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“Google it!” Forecasting the US Unemployment Rate with a Google Job Search index AgEcon
D’Amuri, Francesco; Marcucci, Juri.
We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. We find that models augmented with the GI outperform the traditional ones in predicting the monthly unemployment rate, even in most state-level forecasts and in comparison with the Survey of Professional Forecasters.
Tipo: Working or Discussion Paper Palavras-chave: Google Econometrics; Forecast Comparison; Keyword search; US Unemployment; Time Series Models; Labor and Human Capital; C22; C53; E27; E37; J60; J64.
Ano: 2010 URL: http://purl.umn.edu/60680
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The Labor Market Impact of Immigration in Western Germany in the 1990’s AgEcon
D’Amuri, Francesco; Ottaviano, Gianmarco I.P.; Peri, Giovanni.
We adopt a general equilibrium approach in order to measure the effects of recent immigration on the Western German labor market, looking at both wage and employment effects. Using the Regional File of the IAB Employment Subsample for the period 1987-2001, we find that the substantial immigration of the 1990’s had no adverse effects on native wages and employment levels. It had instead adverse employment and wage effects on previous waves of immigrants. This stems from the fact that, after controlling for education and experience levels, native and migrant workers appear to be imperfect substitutes whereas new and old immigrants exhibit perfect substitutability. Our analysis suggests that if the German labor market were as ‘flexible’ as the UK labor...
Tipo: Conference Paper or Presentation Palavras-chave: Immigration; Skill Complementarities; Employment; Wages; Labor and Human Capital; E24; F22; J61; J31.
Ano: 2008 URL: http://purl.umn.edu/6384
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