nep-for New Economics Papers
on Forecasting
Issue of 2009‒10‒10
seven papers chosen by
Rob J Hyndman
Monash University

  1. UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? By Gary Koop; Dimitris Korobilis
  2. Improving Unemployment Rate Forecasts Using Survey Data By Österholm, Pär
  3. Incorporating Market Information into the Construction of the Fan Chart By Selim Elekdag; Prakash Kannan
  4. Forecasting Inflation in Sudan By Kenji Moriyama; Abdul Naseer
  5. On-Going versus Completed Interventions and Yen/Dollar Expectations - Evidence from Disaggregated Survey Data By Yushi Yoshida; Jan C. Rülke
  6. Who will go down this year? The Determinants of Promotion and Relegation in European Soccer Leagues By Jean-Baptiste Dherbecourt; Bastien Drut
  7. A general "bang-bang" principle for predicting the maximum of a random walk By Pieter C. Allaart

  1. By: Gary Koop (Department of Economics, University of Strathclyde); Dimitris Korobilis (Department of Economics, University of Strathclyde)
    Abstract: Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.
    Keywords: Bayesian, state space model, factor model, dynamic model averaging
    JEL: E31 E37 C11 C53
    Date: 2009–08
  2. By: Österholm, Pär (National Institute of Economic Research)
    Abstract: This paper investigates whether forecasts of the Swedish unemployment rate can be improved by using business and household survey data. We conduct an out-of-sample forecast exercise in which the performance of a Bayesian VAR model with only macroeconomic data is compared to that when the model also includes survey data. Results show that the forecasting performance at short horizons can be improved. The im-provement is largest when forward-looking data from the manufacturing industry is employed.
    Keywords: Bayesian VAR; Labour market
    JEL: E17 E24 E27
    Date: 2009–06–01
  3. By: Selim Elekdag; Prakash Kannan
    Abstract: This paper develops a simple procedure for incorporating market-based information into the construction of fan charts. Using the International Monetary Fund (IMF)'s global growth forecast as a working example, the paper goes through the theoretical and practical considerations of this new approach. The resulting spreadsheet, which implements the approach, is available upon request from the authors.
    Keywords: Data analysis , Economic forecasting , Economic growth , Economic models , Forecasting models , Markets , World Economic Outlook ,
    Date: 2009–08–24
  4. By: Kenji Moriyama; Abdul Naseer
    Abstract: This paper forecasts inflation in Sudan following two methodologies: the Autoregressive Moving Average (ARMA) model and by looking at the leading indicators of inflation. The estimated ARMA model remarkably tracks the actual inflation during the sample period. The Granger causality test suggests that private sector credit and world wheat prices are the leading indicators explaining inflation in Sudan. Inflation forecasts based on both approaches suggest that inflationary pressures for 2009 and 2010 will be modest and that inflation will remain in single-digits, assuming that prudent macroeconomic policies are maintained.
    Keywords: Central banks , Commodity price fluctuations , Credit expansion , Data analysis , External shocks , Forecasting models , Inflation , Inflation targeting , Monetary policy , Money supply , Private sector , Sudan , Wheat ,
    Date: 2009–06–24
  5. By: Yushi Yoshida (Faculty of Economics, Kyushu Sangyo University); Jan C. Rülke (Otto Beisheim School of Management, WHU)
    Abstract: This paper analyzes the effectiveness of Bank of Japan interventions between November 1995 and December 2004. We follow the methodology proposed by Fatum and Hutchison (2006) to determine the success of intervention by measuring prior and posterior exchange rate movements. Conditional on the successful intervention activities, we examine the impact of interventions on exchange rate expectations of market participants using the Foreign Exchange Consensus Forecasts poll in a panel data framework, rather than only focusing on sample average and variance of forecasts. Compared to the existing literature, which argues that interventions have, if at all, only very short-term effects on the exchange rate, we also find medium-term effects of interventions on exchange rate expectations.
    Keywords: Bank of Japan; Central bank intervention; Forecasts; Exchange rate expectations; Successful intervention
    JEL: F31 G15
    Date: 2009–10
  6. By: Jean-Baptiste Dherbecourt (Ecole doctorale de l’Ecole Polytechnique, Palaiseau, France); Bastien Drut (Centre Emile Bernheim, Solvay Brussels School of Economics and Management, Université Libre de Bruxelles, Brussel, Credit Agricole Asset Management SGR and University of Paris Ouest, Paris.)
    Abstract: Contributing to the lively debate on closed leagues (North American model) versus open leagues (European model) in professional sport league, this paper aims at determining the drivers of promotion and relegation in the major European soccer leagues. Using a large and original dataset (for example: club’s link with a billionaire, club listed in the stock market, etc.) and logistic regressions, our results show that institutional factors matter to settle in the elite. It also indicates that open leagues system in European soccer championships is de facto very similar to closed leagues system. Furthermore, our forecasting model can be of interest for soccer investors or bookmakers.
    Keywords: Economics of Sport, Organization of Sports Leagues, Soccer, Promotion and Relegation, Economic Forecasting, Regional Economy, Billionaires, Stock Market.
    JEL: L83 R11 R58
    Date: 2009–10
  7. By: Pieter C. Allaart
    Abstract: Let $(B_t)_{0\leq t\leq T}$ be either a Bernoulli random walk or a Brownian motion with drift, and let $M_t:=\max\{B_s: 0\leq s\leq t\}$, $0\leq t\leq T$. This paper solves the general optimal prediction problem \sup_{0\leq\tau\leq T}\sE[f(M_T-B_\tau)], where the supremum is over all stopping times $\tau$ adapted to the natural filtration of $(B_t)$, and $f$ is a nonincreasing convex function. The optimal stopping time $\tau^*$ is shown to be of "bang-bang" type: $\tau^*\equiv 0$ if the drift of the underlying process $(B_t)$ is negative, and $\tau^*\equiv T$ is the drift is positive. This result generalizes recent findings by S. Yam, S. Yung and W. Zhou [{\em J. Appl. Probab.} {\bf 46} (2009), 651--668] and J. Du Toit and G. Peskir [{\em Ann. Appl. Probab.} {\bf 19} (2009), 983--1014], and provides additional mathematical justification for the dictum in finance that one should sell bad stocks immediately, but keep good ones as long as possible.
    Date: 2009–10

This nep-for issue is ©2009 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.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.