nep-for New Economics Papers
on Forecasting
Issue of 2006‒11‒18
sixteen papers chosen by
Rob J Hyndman
Monash University

  1. Beyond Optimal Forecasting By Richard A. Ashley.
  2. Forecast Encompassing Tests and Probability Forecasts By Clements, Michael P; Harvey, David I
  3. Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation. By Clements, Michael P; Galvão, Ana Beatriz
  4. Monetary Policy Rules under Heterogeneous Inflation Expectations By Sophocles N. Brissimis; Nicholas S. Magginas
  5. Inflation Forecasts and the New Keynesian Phillips Curve By Sophocles N. Brissimis; Nicholas S. Magginas
  6. Price Impacts of Deals and Predictability of the Exchange Rate Movements By Takatoshi Ito; Yuko Hashimoto
  7. A Behavioral Finance Model of the Exchange Rate with Many Forecasting Rules By Paul De Grauwe; Pablo Rovira Kaltwasser
  8. Real-time forecasting of GDP based on a large factor model with monthly and quarterly data By Schumacher, Christian; Breitung, Jörg
  9. The European Union GDP Forecast Rationality under Asymmetric Preferences By George A. Christodoulakis
  10. Forecasting Euro-Area Variables with German Pre-EMU Data By Ralf Brueggemann; Helmut Luetkepohl; Massimiliano Marcellino
  11. Regime Switching and Artificial Neural Network Forecasting By Eleni Constantinou; Robert Georgiades; Avo Kazandjian; George Kouretas
  12. Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters By Clements, Michael P
  13. Accurate Value-at-Risk Forecast with the (good old) Normal-GARCH Model By Christoph Hartz; Stefan Mittnik; Marc S. Paolella
  14. Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components? By De Mol, Christine; Giannone, Domenico; Reichlin, Lucrezia
  15. Thin-Slice Forecasts of Gubernatorial Elections By Daniel J. Benjamin; Jesse M. Shapiro
  16. Modeling the Components of Market Discipline By Faidon Kalfaoglou; Alexandros Sarris

  1. By: Richard A. Ashley.
    Keywords: forecasting,forecast loss functions,stochastic dominance.
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:vpi:wpaper:e06-10&r=for
  2. By: Clements, Michael P (Department of Economics, University of Warwick); Harvey, David I (School of Economics, University of Nottingham)
    Abstract: We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models’ parameters on these distributions. The small-sample performance of the various statistics is investigated, both in terms of small numbers of forecasts and model estimation sample sizes. Two empirical applications show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts. Probability forecasts ; encompassing tests ; recession probabilities
    JEL: C12 C15 C53
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:wrk:warwec:774&r=for
  3. By: Clements, Michael P (Department of Economics, University of Warwick); Galvão, Ana Beatriz (Bank of Portugal)
    Abstract: Although many macroeconomic series such as US real output growth are sampled quarterly, many potentially useful predictors are observed at a higher frequency. We look at whether a recently developed mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth and inflation. We carry out a number of related real-time forecast comparisons using various indicators as explanatory variables. We find that MIDAS model forecasts of output growth are more accurate at horizons less than one quarter using coincident indicators ; that MIDAS models are an effective way of combining information from multiple indicators ; and that the forecast accuracy of the unemployment-rate Phillips curve for inflation is enhanced using the MIDAS approach.
