The public-private sector wage gap in Zambia in the 1990s: A quantile regression approach

We investigate the determinants of wages in Zambia and based on the quantile regression approach, we analyze how their effects differ at different points in the wage distribution and over time. We use three cross-sections of Zambian household data from the early nineties, which was a period of economic transition, because items as privatization and deregulation were on the political agenda. The focus is placed on the public-private sector wage gap, and the results show that this gap was relatively favorable for the low-skilled and less favorable for the high-skilled. This picture was further strengthened during the period 1991–1996.     

Asymmetric inflation dynamics: Evidence from quantile regression analysis

This paper applies the regression quantile approach developed by Koenker and Xiao (2004) to investigate the dynamic behavior of inflation in 12 OECD countries. By analyzing the behavior in a wide range of quantiles, this method allows us to quantify the influence of various sizes of shocks that hit the inflation, and is able to capture possible asymmetric adjustment of the inflation towards to its long-run equilibrium. It therefore sheds new lights on the inflation dynamics compared with the conventional unit root methodologies. Our results suggest that generally, the inflation rates are not only mean-reverting but also exhibit asymmetries in their dynamic adjustments, in which large negative shocks tend to induce strong mean reversion, and on the contrary, large positive shocks do not. Policy implications related to the empirical findings are also provided.     

Wage differentials by sector and gender: a quantile analysis for the Spanish case

This paper analyses existing wage differentials between workers in the public and private sectors and by gender in Spain. This analysis is run throughout the entire earnings distribution and observed wage differentials are decomposed into a part explained by differences in productive characteristics and a part due to differences in returns to such characteristics. Our results show that public sector workers tend to earn higher wages than private employees, although most of this sector wage gap is due to better public workers’ productive characteristics. A wage premium in favour of men is also found in both the public and private sectors, with the gender wage gap greater at the top of the earnings distribution.     

Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach

This paper analyzes the gender-based wage gaps across the wage distribution in the private and public sectors in Italy for the years 2005–2010. We use quantile regression methods to estimate and decompose the wage gap at all wage levels and propose a two-step procedure that relies on a novel approach to estimating fixed effects quantile regressions. The method's main advantage is that it allows the employment sector's marginal effect on wages at various points of the distribution to be estimated, while accounting for both observable and time-invariant unobservable factors. The new method stresses important differences with respect to standard decomposition analyses and amplifies the differences in the two sectors' wage-setting mechanisms. When the estimation is net of individual heterogeneity, the gender-based wage gap decreases in both sectors and there is evidence of a glass ceiling effect, but only in the public sector. Economic grounds are provided.     

Interindustry wage differentials in dummy variable models

Normalized interindustry wage differentials à la Krueger and Summers [Krueger, A.B., Summers, L.H., 1988. Efficiency wages and the inter-industry wage structure. Econometrica 56, 259–293] derive from a general specification of wage equations with dummy variables which cannot be directly estimated. This note illustrates how they can be obtained from the coefficients of a more specific parameterization and how their estimated variances can be transformed accordingly.     

Exploring the effect of diversification strategy on R&D intensity using quantile regression: evidence from France

This study examines the relationship between firm diversification strategy and R&D intensity for a sample of large French companies between 2008 and 2012. Applying quantile regression, we provide evidence that the choice of diversification affects R&D intensity in a differentiated way. The results indicate that a low level of diversification (below the twentieth quantile) has no significant impact on R&D intensity. Conversely, a moderate or high level of diversification has a negative and significant impact on R&D intensity. These findings suggest that R&D intensity seems to be significantly higher in related-business firms than in unrelated-business firms.     

A quantile regression approach for estimating panel data models using instrumental variables

We introduce a quantile regression approach to panel data models with endogenous variables and individual effects correlated with the independent variables. We find newly developed quantile regression methods can be easily adapted to estimate this class of models efficiently.     

Nonparametric quantile regression analysis of R&D-sales relationship for Korean firms

This paper applies the nonparametric quantile regression estimation procedure to the analysis of the innovation-firm size relationship using Korean manufacturing firms data. Due to the high asymmetric distribution of R&D expenditure, the mean regression does not capture properly the stylized facts of R&D behavior; hence it underestimates the sales elasticity. Comparing the parametric estimates and nonparametric estimates allows us to see that there exists a nonlinear relationship in innovative activity and sales. Dividing the data into three groups according to the sales volume, the elasticity in the medium-sized firms is the biggest for scientific firms. This result conforms that the findings of Scherer (1965) coincide with findings from Korean manufacturing firms data in the sense that R&D expenditure tends to increase faster than firm size with size up to a point and then more slowly among larger firms. For the non-scientific firms, it steadily increases showing increasing returns to scale in innovative activity in large firms.     

