Past Events

We study whether machine learning forecast combinations can improve on the equal-weight mean of survey forecasts from Slovak commercial banks for GDP growth and inflation. Using monthly bank forecasts with full histories (2007–2024; 216 observations per series) and real-time data vintages that respect publication lags, we run a rolling out-of-sample evaluation. We compare linear and penalised regressions (OLS, ridge, lasso, elastic net), nonlinear methods (trees, random forests, XGBoost, kNN, SVR), an ARIMA benchmark, and stacked ensembles estimated via non-negative least squares. Performance is measured by relative MSE versus the bank mean. For inflation, regularised linear combinations deliver consistent gains (RelMSE at around 0.81–0.82), while nonlinear and stacked approaches underperform, suggesting overfitting in small panels. For GDP, several nonlinear models and a restricted stack improve materially on equal weights.

Despite years of transparency reforms, their impact on civic participation is not well understood. We study whether government performance information from one of the largest transparency initiatives can motivate citizens to participate and whether changes in beliefs are the mechanisms driving this effect. The initiative tracks 112 of India’s 806 most underperforming districts across key development indicators and posts performance information online for public accountability. We conducted a randomized field experiment with 2,107 adults in a district targeted by the initiative. Over 90% in our setting were unaware of the initiative, and 75% overestimated their district’s performance. Our low-cost, scalable video intervention informed citizens that their district was included, revealed its declining performance relative to neighboring districts, and listed formal grievance channels. Citizens randomly assigned to watch the video were 5 pp more likely to sign the petitions and 8.4 pp more likely to attend workshops on complaint filing portals. They updated beliefs about their district’s low rank and became more aware of the initiative. Citizens who initially overestimated their district’s rank updated their beliefs and increased participation, while we observed no effects among those who had not overestimated prior to treatment. Beliefs about citizens’ influence over service delivery remained unchanged. One month later, beliefs about the district’s rank converged, yet citizens in the intervention group continued to meet civic officials and file complaints. Those who initially overestimated their district’s rank remained significantly more likely to participate. To explain why citizens continue participating despite low perceived influence, we develop a model where participation depends on expected performance gaps relative to aspirational service levels and perceived influence over government. Larger perceived gaps alone can sustain participation through an accountability channel. These findings have implications for 250 million Indians in most-underperforming districts and highlight how prior beliefs mediate effectiveness of transparency programs.

We assess the welfare impact of the introduction of universal daycare services in Qu´ebec in 1997. Unlike the standard sufficient-statistic metric, which assumes marginal changes in fiscal policy, our approach accounts for the non-marginal nature of the program and quantifies nonpecuniary benefits. Through a structural model of childcare demand, we estimate substantial welfare gains from the policy, yielding a Marginal Value of Public Funds (MVPF) above 3.5. Using the sufficient-statistic approach underestimates welfare gains by half. Counterfactual simulations and a difference-in-differences analysis suggest that increasing availability, rather than solely improving affordability, is crucial for the effective design of universal programs.

This paper studies the relationship between patient cost-sharing and the demand for care after hospital stays (post-acute care), and how this relationship is mediated by non-medical custodial care needs and the presence of the family. Using plausibly exogenous variation in the number of free skilled nursing facility (SNF) days at hospital discharge, I first show that higher cost-sharing for SNFs leads to substitution away from SNFs to home health and routine discharges with no care. Moreover, for those who are already in a SNF, discharges rise sharply when cost-sharing begins. I further document that people with family are less likely to use SNFs, while people with custodial care needs are more likely to use SNFs. I use these findings to motivate a dynamic structural model that begins at hospital discharge and follows patients through further discharge decisions in different post-acute settings. Using the model, I explore the implications of alternative cost-sharing structures. I find that eliminating the non-linearity in SNF copay can generate large Medicare savings at small costs to the patients. Medicare subsidizing custodial care at home enhances patient welfare substantially for individuals without family, at no additional cost to Medicare. For patients with family, the same policy, while still beneficial to the patient, will increase Medicare costs substantially, resulting in a net zero effect overall.

