nep-for New Economics Papers
on Forecasting
Issue of 2013‒07‒28
eight papers chosen by
Rob J Hyndman
Monash University

  1. Banks, Asset Management or Consultancies' Inflation Forecasts: is there a better forecaster out there? By Tito Nícias Teixeira da Silva Filho
  2. On the correlation between commodity and equity returns: implications for portfolio allocation By Marco Jacopo Lombardi
  3. A Fear Index to Predict Oil Futures Returns By Julien Chevallier; Benoît Sévi
  4. Are benefits from oil - stocks diversification gone? A new evidence from a dynamic copulas and high frequency data By Krenar Avdulaj; Jozef Barunik
  5. The Forward Exchange Rate Unbiasedness Hypothesis: A Single Break Unit Root and CointegrationAnalysis By Michael Mazur; Miguel Ramirez
  6. The Future of Global Poverty in a Multi-Speed World: New Estimates of Scale, Location and Cost By Peter Edward; Andy Sumner
  7. Macroeconomic Modelling of the Global Economy-Energy-Environment Nexus - An Overview of Recent Advancements of the Dynamic Simulation Model GINFORS By Mark Meyer; Martin Distelkamp; Gerd Ahlert; Prof. Dr. Bernd Meyer
  8. Overconfidence in Political Behavior By Pietro Ortoleva; Erik Snowberg

