(with Stig Vinther Møller). To be presented at EFA 2012. Submitted.
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We examine US housing price forecastability using a common factor approach based on a large panel of 122 economic time series. We find that a simple three-factor model generates an explanatory power of about 50% in one-quarter ahead in-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly statistically significant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power and performs remarkably well compared to both autoregressive benchmarks and computational intensive forecast combination models.
Keywords: House prices; Forecasting; Factor model; Principal components; Macroeconomic factors; Factor forecast combination; Bootstrap.
(under revision).
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Economy-wide effects of shocks to the US federal funds rate are estimated in a state space model with 120 US macroeconomic and financial time series driven by the dynamics of the federal funds rate and a few dynamic factors. This state space system is denoted a factor-augmented VAR (FAVAR) by Bernanke et al. (2005). I estimate the FAVAR by the fully parametric one-step EM algorithm as an alternative to the two-step principal component method and the one-step Bayesian method in Bernanke et al. (2005) .......
Keywords: Monetary policy, Dynamic Factor Models, EM Algorithm, Factor-augmented VAR (FAVAR).
(with Hans Dewachter & Romain Houssa). Under revision.
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This paper presents a dynamic factor model in which the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of over-identifying loading restrictions, while the structural shocks are estimated following standard practices in the SVAR literature. Estimators based on the EM algorithm are developed. .......
Keywords: Monetary policy, Dynamic Factor Models, EM Algorithm, Factor-augmented VAR (FAVAR).
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Defended February 26, 2010.
The thesis consists of three self-contained chapters. Chapter 1 is about estimation of the Factor-Augmented VAR (FAVAR) by the EM algorithm. Chapter 2 is about well-defined economic interpretation of the dynamic factors which is achieved by means of over-identifying loading restrictions. Chapter 3 is about macroeconomic sources of variation in the expected excess bond returns as implied by an affine term structure model driven by data-rich macroeconomic state variables.
Keywords: Affine term structure model, Monetary policy. Dynamic Factor Models, EM Algorithm, Factor-augmented VAR (FAVAR).
Assistant professor, Department of Business and Management, Aalborg University.
PhD in Finance, Finance Research Group, Aarhus School of Business, Aarhus University. MSc Economics.
Research interests:
Asset Pricing and Macro-Finance models of the yield curve. Dynamic factor models. State-space models. Monetary economics and macroeconomics. Financial econometrics.
