nep-for New Economics Papers
on Forecasting
Issue of 2013‒01‒26
ten papers chosen by
Rob J Hyndman
Monash University

  1. Forecasting regional growth in Germany: A panel approach using business survey data By Wenzel, Lars
  2. Short-Term Forecasting of Inflation in Bangladesh with Seasonal ARIMA Processes By Akhter, Tahsina
  3. Has the Basel Accord Improved Risk Management During the Global Financial Crisis? By Michael McAleer; Juan-Ángel Jiménez-Martín; Teodosio Pérez Amaral
  4. Behavioral Learning Equilibria By Cars Hommes; Mei Zhu
  5. Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns By Gürtler, Marc; Rauh, Ronald
  6. Measuring Disagreement in Qualitative Survey Data By Frieder Mokinski; Xuguang Sheng; Jingyun Yang
  7. Behavioral Heterogeneity in U.S. Inflation Dynamics By Adriana Cornea; Cars Hommes; Domenico Massaro
  8. A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns By René Garcia; Daniel Mantilla-Garcia; Lionel Martellini
  9. Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series By Nalan Basturk; Cem Cakmakli; Pinar Ceyhan; Herman K. van Dijk
  10. Prediction Markets in the Laboratory By Cary Deck; David Porter

  1. By: Wenzel, Lars
    Abstract: This paper is a first attempt to construct quantitative forecasts for regional growth in Germany using business survey data (BSD) from the German chambers of commerce. A panel approach is used to model the growth rates of the Bundesländer from the year 2000 onwards. The proposed model does well in explaining regional growth and the coefficients on the BSD are relatively stable. Results suggest that an indicator that is 10 points higher reflects growth rates that are 0.3-0.4 percentage points higher, while a 10 point increase from the previous year suggests an increase in growth by 0.25 percentage points. Fixed effects are found to play a negligible role. The BSD provides additional information on regional growth and outperforms the benchmark without BSD by up to 14 per cent for the full time period. For the period from 2000 to 2007 this value is as much as 20 per cent. However, for the time period from 2008 onwards, BSD does not provide significant information content over the benchmark. This reflects several shortcomings of the BSD, which nonetheless appears a valuable source of information in forecasting regional growth. --
    Date: 2013
    URL: http://d.repec.org/n?u=RePEc:zbw:hwwirp:133&r=for
  2. By: Akhter, Tahsina
    Abstract: The purpose of this study is to forecast the short-term inflation rate of Bangladesh using the monthly Consumer Price Index (CPI) from January 2000 to December 2012. To do so, the study employed the Seasonal Auto-regressive Integrated Moving Average (SARIMA) models proposed by Box, Jenkins, and Reinsel (1994). CUSUM, Quandt likelihood ratio (QLR) and Chow test have been utilized to identify the structural breaks over the sample periods and all three tests suggested that the structural breaks in CPI series of Bangladesh are in the month of February 2007 and September 2009. Hence, the study truncated the series and using CPI data from September 2009 to December 2012, the ARIMA(1,1,1)(1,0,1)12 models were estimated and forecasted. The forecasted result suggests an increasing pattern and high rates of inflation over the forecasted period 2013. Therefore, the study recommends that Bangladesh Bank should come forward with more appropriate economic and monetary policies in order to combat such increase inflation in 2013.
    Keywords: Inflation; Forecasting; SARIMA; Bangladesh
    JEL: E31 E17 C22
    Date: 2013–01–10
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:43729&r=for
  3. By: Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam.); Juan-Ángel Jiménez-Martín (Departamento de Economía Cuantitativa (Department of Quantitative Economics), Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad Complutense de Madrid); Teodosio Pérez Amaral (Departamento de Economía Cuantitativa (Department of Quantitative Economics), Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad Complutense de Madrid)
    Abstract: The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. In this paper we define risk management in terms of choosing from a variety of risk models, and discuss the selection of optimal risk models. A new approach to model selection for predicting VaR is proposed, consisting of combining alternative risk models, and we compare conservative and aggressive strategies for choosing between VaR models. We then examine how different risk management strategies performed during the 2008-09 global financial crisis. These issues are illustrated using Standard and Poor’s 500 Composite Index.