    Keywords: Data frequency ; multiple predictors ; combination ; real-time forecasting
    JEL: C51 C53
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:wrk:warwec:773&r=for
  4. By: Sophocles N. Brissimis (Bank of Greece, Economic Research Department and University of Piraeus); Nicholas S. Magginas (National Bank of Greece)
    Abstract: This paper evaluates the role of inflation-forecast heterogeneity in US monetary policy making. The deviation between private and central bank inflation forecasts is identified as a factor increasing inflation persistence and thus calling for a policy reaction. An optimal policy rule is derived by the minimization under discretion of a standard central bank loss function subject to a Phillips curve, modified to include the forecast deviation, and a forward-looking aggregate demand equation. This rule, which itself includes the forecast deviation as an additional argument, is estimated for the period 1974-1998, covering the Chairmanships of Arthur Burns, Paul Volcker and Alan Greenspan, by using real-time forecasts of inflation and the output gap obtained from the FOMC’s Greenbook and the Survey of Professional Forecasters. The estimated rule remains remarkably stable over the whole sample period, challenging the conventional view of a structural break following Volcker’s appointment as Chairman of the Fed. Finally, the substantial decline in the significance of the interest-rate smoothing term in the rule indicates that monetary policy inertia may, to a large extent, be an artifact of serially correlated inflation-forecast errors that feed into policy decisions in real time.
    Keywords: Forward-looking model; Monetary policy reaction function; Expectations formation; Inflation expectations
    JEL: D84 E31 E43 E52 E58
    Date: 2006–03
    URL: http://d.repec.org/n?u=RePEc:bog:wpaper:35&r=for
  5. By: Sophocles N. Brissimis (Bank of Greece, Economic Research Department and University of Piraeus); Nicholas S. Magginas (National Bank of Greece)
    Abstract: The ability of the New Keynesian Phillips curve to explain US inflation dynamics when official central bank forecasts (Greenbook forecasts) are used as a proxy for inflation expectations is examined. The New Keynesian Phillips curve is estimated on quarterly data spanning the period 1970Q1-1998Q2 against the alternative of the Hybrid Phillips curve, which allows for a backward-looking component in the price-setting behavior in the economy. The results are compared to those obtained using actual data on future inflation as conventionally employed in empirical work under the assumption of rational expectations. The empirical evidence provides, in contrast to most of the relevant literature, considerable support for the standard forward-looking New Keynesian Phillips curve when inflation expectations are measured using official inflation forecasts. In this case, lagged inflation terms become insignificant in the hybrid specification. The usefulness of real unit labor cost as the preferred proxy for real marginal cost in recent empirical work on the Phillips curve is confirmed by our results.
    Keywords: Money demand; Inflation; Phillips curve; Real marginal cost; Real-time data; GMM estimation
    JEL: C13 C52 E31 E37 E50 E52
    Date: 2006–05
    URL: http://d.repec.org/n?u=RePEc:bog:wpaper:38&r=for
  6. By: Takatoshi Ito; Yuko Hashimoto
    Abstract: This paper examines the price impact and the predictability of the exchange rate movement using the transaction data recorded in the electronic broking system of the spot foreign exchange market. The number of actual deals at the ask (or bid side) for a specified time interval may be regarded as "order flows" to buy (or sell) in Richard Lyons' work. First, the contemporaneous impact of order flows on the quote and deal prices are analyzed. Second, the price predictability is examined. Our forecasting equations of the exchange rate for the next X minutes (X=1, 5, 15, 30) show that coefficients are significantly different from zero in both 5-min and 1-min forecast horizons, but the significance disappears in the 30-minute interval. The t-statistics become larger as the prediction window becomes shorter. Price impacts of deals at one side of the market are significant but short-lived. Market participants, if they can observe and analyze all the transactions information in real time, may be able to extract information to predict the price movements in the following next few minutes.
    JEL: F31 F33 G15
    Date: 2006–11
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:12682&r=for
  7. By: Paul De Grauwe; Pablo Rovira Kaltwasser
    Abstract: This paper presents a behavioral finance model of the exchange rate. Agents forecast the exchange rate by means of very simple rules. They can choose between three groups of forecasting rules: fundamentalist, extrapolative and momentum rules. Agents using a fundamentalist rule are not able to observe the true value of the fundamental exchange and therefore have to rely on an estimate of this variable to make a forecast. Based on simulation analysis we find that two types of equilibria exist, a fundamental and a non-fundamental one. Both the probability of finding a particular type of equilibrium and the probability of switching between different types of equilibria depend on the number of rules available to agents. Furthermore, we find that the exchange rate dynamics is sensitive to initial conditions and to the risk perception about the underlying fundamental. Both results are dependent on the number of forecasting rules.
