We revisit classical asymptotics when testing for a structural break in linear regression models by obtaining the limit theory of residual-based and Wald-type processes. First, we establish the Brownian bridge limiting distribution of these test statistics. Second, we study the asymptotic...

This paper aims to investigate the predictability of crude oil futures prices using a data-heavy approach with traditional macroeconomic and financial variables as well as new predictors. To do so, we adopt diverse combination approaches of bivariate regressions. A particular emphasis of the...

In order to be able to develop effective energy policies based on accurate projections, the search for better consumption modeling options is nowadays the focus of many researchers. Given the emerging use of quantile regression, decision tree and artificial neural network models for energy...

Do conditional cash transfers enhance children’s educational outcomes? Unlike previous studies, we explore this question at scale, in the context of a sustained exposure to education transfers. A regression discontinuity analysis shows positive effects on enrollment but small and seemingly...

We use plausibly exogenous shocks to stock price to study share repurchases. We exploit variations in stock price around the cutoff of Russell indexes. Russell 1000 consists of the largest 1,000 stocks, and Russell 2000 the next 2,000. This discontinuity leads to price decreases for stocks...

We propose an extension of the Fama-MacBeth regression by allowing stock returns to respond differently to firm characteristics. This heterogeneous model can potentially capture non-linearity and interactions. Empirical, applying it to a common set of fifteen firm characteristics, we find that...

Network (or matrix) reconstruction is a general problem that occurs if the marginsof a matrix are given and the matrix entries need to be predicted. In this paper,we show that the predictions obtained from the iterative proportional fitting procedure(IPFP) or equivalently maximum entropy (ME)...

Spatial models in retailing allow for correlations among purchase decisions from consumers within predefined geographic areas. The purpose of these models is to control for unobserved demand side effects at the regional-level (e.g., a neighborhood), but they typically ignore synergies among...

The goal of this paper is to predict salary of a person after a certain year. The graphical representation of predicting salary is a process that aims for developing computerized system to maintain all the daily work of salary growth graph in any field and can predict salary after a certain time...

Assessing determinants of health care quality and efficiency is of importance to researchers, policy-makers, and public health officials. Doing so allows for improved human capital and resource allocation as well as long-term fiscal planning. Statistical analysis has been used to understand...