ABSTRACT: Most of the welfare differences between countries and regions that we observe in the world today already existed more than a century ago, hence understanding how and why they emerged requires new methods to measure early developments. While for early millennia, reliable GDP per capita estimates do not exist, proxy indicators for human health and welfare can be reconstructed using archaeologically excavated skeletons for Asia and Europe on a large scale. Apart from average welfare trends, this bioarchaeological “big data” approach also allow to quantify gender and social inequalities. For example, our study identifies for the first time at which point time the substantial gender inequality in East Asia emerged. In this presentation, nearly 40,000 human skeletons are used to provide an overview on these research methods and first results. 

ABSTRACT: In this paper we estimate the causal impact of immigration to Italy on local public finances, at the municipality level (Comuni), between 2008 and 2015. We make use of administrative data to analyze public revenues and expenditures disaggregated by type. We find that, when immigrants arrive, total (current plus capital) revenues increase while total expenditures are not affected, giving rise to an increase in the surplus of the municipality (all outcome variables in the paper are defined in per capita terms). The arrival of immigrants increases current revenues and, in particular, property tax revenues, fees, and other revenues, as well as transfers from other levels of government. We show that there is an increase in property tax revenues from “secondary residences”, which are often rented out and are subject to higher taxation compared to owner-occupied units. On the expenditure side, immigrant inflows lead to greater current spending in total and on various items such as: garbage collection, local police, cultural programs, and public transportation. Capital expenditures decrease instead, when immigrants arrive.

ABSTRACT: Composite indicators are a common choice for synthesizing complex phenomena. Over the years, they have grown in popularity and are now applied in many social and environmental sciences. Among others, a subject of increasing interest is gender equality analysis. Gender composite indicators, even if easy to read, may provide a limited picture of the problem. Potentiality of Bayesian networks (BNs) to complement and build composite indicators are discussed. BNs are powerful tools for explaining the complex association structure in the dataset and developing scenarios to orient policy-making. We propose to use BNs to model the association structure among the gender equality index, its ingredient variables and other context socio-economic variables. In such a way the synergy between composite indicator and BN gives rise to both a monitoring tool for the gender equality gap status and a proactive inferential machine for proposing policies to reduce inequality. BNs can be also used to build the gender equality index, and, in general, any composite indicator. Specifically, we focus attention on an extension of BNs, namely Object-Oriented Bayesian networks (OOBNs). The modularity of the OOBN ensures a computational logic that is consistent with composite indicators, while also providing additional information about the relational structure of variables. An example is carried out on Italian province-level data. 

ABSTRACT: This study introduces a novel "hybrid" indicator to count and identify households at risk of falling into poverty. Bridging the gap between the theoretical vulnerability literature, traditionally focused on in-sample estimation, and recent data-driven methodologies for out-of-sample prediction, the indicator integrates an innovative machine learning approach into the theory-based vulnerability-to-poverty framework. After introducing this hybrid model, we test the out-of-sample forecasting ability of the indicator on multi-topic household data from Nigeria taken from the World Bank's Living Standards Measurement Study Integrated Survey on Agriculture (LSMS-ISA). The results reveal that the indicator showcases a considerable ability to effectively anticipate households experiencing poverty in future waves. Given the need for new and better forecasting models of vulnerability to poverty, the proposed indicator can serve as a supporting tool for ex-ante policy targeting by enabling preventive interventions, mapping of vulnerability hotspots, and the design of early-warning mechanisms. 

