nep-for New Economics Papers
on Forecasting
Issue of 2008‒02‒02
four papers chosen by
Rob J Hyndman
Monash University

  1. A Manager's Perspective on Combining Expert and Model-based Forecasts By Franses, Ph.H.B.F.; Legerstee, R.
  2. A note on long horizon forecasts of nonlinear models of real exchange rates: Comments on Rapach and Wohar (2006) By Buncic, Daniel
  3. Projecting the Medium-Term: Outcomes and Errors for GDP Growth By Kappler, Marcus
  4. Does Benford’s law hold in economic research and forecasting? By Günnel, Stefan; Tödter, Karl-Heinz

  1. By: Franses, Ph.H.B.F.; Legerstee, R. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
    Abstract: We study the performance of sales forecasts which linearly combine model-based forecasts and expert forecasts. Using a unique and very large database containing monthly model-based forecasts for many pharmaceutical products and forecasts given by thirty-seven different experts, we document that a combination almost always is most accurate. When correlating the specific weights in these "best" linear combinations with experts' experience and behaviour, we find that more experience is beneficial for forecasts for nearby horizons. And, when the rate of bracketing increases the relative weights converge to a 50%-50% distribution, when there is some slight variation across forecasts horizons.
    Keywords: model-based forecasts;experts forecast;combining forecasts
    Date: 2007–12–06
  2. By: Buncic, Daniel
    Abstract: We show that long horizon forecasts from the nonlinear models that are considered in the study by Rapach andWohar (2006) cannot generate any forecast gains over a simple AR(1) specification. This is contrary to the findings reported in Rapach and Wohar (2006). Moreover, we illustrate graphically that the nonlinearity in the forecasts from the ESTAR model is the strongest when forecasting one step-ahead and that it diminishes as the forecast horizon increases. There exists, therefore, no potential whatsoever for the considered nonlinear models to outperform linear ones when forecasting far ahead. We also illustrate graphically why one step-ahead forecasts from the nonlinear ESTAR model fail to yield superior predictions to a simple AR(1).
    Keywords: PPP; regime modelling; nonlinear real exchange rate models; ESTAR; forecast evaluation.
    JEL: C53 C52 F47 C22 F31
    Date: 2008–01–24
  3. By: Kappler, Marcus
    Abstract: The focus of this paper is the evaluation of a very popular method for potential output estimation and medium-term forecasting— the production function approach—in terms of predictive performance. For this purpose, a forecast evaluation for the three to five years ahead predictions of GDP growth for the individual G7 countries is conducted. To carry out the forecast performance check a particular testing framework is derived that allows the computation of robust test statistics given the specific nature of the generated out-of sample forecasts. In addition, medium-term GDP projections from national and international institutions are examined and it is assessed whether these projections convey a reliable view about future economic developments and whether there is scope for improving their predictive content.
    Keywords: Potential output, projections, forecast evaluation
    JEL: C53 E23 E27
    Date: 2007
  4. By: Günnel, Stefan; Tödter, Karl-Heinz
    Abstract: First and higher order digits in data sets of natural and socio-economic processes often follow a distribution called Benford’s law. This phenomenon has been used in many business and scientific applications, especially in fraud detection for financial data. In this paper, we analyse whether Benford’s law holds in economic research and forecasting. First, we examine the distribution of leading digits of regression coefficients and standard errors in research papers, published in Empirica and Applied Economics Letters. Second, we analyse forecasts of GDP growth and CPI inflation in Germany, published in Consensus Forecasts. There are two main findings: The relative frequencies of the first and second digits in economic research are broadly consistent with Benford’s law. In sharp contrast, the second digits of Consensus Forecasts exhibit a massive excess of zeros and fives, raising doubts on their information content.
    Keywords: Benford’s Law, fraud detection, regression coefficients and standard errors, growth and inflation forecasts
    JEL: C12 C52 C8
    Date: 2007

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