nep-for New Economics Papers
on Forecasting
Issue of 2010‒10‒16
sixteen papers chosen by
Rob J Hyndman
Monash University

  1. Reality checks and nested forecast model comparisons By Todd E. Clark; Michael W. McCracken
  2. Forecasting with many predictors - Is boosting a viable alternative? By Buchen, Teresa; Wohlrabe, Klaus
  3. Testing for unconditional predictive ability By Todd E. Clark; Michael W. McCracken
  4. Robust forecasting of non-stationary time series. By Croux, Christophe; Fried, R.; Gijbels, Irène; Mahieu, Koen
  5. Forecasting Private Consumption by Consumer Surveys By Christian Dreger; Konstantin A. Kholodilin
  6. Economic Prediction of Sport Performances: From Beijing Olympics to 2010 FIFA World Cup in South Africa By Madeleine Andreff; Wladimir Andreff
  7. Data Dissemination Standards and the Statistical Quality of the IMF’s World Economic Outlook Forecasts By Mico Mrkaic
  8. MICA-BBVA: A Factor Model of Economic and Financial Indicators for Short-term GDP Forecasting By Máximo Camacho; Rafael Doménech
  9. Cyclical Behavior of Inventories and Growth Projections Recent Evidence from Europe and the United States By Jens R. Clausen; Alexander W. Hoffmaister
  10. Predicting bond excess returns with forward rates: an asset-allocation perspective By Daniel L. Thornton; Giorgio Valente
  11. Asymmetry and Long Memory in Volatility Modelling By Manabu Asai; Michael McAleer; Marcelo C. Medeiros
  12. Electricity Demand Analysis and Forecasting- The Tradition is Questioned By N. Vijayamohanan Pillai
  13. Industrial Electricity Demand for Turkey: A Structural Time Series Analysis By Zafer Dilaver; Lester C Hunt
  14. Evaluating currency crisis:A multivariate Markov switching approach By Kostas Mouratidis; Dimitris Kenourgios; Aris Samitas
  15. Valuation when Cash Flow Forecasts are Biased By Richard S. Ruback
  16. Can Global Liquidity Forecast Asset Prices? By Reginald Darius

  1. By: Todd E. Clark; Michael W. McCracken
    Abstract: This paper develops a novel and effective bootstrap method for simulating asymptotic critical values for tests of equal forecast accuracy and encompassing among many nested models. The bootstrap, which combines elements of fixed regressor and wild bootstrap methods, is simple to use. We first derive the asymptotic distributions of tests of equal forecast accuracy and encompassing applied to forecasts from multiple models that nest the benchmark model – that is, reality check tests applied to nested models. We then prove the validity of the bootstrap for these tests. Monte Carlo experiments indicate that our proposed bootstrap has better finite-sample size and power than other methods designed for comparison of non-nested models. We conclude with empirical applications to multiple-model forecasts of commodity prices and GDP growth.
    Keywords: Economic forecasting
    Date: 2010
  2. By: Buchen, Teresa; Wohlrabe, Klaus
    Abstract: This paper evaluates the forecast performance of boosting, a variable selection device, and compares it with the forecast combination schemes and dynamic factor models presented in Stock and Watson (2006). Using the same data set and comparison methodology, we find that boosting is a serious competitor for forecasting US industrial production growth in the short run and that it performs best in the longer run.
    Keywords: Forecasting; Boosting; Cross-validation
    JEL: C53 E27
    Date: 2010–09–06
  3. By: Todd E. Clark; Michael W. McCracken
    Abstract: This chapter provides an overview of pseudo-out-of-sample tests of unconditional predictive ability. We begin by providing an overview of the literature, including both empirical applications and theoretical contributions. We then delineate two distinct methodologies for conducting inference: one based on the analytics in West (1996) and the other based on those in Giacomini and White (2006). These two approaches are then carefully described in the context of pairwise tests of equal forecast accuracy between two models. We consider both non-nested and nested comparisons. Monte Carlo evidence provides some guidance as to when the two forms of analytics are most appropriate, in a nested model context.
    Keywords: Economic forecasting
    Date: 2010
  4. By: Croux, Christophe; Fried, R.; Gijbels, Irène; Mahieu, Koen
    Abstract: This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estimator. An additional advantage of the MM-estimator is that it provides a robust estimate of the local variability of the time series.
