This paper is concerned with variable selection in linear high-dimensional frameworks when the covariates under consideration are highly correlated. Existing methods in the literature generally require that the degree of correlation among covariates be weak, yet, often in applied research,...

We evaluate the impact of a nationwide public health intervention on deaths from sudden infant death syndrome (SIDS), using population data from Denmark in a regression discontinuity research design. The information campaign implemented primarily through a universal nurse home visiting program...

Conventional hedonic valuations of environmental amenities and cultural ecosystem services (CES) expose two limitations. First, it does not provide a segmented estimate based on the value type, namely use and non-use values. Second, studies using linear hedonic regression cannot address...

This study was conducted to advance methodology of utilizing leading indicators in prediction of occupational health and safety losses. The qualitative association between leading and lagging indicators is not well documented in the literature. A method was proposed to link leading indicators to...

We study inference for threshold regression in the context of a large panel factor model with common stochastic trends. We develop a Least Squares estimator for the threshold level, deriving almost sure rates of convergence and proposing a novel, testing based, way of constructing confidence...

We examine the impact of increasing minimum wage on employment by exploiting variation in the age-dependent National Minimum Wage (NMW) in the UK. We extend the Regression Discontinuity model to evaluate the procyclicality of employment effect and show that previous estimates may be biased due...

We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using...

Despite the widespread use of graphs in empirical research, little is known about readers' ability to process the statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression discontinuity (RD) designs by measuring how...

In this paper I demonstrate, both theoretically and empirically, that the interpretation of regression estimates of between-group differences in economic outcomes depends on the relative sizes of subpopulations under study. When the disadvantaged group is small, regression estimates are similar...

The rise in unemployment since the 1980s has been predominantly understood as driven by short-term shocks, or rigid labor market institutions. Aggregate demand is usually assumed to have no long-run impact on unemployment, but recent contributions call this into question. This paper adopts a...