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What determines individuals’ preferences for efficiency over equity-based wages?

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Prosper F. Bangwayo-Skeete International College of Cayman Islands, Newlands, Cayman Islands

Afaf H. Rahim Feinstein International Center, Tufts University, Somerville, Massachusetts, USA, and

Precious Zikhali International Water Management Institute, Southern Africa Regional Office, Pretoria, South Africa Abstract Purpose – The paper aims to examine factors that influence individuals’ preferences between wages indexed on job performance or efficiency over equity-based wages. Design/methodology/approach – Generalized linear latent and mixed models (GLLAMM) are estimated on the 2005 wave of the World Values Survey on employed individuals from 43 countries. Findings – Results suggest that employees’ preference for efficiency-based wages increases with education and globalization, while it decreases with unemployment rates. Research limitations/implications – Institutions and specifically public policies that promote education, and globalization, along with policies that reduce unemployment rates could be used to promote wage setting policies that reward performance or efficiency. Originality/value – The originality of the study lies in its use of both individual- and country-level data to estimate GLLAMM that take into account the multi-level nature of the dataset. This study can inform firms and policymakers on what measures to adopt to promote preferences for efficiency-based wages among individuals. Keywords Efficiency-based wages and equity-based wage, Generalized linear latent and mixed models, Wage differentials, Workers’ perceptions Paper type Research paper

Journal of Economic Studies Vol. 40 No. 5, 2013 pp. 600-613 q Emerald Group Publishing Limited 0144-3585 DOI 10.1108/JES-10-2011-0126

1. Introduction Standard neoclassical economic theory predicts that under conditions of perfect competition that assumes profit maximization and homogeneous workers, wages will equal the marginal product of labour. This implies that workers’ wages give full information on their productivity. In reality and contrary to the assumptions of neoclassical economic theory, wages might not necessarily be indicative of workers’ productivity meaning that wage differences are observed among workers performing similar tasks. There exist a large body of economic literature that seeks to explain the The authors gratefully acknowledge comments from Ryan Skeete as well as comments and suggestions from an anonymous referee on an earlier version of this paper.

sources of such wage differentials (Stiglitz, 1974; Shapiro and Stiglitz, 1984; Groshen, 1986; Krueger and Summers, 1988; Akerlof and Yellen, 1990). Further, in the real world markets deviate from perfect competition. This is because in the real world heterogeneity of labour exists and profit maximization need not be the main goal of employers. For instance, it is possible that employers may have preferences for different characteristics in employees such as gender and race that are not directly related to productivity (Bayard et al., 1999; Baldwin et al., 2001). In this case employers might not always equate wages to the marginal product of labour and given that markets are imperfect, these employers may not necessarily incur losses nor be driven out of business. Alternatively, if employers consider labour productivity as the main factor in their wage-setting policies, wage differentials might still exist in recognition of labour heterogeneity that leads to differences in labour productivity. In addition, the notion that productivity is dependent on workers’ efforts might encourage employers to pay higher wages as an incentive for workers to exert more effort. Higher wages are expected to enable employers to attract more competent job candidates (Malcolmson, 1981) as well as increase workers’ efforts in situations where moral hazard problems exist as firms cannot monitor workers’ performance perfectly (Akerlof and Yellen, 1990). Moreover, offering wages that reflect worker performance reduces labour turnover which can be costly (Stiglitz, 1974; Gottfries and Westermark, 1998). Analogously, from the employees’ perspective, wage differentials could be motivated by the employee’s desire to benefit from investments in enhancing their human capital, where human capital represents the investment people make to enhance their economic productivity (Psacharopoulos and Woodhall, 1997). In line with this argument, wage differentials could exist to compensate for differing human capital stocks, i.e. stock of knowledge, skills, aptitudes, education, and training an individual possesses. Theoretically, this concept is captured by the human capital theory which emphasizes that the development of skills is an important factor in production activities (Schultz, 1971; Sakamota and Powers, 1995; Psacharopoulos and Woodhall, 1997). Furthermore, studies suggest that workers consider the reward-to-human capital investment and will alter their investments accordingly until their wage is perceived to reflect the cost of human capital investments (Adams and Rosenbaum, 1962; Austin and Walster, 1974). The desire of employees to have wages that are perceived to be fair in terms of compensation for their human capital investments, implies that fairness, a subjective individual evaluation, plays a role in the perceptions of wage policies. Accordingly fairness considerations could also explain why in reality wages diverge from those predicted by the standard neoclassical economic theory. The foregoing discussion demonstrates the importance of understanding the drivers of firms’ wage policies from the perspective of both employers and employees. In order to create an environment that encourages workers to exert effort, it is of paramount importance that employers take into consideration workers’ preferences across different wage policies. Blinder and Choi (1990) and Campbell and Kamlani (1997) provide evidence that firms take into account employee’s perceptions on wages or concern for fairness. This is important given existing evidence that finds a positive relationship between fairness-of-pay perceptions and workers’ productivity, with workers found to change their effort levels whenever they perceive their pay to be unfair (Adams and Rosenbaum, 1962; Andrews, 1967; Akerlof and Yellen, 1990; Fehr et al., 1993; Paul, 2006)[1].

