nep-for New Economics Papers
on Forecasting
Issue of 2011‒05‒14
twelve papers chosen by
Rob J Hyndman
Monash University

  1. Real-time Forecasts of Economic Activity for Latin American Economies By Rafael Romeu; Troy Matheson; Philip Liu
  2. A comparison of forecasting procedures for macroeconomic series: the contribution of structural break models By BAUWENS, Luc; KOOP, Gary; KOROBILIS, Dimitris; ROMBOUTS, Jeroen V. K.
  3. Financial Conditions Indexes for the United States and Euro Area By Troy Matheson
  4. Identifying Fiscal Policy Transmission in Stochastic Debt Forecasts By Rafael Romeu; Kei Kawakami
  5. Evaluating Individual and Mean Non-Replicable Forecasts By Chia-Lin Chang; Philip Hans Franses; Michael McAleer
  6. Communicational Bias in Monetary Policy: Can Words Forecast Deeds? By Pablo Pincheira; Mauricio Calani
  7. Multi-period credit default prediction with time-varying covariates By Orth, Walter
  8. Toward Inflation Targeting in Sri Lanka By Shanaka J. Peiris; Rahul Anand; Ding Ding
  9. Measurement, Monitoring, and Forecasting of Consumer Credit Default Risk - An Indicator Approach Based on Individual Payment Histories By Alexandra Schwarz
  10. Developing a short-term comparative optimization forecasting model for operational units’ strategic planning By Filippou, Miltiades; Zervopoulos, Panagiotis
  11. Rational vs. Professional Forecasts By João Valle e Azevedo; João Tovar Jalles
  12. A Dynamic Macroeconometric Model of Pakistan’s Economy By Muhammad Arshad Khan; Musleh ud Din

  1. By: Rafael Romeu; Troy Matheson; Philip Liu
    Abstract: Macroeconomic policy decisions in real-time are based the assessment of current and future economic conditions. These assessments are made difficult by the presence of incomplete and noisy data. The problem is more acute for emerging market economies, where most economic data are released infrequently with a (sometimes substantial) lag. This paper evaluates "nowcasts" and forecasts of real GDP growth using five alternative models for ten Latin American countries. The results indicate that the flow of monthly data helps to improve forecast accuracy, and the dynamic factor model consistently produces more accurate nowcasts and forecasts relative to other model specifications, across most of the countries we consider.
    Keywords: Cross country analysis , Data quality assessment framework , Economic forecasting , Economic growth , Forecasting models , Latin America ,
    Date: 2011–04–29
  2. By: BAUWENS, Luc (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium); KOOP, Gary (University of Strathclyde, U.K); KOROBILIS, Dimitris (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium); ROMBOUTS, Jeroen V. K. (Institute of Applied Economics at HEC Montréal, CIRANO, CIRPEE, Canada; Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium.)
    Abstract: This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.
    Keywords: forecasting, change-points, Markov switching, Bayesian inference
    JEL: C11 C22 C53
    Date: 2010–12–01
  3. By: Troy Matheson
    Abstract: Financial conditions indexes are developed for the United States and euro area using a wide range of financial indicators and a dynamic factor model. The financial conditions indexes are shown to be useful for forecasting economic activity and have good revision properties.
    Keywords: Economic conditions , Economic forecasting , Euro Area , Forecasting models , United States ,
    Date: 2011–04–27
  4. By: Rafael Romeu; Kei Kawakami
    Abstract: A stochastic debt forecasting framework is presented where projected debt distributions reflect both the joint realization of the fiscal policy reaction to contemporaneous stochastic macroeconomic projections, and also the second-round effects of fiscal policy on macroeconomic projections. The forecasting framework thus reflects the impact of the primary balance on the forecast of macro aggregates. Previously-developed forecasting algorithms that do not incorporate these second-round effects are shown to have systematic forecast errors. Evidence suggests that the second-round effects have statistically and economically significant impacts on the direction and dispersion of the debt-to-GDP forecasts. For example, a positive structural primary balance shock lowers the domestic real interest rate, in turn raising GDP and lowering the median debt-to-GDP projection by an additional 10 percent of GDP in the medium term relative to prior forecasting algorithms. In addition, the framework employs a new long-term (five decade) data base and accounts for parameter uncertainty, and for potentially non-normally distributed shocks.
