nep-for New Economics Papers
on Forecasting
Issue of 2009‒11‒27
seventeen papers chosen by
Rob J Hyndman
Monash University

  1. Macroeconomic Forecasting and Structural Change By D Agostino, Antonello; Gambetti, Luca; Giannone, Domenico
  2. Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models By Carriero, Andrea; Kapetanios, George; Marcellino, Massimiliano
  3. The Role of Financial Variables in Predicting Economic Activity in the Euro Area By Raphael A. Espinoza; Fabio Fornari; Marco Lombardi
  4. Predicting recoveries and the importance of using enough information By Cai, Xiaoming; Den Haan, Wouter
  5. Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7 By Jonas Dovern; Johannes Weisser
  6. A defence of the FOMC By Ellison, Martin; Sargent, Thomas J
  7. MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area By Kuzin, Vladimir; Marcellino, Massimiliano; Schumacher, Christian
  8. The Taylor Rule and Interest Rate Uncertainty in the U.S. 1970-2006 By Martin Mandler
  9. "Forecasting Realized Volatility with Linear and Nonlinear Models" By Michael McAleer; Marcelo C. Medeiros
  10. Can Parameter Instability Explain the Meese-Rogoff Puzzle? By Bacchetta, Philippe; Beutler, Toni; van Wincoop, Eric
  11. The role of Regime Shifts in the Term Structure of Interest Rates: Further evidence from an Emerging Market By Saltoglu, Burak; Yazgan, Ege
  12. "VaR Forecasts and Dynamic Conditional Correlations for Spot and Futures Returns on Stocks and Bonds" By Abdul Hakim; Michael McAleer
  13. Decomposing Federal Funds Rate forecast uncertainty using real-time data By Martin Mandler
  14. The Fed’s perceived Phillips curve: Evidence from individual FOMC forecasts By Peter Tillmann
  15. Monetary Policy Analysis and Forecasting in the World Economy: A Panel Unobserved Components Approach By Francis Vitek
  16. Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models By K. COUSSEMENT; D. F. BENOIT; D. VAN DEN POEL
  17. Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available By Lee, Kevin; Olekalns, Nils; Shields, Kalvinder K

  1. By: D Agostino, Antonello; Gambetti, Luca; Giannone, Domenico
    Abstract: The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coefficients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the naïve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.
    Keywords: Forecasting; Inflation; Stochastic Volatility; Time Varying Vector Autoregression
    JEL: C32 E37 E47
    Date: 2009–11
  2. By: Carriero, Andrea; Kapetanios, George; Marcellino, Massimiliano
    Abstract: 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 compare their predictive performance for US time series with the most promising existing alternatives, namely, factor models, large scale Bayesian VARs, and multivariate boosting. Specifically, we focus on classical reduced rank regression, a two-step procedure that applies, in turn, shrinkage and reduced rank restrictions, and the reduced rank Bayesian VAR of Geweke (1996). We find that using shrinkage and rank reduction in combination rather than separately improves substantially the accuracy of forecasts, both when the whole set of variables is to be forecast, and for key variables such as industrial production growth, inflation, and the federal funds rate. The robustness of this finding is confirmed by a Monte Carlo experiment based on bootstrapped data. We also provide a consistency result for the reduced rank regression valid when the dimension of the system tends to infinity, which opens the ground to use large scale reduced rank models for empirical analysis.
    Keywords: Bayesian VARs; factor models; forecasting; reduced rank.