    Keywords: Value-at-Risk (VaR), daily capital charges, violation penalties, optimizing strategy, risk forecasts, aggressive or conservative risk management strategies, Basel Accord, global financial crisis.
    JEL: G32 G11 G17 C53 C22
    Date: 2012–10
    URL: http://d.repec.org/n?u=RePEc:ucm:doicae:1226&r=for
  4. By: Cars Hommes (University of Amsterdam); Mei Zhu (Shanghai University of Finance and Economics)
    Abstract: We propose behavioral learning equilibria as a plausible explanation of coordination of individual expectations and aggregate phenomena such as excess volatility in stock prices and high persistence in inflation. Boundedly rational agents use a simple univariate linear forecasting rule and correctly forecast the unconditional sample mean and first-order sample autocorrelation. In the long run, agents learn the best univariate linear forecasting rule, without fully recognizing the structure of the economy. The simplicity of behavioral learning equilibria makes coordination of individual expectations on such an aggregate outcome more likely. In a first application, an asset pricing model with AR(1) dividends, a unique behavioral learning equilibrium exists characterized by high persistence and excess volatility, and it is stable under learning. In a second application, the New Keynesian Phillips curve, multiple equilibria co-exist, learning exhibits path dep endence and inflation may switch between low and high persistence regimes.
    Keywords: Bounded rationality; Stochastic consistent expectations equilibrium; Adaptive learning; Excess volatility; Inflation persistence
    JEL: E30 C62 D83 D84
    Date: 2013–01–14
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20130014&r=for
  5. By: Gürtler, Marc; Rauh, Ronald
    Abstract: In this paper we analyze a multivariate non-stationary regression model empirically. With the knowledge about unconditional heteroscedasticty of financial returns, based on univariate studies and a congruent paradigm in Gürtler and Rauh (2009), we test for a time-varying covariance structure firstly. Based on these results, a central component of our non-stationary model is a kernel regression for pairwise covariances and the covariance matrix. Residual terms are fitted with an asymmetric Pearson type VII distribution. In an extensive study we estimate the linear dependence of a broad portfolio of equities and fixed income securities (including credit and currency risks) and fit the whole approach to provide distributional forecasts. Our evaluations verify a reasonable approximation and a satisfactory forecasting quality with an out performance against a traditional risk model. --
    Keywords: heteroscedasticity,non-stationarity,nonparametric regression,volatility,covariance matrix,innovation modeling,asymmetric heavy-tails,multivariate distributional forecast,empirical studies
    JEL: C14 C5
    Date: 2013
    URL: http://d.repec.org/n?u=RePEc:zbw:tbsifw:if43v1&r=for
  6. By: Frieder Mokinski; Xuguang Sheng; Jingyun Yang
    Abstract: To measure disagreement among respondents in qualitative survey data, we propose new methods applicable to both univariate and multivariate comparisons. Based on prior work, our first measure quantifies the level of disagreement in predictions of a single variable. Our second method constructs an index of overall disagreement from a dynamic factor model across several variables. Using directional forecasts from the Centre for European Economic Research Financial Market Survey, we find that our measures yield levels of disagreement consistent with point forecasts from the European Central Bank's Survey of Professional Forecasters. To illustrate usefulness, we explore the source and predictive power of forecast disagreement.