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The evidence that individuals’ perception of wage policies can influence their attitudes towards work and hence their productivity leads to the following interesting research question: what factors influence individuals’ preferences for different wage policies? Specifically, what factors influence individuals’ preferences between wages indexed on job performance or efficiency over equity-based wages? In line with this, this paper uses both individual- and country-level data to investigate the socio-economic factors and macro-level policy variables that influence individuals’ preferences for efficiency-based wages over horizontal egalitarian wages. We employed the generalized linear latent and mixed models (GLLAMM) to take into account the multi-level nature of our dataset. To the best of our knowledge no such study has been done. This study can inform firms and policymakers on what measures to adopt to promote preferences for efficiency-based wages among individuals. The rest of the paper is organised as follows: Section 2 presents the econometric framework and data used in the empirical estimation while the presentation and discussion of results is done in Section 3. We conclude in Section 4. 2. The empirical model and data This section briefly outlines the econometric framework as well as the data used in the analysis. 2.1 The empirical model What makes an individual consider it fair for workers to be paid according to their performance or efficiency? Conversely, what factors make individuals have a preference for equal horizontal pay? Specifically, how does the probability that an individual prefers wages that are indexed on efficiency or job performance over equity-based wages vary with individual socio-economic characteristics? Furthermore, do country-level characteristics such as GDP, individual income tax rates and globalisation have an influence on an individual’s preference for indexing wages on efficiency? The empirical analysis employs both individual- and country-level data. Given the hierarchical structure of the data, the standard probit regression will provide biased estimates because with grouped data, observations from the same group are generally more similar than the observations from different groups, which violates the assumption of independence of all observations. Hence, the multi-level probit random effects estimator is employed using the GLLAMM program written by Rabe-Hesketh and Skrondal (2005). The model has two levels: the individual represents level 1 and the country represents level 2. The GLLAMM approach has four major advantages over the probit regression: (1) it facilitates a systematic analysis of the effects of various covariates measured on different levels on the dependent variable; (2) taking the multi-level structure into account provides unbiased parameter estimators; (3) the standard errors are correctly estimated, taking clustering into account; and (4) the total variation can be divided into the two levels (Guo and Zhao, 2000, p. 444).

The GLLAMM procedure developed by Rabe-Hesketh and Skrondal (2005) involves maximum likelihood estimation of probit random effects models using Naylor and Smith’s version of adaptive quadrature. The maximization of the likelihood function over the set of parameters is achieved by a Newton-Raphson algorithm. In our model the dependent variable “efficiency wages” (Y) is measured at the individual level (level 1). It is a binary response variable taking the value 1 if the respondent believes it is fair to base wages on the efficiency of the worker and 0 otherwise. It is formulated based on the following question from the World Values Survey questionnaire: Imagine two secretaries, of the same age, doing practically the same job. One finds out that the other earns considerably more than she does. The better paid secretary, however, is quicker, more efficient and more reliable at her job. In your opinion, is it fair or not fair that one secretary is paid more than the other?

