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Location choice and dispersal policies: Ukrainian war immigrants in the Czech Republic
Adunts, Davit ; Kurylo, Bohdana ; Špeciánová, J.
The large influx of Ukrainian immigrant refugees to the Czech Republic fleeing from the war has attracted the attention of many policymakers due to their unequal geographical distribution. The high concentration of refugees in some districts has the potential to burden the school and healthcare systems, as well as the housing market. This project aims to provide an explanation for the unequal distribution of refugees by studying the determinants of refugee location choices in the Czech Republic, including ethnic networks and employment prospects. We provided evidence of a positive association between the number of Ukrainian refugees and (i) the stock of previous Ukrainian immigrants (our measure of ethnic networks) and (ii) the number of available job positions. In addition, we conducted a review of previous studies on the effectiveness of dispersal policies and determined that such policies exert ambiguous effects on refugee labor market integration. Hence, dispersal policies need to consider the integration of refugees and their intentions to remain in the country.
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Head teachers’ salaries: long overlooked
Korbel, Václav ; Münich, Daniel ; Smolka, Vladimír
School leadership staff (head teachers and their deputies) are crucial to teaching quality. Pay for primary school leadership staff in the Czech Republic, however, is not closely monitored in the long term, despite the fact that pay influences the efficiency of managerial work and educational leadership and, moreover, affects potential candidates’ motivation to apply for school leadership roles. For our analysis, we use employee level data from the ISPV database of salary statements for the years 2017–2021. The classification used in the ISPV database does not enable us to distinguish between different leadership roles – head teacher vs. deputy – so our analysis looks at sets of school leadership staff as a whole. We analyse their average total gross monthly salaries, the average value of bonuses, the variability in their pay range and the factors that influence the amount of their pay and its variability.
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The price of war: macroeconomic and cross-sectional effects of sanctions on Russia
Mamonov, Mikhail ; Pestova, Anna
How much do sanctions harm the sanctioned economy? We examine the case of Russia, which has faced three major waves of international sanctions over the last decade (in 2014, 2017, and 2022). In a VAR model of the Russian economy, we first apply sign restrictions to isolate shocks to international credit supply to proxy for the financial sanctions shocks. We provide a microeconomic foundation for the sign restriction approach by exploiting the syndicated loan deals in Russia. We then explore the effects of the overall sanctions shocks (financial, trade, technological, etc.) by employing a high-frequency identification (HFI) approach. Our HFI is based on each OFAC/EU sanction announcement and the associated daily changes in the yield-to-maturity of Russia’s US dollar-denominated sovereign bonds. Our macroeconomic estimates indicate that Russia’s GDP may have lost no more than 0.8% due to the financial sanctions shock, and up to 3.2% due to the overall sanctions shock cumulatively over the 2014–2015 period. In 2017, the respective effects are 0 and 0.5%, and in 2022, they are 8 and 12%. Our cross-sectional estimates show that the real income of richer households declines by 1.5–2.0% during the first year after the sanctions shock, whereas the real income of poorer households rises by 1.2% over the same period. Finally, we find that the real total revenue of large firms with high (low) TFPs declines by 2.2 (4.0)% during the first year after the sanctions shock, whereas the effects on small firms are close to zero. Overall, our results indicate heterogeneous effects of sanctions with richer households residing in big cities and larger firms with high TFPs being affected the most.
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Quo vadis? Evidence on new firm-bank matching and firm performance following “sin” bank closures
Goncharenko, R. ; Mamonov, Mikhail ; Ongena, S. ; Popova, S. ; Turdyeva, N.
In this paper, we analyze how firms search for new lenders after a financial regulator forcibly closes their prior banks, and what happens to the firms’ performance during this transition period. In 2013, the Central Bank of Russia launched a large-scale bank closure policy and started detecting fraudulent (sin) banks and revoking their licenses. By 2020, two-thirds of all operating banks had been shuttered. We analyze this unique period in history using credit register data. First, we establish that before sin bank closures, there was no informational leakage and the borrowing firms remain unaffected. After the closures, there is a clear sorting pattern: poorly-performing firms rush to other (not-yet-detected) sin banks, while profitable firms transfer to financially solid banks. We find that the coupling of poorly-performing firms and not-yet-detected sin banks occurs more frequently when the two sin banks (the prior and the next lender) are commonly owned or when the local banking market is unconcentrated. Finally, we show that during the transition period (i.e., after the sin bank closures and before matching to new banks), poorly-performing firms shrink in size and experience a sharp decline in borrowings and market sales, whereas profitable firms strengthen in terms of employment, investment, and market sales. A potential mechanism involves credit risk underpricing by sin banks: we find that poorly-performing firms (especially commonly owned) received loans at lower interest rates than profitable firms prior to sin bank closures.
