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.

Relying on the epidemiological approach, we show that culture is a significant driver of household saving behavior. Second-generation immigrants from countries that put strong emphasis on thrift or wealth accumulation tend to save more in Germany. We confirm these results in data from the UK. By linking parents to their children, we show that these two cultural components affect the saving behavior of both first-generation immigrants and their children, and also provide suggestive evidence that long-term orientation is related to saving behavior through the intergenerational transmission of language.

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 user-friendly and easily integrable set of Matlab codes. JEL-Codes: E600, H200, H310, J220.

We study whether and how time preferences change over the life cycle, exploiting representative long-term panel data. We estimate the age patterns of discount rates from age 25 to 80. In order to identify age effects, we have to disentangle them from cohort and period factors. We address this identification problem by estimating individual fixed effects models, where we substitute period effects with determinants of time preferences that depend on calendar years. We find that discount rates decrease with age and the decline is remarkably linear over the life cycle.

Most economic models assume that time preferences are stable over time, but the evidence on their long-term stability is lacking. We study whether and how time preferences change over the life cycle, exploiting representative long-term panel data. We provide new evidence that discount rates decrease with age and the decline is remarkably linear over the life cycle. Decreasing discounting helps a canonical life-cycle model to explain the household saving puzzles of undersaving when young and oversaving after retirement. Relative to the model with constant discounting, the model's fit to consumption and asset data profiles improves by 40% and 30%, respectively.