ABSTRACT: High-dimensional panels of time series arise in many scientific disciplines such as neuroscience, finance, and macroeconomics. Often, co-movements within groups of the panel components occur. Extracting these groupings from the data provides a course-grained description of the complex system in question and can inform subsequent prediction tasks. We develop a novel methodology to model such a panel as a restricted vector autoregressive process, where the coefficient matrix is the weighted adjacency matrix of a stochastic block model. This network time series model, which we call the Network Informed Restricted Vector Autoregression (NIRVAR) model, yields a coefficient matrix that has a sparse block-diagonal structure. We propose an estimation procedure that embeds each panel component in a low-dimensional latent space and clusters the embedded points to recover the blocks of the coefficient matrix. Crucially, the method allows for network based time series modelling when the underlying network is unobserved. We derive the bias, consistency and asymptotic normality of the NIRVAR estimator. Simulation studies suggest that the NIRVAR estimated embedded points are Gaussian distributed around the ground truth latent positions. On three applications to finance, macroeconomics, and transportation systems, NIRVAR outperforms competing models in terms of prediction and provides interpretable results regarding group recovery. 

ABSTRACT: The paper provides estimates of the Marginal Propensity to Consume (MPC) for Italy, using a quasi-panel structure from 2018 to 2022. Specifically, we estimate the MPC at different points of the income distribution and with different characteristics of the population (labour and marital status, type of income, demographic characteristics, geographical location etc.) and type of goods (durables, non-durables and services). We observe significant heterogeneity in the MPC distribution, which is strictly decreasing across quantiles and persistent across time, with an extraordinary reduction in 2020 due to the pandemic outbreak. Consistently with the literature, we observe that labour status and demographic factors play an important role in accounting for the MPC heterogeneity. The geographical location of households reveals strong differences in consumption habits due to cultural and climatic factors, although age and family size cause some non-linearities in the MPC throughout the distribution quantiles. The MPC is also shown to vary according on the type of product or service. 

ABSTRACT: Reduced-rank (RR) regression may be interpreted as a dimensionality reduction technique able to reveal complex relationships among the data parsimoniously. However, RR regression models typically overlook any potential group structure among the responses by assuming a low-rank structure on the coefficient matrix. To ad- dress this limitation, a Bayesian Partial RR (BPRR) regression is exploited, where the response vector and the coefficient matrix are partitioned into low- and full-rank sub-groups. As opposed to the literature, which assumes known group structure and rank, a novel strategy is introduced that treats them as unknown parameters to be estimated. The main contribution is two-fold: an approach to infer the low- and full-rank group memberships from the data is proposed, and then, conditionally on this allocation, the corresponding (reduced) rank is estimated. Both steps are carried out in a Bayesian approach, allowing for full uncertainty quantification and based on a partially collapsed Gibbs sampler. It relies on a Laplace approximation of the marginal likelihood and the Metropolized Shotgun Stochastic Search to estimate the group allocation efficiently. Applications to synthetic and real-world data reveal the potential of the proposed method to reveal hidden structures in the data. 

ABSTRACT: We analyse a model of repeated procurement whereby a buyer may elicit unverifiable quality by relying on two types of competitive procedures. The first type is non- discriminatory, namely a low-price auction with a public reserve price, whereas the second type is a scoring auction, also comprising a non-financial and discriminatory dimension based on past performance. We first provide sufficient conditions for the existence of relational procurement contracts under which the buyer can elicit the desired level of quality. We then assess which mechanism is preferable in terms of i) the buyer’s preferences and ii) the equilibrium existence conditions. As for i), we establish the conditions whereby the two procedures yield the buyer the same utility as well as those under which a non-discriminatory procedure ensures a lower cost of the project, although this comes with a lower quality and a positive probability of the project not being delivered altogether. As for ii), no clear-cut results can be established. Indeed, the range of values of the project net-of-quality utility for which an equilibrium exists under the non-discriminatory procedure is always larger than under the discriminatory one. Conversely, the two procedures have a different ranking in terms of stringency of equilibrium existence requirements for the discount factor and the net benefit of quality. 

