nep-for New Economics Papers
on Forecasting
Issue of 2013‒12‒06
eleven papers chosen by
Rob J Hyndman
Monash University

  1. Do unobserved components models forecast inflation in Russia? By Bulat Gafarov
  2. On the prediction of corporate financial distress in the light of the financial crisis: empirical evidence from Greek listed firms By Evangelos C. Charalambakis
  3. An evaluation of simple forecasting model selection rules By Fildes, Robert; Petropoulos, Fotios
  4. DGSE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa By Rangan Gupta; Patrick Kanda; Mampho Modise; Alessia Paccagnini
  5. The Centre Matters for the Periphery of Europe: The Predictive Ability of a GZ-Type Spread for Economic Activity in Europe By Alfred V Guender; Bernard Tolan
  6. High-Frequency Real Economic Activity Indicator for Canada By Gitanjali Kumar
  7. How Well do Analysts Predict Stock Prices? Evidence from Russia By Henry Penikas; Proskurin S.
  8. Perceived Inflation Persistence By Monica Jain
  9. Coalition Formation in a Legislative Voting Game By Christiansen, N.; Georganas, S.; Kagel, J. H.
  10. Introducing time-changing economics into credit scoring By Maria Rocha Sousa; João Gama; Elísio Brandão
  11. Using the new products margin to predict the industry-level impact of trade reform By Timothy J. Kehoe; Jack Rossbach; Kim J. Ruhl