    Keywords: Heteroscedasticity; Non-parametric regression; Prediction; Outliers; Robustness;
    Date: 2010–09
  5. By: Christian Dreger; Konstantin A. Kholodilin
    Abstract: Survey-based indicators such as the consumer confidence are widely seen as leading indicators for economic activity, especially for the future path of private consumption. Although they receive high attention in the media, their forecasting power appears to be very limited. Therefore, this paper takes a fresh look on the survey data, which serve as a basis for the consumer confidence indicator (CCI) reported by the EU Commission for the euro area and individual member states. Different pooling methods are considered to exploit the information embedded in the consumer survey. Quantitative forecasts are based on Mixed Data Sampling (MIDAS) and bridge equations. While the CCI does not outperform an autoregressive benchmark for the majority of countries, the new indicators increase the forecasting performance. The gains over the CCI are striking for Italy and the entire euro area (20 percent). For Germany and France the gains seem to be lower, but are nevertheless substantial (10 to 15 percent). The best performing indicator should be built upon pre-selection methods, while data-driven aggregation methods should be preferred to determine the weights of the individual ingredients.
    Keywords: Consumer confidence, consumption, nowcasting, mixed frequency data
    JEL: E21 C22
    Date: 2010
  6. By: Madeleine Andreff (University of Paris-Est Marne la Vallée); Wladimir Andreff (University of Paris 1 Panthéon Sorbonne)
    Abstract: This paper uses forecasting techniques to predict outcomes in the Beijing Olympics and 2010 World Cup using economic variables.
    Keywords: sport, Olympics, World Cup
    JEL: L83
    Date: 2010–10
  7. By: Mico Mrkaic
    Abstract: This paper analyzes the effects of IMF member countries participation in the IMF’s Data Standards Initiatives (DSI) on the statistical quality of WEO forecasts. Results show that WEO forecasts for SDDS subscribers are in general better than for GDDS participants and those member countries than do not participate in the DSIs. Policy implications are that the DSI positively affect the statistical quality of forecasts and by extension improve the necessary conditions for multilateral surveillance and the provision of member countries with high quality policy advice.
    Keywords: Data quality assessment framework , Economic forecasting , General Data Dissemination System , Government finance statistics , Members , Special Data Dissemination Standard , World Economic Outlook ,
    Date: 2010–09–03
  8. By: Máximo Camacho; Rafael Doménech
    Abstract: In this paper we extend the Stock and Watson’s (1991) single-index dynamic factor model in an econometric framework that has the advantage of combining information from real and financial indicators published at different frequencies and delays with respect to the period to which they refer. We find that the common factor reflects the behavior of the Spanish business cycle well and helps to estimate with high precision the regime-switching probabilities in line with business cycle phases. We also show that financial indicators are useful for forecasting output growth, particularly when certain financial variables lead the common factor. Finally, we provide a simulated real-time exercise and prove that the model is a very useful tool for the short-term analysis of the Spanish Economy.
    Keywords: dynamic factor model, GDP forecast, financial variables.
    JEL: E32 C22 E27
    Date: 2010–08
  9. By: Jens R. Clausen; Alexander W. Hoffmaister
    Abstract: In the United States and a few European countries, inventory behavior is mainly the outcome of demand shocks: a standard buffer-stock model best characterizes these economies. But most European countries are described by a modified buffer-stock model where supply shocks dominate. In contrast to the United States, inventories boost growth with a one-year lag in Europe. Moreover, inventories provide limited information to improve growth forecasts particularly when a modified buffer-stock model characterizes inventory behavior.
    Keywords: Business cycles , Cross country analysis , Europe , Forecasting models , Manufacturing sector , Production growth , United States ,
    Date: 2010–09–14
  10. By: Daniel L. Thornton; Giorgio Valente
    Abstract: This paper revisits the predictability of bond excess returns by means of long-term forward interest rates. We assess the economic value of out-of-sample forecasting ability of empirical models based on forward rates in a dynamic asset allocation strategy. Our results show that the information content of forward rates does not generate any systematic economic value to investors. The performance of the predictive models against the no-predictability benchmark worsens over time and the few positive performance fees recorded from dynamic portfolio strategies based on forward rates are generally small in size and do not offset realistic transaction costs.
