Performance Pay in China:Gender Aspectsbjir_887 124..147
Lin Xiu and Morley Gunderson
Abstract
We provide an in-depth analysis of gender differences in performance pay inChina based on a unique dataset — the Life Histories and Social Change inContemporary China — that provides information on the different componentsof pay including performance pay and base pay as well as a wide array of paydetermining characteristic. The share of performance pay is documented and itsdeterminants, including gender, analysed. Particular attention is paid to genderdifferences in the different dimensions of performance pay: the probability ofreceiving it; the magnitude conditional upon receiving it; and their product beingthe overall unconditional magnitude. Gender differences in these dimensions aredecomposed into components due to male–female differences in the endowmentsof characteristics that explain these dimensions of pay, and gender differencesthat arise even when men and women have the same endowments of suchcharacteristics with the later component, often taken to reflect discrimination.
1. Introduction
Performance pay in general has increased in importance as a form of compen-sation for a variety of interrelated reasons: skill-biased technological changehas increased the premium on performance related skills (Lemieux et al. 2009);it can foster innovation that is increasingly important in the knowledgeeconomy (Anderson et al. 2009); new information technologies have facili-tated the measurement of individual performance (Shaw 2009); the survival offirms under global competition depends upon firm performance, and perfor-mance pay has been shown to have positive effects on individual and firmperformance (examples of recent evidence include in Boning et al. 2007;Dohmen and Falk 2011; Jones et al. 2010; and Pekkarinen and Riddell 2008).
Performance pay in China is of relevance to this literature and of increas-ing policy and practical importance as China moves towards a more marketoriented economy with incentives playing a larger role. In the earlier period
Lin Xiu is at the University of Minnesota, Duluth. Morley Gunderson is at the University ofToronto.
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British Journal of Industrial Relations doi: 10.1111/j.1467-8543.2011.00887.x51:1 March 2013 0007–1080 pp. 124–147
of the planned economy (1949–1978), wage differentials were suppressed infavour of a system of national wage scales based on socialist egalitarianprinciples. In 1978, the Chinese government adopted a policy of market-oriented reform, although it did not take place until the fourteenth PartyCongress proclaimed a ‘socialist market economy’ in 1992 (Naughton 1995).As part of that change, the formerly centrally controlled employment systemgradually gave way to a more decentralized employment system where firmswere given more discretion in making decisions on recruitment, promotion,layoffs and termination. Incentives were fostered in the wage determinationsystem by introducing performance-based bonuses that linked the earnings ofindividuals to their performance and productivity. In the 1990s, the ‘wageplus bonus system’ became the most frequently adopted pay scheme, with theshare of performance-based bonuses increasing substantially from 2.4 percent of total pay in 1978 to 23.3 per cent in 1993 (Meng 2000).
Increased attention has also been paid to male–female wage differentials inChina as the economy moves towards a more market-based system wherewage differentials will play a more important role in allocating labour andrewarding human capital formation. This is evidenced by the growingnumber of studies analysing male–female wage differences in China.1 Thesestudies have provided a wealth of information on the male–female wage gapin China, how it has changed over time and its determinants. These studieshave been based mainly on surveys such as the Urban Household Survey datacollected by China’s National Bureau of Statistics (NBS) and urban house-hold surveys conducted by the Chinese Academy of Social Science (CASS)also called the Chinese Household Income Project (CHIP). However, none ofthese studies have examined the gender pay gap in performance pay. In lightof the increasing importance of performance pay and its potential incentiveeffects, this is a gap that our study intends to fill with new survey information(discussed subsequently) on performance pay as well as total compensation.
Clearly, each of the issues of performance pay and of male–female wagedifferentials in China is of increased importance. While each issue is ofinterest and importance, the intersection of both issues — the focus of ouranalysis — compounds that importance.
The article is organized as follows. Section 2 discusses the expected rela-tionship between the receipt of performance pay and gender. Section 3provides the existing international evidence on performance pay and gender.Section 4 describes the data and Section 5 outlines our empirical methodol-ogy. Section 6 presents the empirical results, and Section 7 concludes with asummary and general discussion.
2. Expectation between receipt of performance pay and gender
There are theoretical reasons as to why women may be more likely to receiveperformance pay and to receive a larger component of performance pay intheir total compensation package, and there are theoretical reasons for theopposite relationship to prevail.
To the extent that women have shorter expected tenure with an organiza-tion2 they are less likely to enter into arrangements that involve deferredcompensation and are more likely to enter arrangements with performancepay involving bonuses, piece rates and commission that reward employeesimmediately for increased output (Geddes and Heywood 2003; Goldin 1986).Under deferred compensation systems, individuals tend to be paid less thanthe value of their marginal product early in their career in return for beingpaid more than the value of their marginal product late in their career.3 Suchdeferred compensation can serve a variety of positive functions. It can deterunwanted turnover and foster effort, honesty, commitment and performanceon the part of the employee. It can reduce the need for constant monitoringof performance, requiring only periodic monitoring of past performancewhich is easily observed. Deferred compensation can discourage ‘lemons’from applying since their traits will be revealed over time.