    Date: 2011–05–05
  5. By: Chia-Lin Chang (Department of Applied Economics, Department of Finance, National Chung Hsing University); Philip Hans Franses (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam); Michael McAleer (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, Complutense University of Madrid, and Institute of Economic Research, Kyoto University)
    Abstract: Macroeconomic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates expert intuition, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qualities of individual and means of non-replicable forecasts. One part of the methodology seeks to retrieve a replicable component from the non-replicable forecasts, and compares this component against the actual data. A second part modifies the estimation routine due to the assumption that the difference between a replicable and a non-replicable forecast involves measurement error. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the methodological approach using both individuals and mean forecasts.
    Keywords: Individual forecasts, mean forecasts, efficient estimation, generated regressors, replicable forecasts, non-replicable forecasts, expert intuition.
    JEL: C53 C22 E27 E37
    Date: 2011–05
  6. By: Pablo Pincheira; Mauricio Calani
    Abstract: Communication with the public is an ever-growing practice among central banks and complements their decisions of interest rate setting. In this paper we examine one feature of the communicational practice of the Central Bank of Chile which summarizes the assessment of the Board about the most likely future of monetary policy. We show that this assessment, which is called communicational bias or simply c-bias, contains valuable information regarding the future stance of monetary policy. We do this by comparing, against several benchmarks, the c-bias ability to correctly forecast the direction of monetary policy rates. Our results are consistent with the hypothesis that the Central Bank of Chile has (in our sample period) matched words and deeds. In fact, the c-bias is a more accurate predictor than two versions of random walks and than a uniformly-distributed random variable. It also outperforms, at some horizons, the predictive ability of a discrete Taylor-rule-type model that uses persistence, output gap and inflation-deviation-from-target as arguments. Furthermore, the c-bias is more accurate than survey-based forecasts at several forecasting horizons. We also show that the c-bias can provide information to improve monetary policy rate forecasts based on the forward rate curve.
    Date: 2011–02–28
  7. By: Orth, Walter
    Abstract: In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock market variables. If the prediction horizon covers multiple periods, this leads to the problem that the future evolution of these covariates is unknown. Consequently, some authors have proposed a framework that augments the prediction problem by covariate forecasting models. In this paper, we present simple alternatives for multi-period prediction that avoid the burden to specify and estimate a model for the covariate processes. In an application to North American public firms, we show that the proposed models deliver high out-of-sample predictive accuracy. --
    Keywords: credit default,multi-period predictions,hazard models,panel data,out-of-sample tests
    JEL: C41 C53 G32 G33
    Date: 2011
  8. By: Shanaka J. Peiris; Rahul Anand; Ding Ding
    Abstract: This paper develops a practical model-based forecasting and policy analysis system (FPAS) to support a transition to an inflation forecast targeting regime in Sri Lanka. The FPAS model provides a relatively good forecast for inflation and a framework to evaluate policy trade-offs. The model simulations suggest that an open-economy inflation targeting rule can reduce macroeconomic volatility and anchor inflationary expectations given the size and type of shocks faced by the economy. Sri Lanka could aim to target a broad inflation range initially due to its susceptibility supply-side shocks while enhancing exchange rate flexibility and strengthening the effectiveness of monetary policy in the transition to an inflation forecast targeting regime.
