World Bank Reprint Series: Number 261

David L. Lindauer and Richard H. Sabot

The Public/Private WageDifferential in a PoorUrban Economy

Reprinted with permission from Journal of Development Economics, vol. 12 (1983),pp. 137-52.

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Journal of Development Economics 12 (1983) 137-152. North-Holland Publishing Company

THE PUBLIC/PRIVATE WAGE DIFFERENTIALIN A POOR URBAN ECONOMY

David L. LINDAUER*Wellesley College, Wellesley, MA 02181, USA

Richard H. SABOT*

World Bank, Washington, DC 20433, USA

Received February 1981, final version received June 1982

This paper considers how wage differentials may be generated between the public and privatesectors of a developing economy. Data from a 1971 household survey of the Tanzanian urbanwage labor force are used to determine the pattern of wage differences across employer groups.After standardizing by worker characteristics, public sector employees are found to have earneda substantial wage premium over workers employed in the private sector. The non-marketcharacter of these differentials is examined in light of a number of hypotheses on public sectorwage determination.

1. Introduction

The occupational structure of wages is generally more compressed in highthan in low income countries. This may simply be due to the relative scarcityof educated workers, more generally of human capital, in poor nations. If sowe can expect the wage structure to be compressed in poor countries, withobvious distributional consequences, as human capital accumulates in thecourse of economic development. Alternatively, the large wage premiumsreceived, for example, by white collar workers may be due to non-marketforces brought to bear on the wage structure by trade unions, multinationalcorporations, or the government. In this case the evolution of the wagestructure in the course of development is less predictable.

The role of non-market forces in determining the structure of wages is ofinterest for reasons of allocative efficiency as well as for distributionalconcerns. There is a strong presumption that the greater the distortion of thewage structure by non-market forces the greater the inefficiences in the

*The authors would like to acknowledge the helpful comments of an anonymous referee. Wealso wish to thank Maurice Boissiere for his careful research assistance. The views reported hereare those of the authors and they should not be interpreted as reflecting the views of the WorldBank.

0304-3878/83/0000-0000/$03.00 t 1983 North-Holland

138 D.L. Lindauer and R.H. Sabot, The public/priv'ate wvage differential

allocation of human resources, with consequent negative implications for thepace of economic growth.

Our focus in this paper is on wage differentials between the public andprivate sectors in urban Tanzania in 1971. The general issue of public versusprivate compensation has not received nearly as much attention in highincome economies as, for example, wage differentials between unionized andnon-unionized establishments. In the United States this is because the'prevailing wage rate' model has been used both to determine and henceexplain government pay scales. The government is viewed as just anotherprice taker accepting a market-determined rate. In a perfectly competitivelabor market group affiliation does not influence wages. Irrespective ofdifferences among groups of workers in goods produced, in the technology ororganization used to produce them, in the profitability of such production, orin the ownership of the establishments in which they work, competition inthe labor market will ensure that all workers with the same personaleconomic characteristics and preferences for work activity receive the samerate of pay. If public/private wage differences occur, they are generallyinterpreted, within the competitive model, as due to short-run adjustmentproblems to lags in government wage movements.

Group affiliation matters only if non-market forces are sufficientlypowerful to prevent competiton in the market from eroding differentialsamong homogeneous workers. The public sector holds a commandingposition in the labor markets of many developing countries. It is notuncommon to find 50',, or more of all wage earners in the employ of thegovernment or of parastatals.' Moreover not all governments of developingcountries either choose or are in a position to choose the 'prevailing wage'model in setting their pay scales. Government pay policies are ofteninfluenced by distributional, fiscal, employment or political goals.2 In sum, inmany low income countries the public sector has neither the need nor thedesire, nor even the ability, to act as if it is another wage taker.

In order to study the relationship of public to private wages, data for thisanalysis were obtained from the 1971 NUMEIST 3 survey conducted by oneof the authors. A random sample of households in Dar es Salaam and sixother urban areas was surveyed. Over 5000 individuals including 1500 male

'The pay of government employees is generally governed by civil service pay codes.Parastatals are enterprises wholly or partly owned by the government but with some autonomyin factor and product pricing decisions. For a discussion of the relative size of government andparastatal employment in Africa see Lindauer (1981).

