This paper proposes a simple and efficient estimation procedure for the model with non-ignorable missing data studied by Morikawa and Kim (2016). Their semiparametrically efficient estimator requires explicit nonparametric estimation and so suffers from the curse of dimensionality and requires a...

This paper investigates the nature of the linkage that exist between the agricultural sector and industrial sector in Zimbabwe using unrestricted bivariate Vector Autoregressive (VAR) model. Using annual time series macroeconomic data for the periods between 1990 and 2015 obtained from the...

This paper investigates the nature of the linkage that exist between the agricultural sector and industrial sector in Zimbabwe using unrestricted bivariate Vector Autoregressive (VAR) model. Using annual time series macroeconomic data for the periods between 1990 and 2015, obtained from the...

This article reviews methods for extracting both risk-neutral and physical density forecasts for interest rates. It presents some applications, with particular focus on issues pertaining to forward guidance and the zero lower bound. Several important applied questions in macroeconomics and...

We consider the regression discontinuity (RD) design with the duration outcome which has discrete support. The parameters of policy interest are treatment effects on unconditional (duration effect) and conditional (hazard effect) exiting probabilities for each discrete level. We propose a novel...

The Two-Stage Least squares method for obtaining the estimated structural coefficients of a simultaneous linear equations model is a celebrated method that uses OLS at the first stage for estimating the reduced form coefficients and obtaining the expected values in the arrays of current...

Biases may reduce variability, which increases the decision maker's (concave) expected utility. Hence seeking unbiased estimates can be a strictly dominated decision approach under the expected utility criterion. Moreover, James-Stein shrinkage demonstrates that, by aggregating unrelated tasks...

We propose a new variational Bayes method for estimating high-dimensional copulas with discrete, or discrete and continuous, margins. The method is based on a variational approximation to a tractable augmented posterior, and is substantially faster than previous likelihood-based approaches. We...

We consider estimation and inference on average treatment effects under unconfoundedness conditional on the realizations of the treatment variable and covariates. We derive finite-sample optimal estimators and confidence intervals (CIs) under the assumption of normal errors when the conditional...

We develop novel regression discontinuity inferences where the binary treatment and/or continuous assignment variable may contain measurement errors. For a measurement error of the binary treatment, the standard estimator is inconsistent for the causal parameter. To solve the problem, we develop...