Tanulmányunk a KSH időmérleg-felméréseinek és háztartási költségvetési adatfelvételeinek segítségével vizsgálja a gyermekes családok körében tapasztalható időfelhasználási és kiadási mintázatok jellegzetes társadalmi különbségeit és azok időbeli alakulását. Eredményeink szerint a magasabb iskolai végzettségű családok többet költenek készségfejlesztő eszközökre és szolgáltatásokra, mint az alacsony iskolázottságú szülőkkel rendelkező családok. Emellett a magasabb iskolai végzettségű anyák és apák több időt is fordítanak gyermekgondozásra és a gyermekeik készségeit közvetlenül vagy közvetve fejlesztő tevékenységekre, mint az alacsonyabb iskolázottságú szülők. A különbségek igen jelentősek. A felsőfokú végzettségű anyával és apával rendelkező kétgyermekes családok éves szinten átlagosan 350 órával többet töltenek gyermekgondozási tevékenységgel és 400 ezer forinttal többet költenek készségfejlesztő kiadásokra, mint a két középfokú végzettségű szülővel rendelkező családok. A keresztmetszeti különbségek mellett jelentős időbeli változásokat is látunk. A rendszerváltás utáni két évtizedben a gyermekekre fordított időben és készségfejlesztő kiadásokban mért társadalmi különbségek növekedtek.

The shortage of primary care physicians is a global healthcare problem, especially in rural areas. In this paper, we analyse the choice of location of primary care physicians and estimate the causal effect of financial incentives on the supply of primary care physicians in underserved areas. Our analysis is based on a quasi-experimental setting from Hungary. After 2015, primary care physicians could receive financial subsidy if they filled such a primary care position which has been vacant for at least a year, the amount of the subsidy increasing with the duration of the vacancy. Our results suggest that targeted financial incentives can help fill long-time vacant primary care positions but cannot completely eliminate primary care shortages. We also provide evidence on the role of demographic characteristics and individual preferences in the location choice of primary care physicians.

A basic function of public pension systems is to guarantee a satisfactory old-age income for short-sighted low earners. In proportional (i.e., earnings-related) systems, this requires a sufficiently high contribution rate. At the same time, there should be a cap on the pension contribution base to leave sufficient room for the efficient private savings of prudent high earners. Taking into account the dependence of life expectancy on the earnings (figuratively called longevity gap), a well-chosen cap has an additional advantage: it limits the unintended income redistribution from the short-lived to the long-lived. Our strongly stylized model is able to illustrate numerically the impact of the contribution rate and of the cap on the social welfare and the unintended income redistribution.

We consider financial networks where agents are linked to each other with financial contracts. A centralized clearing mechanism collects the initial endowments, the liabilities and the division rules of the agents and determines the payments to be made. A division rule specifies how the assets of the agents should be rationed, the four most common ones being the proportional, the priority, the constrained equal awards, and the constrained equal losses division rules. Since payments made depend on payments received, we are looking for solutions to a system of equations. The set of solutions is known to have a lattice structure, leading to the existence of a least and a greatest clearing payment matrix. Previous research has shown how decentralized clearing selects the least clearing payment matrix. We present a centralized approach towards clearing in order to select the greatest clearing payment matrix. To do so, we formulate the determination of the greatest clearing payment matrix as a programming problem. When agents use proportional division rules, this programming problem corresponds to a linear programming problem. We show that for the other common division rules, it can be written as an integer linear programming problem.

Many countries have secured larger quantities of COVID-19 vaccines than their populace is willing to take. This abundance and variety of vaccines created a historical moment to understand vaccine hesitancy better. Never before were more types of vaccines available for an illness and the intensity of vaccine-related public discourse is unprecedented. Yet, the heterogeneity of hesitancy by vaccine types in certain segments of society has been neglected so far, even though factual or believed vaccine characteristics and patient attributes are known to influence acceptance. In this paper, we address this problem by analysing acceptance and assessment of five vaccine types using information collected with a nationally representative survey (N=1000) at the end of the third wave of the COVID-19 pandemic in Hungary, where a unique portfolio of vaccines were available to the public in large quantities. Our special case enables us to quantify revealed preferences across vaccine types since one could evaluate a vaccine unacceptable and even could reject an assigned vaccine to wait for another type. We find that the source of information that respondents trust characterizes their attitudes towards vaccine types differently and leads to divergent vaccine hesitancy. Believers of conspiracy theories were significantly more likely to evaluate the mRNA vaccines (Pfizer and Moderna) unacceptable while those who follow the advice of politicians evaluate vector-based (AstraZeneca and Sputnik) or whole-virus vaccines (Sinopharm) acceptable with higher likelihood. We illustrate that the rejection of non-desired and re-selection of preferred vaccines fragments the population by the mRNA versus other type of vaccines while it generally improves the assessment of the received vaccine. These results highlight that greater variance of available vaccine types and individual free choice are desirable conditions that can widen the acceptance of vaccines in societies.

In this study we reveal the impact of spatial clustering of occupations on the probability of employment and commuting time, with particular emphasis on differences between genders and household types. Based on Hungarian 2011 census data our research confirmed previous results of some USA studies according to which women work in less spatially clustered occupations compared to men. Our most important result is that more clustered the occupation, the longer the commuting time, and the lower the probability of employment. The effect of occupational clustering on commuting time is larger for women regardless of household type and for those living in a relationship compared to singles. Our further result is that the greater the occupational diversity of the place of residence, the shorter the commuting time and higher the probability of employment, and the occupational diversity of the place of residence modifies the effect of occupational clustering on commuting time.

