nep-for New Economics Papers
on Forecasting
Issue of 2013‒12‒20
eight papers chosen by
Rob J Hyndman
Monash University

  1. Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank By Jan Bruha; Tibor Hledik; Tomas Holub; Jiri Polansky; Jaromir Tonner
  2. Financial Signaling and Earnings Forecasts. By Iuliia Brushko
  3. Rethinking What Survey Data has to Say about the Role of Risk and Irrationality in Currency Markets By Josh Stillwagon
  4. The Excess Returns Puzzle in Currency Markets: Clues on Moving Forward By Josh Stillwagon
  5. Money Targeting in a Modern Forecasting and Policy Analysis System: an Application to Kenya By Michal Andrle; Andrew Berg; Enrico Berkes; Rafael A Portillo; Jan Vlcek; R. Armando Morales
  6. Linear mixed models for predictive modelling in actuarial science. By Antonio, Katrien; Zhang, Yanwei
  7. Non linear mixed models for predictive modelling in actuarial science. By Antonio, Katrien; Zhang, Yanwei
  8. Decadal Climate Variability: Economic Implications In Agriculture And Water In The Missouri River Basin By Fernandez, Mario Andres

  1. By: Jan Bruha; Tibor Hledik; Tomas Holub; Jiri Polansky; Jaromir Tonner
    Abstract: This paper focuses on the forecasting process at the Czech National Bank with an emphasis on incorporating expert judgments into forecasts and addressing data uncertainty. At the beginning, the core model and the forecasting process are described and it is presented how data and the underlying uncertainty are handled. The core of the paper contains five case studies, which reflect policy issues addressed during forecasting rounds since 2008. Each case study first describes a particular forecasting problem, then the way how the issue was addressed, and finally the effect of incorporating off-model information into the forecast is briefly summarized. The case studies demonstrate that a careful incorporation of expert information into a structural framework may be useful for generating economically intuitive forecasts even during very turbulent times, and we show that such judgements may have important monetary policy implications.
    Keywords: DSGE models, forecasting, Kalman filter, monetary policy.
    JEL: C53 C54 E17
    Date: 2013–10
  2. By: Iuliia Brushko
    Abstract: This paper examines the extent to which financial signaling affects the analysts' and managers' forecast releases. The findings give evidence of heterogeneity of analysts' forecast errors between firms with strong financial indicators (high signal group), weak financial indicators (low signal group), and those with both positive and negative signals (mixed signal group). The paper further indicates that managers' forecast releases also depend on the type of the firm and that managers may try to use the heterogeneity in analysts' treatment. The findings also suggest that the analysts sometimes fail to adjust for managers' forecast biases and that is why may be misled by managers' forecasts. This provides evidence of inaccuracy on the part of analysts and potential gaming on information disclosures between analysts and managers.
    Keywords: analysts' underreaction, earnings per share, analysts' forecast revisions, managers' forecast practices, earnings announcements
    JEL: D84 G14 G17 G32 M40
    Date: 2013–11
  3. By: Josh Stillwagon (Department of Economics, Trinity College)
    Abstract: A number of studies have used survey data on traders' exchange rate forecasts to examine the role of risk and non-REH forecasting in accounting for excess returns in currency markets. This work re-examines those results using an alternative estimation technique, the Cointegrated VAR, which allows for better examination of non-stationarity in a multivariate framework. The results demonstrate the importance of focusing on the persistence of deviations from any found relationships. Consistent with some later studies, clear evidence of a time-varying risk premium is found, and REH is rejected for all three exchange rate samples examined (BP/USD, DM/USD, and JY/USD). The results strongly draw into question though the interpretation that this represents obvious irrationality. The relationship between the forecast error and interest rate differential is found to be non-stationary at very high significance levels, implying that the correlations are spurious and unstable over time, and individuals are not, in fact, mis-forecasting in a fixed manner relative to interest rates.
    Keywords: Excess returns puzzle, survey data, risk premium, non-stationarity, irrationality
    JEL: F31 G02 G14 G15
    Date: 2013–12
  4. By: Josh Stillwagon (Department of Economics, Trinity College)
    Abstract: This paper is designed to review the empirical literature on the excess returns puzzle: the difficulty encountered by standard risk premium models in accounting for relative returns in the foreign exchange market. Of particular interest are the studies using survey data to decompose ex post excess returns into an expected component - the risk premium - and a forecast error. On the whole, these studies have found evidence of violations of the rational expectations hypothesis (non-white noise forecast errors), and a time-varying risk premium. This suggests the need for an alternative specification of forecasting. The literature has left open however the question of whether the traditional models can account for movements in the premium as measured by survey. Although the traditional models have not been tested against survey data, there is reason from the outset to believe EUT provides a deficient foundation for a model of the risk premium. Experimental evidence is discussed showing that the predictions of EUT are grossly inconsistent with the behavior of actual subjects towards risky gambles. Lastly, the paper discusses alternative models of risk preferences drawing from the experimental findings on prospect theory, and ways in which their testing can be improved through use of the I(2) Cointegrated VAR model.
    Keywords: Excess returns puzzle, survey data, prospect theory, cointegration
    JEL: F31 G02 G15
    Date: 2013–12
  5. By: Michal Andrle; Andrew Berg; Enrico Berkes; Rafael A Portillo; Jan Vlcek; R. Armando Morales
    Abstract: We extend the framework in Andrle and others (2013) to incorporate an explicit role for money targets and target misses in the analysis of monetary policy in low-income countries (LICs), with an application to Kenya. We provide a general specification that can nest various types of money targeting (ranging from targets based on optimal money demand forecasts to those derived from simple money growth rules), interest-rate based frameworks, and intermediate cases. Our framework acknowledges that ex-post adherence to targets is in itself an objective of policy in LICs; here we provide a novel interpretation of target misses in terms of structural shocks (aggregate demand, policy, shocks to money demand, etc). In the case of Kenya, we find that: (i) the setting of money targets is consistent with money demand forecasting, (ii) targets have not played a systematic role in monetary policy, and (iii) target misses mainly reflect shocks to money demand. Simulations of the model under alternative policy specifications show that the stronger the ex-post target adherence, the greater the macroeconomic volatility. Our findings highlight the benefits of a model-based approach to monetary policy analysis in LICs, including in countries with money-targeting frameworks.
    Keywords: Monetary policy;Kenya;Interest rates;Inflation targeting;Monetary aggregates;Demand for money;Low-income developing countries;Economic models;Monetary Policy, Money Targeting, Forecasting, Kenya, Low-Income Countries
    Date: 2013–11–25
  6. By: Antonio, Katrien; Zhang, Yanwei
    Date: 2013
  7. By: Antonio, Katrien; Zhang, Yanwei
    Date: 2013
  8. By: Fernandez, Mario Andres
    Abstract: Economic research on decadal climate variability (DCV) is scarce. DCV refers to ocean-related climate influences of duration from seven to twenty years. The DCV phenomena and their phases are associated with variations in crop and water yields. This paper examines the value of DCV information in the Missouri river basin using a mathematical programming model. The analysis shows the value of a perfect forecast is about 5.2 billion dollars, though 86% of this value can be obtained by a less perfect forecast based on already available data. Results show differential responses in major crops acreage and water usage.
    Keywords: Decadal climate variability, value of information, adaptation, crop insurance, Agribusiness, Community/Rural/Urban Development, Crop Production/Industries, Demand and Price Analysis, Environmental Economics and Policy, Farm Management, Land Economics/Use,
    Date: 2013–08

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