    JEL: C11 C13 C33 C53
    Date: 2009–09
  3. By: Raphael A. Espinoza; Fabio Fornari; Marco Lombardi
    Abstract: The U.S. business cycle typically leads the European cycle by a few quarters and this can be used to forecast euro area GDP. We investigate whether financial variables carry additional information. We use vector autoregressions (VARs) which include the U.S. and the euro area GDPs as a minimal set of variables as well as growth in the Rest of the World (an aggregation of seven small countries) and selected combinations of financial variables. Impulse responses (in-sample) show that shocks to financial variables influence real activity. However, according to out-of-sample forecast exercises using the Root Mean Square Error (RMSE) metric, this macro-financial linkage would be weak: financial indicators do not improve short and medium term forecasts of real activity in the euro area, even when their timely availability, relative to GDP, is exploited. This result is partly due to the 'average' nature of the RMSE metric: when forecasting ability is assessed as if in real time (conditionally on the information available at the time of the forecast), we find that models using financial variables would have been preferred, ex ante, in several episodes, in particular between 1999 and 2002. This result suggests that one should not discard, on the basis of RMSE statistics, the use of predictive models that include financial variables if there is a theoretical prior that a financial shock is affecting growth.
    Keywords: Asset prices , Business cycles , Cross country analysis , Economic forecasting , Economic growth , Economic models , Euro Area , Financial crisis , Financial sector , Global Financial Crisis 2008-2009 , Stock markets ,
    Date: 2009–09–14
  4. By: Cai, Xiaoming; Den Haan, Wouter
    Abstract: Several papers that make forecasts about the long-term impact of the current financial crisis rely on models in which there is only one type of financial crisis. These models tend to predict that the current crisis will have long lasting negative effects on economic growth. This paper points out the deficiency in this approach by analyzing the ability of "one-type-shock" models to correctly forecast the recovery from past economic downturns. It is shown that these models often overestimate the long-run impact of recessions and that slightly richer models that allow the effects of recessions to be both persistent and transitory predict recoveries much better.
    Keywords: financial crisis; forecasting; great recession; unit root
    JEL: C51 C53 E37
    Date: 2009–10
  5. By: Jonas Dovern (Kiel Economics Research & Forecasting GmbH & Co. KG,); Johannes Weisser (Max Planck Institute for Economics, Jena)
    Abstract: In this paper, we use survey data to analyze the accuracy, unbiasedness, and the efficiency of professional macroeconomic forecasts. We analyze a large panel of individual forecasts that has not been analyzed in the literature so far. We provide evidence on the properties of forecasts for all G7 counties and for four diffierent macroeconomic variables. Our results show a high degree of dispersion of forecast accuracy across forecasters. We also find that there are large diffierences in the performance of forecasters not only across countries but also across diffierent macroeconomic variables. In general, forecasts tend to be biased in situations where forecasters have to respond to large structural shocks or gradual changes in the trend of a variable. Furthermore, while a sizable fraction of forecasters seem to smooth their GDP forecasts significantly, this does not apply to forecasts made for other macroeconomic variables.
    Keywords: Evaluating forecasts, Macroeconomic Forecasting, Rationality, Survey Data, Fixed-Event Forecasts
    JEL: C25 E32 E37
    Date: 2009–11–16
  6. By: Ellison, Martin; Sargent, Thomas J
    Abstract: We defend the forecasting performance of the FOMC from the recent criticism of Christina and David Romer. Our argument is that the FOMC forecasts a worst-case scenario that it uses to design decisions that will work well enough (are robust) despite possible misspecification of its model. Because these FOMC forecasts are not predictions of what the FOMC expects to occur under its model, it is inappropriate to compare their performance in a horse race against other forecasts. Our interpretation of the FOMC as a robust policymaker can explain all the findings of the Romers and rationalises differences between FOMC forecasts and forecasts published in the Greenbook by the staff of the Federal Reserve System.
    Keywords: forecasting; monetary policy; robustness
    JEL: C53 E52 E58
    Date: 2009–10
  7. By: Kuzin, Vladimir; Marcellino, Massimiliano; Schumacher, Christian
    Abstract: This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coefficients, whereas MF-VAR does not restrict the dynamics and therefore can suffer from the curse of dimensionality. But if the restrictions imposed by MIDAS are too stringent, the MF-VAR can perform better. Hence, it is difficult to rank MIDAS and MF-VAR a priori, and their relative ranking is better evaluated empirically. In this paper, we compare their performance in a relevant case for policy making, i.e., nowcasting and forecasting quarterly GDP growth in the euro area, on a monthly basis and using a set of 20 monthly indicators. It turns out that the two approaches are more complementary than substitutes, since MF-VAR tends to perform better for longer horizons, whereas MIDAS for shorter horizons.