2There is evidence, for example, that in Tanzania, colonial wage and salary structures, gearedto the supply prices of Europeans, were not dismantled at Independence because to do awaywith what many regard-d as the Fruits of Independence would have been politically untenable.See Sabot (1979, p. 210).

3 National Urban Mobility, Employment and Income Survey of Tanzania.

D.L. Lindauer and R.H. Sabot, The public/private wage differential 139

African regular wage earners are included in the sample.4 Respondentsprovided information on their monthly earnings, non-wage benefits,education, employment history, and other personal characteristics, as well asthe type of employer they worked for. Roughly one third of the sample fellinto each employment category - private firms, government and parastatalenterprises.5 These proportions correspond to the distribution of employmentby firm type reported in the 1971 Tanzania, Survey of Employment and

Earnings.In section 2 below, we present measures of differences in mean wages

between government workers and workers in the employ of privately ownedenterprises, between parastatal employees and workers in private enterprisesand between parastatal and government employees. Both G, the absolutedifferential and x, the relative differential, are presented where G = Wa-Wb

and 0C=(Wa-Wb/Wb) with Wa representing the mean wage of the higherpaid group. Measures of G disaggregated by occupation level are alsopresented and hypotheses to explain the public/private differential thatremain are suggested. We go on to contrast a with the value of ,B, where ,Brepresents the average percentage by which the pay of group a exceeds thatof group b after standardizing for various personal characteristics of thewage labor force. Standardization is performed by estimating a simple wagefunction of the following general form: In WL = f(XL), where the log ofmonthly earnings of the urbani wage earner is the dependent variable and XL

is a vector of his characteristics. In addition to those characteristics generallyfound in both low and high income countries to be good predictors ofearnings, included among the independent variables are dummy variables forownership category of the worker's employer. The only other additionalfeature of the specification is a variable indicating whether the worker wasemployed in Dar es Salaam, the capital, or in one of the six smaller townsincluded in the sample. ,B is derived from the coefficient on the ownershipdummy denoting group a (the high paid group, with group b as the basecategory) in the earnings function for the full sample.6

In an aggregate earnings function such as this where the coefficients on theindependent variables are constrained to be the same for all ownershipgroups, /B can be a misleading indicator of the magnitude of standardizedwage differences between ownership groups if there are marked differences in

4Wage earners include employees of all firms, regardless of size. In this way this survey differsfrom most formal sector establishment surveys wlhich usually select some arbitrary, usually 10 or20, employment level as a cut-off point. Most African wage data are derived from such sourcesand thus exclude a sizeable proportion of private sector wage labor. Our sample does notexhibit this bias. Furthermore, since our sample is based on a household survey, it is not biasedtoward public employees as is often the case with establishment data which may suffer fromunderreporting of the private sector.

5Specifically, private firms accounted for 31.8°,,, government 29.7",, and parastatals 38.5",, ofall urban wage employment.

'See Halvorsen and Palmquist (1980) for derivation.

140 D.L. Lindauer and R.II. Sabot, The public/private wage differential

the 'wage structure' (coefficients in separate earnings functions) betweenparastatals, the government and private enterprises. Therefore, in section 3we examine the nature and degree of differences between ownershipcategories in the structure of earnings. The following stratifed regressionsare estimated and subjected to a series of Chow tests: In WGO = f(XG,);In Wp,f(Xpr); in Wpa =f(Xpa), where Go = government, Pr=private, andPa=parastatal and X is a vector of independent variables, in this case ofcourse, excluding the ownership dummies. These tests do not, however, allowone to determine whether differences between the stratified regressions aredue to differences in slopes or to differences in intercept terms. Therefore, weal'so estimate an interactive version of our aggregate earnings function.Specifically, we estimate the following equation:

In WL=a+bX+c(X * Go)+d(X Pa)+e, (1)

where a is the constant, and b, c and d are coefficients measuring respectivelythe impact of the independent variables on earnings in the private sector, theincremental impact of those variables for government workers, and theincremental impact of those variables for workers in the parastatal sector.