Older workers are often viewed as obstacles to innovation, suggesting that their exit allows firms to reallocate resources toward new capital and technology. I argue instead that older, experienced workers support both the continuity of current production and the capacity to integrate new technologies into existing operations. The key empirical challenge is that when retirements are anticipated, firms have time to transfer knowledge internally, making the productivity value of older workers difficult to observe. I address this by studying a 2014 German pension reform that unexpectedly lowered the early retirement age for experienced workers by up to 29 months, inducing a sudden and unanticipated loss of long-tenured employees. Firms exposed to the reform reduce capital accumulation, delay technology adoption, and experience subsequent declines in revenue and value added, consistent with the erosion of firm-specific human capital. To interpret these findings, I develop a stylized model in which older workers transfer uncodified, firm-specific knowledge that is essential for maintaining legacy capital and integrating new technologies into firms’ operations. The model predicts, and the data confirm, that unexpected retirements weaken firms’ ability to sustain production and slow the pace of technological upgrading.

I provide new evidence on the labor market impacts of military conscription using employer-employee administrative data covering the universe of men born between 1958 and 1975 in Argentina. For identification, I exploit the random assignment of draft eligibility generated by 18 draft lotteries. I find that draft eligibility depresses early-career outcomes: At ages 20-24, eligible men exhibit lower employment and earnings. These penalties fade with age and do not accumulate into sizable long-run losses. Eligibility to conscription increases the likelihood of holding formal employment and a permanent contract, with no average effect on medium- or long-run earnings. The enduring consequence of conscription is a modest reallocation of employment away from agricultural activities and toward service-oriented and higher-paying sectors, reducing employment in the lowest-wage activities among the most geographically disadvantaged individuals. Overall, these results indicate that conscription can affect industry sorting rather than merely disrupt labor market entry in early adulthood, but the magnitudes are modest and do not translate into measurable gains in earnings.

Using household-level survey data on 22 European countries collected in four waves between 2010 and 2022, we document the distributional effects of borrower-based macroprudential measures (BBM). We find that the tightening of the BBM significantly reduces the availability of mortgages for lower-income households, leading to increased reliance on renting. Regulation works not only through the extensive margin by cutting off risky borrowers from the mortgage market, but also through the intensive margin by reducing the average loan amount of households with lower incomes. This reduction in risk has the positive side effect of lower borrowing costs, benefiting mainly households with above-average incomes. The easing of BBM, observed in several countries, does not yet fully reverse these effects.

Systematic reviews show that multinationality is measured in many ways, yet these measures are often treated as equivalent. This study conducts a systematic literature review of multinationality metrics used since the 1960s and maps their operationalizations across empirical, theoretical, and review articles. Building on and extending Vaněk’s (2024) framework, the metrics are classified by construct, dimension, indicators, segmentation, and format, revealing substantial conceptual and structural differences behind similar-looking measures. Selected metrics are then empirically compared using Taiwanese firm data to show how they lead to conflicting assessments of internationalization. The study explains why multinationality is difficult to measure consistently and offers a structured basis for selecting and interpreting metrics in future research.

This paper examines how prison inmates anticipate being stigmatized by the inmate label and whether a brief self-affirmation intervention can recalibrate these beliefs. In Study 1, we assess the perceptions of inmates (N = 297) about the extent of trust and altruism that will be given to them by general society by manipulating disclosure of their prison status in an incentivized lab-in-the-field experiment. The findings reveal that when their prison status was disclosed, inmates anticipated greater altruism, reflecting optimism rather than anticipated stigma, although their expectations of trust did not differ. We find no significant effects of self-affirmation on their beliefs about altruism, trust, or trustworthiness; nor on the proposed psychological channels of inmates’ confidence and risk taking. In Study 2 (N=489), we conceptually replicate optimism about altruism in a one-shot setting using incentivized spectator predictions, and identify the likely underlying mechanism as the perception that society will treat them favorably due to hardships they face during incarceration spells and uncertainty about the nature of their crime. Their expectations were more realistic for longer-horizon trust-based domains such as securing employment and housing, and for general kindness ratings. 

This study evaluates the impact of the 2018 mandatory transition to electronic prescribing in the Czech Republic. Leveraging administrative registry data on medical prescriptions and dispensations, we analyze the reform’s influence on the spatial relationship between prescribing physicians and dispensing pharmacies-specifically focusing on changes in patient travel time. Furthermore, we examine potential heterogeneous effects across different age cohorts and regions.