    Keywords: euro area growth; MIDAS; mixed-frequency data; mixed-frequency VAR; nowcasting
    JEL: C53 E37
    Date: 2009–09
  8. By: Martin Mandler (University of Giessen, Department of Economics and Business, Licher Straße 62, D-35394 Gießen)
    Abstract: This paper shows how to estimate forecast uncertainty about future short-term interest rates by combining a time-varying Taylor rule with an unobserved components model of economic fundamentals. Using this model I separate interest rate uncertainty into economically meaningful components that represent uncertainty about future economic conditions and uncertainty about future monetary policy. Results from estimating the model on U.S. data suggest important changes in uncertainty about future short-term interest rates over time and highlight the relative importance of the different elements which underlie interest rate uncertainty for the U.S.
    Keywords: Monetary policy, reaction functions, state-space models, output-gap forecasts, inflation forecasts
    JEL: E52 C32 C53
    Date: 2009
  9. By: Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo); Marcelo C. Medeiros (Department of Economics, Pontifical Catholic University of Rio de Janeiro)
    Abstract: In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.
    Date: 2009–10
  10. By: Bacchetta, Philippe; Beutler, Toni; van Wincoop, Eric
    Abstract: The empirical literature on nominal exchange rates shows that the current exchange rate is often a better predictor of future exchange rates than a linear combination of macroeconomic fundamentals. This result is behind the famous Meese-Rogoff puzzle. In this paper we evaluate whether parameter instability can account for this puzzle. We consider a theoretical reduced-form relationship between the exchange rate and fundamentals in which parameters are either constant or time varying. We calibrate the model to data for exchange rates and fundamentals and conduct the exact same Meese-Rogoff exercise with data generated by the model. Our main finding is that the impact of time-varying parameters on the prediction performance is either very small or goes in the wrong direction. To help interpret the findings, we derive theoretical results on the impact of time-varying parameters on the out-of-sample forecasting performance of the model. We conclude that it is not time-varying parameters, but rather small sample estimation bias, that explains the Meese-Rogoff puzzle.
    Keywords: Exchange rate forecasting; exchange rate models
    JEL: F31 F37 F41
    Date: 2009–07
  11. By: Saltoglu, Burak; Yazgan, Ege
    Abstract: In this paper, we investigate the interrelations among Turkish interest rates with different maturities by using a regime switching Vector Error Correction (VECM) model. We find a long run equilibrium relationship among interest rates with various maturities. Furthermore we conclude that term structure dynamics exhibit significant nonlinearity. Forecasting experiment also reveals that the nonlinear term structure models do fare better than other linear specifications. However, we cannot conclude that interest rate adjustments are made in an asymmetric way in the long run equilibrium.
    Keywords: Term Structure of Interest Rates; Regime Switching; Forecasting; Foreacast Evaluation; Cointegration
    JEL: C13 C22
    Date: 2009
  12. By: Abdul Hakim (Faculty of Economics, Indonesian Islamic University); Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)
    Abstract: The paper investigates the interdependence and conditional correlations between futures contracts and their underlying assets, both for stock and bond markets, and the impact of the interdependence and conditional correlations on VaR forecasts. The paper finds evidence of volatility spillovers from spot (futures) to futures (spot) markets, and time-varying conditional correlations between futures and their underlying assets. It also finds evidence that the DCC model of Engle (2002) provides slightly better VaR forecasts as compared with the CCC model of Bollerslev (1990) and the BEKK model of Engle and Kroner (1995).