Having specified and measured as best we can the differences betweenprivate, government and parastatal establishments in the level and slope oftheir earnings functions, in section 4 we illustrate the impact of thesedifferences on the earnings of representative workers from each of theownership categories. The representative workers are constructs; thecharacteristics of the government worker, for example, are given by the meanvalue for all government workers of each of the independent variables. Foreach of the three representative workers we use the stratified wage functionsto predict, given their characteristics, what they would be paid in the othertwo ownership categories. The procedure we use, which is a simple form ofsimulation analysis, has been widely used in the analysis of labor marketdiscrimination in high income countries and is beginning to be applied inlow income countries.' In effcct we decompose the gross wage differencesbetween ownership categories into the parts (E) 'explained' by variousdifferences between categories in the characteristics of their labor force andthe unexplained residual (R) reflecting differences between categories in wagefunctions. In explaining the method we focus on government and privatesector employees. We assume that the mean wage of government workers isdetermined by the earnings function Wa= fa(Xa), where Xa are the meanvalues of a vector of characteristics. The mean wage that private sectoremployees would receive if they were paid according to the governrnent wage

Sece Blinder d19731. and Malkiel and Malkiel (1973i.'See Knight and Sabot (1982). Birdsall 11981), and Behrman and Wolfe (1981).

D.L. Lindauer and R.H. Sabot, The public, private wage differential 141

structure is fa(Xb). The gross difference between sectors is then decomposedas follows:

G W- -Wa b = (W - fa(Xb)) + (fa(Xb) - Wb)

- E + R.

A similar decomposition is obtained by substituting fb(Xa) for fa(Xb), i.e.,the wage received by government workers if they were paid according to theprivate sector wage structure. This procedure allows us to answer as best wecan the fundamental question addressed by this paper: how much of theobserved differences in mean earnings between ownership categories is duesimply to differences in composition; how much is due to various non-marketforces driving a wedge between employer categories in pay levels for workerswith the same characteristics? This section also summarizes and concludes.

2. Gross and standardized wage differentials

Table 1 reveals that in 1971 government urban employees earned 133 sh.(51°%) more, and parastatal employees 146sh. (56%) more than employees inprivately-owned establishments. 9 Table 2, however, indicates that, as is usual,labor demand in the government is much more skill-intensive than in theprivate sector. Because of these differences in composition the government-private differential for particular occupations is much less than thedifferential in mean earrnings. Indeed, table 1 indicates that in six of elevenoccupational categories the earnings advantage is to private firms. If theprivate sector had the occupational composition of the government theremaining differential in mean earnings between the two sectors would onlybe 16%,X and would be almost entirely due to the higher salaries of managersin the government than in the private sector.

With respect to skill intensity the parastatal sector falls between the othertwo and, therefore, differences in occupational composition do not explain asmuch of the parastatal-private as of the government-private gross wagedifferential. Parastatal earnings are higher in ten of the eleven occupationalcategories. If the parastatal sector had the occupational composition of thegovernment the differential in mean wages between the sectors would remaina substantial 23O.

The observed differentials may in part represent differences in thecharacteristics of specific jobs. No occupational standardization can everaccount for all the variations in working conditions, security of job tenure

9The available data are on earnings per month. Lacking wage rate information we cannotreject the hypothesis that observed earnings differentials can be explained by differences innumber of hours worked. Since we have no a priori reason to expect hours worked to be relatedto employer groups, we proceed assuming earnings to be a suitable proxy for wage rates.

142 D.L Lindauer and R.H. Sabot, The pu,hlie 'prii .le vage differential

Table 1

Occupational earningsa in Tanzania for male African employees by type ofemployer (1 9 71 ).'