Employers are also more likely to use individual incentive systems involv-ing performance pay for women to the extent that female workers havehigher supervisory costs than males if paid on time rates. Even if the timerates involve deferred compensation, women may be less likely to be moti-vated by deferred compensation because of their shorter expected tenure andhence, lower likelihood of receiving deferred compensation. In such circum-stances, firms may utilize more supervision to monitor female performance.Geddes and Heywood (2003) and Goldin (1986) outline this argument, andGoldin (1986) provides evidence that the supervisory cost of women on timerates is higher than that of men and that the supervisory cost saving of usingpiece rates is much greater for women than men — hence, the greater pro-pensity to put women on piece rates.
Women are also more likely to opt for performance pay to the extent thatdiscrimination is less likely under performance pay systems if they are basedon more objective measures of performance (Geddes and Heywood 2003;Jirjahn and Stephan 2004).
While there are these reasons for women to be more likely to receiveperformance pay, there are factors working in the other direction. Accordingto Gomez-Mejia and Balkin (1992) and Reskin (2000), incentive bonus pay-ments are characterized by less formalized pay procedures in that managershave more discretion in designing pay plans and using subjective criteria forpay allocation in performance-based systems. In essence, performance pay canbe less attractive for women to the extent that it provides a further channel fordiscrimination rather than mitigating discrimination. Women prefer perfor-mance pay if it is objective but want to avoid performance pay if it is subjectiveand hence, potentially subject to discrimination. If discrimination does exist, itcould be more evident in such incentive pay schemes in that women are lesslikely to receive bonuses or their bonus levels are lower after controlling forother factors (Elvira and Graham 2002). Women also may be more risk averseand less responsive to competition and monetary prizes in general (Fisman andO’Neill 2009; Gneezy et al. 2003; Gneezy and Rustichini 2004). Risk aversionfor women is especially likely in China because the generally low income of
husbands is often insufficient to support a family making it imperative forwomen to have secure income. This is compounded by the fact that it is harderfor women to find and maintain their jobs in China because of possiblediscrimination (Chi and Li 2008; Li and Zhang 2010; Xiu and Gunderson2010; Zhang et al. 2008). This is so in spite of the extensive regulations andpublic policies on women’s employment that are ‘on the books’ in China butwhere their enforcement and implementation are highly debatable (Cooke2006; Potter 1999; Rawski 2006). To the extent that women are more risk-averse than are men, they are also more likely to choose firms which providebase pay rather than performance pay.
Clearly, theoretical considerations give ambiguous predictions as towhether performance pay is likely to be more prominent for women com-pared to men. It is likely to be more prominent for women to the extent thatthey have shorter tenure (and hence, less likely to enter into deferred com-pensation arrangements), higher supervisory costs if paid on time rates and ifperformance pay mitigates the effect of discrimination. In contrast, it is likelyto be less prominent for women to the extent that they are risk averse, andit offers more avenues for discretion and hence, discrimination. Theoreticalconsiderations give ambiguous predictions as to expected relationships;hence, it is necessary to appeal to the empirical evidence.
These theoretical determinants of performance pay apply to both compo-nents of the probability of women receiving performance pay and the mag-nitude of performance pay if they do receive it (and hence, the unconditionalmagnitude which is the probability of receiving performance pay timesthe conditional magnitude if they receive performance pay). It is the case,however, that the component involving the conditional magnitude is mostlikely to differ between men and women to the extent that women are morerisk averse and hence, not wanting to put a large portion of their pay at risk.Also if discrimination is present, it is more likely to affect the conditionalmagnitude if subjective as opposed to objective assessments are made.
In contrast, the probability component is less likely to differ between menand women, because it is more difficult to discriminatorily assign individualwomen to performance pay (as opposed to give them different magnitudes ofperformance pay if subjectively evaluated) when men in the same jobs are notassigned to such pay. As well, it is more difficult for risk-averse women to optout of performance pay if it is a compensation component of the job for bothmen and women. Nevertheless, performance pay could be disproportionatelyused in women-dominated jobs (for both men and women) in which case theprobability component (and hence, the unconditional magnitude that it alsoaffects) can differ between men and women.
3. Existing evidence on performance pay and gender
The existing empirical literature provides conflicting evidence with respectto the relationship between gender and performance-related pay. As well,
the existing evidence generally shows only the association betweengender and performance-related pay systems. It does not indicate theunderlying causal channels such as discrimination, risk aversion, supervi-sory costs or shorter tenure and hence, difficulty of utilizing deferredcompensation.
Evidence that performance-based pay is likely to be less prominent forwomen than men is found in various studies: Cowling (2000) for the Nether-lands but the opposite in Belgium; Booth and Frank (1999) for Britain; Barthet al. (2008) for Norway; Bertrand and Hallock (2001) for executives in theUSA; and Chauvin and Ash (1994) for business school graduates in the USA.Evidence from laboratory experiments also indicates that women are lesslikely to opt for performance pay when given a choice (Dohmen and Falk2011; Gneezy et al. 2003; Gneezy and Rustichini 2004). Not all studies,however, find performance pay is less prominent for women then men.Performance-based pay is found to be more prominent for women than men inBrown and Heywood (2003) for Australia, and in Geddes and Heywood(2003) for the USA. For Germany, Heywood and Jirjahn (2002) find thatwomen are more likely to receive pay based on individual productivity andprofit sharing but not on group profit sharing. Overall, while women mayprefer performance pay when it is objective as opposed to subjective, theevidence is ambiguous as to performance pay is more prominent for men orwomen.
