nep-for New Economics Papers
on Forecasting
Issue of 2008‒04‒29
ten papers chosen by
Rob J Hyndman
Monash University

  1. Forecasting Inflation in China By Mehrotra , Aaron; Sánchez-Fung, José R.
  2. The dynamics of economics functions: modelling and forecasting the yield curve By Clive G. Bowsher; Roland Meeks
  3. Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System By George Atsalakis; Dimitrios Nezis; George Matalliotakis; Camelia Ioana Ucenic; Christos Skiadas
  4. Estimating fundamental cross-section dispersion from fixed event forecasts By Jonas Dovern; Ulrich Fritsche
  5. The Term Structure of Inflation Expectations By Chernov, Mikhail; Mueller, Philippe
  6. Predicting cycles in economic activity By Jane Haltmaier
  7. The Accuracy of Long-term Real Estate Valuations By Rainer Schulz; Markus Staiber; Martin Wersing; Axel Werwatz
  8. Oil and the U.S. macroeconomy: an update and a simple forecasting exercise By Kevin L. Kliesen
  9. A non-parametric method to nowcast the Euro Area IPI By Laurent Ferrara; Thomas Raffinot
  10. Interpreting long-horizon estimates in predictive regressions By Erik Hjalmarsson

  1. By: Mehrotra , Aaron (BOFIT); Sánchez-Fung, José R. (BOFIT)
    Abstract: This paper forecasts inflation in China over a 12-month horizon. The analysis runs 15 alternative models and finds that only those considering many predictors via a principal component display a better relative forecasting performance than the univariate benchmark.
    Keywords: inflation forecasting; data-rich environment; principal components; China
    JEL: C53 E31
    Date: 2008–04–21
  2. By: Clive G. Bowsher; Roland Meeks
    Abstract: The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions. The underlying, continuous economic function (or "signal") is a natural cubic spline whose dynamic evolution is driven by a cointegrated vector autoregression for the ordinates (or "y-values") at the knots of the spline. The natural cubic spline provides flexible cross-sectional fit and results in a linear, state space model. This FSN model achieves dimension reduction, provides a coherent description of the observed yield curve and its dynamics as the cross-sectional dimension N becomes large, and can feasibly be estimated and used for forecasting when N is large. The integration and cointegration properties of the model are derived. The FSN models are then applied to forecasting 36-dimensional yield curves for US Treasury bonds at the one month ahead horizon. The method consistently outperforms the Diebold and Li (2006) and random walk forecasts on the basis of both mean square forecast error criteria and economically relevant loss functions derived from the realised profits of pairs trading algorithms. The analysis also highlights in a concrete setting the dangers of attempts to infer the relative economic value of model forecasts on the basis of their associated mean square forecast errors.
    Keywords: Time-series analysis ; Forecasting ; Mathematical models ; Macroeconomics - Econometric models
    Date: 2008
  3. By: George Atsalakis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); Dimitrios Nezis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); George Matalliotakis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); Camelia Ioana Ucenic (University of Crete - Technical University Cluj Napoca); Christos Skiadas (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE)
    Abstract: Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS. The model predicts the yearly mortality in a one step ahead prediction scheme. The method of trial and error was used in order to decide the type of membership function that describe better the model and provides the minimum error. The output of the models is the next year¢s mortality. The results were presented and compared based on three different kinds of errors: RMSE, MAE, and MAPE. The ANFIS model gives good results for the case of two gbell membership functions and 500 epochs. Finally, the ANFIS model gives better results than the AR and ARMA model.
    Keywords: ANFIS, Forecasting, Mortality, Modeling.
    Date: 2007
  4. By: Jonas Dovern (The Kiel Institute for the World Economy (IfW)); Ulrich Fritsche (Department for Economics and Politics, University of Hamburg, and DIW Berlin)
    Abstract: A couple of recent papers have shifted the focus towards disagreement of professional forecasters. When dealing with survey data that is sampled at a frequency higher than annual and that includes only fixed event forecasts, e.g. expectation of average annual growth rates measures of disagreement across forecasters naturally are distorted by a component that mainly reflects the time varying forecast horizon. We use data from the Survey of Professional Forecasters, which reports both fixed event and fixed horizon forecasts, to evaluate different methods for extracting the ``fundamental'' component of disagreement. Based on the paper's results we suggest two methods to estimate dispersion measures from panels of fixed event forecasts: a moving average transformation of the underlying forecasts and estimation with constant forecast-horizon-effects. Both models are easy to handle and deliver equally well performing results, which show a surprisingly high correlation (up to 0.94) with the true dispersion.
    Keywords: survey data, dispersion, disagreement, fixed event forecasts
