We study the distribution of the adaptive LASSO estimator (Zou (2006)) in finite samples as well as in the large-sample limit. The large-sample distributions are derived both for the case where the adaptive LASSO estimator is tuned to perform conservative model selection as well as for the case...

The recent rise and distinct geography of populism highlights the need for high resolution data on the economic and political landscapes and improved spatial political economy models that explain their interrelation. This paper shows that divergent development generates political externalities...

This paper introduces a two-step procedure for convex penalized estimation in dynamic location-scale models. The method uses a consistent, non-sparse first-step estimator to construct a convex Weighted Least Squares (WLS) optimization problem compatible with the Least Absolute Shrinkage and...

The past few years have been marked by the occurrence of many unexpected events that have had many social and economic repercussions, with the COVID-19 pandemic and rising tensions in energy commodity markets standing out above the others. This period of great uncertainty has also had a...

The past few years have been marked by the occurrence of many unexpected events that have had many social and economic repercussions, with the COVID-19 pandemic and rising tensions in energy commodity markets standing out above the others. This period of great uncertainty has also had a...

The past few years have been marked by the occurrence of many unexpected events that have had many social and economic repercussions, with the COVID-19 pandemic and rising tensions in energy commodity markets standing out above the others. This period of great uncertainty has also had a...

I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatility), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about...

An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and...

Even though the output and unemployment relation has always been a key theme in applied macroeconometrics research, the global hypothesis of modular short and long run dynamics assuming classic macroeconomic assumptions, is still to become a widely discussed subject in the field, and, therefore...

The finite-sample as well as the asymptotic distribution of Leung and Barron's (2006) model averaging estimator are derived in the context of a linear regression model. An impossibility result regarding the estimation of the finite-sample distribution of the model averaging estimator is obtained.