Given the ubiquitous presence of endogenous regressors and the challenges in finding good instruments to overcome the endogeneity problem, a forefront of recent research is the development and application of endogeneity correction methods without requiring instruments. In this article, we...

The availability of many variables with predictive power makes their selection in a regression context difficult. This study considers robust and understandable low-dimensional estimators as building blocks to improve overall predictive power by optimally combining these building blocks. Our new...

In a fuzzy regression discontinuity (RD) design, the probability of treatment jumps when a running variable (R) passes a threshold (R0). Fuzzy RD estimates are obtained via a procedure analogous to two-stage least squares (2SLS), where an indicator I(R R0) plays the role of the instrument....

This paper investigates potential nonlinearities in the gain function, which, under adaptive learning, regulates the updating of agents' beliefs in response to recent forecast errors. I use data on professional survey forecasts to estimate nonparametric functional-coefficient regression models....

We employ distribution regression to estimate the joint distribution of two outcome variables conditional on covariates. Bivariate Distribution Regression (BDR) is particularly valuable when some dependence between the outcomes persists after accounting for the impact of the covariates. Our...

The aim of this paper is to show that measures on tail dependence can be estimated in a convenient way by regression analysis. This yields the same estimates as the non-parametric method within the multivariate Extreme Value Theory framework. The advantage of the regression approach is contained...

Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas...

The focus of the paper is the nonparametric estimation of an instrumental regression function f defined by conditional moment restrictions stemming from a structural econometric model: E [Y - f (Z) | W] = 0, and involving endogenous variables Y and Z and instruments W. The function f is the...

In fitting parametric or nonparametric regression models, one or a few observations may have undue effects on estimators. These influential observations are precisely detected by the well-known influence measure, Cook's distance. In this paper, we introduce a type of Cook's distance for one or a...

We describe and examine a consistent test for the correct specification of a regression function with dependent data. The test is based on the supremum of the difference between the parametric and nonparametric estimates of the regression model. Rather surprisingly, the behaviour of the test...