The international literature on gender and performance pay canbe placed in the context of the literature on gender pay differences inChina.4 That literature suggests the following generalizations: an overallgender pay gap prevails; it is reduced slightly after controlling for the effectof various factors that affect pay; the portion of the gap that is explainedby differences in endowments of pay determining characteristics is smallerthan the unexplained component that reflects differences in pay for thesame pay determining characteristics; the evidence is mixed as to whetherthe unexplained component has declined over time, and whether it isgreater in the state and collective sectors as opposed to the private sectors;and the unexplained component is greater for less educated and marriedwomen.
Specific questions that are unanswered in the literature and thatare addressed in this study are: How does gender affect the probability ofreceiving performance pay and the magnitude of performance pay? Doesgender have a differential effect on the probability of receiving perfor-mance pay and the magnitude of such pay conditional upon receiving it?How much of the male–female difference in performance pay canbe attributed to differences in endowments of characteristics that affectperformance pay, and how much can be attributed to differences inperformance pay that is awarded for the same endowments of such char-acteristics? The purpose of this analysis is to address these questions bydrilling deeper into the performance pay component of total compensationin China.
Our empirical strategy involves various procedures to analyse male–femaledifferences in performance pay and to place it in the context of genderdifferences in other components of pay.
Gender Effects on the Shares of the Different Components of Compensation
We first place performance pay in the context of the other components of pay(Table 2) by providing estimates of gender differences in the shares of thedifferent components of compensation: base pay, performance pay and otherpay as outlined previously in Table 1. Two of the share measures — perfor-mance pay and other pay — have a large clustering of observations at zerovalues since 45.1 per cent of men and 51.3 per cent of women do not receiveperformance pay, and 55.5 per cent of men and 60.1 per cent of women donot receive the ‘other’ forms of pay. As appropriate for such clustered orlimited dependent variables, we use Tobit analysis. The marginal effects givethe effect of a unit change in each explanatory variable on the unconditionalmagnitude of each of the shares (e.g. the share of performance pay).
Tobit Estimates of the Dimensions of Performance Pay
We then drill more deeply into the gender aspect of performance pay(Table 3) by providing estimates of the gender gap of the separate dimensionsof performance pay: the probability of receiving any performance pay,P(Y > 0); the conditional magnitude of performance pay conditional uponreceiving it, E(Y|Y > 0); and the total unconditional magnitude of such pay,E(Y). As with the share equations, Tobit estimates are appropriate whenthere is a clustering of many observations at the limit value of zero.
To ascertain the sensitivity of our results to the inclusion of different sets ofcontrol variables, we estimate two different models that reflect the addition ofcontrol variables, as well as an estimate with no control variables to illustratethe unadjusted female pay gap in each of the dimensions of performance pay.Model 1 includes basic controls for personal and human capital characteristicssuch as education, firm-specific job tenure, general work experience, maritalstatus, having children under 6, having elders above 64, ethnicity, residencearea and membership in the Chinese Communist Party (CCP). Model 2 addsfurther controls for the ownership type of the firm (public, state, collective,private and foreign owned), the occupation of the individuals and their rank inthe workplace (worker, supervisor, higher-level leader). There can be legiti-mate debate as to whether it is appropriate to control for such factors as theownership type and especially occupation and rank since they may be mecha-nisms through which discrimination occurs. If they are regarded as mecha-nisms through which discrimination may occur, then the results of Model 1 arerelevant since they do not control for these factors.
Separate Male–Female Equations on the Dimensions of Performance Pay
The previous analysis was based on regressions with a female dummy vari-able, which restricts the effect of the other explanatory variables to be thesame for men and women. We relax that restriction and drill deeper into theanalysis of performance pay by estimating separate equations for both menand women. We do so for each of the dimensions of performance pay: theprobability of receiving performance pay; the conditional magnitude of per-formance pay; and the unconditional magnitude (Table 4). The separate maleand female equations allow the effect (i.e. the coefficient) to each of the paydetermining explanatory variables to differ for men and women. This illus-trates, for example, the differences in performance pay that men and womenreceive for their education, labour market experience or marital status.
Decomposition
The estimation of separate pay equations also enables the average perfor-mance pay difference between males ym and females yf to be decomposedinto two component parts (Blinder 1973; Oaxaca 1973):
y y X X Xm f m f m m f f− = −( ) + −( )β β β
The first component — termed the explained or endowment component —captures the effect of male–female differences in the endowments of wagedetermining factors (i.e. differences in the mean values of the explanatoryvariables or X’s) such as education and experience, as well as controls for suchfactors as occupation and industry. The second component — termed theunexplained or returns component — captures male–female differences in pay(i.e. the regression coefficients or b’s) that men and women receive for the sameproductivity related characteristics. The latter component is often labelled ameasure of wage discrimination since it reflects the pay differences that menand women receive for the same productivity related characteristics, althoughpart of that component could reflect the effects of unobservable variables suchas differences in career ambition, risk aversion and family burdens.
Since Tobit analysis involves a nonlinear relationship between the depen-dent variable outcome and the explanatory variables, the conventional decom-position procedures do not apply. Bauer and Sinning (2005, 2008) havedeveloped decomposition procedures for Tobit models, and we utilize thoseprocedures here.5 These results are presented in Table 5 for the various dimen-sions of performance pay, and in Table 6 for the different components of pay.
