Predicting unemployment in short samples with internet job search query data

This article tests the power of a novel indicator based on job search related web queries in predicting quarterly unemployment rates in short samples. Augmenting standard time series specifications with this indicator definitely improves out-of-sample forecasting performance at nearly all in-sample interval lengths and forecast horizons, both when compared with models estimated on the same or on a much longer time series interval.

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Year of publication:	2009-10-30
Authors:	Francesco, D'Amuri
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Google econometrics \| Forecast comparison \| Keyword search \| Unemployment \| Time series models

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C53 - Forecasting and Other Model Applications ; E27 - Forecasting and Simulation ; J60 - Mobility, Unemployment, and Vacancies. General ; J64 - Unemployment: Models, Duration, Incidence, and Job Search ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008527375