Analyses using aggregated data may bias inference. In this work we show how to aggregate data to avoid or at least reduce this bias when estimating quantile regressions.

Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable...

Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable...

Analyses using aggregated data may bias inference. In this work we show how to avoid or at least reduce this bias when estimating quantile regressions using aggregated information. This is possible by considering the unconditional quantile regression recently introduced by Firpo et al (2009) and...

Researchers are often interested in combined measures such as overall ratings, indices of physical or mental health, or health-related quality-of-life (HRQoL) outcomes. Such measures are typically composed of two or more underlying discrete variables. I show that estimating the effect of a...

The relationship between city size and territorial productivity hasattracted much attention in the urban economic literature. Some theories on thefield claim for a strong positive correlation between the size of the municipalitiesand their income, mainly motivated by economical reasons,...

This paper introduces Information Theoretic - based methods for estimating a target variable in a set of small geographical areas, by exploring spatially heterogeneous relationships at the disaggregate level. Controlling for spatial effects means introducing models whereby the assumption is that...

Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms...

In this paper, we investigate what can be learned about average counterfactual outcomes when it is assumed that treatment response functions are smooth. The smoothness conditions in this paper amount to assuming that the differences in average counterfactual outcomes are bounded under different...