kgoraus

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Karolina
Goraus

Karolina Goraus worked with GRAPE on one of our first pension project and labor market inequality. She is currently an economist at The World Bank and an Assistant Professor at Faculty of Economics, University of Warsaw.

Opublikowane | Published

  • How to make a country look equal | PLOS ONE

    Methods for estimating the the scope of inequality in various outcome measures such as income, education, health or poverty are fairly accurate in detecting differences adjusted for individual characteristics. However, the actual estimated inequality may depend on the interaction between (the weakness of) the method and (the weakness of) the institutional environment. We make a case by comparing the country rankings for the adjusted gender wage gap among 23 EU countries. We show that the effects of these interactions are indeed large by comparing the estimates from various methods obtained from the same database. In fact, depending on the control variables and estimation method, a country may change its position in the ranking by as much as 10 positions -- both towards greater equality and towards greater inequality. We argue that this variability in country ranking position may yield important policy insights into prioritizing intervention. We also infer that given the intimate and unbreakable relationship between institutional deficiencies and features of the adjustment methods, ranking per se may be misguiding the public debate and thus should be abandoned or substantially refined.

    Gender wage gaps are typically measured by the means of decomposition. Proliferation of methods makes the choice of the correct estimator for a given data a conceptual challenge, especially if data availability necessitates simplifications. The challenge lies in accounting for observable differences adequately, which in itself is not only a data issue, but also a conceptual issue. Ideally, one would want to compare men and women actually “alike” in terms of all relevant characteristics, including hours effectively worked, commitment, talent. However, many of these characteristics are not observable (or are imperfectly measured, e.g. human capital).

    Decompositions are prone to multiple risks. For example, the urge to compare only the comparable implies that a decision needs to be made about the use of observations which clearly are not comparable. Nopo (2008) proposes to use these observations to infer about the possible selectivity in this process, but alternative approaches consist of reweighing or neglecting this issue. Similar choices concern the treatment of distributional issues. Finally, for the parametric methods, the dependence on the functional form may influence the results as well. Consequently, depending on the features of a given labor market, an estimate of gender wage gap obtained with a given method is likely to overstate or understate the extent of true unjustified inequality in wages.

    We make available a dataset which provides a full selection of gender wage gap estimates for the EU countries, using data from EU-SILC. Across countries and years, everybody can see for themselves, what is the source of the gender wage inequality in a given European country. We provide:

    • A dta file with the full set of estimates for the gender wage gaps and a generating dofile
    • Data documentation
    Joanna
    Tyrowicz
    Karolina
    Goraus
    Lucas
    van der Velde
  • How (not) to make women work? Evidence from transition countries | Social Science Research

     
    Women in developed economies have experienced an unparalleled increase in employment rates, to the point that the gap with respect to men was cut in half. This positive trend has often been attributed to changes in the opportunity costs of working (e.g. access to caring facilities) and not-working (e.g. educational attainment). Meanwhile, the gender employment gaps were stagnant in transition economies. Admittedly, employment equality among genders was initially much higher in transition countries. We exploit this unique evidence from transition and advanced countries, to analyze the distributional nonlinearities in the relationship between the institutional environment and the (adjusted) gender employment gaps. We estimate comparable gender employment gaps on nearly 1600 micro databases from over 40 countries. We relate these estimates to changes in the opportunity costs of working and not-working. Changes in opportunity costs exhibited stronger correlation with gender employment equality where the gap was larger, i.e. advanced economies. We provide some evidence that these results are not explained away by transition-based theories, and argue that the observed patterns reflect a level effect. Currently, advanced and transition economies are at par in terms of gender employment equality. Hence, the existing instruments might not be sufficient to further reduce the gender employment gap.

    The data for replication is distributed here.