Testing for uniform wage trends in West-Germany: A cohort analysis using quantile regressions for censored data

The rise of unemployment in West Germany is often attributed to an inflexibility of the wage structure in the face of a skill bias in labor demand trends. In addition, there is concern in Germany that during the 70s and 80s unions were pursuing a too egalitarian wage policy. In a cohort analysis, we estimate quantile regressions of wages taking account of the censoring in the data. We present a new framework to describe trends in the entire wage distribution across education and age groups in a parsimonious way. We explore whether wage trends are uniform across cohorts, thus defining a macroeconomic wage trend. Our findings are that wages of workers with intermediate education levels, among them especially those of young workers, deteriorated slightly relative to both high and low education levels. Wage inequality within age-education groups stayed fairly constant. Nevertheless, the German wage structure was fairly stable, especially in international comparison. The results appear consistent with a skill bias in labor demand trends, recognizing that union wages are only likely to be binding floors for low-wage earners.     

Integrated Conditional Moment testing of quantile regression models

In this paper we propose a consistent test of the linearity of quantile regression models, similar to the Integrated Conditional Moment (ICM) test of Bierens (1982) and Bierens and Ploberger (1997). This test requires re-estimation of the quantile regression model by minimizing the ICM test statistic with respect to the parameters. We apply this ICM test to examine the correctness of the functional form of three median regression wage equations.     

School composition effects in Denmark: quantile regression evidence from PISA 2000

Data from the first wave of the OECD PISA study are combined with register data for Denmark to estimate the effect of the socioeconomic mix of schools on students’ test scores. A major disadvantage of the PISA design for the analysis of school composition effects is the small students-per-school samples. Adding family background data from administrative registers for all same-aged schoolmates of the PISA students helps overcome this. To compensate for endogeneity in the school composition variable, the results are conditioned on a rich set of family and school variables from the PISA data. Quantile regression results suggest differential school composition effects across the conditional reading score distribution, with students in the lower quantiles achieving the largest test score gains. Mathematics results suggest that high- and low-ability students benefit equally from attending schools with a better student intake, and most results for science are only marginally significant. These results imply that mixing students of different home backgrounds could improve equity of achievement for both reading and mathematics; however, the average skill level would improve only for reading literacy. In mathematics, mixing students would not raise average outcomes, because the detrimental effect on students in the higher quantiles would offset positive effects on those in the lower quantiles. I thank Amelie Constant, Bernd Fitzenberger, Eskil Heinesen, Peter Jensen, Craig Riddell, Michael Rosholm, Nina Smith, Robert Wright and participants at the ESPE and EALE 2003 conferences and at AKF seminars, and two anonymous referees for helpful comments and suggestions. Financial support provided by the Danish Social Science Research Council is gratefully acknowledged.     

Political stability and growth: An application of dynamic GMM and quantile regression

This paper studies the effect of political stability on economic growth by taking 120 developing countries over the period of 1996–2014. We apply relatively advanced dynamic two step system-GMM and quantile regression. Political stability is found to be a key determinant of economic growth. More importantly, political instability (or risk) is found to be higher in the OIC countries and is a deterrent to economic growth. Also, for the lower and middle income OIC countries, political instability appears to affect economic growth more severely perhaps due to the absence of strong economic and political institutions. Moreover, political instability is also found to be significantly higher in the oil-dependent OIC countries. Notably, political instability is likely to affect growth through the channels of investment and human capital accumulation in the developing countries. Finally, the impact of political stability and political instability on growth is found to be equally distributed across the OIC countries with higher or lower growth level. Therefore, the development of political and economic institutions along with human capital development is recommended for all the developing countries in general and the OIC countries in particular.     

Portfolio style: Return-based attribution using quantile regression

Return-based classification identifies a portfolio's style signature in the time series of its returns. Detection is based on a regression of portfolio returns on returns of factor mimicking indices. The method is easy to apply and does not require information about portfolio composition. Classification using least squares means that style is determined by the way factor exposure influences expected returns. We introduce regression quantiles as a complement to the standard analysis. The regression quantiles extract additional information from the time series of returns by identifying the way style affects returns at places other than the expected value. This allows discrimination among portfolios that would be otherwise judged equivalent based on conditional expectations. It also provides direct information about the impact of style on the tails of the conditional return distribution. Simple examples are presented to illustrate regression quantile classification.     

