Eliciting permanent and transitory undeclared work from matched administrative and survey data

We study the undeclared work patterns of Hungarian employees in relatively stable jobs, using a panel dataset that matches individual-level self-reported Labour Force Survey (LFS) data with administrative data from the Pension Directorate for 2001–2006. We estimate the determinants of undeclared work using Heckman-type random-effects panel probit models, and develop a two-regime model to separate permanent and transitory undeclared work, where the latter follows a Markov chain. We find that about 6 per cent of workers went permanently unreported for six consecutive years, and a further 3-4 per cent were transitorily unreported in any given year. By simulating the permanent and transitory components of undeclared work, we examine the implications for health and pension eligibility

Caesarean delivery and the use of antidepressants

Background The high ratio of caesarean sections (C-sections) is a major public health issue in the developed world; but its implications on maternal mental health are not well understood. Methods We use individual-level administrative panel data from Hungary between 2010 and 2016 to analyze the relationship between caesarean delivery and antidepressant consumption, an objective indicator of mental health. We focus on low-risk deliveries of mothers without subsequent birth in 3 years, and include around 135 000 observations. Results After controlling for medical and socio-economic variables, antidepressant use before delivery is associated with an elevated risk of C-section (adjusted OR = 1.10, 95% CI 1.05–1.14) and C-section is associated with a higher probability of antidepressant use within 1–3 years after delivery (e.g. adjusted OR = 1.21, 95% CI 1.12–1.30, within 3 years after delivery, among mothers without pre-delivery antidepressant consumption). Our data restriction ensures that the results are not driven by a mechanical impact of decreasing fertility on the continuation of antidepressant use after a C-section. Conclusions The results suggest that C-section is associated with worse mental health over the 1- to 3-year horizon after birth. This relationship is particularly important if a caesarean delivery is not necessary due to medical reasons, and physicians as well as expectant mothers should be made aware of the potential mental health implications of the mode of delivery

Az effektív társasági adókulcs rugalmassága Magyarországon a 2009–2011 közötti adókulcscsökkentés alapján

Tanulmányunkban a társasági adókulcs 2009–2011 közötti csökkentésének vállalati adófizetésekre gyakorolt hatását becsüljük vállalati szintű paneladatok alapján. Először keresztmetszeti regressziós modellel vizsgáljuk az átlagos effektív adórátára (azaz a tényleges adókötelezettség és az adózás előtti eredmény arányára) ható vállalati jellemzőket. Megállapítjuk, hogy – más változókra kontrollálás után is – az exportáló vállalatok, a legkisebb és legnagyobb vállalatok, valamint a mezőgazdaságban tevékenykedő vállalatok effektív adókulcsai az adókedvezmények és egyéb korrekciós tényezők levonása után az átlagnál kisebbek. Majd vállalati szintű fixhatás-panelregressziós becsléssel elemezzük az effektív adókulcs rugalmasságát a névleges adókulcs változására, és 0,7–0,9 közötti rugalmassági együtthatót kapunk. Ennek a becslésnek az érvényességét – egy speciális adókedvezményre vonatkozó szabályozást kihasználva – párosításos módszerrel is teszteljük. Journal of Economic Literature (JEL) kód: C21, C23, H25

Macroeconomic policy empirical analysis using an unrestricted standard VAR Model : the case of Mongolia

This paper is mainly about key fiscal policy indicators and their interrelations between each other. The model that is used in the analysis is the Vector Autoregressive Model. There are seven variables selected: GDP, Money Supply, Government Revenue, Government Expenditure, Export, Government Debt, and Global Copper Price. Besides VAR estimation, IRFs are computed to define how variables react to certain shocks. The key finding of the research is that both GDP and government revenue are sensitive to copper price changes and the resulting shock. Copper Price is an effective tool to predict these two variables in the shortrun. Government Revenue is an effective tool to impact export in the short-run. Government Debt is not an effective indicator to affect any variables except Government Expenditure. Money Supply is only effective for GDP. Government Expenditure is also not significantly effective in having an impact on other variables, but is weakly affected by Government Revenue, Copper Price, and Export. Most variables considered in the research belong to fiscal policy, thus, effective fiscal policy can be implemented using the results of this paper

Detecting Wage Under-reporting Using a Double Hurdle Model

We estimate a double hurdle (DH) model of the Hungarian wage distribution assuming censoring at the minimum wage and wage under-reporting (i.e. compensation consisting of the minimum wage, subject to taxation, and an unreported cash supplement). We estimate the probability of under-reporting for minimum wage earners, simulate their genuine earnings and classify them and their employers as 'cheaters' and 'non-cheaters'. In the possession of the classification we check how cheaters and non-cheaters reacted to the introduction of a minimum social security contribution base, equal to 200 per cent of the minimum wage, in 2007. The findings suggest that cheaters were more likely to raise the wages of their minimum wage earners to 200 per cent of the minimum wage thereby reducing the risk of tax audit. Cheating firms also experienced faster average wage growth and slower output growth. The results suggest that the DH model is able to identify the loci of wage under-reporting with some precision.tax evasion, double hurdle model, Hungary

Effects of geographical accessibility on the use of outpatient care services: quasi-experimental evidence from panel count data

In 2010–2012, new outpatient service locations were established in Hungarian micro-regions, which had lacked such capacities before. We exploit this quasi-experiment to estimate the effect of geographical accessibility on outpatient case numbers using both individual-level and semi-aggregate panel data. We find a 24–27 per cent increase of case numbers as a result of the establishments. Our specialty-by-specialty estimates imply that a 1-min reduction of travel time to the nearest outpatient unit increases case numbers for example by 0.9 per cent in internal care and 3.1 per cent in rheumatology. The size of the new outpatient capacities has a separate effect, raising the possibility of the presence of supplier-induced demand. By combining a fixed-effects logit and a fixed-effects truncated Poisson estimator, we decompose the effects into increases in the probability of ever visiting a doctor on the one hand and an increase of the frequency of visits on the other hand. We find that new visits were dominant in the vast majority of specialties, whereas both margins were important for example in rheumatology. Finally, we demonstrate the usefulness of the fixed-effects truncated Poisson estimator in modelling count data by examining its robustness by simulations