Understanding the determinants of judicial performance is of the utmost importance to promote economic prosperity. The Italian judiciary is notoriously slow, with an estimated backlog of more than three million cases. We use a sample of 652,174 cases from one small claims court in Italy to limit geographical heterogeneity. Despite being generally overlooked by scholarly literature, small claims courts provide justice for a third of the overall civil litigation in Italy. We study the roles of different procedures in judicial timeliness. We exploit plausibly exogenous variation in the procedures governing how judges rule on small claims via a regression discontinuity approach. Our estimates reveal that when litigants are required to pay a fee to have their case heard, resolution takes about 5 months longer. We do not find conclusive evidence that when judges are able to rule without providing legal justification, decisions are actually made faster. We document the robustness of these results in light of both selection and observable strategic behavior on the part of litigants. We discuss how our results align with recent policy reforms in the realm of small claims, including methods to ease congestion in Italian courts and efforts to improve judicial performance more broadly.

Using a regression discontinuity design, we examine the causal impact of far-right parties’ first-time entry into Swedish municipal politics on the inclusion of candidates from groups frequently targeted by their rhetoric, namely immigrants and sexual minorities. Leveraging validated candidate data, we find that far-right entry has a negative effect on the share of immigrant candidates within mainstream parties. However, this average effect masks important differences across parties. Left-wing parties respond by increasing immigrant recruitment, resulting in a net increase in immigrant representation on ballots. In contrast, right-wing parties reduce their share of immigrant candidates, largely due to limited recruitment of new candidates. These findings highlight how far-right legislative presence shapes the recruitment and retention of minority candidates in democratic politics.

Prior work has often studied how focusing events – in particular police killings of unarmed people – affect citizens’ attitudes. Do focusing events also affect citizens’ behaviors – changing the scope of conflict by incorporating prospective voters into the political system? We take as an empirical case the murder of George Floyd. Using nationwide voter file data from the United States, we leverage regression discontinuity in time methods to show that Floyd’s murder noticeably increased voter registration. These effects are present across many individual subgroups, providing evidence of mobilization and counter-mobilization. Floyd’s untimely death sparked many people from previously marginalized backgrounds to register, but simultaneously also increased registrations among the politically advantaged – thus mitigating any impact on the partisan balance of power. In short, high-profile traumatic events like Floyd’s death do not appear to disproportionately advantage groups seeking reforms to change the circumstances surrounding such events.

Many inferential tasks involve fitting models to observed data and predicting outcomes at new covariate values, requiring interpolation or extrapolation. Conventional methods select a single best-fitting model, discarding fits that were similarly plausible in-sample but would yield sharply different predictions out-of-sample. Gaussian processes (GPs) offer a principled alternative. Rather than committing to one conditional expectation function, GPs deliver a posterior distribution over outcomes at any covariate value. This posterior effectively retains the range of models consistent with the data, widening uncertainty intervals where extrapolation magnifies divergence. In this way, the GP’s uncertainty estimates reflect the implications of extrapolation on our predictions, helping to tame the “dangers of extreme counterfactuals” (King and Zeng, 2006). The approach requires (i) specifying a covariance function linking outcome similarity to covariate similarity and (ii) assuming Gaussian noise around the conditional expectation. We provide an accessible introduction to GPs with emphasis on this property, along with a simple, automated procedure for hyperparameter selection implemented in the R package gpss. We illustrate the value of GPs for capturing counterfactual uncertainty in three settings: (i) treatment effect estimation with poor overlap, (ii) interrupted time series requiring extrapolation beyond pre-intervention data, and (iii) regression discontinuity designs where estimates hinge on boundary behavior.

