nep-for New Economics Papers
on Forecasting
Issue of 2007‒09‒16
four papers chosen by
Rob J Hyndman
Monash University

  1. Hierarchical forecasts for Australian domestic tourism By George Athanasopoulos; Roman A. Ahmed; Rob J. Hyndman
  2. Forecasting economic growth for Estonia : application of common factor methodologies By Christian Schulz
  3. Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset By Jon Faust; Jonathan H. Wright
  4. The Information Content of Elections and Varieties of the Partisan Political Business Cycle By Cameron A. Shelton

  1. By: George Athanasopoulos; Roman A. Ahmed; Rob J. Hyndman
    Abstract: In this paper we explore the hierarchical nature of tourism demand time series and produce short-term forecasts for Australian domestic tourism. The data and forecasts are organized in a hierarchy based on disaggregating the data for different geographical regions and for different purposes of travel. We consider five approaches to hierarchical forecasting: two variations of the top-down approach, the bottom-up method, a newly proposed top-down approach where top-level forecasts are disaggregated according to forecasted proportions of lower level series, and a recently proposed optimal combination approach. Our forecast performance evaluation shows that the top-down approach based on forecast proportions and the optimal combination method perform best for the tourism hierarchies we consider. By applying these methods, we produce detailed forecasts for the Australian domestic tourism market.
    Keywords: Australia, exponential smoothing, hierarchical forecasting, innovations state space models, optimal combination forecasts, top-down method, tourism demand.
    JEL: C13 C22 C53
    Date: 2007–08
    URL: http://d.repec.org/n?u=RePEc:msh:ebswps:2007-12&r=for
  2. By: Christian Schulz
    Abstract: In this paper, the application of two different unobserved factor models to a data set from Estonia is presented. The small-scale state-space model used by Stock and Watson (1991) and the large-scale static principal components model used by Stock and Watson (2002) are employed to derive common factors. Subsequently, using these common factors, forecasts of real economic growth for Estonia are performed and evaluated against benchmark models for different estimation and forecasting periods. Results show that both methods show improvements over the benchmark model, but not for the all the forecasting periods
    Keywords: Estonia, forecasting, principal components, state-space model, forecast perfomance
    JEL: C53 C22 C32 F43
    Date: 2007–09–04
    URL: http://d.repec.org/n?u=RePEc:eea:boewps:wp2007-09&r=for
  3. By: Jon Faust; Jonathan H. Wright
    Abstract: Many recent papers have found that atheoretical forecasting methods using many predictors give better predictions for key macroeconomic variables than various small-model methods. The practical relevance of these results is open to question, however, because these papers generally use ex post revised data not available to forecasters and because no comparison is made to best actual practice. We provide some evidence on both of these points using a new large dataset of vintage data synchronized with the Fed's Greenbook forecast. This dataset consists of a large number of variables, as observed at the time of each Greenbook forecast since 1979. Thus, we can compare real-time large dataset predictions to both simple univariate methods and to the Greenbook forecast. For inflation we find that univariate methods are dominated by the best atheoretical large dataset methods and that these, in turn, are dominated by Greenbook. For GDP growth, in contrast, we find that once one takes account of Greenbook's advantage in evaluating the current state of the economy, neither large dataset methods nor the Greenbook process offers much advantage over a univariate autoregressive forecast.
    JEL: C32 C53 E32 E37
    Date: 2007–09
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:13397&r=for
  4. By: Cameron A. Shelton (Economics Department, Wesleyan University)
    Abstract: This event study uses economic forecasts and opinion polls to measure the response of expectations to election surprise. Use of forecast data complements older work on partisan cycles by allowing a tighter link between election and response thereby mitigating concerns of endogeneity and omitted variables. I fin that forecasters respond swiftly and significantly to election surprise. I further argue that the response ought to vary across countries with different institutional foundations. In support, I find that there exist three distinct patterns in forecasters' responses to partisan surprise corresponding to Hall and Soskice's three varieties of capitalism. In liberal market economies, forecasters expect the left to achieve jobless growth with virtually no cost to inflation. In Mediterranean market economies, forecasters expect the left to achieve deliver both higher output growth and lower unemployment but with higher inflation. And in coordinated market economies, forecasters expect the left to deliver lower growth, higher unemployment, and higher inflation.
    Keywords: political business cycle, varieties of capitalism, forecast data, opinion polls
    JEL: E32 E63 P16 P51
    Date: 2007–04
    URL: http://d.repec.org/n?u=RePEc:wes:weswpa:2007-003&r=for

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