We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...

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...

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 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...

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 prompt availability of information on the current state of the economy in real-time is required for prediction purposes and crucial for timely policy adjustment and economic decision-making. While important macroeconomic indicators are reported only quarterly and also published with...