This question asks the respondent to make efficiency and equity considerations with reference to wages. As the question indicates, efficiency is with regards to being efficient on the job and can be interpreted as relating to productive efficiency. Thus, if a respondent says it is fair to pay the “quicker, more efficient and more reliable” secretary more, then the respondent expresses the belief that wages should reward good performance. On the other hand, if the respondent says that it is unfair to have one secretary paid more than the other we consider the respondent as believing in equal horizontal pay, i.e. he or she believes workers should be paid the same for the same job regardless of the differences in performance. This allows us to interpret the question as asking the respondent to state their preference for efficiency or performance-based wages vis-a`-vis equity-based wages. The outcome variable Y is dependent on individual level explanatory variables X and country level explanatory variables Z. First we set up a pooled probability regression equation to predict the dichotomous outcome variable Y by the individual level explanatory variables X. Second we introduce country level variables to capture the effect of the macro environment on the outcome variable. In addition to assuming the random intercept model where the intercept coefficients vary across countries we assume that the error is normally distributed. This means that the indicator function can be represented as follows: I ¼ PðY ij ¼ 1nX ij Þ ¼ F21 ðP ij Þ ¼ boj þ b1 X ij ;

ð1Þ

where I denotes the indicator function, boj is the intercept, b1 is the vector of coefficients to be estimated and F represents the cumulative distribution function of the error term. The subscript j ¼ 1, . . . , 43 is for the countries (level 2) and the subscript i ¼ 1, . . . , 60,579 is for individual (level 1). In general, a country with a higher intercept is predicted to have higher likelihood of choosing efficiency-based wages than a country with low value for the intercept. Across all countries, the intercepts boj have a distribution with a mean and variance. The next step in the two-level regression model (i.e. individual level and country level) is to explain the variation of the intercepts boj by introducing explanatory variables at the country level as follows:

boj ¼ a 00 þ a 01 Z j þ 10 j :

ð2Þ

Equation (2) predicts the average likelihood of choosing efficiency-based wages (over equity-based wages) in a country depending on the country’s variables Z. Hence, if a is


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positive, the average likelihood of choosing efficiency-based wages over equity-based wages is higher in countries with higher Z. Conversely, if a is negative, the average likelihood of choosing efficiency-based wages over equity-based wages is lower in countries with higher Z. 10j is a random residual error assumed to be identical and independently distributed. The a coefficients are assumed not to vary across countries so they are referred to as fixed coefficients. By substituting equation (2) into equation (1), the individual and country-level explanatory variables can be written as a single equation: F21 ðP ij Þ ¼ a 00 þ b1j X ij þ a01 Z j þ 10j :

ð3Þ

In order to estimate the intra-country correlation, we estimate equation (3) without explanatory variables at all, the so-called “intercept-only” model. The intercept-only model decomposes the variance into two independent components: s12 which is the variance of the errors at the lowest level (level 1) and s22 , which is the variance of the errors at the highest-level (level 2). This leads to the intra-country dependence or correlation r defined by the equation:

r¼

s22 : s22 þ s12

ð4Þ

The intra-country correlation r indicates the proportion of the variance explained by the grouping structure in the population. Equation (4) states that the intra-country correlation is the proportion of group level variance relative to the total variance. The intra-country correlation can also be interpreted as the expected correlation between two randomly chosen units that are in the same group. 2.2 Data and descriptive statistics The 2005 wave of the World Value Surveys (WVS) consists of 60,579 observations from 43 countries[2]. The paper utilizes the data to investigate the socio-economic factors that influence individuals’ preferences for efficiency over equity-based wages. To control for macro or country-specific effects on workers’ preferences we augment the socio-economic variables from the WVS data by country-level data on GDP per capita, globalization indices, income inequalities and the country’s maximum individual income tax rates[3]. Table I gives descriptive and summary statistics of the variables used in our empirical analysis. Around 78 per cent of the respondents believe that it is fair to pay higher wages to more efficient workers. On average, the surveyed respondent has an intermediate level of education (the mean for education level is 3.2) and around 21 per cent of the respondents are Muslims, 28 per cent Catholic and 32 per cent Protestant. The rest (19 per cent) are classified as “other religions” (for example Jewish, Hindu, etc.). 53 per cent of the respondents are employed. On average, the surveyed respondents perceive their health status to be good (the mean for self-reported health status is 3.85). Regarding the country-specific variables, the average GDP per capita is around 12,000 at purchasing power parity (PPP) (current international $). The level of income inequality as reflected by the Gini coefficient is 40.3 per cent and the average maximum individual income tax rate is 32.6 per cent. The average globalization index

Variable Dependent variable Preference for efficiency-based wages (Yi) Socio-economic characteristics Educationa Healthb Gender Age Married Employed Incomec Muslim Catholic Protestant White Country level variables GDP Ginid Globalizatione Tax

Description

Mean

SD

1 if respondent believes it is fair to reward efficiency or job performance, 0 otherwise

