nep-for New Economics Papers
on Forecasting
Issue of 2006‒11‒25
fifteen papers chosen by
Rob J Hyndman
Monash University

  1. Averaging forecasts from VARs with uncertain instabilities By Todd E. Clark; Michael W. McCracken
  2. Forecasting with the yield curve; level, slope, and output 1875-1997 By Michael D. Bordo; Joseph G. Haubrich
  3. An evaluation of inflation forecasts from surveys using real-time data By Dean Croushore
  4. The Role of Seasonality and Monetary Policy in Inflation Forecasting By Francis Y. Kumah
  5. Measures of Underlying Inflation in the Euro Area: Assessment and Role for Informing Monetary Policy By Emil Stavrev
  6. Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach By Vitek, Francis
  7. Does Consumer Confidence Forecast Household Spending? The Euro Area Case By DION, David Pascal
  8. Who Gains from the Demographic Dividend? Forecasting Income by Age By Sang Hyop Lee; Andrew Mason
  9. "Population Forecasts, Fiscal Policy, and Risk" By Shripad Tuljapurkar
  10. Traffic Accessibility and the Effect on Firms and Population in 99 Austrian Regions By Polasek, Wolfgang; Schwarzbauer, Wolfgang
  11. Using ARIMA Forecasts to Explore the Efficiency of the Forward Reichsmark Market: Austria-Hungary, 1876-1914 By Komlos, John; Flandreau, Marc
  12. The Aggregate Labor Market Effects of the Swedish Knowledge Lift Program By James Albrecht; Gerard J. van den Berg; Susan Vroman
  13. The political economy of unemployment and threshold effects. A nonlinear time series approach. By Ruthira Naraidoo; Patrick Minford; Ioannis A. Venetis
  14. Understanding and Comparing Factor-Based Forecasts By Boivin, Jean; Ng, Serena
  15. A Technical Note on a Direct Estimate of the Significance of Bias in Forecasts. By Albert E. DePrince

  1. By: Todd E. Clark; Michael W. McCracken
    Abstract: A body of recent work suggests commonly–used VAR models of output, inflation, and interest rates may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. These methods include using different approaches to lag selection, different observation windows for estimation, (over-) differencing, intercept correction, stochastically time–varying parameters, break dating, discounted least squares, Bayesian shrinkage, and detrending of inflation and interest rates. Although each individual method could be useful, the uncertainty inherent in any single representation of instability could mean that combining forecasts from the entire range of VAR estimates will further improve forecast accuracy. Focusing on models of U.S. output, prices, and interest rates, this paper examines the effectiveness of combination in improving VAR forecasts made with real–time data. The combinations include simple averages, medians, trimmed means, and a number of weighted combinations, based on: Bates-Granger regressions, factor model estimates, regressions involving just forecast quartiles, Bayesian model averaging, and predictive least squares–based weighting. Our goal is to identify those approaches that, in real time, yield the most accurate forecasts of these variables. We use forecasts from simple univariate time series models and the Survey of Professional Forecasters as benchmarks.
    Keywords: Economic forecasting ; Vector autoregression
    Date: 2006
  2. By: Michael D. Bordo; Joseph G. Haubrich
    Abstract: Using the yield curve helps forecast real growth over the period 1875 to 1997. Using both the level and slope of the curve improves forecasts more than using either variable alone. Forecast performance changes over time and depends somewhat on whether recursive or rolling out of sample regressions are used.
    Keywords: Interest rates ; Gross national product
    Date: 2006
  3. By: Dean Croushore
    Abstract: This paper carries out the task of evaluating inflation forecasts from the Livingston Survey and the Survey of Professional Forecasters, using the real-time data set for macroeconomists as a source of real-time data. The author examines the magnitude and patterns of revisions to the inflation rate based on the output price index and describe what data to use as “actuals” in evaluating forecasts. The author then runs tests on the forecasts from the surveys to see how good they are, using a variety of actuals. The author finds that much of the empirical work from 20 years ago was a misleading guide to the quality of forecasts because of unique events during the earlier sample period. Repeating that empirical work over a longer sample period shows no bias or other problems in the forecasts. The use of real-time data also matters for some key tests on some variables. If a forecaster had used the empirical results from the late 1970s and early 1980s to adjust survey forecasts of inflation, forecast errors would have increased substantially.
