We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model's...

I study 46 vintages of FRB/US, the principal macro model used by Federal Reserve Board staff for forecasting and policy analysis, as measures of real-time model uncertainty. I also study the implications of model uncertainty for the robustness of commonly applied, simple monetary policy rules. I...

This paper proposes a novel approach to introduce time-variation in structural parameters of DSGE models. Structural parameters are allowed to evolve over time via an observation-driven updating equation. The estimation of the resulting DSGE model can be easily performed by maximum likelihood...

I study 46 vintages of FRB/US, the principal macro model used by Federal Reserve Board staff for forecasting and policy analysis, as measures of real-time model uncertainty. I also study the implications of model uncertainty for the robustness of commonly applied, simple monetary policy rules. I...

Investors recently are really concerned about the risk aspects associated with the investment in securities. Volatility calculation, therefore, has become an important aspect in the financial markets. For these reasons time series models are greatly used to forecast volatility. One such model is...

This chapter is concerned with methods for analyzing spatial data. After initial discussion of the nature of spatial data, including the concept of randomness, we focus most of our attention on linear regression models that involve interactions between agents across space. The introduction of...

Over the past 15 years there has been remarkable progress in the specification and estimation of dynamic stochastic general equilibrium (DSGE) models. Central banks in developed and emerging market economies have become increasingly interested in their usefulness for policy analysis and...

We propose a Nelson-Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying...

In this paper we develop a business cycle measure that can be shown to have excellent ex-ante forecasting properties for GDP growth. For identifying business cycle movements, we use a semantic approach. We infer nine different states of the economy directly from firms' responses in business...

Die vorliegende Arbeit untersucht, wie sich Angebots-, Nachfrage- und geldpolitische Schocks aus den Vereinigten Staaten auf Deutschland übertragen. Dabei wird ein so genanntes factor-augmented vector autoregressive model (FAVAR) auf einen neu zusammengestellten Datensatz mit mehr als 200...