We describe a new simulation-based algorithm for Bayesian estimation of structural effects in models where the outcome of interest and an endogenous treatment variable are ordered. Our algorithm makes use of a reparameterization, suggested by Nandram and Chen (1996) in the context of a single...

This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression function is well-approximated by a parsimonious,...

Over the past decade, productivity growth in the euro area has suffered from a series of sectoral adjustments. As these adjustments appear to be temporary, we expect a structural acceleration of productivity growth.

This primary objective of this paper is to examine the causes for the change in energy consumption in the transport sector in India. The pattern of energy consumption and their causes for change are benchmarked against select countries. A mathematical model that decomposes changes in energy...

This paper shows how the dynamic linear model with fixed regressors can be efficiently estimated. This dynamic model can be used to distinguish spurious correlation from state dependence and we show that the integrated likelihood estimator is adaptive for any asymptotics with T increasing where...

Stochastically ordered random variables with given marginal distributions are combined into a joint distribution preserving the ordering and the marginals using a maximum entropy formulation. A closed-form expression is obtained. An application is in default estimation for different portfolio...