    Date: 2009–10
  13. By: Martin Mandler (University of Giessen, Department of Economics and Business, Licher Straße 66, D-35394 Gießen)
    Abstract: Using real-time data I estimate out-of-sample forecast uncertainty about the Federal Funds Rate. Combining a Taylor rule with a model of economic fundamentals I disentangle economically interpretable components of forecast uncertainty: uncertainty about future economic conditions and uncertainty about future monetary policy. Uncertainty about U.S. monetary policy fell to unprecedented low levels in the 1980s and remained low while uncertainty about future output and inflation declined only temporarily. This points to an important role of increased predictability of monetary policy in explaining the decline in macroeconomic volatility in the U.S. since the mid-1980s.
    Keywords: monetary policy reaction function, interest rate uncertainty, state-space model
    JEL: E52 C32 C53
    Date: 2009
  14. By: Peter Tillmann (Justus Liebig University Gießen, Department of Economics, Licher Straße 62, D-35394 Gießen)
    Abstract: This note uncovers the Phillips curve trade-off perceived by U.S. monetary policymakers. For that purpose we use data on individual forecasts for unemployment and inflation submitted by each individual FOMC member, which was recently made available for the period 1992-1998. The results point to significant changes in the perceived trade-off over time with the Phillips curve flattening and the implied NAIRU falling towards the second half of the sample. Hence, the results suggest that policymakers were aware of these changes in real-time.
    Keywords: inflation forecast, NAIRU, Phillips curve, monetary policy, Federal Reserve
    JEL: E43 E52
    Date: 2009
  15. By: Francis Vitek
    Abstract: This paper develops a panel unobserved components model of the monetary transmission mechanism in the world economy, disaggregated into its fifteen largest national economies. This structural macroeconometric model features extensive linkages between the real and financial sectors, both within and across economies. A variety of monetary policy analysis and forecasting applications of the estimated model are demonstrated, based on a novel Bayesian framework for conditioning on judgment.
    Keywords: Business cycles , Cross country analysis , Developed countries , Economic forecasting , Economic models , Emerging markets , Financial sector , Inflation , International financial system , Monetary policy , Monetary transmission mechanism , Real sector ,
    Date: 2009–10–28
    Abstract: Nowadays, companies are investing in a well-considered CRM strategy. One of the cornerstones in CRM is customer churn prediction, where one tries to predict whether or not a customer will leave the company. This study focuses on how to better support marketing decision makers in identifying risky customers by using Generalized Additive Models (GAM). Compared to Logistic Regression, GAM relaxes the linearity constraint which allows for complex non-linear fits to the data. The contributions to the literature are three-fold: (i) it is shown that GAM is able to improve marketing decision making by better identifying risky customers; (ii) it is shown that GAM increases the interpretability of the churn model by visualizing the non-linear relationships with customer churn identifying a quasi-exponential, a U, an inverted U or a complex trend and (iii) marketing managers are able to significantly increase business value by applying GAM in this churn prediction context.
    Date: 2009–07
  17. By: Lee, Kevin; Olekalns, Nils; Shields, Kalvinder K
    Abstract: A canonical model is described which reflects the real-time informational context of decision-making. Comparisons are drawn with ‘conventional’ models that incorrectly omit market-informed insights on future macroeconomic conditions and inappropriately incorporate information that was not available at the time. It is argued that conventional models are misspecified and misinterpret news but that these deficiencies will not be exposed either by diagnostic tests applied to the conventional models or by typical impulse response analyses. This is demonstrated through an analysis of quarterly US data 1968q4-2008q4. However, estimated real-time models considerably improve out-ofsample forecasting performance, provide more accurate ‘nowcasts’ of the current state of the macroeconomy and provide more timely indicators of the business cycle. The point is illustrated through an analysis of the US recessions of 1990q3-1991q2 and 2001q1-2001q4 and the most recent experiences of 2008.
    Keywords: Business Cycles; Nowcasting; Real-Time Data; Structural Modelling
    JEL: E52 E58
    Date: 2009–09

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