While most empirical studies document that cognitive and social skills are strong predictors of individual earnings, their impact is not homogenous in space. We argue that dense urban settings utilize cognitive and social skills more intensively than rural areas, therefore the labour market return to these skills is higher in cities. Using data from a representative survey recording the skills requirements of Hungarian firms, we show that social skills are rewarded more in dense urban areas. Surprisingly, this pattern is not observed for cognitive skills. We use instrumental variables strategy to correct for measurement errors in skills, and to deal with the endogeneity of agglomeration. Our results are robust to alternative agglomeration measures and a large set of controls, however, returns to skills vary considerably across worker groups and industries.

A koronavírus-járvány első másfél évében 28,4 ezer fővel többen haltak meg Magyarországon, mint ahányan elhunytak volna ebben az időszakban a járvány nélkül. Az így mért többlethalandóság 1,7 ezerrel alacsonyabb, mint a koronavírus áldozataira vonatkozó hivatalos statisztika. Ez részben azzal magyarázható, hogy a koronavírus elleni védekezésnek köszönhetően elmaradt az influenzajárvány, ami korábban átlagosan évente 3 ezer ember halálát okozta. A második hullámhoz képest a harmadik hullámban csökkentek a többlethalandóságban mért különbségek mind a korcsoportok, mind a régiók között. Az előbbi esetében részben az oltási sorrendnek, illetve az elmaradt influenzának köszönhető, hogy jelentősen csökkent a 75 éves és annál idősebbek többlethalálozási rátája, miközben a 40-74 éves korosztályé kissé emelkedett. A régiók közül Észak-Magyarországon és Nyugat-Dunántúlon volt a legnagyobb a többlethalandóság, a fővárost is magában foglaló Közép-Magyarországon pedig a legalacsonyabb az országban. A férfiak többlethalandósági rátája a vizsgált másfél év egészében majdnem minden korcsoportban közel kétszer nagyobb volt mint a nőké.

Ebben a tanulmányban egy, az iskoláskorú gyermeket nevelő családok körében végzett telefonos adatfelvétel első eredményeit mutatjuk be. Az adatfelvétel során a szülőket a koronavírus járvány következtében elrendelt távoktatással kapcsolatos tapasztalataikról kérdeztük. Az adatfelvételre 2021 áprilisában került sor, közvetlenül a teljes oktatási rendszerre kiterjedő egyik kötelező távoktatási időszakot követően. A tanulmány bemutatja, hogy a tanulók gondviselőinek a munkapiaci helyzetét figyelembe véve a háztartások mekkora hányadának okozott nehézséget a távoktatás, mennyire álltak rendelkezésre elkülöníthető terek a tanuláshoz, hogy milyen eszközöket és platformokat használtak a tanulók a távoktatásban hogyan változott a tanulási idő és milyen tanítási módszerek voltak jellemzőek az online oktatás során. A tanulmány egyszerű leíró elemzését adja e kérdéseknek.

This paper assesses the network robustness of the technological capability base of 269 European metropolitan areas against the potential elimination of some of their capabilities. By doing so it provides systematic evidence on how network robustness conditioned the economic resilience of these regions in the context of the 2008 economic crisis. The analysis concerns calls in the relevant literature for more in-depth analysis on the link between regional economic network structures and the resilience of regions to economic shocks. By adopting a network science approach that is novel to economic geographic inquiry, the objective is to stress-test the technological resilience of regions by utilizing information on the co-classification of CPC classes listed on European Patent Office patent documents. We find that European metropolitan areas show heterogeneous levels of technology network robustness. Further findings from regression analysis indicate that metropolitan regions with a more robust technological knowledge network structure exhibit higher levels of resilience with respect to changes in employment rates. This finding is robust to various random and targeted elimination strategies concerning the most frequently combined technological capabilities. Regions with high levels of employment in industry but with vulnerable technological capability base are particularly challenged by this aspect of regional economic resilience.

During the COVID-19 pandemic, many countries eased the burden of borrowers through loan forbearance. Using a representative sample of the Hungarian adult population, we investigate if time discounting and locus of control predict who takes up loan forbearance. We find convincing evidence that time discouting associates with the resort to forbearance: individuals who discount the future less are less likely to take up forbearance, even if we take into account their educational level and financial status. Data suggest that the channel through which time discounting and loan forbearance are related is savings. There is no statistically significant relationship between locus of control and forbearance takeup.

The potential restructuring of global value chains (GVCs) is a widely discussed question in current debates. At the same time, a proper way of capturing these value chains is challenging. This paper focuses on the automotive industry, using detailed data on firm-to-firm transactions in Hungary, as well as on cross-border sales and purchases. Its aim is twofold, capturing to what extent firms being connected to a GVC differ from other firms in the same industry, and what is the impact of integration into GVCs. Findings suggest that firms being part of GVCs tend to be larger, more productive, foreign-owned and having a higher level of intangible capital. There is some suggestive evidence that entering the GVC has a positive impact on size, productivity and per capita wage for certain firm groups and it is preceeded by increased imports of capital. Finally, there are also differences by employee composition.