nep-for New Economics Papers
on Forecasting
Issue of 2007‒10‒13
four papers chosen by
Rob J Hyndman
Monash University

  1. Predictable or Not? Forecasting Office Markets with a Simultaneous Equation Approach By Fuerst, Franz
  2. An analysis of the informational content of New Zealand data releases: the importance of business opinion surveys By Troy Matheson
  3. Real-Time Measurement of Business Conditions By S. Boragan Aruoba; Francis X. Diebold; Chiara Scotti
  4. The Affine Arbitrage-Free Class of Nelson-Siegel Term Structure Models By Jens H. E. Christensen; Francis X. Diebold; Glenn D. Rudebusch

  1. By: Fuerst, Franz
    Abstract: The main objective of this paper is to elucidate the capability of time-series regression models to capture and forecast movements in occupancy patterns, rental rates and construction activity. The model presented is a three-stage simultaneous equation model. The first stage incorporates the office space market in terms of occupied space and absorption of new space. The second stage captures the adjustment of office rents to changing market conditions and the third stage specifies the supply response to market signals in terms of construction of new office space. The standard simultaneous model is subsequently modified to account for the specific characteristics using the New York market as a case study. The results demonstrate that the market reacts efficiently and predictably to changes in market conditions. The significance of the estimated parameters underscores the general validity and robustness of the simultaneous equation approach in modeling real estate markets. The modifications of the standard model, notably the inclusion of sublet space in the rent equation, contributed considerably to improving the explanatory power of the model. Finally, we test whether a non-linear function performs better than the original linear approach and find mixed evidence based on the limited empirical dataset of this study.
    Keywords: forecasting; real estate; office markets; dynamic models; simultaneous equation approach; multivariate regression models;
    JEL: R33 C53 C3
    Date: 2006–06–20
  2. By: Troy Matheson (Reserve Bank of New Zealand)
    Abstract: We examine the informational content of New Zealand data releases using a parametric dynamic factor model estimated with unbalanced real-time panels of quarterly data. The data are categorised into 21 different release blocks, allowing us to make 21 different factor model forecasts each quarter. We compare three of these factor model forecasts for real GDP growth, CPI inflation, non-tradable CPI inflation, and tradable CPI inflation with real-time forecasts made by the Reserve Bank of New Zealand each quarter. We find that, at some horizons, the factor model produce forecasts of similar accuracy to the Reserve Bank’s forecasts. Analysing the marginal value of each of the data releases reveals the importance of the business opinion survey data – the Quarterly Survey of Business Opinion and the National Bank’s Business Outlook survey – in determining how factor model predictions, and the uncertainty around those predictions, evolves through each quarter.
    JEL: E52 E58 C33 C53
    Date: 2007–09
  3. By: S. Boragan Aruoba (Department of Economics, University of Maryland); Francis X. Diebold (Department of Economics, University of Pennsylvania); Chiara Scotti (Division of International Finance, Federal Reserve Board)
    Abstract: We construct a framework for measuring economic activity in real time (e.g., minute-by-minute), using a variety of stock and flow data observed at mixed frequencies. Specifically, we propose a dynamic factor model that permits exact filtering, and we explore the efficacy of our methods both in a simulation study and in a detailed empirical example.
    Keywords: Business cycle, Expansion, Recession, State space model, Macroeconomic forecasting, Dynamic factor model
    JEL: E32 E37 C01 C22
    Date: 2007–07–24
  4. By: Jens H. E. Christensen (Financial Research, Federal Reserve Bank of San Francisco); Francis X. Diebold (Department of Economics, University of Pennsylvania); Glenn D. Rudebusch (Economic Research Department, Federal Reserve Bank of San Francisco)
    Abstract: We derive the class of arbitrage-free affine dynamic term structure models that approximate the widely-used Nelson-Siegel yield-curve specification. Our theoretical analysis relates this new class of models to the canonical representation of the three-factor arbitrage-free affine model. Our empirical analysis shows that imposing the Nelson-Siegel structure on this canonical representation greatly improves its empirical tractability; furthermore, we find that improvements in predictive performance are achieved from the imposition of absence of arbitrage.
    Keywords: arbitrage, Nelson-Siegel, term structure, factor models, forecast accuracy
    JEL: C5 G1 E4
    Date: 2007–09–11

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