    Date: 2013
    URL: http://d.repec.org/n?u=RePEc:amu:wpaper:2013-04&r=for
  7. By: Adriana Cornea (University of Exeter); Cars Hommes (University of Amsterdam); Domenico Massaro (University of Amsterdam)
    Abstract: In this paper we develop and estimate a behavioral model of inflation dynamics with monopolistic competition, staggered price setting and heterogeneous firms. In our stylized framework there are two groups of price setters, fundamentalists and naive. Fundamentalists are forward-looking in the sense that they believe in a present-value relationship between inflation and real marginal costs, while naive are backward-looking, using the simplest rule of thumb, naive expectations, to forecast future inflation. Agents are allowed to switch between these different forecasting strategies conditional on their recent relative forecasting performance. The estimation results support behavioral heterogeneity and the evolutionary switching mechanism. We show that there is substantial time variation in the weights of forward-looking and backward-looking behavior. Although on average the majority of firms use the simple backward-looking rule, the market has phases in which it is dominated by either the fundamentalists or the naive agents.
    Keywords: Inflation; Phillips Curve; Heterogeneous Expectations; Evolutionary Selection
    JEL: E31 E52 C22
    Date: 2013–01–14
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20130015&r=for
  8. By: René Garcia; Daniel Mantilla-Garcia; Lionel Martellini
    Abstract: In this paper, we formally show that the cross-sectional variance of stock returns is a consistent and asymptotically efficient estimator for aggregate idiosyncratic volatility. This measure has two key advantages: it is model-free and observable at any frequency. Previous approaches have used monthly model based measures constructed from time series of daily returns. The newly proposed cross-sectional volatility measure is a strong predictor for future returns on the aggregate stock market at the daily frequency. Using the cross-section of size and book-to-market portfolios, we show that the portfolios’ exposures to the aggregate idiosyncratic volatility risk predict the cross-section of expected returns. <P>
    Keywords: Aggregate idiosyncratic volatility, cross-sectional dispersion, prediction of market returns,
    Date: 2013–01–01
    URL: http://d.repec.org/n?u=RePEc:cir:cirwor:2013s-01&r=for
  9. By: Nalan Basturk (Erasmus University Rotterdam); Cem Cakmakli (University of Amsterdam); Pinar Ceyhan (Erasmus University Rotterdam); Herman K. van Dijk (Erasmus University Rotterdam, and VU University Amsterdam)
    Abstract: Changing time series properties of US inflation and economic activity are analyzed within a class of extended Phillips Curve (PC) models. First, the misspecification effects of mechanical removal of low frequency movements of these series on posterior inference of a basic PC model are analyzed using a Bayesian simulation based approach. Next, structural time series models that describe changing patterns in low and high frequencies and backward as well as forward inflation expectation mechanisms are incorporated in the class of extended PC models. Empirical results indicate that the proposed models compare favorably with existing Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and predictive performance. Weak identification and dynamic persistence appear less important when time varying dynamics of high and low frequencies are carefully modeled. Modeling inflation expectations using survey data and adding level shifts and stochastic volatility improves substantially in sample fit and out of sample predictions. No evidence is found of a long run stable cointegration relation between US inflation and marginal costs. Tails of the complete predictive distributions indicate an increase in the probability of disinflation in recent years.
    Keywords: New Keynesian Phillips curve; unobserved components; level shifts; inflation expectations
    JEL: C11 C32 E31 E37
    Date: 2013–01–10
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20130011&r=for
  10. By: Cary Deck (University of Arkansas & Chapman University); David Porter (Economic Science Institute, Chapman University)
    Abstract: The idea that there is wisdom from the collective has been forcefully described in “The Wisdom of the Crowds” by James Surowiecki, who argues that the aggregation of information in groups results in better decisions than those that are afforded by any single member of the group. Markets, like opinion polls, are one mechanism for aggregating disparate pieces of information. The aggregation properties of prices were first noted by Hayek (1945) and were formally examined by Muth (1961). In particular, Hayek argues that market prices serve the purpose of sharing and coordinating local and personal knowledge, while Muth shows that markets do not waste information and that the current price contains all the information available from market participants.
    Date: 2013
    URL: http://d.repec.org/n?u=RePEc:chu:wpaper:13-05&r=for

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