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...

Forecasting hourly electricity prices and their characteristic properties is a core challenge for energy generation companies and trading houses. The short-term marketing and purchase of electricity is usually managed with standardized products traded on different markets and with specific...

In this paper we present an evaluation framework for predictions of binary events in probabilistic electricity price forecasting. It employs the MSE-equivalent QPS together with the DM test and allows for further insights about deficiencies of the considered models. Additionally, techniques from...

The transition to a carbon-neutral economy is necessary to limit the negative impact of climate change and has become one of the world's most urgent priorities. This paper assesses the impact of three potential transition pathways, differing in the timing and level of ambition of emission...

A substantial and rapidly growing literature has developed around estimating earnings gains from two-year college degrees using administrative data. These papers almost universally employ a person-level fixed effects strategy to estimate earnings premia net of fixed attributes. We note that the...

A conspicuous lacuna in the literature on Sub-Saharan Africa (SSA) is the lack of clarity on variables key for driving and predicting inclusive growth. To address this, I train the machine learning algorithms for the Standard lasso, the Minimum Schwarz Bayesian Information Criterion (Minimum...

The sustained current account deficit in any country has an important implication for policy. If it continues, then it suggests that the regime ought to have no motivation to avoid or to diminish its international debt. In this paper, we test empirically the relationship among current account...

A conspicuous lacuna in the literature on Sub-Saharan Africa (SSA) is the lack of clarity on variables key for driving and predicting inclusive growth. To address this, I train the machine learning algorithms for the Standard lasso, the Minimum Schwarz Bayesian Information Criterion (Minimum...

This paper discusses how the forecast accuracy of a Bayesian vector autoregression(BVAR) is affected by introducing the zero lower bound on the federal funds rate. As abenchmark I adopt a common BVAR specification, including 18 variables, estimatedshrinkage, and no nonlinearity. Then I entertain...

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...