nep-for New Economics Papers
on Forecasting
Issue of 2007‒02‒17
eight papers chosen by
Rob J Hyndman
Monash University

  1. Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation By Calista Cheung; Frédérick Demers
  2. Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder By Konstantin A. Kholodilin; Boriss Siliverstovs; Stefan Kooths
  3. German Exports to the Euro Area - A Cointegration Approach By Sabine Stephan
  4. Forecasting Employment for Germany By Darius Hinz; Camille Logeay
  5. The Hungarian Quarterly Projection Model (NEM) By Szilárd Benk; Zoltán M. Jakab; Mihály András Kovács; Balázs Párkányi; Zoltán Reppa; Gábor Vadas
  6. Assesing the Economic Significance of the Intra-daily Volatility Seasonalities By Zdravetz Lazarov
  7. Are analysts’ loss functions asymmetric? By Peter Pope; David Peel; Mark Clatworthy
  8. Exploring the bullwhip effect by means of spreadsheet simulation By Boute, R.; Lambrecht, M.

  1. By: Calista Cheung; Frédérick Demers
    Abstract: This paper evaluates the performance of static and dynamic factor models for forecasting Canadian real output growth and core inflation on a quarterly basis. We extract the common component from a large number of macroeconomic indicators, and use the estimates to compute out-of-sample forecasts under a recursive and a rolling scheme with different window sizes. Factor-based forecasts are compared with AR(p) models as well as IS- and Phillips-curve models. We find that factor models can improve the forecast accuracy relative to standard benchmark models, for horizons of up to 8 quarters. Forecasts from our proposed factor models are also less prone to committing large errors, in particular when the horizon increases. We further show that the choice of the sampling-scheme has a large influence on the overall forecast accuracy, with smallest rolling-window samples generating superior results to larger samples, implying that using "limited-memory" estimators contribute to improve the quality of the forecasts.
    Keywords: Econometric and statistical methods
    JEL: C32 E37
    Date: 2007
  2. By: Konstantin A. Kholodilin; Boriss Siliverstovs; Stefan Kooths
    Abstract: In this paper we forecast the annual growth rates of the real GDP for each of the 16 German Länder (States) simultaneously. To the best of our knowledge, this is the first attempt in the literature that addresses this question for all German Länder as most of the studies try to forecast the German GDP either on the aggregate level or focus on selected Länder only. Our further contribution to the literature is that next to the usual panel data models such as pooled and within models we apply within models that explicitly account for the spatially autocorrelated errors. On the one hand, it allows us to take advantage of the panel dimension, given the short sample for which the data are available, and hence gain efficiency and precision. On the other hand, accounting for the spatial heterogeneity and correlation is important due to the substantial differences existing between the German regions, in particular between East and West Germany. Our main finding is that pooling helps to significantly (up to 25% in terms of the root mean squared forecast errors) increase the forecasting accuracy compared to the individual autoregressive models estimated for each of the Länder separately.
    Keywords: German Länder; forecasting; dynamic panel model; spatial autocorrelation
    JEL: C21 C23 C53
    Date: 2007
  3. By: Sabine Stephan (IMK at the Hans Boeckler Foundation)
    Abstract: This paper analyses the determinants of German exports to the euro area, which is by far the biggest market for German products. Four conditional error-correction models based on regionally disaggregated data are developed. One specification includes EMU industrial production and a real external value based on consumer prices, the other three use different EMU investment aggregates, the corresponding real external values and a proxy for European market integration to explain exports. The models perform equally well in a number of diagnostic tests. For short-term forecasts, however, the model using industrial production seems to be the best, since it outperforms the other models in terms of one-step ahead out-of-sample forecasts. Furthermore, the explanatory variables of this equation (industrial production and consumer prices) are easier to forecast than investment aggregates and the corresponding prices.
    Keywords: Export Function, Income and Price Elasticity of Exports, Intra-EMU Trade, Error Correction Model, Forecasting
    JEL: C22 C52 F47
    Date: 2005–09
  4. By: Darius Hinz (University of Bielefeld (Student)); Camille Logeay (IMK at the Hans Boeckler Foundation)
    Abstract: This paper deals with the estimation of employment equations for Germany, which are to be used for forecasting and simulation purposes. The authors estimate both single and system error correction equations for German working hours using quarterly raw data covering the period 1980:1-2004:2. Since the focus is on the question whether German reunification has affected or even modified the underlying economic relationships, the authors compare the results to those reported in previous studies for West Germany and Germany, respectively. The authors find that the elasticity of employment with respect to output is robustly estimated and can therefore be restricted to one. The elasticity of employment with respect to the real wage, however, is affected by German reunification and relative factor prices no longer play a significant role. The forecasting quality of the employment equation is satisfactory.
    Keywords: employment, forecasting, cointegration, Germany
    JEL: E24 E27 C22 C32 C53
    Date: 2004–11
  5. By: Szilárd Benk (Magyar Nemzeti Bank); Zoltán M. Jakab (Magyar Nemzeti Bank); Mihály András Kovács (Magyar Nemzeti Bank); Balázs Párkányi (Magyar Nemzeti Bank); Zoltán Reppa (Magyar Nemzeti Bank); Gábor Vadas (Magyar Nemzeti Bank)
    Abstract: This document gives a detailed account of the current version of the Hungarian Quarterly Projection Model (NEM). It describes the main building blocks, presents the forecast performance of the model and, finally, it illustrates the responses to the most important shocks the Hungarian economy may face. This version of the model is used to produce the Bank’s quarterly projections, as well as to perform simulations and scenario analyses.
    Keywords: econometric modelling, forecasting, simulation.
    JEL: C50 C53 E17
    Date: 2006
  6. By: Zdravetz Lazarov (School of Economics and Finance, Queensland University of Technology)
    Abstract: It is a well established empirical fact that volatility follows approxi- mately an inverted U-shaped pattern during the day. It is high in the morning, gradually decreasing, reaching a minimum at lunch time and then starting to increase again until the end of the trading day. In this paper we investigate the dynamic properties of these intra-daily volatility seasonalities. More specifically, we divide daily volatility into several parts and model them separately. Our analysis shows that morning/afternoon volatility has a different time-series behaviour in comparison to lunch time volatility. Also, a substantial improvement in forecasting performance can be obtained by partitioning daily volatility into parts which correspond to the observed intra-daily seasonalities.
  7. By: Peter Pope; David Peel; Mark Clatworthy
    Abstract: Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts’ earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.
    Date: 2006
  8. By: Boute, R.; Lambrecht, M.
    Abstract: An important supply chain research problem is the bullwhip effect: demand fluctuations increase as one moves up the supply chain from retailer to manufacturer. It has been recognized that demand forecasting and ordering policies are two of the key causes of the bullwhip effect. In this paper we present a spreadsheet application, which explores a series of replenishment policies and forecasting techniques under different demand patterns. It illustrates how tuning the parameters of the replenishment policy induces or reduces the bullwhip effect. Moreover, we demonstrate how bullwhip reduction (order variability dampening) may have an adverse impact on inventory holdings. Indeed, order smoothing may increase inventory fluctuations resulting in poorer customer service. As such, the spreadsheets can be used as an educational tool to gain a clear insight into the use or abuse of inventory control policies and improper forecasting in relation to the bullwhip effect and customer service.
    Keywords: Bullwhip effect, forecasting techniques, replenishment rules, inventory fluctuations, spreadsheet simulation
    Date: 2007–02–09

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