70 datasets found

This paper examines the determinants of inflation forecast uncertainty using a panel of density forecasts from the Survey of Professional Forecasters (SPF). Based on a dynamic...

The Federal Reserve Greenbook forecasts of real GDP, inflation and unemployment are analysed for the period 1974-1997. We consider whether these forecasts exhibit systematic...

We examine directional predictability in foreign exchange markets using a model-free statistical evaluation procedure. Based on a sample of foreign exchange spot rates and...

We provide a general methodology for forecasting in the presence of structural breaks induced by unpredictable changes to model parameters. Bayesian methods of learning and...

This paper assesses the robustness of the relative performance of spot? and options-based volatility forecasts to the treatment of microstructure noise. Robustness of the...

We estimate the EU Commission loss preferences for major economic forecasts of 12 Member States. Based on a recently proposed method by Elliott, Komunjer and Timmermann (2005)...

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and...

In this paper we propose a smooth transition tree model for both the conditional mean and variance of the short-term interest rate process. The estimation of such models is...

This paper reviews current density forecast evaluation procedures, and considers a proposal that such procedures be augmented by an assessment of sharpness. This was motivated...

We investigate whether return volatility is predictable by macroeconomic and financial variables to shed light on the economic drivers of financial volatility. Our approach is...

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally...

This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular,...

In this paper we modify the expectation maximization algorithm in order to estimate the parameters of the dynamic factor model on a dataset with an arbitrary pattern of missing...

Although speculative activity is central to black markets for currency, the out-of-sample performance of structural models in those settings is unknown. We substantially update...

We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor loadings by using cubic spline functions. We develop statistical procedures...

This paper provides a sensitivity analysis on the prior choice for interaction terms for the results of Masanjala and Papageorgiou (Rough and lonely road to prosperity. Journal...

We examine aggregate consumption growth predictability. We derive a dynamic consumption equation which encompasses relevant predictability factors: habit formation,...

This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to estimate person-centered treatment (PeT) effects that...

Reliable estimates of crime detection probabilities could help in designing better sanctions and improve our understanding of the efficiency of law enforcement. For cartels, we...

Applications of duration analysis in economics and finance exclusively employ methods for events of stochastic duration. In application to credit data, previous research...