5. Data, variables and summary statistics
Data
As discussed previously, there are only a small number of studies thatexamine the extent to which the prevalence of performance pay differs by
gender. Furthermore, the existing studies of male–female pay differences inChina tend to use datasets that provide information on total pay to includebonuses, subsidies and other labour-related income in addition to the basicwage, but they do not separate out these components so as to enable adetailed analysis of performance pay.
Our analysis is designed to fill this gap by using a dataset based on a 1996survey — Life Histories and Social Change in Contemporary China(LHSCC)6 — that not only provides information on total compensation butalso on its three components: base pay, performance pay and ‘other’ forms ofpay such as allowances, subsidies and other forms of employment income butnot fringe benefits. In particular, the respondents were asked three separatequestions: (a) How much was your base pay from work last month? (b) Howmuch was your performance pay from work last month? (c) How much wasyour total pay from work last month, including base pay, performance pay,allowances and other forms of employment income? While a separate ques-tion was not asked about the magnitude of ‘other’ employment-relatedincome, we calculate it as total pay minus the base and performance paycomponent.
Performance pay includes year-end bonuses, merit pay and individualbonuses. Base pay, year-end bonuses and merit pay are the top three items inemployees’ compensation package with base pay ranking highest, year-endbonus second, followed by merit pay (Chiu et al. 2002). Compensation basedon wages plus bonuses were commonly adopted in the 1990s (Meng 2000),and bonuses have increased as a component of compensation (Chiu et al.2002; Warner 1996). Bonuses are often distributed on an annual or bi-annualbases and paid before major holidays, sometimes distributed to departmentsto be shared across workers and sometimes based on employer discretion(Cooke 2002; Taylor 2002).
While the performance pay component of compensation is obviously adirect measure of performance pay, we treat the component of ‘other’ income(allowances, subsidies and other forms of employment income) as a compo-nent that can also be subject to more discretion and hence, potential discrimi-nation. This is in contrast to the base pay component which is likely to bemore known and subject to less discretion and hence, discrimination.
The dataset is also ideally suited for our analysis, because it includes a richarray of other variables that are important to control for in any analysisof male–female pay differences. In our analysis, these are categorized as:individual personal and human capital characteristics (detailed educationcategories, general labour market experience, specific tenure with theorganization, marital status, ethnicity, child and elder-care status, member-ship in the Chinese Communist Party); the ownership structure of the enter-prise (public, state, collective, private and foreign owned); occupation andsupervisory rank within the organization; and region. As such, it enables usto see how the male–female differences in performance pay and the othercomponents of total pay are affected by differences between men andwomen in their endowments of these characteristics, as well as the different
returns they receive from the same characteristics. It also enables us to dothe analysis with and without controls for such factors as occupation, enter-prise ownership and rank in the workplace, given the debate over whether itis appropriate to control for such factors since they may be mechanismsthrough which discrimination occurs (e.g. Dong and Bowles 2002; Olson andBecker 1983).
The Local Health Care Co-operative involves a multistage stratifiednational probability sample of 6,090 adults aged 20–69 from all regions ofChina (except Tibet). As is common in the literature on male–female wagedifferentials in China, we restrict our analysis to urban workers (3,087 obser-vations) who have an urban registration status (2,627 observations) in partbecause they are more homogenous in terms of receiving and reporting ontheir pay. As is also common in most research on gender pay differentials,we also exclude self-employed workers because of their different earningsmechanism, as well as police and soldiers because no women in the datareported they worked as police or soldiers (reduced to 2,515 observations).We also excluded those workers who have missing values on their wage(reduced to 1,810 observations) and who report zero on all the three paymeasures: base pay, bonus and total pay. After such exclusions, the workingsample consisted of 1,790 observations, with 966 men and 824 women.
For item non-responses for respondents who did not provide informationon questions pertaining to their industry (383 observations), occupation(381 observations) or rank in the work unit (417 observations), we con-structed a separate dummy variable of ‘unknown’. This enabled retaining theobservation for its other information, with the estimated effect of the‘unknown’ category providing information on whether the ‘unknowns’ wereassociated with different relationships to their earnings. Only two otherobservations had missing values — two women were missing their education,and one of those was also missing information on other work experience.They were assigned the mean values for those variables. We also re-did theanalysis by dropping the two observations with the missing values for edu-cation and experience, as well as those that were missing their industry,occupation or rank yield a working sample of 1,371 observations. The results(Appendix available on request) were largely unaffected.