    Keywords: Central banks , Forecasting models , Inflation targeting , Monetary policy , Sri Lanka ,
    Date: 2011–04–13
  9. By: Alexandra Schwarz (German Institute for International Educational Research, Frankfurt am Main, Germany)
    Abstract: The statistical techniques which cover the process of modeling and evaluating consumer credit risk have become widely accepted instruments in risk management. In contrast, we find only few and vague statements on how to define the default event, i. e. on the concrete circumstances that lead to the decision of identifying a certain credit as defaulted. Based on a unique data set of individual payment histories this paper proposes a definition of default which is based on the time due amounts are outstanding and the resulting profitability of the receivables portfolio. Furthermore, to assess the individual payment performance during the credit period, indicators for monitoring and forecasting default events are derived. The empirical results show that these indicators generate valuable information which can be used by the creditor to improve his credit and collection policy and hence, to improve cash flows and reduce bad debt loss.
    Keywords: Credit Risk Analysis, Credit Default, Risk Management, Accounts Receivable Management, Performance Measurement
    JEL: C44 G32 M21
    Date: 2011–04
  10. By: Filippou, Miltiades; Zervopoulos, Panagiotis
    Abstract: Data drain for peer active units operating in the same sector is a major factor that prevents policy makers from developing flawless strategic plans for their organisation. This study introduces a hybrid model that incorporates a purely deterministic method, Data Envelopment Analysis (DEA), and a semi-parametric technique, Artificial Neural Networks (ANNs), to provide a strategic planning tool for efficiency optimization applicable to short-term lag of data availability. For consecutive time instances, t and t+1, the developed DEANN model returns optimum “regression-type” input and output levels for every sample operational unit, even for the fully efficient ones, that may decide to alter the levels of the efficiency determinants, respecting the t-time efficiency frontier.
    Keywords: Forecasting; Optimization; Efficiency; Data Envelopment Analysis (DEA); Artificial Neural Networks (ANN); Adaptive Techniques
    JEL: C53 C14 C45
    Date: 2011–04–20
  11. By: João Valle e Azevedo; João Tovar Jalles
    Abstract: We compare theoretical and empirical forecasts computed by rational agents living in a model economy to those produced by professional forecasters. We focus on the variance of the prediction errors as a function of the forecast horizon and analyze the speed with which it converges to a constant (which can be seen as a measure of the speed of convergence of the economy to the steady state). We look at a standard sticky-prices-wages model, concluding that it delivers a strong theoretical forecastability of the variables under scrutiny, at odds with the data (professional forecasts). The flexible prices-wages version delivers a forecastability closer to the data and performs relatively better empirically (with actual data), but mainly because forecasts deviate little from the unconditional mean. These results can be interpreted in at least two ways: first, actual deviations from the steady-state are not persistent, in which case the implications of the specific formulation of nominal rigidities for short-run dynamics are unrealistic; second, and still looking through the lens of a model, exogenous (or unmodelled) steady-state shifts attributable to, e.g., changes in monetary-policy, taxation, regulation or in the growth of the technological frontier, occur in such a way as to strongly limit the performance of professional forecasters.  
    JEL: C32 C53 C68 E12 E13 E17
    Date: 2011
  12. By: Muhammad Arshad Khan (Pakistan Institute of Development Economics, Islamabad.); Musleh ud Din (Pakistan Institute of Development Economics, Islamabad.)
    Abstract: In this study, an attempt has been made of develop a dynamic macroeconometric model of Pakistan’s economy to examine the behaviour of major macroeconomic variables such as output, consumption, investment, government expenditure, money, interest rates, prices, exports, and imports. The model consists of 21 equations, of which 13 are behavioural and the rest are identities. The Engle-Granger two-step cointegration procedure is used to derive the long-run and short -run elasticities for the period 1972-2009. The test of significance of each estimated equation seems to validate the model. The estimated long-run parameters are used to perform simulation experiments to determine the model’s ability to track historical data and to assess the behaviour of the key macroeconomic variables in response to the changes in selected exogenous variables. The results indicate that the majority of macroeconomic variables follow an increasing trend over the period of simulation, 2009-2013.
    Keywords: Macroeconometric Model; Pakistan Economy, Cointegration, Forecasting
    JEL: C20 C53 E1 E6 O5 R10
    Date: 2011

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