    Keywords: Bond market ; Interest rates
    Date: 2010
  11. By: Manabu Asai; Michael McAleer (University of Canterbury); Marcelo C. Medeiros
    Abstract: A wide variety of conditional and stochastic variance models has been used to estimate latent volatility (or risk). In this paper, we propose a new long memory asymmetric volatility model which captures more flexible asymmetric patterns as compared with existing models. We extend the new specification to realized volatility by taking account of measurement errors, and use the Efficient Importance Sampling technique to estimate the model. As an empirical example, we apply the new model to the realized volatility of Standard and Poor’s 500 Composite Index to show that the new specification of asymmetry significantly improves the goodness of fit, and that the out-of-sample forecasts and Value-at-Risk (VaR) thresholds are satisfactory. Overall, the results of the out-of-sample forecasts show the adequacy of the new asymmetric and long memory volatility model for the period including the global financial crisis.
    Keywords: Asymmetric volatility; long memory; realized volatility; measurement errors; efficient importance sampling
    Date: 2010–10–01
  12. By: N. Vijayamohanan Pillai
    Abstract: The present paper seeks to cast scepticism on the validity and value of the results of all earlier studies in India on energy demand analysis and forecasting based on time series regression, on three grounds. (i) As these studies did not care for model adequacy diagnostic checking, indispensably required to verify the empirical validity of the residual whiteness assumptions underlying the very model, their results might be misleading. (ii) As the time series regression approach of these studies did not account for possible non-stationarity (i.e., unit root integratedness) in the series, their significant results might be just the misleading result of spurious regression. (iii) These studies, by adopting a methodology suitable to a developed power system in advanced economies, sought to correlate the less correlatables in the context of an underdeveloped power system in a less developed economy. [Working Paper No. 312]
    Keywords: India, Kerala, demand analysis, forecasting, non-stationarity
    Date: 2010
  13. By: Zafer Dilaver (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey); Lester C Hunt (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)
    Abstract: This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and -0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020.
    Keywords: Turkish Industrial Electricity Demand; Energy Demand Modelling and Forecasting; Structural Time Series Model (STSM); Future Scenarios.
    JEL: C22 Q41 Q48
    Date: 2010–09
  14. By: Kostas Mouratidis (Department of Economics, The University of Sheffield); Dimitris Kenourgios; Aris Samitas
    Abstract: This paper provides an empirical framework to analyse the nature of currency crises by extending earlier work of Jeanne and Masson (2000) who suggest that a currency crisis model with multiple equilibria can be estimated using Markov regime switching (MRS) models. However, Jeanne and Masson (2000) assume that the transition probabilities across equilibria are constant and independent of fundamentals. Thus, currency crisis is driven by a sunspot unrelated to fundamentals. This paper further contributes to the literature by suggesting a multivariate MRS model to analyse the nature of currency crises. In the new set up, one can test for the impact of the unobserved dynamics of fundamentals on the probability of devaluation. Empirical evidence shows that expectations about fundamentals, which are reflected by their unobserved state variables, not only affect the probability of devaluation but also can be used to forecast a currency crisis one period ahead.
    JEL: C32 F31
    Date: 2010–10
  15. By: Richard S. Ruback (Harvard Business School, Finance Unit)
    Abstract: This paper focuses adaptations to the discount cash flow (DCF) method when valuing forecasted cash flows that are biased measures of expected cash flows. I imagine a simple setting where the expected cash flows equal the forecasted cash flows plus an omitted downside. When the omitted downside is temporary, the adjustment is to deflate the forecasts and to set the discount rate equal to the cost of capital. However, when the downside is permanent, the adjustment is to deflate the cash flows and to increase the discount rate so that it includes the cost of capital plus the probability of a downside.
    Date: 2010–10
  16. By: Reginald Darius
    Abstract: During the period leading up to the global financial crisis many asset classes registered rapid price increases. This coincided with a significant rise in global liquidity. This paper attempts to determine the extent to which the rise in asset prices was influenced by developments in global liquidity. We confirm that global liquidity had a significant impact on the buildup in house prices; however, the impact on equity prices was limited. In contrast to common perception, we find that the impact of global liquidity declined during the period of the Great Moderation. The paper also examines spillovers from global liquidity to domestic variables and concludes that domestic factors generally played a more significant role in house price appreciation relative to global factors. This contradicts the hypothesis of weakened potency of domestic monetary policy in the presence of increased international liquidity.
    Keywords: Asset prices , Economic growth , Forecasting models , Inflation , International liquidity , Price increases , Real estate prices , Spillovers ,
    Date: 2010–08–25

This nep-for issue is ©2010 by Rob J Hyndman. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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