    Keywords: Inflation (Finance)
    Date: 2006
  4. By: Francis Y. Kumah
    Abstract: Adequate modeling of the seasonal structure of consumer prices is essential for inflation forecasting. This paper suggests a new econometric approach for jointly determining inflation forecasts and monetary policy stances, particularly where seasonal fluctuations of economic activity and prices are pronounced. In an application of the framework, the paper characterizes and investigates the stability of the seasonal pattern of consumer prices in the Kyrgyz Republic and estimates optimal money growth and implied exchange rate paths along with a jointly determined inflation forecast. The approach uses two broad specifications of an augmented error-correction model-with and without seasonal components. Findings from the paper confirm empirical superiority (in terms of information content and contributions to policymaking) of augmented error-correction models of inflation over single-equation, Box-Jenkins-type general autoregressive seasonal models. Simulations of the estimated errorcorrection models yield optimal monetary policy paths for achieving inflation targets and demonstrate the empirical significance of seasonality and monetary policy in inflation forecasting.
    Keywords: Inflation forecasting , seasonal unit roots , monetary policy stance , erroro-correction models and VAR , Monetary policy , Inflation , Forecasting models ,
    Date: 2006–07–28
  5. By: Emil Stavrev
    Abstract: The paper evaluates the 24-month ahead inflation forecasting performance of various indicators of underlying inflation and structural models. The inflation forecast errors resulting from model misspecification are larger than the errors resulting from forecasting of exogenous variables. Also, measures derived using the generalized dynamic factor model (GDFM) overperform other measures over the monetary policy horizon and are leading indicators of headline inflation. Trimmed means, although weaker than GDFM indicators, have good forecasting performance, while indicators by permanent exclusion underperform but provide useful information about short-term dynamics. The forecasting performance of theoretically-founded models that relate monetary aggregates, the output gap, and inflation improves with the time horizon but generally falls short of that of the GDFM. A composite measure of underlying inflation, derived by averaging the statistical indicators and the model-based estimates, improves forecast accuracy by eliminating bias and offers valuable insight about the distribution of risks.
    Keywords: Underlying inflation , forecast evaluation , composite indicators , forecast risk assessment , Inflation , Euro area , Monetary policy , Economic models ,
    Date: 2006–09–11
  6. By: Vitek, Francis
    Abstract: This paper develops and estimates a dynamic stochastic general equilibrium model of a small open economy which provides a quantitative description of the monetary transmission mechanism, yields a mutually consistent set of indicators of inflationary pressure together with confidence intervals, and facilitates the generation of relatively accurate forecasts. The model features short run nominal price and wage rigidities generated by monopolistic competition and staggered reoptimization in output and labour markets. The resultant inertia in inflation and persistence in output is enhanced with other features such as habit persistence in consumption and labour supply, adjustment costs in housing and capital investment, and variable capital utilization. Incomplete exchange rate pass through is generated by monopolistic competition and staggered reoptimization in the import market. Cyclical components are modeled by linearizing equilibrium conditions around a stationary deterministic steady state equilibrium which abstracts from long run balanced growth, while trend components are modeled as random walks while ensuring the existence of a well defined balanced growth path. Parameters and unobserved components are jointly estimated with a novel Bayesian full information maximum likelihood procedure, conditional on prior information concerning the values of parameters and trend components.
    Keywords: Stance of monetary policy; Small open economy; Dynamic stochastic general equilibrium model; Monetary transmission mechanism; Forecast performance evaluation
    JEL: C11 E52 F41 C13 F47 C32
    Date: 2006–06–11
  7. By: DION, David Pascal
    Abstract: The following analysis, based on error correction models, suggests that consumer confidence, together with traditional macroeconomic variables, contains a forecasting and explicative power on consumption. By including consumer confidence in a consumption function, consumer confidence releases a significant coefficient. Such a confidence-augmented consumption model provides good forecasting results.
    Keywords: Consumer confidence; consumption function; forecasting; consumer attitudes and behaviour; households
    JEL: D12 C52 D11 E27 E21 C53
    Date: 2006–11–22
  8. By: Sang Hyop Lee (Department of Economics, University of Hawaii at Manoa); Andrew Mason (Department of Economics, University of Hawaii at Manoa)
    Date: 2006
  9. By: Shripad Tuljapurkar
    Abstract: This paper describes how stochastic population forecasts are used to inform and analyze policies related to government spending on the elderly, mainly in the context of the industrialized nations. The paper first presents methods for making probabilistic forecasts of demographic rates, mortality, fertility, and immigration, and shows how these are combined to make stochastic forecasts of population number and composition, using forecasts of the U.S. population by way of illustration. Next, the paper discusses how demographic models and economic models can be combined into an integrated projection model of transfer systems such as social security. Finally, the paper shows how these integrated models describe various dimensions of policy-relevant risk, and discusses the nature and implications of risk in evaluating policy alternatives.
    Date: 2006–08
  10. By: Polasek, Wolfgang (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria); Schwarzbauer, Wolfgang (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)
    Abstract: In this paper we describe the EAR (regional economic accessibility) model to investigate the impact of the improvement of railroad infrastructure on regional GDP, population and firms growth in 99 Austrian regions. We evaluate the impact of four potential railroad infrastructure investment projects on the accessibility of Austrian regions, which is used to forecast future growth of these regions. Regional performance is measured by four variables, gross regional product, number of firms, population size, and employment. Eventually a ranking of these four projects is carried out for the first ten years of operation of the four potential investment projects. We show that the improvement of train accessibility has different impacts on regions with high and low overall performance.
