We present a sharp test for the efficiency of job separations. First, we document a dramatic increase in the separation rate - 11.2ppt (28%) over five years - in response to a quasi-experimental extension of UI benefit duration for older workers. Second, after the abolition of the policy, the...

This paper proposes two consistent model selection procedures for factor-augmented regressions in finite samples. We first demonstrate that the usual cross-validation is inconsistent, but that a generalization, leave-d-out cross-validation, selects the smallest basis for the space spanned by the...

We consider a variable selection problem for the prediction of binary outcomes. We study the best subset selection procedure by which the explanatory variables are chosen by maximizing Manski (1975, 1985)'s maximum score type objective function subject to a constraint on the maximal number of...

Ian Bremmer published a treatise on the stability of states built on the notion that states fall along a curve resembling a slanted "J" when plotting their stability against openness. States in the turnover process are considered unstable, and are at risk of either reversing to a closed and...

Large Bayesian VARs are now widely used in empirical macroeconomics. One popular shrinkage prior in this setting is the natural conjugate prior as it facilitates posterior simulation and leads to a range of useful analytical results. This is, however, at the expense of modeling flexibility, as...

This paper outlines a strategic plan for the development of the fourth generation of Bank of Canada projection and policy analysis models. The plan features a new Canadian workhorse macroeconomic model as well as a suite of alternative models to better support a risk management approach to...

Commodity prices co-move, but the strength of this co-movement changes over time due to structural factors, like changing energy intensity in production and consumption as well as changing composition of underlying shocks. This paper explores whether econometric models that exploit this...

In this research, we propose the bootstrap procedure as a method for train/test splitting in machine learning algorithms for classification. We show that this resampling method can be a reliable alternative to cross validation and repeated random test/train splitting algorithms. The bootstrap...

This research aims at exploring whether simple trading strategies developed using state-ofthe-art Machine Learning (ML) algorithms can guarantee more than the risk-free rate of return or not. For this purpose, the direction of S&P 500 Index returns on every 6th day (SPYRETDIR6) and magnitude of...