We discuss the economic reasons why the predictions of price and return statistical moments in the coming decades, in the best case, will be limited by their averages and volatilities. That limits the accuracy of the forecasts of price and return probabilities by Gaussian distributions. The...

An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and...

This paper investigates the use of DMA approach for identifying good inflation predictors and forecasting inflation in Mongolia, one of the most commodity dependent economies, using dynamic model averaging (DMA). The DMA approach allows for both set of predictors for inflation and marginal...

This paper presents evidence that accounting (or flow-of-fund) macroeconomic models helped anticipate the credit crisis and economic recession. Equilibrium models ubiquitous in mainstream policy and research did not. This study identifies core differences, traces their intellectual pedigrees,...

This paper criticises the econometric inflation uncertainty proxies found in the literature, which show an overly optimistic picture about our real ability to forecast, and highlights the sharp contrast between the evidence portrayed by that literature and the evidence conveyed by the literature...

I generate priors for a VAR from four competing models of economic fluctuations: a standard RBC model, Fisher’s (2006) investment-specific technology shocks model, an RBC model with capital adjustment costs and habit formation, and a sticky price model with an unaccommodating monetary...

In this paper we suggest the use of an internet job-search indicator (Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample comparison of many forecasting models. With respect to the previous literature we concentrate on the monthly...

We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard...

This paper, using a threshold vector error-correction (TVECM) model, examines whether BRENT crude spot and futures oil prices are cointegrated. By employing this methodology we are able to evaluate the degree and dynamics of transaction costs resulting from various market imperfections. TVECM...

This document provides a summary of the aggregate results of a special questionnaire which was sent to the participants in the ECB Survey of Professional Forecasters (SPF) in autumn 2008, in the context of the ten-year anniversary of the SPF’s launch in January 1999. In summary, the results...