Company Taxation in the European Union

This paper investigates different measures of corporate tax burden ranging from the most basic ones such as the statutory tax rate to the effective tax rates. Each of these measures has advantages and disadvantages and they may lead to different rankings of countries. One of the reasons lies the fact that they measure different things. The comparison of the statutory tax rates to the effective ones for the EU-27 during the period of 1998-2009 sometimes reveals very significant differences between these indicators. Taking this into consideration, the paper suggests that corporate tax burden analysis should not be limited to the most basic and readily available measure in the form of the statutory tax rate. Different measures are tailored to answer different research questions. Moreover, the article presents changes of company taxation for the EU-27 within 1998-2009.W artykule dokonano przeglądu miar obciążenia podatkowego przedsiębiorstw. Rozpoczynając od wielkości najprostszych, jak stopa nominalna, a kończąc na miarach efektywnych. Każdy ze wskaźników ma wady i zalety, a jego wykorzystanie może prowadzić do różnego uszeregowania państw ze względu na poziom opodatkowania. Jedną z przyczyn jest fakt, iż wielkości te mierzą inne rzeczy. Porównanie stóp nominalnych i efektywnych w krajach UE-27, w latach 1998-2009, wskazuje na istnienie niekiedy bardzo istotnych różnic pomiędzy analizowanymi wskaźnikami. W związku z tym artykuł sugeruje, iż nie należy ograniczać analiz opodatkowania przedsiębiorstw, do najprostszego i najłatwiej dostępnego wskaźnika w postaci ustawowej stopy podatkowej a rozszerzyć je o miary efektywne. Wielkości te, stanowiące lepszy instrument do porównań międzynarodowych, umożliwiają przeprowadzenie wszechstronnych badań

Small Sample Bias in Synthetic Cohort Models of Labor Supply

In synthetic cohort models (cross-sectional data grouped at the cohort and year level), researchers often ignore potential biases induced by sampling error because they have 100 or 200 observations per group. I investigate small sample biases in the context of two synthetic cohort labor supply applications ? a model of intertemporal labor supply of men (similar to that of Browning, Deaton, and Irish, 1985) and a female labor supply model (similar to that of Blundell, Duncan, and Meghir, 1998). My approach is to use the Current Population Survey to compare the estimates when group sizes are extremely large to those that arise from randomly drawing subsamples of observations from the large groups. This provides a natural framework for examining the extent of small sample biases and the group sizes required so that small sample biases are negligible. I augment this approach with Monte Carlo analysis so as to precisely quantify biases and coverage rates. I find that, in these two applications, thousands of observations per group are required before small sample issues can be ignored in estimation. In these applications, sampling error leads one to underestimate intertemporal labor supply elasticities for men, and conclude that the income response of female labor supply is zero or tiny when in fact it is quite large.

Improved Errors-in-Variables Estimators for Grouped Data

Grouping models are widely used in economics but are subject to finite sample bias. I show that the standard errors-in-variables estimator (EVE) is exactly equivalent to the Jackknife Instrumental Variables Estimator (JIVE), and use this relationship to develop an estimator which, unlike EVE, is unbiased in finite samples. The theoretical results are demonstrated using Monte Carlo experiments. Finally, I implement a model of intertemporal male labor supply using microdata from the United States Census. There are sizeable differences in the wage elasticity across estimators, showing the practical importance of the theoretical issues even when the sample size is quite large.psuedo-panel, small sample bias, labor supply

The effect of high school rank in English and math on college major choice. ESRI Working Paper No. 650 January 2020

