This paper analyses the real-time nowcasting performance of machine learning algorithms estimated on New Zealand data. Using a large set of real-time quarterly macroeconomic indicators, we train a range of popular machine learning algorithms and nowcast real GDP growth for each quarter over the...

This study assesses the global economic consequences of climate-related risk in three broad areas: (1) the macroeconomic impacts of physical climate risk due to chronic climate change associated with global temperature increases and climate-related extreme shocks; (2) the macroeconomic effects...

The paper examines climate mitigation strategies to reach net-zero emissions by mid-century, focusing on smoothing macroeconomic costs in the short- to medium-term - the horizon relevant for policymakers. It explores a comprehensive policy package, which complements carbon pricing with an...

Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. The key to make these highly parameterized VARs useful is the use of shrinkage priors. We develop a family of priors that captures the best features of two prominent classes of shrinkage priors:...

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 modelling exibility, as it...

Time-varying parameter VARs with stochastic volatility are routinely used for structural analysis and forecasting in settings involving a few macroeconomic variables. Applying these models to high-dimensional datasets has proved to be challenging due to intensive computations and...

Using a machine learning approach, we attempt to identify the school-, student-, and country-related factors that predict East Asian students’ higher PISA mathematics scores compared to their international peers. We identify student- and school-related factors, such as metacognition–assess...

We examine whether knowledge of in-sample co-movement across countries can be used in a more systematic way to improve forecast accuracy at the national level. In particular, we ask if a model with common international business cycle factors adds marginal predictive power compared to a domestic...

Our analysis suggests; they do not! To arrive at this conclusion we construct a real-time data set of interest rate projections from central banks in three small open economies; New Zealand, Norway, and Sweden, and analyze if revisions to these projections (i.e., forward guidance) can be...

This paper evaluates the real-time forecast performance of alternative Bayesian Vector Autoregressive (VAR) models for the Australian macroeconomy. To this end, we construct an updated vintage database and estimate a set of model specifications with different covariance structures. The results...