This paper describes the set of Bayesian vector autoregression (BVAR) models that Banco de España uses to project GDP growth rates and to simulate macrofinancial risk scenarios for Brazil and Mexico. The toolkit consists of large benchmark models to produce baseline projections and various...

Evidence in favor of the monetary model of exchange rate determination for the South African Rand is, at best, mixed. A co-integrating relationship between the nominal exchange rate and monetary fundamentals forms the basis of the monetary model. With the econometric literature suggesting that...

Vorhersagen der konjunkturellen Entwicklung werden in Deutschland meist für die Ebene der Gesamtwirtschaft durchgeführt. Sie sind jedoch nicht auf die regionalen Verhältnisse übertragbar. Signifikante Abweichungen können sich unter anderem wegen einer unterschiedlichen Sektoralstruktur...

This article explores the determinants of people’s growth prospects in survey data as well as the impact of the European recovery fund to future growth. The focus is on the aftermath of the Corona pandemic, which is a natural limit to the sample size. We use Eurobarometer survey data and...

Sowohl in den USA als auch in Großbritannien ist in naher Zukunft mit einer Zinswende zu rechnen. Die Länder des Euroraums sind davon sicher unterschiedlich betroffen. Die Autoren stellen die wichtigsten Transmissionskanäle der internationalen Übertragung der geldpolitischen Impulse dar und...

A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on continuous time theory. In explanatory financial...

This study contributes to research on the nonparametric evaluation of German trade forecasts. To this end, I compute random classification and regression forests to analyze the optimality of annual German export and import growth forecasts from 1970 to 2017. A forecast is considered as optimal...

The research examines an approach to forecast return on equity using leading economic indicators for short periods in banks. ROE is one of the most important ratios for performance measurement. Its adequacy is necessary for competitiveness, attract funding in financial markets, accumulate...

In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out-of-sample forecasting exercise is designed with multiple horizons, a large database of 501 series, and 50 forecasting methods, including new ML techniques proposed here,...

In the rapidly developing world, forecasting is very important for numerous aspects of our lives, the finance realm not being an exception. Various qualitative and quantitative methods are used to predict what is ahead. One of them is the Delphi method, an anonymous, structured discussion among...