Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related...

This article highlights the importance of statistical tests on the trend coefficient in cointegrating regressions when the stochastic regressors contain a deterministic linear trend. In addition to deriving asymptotic theory for t statistics constructed using integrated and modified ordinary...

Researchers in the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of...

In this paper we reconsider large Bayesian Vector Autoregressions (BVAR) from the point of view of Bayesian Compressed Regression (BCR). First, we show that there are substantial gains in terms of out-of-sample forecasting by treating the problem as an error-in-variables formulation and...

This article characterizes China's between-city skyscraper contest with an infinitely-repeated game. The mixed strategy equilibrium of this dynamic game-theoretic model implies that a Chinese city would be more inclined to build a taller skyscraper if the height of its current tallest building...

We study the estimation of heterogeneous effects of group-level policies, using quantile regression with interactive fixed effects. Our approach can identify distributional policy effects, particularly effects on inequality, under a type of difference-in-differences assumption. We provide...

This work looks at the impact of electoral rules on female participation in local legislative bodies using a natural experiment involving a series of changes to electoral law in Poland. Using an exogenous population threshold dividing municipalities into ones with proportional and ones with...

Unconditional quantile regressions, as introduced by Firpo, Fortin, and Lemieux (2009), are a special case of Recentered Influence Functions (RIF) Regressions that can be used to relate how small changes in the distributions of explanatory variables affect an unconditional statistic of interest....

The carbon emission reduction potential of photothermal utilization of solar energy is outstanding, but the breakthrough of technology is closely related to the management of innovation and research in higher educational institutions. What factors affect such relationship is discussed in this...

This paper proposes a minimum distance (MD) estimator to estimate panel regression models with measurement error. The model considered is more general than examined in the literature in that (i) measurement error can be non-classical in the sense that they are allowed to be correlated with the...