Projects
Published work:
Poor housing quality and the health of newborns and young children (joint work with Tamás Hajdu and Gábor Kertesi)
This study uses linked administrative data on live births, hospital stays, and census records for children born in Hungary between 2006 and 2011 to examine the relationship between poor housing quality and the health of newborns and children aged 1–2 years. We show that poor housing quality, defined as lack of access to basic sanitation and exposure to polluting heating, is not a negligible problem even in a high-income EU country like Hungary. This is particularly the case for disadvantaged children, 20–25% of whom live in extremely poor-quality homes. Next, we provide evidence that poor housing quality is strongly associated with lower health at birth and a higher number of days spent in inpatient care at the age of 1–2 years. These results indicate that lack of access to basic sanitation, hygiene, and non-polluting heating and their health impacts cannot be considered as the exclusive problem for low- and middle-income countries. In high-income countries, there is also a need for public policy programs that identify those affected by poor housing quality and offer them potential solutions to reduce the adverse effects on their health.
Work in progress:
The Impact of Childcare on Maternal Employment (joint work with Judit Berei, Márton Csillag, Hanna Erős, Judit Krekó, Ágota Scharle, 2022)
This paper examines the effect of childcare availability on maternal employment in Hungary based on 2016 Microcensus data. We exploit the exogenous variation in access to childcare due to informal admission practices based on the date of birth, to identify the effect of childcare availability on maternal employment and the children’s enrolment. We find that on average, expanding the coverage of nurseries to the same level as kindergartens would lead to around 7.3 percentage points higher maternal employment, an around 25% higher employment rate compared to the baseline of mothers with a child aged 2-2.5 years. At the same time, the decomposition of the link between childcare availability and employment shows that enrolment would increase by 17.7 percentage points due to the higher coverage, close to 40% compared to the baseline. Enrolment in childcare would increase maternal employment probability by around 41 percentage points, around two-thirds of the employment rate of mothers. We also investigate the heterogeneities of the effect along demographic characteristics using causal forests, and the economic cycle by expanding the analysis to the 2011 Census. We find that in 2016 the childcare availability effect is higher for mothers with 3 children, living in villages, or municipalities without nurseries. The employment effect is lower in the 2011 Census, while the effect on enrolment in formal childcare remains similar, suggesting the importance of weaker labour demand in 2011.
How do workers learn from their coworkers in the workplace, especially when collaboration is essential? We investigate the mechanism of learning in a high-skill collaborative environment: elite male soccer. We start by confirming positive effect of coworker quality found in administrative data. Our setting is conducive to find evidence of learning as it can compare players in very similar units of soccer squads. Instead of a wage, we can observe how much value a player could generate in another team over many years. This is our human capital estimate. Workers with coworkers of higher average human capital will see their human capital grow faster. We also confirm that beyond average, skewness matters, being together with stars is helpful in learning. However, proximity is not enough, learning happens via exposure to the best players and the depth of interaction with them. Our special dataset allows investigating details of what happens among coworkers. First, we show that players with high exposure to peers, playing more minutes in games, will experience higher growth of their human capital. Again, by collaborating with stars, learning will be more pronounced. Second, the strength of on the pitch interaction measured via passing intensity will point to even more learning opportunities. All results are especially important for younger players. Finally, integrating data measuring actual skills, such as short pass accuracy, we can tell apart actual learning from higher valuation due to better performance when surrounded by better coworkers.
Projects for the Ph.D. Thesis:
This paper studies the effect of tax incentives on completed fertility and female labor supply based on the 2011 family tax break reform in Hungary. I build a unique, family-level linked dataset from the 2016 Microcensus and the 2011 Census of Hungary to measure changes in the number of children and labor market outcomes. I take advantage of the nonlinearity of the tax break along the initial number of children and prospective household income and compare cohorts just before and after the end of fecundity. I argue that the policy introduced quasiexperimental variation, enabling the identification of the long-run completed fertility effects without capturing adjustments in the timing of births. The estimates suggest an overall 3.2% increase in completed fertility, driven by religious households and mothers with secondary education. Additionally, I estimate a structural model to augment the reduced-form findings, enabling the study of long-run labor supply effects and alternative policies. The model suggests a small long-run increase in mothers’ labor force participation, induced by low-income households.
Charitable Behavior and Public Intervention: a Survey Experiment (joint work with Francesca Leombroni)
In this paper we measure the extent of charitable behavior crowding out public intervention, and how this phenomenon affects the welfare of the poor. To achieve this objective we collect novel survey data on a representative sample of the U.S. adult population. In the survey, respondents are asked to go through several hypothetical scenarios which are built starting from a simple model of public good contribution, in order to learn about their preferences and expectations regarding donations and taxation. We find that when donations are available, government expenditure on the poor is lower in equilibrium. Yet, households in need are better off due to disproportionately higher donations. This means that, in our setting, private charity crowds out public intervention only to a limited extent, affecting equilibrium-level taxes only slightly. Moreover, as equilibrium tax rates without donations are not high enough to compensate for the lack of private charity, our results suggest that people are less driven by inequity aversion than by the direct utility of donating (warm glow). As an implication, we conclude that in the United States the widespread availability of private charity plays a pivotal role in alleviating poverty, which government intervention cannot substitute for due to the structure of voters' preferences.
I build a dynamic equilibrium model of household behavior with unobserved heterogeneity in the desired number of children to examine how policies targeting the housing market affect choices of fertility, location, and house size of young households. I estimate the model's structural parameters using data from Hungary to evaluate the dynamic effects of the Family Housing Allowance policy, which provided a sizeable lump-sum subsidy for house purchases, with built-in commitment regarding the number of children the family would have. The model suggests that the combination of lower interest rates and the allowance increases house prices substantially compared to the baseline, which for poorer households counteract some of the positive welfare effects of the policy. While according to the model, completed fertility increases due to the policy by around 5-10\% on average, mainly driven by poorer households, their housing conditions worsen in the long run due to the elevated house prices. Richer households experience no adverse effects of the policy, however, their completed fertility remains unaffected.
Other Works:
Measuring the Influence of Coaches on NBA Players’ Development, with Spillovers (Data Science Term Project, 2017)
In this paper I construct a quantitative measure to evaluate the influence of NBA coaches on long-term player development, based on the players’ productivity measured in win shares. Using scraping methods I collect data of 17 seasons of NBA statistics (1999-2016) on all players, coaches and assistant coaches, recording their performance and occupation, to create a network dataset with two types of nodes: mentors and mentees. Mentees are young players who are potentially influenced by coaches, assistant coaches, and older players (the mentors). Controlling for their initial skill level I quantify their prime production and link it to the previous network of mentors. The mentors are allowed to have direct and indirect effects, the latter resulting from spillovers through their mentees becoming mentors later in their careers.