Dependent Variables: Performance Pay and Other Components of Total Pay
Although the focus of our analysis is on performance pay, we embed thatanalysis in the context of the other components of base pay and ‘other’ paysuch as allowances and subsidies, as well as total pay. Table 1 provides themean values for total pay as well as its three components — base pay,performance pay and ‘other pay’ which includes allowances, subsidies andother forms of employment income, separately for men and women. Becausenot all persons receive the components of performance pay or ‘other pay’, wealso include the proportion who receives such pay (i.e. the mean probability
of them receiving such pay). Multiplying this by the magnitude of such payconditional upon them receiving it yields the unconditional magnitude ofthose components of pay.7
As indicated in Table 1, performance pay is a substantial component oftotal pay with the share of performance pay as a per cent of total pay beingfairly similar for men (17.2 per cent) and women (17.5 per cent). Women wereless likely to receive performance pay (54.9 per cent of men and 48.7 per centof women) and conditional upon receiving performance pay, the averageconditional magnitude of performance pay was also lower for women thanfor men, being 168 Yuan/month (¥) for men and 144¥ for women.8 Since boththe probability of receiving performance pay and the conditional magnitudeof such pay is lower for women, the unconditional magnitude of performancepay is obviously also lower for them. Specifically, multiplying the probabilityof receiving performance pay by the conditional magnitude of such payconditional upon receiving it yields the unconditional magnitude of perfor-mance pay of 91¥ for men and 70¥ for women, for a ratio of female / maleperformance pay of 0.77, close to the ratio of base pay and total pay. Inessence, women are less likely than are men to receive performance pay, andthey receive a smaller amount of it when they do receive performance pay, sothat their unconditional magnitude of performance pay is smaller than thatof men. In spite of the lower amounts of performance pay received bywomen, the share of performance pay as a component of total pay is fairlysimilar for men (17.2 per cent) and women (17.5 per cent). This reflects thefact that women also receive smaller amounts of the other componentsof pay.
For the ‘other’ component of pay to include allowances, subsidies andother forms of employment income, a somewhat different picture emerges.Their share of total pay is somewhat lower for women (12.8 per cent) com-pared to men (15.3 per cent). Women are less likely to receive these otherforms of pay (44.5 per cent of men and 39.9 per cent of women), and theyreceive smaller amounts of these other forms of pay conditional upon receiv-ing them (183¥ for men and 128¥ for women). Multiplying the probability ofreceiving ‘other’ pay by the conditional magnitude of such pay conditionalupon receiving it yields the unconditional magnitude of ‘other’ pay of 81¥ formen and 51¥ for women, for a ratio of female / male other pay of only 0.63— the lowest ratio of all components of pay. In essence, women are less likelythan are men to receive these other forms of pay and they receive a smalleramount of it when they do receive such pay, so that their unconditionalmagnitude of other forms of pay is considerably smaller than that of men.
Clearly, the components of performance pay and ‘other’ forms of paymerit more in-depth analysis given their combined importance of accountingfor almost one third of total compensation for men (32.5 per cent) and onlyslightly less for women (30.3 per cent). This importance is further illustratedby the fact that a regression of the logarithm of total pay on performancepay, as well as other determinants of pay, yielded a statistically significantcoefficient of 0.32 for men and 0.36 for women implying that total
compensation was about 32 per cent higher for men and 36 per cent higherfor women who received performance pay compared to men and women,respectively, who did not receive performance pay.9 In essence, performancepay is both an important component of total pay, and it is an importantfactor influencing the magnitude of total pay. Hence, it merits more in-depthanalysis. The purpose of this article is to provide such analysis based onChina’s emerging market economy.
6. Empirical results
We first present estimates of the share equations, as well as the total payequation, highlighting the effect of being female on the shares of compensa-tion, as well as on total pay. Tobit marginal effects for the probability ofreceiving performance pay, the conditional magnitude of performance payconditional upon receiving it and the unconditional magnitude of perfor-mance pay are then provided. This is followed by the decomposition analysisindicating the explained portion of the overall magnitude of performance paythat is attributable to differences in the endowments of pay determiningcharacteristics and the unexplained portion that is attributable to differencesin the performance pay that men and women received for the same paydetermining characteristics. For comparative purposes, these portions arealso portrayed for the different components of pay (i.e. base pay, perfor-mance pay and ‘other’ pay), as well as for total pay.
Tobit Estimates of Share Equations
Table 2 gives the Tobit estimates of the share equations, highlighting theeffect of being female on the shares of compensation after controlling for theeffect of the other variables that affect the shares. As indicated in the firstrow, compared to men, women have a lower share of both performance payand ‘other’ pay and a higher share of base pay. The effects, however, arestatistically insignificant at conventional levels, and the quantitative magni-tude of the gender gap in the share of performance pay is minuscule.
Persons with higher education have larger shares of both performance payand ‘other’ forms of pay and correspondingly smaller shares of base pay.Performance pay may be more important in fostering incentives among thosewith greater human capital. The quantitative magnitudes of the effects,however, are small.
Persons with higher tenure at their current job have smaller shares of bothperformance pay and other forms of pay and correspondingly larger sharesof base pay. Performance pay may be more important in fostering incentivesamong those in the initial phases of their job; once they are more established,performance pay may be less important. Again, however, the quantitativemagnitudes of the effects are small. The same pattern prevails for otherlabour market experience outside of the current job.
The share of performance pay is significantly and quantitatively smaller forpersons with children under the age of 6 and greater for persons of Hanethnicity, state-owned organizations and skilled manual as well as profes-sional occupations. In all of these cases, the share of base pay is correspond-ingly in the opposite direction.
Tobit Marginal Effects on Dimensions of Performance Pay
Table 3 probes deeper into the performance pay component by analysing theeffects of being female on the magnitudes of the different dimensions ofperformance pay: the probability of receiving performance pay; the condi-tional magnitude of performance pay conditional upon receiving it; and theunconditional magnitude of performance pay.10 It does so for the two differ-ent models discussed previously that reflect the addition of control variables,as well as an estimate with no control variables, to illustrate the unadjustedfemale pay gap in each of the dimensions of performance pay.