Many observational studies often involve multiple levels of treatment assignment. In particular, fuzzy regression discontinuity (RD) designs have sequential treatment assignment processes: first based on eligibility criteria, and second, on (non-)compliance rules. In such fuzzy RD designs, researchers typically use either an intent-to-treat approach or an instrumental variable-type approach, and each is subject to both overlapping and unique biases. This article proposes a new evidence factors (EFs) framework for fuzzy RD designs with sequential treatment assignments, which may be influenced by different levels of decision-makers. Each of the proposed EFs aims to test the same causal null hypothesis while potentially being subject to different types of biases. Our proposed framework utilizes the local RD randomization and randomization-based inference. We evaluate the effectiveness of our proposed framework through simulation studies and two real datasets on pre-kindergarten programs and testing accommodations.

Do ideologically extreme candidates enjoy fundraising advantages over more moderate candidates? Extant work documents a relationship between candidates’ positions and campaign contributions subnationally and in donor surveys, yet identification challenges have hampered investigation in the congressional context. I employ a close primaries regression discontinuity design to examine how “as-if random” nominations of extreme versus moderate House candidates influence general election contributions from individual donors and corporate political action committees (PACs) from 1980 to 2020. Results at both the nominee and contributor levels demonstrate that corporate PACs financially penalize extremists, while individual donors respond similarly to extreme and moderate candidates. These findings contribute to ongoing debates regarding the extent and nature of campaign contributors’ role in congressional polarization.

State and local governments put hundreds of referendums on the ballot each year. Often, they pass but sometimes they fail. What happens after a successful or failed attempt at the ballot box? Do advocates go back to voters with another request? And if they do, do they tend to succeed? We employ a regression discontinuity empirical framework to causally estimate referendum dynamics in the arena of land conservation. Our results suggest municipalities where a referendum just barely fails hold about 0.5 more referendums and pass about 0.28 more referendums than municipalities that just barely pass, meaning initial defeat is often reversed. We also investigate whether strategic changes are made in election approaches for those that try again. We find no evidence of systematic patterns in strategic revisions for municipalities that fail their first referendum. However, when revisions are made, our evidence suggests that voters appear to respond positively.

Sleep changes predate shifts in mood/affect, thought processing, mental and physical health, civic engagement, and contextual circumstances, among other things. Theory predicts that these changes may lead to shifts in political and social beliefs. Do sleep disruptions shape how individuals see the world, the people around them, and themselves in relation to others? In this article, we use daily survey data from the 77 waves (N $ \approx $ 460,000) of the University of California, Los Angeles’s 2019–2021 Nationscape Survey—a nationally representative political survey—to examine the effect of an exogenous short-term sleep disruption on measures of political views, polarization, and discriminatory beliefs. Using this data set, we leverage the modest sleep disruption that occurs at the start (and end) of Daylight Saving Time (DST) and employ a regression discontinuity in time design around the precise DST cutoff (which we supplement with event study models). Despite strong theoretical expectations and correlational connection between measures of sleep and many outcomes related to social fragmentation, we find that the DST change has little to no causal effect on citizens’ levels of polarization or their discriminatory attitudes. These effects are precise enough to rule out small effects, robust to a host of specification checks, and consistent across potential subgroups of interest. Our work adds to a small but growing body of research on the social and political effects of sleep disruptions.

This paper uses Socio-Economic Surveys covering the period from 2013 to 2019 and the 2015 Time Use Survey to investigate the extent to which household consumption changes at retirement in Thailand. A fuzzy regression discontinuity design is applied to evaluate the retirement effect on total household expenditure and expenditures on four major categories: food-at-home, work-related items, non-durable entertainment, and others. The results reveal that retirement decreases household expenditure by 11%. Further investigations show that the dramatic declines in expenditures on work-related and non-durable entertainment contribute significantly to the spending drop at retirement. The magnitudes of the declines are more pronounced for low-income and low-wealth households. The results also indicate that the retirees spend more leisure time on home production activities after retirement. Once accounting for this effect, it finds that the drop in total household expenditure decreases to 6%. These results suggest that the sizable consumption expenditure drop at retirement is due to substituting away from market purchased goods toward home-produced goods.

