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Author: Ludwig, Volker
Resulting in 2 citations.
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Ludwig, Volker Bruderl, Josef |
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Is There a Male Marital Wage Premium? New Evidence from the United States American Sociological Review 83,4 (August 2018): 744-770. Also: http://journals.sagepub.com/doi/abs/10.1177/0003122418784909 Cohort(s): NLSY79 Publisher: American Sociological Association Keyword(s): Earnings, Husbands; Modeling, Fixed Effects; Wage Growth; Wage Levels; Wages, Men Permission to reprint the abstract has not been received from the publisher. This study reconsiders the phenomenon that married men earn more money than unmarried men, a key result of the research on marriage benefits. Many earlier studies have found such a "male marital wage premium." Recent studies using panel data for the United States conclude that part of this premium is due to selection of high earners into marriage. Nevertheless, a substantial effect of marriage seems to remain. The current study investigates whether the remaining premium is really a causal effect. Using conventional fixed-effects models, previous studies statistically controlled for selection based on wage levels only. We suggest a more general fixed-effects model that allows for higher wage growth of to-be-married men. The empirical test draws on panel data from the National Longitudinal Survey of Youth (1979 to 2012). We replicate the main finding of the literature: a wage premium remains after controlling for selection on individual wage levels. However, the remaining effect is not causal. The results show that married men earn more because selection into marriage operates not only on wage levels but also on wage growth. Hence, men on a steep career track are especially likely to marry. We conclude that arguments postulating a wage premium for married men should be discarded. |
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Bibliography Citation
Ludwig, Volker and Josef Bruderl. "Is There a Male Marital Wage Premium? New Evidence from the United States." American Sociological Review 83,4 (August 2018): 744-770.
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Ruttenauer, Tobias Ludwig, Volker |
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Fixed Effects Individual Slopes: Accounting and Testing for Heterogeneous Effects in Panel Data or Other Multilevel Models Sociological Methods and Research published online (10 June 2020): DOI: 10.1177/0049124120926211 Cohort(s): Children of the NLSY79, NLSY79 Publisher: Sage Publications Keyword(s): Head Start; Marital Status; Modeling, Fixed Effects; Monte Carlo; Research Methodology; Wage Dynamics Permission to reprint the abstract has not been received from the publisher. Fixed effects (FE) panel models have been used extensively in the past, as those models control for all stable heterogeneity between units. Still, the conventional FE estimator relies on the assumption of parallel trends between treated and untreated groups. It returns biased results in the presence of heterogeneous slopes or growth curves that are related to the parameter of interest (e.g., selection into treatment is based on individual growth of the outcome). In this study, we derive the bias in conventional FE models and show that fixed effects individual slope (FEIS) models can overcome this problem. This is a more general version of the conventional FE model, which accounts for heterogeneous slopes or trends, thereby providing a powerful tool for panel data and other multilevel data in general. We propose two versions of the Hausman test that can be used to identify misspecification in FE models. The performance of the FEIS estimator and the specification tests is evaluated in a series of Monte Carlo experiments. Using the examples of the marital wage premium and returns to preschool education (Head Start), we demonstrate how taking heterogeneous effects into account can seriously change the conclusions drawn from conventional FE models. Thus, we propose to test for bias in FE models in practical applications and to apply FEIS if indicated by the specification tests. |
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Bibliography Citation
Ruttenauer, Tobias and Volker Ludwig. "Fixed Effects Individual Slopes: Accounting and Testing for Heterogeneous Effects in Panel Data or Other Multilevel Models." Sociological Methods and Research published online (10 June 2020): DOI: 10.1177/0049124120926211.
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