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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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Sequential Migration, and the German Reunification AgEcon
Birk, Angela.
The paper develops a sequential migration model and derives a worker's optimal policies for migration and employment. With the worker's simulated reservation wage functions for employment and migration, a stationary equilibrium is defined. In that equilibrium, stationary distributions of employed and unemployed stayers and movers over different states are derived. The analysis of Markov equilibria shows that mainly unemployed skilled and unskilled migrants will migrate. I have referred to this unemployed self-selection of skilled and unskilled migrants. Furthermore, in the stationary equilibrium, a trade off between equity and efficiency is derived and represents the adverse effects when a government fosters income increases too much.
Tipo: Working or Discussion Paper Palavras-chave: Sequential Migration; Markov Equilibria; German Reunification; Labor and Human Capital; C61; E27; J61.
Ano: 2004 URL: http://purl.umn.edu/26338
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