent of occupations and 7.5 percent of the workers are in the category where government employment comprises over 85 percent of the occupation. The second specification was chosen so that about one-fifth of the sample of occupations, and of people, are in each category. Table 3 contains results for these specifications by race-sex group and sector. Some strong nonlinear patterns arise when these regressions are analyzed and the two regression specifications yield different results. For example, for white women in the private sector, the first specification yields a positive effect for GOVI550, but a negative coefficient for GOVGT85. In the second specification the coefficients increase through GOV1636, and then decline for GOVGT36, but are all positive. The magnitudes of the effects are still larger and positive in general for women than for men. In terms of affecting the overall fit of the regressions, these specifications do not differ from those regressions represented in table 2. However, it is difficult to find clear patterns in these results on how governmental presence affects overall wage levels in particular labor markets. In conclusion, while it is difficult to arrive at a clear-cut theoretical interpretation of this ‘spillover effect’, similar to the difficulty in interpreting the positive effect of percent unionized on earnings, the evidence presented in this paper supports the idea that governmental labor demand raises hourly earnings in both the public and private sectors.
References Katz, L.F. and A.B. Krueger, 1991, Changes in the structure of wages in the public and private sectors, Working Moulton, B.R., 1990, A reexamination of the federal-private wage differential in the United States. Journal Economics 8, 270-293.
paper. of Labor