    JEL: C53 F31
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_1849&r=for
  8. By: Schumacher, Christian; Breitung, Jörg
    Abstract: This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm combined with a principal components estimator. We discuss the in-sample properties of the estimator in real-time environments and methods for out-of-sample forecasting. As an empirical application, we estimate monthly German GDP in real-time, discuss the nowcast and forecast accuracy of the model and the role of revisions. Furthermore, we assess the contribution of timely monthly data to the forecast performance.
    Keywords: monthly GDP, EM algorithm, principal components, factor models
    JEL: C53 E37
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:zbw:bubdp1:5097&r=for
  9. By: George A. Christodoulakis (Bank of Greece and Manchester Business School)
    Abstract: This paper examines the behaviour of the demand for money in Greece during 1976:1-2000:4, a period that included many of the influences that cause money-demand instability. Two empirical methodologies, vector error correction (VEC) modelling and second-generation random coefficient (RC) modelling, are used to estimate the demand for money. The coefficients of both the VEC and RC procedures support the hypothesis that the demand for money becomes more responsive to both the own rate of return on money balances and the opportunity cost of holding money because of financial deregulation. In general, both procedures also support the hypothesis that the income elasticity of money demand declines over time as a result of technological improvements in the payments system and the development of money substitutes, which lead to economies of scale in holding money.
    Keywords: Asymmetric Loss Preferences, Forecast Rationality, GDP Growth Forecasts, GMM Estimation, Lin-Lin.
    JEL: C1 C44 C53 E17 E27
    Date: 2005–12
    URL: http://d.repec.org/n?u=RePEc:bog:wpaper:30&r=for
  10. By: Ralf Brueggemann; Helmut Luetkepohl; Massimiliano Marcellino
    Abstract: It is investigated whether Euro-area variables can be forecast better based on synthetic time series for the pre-Euro period or by using just data from Germany for the pre-Euro period. Our forecast comparison is based on quarterly data for the period 1970Q1 - 2003Q4 for ten macroeconomic variables. The years 2000 - 2003 are used as forecasting period. A range of different univariate forecasting methods is applied. Some of them are based on linear autoregressive models and we also use some nonlinear or time-varying coefficient models. It turns out that most variables which have a similar level for Germany and the Euro-area such as prices can be better predicted based on German data while aggregated European data are preferable for forecasting variables which need considerable adjustments in their levels when joining German and EMU data. These results suggest that for variables which have a similar level for Germany and the Euro-area it may be reasonable to consider the German pre-EMU data for studying economic problems in the Euro-area.
    Keywords: Aggregation, forecasting, European monetary union, constructing EMU data
    JEL: C22 C53
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:eui:euiwps:eco2006/30&r=for
  11. By: Eleni Constantinou (Department of Accounting and Finance, The Philips College, 4-6 Lamias Street, CY-2100, Nicosia,); Robert Georgiades (Department of Accounting and Finance, The Philips College, 4-6 Lamias Street, CY-2100, Nicosia,); Avo Kazandjian (Department of Business Studies, The Philips College, 4-6 Lamias Street, CY-2100, Nicosia, Cyprus.); George Kouretas (Department of Economics, University of Crete, Greece)
    Abstract: This paper provides an analysis of regime switching in volatility and out-of-sample forecasting of the Cyprus Stock Exchange using daily data for the period 1996-2002. We first model volatility regime switching within a univariate Markov-Switching framework. Modelling stock returns within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. The results show that linearity is rejected in favour of a MS specification, which forms statistically an adequate representation of the data. Two regimes are implied by the model; the high volatility regime and the low volatility one and they provide quite accurately the state of volatility associated with the presence of a rational bubble in the capital market of Cyprus. Another implication is that there is evidence of regime clustering. We then provide out-of-sample forecasts of the CSE daily returns using two competing non-linear models, the univariate Markov Switching model and the Artificial Neural Network Model. The comparison of the out-of-sample forecasts is done on the basis of forecast accuracy, using the Diebold and Mariano (1995) test and forecast encompassing, using the Clements and Hendry (1998) test. The results suggest that both non-linear models equivalent in forecasting accuracy and forecasting encompassing and therefore on forecasting performance.