Employer

Occupation Private firm Government Parastatal

(1) White collar 416d 526 654Managerial' 416 1098 1782Semi-technical - 603 672Clerks, typists 409 375 530

(II) Production related 277 312 349Craftsmen 264 262 315Drivers 327 329 385Machine operators 232 310 308Skilled 315 358 379

(111) Unskilled 214 205 279Messengers 216 208 243Porters 293 213 270Watchmen 200 188 302Other unskilled 220 214 301

(IV) All occupations 263 396 409

aEarnings are expressed in Shillings-month and are net of fringe benefits. In1971 there were approximately 7 shillings to the U.S. Dollar.

bSource: Sabot, NlUMEIST (1972).'All earnings represent the mean value of a given occupation employer cell.

The reported occupations had a minimum of 8 employees per occupationemployer cell.

dThe disaggregated occupation categories are representative samples of thegiven occupation category and, therefore, their weighted average will notprecisely equal the aggregated categories mean value.

Table 2

The distribution of formal sector employment by occupation and employer.

Employer

Occupation Private firms Government Parastatal

(I) White collar 9.6 51.3 27.8(II) Production related 46.9 24.2 37.5(III) Unskilled 43.5 24.5 34.7

100.0°,, 100.00. 100.0100

D.L. Lindauer and R.H. Sabot, The public/private wage differential 143

Table 3

Fringe benefits by type of employer.

Percent of workers receiving benefit

Benefit Private firm Government Parastatal Total

Food 4.6 0.5 4.0 3.1Housing 4.8 6.4 23.2 12.4Medical 49.9 73.3 76.8 67.4Transportation 34.0 57.2 52.0 48.0

and risks involved in different work activities. Even within a competitiveenvironment such differences will generate equilibrium wage differentials.However, in a labor market such as Tanzania's, where wage paying jobs arerelatively suarce, it is unlikely that job attributes alone can account for all ofthe observed wage differences.

Another explanation for these differentials can be rejected immediately.Higher public sector earnings do not compensate for lower levels of non-wage benefits. Our survey includes information on whether non-wage benefitsof food, housing, medical treatment and transportation were received. Table3 presents results on the distribution of these benefits which suggest thatfringe benefits are generally more prevalent in the public sectors.

Alternative hypotheses abound. The premium paid to public sectoremployees at the top of the occupational hierarchy could be a residual of thecolonial wage structure. The relatively inferior wage position of the leastskilled government workers may reflect the resolution of a conflict betweenthe government's employment goals and fiscal constraints. The premia paidby parastatals could reflect the sharing of rents accrued as a consequence ofmonopoly power in product markets. Or, given that in Tanzania in 1971many of the parastatals were recently nationalized multi-nationals, theycould be the residuals of premia once paid by foreign firms as a way ofsecuring the loyalty of employees or of avoiding charges of 'exploitation'. Ofcourse, simply disaggregating mean wages by occupation is not sufficient toreject the hypothesis that wage differentials between ownership categories aredue to differences in labor force composition, e.g., with regard to levels ofeducation or employment experience. To examine this last hypothesis furtherwe consider the results of our multivariate analysis.

Table 4 presents the mean values for workers in private, government andparastatal establishments of the independent variabies included in theearnings functions. Public sector employees have more education thanemployees in the private sector; within the public sector the proportion ofpost-primary leavers is higher in government. Similarly public sectoremployees are somewhat older and have 50O" more experience in their

144 D.L. Lindauer and R.H. Sabot, The pubNic/private wage differential

Table 4

Worker' characteristics by type of employer.

Employer

Privatefirm Government Parastatal

Characteristic (Pr) (Go) (Pa)

(I) Education (0)

None 17.8 13.2 22.3Primary (E,) 75.9 58.1 57.8Post-primary (E2) 6.3 28.7 19.9

100.0 100.0 100.0(1I) Age (years) (A)

Mean 29 31 32(Standard deviation) (8.6) (10.3) (10.1)

(III) Experience (years onpresent job) (L)Mean 3.9 5.8 6.2(standard deviation) (5.5) (8.01 (7.8)

(IV) Location (l,, of workersin Dar-es-Salaam) (D) 60.5 57.6 71.0

aMale African employees only.

current job than workers in the private sector.10 Moreover, parastatalenterprises have a higher proportion of workers in the capital city.Standardizing for each of these differences in characteristics is likely toreduce the magnitude of differences in earnings between ownershipcategories.