    Joanna
    Tyrowicz
    Karolina
    Goraus
    Lucas
    van der Velde
  • Which gender wage gap estimates to trust? A comparative analysis using data from Poland | Review of Income and Wealth

    The aim of this paper is to compare estimates of the adjusted wage gap from different methods and sets of conditioning variables. We apply available parametric and non‐parametric methods to LFS data from Poland for 2012. While the raw gap amounts to nearly 10 percent of the female wage; the adjusted wage gap estimates range between 15 percent and as much as 23 percent depending on the method and the choice of conditional variables. The differences across conditioning variables within the same method do not exceed 3pp, but including more variables almost universally results in larger estimates of the adjusted wage gaps. Methods that account for common support and selection into employment yielded higher estimates of the adjusted wage gap. While the actual point estimates of adjusted wage gap are slightly different, all of them are roughly twice as high as the raw gap, which corroborates the policy relevance of this methodological study.

    Joanna
    Tyrowicz
    Karolina
    Goraus
    Lucas
    van der Velde
  • Decreasing fertility vs increasing longevity: raising the retirement age in the context of ageing processes | Economic Modelling

    Given the decreasing fertility and increasing longevity, in many countries the policy debate emphasizes the role of either raising the minimum eligible retirement age (MERA) or raising fertility to avoid adverse changes in the population structure. In this paper we evaluate the welfare and macroeconomic effects of increasing the retirement age for various demographic scenarios under three major pension systems (defined benefit, notionally defined contribution and funded defined contribution). We compare populations with decreasing fertility, increasing longevity and one subject to both of these changes, and show that the welfare effects of raising MERA stem mainly from longevity. We show that – for increasing longevity – raising the retirement age is universally welfare enhancing for all living and future cohorts, regardless of the pension system and fertility. Finally, we show scope for further welfare gains if productivity is relatively high at old ages.

    Joanna
    Tyrowicz
    Jan
    Hagemejer
    Karolina
    Goraus
    Marcin
    Bielecki
  • Small assumptions (can) have a large bearing: evaluating pension system reforms with OLG models | Economic Modelling

    The objective of this paper is to inquire the consequences of some simplifying assumptions typically made in the overlapping generations (OLG) models of pension systems and pension system reforms. This literature is largely driven by policy motivations. Consequently, the majority of the papers is extremely detailed in the dimension under scrutiny. On the other hand, complexity of general equilibrium OLG modeling necessitates some simplifications in the model. We run a series of experiments in which the same reform in the same economy is modeled with six different sets of assumptions concerning the shape of the utility function, time inconsistency, bequests? redistribution, labor supply decisions and internalizing the linkage between social security contributions and benefits in these decisions as well as public spending. We find that these assumptions significantly affect both the size and the sign of the macroeconomic and welfare measures of policy effects with the order of magnitude comparable to the reform itself.

    Joanna
    Tyrowicz
    Krzysztof
    Makarski
    Jan
    Hagemejer
    Karolina
    Goraus
    Marcin
    Bielecki
  • Gender Wage Gap in Poland – Can It Be Explained by Differences in Observable Characteristics? | Ekonomia

    The raw gender wage gap over the period 1995-2012 amounts to app. 9% of hourly wage and is fairly stable. However, the raw gap does not account for differences in endowments between genders. In fact, the adjusted wage gap amounts to as much as 20% on average over the analysed period and shows some cyclical properties. The estimates of adjusted gender wage gap do not seem to exhibit any long-term trends, which suggest that in general neither demographic changes nor the progressing transition underlie the phenomenon of unequal pay for the same work among men and women.

    Joanna
    Tyrowicz
    Karolina
    Goraus
  • Estimates of the gender employment gap

    This data contains the estimates of gender employment gaps on nearly 1600 micro databases from over 40 countries, spanning from Kazakhstan to Spain and covering 30 years of history. The estimates of gender employment gap are adjusted for individual characteristics. We use this data to ask if the existing instruments are sufficient to further reduce the gender inequality in employment.

  • Gender wage gaps around EU and across methods

    Gender wage gaps are typically measured by the means of decomposition. Proliferation of methods makes the choice of the correct estimator for a given data a conceptual challenge, especially if data availability necessitates simplifications. The challenge lies in accounting for observable differences adequately, which in itself is not only a data issue, but also a conceptual issue. Ideally, one would want to compare men and women actually “alike” in terms of all relevant characteristics, including hours effectively worked, commitment, talent.