Scholars and policymakers have recognized the importance of entrepreneurship to enhance
national development. Yet, it can be difficult to identify what type of entrepreneurship is …

In this study we examine the middle-income trap as a special case of growth slowdowns. We
identify slowdowns as large sudden and sustained deviations from the growth path …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

Variable selection methods and model selection approaches are valuable statistical tools
that are indispensable for almost any statistical modeling question. This review first …

Model selection has an important impact on subsequent inference. Ignoring the model
selection step leads to invalid inference. We discuss some intricate aspects of data-driven …

This chapter launches a more detailed examination of statistical learning within a regression
framework. Once again, the focus is on conditional distributions. How does the conditional …

This paper offers a theoretical explanation for the stylized fact that forecast combinations
with estimated optimal weights often perform poorly in applications. The properties of the …

In applications, the traditional estimation procedure generally begins with model selection.
Once a specific model is selected, subsequent estimation is conducted under the selected …

The main objective of this study is to evaluate 22 explanatory variables on ecological
footprints and rank each of them by using the two approaches of Bayesian model averaging …

Parameter estimation under model uncertainty is a difficult and fundamental issue in
econometrics. This paper compares the performance of various model averaging …