0.78

0.41

Highest education level attained by the respondent Respondent general health status (self-reported) Sex of the respondent (1 – male and 0 – female) Age of the respondent 1 if respondent is married or living together with a partner, 0 otherwise 1 if respondent is employed, 0 otherwise Income scale of the household 1 if respondent belongs to Muslim religion, 0 otherwise 1 if respondent belongs to Catholic church, 0 otherwise 1 if respondent belongs to Protestant church, 0 otherwise 1 if respondent is White, 0 otherwise

3.18 3.85 0.48 41.44 0.63

1.27 0.86 0.50 16.40 0.48

0.53 4.63 0.21

0.50 2.24 0.41

0.28

0.44

0.32

0.46

0.20

0.40

GDP per capita/1,000, in PPP (current international $) Gini coefficient in percentage terms Overall globalization index (2004) Maximum individual income tax rate (per cent)

12.00 40.29 0.47 32.61

11.32 10.15 0.18 10.93

Notes: aThe variable education is formulated by grouping categories based on WVS responses as follows: 1 – no formal education, 2 – primary education refers to individuals who either completed or started but did not complete primary school, 3 – vocational training/education refers to individuals who either completed or started but did not complete secondary schooling of technical/vocational type, 4 – secondary education refers to individuals who either completed or started but did not complete secondary schooling of university-preparatory type, 5 – university education refers to individuals who either completed or started but did not complete university-level education; bwe use a self-reported measure of health based on responses in WVS to a question asking respondents about their general health status; the ordinal responses on health variable are as follows: 1 – very poor, 2 – poor, 3 – fair; 4 – good and 5 – very good; c the scale is from 1 to 10 where 1 – “lowest income decile” and 10 – “highest income decile in the country”; d the Gini coefficient for the sampled countries ranges from 24.9 (Japan) to 60.7 (Brazil); a lower value indicates less income inequality; ea higher value of the index indicates that a country is more integrated in the global economy; 0 implies no integration and 1 indicates full integration

is 0.47 indicating that on average, countries in the sample enjoy some level of global interaction, integration and interdependence with regards to economic, social and political spheres. 3. Results and discussion Table II presents the results from the GLLAMM probit random effects estimation of equation (3). We estimate two models: the first is an intercept-only model and the second is a random intercept model with both individual- and country-level variables. Using equation (4), the intercept only model reveals an intra-country correlation of 12 per cent (r ¼ 0.142/0.142 þ 1 ¼ 0.12). This implies that 12 per cent of the variance of the likelihood that individuals would prefer efficiency wages over equity wages is


Table I. Descriptive statistics of variables used in the empirical analysis

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Table II. Probit random effects estimation of preferences for efficiency over equity-based wages: intercept-only model and full model

Variable Constant Socio-economic characteristics Education (predicted values) Health (predicted values) Gender Age Married Employed Income Muslim Catholic Protestant White Country-level variables GDP Income tax rate Gini Globalization Log likelihood Variances of level effects Level 1 Level 2

Intercept-only model Coefficient Robust SE 0.828 * * *

0.057

228,199 1 0.142

0.031

Full model Coefficient Robust SE 0.108

0.250

0.256 * * * 0.023 0.067 * * * 0.007 * * * 0.052 * * * 0.025 0.008 * 0.009 2 0.078 * * 0.025 0.164 * * *

0.020 0.038 0.017 0.001 0.018 0.017 0.005 0.044 0.039 0.037 0.038

2 0.011 * * 2 0.008 * 2 0.012 * * * 0.615 * 216,628

0.005 0.004 0.005 0.289

1 0.190

0.025

Note: Significant at: *10, * *5 and * * *1 per cent

due to grouping of individuals at the country level. This supports the use of the multi-level modelling approach the results of which are presented in the second column of Table II. Given existing empirical research that has shown that education improves productivity (Kirby and Riley, 2008), it is possible that individuals who prefer efficiency-based wages to equity-based wages are more likely to have more education. This implies that the individual’s education may be jointly determined with our dependent variable leading to endogeneity problems. We accordingly use predicted values for education to account for potential endogeneity between education and preferences for efficiency over equity-based wages[4]. Results show that the estimated education coefficient is positive and significant; indicating that more educated individuals consider it fair to index wages on job performance or efficiency compared to having egalitarian wages. This is further confirmed by Figure 1 which reports the predicted probability that individuals prefer efficiency to equity-based wages for a given level of education, holding the rest of the variables constant at their means. Figure 1 reveals that the probability that individuals prefer to have wages indexed on worker’s efficiency or performance over equity-based wages increases with advancement in education. A possible explanation for this finding is that more educated employees prefer “pro-efficiency” over “pro-equity” wage setting policies in order to capture returns to education or schooling. This is consistent with existing empirical literature that confirms the presence of significant returns to education in several countries. Examples of such studies include Byron and Manaloto (1990) and