Estimation of our aggregate wage function, ln Wl = f(XL) yields thefollowing results (note, standard errors appear in parentheses):

In W=4.758 +0.219E, +0.914E 2 +0.018L-0.00016L1(0.036) (0.045) (0.003) (0.00011)

+ 0.012A + 0.138D + 0.068Go +0.194Pa,(0.002) (0.027) (0.034) (0.032)

n=1291, K2 =0.365. (2)

'('For most employees their current job is their first job so the experience variable capturestheir total employment experience. The age variable is included to capture the effects onearnings of prior employment experience of workers who have had more than one job and of.pure age' effects. The square of the experience variabl, (L2

) is included to capture non-linearitiesin returns to experience.

D.L. Lindauer and R.H. Sabot, The public private wage differential 145

Ali but one of the coefficients, that on the squared experience variable, aresignificant. As expected, the coefficients on education, experience, andlocation in Dar es Salaam are positive and substantial and, as between theeducation variables, are in the usual size order. Nevertheless, the coefficientsoni the government and parastatal variables are significant and positive. Thegovernment coefficient is small; the parastatal coefficient is nearly three timesits size. What this implies is that even after standardizing for differences intheir education, employment experience (and age) and the location of theirwork, wage earners employed by the government earn a premium with apoint estimate of 7"O relative to private sector employees; parastatal workersearn a premium of 210 .11

These estimates of public-private differentials may be biased, however. Theemployer shift parameters only permit differences in the intercept terms ofemployer specific earnings functions. Bec-.use it constrains all three functionsto have identical slopes, the aggregate equation may be misspecified. In thesection that follows we consider whether there are observable differencesbetween ownership categories in the structure of earnings. Our exercisesprovide the basis for a refined measure of public-private differentials. Equallyimportant the comparison of wage structures provides insights inito whatexplains these differentials and, in particular, into what explains workers inparastatals earning so much more than similarly qualified workers in privateand government establishments.

3. Differences in wage structures

Stratifying by ownership categories entirely relieves the slope constraintimposed by the aggregate wage equation. Table 5 presents the results. Thefirst question is whether there are statistically significant differences betweenemployer categories in the level and/or structure of wages. The lower panelof table 5 presents the results of a series of Chow tests which enable us toanswer that question affirmatively. None of the possible pairwisecombinations produces an F statistic below the critical value at the 95th?0confidence level. Therefore we can reject the hypothesis that observeddifferences between employer categories in observed wage levels andstructures are simply the product of chance.12

These F tests do not tell us, however, whether the observed differences inequations between employer categories are due to differences in intercept

1 It is important to note that consistent and unbiased coefficients on the ownership categoryvariables require that mobility between sectors is not a function of individual earnings, ceterisparibus. If inter-employer mobility is a function of earnings than a simultaneous model of bothearnings and sector of employment would be required to test for the independent effect ofemployer type on wages.

'2 This approach was employed by Smith (19771 in her extensive empirical treatment ofpublic 'private wage differentials in the U.S.

146 D.L. Lindauer and R.H. Sahot, The public'pritate wage differential

Table 5

Earnings f"nctions stratified by employer.a

Privatefirms Government Parastatals(Pr) (Go) (Pa)

, 0.196 0.221 0.238(0.050) (0.0921 (0.054)

E, 0.874 0.914 0.948(0.088) (0.102) (0.067)

L 0.013 0.021 0.020(0.004) (0.006) (0.(X)4)

L2 0.0001 -0.0002 -0.0003(0.0002) (0.0002) (0.0002)

A 0.012 0.014 0.010(0.002) (0.004) (0.03)

D 0.250 0.015 0.151(0.039) (0.057) (0.045)

