Social Sciences (miscellaneous)Economics and Econometrics
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The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of problems in economics and related subjects, covering topics in measurement, estimation, testing, forecasting, and policy analysis. The emphasis is on the careful and rigorous application of econometric techniques and the appropriate interpretation of the results. The economic content of the articles is stressed. A special feature of the Journal is its emphasis on the replicability of results by other researchers. To achieve this aim, authors are expected to make available a complete set of the data used as well as any specialised computer programs employed through a readily accessible medium, preferably in a machine-readable form. The use of microcomputers in applied research and transferability of data is emphasised. The Journal also features occasional sections of short papers re-evaluating previously published papers. The intention of the Journal of Applied Econometrics is to provide an outlet for innovative, quantitative research in economics which cuts across areas of specialisation, involves transferable techniques, and is easily replicable by other researchers. Contributions that introduce statistical methods that are applicable to a variety of economic problems are actively encouraged. The Journal also aims to publish review and survey articles that make recent developments in the field of theoretical and applied econometrics more readily accessible to applied economists in general.
Carlo Altavilla, Raffaella Giacomini, Giuseppe Ragusa
SummaryThe dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations can accurately predict yields, but they are typically not available for all maturities and/or forecast horizons. We show how survey expectations can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible exponential tilting method that anchors the model forecasts to the survey expectations, and we develop a test to guide the choice of the anchoring points. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to—such as information about the current state of the economy or forward‐looking information contained in monetary policy announcements—without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.