  1. By: Bulat Gafarov (Higher School of Economics (Moscow, Russia). Laboratory for Inflation Problems and Economic Growth Research.)
    Abstract: I apply the model with unobserved components and stochastic volatility (UC-SV) to forecast the Russian consumer price index. I extend the model which was previously suggested as a model for inflation forecasting in the USA to take into account a possible difference in model parameters and seasonal factor. Comparison of the out-of-sample forecasting performance of the linear AR model and the UC-SV model by mean squared error of prediction shows better results for the latter model. Relatively small absolute value of the standard error of the forecasts calculated by the UC-SV model makes it a reasonable candidate for a real time forecasting method for the Russian CPI.
    Keywords: Stochastic volatility, MCMC, Russia, CPI, forecasting.
    JEL: C53 E37
    Date: 2013
  2. By: Evangelos C. Charalambakis (Bank of Greece)
    Abstract: This paper evaluates the impact of accounting and market-driven information on the prediction of bankruptcy for Greek firms using the discrete hazard approach. The findings show that a hazard model that incorporates three accounting ratio components of Z-score and three market-driven variables is the most appropriate model for the prediction of corporate financial distress in Greece. This model outperforms a univariate model that uses the expected default frequency (EDF) derived from the Merton distance to default model, a multivariate model that is exclusively based on accounting variables, a model that combines EDF and accounting variables and a multivariate model that uses only market-driven variables. In-sample forecast accuracy tests confirm the main results. The out-of-sample evidence also suggests that the model yields the highest predictive ability during financial crisis when using data prior to the financial crisis.
    Keywords: financial distress; financial forecasting; hazard model; expected default frequency
    JEL: G13 G17 G33 C41
    Date: 2013–10
  3. By: Fildes, Robert; Petropoulos, Fotios
    Abstract: A major problem for many organisational forecasters is to choose the appropriate forecasting method for a large number of data series. Model selection aims to identify the best method of forecasting for an individual series within the data set. Various selection rules have been proposed in order to enhance forecasting accuracy. In theory, model selection is appealing, as no single extrapolation method is better than all others for all series in an organizational data set. However, empirical results have demonstrated limited effectiveness of these often complex rules. The current study explores the circumstances under which model selection is beneficial. Three measures are examined for characterising the data series, namely predictability (in terms of the relative performance of the random walk but also a method, theta, that performs well), trend and seasonality in the series. In addition, the attributes of the data set and the methods also affect selection performance, including the size of the pools of methods under consideration, the stability of methods’ performance and the correlation between methods. In order to assess the efficacy of model selection in the cases considered, simple selection rules are proposed, based on within-sample best fit or best forecasting performance for different forecast horizons. Individual (per series) selection is contrasted against the simpler approach (aggregate selection), where one method is applied to all data series. Moreover, simple combination of methods also provides an operational benchmark. The analysis shows that individual selection works best when specific sub-populations of data are considered (trended or seasonal series), but also when methods’ relative performance is stable over time or no method is dominant across the data series.
    Keywords: automatic model selection, comparative methods, extrapolative methods, combination, stability
    JEL: C13 C22
    Date: 2013–04
  4. By: Rangan Gupta; Patrick Kanda; Mampho Modise; Alessia Paccagnini
    Abstract: Inflation forecasts are a key ingredient for monetary policymaking - especially in an inflation targeting country such as South Africa. Generally, a typical Dynamic Stochastic General Equilibrium (DSGE) only includes a core set of variables. As such, other variables, e.g. such as alternative measures of inflation that might be of interest to policymakers, do not feature in the model. Given this, we implement a closed-economy New Keynesian DSGE model-based procedure which includes variables that do not explicitly appear in the model. We estimate such a model using an in-sample covering 1971Q2 to 1999Q4, and generate recursive forecasts over 2000Q1-2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables (both core and non-modeled) in comparison with forecasts reported by other models such as AR(1).
    Keywords: DSGE model, in ation, core variables, non-core variables
    JEL: C11 C32 C53 E27 E47
    Date: 2013–11
  5. By: Alfred V Guender (University of Canterbury); Bernard Tolan
    Abstract: This paper examines whether information from bond markets provides a reliable signal for future economic activity in Europe. It evaluates the marginal predictive content and economic significance of a risk-adjusted yield credit spread in five European countries from the early 1990s to the recent past. The inclusion of this bond yield spread improves markedly the goodness of fit of the forecasting equation for economic activity in countries on the European periphery. The within-sample forecasting ability of the GZ-spread is remarkable, both over the whole sample period and a sub-sample period marking the effective beginning of the Economic and Monetary Union of Europe in 1999. Its effect on economic activity is felt particularly during the 2007-12 Crisis period.
    JEL: E3 E4 G1
    Date: 2013–09–01
  6. By: Gitanjali Kumar
    Abstract: I construct a weekly measure of real economic activity in Canada. Based on the work of Aruoba et al. (2009), the indicator is extracted as an unobserved component underlying the co-movement of four monthly observed real macroeconomic variables - employment, manufacturing sales, retail sales and GDP. The indicator has a number of applications in macroeconomics and finance - it can be used to measure macroeconomic news, to quantify the impact of news on financial asset prices, to study exchange rate movements and as an input in nowcasting and forecasting exercises.
    Keywords: Business fluctuations and cycles; Econometric and statistical methods
    JEL: C38 E32
    Date: 2013
  7. By: Henry Penikas (National Research University Higher School of Economics (Moscow, Russia). International Laboratory of Decision Choice and Analysis); Proskurin S. (National Research University Higher School of Economics, Department of Finance)
    Abstract: In this research we found that 56.8% of expert recommendations on selling or buying stocks of Russian companies were profitable. We show that the recommendations being publically released have an impact on stock prices, hence market players are likely to follow the recommendations. There also no difference in an analyst’s gender and almost no difference in the day the recommen-dation was made
    Keywords: financial analyst, forecast
    JEL: G32
    Date: 2013
  8. By: Monica Jain
    Abstract: The Survey of Professional Forecasters (SPF) has had vast influence on research related to better understanding expectation formation and the behaviour of macroeconomic agents. Inflation expectations, in particular, have received a great deal of attention, since they play a crucial role in determining real interest rates, the expectations-augmented Phillips curve and monetary policy. One feature of the SPF that has surprisingly not been explored is the natural way in which it can be used to extract useful measures of inflation persistence. This paper presents a new measure of U.S. inflation persistence from the point of view of a professional forecaster, referred to as perceived inflation persistence. It is built via the implied autocorrelation function that follows from the estimates obtained using a forecaster-specific state-space model. Findings indicate that perceived inflation persistence has changed over time and that forecasters are more likely to view unexpected shocks to inflation as transitory, particularly since the mid-1990s. When compared to the autocorrelation function for actual inflation, forecasters react less to shocks than the actual inflation data would suggest, since they may engage in forecast smoothing.
    Keywords: Inflation and prices; Econometric and statistical methods
    JEL: E31 E37
    Date: 2013
  9. By: Christiansen, N.; Georganas, S.; Kagel, J. H.
    Abstract: We experimentally investigate the Jackson-Moselle (2002) model where legislators bargain over policy proposals and the allocation of private goods. Key comparative static predictions of the model hold as policy proposals shift in the predicted direction with private goods, with the variance in policy outcomes increasing as well. Private goods increase total welfare even after accounting for their cost and help secure legislative compromise. Coalition formations are better characterized by an efficient equal split between coalition partners than the stationary subgame perfect equilibrium prediction.
    Keywords: legislative bargaining; policy decisions; private goods; experiment
    Date: 2013
  10. By: Maria Rocha Sousa (School of Economics and Management, University of Porto); João Gama (LIAAD-INESC TEC; School of Economics and Management, University of Porto); Elísio Brandão (School of Economics and Management, University of Porto)
    Abstract: We propose a two-stage model for dealing with the temporal degradation of credit scoring models. First, we develop a model from a classical framework, with a static supervised learning setting and binary output. Then, we introduce the time-changing economic factors, using a regression between the macroeconomic data and the internal default in the portfolio. In so doing, the specific risk is captured from the bank internal database, and the movement of systemic risk is determined with the regression. This methodology produced motivating results in a 1-year horizon, for a portfolio of customers with credit cards in a financial institution operating in Brazil. We anticipate that it can be extended to other applications of risk assessment with great success. This methodology can be further improved if more information about the economic cycles is integrated in the forecasting of default.
    Keywords: risk assessment; credit scoring; temporal degradation; score adjustment; time-changing economics
    JEL: C5 C8
    Date: 2013–11
  11. By: Timothy J. Kehoe; Jack Rossbach; Kim J. Ruhl
    Abstract: This paper develops a methodology for predicting the impact of trade liberalization on exports by industry (3-digit ISIC) based on the pre-liberalization distribution of exports by product (5-digit SITC). Using the results of Kehoe and Ruhl (2013) that much of the growth in trade after trade liberalization is in products that are traded very little or not at all, we predict that industries with a higher share of exports generated by least traded products will experience more growth. Using our methodology, we develop predictions for industry-level changes in trade for the United States and Korea following the U.S.-Korea Free Trade Agreement (KORUS). As a test for our methodology, we show that it performs significantly better than the applied general equilibrium models originally used for the policy evaluation of the North American Free Trade Agreement (NAFTA).
    Keywords: Trade ; North American Free Trade Agreement ; Korea
    Date: 2013

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