Constant 4.717 4.821 4.992

02 0.306 0.303 0.351

No. of observations 41(0 384 497

Chow test F-statistics

Pr + Go 2.48Pa±Go -- 7.10Pr+Pa 3.33

'Standard errors appear in parentheses.

terms (levels) or to differences in coefficients (structures). The stratifiedregressions suggest that most of the difference is due to differences inconstants rather than differences in coefficients. The coefficients on all butone independent variable are very similar across the three ownershipcategories. For example, controlling for differences in other characteristics theestimated premium earned by secondary leavers relative to the uneducated is140<,, in private establishments and 149°o and 158%" in government andparastatal establishments. The exception pertains to the location variable.While private firms pay a premium of 28% to workers employed in Dar esSalaam and parastatals pay a premium of 16° the government pays apremium of only 1.5%O.

In contrast to the similarity across ownership categories in coefficientsthere are large differences in constant terms. The difference between theprivate and parastatal constants represerits an across the board wagepremium for parastatal employees of 35 shillings or 32%lO above base

D.L. Lindauer and R.H. Sabot, The public/private wage differential 147

Table 6

Aggregate earnings function with interactions between employer categories and otherindependent variables.a

Coefficients oninteractive variables

Coefficients with:on independentvariables Government Parastatals

E, 0.196b 0.025 0.042(0.061) (0.098) (0.083)

2 0.874b 0.040 0.074(0.107) (0.137) (0.127)

L 0.013b 0.008 0.007(0.005) (0.007) (0.007)

L2 0.0001 -0.0004 -0.0004(0.0003) (0.0003) (0.0003)

A 0.012b 0.002 -0.002(0.003) (0.004) (0.004)

D 0.250b -0.236b -0.100(0.048) (0.068) (0.066)

Constant 4.717 0.104 0.275'(0.173) (0.153)

K2 = 0.369No. of observations= 1291

'See section 1 for a discussion of this specification. (Standard errors appear inparentheses.)

bSigniFicant at the 950 level.

earnings. The constant in the government equation represents a smallerpremium of 1 l relative to the private sector.

The results of the stratified equations are only suggestive, because thecomparisons of coefficients across equations have not been subjected torigorous tests for statistical significance. The fully interactive equationestimated next does permit such tests. The addition of the interaction termsto our aggregate equation allows us to measure whether any observeddifferences between ownership categories in the magnitude of the constantand of the coefficients on each of the independent variables is statisticallysignificant. The estimated interactive equation is presented in table 6.

The results confirm the impression conveyed by the stratified equations.The premium in government establishments, for example to primaryeducation, is given by hE1 +b(Go- EJ).3 Similarly the premium to primaryeducation in parastatals is given by bE1 + b(Pa El). It is notable that not a

1 3Adjusted. of course, according to the proper interpretation of dummy variables in semi-logarithmic equations.

148 D.L. Lindauer and R.H. Sabot, The public private wage diferential

single one of the interaction terms on primary education, secondaryeducation, employment experience (and experience squared), and on age isstatistically significant. The conclusion drawn is that in these respects thewage structure in government and parastatal establishments is very similar tothe wage structure in private establishments.

The two significant interactive terms are also notable. The results confirmthat the premium a government worker earns for being located in Dar esSalaam is significantly below the premium earned by private sector workersin Dar. The location premium in parastatals is lower than in privateestablishments, but not significantly so. The results also confirm thatirrespective of personal characteristics workers in parastatals receive apremium, relative to workers in private and government establishments. Theparastatal-constant interaction term is positive and statistically significant.The government-constant interaction term is positive but insignificant.' 4

In section 2, we ventured several alternative hypotheses for the largepremium earned by workers in parastatals. On reflection, the results of theinteractive equation favor one explanation in particular. The large premiumearned by parastatal employees survived our best attempts to standardize fordifferences between ownership categories in labor force composition. Thisdoes not necessarily imply that such differences play no role in explaining theremaining parastatal-private differential. Our measures of human capital,though comparable with tihose employed in other earnings functions, are stillcrude. Parastatals may be paying a premium to attract the very bestcandidates from among those of given levels of education and employmentexperience, a practice referred to as 'creaming'. In unskilled occupations,however, the productivity augmenting effects of higher levels of humancapital are undoubtedly much smaller than in skilled manual, technical orwhite collar occupations. This suggests that the incentives for parastatals to'cream' would increase with occupational level and that, correspondingly, thepremium paid to attract the best candidates would be larger for workers withrelatively high levels of qualifications.

