Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis
10.1016/S1514-0326(17)30015-6
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/112089
Tipus de documentArticle
Data publicació2017-11-01
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
ProjecteTECNOLOGIAS DE APRENDIZAJE PROFUNDO APLICADAS AL PROCESADO DE VOZ Y AUDIO (MINECO-TEC2015-69266-P)
Abstract
In this study we use survey expectations about a wide range of economic variables to forecast real activity. We propose an empirical approach to derive mathematical functional forms that link survey expectations to economic growth. Combining symbolic regression with genetic programming we generate two survey-based indicators: a perceptions index, using agents’assessments about the present, and an expectations index with their expectations about the future. In order to find the optimal combination of both indexes that best replicates the evolution of economic activity in each country we use a portfolio management procedure known as index tracking. By means of a generalized reduced gradient algorithm we derive the relative weights of both indexes. In most economies, the survey-based predictions generated with the composite indicator outperform the benchmark model for one-quarter ahead forecasts, although these improvements are only significant in Austria, Belgium and Portugal.
CitacióClaveria, O., Monte, E., Torra Porras, S. Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis. "Journal of applied economics", 1 Novembre 2017, vol. 20, núm. 2, p. 329-349.
ISSN1514-0326
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
JAE(2017) - Vol ... 349 - post-print - DEF.pdf | 1,462Mb | Visualitza/Obre |