Long-term changes in married couples' labor supply and taxes: Evidence from the US and Europe since the 1980s

Abstract

We document the time-series of employment rates and hours worked per employed by married couples in the US and seven European countries (Belgium, France, Germany, Italy, the Netherlands, Portugal, and the UK) from the early 1980s through 2016. Relying on a model of joint household labor supply decisions, we quantitatively analyze the role of non-linear labor income taxes for explaining the evolution of hours worked of married couples over time, using as inputs the full country-and year-specific statutory labor income tax codes. We further evaluate the role of consumption taxes, gender and educational wage premia, and the educational composition. The model is quite successful in replicating the time series behavior of hours worked per employed married woman, with labor income taxes being the key driving force. It does however capture only part of the secular increase in married women's employment rates in the 1980s and early 1990s, suggesting an important role for factors not considered in this paper. We will make the non-linear tax codes used as an input into the analysis available as a userfriendly and easily integrable set of Matlab codes.

How Does Taxation Affect Hours Worked in EU New Member States?

“…It is well-known that changes in tax policies can affect women's and men's labor market participation in different ways (see for example Bick et al 2018a). We extend our analysis by estimating how sensitive employment rates are to different types of taxes, both for women's and men's employment rates.…”

“…Causa (2009) finds that marginal taxes in OECD countries disincentivize women working longer hours, while the effect is almost insignificant for men. Recent studies by Bick et al (2018a), ©International Monetary Fund. Not for Redistribution Chakraborty et al (2015) and Bick and Fuchs-Schundeln (2018) focus more on demographics, married couple dynamics, and population subgroups within the labor market with disaggregated data.…”

Hours Worked Across the World: Facts and Driving Forces

“…When focusing on Europe and the US (Bick and Fuchs-Schündeln, 2017; Bick and Fuchs-Schündeln, 2018; Bick et al , 2018b; Bick et al , 2019), the data sources are the European Union Labour Force Survey for the European countries, and the Current Population Survey for the US. The European Union Labour Force Survey is a collection of annual labour force surveys from different European countries.…”

“…While both the CPS and the European Union Labour Force Survey (the latter only since 2005) cover the entire year, we find that they still substantially underestimate vacation days, which inhibits the measurement of hours worked per worker. We thus correct for vacation days from external data sources (see Bick et al ., 2019, for details).…”

“…Based on our micro data, we can conduct a full statistical decomposition of the cross-country differences, which gives useful insights into potential driving forces. In Bick et al (2019), we focus on individuals aged 15–64, in line with the OECD, and on the recent cross-section of the years 2013–15. Figure 1 shows average annual hours worked per person for the US and eighteen European countries grouped into Scandinavia (Denmark, Norway, Sweden), Western Europe (Austria, Belgium, France, Germany, Ireland, Netherlands, Switzerland, UK), Eastern Europe (Czech Republic, Hungary, Poland), and Southern Europe (Greece, Italy, Portugal, Spain).…”