This paper examines how the origin of income mobility—whether driven by individual effort or luck—affects preferences for redistribution. The existing literature emphasizes how expectations of future income shape redistributive support, while abstracting from the mechanisms that generate income mobility. I study this question using a laboratory experiment in which individuals face identical income transition structures but differ in whether their mobility prospects are generated by relative effort or by luck. The results reveal that the mobility mechanism triggers significant heterogeneity across the income distribution. Among low-income individuals, effort-based mobility increases support for redistribution relative to luck-based mobility when upward mobility prospects remain insufficient to reach top-income positions. This pattern suggests that meritocratic processes can be perceived as procedurally unfair when advancement opportunities are limited, highlighting the political relevance of procedural features of income mobility. Conversely, high-income individuals tend to reduce their support for redistribution under effort-based mobility when they are more productive than the average. The paper also documents that biased beliefs about relative performance moderate redistributive preferences. Participants who are poorer than average but expect to become richer than average in the future, due to overconfidence in their relative performance, tend to support lower levels of redistribution. Overall, the findings indicate that preferences for redistribution depend not only on expected future income but also on the perceived legitimacy of the process through which mobility is generated.

 This paper investigates the effects of a price transparency policy on spatial competition in a retail fuel market. Using post-policy data, I examine how increased consumer-side transparency affects competition. I develop an empirical model of demand and supply that accounts for both fully informed consumers and those facing price uncertainty. Prior research shows that major brands coordinated before the policy and continued to do so afterward. Building on this evidence, I model coordination among major brands and allow its stability to depend on the share of informed consumers. I find that as more consumers become informed, price dispersion and profit margins decline. However, the extent of coordination among major firms remains stable. These findings suggest that while consumer-side transparency increases competitive pressure, its pro-competitive effects may be limited or even reversed if coordinating firms can also access the same transparency tools.

This study examines whether bid advantages can stimulate innovation by comparing bonus-based incentives with prize-and-penalty schemes. We conduct a controlled laboratory experiment with two sequential stages. In the innovation stage, participants choose an R&D investment level; in the auction stage, they compete for a procurement contract in a second-price auction. We implement three treatments: a benchmark with no incentive, bonus scheme, and prize-and-penalty scheme designed to be payoff-equivalent to the bonuses. While bonuses operate within the auction stage by rewarding the innovator and disadvantaging the non-innovator, prize-and-penalty schemes shift these incentives to the innovation stage, thereby removing auction distortion and reducing uncertainty. We test whether these mechanisms generate different levels of innovation and whether the timing and framing of incentives affect behavior, particularly through sunk-cost bias.

Accurate perception of social relationships is central to human social cognition, yet little is known about how well individuals perceive incoming social ties within their natural social environments. We collected data from 3,077 adolescents across 117 classrooms and analyzed complete social networks comprising four directed relational layers—friends, best friends, enemies, and worst enemies—alongside adolescents’ predictions of who would nominate them in each layer. Across all layers, perceptual accuracy was strikingly low. Only 0.29% of students assessed all of their relationships correctly. Errors were overwhelmingly driven by underestimation: adolescents systematically failed to recognize how many peers named them, both positively and negatively. Misperception was structured rather than random. Popularity (in-degree) was strongly associated with underestimation, whereas sociability (out-degree) was associated with overestimation. These structural patterns were consistent across relational layers and error types and showed no systematic improvement with age. Together, these findings reveal robust structural asymmetries in social cognition, suggesting that young people perceive far less of their social worlds than there is.

This project examines how an exogenous decline in immigration flows induces sorting across the distribution of health conditions in the local labor market adjustment process and documents significant changes in the community health indicators. In the 1920s, a set of immigration laws in the United States imposed quotas based on national origin and restricted immigrant flows. These policies cut immigration flows from constrained countries to around 150,000 individuals a year. The effects of this policy change are identified in a difference-in-difference framework utilizing the LIFE-M, historical labor survey, and full count census data. Results indicate that individuals in areas facing larger declines in immigration are observed transitioning into occupations and industries with worse associated health measures. Increasing native-born employment in high health cost (HHC) positions offset lost immigrant labor leading to no change in HHC employment share. Further, policy exposure was associated with declining average lifespan and increasing mortality rates among counties’ working age US-born population.