Using unique data on preference rankings for all high school students who apply for college in Ireland, we investigate whether, conditional on absolute achievement, within school-cohort rank in English and math affects choice of college major. We find that higher rank in math increases the likelihood of choosing STEM and decreases the likelihood of choosing Arts and Social Sciences. Similarly, a higher rank in English leads to an increase in the probability of choosing Arts and Social Sciences and decreases the probability of choosing STEM. The rank effects are substantial, being about one third as large as the effects of absolute performance in math and English. We identify subject choice in school as an important mediator – students who rank high in math are more likely to choose STEM subjects in school and this can partly explain their subsequent higher likelihood of choosing STEM for college. We also find that English and math rank have significant explanatory power for the gender gap in the choice of STEM as a college major--they can explain about 36% as much as absolute performance in English and math. Overall, the tendency for girls to be higher ranked in English and lower ranked in math within school-cohorts can explain about 6% of the STEM gender gap in mixedsex schools and about 16% of the difference in the STEM gender gap between mixedsex schools and same-sex schools. Notably, these effects occur even though within-school rank plays no role whatsoever in college admissions decisions

The linear bias of radio galaxies at z~0.3 via cosmic microwave background lensing

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical SocietyWe present a new measurement of the linear bias of radio loud active galactic nuclei (RLAGN) at $z\approx0.3$ and $L_{\rm 1.4GHz}>10^{23}\,{\rm W\,Hz^{-1}}$ selected from the Best & Heckman (2012) sample, made by cross-correlating the RLAGN surface density with a map of the convergence of the weak lensing field of the cosmic microwave background from Planck. We detect the cross-power signal at a significance of $3\sigma$ and use the amplitude of the cross-power spectrum to estimate the linear bias of RLAGN, $b=2.5 \pm 0.8$, corresponding to a typical dark matter halo mass of $\log_{10}(M_{\rm h} /h^{-1} M_\odot)=14.0^{+0.3}_{-0.5}$. When RLAGN associated with optically-selected clusters are removed we measure a lower bias corresponding to $\log_{10}(M_{\rm h} /h^{-1} M_\odot)=13.7^{+0.4}_{-1.0}$. These observations support the view that powerful RLAGN typically inhabit rich group and cluster environments.Peer reviewe

Optimally combining Censored and Uncensored Datasets

We develop a simple semiparametric framework for combining censored and uncensored samples so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. No nonparametric smoothing is required to implement our estimators. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. Results from a small simulation experiment suggest that the estimator proposed in this paper can work very well in finite samples.

Earnings Returns to the British Education Expansion

We study the effects of the large expansion in British educational attainment that took place for cohorts born between 1970 and 1975. Using the Quarterly Labour Force Survey, we find that the expansion caused men to increase education by about a year on average and gain about 8% higher wages; women obtained a slightly greater increase in education and a similar increase in wages. Clearly, there was a sizeable gain from being born late enough to take advantage of the greater educational opportunities offered by the expansion. Treating the expansion as an exogenous increase in educational attainment, we obtain instrumental variables estimates of returns to schooling of about 6% for both men and women.return to education; higher education expansion

Recent Developments in Intergenerational Mobility

Economists and social scientists have long been interested in intergenerational mobility, and documenting the persistence between parents and children's outcomes has been an active area of research. However, since Gary Solon's 1999 Chapter in the Handbook of Labor Economics, the literature has taken an interesting turn. In addition to focusing on obtaining precise estimates of correlations and elasticities, the literature has placed increased emphasis on the causal mechanisms that underlie this relationship. This chapter describes the developments in the intergenerational transmission literature since the 1999 Handbook Chapter. While there have been some important contributions in terms of measurement of elasticities and correlations, we will focus primarily on advances in our understanding of the forces driving the relationship and less on the precision of the correlations themselves.Intergenerational Transmission, Educational Mobility

Forced to be Rich? Returns to Compulsory Schooling in Britain

Do students benefit from compulsory schooling? In an important article, Oreopoulos (2006) studied the 1947 British compulsory schooling law change and found large returns to schooling of about 15% using the General Household Survey (GHS). Reanalysing this dataset, we find much smaller returns of about 3% on average with no evidence of any positive return for women and a return for men of 4-7%. Additionally, we utilize the New Earnings Survey Panel Data-set (NESPD) that has earnings information superior to that in the GHS and find similar estimates: zero returns for women and returns of 3 to 4% for men.