TABLE 2Determinants of Shares of Components of Pay (t-values in parentheses)
Note: The omitted reference category for female is male, for region East, for ownership typepublic sector (e.g. government, education, health), for occupation unskilled manual and for rankin the organization ordinary worker. N = 1790.* Significant at 10%; ** significant at 5%; *** significant at 1%.
As shown in first column of Table 3, when there are no control vari-ables, the gross relationship is such that, relative to men, women have a 6percentage point lower probability of receiving performance pay11 and a24.4 per cent lower conditional magnitude of receiving performance payconditional upon receiving it with the combination of these two factorsyielding a 33.9 per cent lower overall unconditional magnitude of perfor-mance pay. This picture is almost identical in Model 1 after adding con-trols for personal and human capital characteristics. These effects becomestatistically insignificant, however, when further controls are added forownership type, occupation and supervisory rank within the organization(Model 2).
These results highlight that women receive a significantly smaller amountof performance pay compared to men, both because they are less likely toreceive performance pay, and they receive a smaller magnitude of such paywhen they do receive it. If they are working at a workplace of the sameownership type, occupation and rank, however, then the probability ofreceiving performance pay and the magnitude of performance pay for womenis not different from that of men. The fact that women are generally less likelyto be paid performance pay and receive lower performance pay occurs,because women are selected or attracted to ownership types, occupations andranks that tend not to provide performance pay.
Separate Male–Female Performance Pay Regressions
As indicated, the previous analysis was based on regressions with a femaledummy variable to indicate the effect of being female on performance payand the other components of pay, as well as the different dimensions of
TABLE 3Tobit Estimates of Marginal Effects of Being Female on Performance Pay:
Various Models with Additional Control Variables
Unadjusted Model 1 Model 2 +No controls Basic controls ownership/occu/rank
(1) (2) (3)
Probability of receiving -0.062*** -0.063*** -0.026Log conditional magnitude if receiving -0.244*** -0.237*** -0.092Log unconditional performance pay -.339*** -0.328*** -0.128Controls
Note: The marginal effects from the Tobit regressions in the top panel are calculated in STATAfrom the Tobit regression coefficients of 0.652 *** for the female dummy variable in the modelwith no controls and from the Model 1 female coefficient of -0.632 and the Model 2 coefficientof -0.235. The marginal effects are assigned the significance levels associated with the Tobitcoefficients.* Significant at 10%; ** significant at 5%; *** significant at 1%.
performance pay. Such an analysis restricts the effects of the other explana-tory variables to be the same for men and women. In this section, we relaxthat restriction and drill deeper into the analysis of performance pay byestimating separate equations for both men and women. We do so for eachof the dimensions of the probability of receiving performance pay and theconditional magnitude of performance pay, as well as the unconditionalmagnitude. Given the mass of detail, we focus our discussion on situationswhere male–female differences are prominent and where differences prevailacross the probability and conditional magnitude dimensions, as well aswhere the effects are statistically significant and quantitatively large.
As indicated in Table 4, education and Han ethnicity generally havestrong positive effects for women (but not for men) on the probability ofreceiving performance pay, the conditional magnitude if it is received andhence, the unconditional magnitude. Having children under the age of 6is associated with substantially lower performance pay for both men andwomen, with the magnitude being slightly larger for women, perhapsreflecting their greater time and effort in raising young children. Perfor-mance pay is much higher in the Western region for men but not forwomen. It is also higher for firms owned by the state for both men andwomen (t = 1.49 for women), and it is substantially smaller for women (butnot for men) in private/foreign/joint owned firms. Performance pay is muchhigher for men (but not for women) in skilled manual occupations and forhigher-level leaders. Performance pay is much higher in professional occu-pations for both men and women. This may reflect the ability to measureperformance, as well as the importance of using performance pay to affectincentives in such occupations.
Overall, the separate male and female equations for the different dimen-sions of performance pay are often consistent with expectations about therole of performance pay and the different effects on men and women of suchfactors as child raising responsibilities. But they also raise puzzles as to whythere should be differences for men and women such as the strong positiverelationship between performance pay and education, as well as Han ethnic-ity and smaller performance pay for private/foreign/and joint-owned firmsfor women but not for men, as well as the higher performance pay in theWestern region, in skilled manual occupations and for higher- level leadersfor men but not for women. It appears that the Chinese labour market isquite heterogeneous and is subject to idiosyncrasies with respect to genderdifferences in performance pay.
Decomposing Dimensions of the Gender Gap in Performance Pay
Table 5 presents the results of decomposing the different dimensions of thegender differences in performance pay into an explained portion becauseof differences in endowments of pay-determining characteristics and anunexplained portion because of differences in the performance pay thatmen and women receive for the same endowments of wage-determining
characteristics. As outlined previously, the latter component is often attrib-uted to pay discrimination since it reflects different returns for the sameendowments of pay determining characteristics, although it can also reflectdifferences in such unobservables as differences in risk aversion, career ambi-tion and family burdens. Our decompositions are based on the Model 2results so as to highlight the effect of the full set of control variables.