Huang et al. (2002) for China; Ashenfelter and Krueger (1994) for the USA; Harmon and Walker (1995) and Kirby and Riley (2008) for the UK; and Hertz (2003) for South Africa. Like education, health is a form of human capital. Thus, health is expected to influence labour market outcomes and accordingly individuals’ preferences for efficiency over equity based wages. Existing theoretical models on efficiency wages link health to productivity basically by asserting that the economic value of health lies in its impact on the individual’s productivity (Leibenstein, 1957; Strauss, 1986). The models argue that at low levels of nutrition there is an increasing monotonic relationship between nutrition and productivity. Similarly, empirical literature in developing countries has postulated a significant effect of calorie intake and health on labour productivity (see, for example, Strauss (1986) using farm household level data from Sierra Leone; Thomas and Strauss (1997) in urban Brazil and Schultz and Tansel (1997) in Ghana and Cote d’Ivoire). Accordingly, it is more likely that individuals who prefer efficiency-based to equity-based wages are those who enjoy better nutrition and health status[5]. Analogous to the case of education, we have therefore, used predicted values for health to account for potential endogeneity between health and preference for efficiency over equity-based wages. However, the health variable was found to be an insignificant determinant of preference for efficiency over equity-based wages. Men are found to favour compensation for efficiency while women prefer equal horizontal wages, independent of effort. This result is consistent with empirical literature that examines gender differences in self-reported distributive justice preferences in work organizations which has found significant differences in the ways that men and women allocate monetary rewards to themselves and/or between themselves and others after performing similar tasks (Kahn et al., 1980). Further, women are found to allocate fewer rewards to themselves and more to their co-workers as compared to men with equivalent inputs (Major et al., 1989). Empirical studies suggest that women are disproportionately represented in lower status and lower paying occupations in which there are less chances for advancement (Treiman and Hartmann, 1981). This might make women expect to give more and get less from work organizations than men do; hence, they would consider it fair to have the more efficient secretary paid equal to the other. An alternative explanation is that men and women may want different things from their work as existing evidence suggests that women are less likely than men to value money and more likely to value the intrinsic nature of work and expressive rewards at work (Nieva and Gutek, 1982). The married dummy is positive and significant suggesting that married employees are more likely to choose efficiency over equity-based wages. One possible explanation


Probability

0.9 0.85 0.8 0.75 0.7 0.65 no education

primary

vocational Education

secondary

university

Figure 1. Illustration of the impact of education on the probability that individuals prefer efficiency over equity-based wages

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for this result is that married employees might want to take advantage of what is commonly referred to in the literature as “the marriage wage premium”. This was originally coined to explain why married men earned more than their unmarried counterparts. In identifying the source of this premium, researchers discarded the presence of self-selection, i.e. the existence of unobservable characteristics that make men more productive in the labour market as well as more attractive in the marriage market. Instead they find evidence that marriage does raise wages via its impact on increased productivity arising from the fact that marriage allows employees to specialize in labour market activities when their spouse specialize in home production (Antonovics and Town, 2004). Furthermore, the resultant wage premium is found to be positively associated with the degree of specialization in the household (Chun and Lee, 2001). Given the evolving nature of division of household duties over time (Gershuny and Robinson, 1988), this result could be indicating that both married men and women employees might want to benefit from this premium. We find that conditional on other factors, preference for wages indexed on worker efficiency increases with age. It could be that older individuals believe in capturing returns to seniority which has been found to be positive and significantly correlated with earnings (Abraham and Farber, 1987; Dohmen, 2004; Dustmann and Meghir, 2005). In terms of ethnicity; our results suggest that Whites are more likely than other races to prefer wage policies indexed on worker efficiency or performance. Catholics are more likely to prefer equity-based wages over efficiency-based wages compared to non-Muslims and non-Protestants. Our results indicate that real GDP per capita negatively affects individuals’ preferences for efficiency over equity-based wages. This possibly indicates that low income nations might be primarily focusing on increasing economic growth and since efficiency and productivity are important determinants of economic growth then individuals are more concerned with efficiency-based wages. We find evidence that individual income tax rates negatively affect individuals’ preferences for efficiency over equity-based wages. These results are confirmed in Figure 2 which reports the predicted probability that individuals prefer efficiency to equity-based wages for a given level of individual income tax rate while holding the rest of the variables constant at their means. This could be capturing the fact that increased individual income taxes might reduce incentives for workers to exert more effort. In this case equity-based wages are preferred as they are independent of workers’ effort or job performance. 0.6