Investor sentiment and the prediction of stock returns: a quantile regression approach

We employ quantile regression to provide a detailed picture of the stock return forecasting ability of investor sentiment. We find that investor sentiment predicts aggregate stock returns at lower quantiles. However, the forecasting power is lost at upper quantiles. The results are robust after controlling for a comprehensive set of macroeconomic and financial predictors and for characteristic portfolios. We also show that investor sentiment consists mainly of cash flow news and contains little information about discount rate news. The ability to forecast cash flows increases gradually from the lower quantiles to upper quantiles. Our results do not support that the ability of investor sentiment to predict stock returns comes from a rational forecast of future cash flows.     

Wage differentials and state‐private sector employment choice in Yugoslavia*

In this study we use the newly available Yugoslavian Labor Force Survey data to investigate wage differentials and employment decisions in the state and private sectors in Yugoslavia. For the analysis we use three empirical models that rely on different statistical assumptions. We extend the standard switching regression model to allow non‐normality in the joint distribution of the error terms. After correcting for the sector selection bias and controlling for workers’ characteristics we find a private sector wage advantage. The wage premium is largest for workers with low education levels and declining for workers with higher educational levels. Given the regulatory and tax policies that pushed the private sector into the informal sphere of the economy during the period covered by our data, we argue that the state/private wage gap is likely to grow in the future. This will make it increasingly difficult for the state sector to attract and retain highly skilled employees.     

Measuring the gender wage gap—a methodological note

ABSTRACT

We propose to estimate the Blinder-Oaxaca decomposition by a single-equation model augmented with interactions between the group membership and other predictors. The relative importance of predictors on the discriminatory wage gap is examined by the interaction coefficients, which may lead to very different conclusions than the usual percentage calculations using the detailed decomposition method. Comparisons are made between the traditional interpretations and those suggested here using wage data from Finland. The decomposition analysis suggests that the discriminatory male-female wage gap is largely related to work experience, while our preferred model points to the importance of family gap and working industry.     

Gender wage gaps and economic crisis in Greece

ABSTRACT

We examine gender wage gap (GWG) in Greece for 2013, by using a survey data set. Our findings show first, that the unadjusted GWG is 15.3%, while European Commission reports a value of 15%. Secondly, we derive the ‘adjusted’ GWG, using the Oaxaca and Ransom (OR) and the Juhn, Murphy and Pierce (JMP) methods to be ranging from 10% to 13.6%. Thirdly, looking into the behaviour of the full population, we find a decreasing trend for the discrimination effects, an increasing trend for the residuals effects and a ‘random’ endowments effects while moving to higher deciles. These three effects are associated to the economic crisis 2008–2015. Fourthly, our findings do not show evidence of either a ‘glass ceiling’ effect or a ‘sticky floor’ effect. Finally, that there is strong evidence that investing in higher education reduces the wage discrimination between sexes.     

Modelling the effect of the geographical environment on Islamic banking performance: A panel quantile regression analysis

While studies have focused on Islamic banking, research on the effect of the geographical environment on Islamic banks is scarce. We investigate this issue by using daily data on 12 Islamic banks in four regions (Africa, Asia, Europe, and the United States) from July 2007 to April 2016. We apply different methodological approaches (principal component analysis, panel data tests, and quantile regression). First, the principal component analysis shows that the performance of Islamic banks varies among regions. Second, the linear panel regression highlights that the geographical environment positively and significantly affects Islamic banking, suggesting the importance of externality effects. Finally, the environmental effect seems to vary with quantiles (positive effect for the lowest quantile versus negative effect for the highest quantile). This quantile specification points to nonlinearity in the environment–Islamic bank performance relationship, reflecting a time-varying discipline imposed by the Sharia board (Islamic Law). This finding helps better explain the main difference between Islamic banks in the East (Africa and Asia) and those in the West (Europe and the United States) and also enables investors to adjust their portfolio choices when considering the products of Islamic banks according to regional specificities.     

Tracing the impact of large minimum wage changes on household welfare in Indonesia

Minimum wage legislation has been introduced and expanded in many developed and developing countries, in the hope that it would improve the living standards of the poor and reduce inequality. This study examines the impact of large minimum wage changes in Indonesia. The results indicate serious limitations of the minimum wage for improving living standards and reducing inequality.     

The effect of minimum wage on firm markup: Evidence from China

Our paper examines the impact of minimum wage on firm markup in China. We find that minimum wage generates a positive effect on firm markup. More value-enhancing innovative activities, TFP improvement, and efficient labor resource allocation are the potential channels. Further, the positive influence of minimum wage is more pronounced for privately-owned firms, for firms with higher labor intensity and firms with less financial constraints. Besides, these findings are generally robust to different estimation methods. Our results provide new insights into understanding the channels through which labor regulation may cause the change of markup for the emerging markets countries.