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“Crime and punishment”? How banks anticipate and propagate global financial sanctions
Mamonov, Mikhail ; Pestova, Anna ; Ongena, S.
We study the impacts of global financial sanctions on banks and their corporate borrowers in Russia. Financial sanctions were imposed consecutively between 2014 and 2019, allowing targeted (but not-yet-sanctioned) banks to adapt their international and domestic exposures in advance. Using a staggered difference-in-differences approach with in-advance adaptation to anticipated treatment, we establish that targeted banks immediately reduced their foreign assets and actually increased their international borrowings after the first sanction announcement compared to other similar banks. We reveal that the added value of the next sanction announcements was rather limited. Despite considerable outflow of domestic private deposits, the government support prevented disorderly bank failures and resulted in credit reshuffling: the banks contracted corporate lending by 4% of GDP and increased household lending by almost the same magnitude, which mostly offset the total economic loss. Further, we introduce a two-stage treatment diffusion approach that flexibly addresses potential spillovers of the sanctions to private banks with political connections. Employing unique hand-collected board membership and bank location data, our approach shows that throughout this period, politically-connected banks were not all equally recognized as potential sanction targets. Finally, using syndicated loan data, we establish that the real negative effects of sanctions materialized only when sanctioned firms were borrowing from sanctioned banks. When borrowing from unsanctioned banks, sanctioned firms even gained in terms of employment and investment but still lost in terms of market sales pointing to a misallocation of government support.
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Differences in the costs of research in higher education across scientific fields: how different are they from „KENs“ in teaching?
Srholec, Martin
Much has been said and written recently about low wages in the social sciences and humanities. Academics have demonstrated in the streets about it, and there has even been talk of a strike. Although a solution seems to be out of sight, one positive outcome cannot be denied. Discussion has finally begun on whether the so-called „koeficienty ekonomické náročnosti“ (KEN), on the base of which the Ministry of Education, Youth and Sports (MEYS) distributes the main part of the subsidy for teaching in higher education over the past thirty years needs to be updated. This study compares the dispersion of KENs with the differences in costs of the academic activity closest to higher education teaching, which is undoubtedly research and development (R&D). We are not attempting to recalculate the KENs - which would be desirable, but is not feasible with the data and resources available to us - but at least to approximate the extent to which current KENs differ from the costs observed in R&D.
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Are subsidies to business R&D effective? Regression discontinuity evidence from the TA CR ALFA programme
Bajgar, Matěj ; Srholec, Martin
Governments subsidise business research and experimental development (R&D) to promote development of the economy, because externalities and information asymmetries inherent to the innovation process make private funding of these activities fall short of what is socially desirable. Nevertheless, how effective such subsidies are and whether they achieve their goals is an open question that needs to be studied empirically. This study leverages the state-of-the-art method of regression discontinuity (RD) that allows us to come very close to making causal inferences about the effects of subsidies, to find out whether the Technology Agency of the Czech Republic’s (TA CR) ALFA programme stimulated new business R&D inputs, outputs, and positive economic impacts that would not have happened otherwise.
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Extrapolative income expectations and retirement savings
Cota, Marta
Why do employees’ retirement contributions gradually increase throughout their careers? This paper uses a structural life-cycle model based on household expectations data to explain workers’ retirement contribution decisions. The Michigan Survey of Consumers data shows that young households extrapolate from their recent income realizations and overstate the persistence and volatility of their future income. The structural life-cycle model with extrapolative expectations quantifies the difference in retirement contribution rates compared to rational expectations. Contrary to rational workers, extrapolative workers’ contributions match the data on retirement contributions over the life cycle. Consequently, mandating automatic enrollment yields negligible effects on retirement savings.
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