ABSTRACT: We present an axiomatic study of various solutions to the social ranking problem, where a solution links any ranking of coalitions of players to a binary relation between individual players. We focus on solutions that align with the desirability relation, asserting that player i is more desirable than player j if any coalition including i but not j ranks higher than the corresponding coalition formed by replacing i with j. Unlike previous characterizations, our study highlights the central role of the desirability property as a foundational axiom in the characterization of five solutions from the related literature: Ceteris Paribus majority, lexicographic excellence and its dual, L^(1) solution and its dual. Our main results reveal additional similarities among these five solutions and empha-size the essential features that should be considered when selecting the most appropriate solution for a given scenario. A practical application involving a bicameral legislature is also presented.

ABSTRACT: Flows between locations cover several forms of mobility, such as journeys to work, migrations, public facilities usage. There exist attributes of separation between origin and destination locations, such as transport friction or distance friction. In this work, we focus on work commuting flows. Administrative data can provide relevant information to be used in the estimation process of commuting flows. Commuting flows are estimated by means of Bayesians Small Area estimation methods, which because of their flexibility can handle easily several model assumptions.

ABSTRACT: Regional public universities educate approximately 70 percent of college students at four-year public universities and an even larger share of students from disadvantaged backgrounds. They aim to provide opportunity for education and social mobility, in part by locating near potential students. In this paper, we use the historical assignment of normal schools and insane asylums (normal schools grew into regional universities while asylums remain small) and data from Opportunity Insights to identify the effects of regional universities on the social mobility of nearby children. Children in counties given a normal school get more education and have better economic and social outcomes, especially lower-income children. For several key outcomes, we show this effect is a causal effect on children, and not only selection on which children live near universities. We use student-level survey data to compare characteristics of college-going students from normal school and asylum counties and to study the geographic barriers that keep asylum-county children from attending college.

ABSTRACT: The proliferation of preferential trade agreements (PTAs) since the early 1990s has led to a large literature on their implications for the multilateral trade system. At the same time, the potential peace-creation effect of economic integration has also been investigated, with evidence consistent with the hypothesis that larger bilateral trade flows decrease the probability of interstate conflict. In this paper, we examine for the first time whether conflict affects the duration of trade negotiations. Past conflict might reduce trust between prospective PTA partners but might, at the same time, induce speedier negotiations in order to benefit from the peace-creation effect of a PTA. Using a unique dataset on the history of formation of a large number of PTAs over the period 1980--2015, we find robust evidence in support of the second hypothesis: country pairs with past history of conflict conclude their trade negotiations about 1.9 times faster in comparison with country pairs with no history of conflict. However, the effect is weaker when the economic motives for integration are more pronounced.

ABSTRACT: Compulsory education (CE) policies are widely known to improve education, economic outcomes, and health, yet their impact on long-term inequality remains unclear. Using data from 80 countries across birth cohorts from 1810 to 2000, this study investigates how these policies influence height inequality, a key marker of historical health and living conditions. Employing a staggered difference-in-differences approach, we find strong evidence that adopting CE significantly reduces height inequality, with the effect size growing over time. Our preferred specification suggests a reduction of height inequality. The findings also reveal regional variations, suggesting that local factors shape the extent of the policy’s impact. The study provides evidence that CE adoption influences height inequality through its effects on average income, democracy and birth rates. The findings of the research are robust to several sensitivity analyses. This research underscores the broader role of education policies in addressing health disparities and promoting equity over the long term. 

ABSTRACT: Firms have incentives to influence regulators' decisions. In a dynamic setting, we show that a firm may prefer to capture regulators through the promise of a lucrative future job opportunity (i.e., the revolving-door channel) than through a hidden payment (i.e., a bribe). This is because the revolving door publicly signals the firm's eagerness and commitment to reward friendly regulators, which facilitates collusive equilibria. Moreover, the revolving-door channel need not require an explicit agreement between the firm and the regulator, but may work implicitly giving rise to an industry norm. This renders ineffective standard anti-corruption practices, such as whistle-blowing protection policies. We highlight that closing the revolving door may give rise to other inefficiencies. Moreover, we show that cooling-off periods may make all players worse off if timed wrongly. Opening the revolving door conditional on the regulator's report may increase social welfare. 

