Publications of Gábor Kézdi

The Roma/non-Roma test score gap in Hungary

This paper documents and decomposes the test score gap between Roma and non-Roma 8th graders in Hungary in 2006. Our data connect national standardized test scores to an individual panel survey with detailed data on ethnicity and family background. The test score gap is approximately one standard deviation for both reading and mathematics, which is similar to the gap between African-American and White students of the same age group in the US in the 1980s. After accounting for on health, parenting, school fixed effects and family background, the gap disappears in reading and drops to 0.15 standard deviation in mathematics.

The effects of child-related benefits and pensions on fertility by birth order: A test on Hungarian data

Using aggregate time-series data from post-war Hungary, we investigated the effect of child-related benefits and pensions on overall fertility and fertility by birth order. The results indicate moderate effects that are robust across a wide range of specifications. According to our estimates, a 1-per-cent increase in child-related benefits would increase total fertility by 0.2 per cent, while the same increase in pensions would decrease fertility by 0.2 per cent. The magnitude of both effects increases by birth order; this is more robust for child-related benefits.

Children of the Post-Communist Transition: Age at the Time of the Parents’ Job Loss and Dropping Out of Secondary School

Using data on children whose parents lost their jobs during the post-communist transition of Hungary, we address the causal effect of unexpected long-term unemployment of parents on their children's educational achievement. We estimate the effect of the children's age at the time of their parents' job loss on their probability of dropping out of secondary school (an event that follows the parents' job loss by many years). The treatment is an additional year reared in a family with regularly employed parents, which can be interpreted as additional human capital investment. We provide bounding estimates to the causal effect. The estimated bounds are tight, they show a substantial effect, and the effect is significantly stronger for preschool age children than for older ones.

Trade in University Training: Cross-State Variation in the Production and Use of College-Educated Labor

The question of this analysis is how the production of college graduates at the state level affects the stock of college-educated workers in the state. The potential mobility of skilled workers implies that the number of college students graduating in an area need not affect the number of college graduates living in the area. However, the production of relatively large numbers of college graduates in a state may lead to increases in the employment of university-trained manpower if industries expand production of goods and services that use college-educated workers intensively. We find at best only a modest link between the production and stock of baccalaureate degree recipients.

Robust Standard Error Estimation in Fixed-Effects Panel Models

This paper focuses on standard error estimation in Fixed-Effects panel models if there is serial correlation in the error process. Applied researchers have often ignored the problem, probably because major statistical packages do not estimate robust standard errors in FE models. Not surprisingly, this can lead to severe bias in the standard error estimates, both in hypothetical and real-life situations. The paper gives a systematic overview of the different standard error estimators and the assumptions under which they are consistent (in the usual large N, small T asymptotics). One of the possible reasons why the robust estimators are not used often is a fear of their bad finite sample properties. The most important results of the paper, based on an extensive Monte Carlo study, show that those fears are in general unwarranted. I also present evidence that it is the absolute size of the cross-sectional sample that primarily affects the finite-sample behaviour, not the relative size compared to the time-series dimension. That indicates good small sample behaviour even when . I introduce a simple direct test analogous to that of White [1980] for the restrictive assumptions behind the estimators. Its finite sample properties are fine except for low power in very small samples.

Jackknife Minimum Distance Estimation

We propose a jackknife minimum distance estimator designed to reduce the finite-sample bias of the optimal minimum distance estimator. Monte Carlo results indicate that our jackknife minimum distance estimator is a promising alternative to existing minimum distance procedures.