Inaccurate inference about economic policy uncertainty affects international investment returns, and investment decisions made with imperfect information result in financial losses for all market participants. The classic widely used Baker et al. (2016) index of economic policy uncertainty (EPU) suffers from methodological imperfections in construction due to (1) neglecting semantics, (2) data quality fluctuations, and (3) ignoring tonality/emotion in the data. In this paper, we introduce a novel emotion-based economic policy uncertainty index that (i) improves the semantic identification of economic policy by extracting a large set of tokens from RoBERTa, (ii) uses a vast CC-News media dataset, and (iii) identifies uncertainty by a finetuned emotion recognition model.

We study the effect of working from home (WFH) on health-related absenteeism. We draw on a monthly panel (2018–2023) of nearly 1.9 million workers insured under a major German statutory health insurance fund. Our identification strategy leverages the differential exposure to the unexpected shift to WFH in 2020, resulting in about one-quarter of German employees regularly working remotely today. Specifically, our difference-in-differences design compares sick leave take-up across workers with different WFH potential, i.e., the teleworkability of their occupation in February 2020. Our results imply a nontrivial lasting response to WFH. Compared to the pre-treatment mean, the monthly likelihood of sick leave take-up declined by 3.3% by 2023 due to a 10-percentage-point increase in WFH potential (comparable to a shift from performing and entertainment professions to media documentation and information services). These effects are driven by reductions in respiratory infections and musculoskeletal disorders, such as back pain. The response reflects not only behavioral changes in sick leave take-up, but also genuine health improvements.

Our research focuses on the area of brownfield revitalisation, examining its potential impact on surrounding residential areas as reflected in property price changes and residential preferences and expectations. The crucial research objective of our study is to determine whether the relevant brownfield neighbouring inhabitants are rationally anticipating property price changes determined by brownfield regeneration, as reflected in real property transactions, and furthermore whether the residents consider the property price increase as a decrease in accessibility of residential housing. We use the data on 63 brownfield revitalisation levels in the city of Brno in Czechia from 2013 to 2025 with an a minimum area of the brownfield larger than 0.5 ha. We accompany these data with property price transactions from 2013 to 2024, comprising 38,418 property transactions. Consequently, we have surveyed the residential expectations via a field survey including 251 residential respondents. Using the hedonic pricing model, our results show that the property prices in the neighbourhood of brownfields are strongly affected by the brownfield site, but the level of brownfield revitalisation has a significant positive impact on property prices in the residential neighbourhood. The positive impact on prices is potentially strengthened by future brownfield use for offices, not for residential areas. Most residents anticipate a property price increase, but even more, they expect a higher level of accessibility to housing. Thus, the existence of new available flats is a stronger expectation compared to a price increase that affects housing accessibility oppositely. Thus, the residents show relatively ambivalent expectations on revitalisation of the long-term effects.

We study how secondary markets for durable goods interact with consumers’ social-responsibility motives to mitigate environmentally harmful new production. On the positive side, secondary markets may allow responsible consumers to acquire used goods that would otherwise be discarded, reducing premature waste. On the negative side, secondary markets introduce two major harmful forces. First, the possibility of buying used goods and thereby causing less harm can raise the demand of responsible consumers, often increasing the production necessary to serve the market. Second, said demand can increase the price of used goods, encouraging purchases of new goods. These forces imply that if used goods have positive private consumption value, then secondary markets always erode the benefits of social responsibility. If, instead, used goods may have negative private value, then secondary markets can enhance or erode the benefits of social responsibility.

The death of a child is a devastating and life-altering event for the entire family, extending beyond the initial grief and shaping the short and long-term life trajectories of the surviving siblings and parents. Although a growing literature documents its negative impact on parental outcomes, very little is known about its causal impact on the human capital accumulation of surviving siblings. This paper examines the effect of losing a sibling during childhood on educational outcomes, using detailed register data from the entire population of Finland. I exploit the timing of an unexpected sibling loss relative to the time of 9th-grade GPA measurement. I find that losing a sibling 2 years before the 9th grade has a negative impact of 19% of a standard deviation on the 9th-grade GPA. The effect is more pronounced and prevalent across different ages at the time of sibling loss for children with a lower socioeconomic background. Further, I find a 12-14 percentage points decrease in the probability of general track choice in the upper-secondary school following a sibling loss. Exploring potential mechanisms, I find notable negative mental health effects on both surviving children and their parents, along with adverse effects on the labor market outcomes for mothers. These findings highlight the large social and economic consequences of such losses, emphasizing the need for targeted policies to support bereaved family members.