How do politicians with coercive linkages govern? This article relies on original data on militia-linked mayors in Colombia from 1988 to 2015 derived from 42,000 pages of Colombian Supreme Court sentencing documents. Using a regression discontinuity design, it examines the governance records of militia-tied mayors who won the elections by a narrow margin. It finds that being ruled by a militia-linked mayor significantly reduces levels of insecurity and crime, but has pernicious effects on the provision of other public goods, especially education. I theorize that these politicians' (perverse) comparative advantage on security, combined with their crowding out of social spending, engenders these outcomes. I evaluate these mechanisms with data on the nature of paramilitary–mayor alliances, police reinforcements, municipal budgets, politicians' Twitter feeds, and in-depth interviews with paramilitary commanders and politicians. The article has implications for understanding the effects of voting for politicians with coercive ties on the quality of governance and democracy.

Using detailed spending and time use data from the Netherlands, this paper analyzes the causal effect of retirement on spending and time use decisions. Both total consumption and disaggregated consumption categories are considered. We do not find empirical evidence for drops in households' total non-durable spending at retirement. Our estimates suggest increases in spending at retirement on goods that are complementary to leisure, but no decreases in spending on goods that are replaceable by home production. The quantitative implication of our empirical results for the Life-Cycle Model is an intertemporal elasticity of substitution for leisure below unity.

Early research suggested that education was a major factor in structuring rates of political participation and social capital. More recent work based on experimental or quasi-experimental evidence offers mixed findings. In this study, we enlist a unique research setting in Romania, where passing the baccalaureate is required for entrance into university, setting up the occasion for a fuzzy RD design. The sample is drawn from a cross section of Romanians whose scores fall just above or below the cutoff. Because the sample is large and the measurement of exam scores are fine-grained, it is plausible to regard the outcome as continuous at the cutoff. Because the number of exam takers is enormous, we are able to focus on a very narrow bandwidth. The assumption of as-if random assignment is, therefore, plausible. We find that university attendance in Romania increases social capital as measured by our composite index, corroborating the main hypothesis.

This letter reports the results of a study that combined a unique natural experiment and a local randomization regression discontinuity approach to estimate the effect of polls on turnout intention. We found that the release of a poll increases turnout intention by 5%. This effect is robust to a number of falsification tests of predetermined covariates, placebo outcomes, and changes in the time window selected to estimate the effect. The letter discusses the advantages of the local randomization approach over the standard continuity-based design to study important cases in political science where the running variable is discrete; a method that may expand the range of empirical topics that can be analyzed using regression discontinuity methods.

In many developing countries, national legislative seats are considered less valuable than (subnational) executive positions. Even then, ambitious politicians may seek a legislative seat either (a) as a window of opportunity for jumping to an executive office; or (b) as a consolation prize when no better option is available. Using a regression discontinuity design adapted to a pr setting, we examine these possibilities in the Argentine Chamber of Deputies between 1983 and 2011. In line with the consolation prize story, we find that marginal candidates from the Peronist party—which controls most provincial governorships—are more likely to be renominated and serve an additional term in the legislature, but not necessarily to jump to an executive office. The effect is stronger in small provinces.

In regression discontinuity (RD), a running variable (or “score”) crossing a cutoff determines a treatment that affects the mean-regression function. This paper generalizes this usual “one-score mean RD” in three ways: (i) considering multiple scores, (ii) allowing partial effects due to each score crossing its own cutoff, not just the full effect with all scores crossing all cutoffs, and (iii) accommodating quantile/mode regressions. This generalization is motivated by (i) many multiple-score RD cases, (ii) the full-effect identification needing the partial effects to be separated, and (iii) informative quantile/mode regression functions. We establish identification for multiple-score RD (MRD), and propose simple estimators that become “local difference in differences” in case of double scores. We also provide an empirical illustration where partial effects exist.