A key concern in the design of education policies relates to the structure of incentives in accountability systems. This paper examines a school accountability program that provides financial support to low-performing schools but has no direct punishment scheme for recipients who do not exhibit...

This working paper aims to stress the role of the institutional capital and its components, as primary factors, in economic results at the national level, using adequate measurement indicators and econometric models. For this purpose, we analysed the following aspects: the definition of...

Multivariate Adaptive Regression Spline (MARS) is a simple and powerful non-parametric technique that automatizes the selection of non-linear terms in regression models. Non-linearities and spatial effects are natural characteristics in numerous spatial hedonic pricing models. In this paper, we...

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting...

We propose in this article a Composite Logistic Regression (CLR) approach for ordinal panel data regression. The new method transforms the original ordinal regression problem into a number of binary ones. Thereafter, the method of conditional logistic regression (Chamberlain, 1984; Wooldridge, 2001;...

The least absolute deviation (LAD) regression is a useful method for robust regression, and the least absolute shrinkage and selection operator (lasso) is a popular choice for shrinkage estimation and variable selection. In this article we combine these two classical ideas together to produce...

shrinkage and selection. In this article, we extend its application to the REGression model with AutoRegressive errors (REGAR). Two types of lasso estimators are carefully studied. The first is similar to the traditional lasso estimator with only two tuning parameters (one for regression...

By slicing the region of the response (Li, 1991, SIR) and applying local kernel regression (Xia et al., 2002, MAVE) to each slice, a new dimension reduction method is proposed. Compared with the traditional inverse regression methods, e.g. sliced inverse regression (Li, 1991), the new method is...