    Keywords: Regime switching, artificial neural networks, stock returns, forecast
    JEL: G
    Date: 2005–01
    URL: http://d.repec.org/n?u=RePEc:crt:wpaper:0502&r=for
  12. By: Clements, Michael P (Department of Economics, University of Warwick)
    Abstract: We ask whether the different types of forecasts made by individual survey respondents are mutually consistent, using the SPF survey data. We compare the point forecasts and central tendencies of probability distributions matched by individual respondent, and compare the forecast probabilities of declines in output with the probabilities implied by the probability distributions. When the expected associations between these different types of forecasts do not hold for some idividuals, we consider whether the discrepancies we observe are consistent with rational behaviour by agents with asymmetric loss functions.
    Keywords: Rationality ; probability forecasts ; probability distributions
    JEL: C53 E32 E37
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:wrk:warwec:772&r=for
  13. By: Christoph Hartz (University of Munich); Stefan Mittnik (University of Munich, Center for Financial Studies and ifo); Marc S. Paolella (University of Zurich)
    Abstract: A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.
    Keywords: Bootstrap, GARCH, Value-at-Risk
    JEL: C22 C53 C63 G12
    Date: 2006–11–03
    URL: http://d.repec.org/n?u=RePEc:cfs:cfswop:wp2000623&r=for
  14. By: De Mol, Christine; Giannone, Domenico; Reichlin, Lucrezia
    Abstract: This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section.
    Keywords: Bayesian VAR, ridge regression, Lasso regression, principal components, large cross-sections
    JEL: C11 C13 C33 C53
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:zbw:bubdp1:5040&r=for
  15. By: Daniel J. Benjamin; Jesse M. Shapiro
    Abstract: We showed 10-second, silent video clips of unfamiliar gubernatorial debates to a group of experimental participants and asked them to predict the election outcomes. The participants' predictions explain more than 20 percent of the variation in the actual two-party vote share across the 58 elections in our study, and their importance survives a range of controls, including state fixed effects. In a horse race of alternative forecasting models, participants' visual forecasts significantly outperform economic variables in predicting vote shares, and are comparable in predictive power to a measure of incumbency status. Adding policy information to the video clips by turning on the sound tends, if anything, to worsen participants' accuracy, suggesting that naïveté may be an asset in some forecasting tasks.
    JEL: D72 J45
    Date: 2006–11
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:12660&r=for
  16. By: Faidon Kalfaoglou (Bank of Greece); Alexandros Sarris (Food and Agricultural Organization of the United Nations and University of Athens)
    Abstract: This paper evaluates the role of inflation-forecast heterogeneity in US monetary policy making. The deviation between private and central bank inflation forecasts is identified as a factor increasing inflation persistence and thus calling for a policy reaction. An optimal policy rule is derived by the minimization under discretion of a standard central bank loss function subject to a Phillips curve, modified to include the forecast deviation, and a forward-looking aggregate demand equation. This rule, which itself includes the forecast deviation as an additional argument, is estimated for the period 1974-1998, covering the Chairmanships of Arthur Burns, Paul Volcker and Alan Greenspan, by using real-time forecasts of inflation and the output gap obtained from the FOMC’s Greenbook and the Survey of Professional Forecasters. The estimated rule remains remarkably stable over the whole sample period, challenging the conventional view of a structural break following Volcker’s appointment as Chairman of the Fed. Finally, the substantial decline in the significance of the interest-rate smoothing term in the rule indicates that monetary policy inertia may, to a large extent, be an artifact of serially correlated inflation-forecast errors that feed into policy decisions in real time.
    Keywords: Market discipline, transparency, bank risk
    JEL: G18 G21 G28
    Date: 2006–04
    URL: http://d.repec.org/n?u=RePEc:bog:wpaper:36&r=for

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