    Keywords: Evaluation of infrastructure projects, Long-term regional forecasts, Accessibility and traffic analysis, Ranking
    JEL: R1 R41 L92 C21 C23
    Date: 2006–11
  11. By: Komlos, John; Flandreau, Marc
    Abstract: We explore the efficiency of the forward Reichsmark market in Vienna between 1876 and 1914. We estimate ARIMA models of the spot exchange rate in order to forecast the one-month-ahead spot rate. In turn we compare these forecasts to the contemporaneous forward rate, i.e., the market's forecast of the future spot rate. We find that shortly after the introduction of a shadow gold standard in the mid-1890s the forward rate became a considerably better predictor of the future spot rate than during the prior flexible exchange rate regime. Between 1907 and 1914 forecast errors were between a half and one-fourth of their pre-1896 level. This implies that the Austro-Hungarian Bank's policy of defending the gold value of the currency was successful in improving the efficiency of the foreign exchange market.
    Keywords: exchange rate; gold standard; ARIMA; efficiency
    JEL: F31 N23
    Date: 2006–11
  12. By: James Albrecht (Georgetown University, IFAU Uppsala, CESifo and IZA Bonn); Gerard J. van den Berg (Free University Amsterdam, IFAU Uppsala, CEPR, IFS and IZA Bonn); Susan Vroman (Georgetown University, IFAU Uppsala, CESifo and IZA Bonn)
    Abstract: The Swedish adult education program known as the Knowledge Lift (1997-2002) was unprecedented in its size and scope, aiming to raise the skill level of large numbers of lowskill workers. This paper evaluates the potential effects of this program on aggregate labor market outcomes. This is done by calibrating an equilibrium search model with heterogeneous worker skills using pre-program data and then forecasting the program impacts. We compare the forecasts to observed aggregate labor market outcomes after termination of the program.
    Keywords: job search, returns to education, program evaluation, wages, unemployment, Swedish labor market, calibration
    JEL: J21 J64 J31 J24 I21 C31
    Date: 2006–10
  13. By: Ruthira Naraidoo (Keele University, Centre for Economic Research and School of Economic and Management Studies); Patrick Minford (Cardiff Business School, Aberconway Building, Cardiff University); Ioannis A. Venetis (University of Patras, Department of Economics)
    Abstract: This paper develops a political economy model of multiple unemployment equilibria to provide a theory of an endogenous natural rate of unemployment using a nonlinear threshold model for a number of OECD countries. The theory here sees the natural rate and the associated path of unemployment as a reaction to shocks (mainly demand in nature) and the institutional structure of the economy. The channel through which these two forces feed on each other is a political economy process whereby voters with limited information on the natural rate react to shocks by demanding more or less social protection. The empirical results obtained confirm the existence of multiple and ``moving'' equilibria (``vicious'' and ``virtuous'' circles). The nonlinear model is compared with a linear version with the nonlinear framework always exhibiting superior in-sample fit and generally better out-of-sample predictive accuracy. The conclusion is that macroeconomics and supply side policies feed on each other via the political economy.
    Keywords: Equilibrium unemployment, political economy, threshold model, forecasting
    JEL: E24 E27 P16
    Date: 2006–10
  14. By: Boivin, Jean; Ng, Serena
    Abstract: Forecasting using "diffusion indices" has received a good deal of attention in recent years. The idea is to use the common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent to which the forecasts are influenced by (i) how the factors are estimated and/or (ii) how the forecasts are formulated. We find that for simple data-generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad. All five methods considered have rather similar properties, though some methods are better in long-horizon forecasts, especially when the number of time series observations is small. However, when the dynamic structure is unknown and for more complex dynamics and error structures such as the ones encountered in practice, one method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the common and idiosyncratic components separately, and it leaves the dynamics of the factors unspecified. By imposing fewer constraints, and having to estimate a smaller number of auxiliary parameters, the method appears to be less vulnerable to misspecification, leading to improved forecasts.
    JEL: G00 G0
    Date: 2005–05–18
  15. By: Albert E. DePrince
    Abstract: This paper provides a direct test for forecast bias using the Thiel equation. In this test the constant term is simply the difference between the mean of the forecast and the mean of the actual data. A simple data transformation leads to this specification of the constant term. The approach is expanded to include a function with additional independent variables where one is interested in the constant term being simply the difference of the means of the dependent and any one of the independent variables.
    Keywords: forecast bias, test for bias
    JEL: C2
    Date: 2006–03

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