Social scientists often estimate models from correlational data, where the independent
variable has not been exogenously manipulated; they also make implicit or explicit causal …

Many empirical questions in economics and other social sciences depend on causal effects
of programs or policies. In the last two decades, much research has been done on the …

Environmental, social, and governance (ESG) factors have become increasingly relevant
within the financial world. Despite extensive evidence regarding the equity side, limited …

We consider inference in regression discontinuity designs when the running variable only
takes a moderate number of distinct values. In particular, we study the common practice of …

This paper evaluates the impact of an R&D subsidy program implemented in a region of
northern Italy in the early 2000s on innovation by beneficiary firms. We use a regression …

Fiscal rules are laws aimed at reducing the incentive to accumulate debt, and many
countries adopt them to discipline local governments. Yet, their effectiveness is disputed …

This paper provides an introduction and “user guide” to Regression Discontinuity (RD)
designs for empirical researchers. It presents the basic theory behind the research design …

In regression discontinuity (RD) designs for evaluating causal effects of interventions,
assignment to a treatment is determined at least partly by the value of an observed covariate …

We hypothesise that the Habsburg Empire with its well‐respected administration increased
citizens' trust in local public services. In several Eastern European countries, communities …

We investigate the impact of job loss on crime and the mitigating role of unemployment
benefits, exploiting detailed individual‐level data linking employment careers, criminal …