nep-for New Economics Papers
on Forecasting
Issue of 2018‒10‒29
five papers chosen by
Rob J Hyndman
Monash University

  1. On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations By Camille Cornand; Paul Hubert
  2. An unobserved component modeling approach to evaluate multi-horizon forecasts By Tian, Jing; Goodwin, Thomas
  3. Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey of professional forecasters By Döpke, Jörg; Waldhof, Gabi; Fritsche, Ulrich
  4. Exchange rate predictability and dynamic Bayesian learning By Schüssler, Rainer; Beckmann, Joscha; Koop, Gary; Korobilis, Dimitris
  5. ALICE: A new inflation monitoring tool By de Bondt, Gable J.; Hahn, Elke; Zekaite, Zivile

  1. By: Camille Cornand (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique); Paul Hubert (OFCE - OFCE - Sciences Po, IEP Paris - Sciences Po Paris - Institut d'études politiques de Paris)
    Abstract: Establishing the external validity of laboratory experiments in terms of inflation forecasts is crucial for policy initiatives to be valid outside the laboratory. Our contribution is to document whether different measures of inflation expectations based on various categories of agents (participants to experiments, households, industry forecasters, professional forecasters, financial market participants and central bankers) share common patterns by analyzing: the forecasting performances of these different categories of data; the information rigidities to which they are subject; the determination of expectations. Overall, the different categories of forecasts exhibit common features: forecast errors are comparably large and autocorrelated, forecast errors and forecast revisions are predictable from past information, which suggests the presence of information frictions. Finally, the standard lagged inflation determinant of inflation expectations is robust to the data sets. There is nevertheless some heterogeneity among the six different sets. If experimental forecasts are relatively comparable to survey and financial market data, central bank forecasts seem to be superior.
    Keywords: inflation expectations,experimental forecasts,survey forecasts,market-based forecasts,central bank forecasts
    Date: 2018
  2. By: Tian, Jing (Tasmanian School of Business & Economics, University of Tasmania); Goodwin, Thomas
    Abstract: We propose an unobserved modeling framework to evaluate a set of forecasts that target the same variable but are updated along the forecast horizon. The approach decomposes forecast errors into three distinct horizon-specific processes, namely, bias, rational error and implicit error, and attributes forecast revisions to corrections for these forecast errors. By evaluating multi-horizon daily maximum temperature forecasts for Melbourne, Australia, we demonstrate how this modeling framework can be used to analyze the dynamics of the forecast revision structure across horizons. Understanding forecast revisions is critical for weather forecast users to determine the optimal timing for their planning decisions.
    Keywords: Decision making, decomposition, evaluating forecasts, state space models, weather forecasting
    JEL: C32 C53
    Date: 2018
  3. By: Döpke, Jörg; Waldhof, Gabi; Fritsche, Ulrich
    Abstract: We report results of a survey among active forecasters of the German business cycle. Using data for 82 respondents from 37 different institutions, we investigate what models and theories forecasters subscribe to and find that they are pronounced conservative in the sense, that they overwhelmingly rely on methods and theories that have been well-established for a long time, while more recent approaches are relatively unimportant for the practice of business cycle forecasting. DSGE models are mostly used in public institutions. In line with findings in the literature there are tendencies of \leaning towards consensus" (especially for public institutions) and \sticky adjustment of forecasts" with regard to new information. We find little evidence that the behaviour of forecasters has changed fundamentally since the Great Recession but there are signs that forecast errors are evaluated more carefully. Also, a stable relationship between preferred theories and methods and forecast accuracy cannot be established.
    Keywords: Forecast error evaluation,questionnaire,survey,business cycle forecast,professional forecaster
    JEL: E32 E37 C83
    Date: 2018
  4. By: Schüssler, Rainer; Beckmann, Joscha; Koop, Gary; Korobilis, Dimitris
    Abstract: This paper considers how an investor in foreign exchange markets might exploit predictive information in macroeconomic fundamentals by allowing for switching between multivariate time series regression models. These models are chosen to reflect a wide array of established empirical and theoretical stylized facts. In an application involving monthly exchange rates for seven countries, we find that an investor using our methods to dynamically allocate assets achieves significant gains relative to benchmark strategies. In particular, we find strong evidence for fast model switching, with most of the time only a small set of macroeconomic fundamentals being relevant for forecasting.
    Keywords: Exchange rates,economic fundamentals,Bayesian vector autoregression,forecasting,dynamic portfolio allocation
    JEL: C11 D83 F31 G12 G15 G17
    Date: 2018
  5. By: de Bondt, Gable J.; Hahn, Elke; Zekaite, Zivile
    Abstract: This paper develops Area-wide Leading Inflation CyclE (ALICE) indicators for euro area headline and core inflation with an aim to provide early signals about turning points in the respective inflation cycle. The series included in the two composite leading indicators are carefully selected from around 160 candidate leading series using a general-to-specific selection process. The headline ALICE includes nine leading series and has a lead time of 3 months while the core ALICE consists of seven series and leads the reference cycle by 4 months. The lead times of the indicators increase to 5 and 9 months, respectively, based on a subset of the selected leading series with longer leading properties. Both indicators identify main turning points in the inflation cycle ex post and perform well in a simulated real-time exercise over the period from 2010 to the beginning of 2018. They also have performed well in forecasting the direction of inflation. In terms of the quantitative forecast accurracy, the headline ALICE has on average performed broadly similarly to the Euro Zone Barometer survey, slightly worse than the Eurosystem/ECB Staff macroeconomic projections and better than the Random Walk model, albeit this is not the case for the core ALICE. JEL Classification: C32, C52, C53, E31, E37
    Keywords: band pass filter, euro area inflation, forecasting, leading indicators, trend-cycle decomposition
    Date: 2018–09

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