As indicated in the last row of the bottom panel of Table 5, half (50.9 percent) of the higher performance pay received by men compared to women isattributed to male–female differences in the endowments of characteristicsthat are associated with performance pay. That is, men are more likely thanwomen to have characteristics that are associated with performance pay. Theother half (49.1 per cent) of the higher performance pay received by mencompared to women is attributed to differences in the performance pay thatmen and women receive when they have the same endowment of character-istics that determine performance pay. This latter portion may reflectdiscrimination to the extent that there is discretion in the awarding of per-formance pay when people have the same observable characteristics thataffect performance pay. However, since we do not have objective measuresof performance in the data, it may also reflect unobservables as discussedpreviously.
The pattern is different for the separate components of the probability ofreceiving performance pay and the conditional magnitudes conditional uponreceiving some performance pay. Specifically, about three-quarters (73.4 percent) of the greater probability of men receiving performance pay is due tothe fact that men have greater endowments of characteristics associated withthe receipt of performance pay, and about one quarter (26.6 per cent) is dueto the fact that they are more likely to receive performance pay even when
TABLE 5Decomposition of Male–Female Gap in Probability of Receiving Performance Pay,
Conditional Magnitude if Receiving and Unconditional Magnitude
Aspects ofperformance pay
Overall gap Explained byendowments
Unexplained orreturns component
y ym f− X Xm f m−( )β β βm f fX−( )
MagnitudeProbability of receiving 0.0620 0.0455 0.0165Conditional magnitude if receiving 0.1468 -0.0007 0.1475Unconditional magnitude 0.3499 0.1781 0.1718
%Probability of receiving 100 73.4 26.6Conditional magnitude if receiving 100 0.5 100.5Unconditional magnitude 100 50.9 49.1
Note: Estimates for the probability of receiving performance pay are based on Logit regressions,the estimates for the conditional magnitude conditional upon receiving performance pay arebased on OLS and estimates for the unconditional magnitude are based on Tobit analysis. Theformula in the column heads for the explained and unexplained components are appropriatestrictly only for the conditional magnitude estimates.
they have the same characteristics as do men that affect performance pay. Incontrast, for the conditional magnitude of performance pay, the unexplainedor ‘discriminatory’ component is essentially 100 per cent indicating that menreceive larger magnitudes of performance pay than do women even whenthey have the same endowments of characteristics that affect performancepay. The larger unexplained component for the conditional magnitude isconsistent with the possibility that there is more discretion and hence, dis-crimination in the awarding of performance pay than there is in the setting upof performance pay systems.
Overall, these decomposition results for the different dimensions of per-formance pay suggest that about half of the (unconditional) gender differ-ences in performance pay can potentially reflect discrimination defined asdifferences in performance pay when men and women have the same char-acteristics that affect performance pay. This discriminatory component ismuch larger (100 per cent) for the conditional magnitude of performance paywhere discretion can be more at play, and somewhat smaller (27 per cent) forthe probability of having a performance pay system where discretion is lesslikely to be at play.
Decomposing Gender Gap in Different Components of Pay
Table 6 places the gender gap in performance pay (and its explained andunexplained components) in perspective by contrasting the gender gap inperformance pay with the gender gap in the other components involving basepay and ‘other’ forms of pay as well as in total pay.
As indicated in the last row of each panel, men tend to earn about 30 percent more than women and about one third (32.2 per cent) of this reflects
TABLE 6Decomposition of Male–Female Pay Gap for Different Components of Pay and Total Pay
Note: As discussed in the text, estimates for the performance pay and ‘other’ pay are from theTobit estimates given the clustering at zero. Estimates for base pay and total pay are based onconventional OLS. The formula in the column heads for the explained and unexplainedcomponents are appropriate strictly only for the OLS estimates for base pay and total pay.
differences in their endowments of wage-determining characteristics, and twothirds (67.8 per cent) reflect differences in the pay that men and womenreceive when they have the same endowments of wage-determining charac-teristics, with that latter component often taken as reflecting discrimination.These magnitudes are in line with the results of other Chinese studies basedon total compensation.12
The gender gaps in performance pay (35 per cent) and in ‘other’ forms of pay(28 per cent) are both higher than the gap in base pay (25.5 per cent). The un-explained or potential discriminatory component, however, is slightly smallerfor performance pay (49.1 per cent) and substantially smaller for the ‘other’pay dimension (37.5 per cent) than for the base pay dimension (63 per cent).This suggests that there is not more discriminatory discretion in the awardingof performance pay and the ‘other’ forms of pay compared to base pay.
In summary, the decomposition of the different components of pay indi-cate that men earn about 30 per cent more than women with the gender gapin performance pay (35 per cent) and in ‘other’ forms of pay (28 per cent)both being greater than the gap in base pay (25.5 per cent). The unexplainedor potential discriminatory component, however, is smaller for performancepay and ‘other’ forms of pay compared to base pay, suggesting that there isnot more discriminatory discretion in the awarding of performance pay andthe ‘other’ forms of pay compared to base pay.
7. Summary and discussion
Our empirical analysis yields the following generalizations.
• Performance pay is slightly over 17 per cent of total compensation forboth men and women, and this similarity remains even after controllingfor other factors that affect the shares of compensation among base pay,performance pay and ‘other’ forms of pay.
• The share of performance pay is higher (and the share of base pay lower)among persons with higher education, Han ethnicity, who work in skilledmanual or professional occupations or in state-owned organizations. Theshare of performance pay is lower among workers who have long tenureand considerable general labour market experience, as well as childrenunder the age of 6.