A similar prediction regarding the relationship between levels of educationand experience, and the magnitude of the wage premium paid by parastatalsflows from the monopoly ;ent hypothesis. If parastatal managers choose todistribute to employees rents earned in product markets, we might expect the

"4 The finding that most of the difference between ownership categories is in the constantrather than n the slope of the earnings functions is further maintained by an F-test comparingthis equation with a restricted specification where only the intercept and regional parameters areentered interactivelv. The F-test strongly rejects the hypothesis that the addition of the otherinteractive terms adds to the explanatory power of the model. Also note that the results fromestimating the interactive equation suggest a larger premium to public emplovment than wasindicated by the results of section 2. However, the interactive estimates are subject to far greater'ariance due to the high degree of collinearity between all the interactive terms of a givenemployer type and, thereFore. the magnitudes of these different estimates may be more similarthan it at first appears.

D.L. Lindauer and R.H. Sabot, The public 'private wage differential 149

wage premium to be higher among the best qualified workers who after allinclude within their ranks the very managers making the distributionaldecisions.

Our third hypothesis was that the premium paid by parastatals was aresidual of the price paid by former multinationals to obtain acceptance inlocal markets. If foreign firms did pay a premium to avoid charges ofexploitation we might expect the premium to be as big or bigger at the largebase of the occupational pyramid as at the small pinnacle. This prediction isthe opposite of the predictions generated by the first two hypotheses. Theestimated interactive regression indicates that in percentage terms thepremium paid by parastatals to workers with very low levels of qualificationsis as great as the premium paid to highly qualified workers. The resultstherefore lend support to the tlhird hypothesis.

The location variable is the exception to the generalization that the slopesof the earnings functions are constant across ownership categories. Privatelyowned establishments pay workers in Dar es Salaam substantially more thanemployees in other towns with the same qualifications. Presumably this isbecause in the capital city the cost of living is higher or because the labormarket is tighter. The government does not pay higher wages to workers inDar, bD - c(D- Go) -0, presumably because the centrally administered wagestructure is insensitive to regional differences in the cost of living or inmarket conditions. Parastatals meanwhile also offer a Dar-es-Salaam wagepremium. This may reflect a responsiveness to local labor demand conditionssimilar to that exhibited by private firms. This in turn may reflect the priormultinational and hence private sector status of many of these enterprises."5

4. Decomposition of gross wage differentials and conclusions

/3 can be a misleading indicator of the magnitude of wage differentialsbetween ownership categories when there are differences between categoriesin wage structures (coefficients in separate earnings functions). Though wehave shown these differences to be small our best estimate of wagedifferentials should nevertheless incorporate them. Table 7 summarizes theresults of the simulation exercise for representative private, government andparastatal sector employees (those with the mean characteristics of allworkers in their ownership category) which allows us to decompose grosswage differentials into the component explained by various differences incharacteristics (E) and the remainder (R) which results from differences inearnings functions.

'5 Note that the magnitude of the location parameter in the aggregate wage equaticn ofsection 2 is a weighted average of what we have now determined to be the separate impact ofDar employment according to employer. The magnitude of the location coefficient in theinteractive equation is, therefore, a more accurate measure of market determined inter-urbanearnings differentials.

G

150 D.L. Lindauer and R.H. Sabot, The public priv'ate wage differential

Table 7

The contribution of difTerences in labor force composition to the explanation of gross wagedifferentials between ownership categories.