    JEL: C22 C32 E37
    Date: 2008–05
  5. By: Chernov, Mikhail; Mueller, Philippe
    Abstract: We use evidence from the term structure of inflation expectations implicit in the nominal yields and survey forecasts of inflation to address the question of whether or not monetary policy is effective. We construct a model that accommodates forecasts over multiple horizons from multiple surveys and Treasury yields by allowing for differences between risk-neutral, subjective, and objective probability measures. We extract private sector expectations of inflation from this model and establish that they are driven by inflation, real activity and one latent factor, which is correlated with survey forecasts. We show that the interest rate responds to this "survey" factor. The inflation premium and out-of-sample estimates of the inflation long-run mean and persistence suggest that monetary policy became effective over time. As an implication, our model outperforms a standard macro-finance model in inflation and yield forecasting.
    Keywords: inflation; macro-finance term structure model; monetary policy; survey forecasts
    JEL: C50 E52 G12
    Date: 2008–04
  6. By: Jane Haltmaier
    Abstract: Predicting cycles in economic activity is one of the more challenging but important aspects of economic forecasting. This paper reports the results from estimation of binary probit models that predict the probability of an economy being in a recession using a variety of financial and real activity indicators. The models are estimated for eight countries, both individually and using a panel regression. Although the success of the models varies, they are all able to identify a significant number of recessionary periods correctly.
    Date: 2008
  7. By: Rainer Schulz; Markus Staiber; Martin Wersing; Axel Werwatz
    Abstract: By using a unique data set of single-family house transactions, we examine the accuracy of the cost and sales comparison approach over different forecast horizons. We find that sales comparison values provide better long-term forecasts than cost values if the economic loss function is symmetric. A weighted average of both sales comparison value and cost value can reduce this loss even further. If the economic loss function is asymmetric, however, cost values might provide better long-term forecasts.
    Keywords: prediction accuracy, mortgage underwriting, risk management
    JEL: C52 C53
    Date: 2008–02
  8. By: Kevin L. Kliesen
    Abstract: Recently, some analysts and economists had warned that the U.S. economy faces a much higher risk of falling into a recession should the price of oil rise to $100 per barrel or more. In February 2008, spot crude oil prices closed above $100 per barrel for the first time ever, and they have since climbed even further. Meanwhile, according to some surveys of economists, there is a high probability that a recession in the United States began in late 2007 or early 2008. Although the findings in this paper are consistent with the view that the U.S. economy has become much less sensitive to large changes in oil prices, a simple forecasting exercise reveals that a permanent increase in the price of crude oil to $150-per barrel-by the end of 2008 would have a significant negative effect on the growth rate of real GDP in the short run. However, the exercise also predicts such an increase in oil prices would have minimal effect on future inflation.
    Keywords: Petroleum products - Prices ; Economic conditions
    Date: 2008
  9. By: Laurent Ferrara (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, DGEI-DAMEP - Banque de France); Thomas Raffinot (CPR-Asset Management - CPR Asset Management)
    Abstract: Non-parametric methods have been empirically proved to be of great interest in the statistical literature in order to forecast stationary time series, but very few applications have been proposed in the econometrics literature. In this paper, our aim is to test whether non-parametric statistical procedures based on a Kernel method can improve classical linear models in order to nowcast the Euro area manufacturing industrial production index (IPI) by using business surveys released by the European Commission. Moreover, we consider the methodology based on bootstrap replications to estimate the confidence interval of the nowcasts.
    Keywords: Non-parametric, Kernel, nowcasting, bootstrap, Euro area IPI.
    Date: 2008–04
  10. By: Erik Hjalmarsson
    Abstract: This paper analyzes the asymptotic properties of long-horizon estimators under both the null hypothesis and an alternative of predictability. Asymptotically, under the null of no predictability, the long-run estimator is an increasing deterministic function of the short-run estimate and the forecasting horizon. Under the alternative of predictability, the conditional distribution of the long-run estimator, given the short-run estimate, is no longer degenerate and the expected pattern of coefficient estimates across horizons differs from that under the null. Importantly, however, under the alternative, highly endogenous regressors, such as the dividend-price ratio, tend to deviate much less than exogenous regressors, such as the short interest rate, from the pattern expected under the null, making it more difficult to distinguish between the null and the alternative.
    Date: 2008

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