This study develops a framework to forecast India's gross domestic product growth on a quarterly frequency from 2004 to 2018. The models, which are based on real and monetary sector descriptions of the Indian economy, are estimated using Bayesian vector autoregression (BVAR) techniques. The real...

Economies, societies, and many natural systems evolve and change, sometimes dramatically, so good models and accurate forecasts are vital for policymakers to prepare for and navigate these changes successfully. Yet history is littered with forecasts that went badly wrong, sharply illustrated...

This paper proposes a simple and model-consistent method for combining forecasts generated by structural micro-founded models and judgmental forecasts. The method also enables the judgmental forecasts to be interpreted through the lens of the model. We illustrate the proposed methodology with a...

This paper proposes a simple and model-consistent method for combining forecasts generated by structural micro-founded models and judgmental forecasts. The method also enables the judgmental forecasts to be interpreted through the lens of the model. We illustrate the proposed methodology with a...

Government agencies and other national and international institutions are asked to perform forecasts over the medium term. In particular, the EU Stability and Growth Pact contains the obligation to formulate stability programmes over four years, covering a general economic outlook as well as the...

In this paper we propose a hierarchical shrinkage approach for multi-country VAR models. In implementation, we consider three different scale mixtures of Normals priors — specifically, Horseshoe, Normal- Gamma, and Normal-Gamma-Gamma priors. We provide new theoretical results for the...

No macroeconometeric forecasting technique anticipated the financial market meltdown and subsequent Great Recession in 2008-2009. This failure is not surprising because it is hard to forecast unprecedented events. The experience explains, however, why many forecasters, particular those supplying...

By employing large panels of survey data for the UK economy, we aim at reviewing linear approaches for regularisation and dimension reduction combined with techniques from the machine learning literature, like Random Forests, Support Vector Regressions and Neural Networks for forecasting GDP...