1',;,,(sh mihI = 396 =409 Wp. =409U'pr(sh mth) =-263 Wpr =263 W,;0 =396G-An,,,-Pr = 133 G-Wp0 W -p = 146 G-Wpa -WGO = 13a =(Go- Pr) WPr 5)1 ) (WFp. P-Wpj)Wpr = 56% O x=( Wpa G Co)iVWGO 3°/3 7°n = -21°o, /I /(tp- fl0 ) = 14%o

(1) (2) (3) (4) (5) (6)

Wage structure Pr Go Pr Pa Go Pa

Contribution of differencesof characteristics as apercentage of G:Education (E,+E 3 ) 58.4 60.2 23.6 24.2 -101.4 -105.1Experience (L+L 2 ) 9.8 1.1 8.4 11.0 -2.5 8.8Age (A) 8.7 10.2 10.1 8.4 17.5 12.5Location ID) -2.5 -0.1 7.3 4.5 2.5 25.0

Total (E): 74.4 71.4 49.4 48.1 -83.9 -58.8Residual contribution 25,) 25.6 28.6 50.6 51.9 183.9 158.8

Wage difference afteraccounting fordifferences incharacteristics Ish mth) 34.0 37.9 72.8 75.8 23.8 20.6

Government employees earned, on average, 51"') more than private sectorworkers. Columns (1) and (2) indicate that differences in characteristicsaccount for roughly 73" of this large differential. The much highereducational attainment of our representative government employee, areflection of the greater white collar intensity of labor demand in thegovernment than iii the private sector accounts for fully 85°'o of (E). Afteraccounting for differences in characteristics our representative governmentworker earns some 36 - per month (l14"',) more than his private sectorcounterpart.

The gross differential in mean wages (146i'- or 56 ?,0) between private andparastatal employees is larger still than the government-private differential.In this case, however, a markedly smaller proportion, roughly half, isexplained by differences in characteristics. Differences in educationalattainment contribute most to (E), followed in descending order of magnitudeof contribution, by the greater experience and age of parastatal workers andtheir greater concentration in the capital city. The remaining half (R) of thedifferential, implying a difference of some 75i- a month or 29',, is thepremium our representative worker earns simply for being a parastatal rathierthan a private sector employee.

D.L. Lindauer andl R.H. Sabot. The puiblic prit-ate wage diBfjrential 151

Given that differences in characteristics explain more of the government-private than of the parastatal-private differential in mean wages, we wouldexpect differences in characteristics to explain the small advantage the'typical' parastatal worker has in mean wages relative to governmentworkers. In fact, this small advantage is more than explained by differencesin characteristics. The proportion of employees who are high paid whitecollar workers is nearly twice as high in the government as in the parastatalsector. As a corollary government workers have a higher level of educationalattainment. If the better qualified government employees were paid accordingto the parastatal wage structure they would actually earn more, on average,than parastatal employees. This is indicated by the negative sign of theestimated total contribution of differences in composition to the gross wagedifferential (E).

In conclusion our analysis of public-private earnings differentials in urbanTanzania in 1971 suggests that worker characteristics cannot account for allof the differences in earnings between the public and private sectors of theformal economy. Both government and parastatal employers pay more thanwage rates prevailing in the private sector. Public sector employers do notappear to be acting simply as wage takers. The government paid a modestpremium while parastatal workers earned 29"O, more than private sectorworkers with the same characteristics. A definitive test of competinghypotheses was not possible due to the crudeness of our human capitalmeasures and our inability to control for job attributes and hours worked.Nonetheless, the evidence pertaining to differences between ownershipcategories in the structure of earnings suggests that the large parastatalpremium was a residual of the premium paid by multinational firms prior totheir nationalization. Whether the labor market distortion indicated by theparastatal premium persisted throughout the 1970's has importantimplications both for reasons of allocative efficiency and hence, economicgrowth, and for the distribution of income in Tanzania. Analysis of changesover time in public--private wage differentials using comparable data andsimilar techniques is currently underway.

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No. 260. Pradeep K. Mitra, "A Theory of Interlinked Rural Transactions,"Journial of Public Econiomics

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