This paper investigates whether there have been time periods between 1999 and 2019 in Hungary when government spending has been self-financing, i.e., when the government has faced a fiscal free lunch. By self-financing, it is meant that government spending, initially financed by issuing bonds, does not lead to an increase in the debt-to-GDP ratio due to improvements in the budget balance resulted in by stimulated economic activity. Some macroeconomists think that while government spending is arguably not self-financing in normal times, it could have become self-financing in the United States (US) during the Global Financial Crisis (GFC) due to 1) stronger fiscal multipliers, 2) stronger hysteresis effects, and 3) lower interest rates than usually. This paper estimates the parameters of a simple model of debt dynamics on Hungarian data to study whether these arguments also hold for an emerging small open economy, like Hungary, in which fiscal multipliers are thought to be weaker, and where interest rates increased during the GFC. It is found that government spending has not been self-financing in the short run before the GFC (1999Q1-2008Q3), has been at the edge of being expected to be self-financing in the long run, but has not actually turned out to be. During the GFC (2008Q4-2012Q4), it cannot be excluded to have been self-financing in the long run, and might have already been self-financing in the short run, as well. However, these findings are much less robust than those for the US. Between the GFC and the COVID recession (2013Q1-2019Q4), government spending was not self-financing in the short run, but was expected to be self-financing in the long run.

We study the impact of delayed school entry on the locus of control (LoC) among Hungarian students, using statutory cutoff dates for school enrollment as a plausibly exogenous variation. Our findings indicate a causal relationship between delayed school entry and an increase in internal LoC, with a policy effect of approximately one-tenth of a standard deviation for 8th-grade students, which corresponds to a one-third standard deviation effect for complier students. The policy implications of these findings are significant, providing evidence that delaying school start could serve as an effective intervention to enhance LoC among students, which is positively associated with many later life outcomes.

Using different variants of the classic climate game, we investigate the role of competition and the source of endowment (windfall vs. earned). Participants completed a detailed personality test (including climate attitudes and economic preferences) before the experiment and were asked about their strategies afterwards. We find that competition did not significantly affect whether groups reached the target, even though the probability of achieving the common goal was lower in the presence of competition. Participants cooperated more when they had to earn the endowment. Based on the pre-experiment questionnaire, participants who viewed their personal actions as more important and effective in combating climate change were more likely to cooperate in the climate game, while the rest of the measured personality items did not exhibit a consistent pattern. Analysis of the post-experiment survey indicates that those who aimed to maximise earnings contributed less to the common pool. In contrast, those who believed the goal was achievable and aimed to achieve it contributed more to the common pool throughout the game.

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In 2013, the Hungarian government cut the school leaving age from 18 to 16. We study the impact of this unique reform on the country's sizeable Roma minority using census data on the universe of 17-year-olds in 2011 and a 10 percent random sample in 2016. School attendance fell by more than 20 percentage points among Roma youth as opposed to less than 6 points with their non-Roma counterparts. Roma's post-reform drawbacks in school enrolment were predominantly explained by their family background, neighborhood characteristics, and, much less importantly, below-average school performance. Changes in local employment prospects had no remarkable impact on the post-reform ethnic gap. More stringent selection and self-selection by social status and school performance (rather than ethnicity) nevertheless affected the Roma minority disproportionally, with close to 30 percent of their 17-year-old children being out of education, training, and employment three years after the reform.

Research on the effect of in utero shocks on health at birth may be influenced by in utero selection. This study outlines a conceptual framework and shows that the results of the standard empirical approach are biased if (i) the exposure changes the probability of fetal death and (ii) health differences exist between deceased and surviving fetuses. Furthermore, an empirical example is provided to illustrate, the potential importance of fetal selection. Examining the impact of heat on birth weight, I find that accounting for fetal selection substantially increases the heat effect compared to the standard approach. These results suggest that incorporating the distorting effect of fetal losses into the estimations may be critical in some cases to provide more informed guidance for public policy.

This paper provides a summary of the latest advancements in generative artificial intelligence using large language models over the past six months. The impact of this breakthrough remains uncertain, but it is evident that GPT is a General-Purpose Technology (GPT) that will significantly alter various aspects of our economy and society in ways that are yet to be fully comprehended. While it is essential for the government to regulate GPT technology, it is inevitable that the technology will continue to expand and evolve at a rapid pace. There is no doubt that every corner of the new world if it exists at all, will be covered by millions of forms of artificial intelligence. The taming of AIs and successful social and personal cooperation with domesticated AIs could ensure our survival and prosperity in that world. Whether or not AIs are capable and willing to cooperate will populate the new world is neither an individual nor a national matter. But how a country and its people fare in the new world is more so.

This paper analyzes the dynamics of sectoral Real Gross Value Added (RGVA) around sudden stops in foreign capital inflows. We identify sudden stop episodes statistically from changes in gross capital inflows from the financial account, and use an event study methodology to compare RGVA before and after the start of sudden stops. In the baseline specification, we estimate changes in the growth rate of sectoral RGVA during sudden stops and in the few quarters following them. In an additional exercise, we analyze deviations from the sectors' long-run growth path. Our findings indicate that: (i) tradable sectors, especially manufacturing, face larger damages during sudden stops than nontradable sectors, (ii) but they also lead the recovery after recessions that accompany sudden stops on impact, partly due to the fact that they benefit from the depreciation of the domestic currency that occurs during sudden stops, (iii) construction and professional services are the most seriously hurt nontradable sectors during sudden stops, while information and communication, and financial services grow slower even in the aftermath of the events than before their onset. However, this slowdown only constitutes a return to their long-run sectoral growth paths. Overall, our results suggest a prolonged reallocation of economic activity away from service sectors, towards the production of goods. This is consistent with a traditional view of the role of tradable and nontradable sectors in a sudden stop episode.

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1. fejezet - online melléklet
2. fejezet - online melléklet
3. fejezet - online melléklet
4. fejezet - online melléklet

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This paper explores the spatial patterns and underlying determinants of repeated inventor collaboration across European NUTS 3 regions. It is found that only a small fraction of co-inventor linkages across regions are repeated, while community detection reveals that these collaborations are clustered in geographical space more intensively compared with collaboration in general. Additional results from gravity modelling indicate that links in the inter-regional co-patenting network emerge mainly through the triadic collaboration of regions, while geographical proximity becomes the most influential factor for repeating co-inventor ties. In addition to that, the combination of technological similarity and shared third partner regions offer a premium for the likelihood of repeating collaboration, but only when geographical proximity is present as an enabler.

Social networks amplify inequalities by fundamental mechanisms of social tie formation such as homophily and triadic closure. These forces sharpen social segregation, which is reflected in fragmented social network structure. Geographical impediments such as distance and physical or administrative boundaries also reinforce social segregation. Yet, less is known about the joint relationships between social network structure, urban geography, and inequality. In this paper we analyze an online social network and find that the fragmentation of social networks is significantly higher in towns in which residential neighborhoods are divided by physical barriers such as rivers and railroads. Towns in which neighborhoods are relatively distant from the center of town and amenities are spatially concentrated are also more socially segregated. Using a two-stage model, we show that these urban geography features have significant relationships with income inequality via social network fragmentation. In other words, the geographic features of a place can compound economic inequalities via social networks.