  1. By: Tito Nícias Teixeira da Silva Filho
    Abstract: The Focus Survey is a cunningly designed economic survey carried out by the Central Bank of Brazil. However, along its existence there have occasionally been some criticisms that its median forecast is “biased” due to allegedly strategic reasons. Although different groups of agents do have different strategic behaviours, one cannot take for granted that some groups predict differently from others. This paper tests if there are statistically significant differences in forecast accuracy between different groups of participants in the Focus Survey. Evidence shows some differences in forecasting ability among groups, but overall financial system forecasters have similar forecasting accuracy than consultancies.
    Date: 2013–07
  2. By: Marco Jacopo Lombardi
    Abstract: In the recent years several commentators hinted at an increase of the correlation between equity and commodity prices, and blamed investment in commodity-related products for this. First, this paper investigates such claims by looking at various measures of correlation. Next, we assess what are the implications of higher correlations between oil and equity prices for asset allocation. We develop a time-varying Bayesian Dynamic Conditional Correlation model for volatilities and correlations and find that joint modelling commodity and equity prices produces more accurate point and density forecasts, which lead to substantial benefits in portfolio allocation. This, however, comes at the price of higher portfolio volatility. Therefore, the popular view that commodities are to be included in one's portfolio as a hedging device is not grounded.
    Keywords: Commodity prices, equity prices, density forecasting, correlation, Bayesian DCC
    Date: 2013–07
  3. By: Julien Chevallier (Université Paris 8 (LED)); Benoît Sévi (Aix-Marseille Université (Aix-Marseille School of Economics), CNRS & EHESS)
    Abstract: This paper evaluates the predictability of WTI light sweet crude oil futures by using the variance risk premium, i.e. the difference between model-free measures of implied and realized volatilities. Additional regressors known for their ability to explain crude oil futures prices are also considered, capturing macroeconomic, financial and oil-specific influences. The results indicate that the explanatory power of the (negative) variance risk premium on oil excess returns is particularly strong (up to 25% for the adjusted Rsquared across our regressions). It complements other financial (e.g. default spread) and oil-specific (e.g. US oil stocks) factors highlighted in previous literature.
    Keywords: Oil Futures, Variance Risk Premium, Forecasting
    JEL: C32 G17 Q47
    Date: 2013–06
  4. By: Krenar Avdulaj; Jozef Barunik
    Abstract: Oil is widely perceived as a good diversification tool for stock markets. To fully understand the potential, we propose a new empirical methodology which combines generalized autoregressive score copula functions with high frequency data, and allows us to capture and forecast the conditional time-varying joint distribution of the oil -- stocks pair accurately. Our realized GARCH with time-varying copula yields statistically better forecasts of the dependence as well as quantiles of the distribution when compared to competing models. Using recently proposed conditional diversification benefits measure which take into account higher-order moments and nonlinear dependence, we document reducing benefits from diversification over the past ten years. Diversification benefits implied by our empirical model are moreover strongly varying over time. These findings have important implications for portfolio management.
    Date: 2013–07
  5. By: Michael Mazur; Miguel Ramirez (Department of Economics, Trinity College)
    Abstract: In an age of globalized finance, Forex market efficiency is particularly relevant as agents engage in arbitrage opportunities across international markets. This study tests the forward exchange rate unbiasedness hypothesis using more powerful tests such as the Zivot-Andrews single-break unit root and the KPSS stationarity (no unit root) tests to confirm that the USD/EUR spot and three-month forward rates are I(1) in nature. The study successfully employs Engle-Granger cointegration analysis which identifies a stable long-run relationship between the spot and forward rates and generates an ECM model that is used to forecast the in-sample (historical) data.The study’s findings refute past conclusions that fail to identify the data’s I(1) nature and suggests that market efficiency is present in the long run but not necessarily in the short run.
    Keywords: Cointegration analysis, Error-correction model (ECM), Forward exchange rate unbiasedness hypothesis (FRUH), KPSS no unit root test, unexploited profits, and Zivot-Andrews single break unit root test
    JEL: F3 F31 C20 C22
    Date: 2013–07
  6. By: Peter Edward (Newcastle Universtiy Business School); Andy Sumner (Institute of Development Studies, Sussex)
    Abstract: Various recent papers have sought to make projections about the scale and locations of global poverty in the next 20 to 30 years. Such forecasts have significant policy implications because they are used to inform debates on the scale and objectives of future aid. However, these papers have produced some very different projections for global poverty so that a complex and rather inconsistent picture has emerged. Estimating even current global poverty levels is problematic for a range of reasons arising largely from the limitations of available data and the various alternative modeling approaches used to compensate for them. Forecasts for future poverty become further complicated by the range of scenarios for future economic growth and changes in inequality. Largely as a result of these differences, not only do different analysts arrive at very different understandings of the extent and prospects for global poverty but it is also extremely difficult to make meaningful comparisons between different analyses. (?)
    Keywords: The Future of Global Poverty in a Multi-Speed World: New Estimates of Scale, Location and Cost
    Date: 2013–06
  7. By: Mark Meyer (GWS - Institute of Economic Structures Research); Martin Distelkamp (GWS - Institute of Economic Structures Research); Gerd Ahlert (GWS - Institute of Economic Structures Research); Prof. Dr. Bernd Meyer (GWS - Institute of Economic Structures Research)
    Abstract: GINFORS (Global INterindustry FORecasting System) represents a state–of–the–art tool for integrated quantitative policy assessments of long run economic developments and associated pressures on the environment. Its empirical modelling framework rests on national input–output accounts which are bilaterally interconnected by international trade at the industry level. Assuming bounded rationality of agents and imperfect markets, an iterative solution algorithm facilitates ex ante simulation studies of the non-equilibrium features of globalizing economies. From a methodological point of view, GINFORS might thus be categorised as a dynamic econometric model. However, its powerful simulation capabilities also provide extensive insights into the broader economy–energy–environment nexus (see, i.a., or for ongoing FP7 research work with references to climate change and the transformation to a low carbon economy as well as to climate change adaptation policy issues). The GINFORS approach relies heavily on the availability of harmonised international Input–Output datasets (preferably as annual time series). As the May 2012 release of the publicly available World Input Output Database (WIOD, see also represents outstanding advancements in this regard, we decided to incorporate the WIOD datasets into the GINFORS database. This paper highlights selected issues of these most recent empirical maintenance works. Given our personal experience we intend to illustrate the significance of the WIOD database but also to stimulate a discussion of its linkages to the underlying United Nations data set on the sequence of accounts and balancing items, the second core data set within the System of National Accounts (SNA), from the viewpoint of applied economic research.
    Keywords: environmental policy, multi-region Input-Output analysis, world trade model, embodied environmental impacts
    JEL: C54 C63 C67 Q01 Q56 F17 F18
    Date: 2013
  8. By: Pietro Ortoleva; Erik Snowberg
    Abstract: This paper studies, theoretically and empirically, the role of overconfidence in political behavior. Our model of overconfidence in beliefs predicts that overconfidence leads to ideological extremeness, increased voter turnout, and increased strength of partisan identification. Moreover, the model makes many nuanced predictions about the patterns of ideology in society, and over a person's lifetime. These predictions are tested using unique data that measure the overconfidence, and standard political characteristics, of a nationwide sample of over 3,000 adults. Our predictions, eight in total, find strong support in this data. In particular, we document that overconfidence is a substantively and statistically important predictor of ideological extremeness and voter turnout.
    JEL: C83 D03 D72 D83
    Date: 2013–07

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