Figure 2. Illustration of the influence of individual income tax rate on the probability that individuals prefer efficiency over equity-based wages

Probability

0.5 0.4 0.3 0.2 0

20

40 60 Income tax rate (%)

80

100

In addition, as Figure 3 shows, the predicted probability that individuals prefer efficiency to equity-based wages decline with income inequality (measured by the Gini coefficient). This is expected since high inequality would likely increase employees’ desire for a more equal income society, which translates into workers’ preferences for equal horizontal wages that will reduce the income inequality levels in the country. We used the globalization index to control for the effect of the country’s integration into the global economy on individuals’ preference for efficiency vis-a`-vis equity indexed wages. Globalization – liberalization of trade, foreign direct investment, and immigration – generally leads to increased competition among nations as well as firms to attract capital. The pro-competition effect of globalization is thought to potentially increase efficiency and lead to productivity gains. The link between trade and productivity gains is supported by several studies, including Kim (2000) for the Republic of Korea, Aghion et al. (2003) and Topalova (2004) for India. Okada (2004) indicates how export promotion in India makes firms put more emphasis on enhancing productivity and promoting a culture for efficiency, this most likely will influence individuals to have preference for efficiency-based wages. Hence, it is not surprising that globalization has a positive impact on employees’ preference for efficiency over equity-based wages as confirmed by our results in Figure 4. Globalization emphasizes profit maximization as well as firms’ competitiveness in the global economy. It is also


Probability

0.5 0.4 0.3 0.2 0.1 0

20

40 60 Gini coefficient

80

100

Figure 3. Illustration of the influence of income inequality on the probability that individuals prefer efficiency over equity-based wages

Probability

0.75 0.7 0.65 0.6 0.55 0

0.2

0.4 0.6 Globalization

0.8

1

Figure 4. Illustration of the influence of globalization on the probability that individuals prefer efficiency over equity-based wages

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expected that all countries pursue a common set of economic policies which foster free markets and efficiency values. This implies that globalization might influence workers to put more emphasis on rewarding efficiency as opposed to equity. In sum, the foregoing discussion highlights the role of both socio-economic and country-level variables in conditioning individuals’ efficiency-equity wages preferences.

610

4. Conclusion Conventional economic theory demonstrates the importance of labour efficiency for economic growth, implying that promoting labour efficiency is one way to achieve increased economic growth. Fundamental to promoting job performance or efficiency is having an understanding of what influences individuals’ preferences for wage structures that reward efficiency. Information on what influences individuals’ preferences for efficiency vis-a`-vis equity-based wages is crucial in designing firms’ wage structures. This paper used the 2005 wave of the World Values Survey data on individuals from 43 countries combined with country-level data to examine socio-economic and country-level characteristics that influence individuals’ preferences for wages that are indexed on job performance or efficiency over equity-based wages. GLLAMM are used to take into account the multi-level nature of our dataset. Our results underscore the importance of both socio-economic and country-level variables in individuals’ efficiency-equity wages considerations. In particular we find that an individual’s preference for efficiency-based wages increases with education and globalization, while it decreases with individual income tax rate and the level of income inequality. This means that institutions and specifically public policy that promotes education and globalization, along with policies that ease individuals’ income tax burden as well as reduced income inequality could be used accordingly to promote mechanisms that reward job performance or efficiency. However, it is important to acknowledge that although empirical evidence supports the importance of rewarding job performance or efficiency for economic growth, different countries or societies might place different relative importance of efficiency vis-a`-vis equity. In some situations equity might be more of a priority to policymakers. Thus, while our analysis has been more inclined to examining the factors that make efficiency-based wages acceptable to individuals, the results need to be put within the context of the policy objectives of the country. Notes 1. Individuals’ preferences for efficiency vis-a`-vis equity-based wages might also affect their decision to remain unemployed or stay out of the labour force. For instance a highly productive individual who prefers efficiency wages and lives in a country that offers a generous unemployment insurance coverage and pro-equity wage policies might choose to stay unemployed. 2. Andorra, Argentina, Australia, Brazil, Bulgaria, Burkina Faso, Chile, China, Cyprus, Egypt, Ethiopia, Finland, Germany, Ghana, India, Indonesia, Italy, Japan, Jordan, Malaysia, Mali, Mexico, Moldova, Morocco, Peru, Poland, Romania, Rwanda, South Africa, South Korea, Serbia, Slovenia, Spain, Sweden, Switzerland, Taiwan, Thailand, Trinidad and Tobago, Turkey, Ukraine, the USA, Vietnam and Zambia. 3. Data on GDP per capita is obtained from the World Development Indicators online database for 2005 (World Bank, 2007). The overall globalization index is obtained from the Centre for