ABSTRACT: We investigate how the gender mix of expert teams affects performance in a high-stakes setting: childbirth. Exploiting the quasi-exogenous assignment of patients to two-member physician teams (Lead and Assisting), we document two main findings: (i) female-only teams achieve the best maternal outcomes, while male-only teams have the worst; and (ii) within mixed-gender teams, female-led teams perform worse than male-led teams. Performance differences are not driven by patient selection, team skill, or gendered physician preferences for “discretionary” obstetric practices (e.g., C-sections). Instead, they are directly attributable to the team’s gender mix. We propose that gender mix affects team performance primarily through gender norms, supported by two pieces of evidence. First, gender mix affects how individual preferences are incorporated into team decisions, with female-only team decisions most closely reflecting average member preferences. Second, gender mix affects how teams manage teamwork challenges (conflicting preferences, limited work history, etc). Female-led mixed-gender teams are especially harmed by these challenges, possibly because female leadership inverts traditional gender norms. Overall, our study offers novel policy insights into effectively supporting an increasingly diverse workforce.

ABSTRACT: We study the long-run effects of early-life exposure to low-dose radiation from the 1986 Chernobyl disaster on adult health and fertility. Leveraging exogenous variation in radioactive fallout across Italian municipalities, driven by weather patterns, we construct a radiation exposure index and link it to administrative records on hospitalizations (2004–2016) and delivery certificates (2002–2019) for 18 cohorts (1976–1993). Women exposed in utero or during early childhood exhibit elevated rates of thyroid disorders, cancers, spontaneous abortions, and stillbirths in adulthood, with no comparable effects among older children. These patterns reflect heightened biological vulnerability during critical developmental windows. We also document behavioral heterogeneity in exposure. Municipalities with high agricultural employment, where avoidance of contaminated food carried higher private costs, experienced more severe health impacts. In contrast, political alignment with the national government did not predict compliance with safety advisories. Our findings underscore the persistent health consequences of early-life radiation and highlight how behavioral frictions can amplify biological risks. 

ABSTRACT: Sport bets are “state contingent assets”, with a negative expected return. Therefore, a rational agent who buys these lotteries behaves as a risk-lover. The rationality of bettors may be supported by the evidence on the informational efficiency of the sport betting market.  While, theoretically, their (local) risk-loving behavior may be explained by adding a (small) utility of gambling in a bettors’ generally concave (risk-averse) utility function. If gambling is amusing, then the gamblers are consumers rather than investors, and the money that they spend on gambling should not be considered as a financial loss, but as the price paid for the pleasure of gambling. Actually, the empirical evidence suggests that the demand for sports entertainment includes sports betting. In particular, betting and watching a game appear to be strong complements, as if betting on the game watched on tv (or on other media) would make attending the game more exciting. A complementarity which is economically very relevant, as the sale of broadcasting rights is (increasingly) the most important revenue for professional sport teams. Theoretically, the pleasure of gambling may also affect some financial traders, therefore explaining some of the noise trading recorded in financial markets.

ABSTRACT: This paper present research using quantitative policy analysis methods to examine impacts of recent policy changes on reproductive health service use, access, and outcomes in Canada. Since 2017, Canada has undergone rapid reproductive health policy change including the 2017 introduction of the medication abortion drug mifepristone under a globally unprecedented regulatory framework and the introduction of universal, no-cost coverage for prescription contraception through provincial insurance programs starting in 2023. Dr. Schummers’s research uses interrupted time series analysis to estimate effects of these policies on contraception and abortion use and access, complications and adverse events, and costs. In the context of a universal health systems (administered by province), Canada’s approach to reproductive policy may provide insight to international settings for improving reproductive health policy and service delivery to improve reproductive population health.