• Relative to men, women have a 6 percentage point lower probability ofreceiving performance pay and a 24.4 per cent lower conditional magni-tude of receiving performance pay conditional upon receiving it, with thecombination of these two factors yielding a 33.9 per cent lower overallunconditional magnitude of performance pay. This occurs largely becausewomen are selected or attracted to ownership types, occupations andranks that tend not to provide performance pay.
• Separate male and female equations for the different dimensions of per-formance pay (probability of receiving, conditional and unconditional
magnitude) are often consistent with expectations about the role of per-formance pay and the different effects on men and women of such factorsas child-raising responsibilities. But they also raise puzzles as to why thereshould be differences for men and women, suggesting that the Chineselabour market is quite heterogeneous and subject to idiosyncrasies withrespect to gender differences in performance pay.
• About half of the (unconditional) gender differences in performance paycan potentially reflect discrimination (but also other unobservables) withthat unexplained component being much larger (100 per cent) for theconditional magnitude of performance pay where discretion and risk aver-sion can be more at play, and somewhat smaller (27 per cent) for theprobability of having a performance pay system where discretion is lesslikely to be at play.
• On a total compensation basis, men earn about 30 per cent more thanwomen, with the gender gap in performance pay (35 per cent) and in‘other’ forms of pay (28 per cent), both being greater than the gap in basepay (25.5 per cent). The unexplained or potential discriminatory compo-nent, however, is smaller for performance pay and ‘other’ forms of paycompared to base pay, suggesting that there is not more discriminatorydiscretion in the awarding of performance pay and the ‘other’ forms of paycompared to base pay.
In terms of the limitations of the analysis, since the survey does not provideinformation on measures of performance, we are not able to examine whetherthe gender pay gap differs across ‘subjective’ and ‘objective’ performance payin China. This is a common issue in most of the national labour surveys inChina including the national urban household surveys (CHIP). Recentresearch has shown that women may respond differently to different perfor-mance pay schemes. For example, Gneezy et al. (2003; Gneezy and Rustichini2004) presented experiment evidence indicating that women do equally well onpiece rates but avoid tournaments and other types of performance pay. Jirjahnand Stephan (2004) claimed women prefer piece rates, because they are subjectto less wage discrimination when objective performance measures are avail-able. The ‘performance pay’ measure that is adopted in this study is a sum of‘subjective’ merit-based bonuses and ‘objective’ piece rates or production-related bonuses. As such, further research on the gender difference in differentforms of performance pay in China would be informative.
Final version accepted on 29 September 2011.
Notes
1. Examples of such studies include Appleton et al. (2005), Bishop et al. (2005),Chi and Li (2008), Gustafsson and Li (2000), Hughes and Maurer-Fazio (2002),Liu et al. (2000), Maurer-Fazio and Hughes (2002), Ng (2007), Shu and Bian
(2003), Wang and Cai (2008), Xiu and Gunderson (2010) and Zhang et al.(2008).
2. Low family income in China compels many women to participate in the labourmarket so that their participation rate is higher than in other industrial countries(World Bank 2009). However, their participation rate is still lower than that ofmen (Maurer-Fazio et al. 2010), and increasing numbers are reporting themselvesas ‘stay-at-home moms’ which would imply lower expected tenure if they droppedout of the labour force to care for children (Maurer-Fazio et al. 2011). As well,the official retirement age in China is generally 60 for men and 55 for femalemanagers and 50 for female workers, and this is likely to lead to shorter tenure forwomen than men (Feng et al. 2011; Maurer-Fazio et al. 2010). Also, layoff prob-abilities are higher for women and re-employment probabilities are lower than formen, both of which would lead to lower tenure for women (Maurer-Fazio 2006).More directly, measure of tenure within an organization is shorter for womenthan for men (Li and Zax 2002).
3. The literature on the theoretical rationale for deferred compensation and evidenceon its prevalence is discussed, for example, in Lazear (1999) and Gunderson (2001).
4. The literature on male–female pay differences in China is reviewed, for example,in Chi and Li (2008), Xiu and Gunderson (2010) and Zhang et al. (2008).
5. The STATA command is nldecompose.6. We gratefully acknowledge Donald J. Treiman at the University of California
Los Angeles and Professor Andrew Walder at Stanford University for makingthis data available.
7. That is, E(Y) = P(Y > 0) * E(Y|Y > 0) where E(Y) is the unconditional magnitudeof pay, P(Y > 0) is the probability of receiving that component of pay, andE(Y|Y > 0) is the conditional magnitude of pay, conditional upon receiving any ofthat form of pay, and * is the multiplication operator.
8. (¥) refers to Yuan per month. For the time period of our analysis, 1(¥) ª US$0.12so that the average female pay of about 400¥ would equal about $48 per month.
9. Full regression results are available from the authors upon request.10. The full set of Tobit coefficients from which these marginal effects are derived are
available from the authors on request.11. This deficit of 0.06 is a fairly substantial amount relative to the mean of 0.52 who
receive performance pay. This is in accord with the results from some of theearlier studies in western countries (e.g. Barth et al. 2008; Bertrand and Hallock2001; Booth and Frank 1999; Chauvin and Ash 1994; Cowling 2000).
12. Reviews of the Chinese literature are contained, for example, in Chi and Li(2008), Xiu and Gunderson (2010) and Zhang et al. (2008).
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