the Study of Globalization and Regionalization (CSGR) at Warwick University, UK (www2. warwick.ac.uk/fac/soc/csgr/research/). The overall Globalization Index is a normalized index based on economic, social, and political sub-indices that allows cross-country comparison of the degree of integration in the global economy over time. We have used the maximum individual income tax rate levied in the country and obtained the data from the complete Worldwide Tax & Finance Site (www.worldwide-tax.com/). We used the Gini coefficient as a measure of income inequality and data on Gini is obtained from Human Development Report by UNDP (2007/2008). 4. We used ordered probit for estimating education and all explanatory variables in the system were used as regressors. 5. In the context of nutrition-based efficiency wage model, poor health is endogenous to the model, as a worker may be healthy in one year but, if he fails to find a job, his health status may deteriorate due to low calorie intake and this could reduce the likelihood of finding a job in the future (Swamy, 1997). References Abraham, K.G. and Farber, H.S. (1987), “Job duration, seniority, and earnings”, American Economic Review, Vol. 77 No. 3, pp. 278-297. Adams, J.S. and Rosenbaum, W.B. (1962), “The relationship of worker productivity to cognitive dissonance about wage inequities”, Journal of Applied Psychology, Vol. 46 No. 3, pp. 161-164. Aghion, P., Burgess, R., Redding, S. and Zilibotti, F. (2003), “The unequal effects of liberalization: theory and evidence from India”, unpublished, London School of Economics, London. Akerlof, G.A. and Yellen, J.L. (1990), “The fair wage-effort hypothesis and unemployment”, The Quarterly Journal of Economics, Vol. 105 No. 2, pp. 255-283. Andrews, I.R. (1967), “Wage inequity and job performance”, Journal of Applied Psychology, Vol. 51 No. 1, pp. 39-45. Antonovics, K. and Town, R. (2004), “Are all the good men married? Uncovering the sources of the marital wage premium”, American Economic Review, Vol. 94, pp. 317-321. Ashenfelter, O. and Krueger, A. (1994), “Estimates of the economic return to schooling from a new sample of twins”, American Economic Review, Vol. 84, pp. 1157-1173. Austin, W. and Walster, E. (1974), “Reactions to confirmations and disconfirmations of expectancies of equity and inequity”, Journal of Personality and Social Psychology, Vol. 30 No. 2, pp. 208-216. Baldwin, M.L., Butler, R.J. and Johnson, W.G. (2001), “A hierarchical theory of occupational segregation and wage discrimination”, Economic Inquiry, Vol. 39 No. 1, pp. 94-110. Bayard, K., Neumark, D., Herllestein, J.K. and Troske, K.R. (1999), “Why are racial and ethnic wage gaps larger for men than for women? Exploring the role of segregation using the new worker-establishment characteristics database”, in Haltiwanger, J., Lane, J., Spietzer, J.R., Theeuwes, J. and Troske, K. (Eds), The Creation and Analysis of Employer-Employee Matched Data, Vol. 241, Elsevier, Amsterdam, pp. 175-203. Blinder, A.S. and Choi, D.H. (1990), “A shed of evidence on theories of wage stickiness”, Quarterly Journal of Economics, Vol. 105 No. 4, pp. 1003-1015. Byron, R.P. and Manaloto, E.Q. (1990), “Returns to education in China”, Economic Development and Cultural Change, Vol. 38, pp. 783-796. Campbell, C.M. and Kamlani, K.S. (1997), “The reasons for wage rigidity: evidence from a survey of firms”, The Quarterly Journal of Economics, Vol. 112 No. 3, pp. 759-789.


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