Nowcasting Unemployment Rate in Turkey : Let's Ask Google
We use linear regression models and Bayesian Model Averaging procedure to investigate whether Google search query data can improve the nowcast performance of the monthly nonagricultural unemployment rate for Turkey for the period from January 2005 to January 2012. We show that Google search query data is successful at nowcasting1 monthly nonagricultural unemployment rate for Turkey both in-sample and out-of-sample. When compared with a benchmark model, where we use only the lag values of the monthly unemployment rate, the best model contains Google search query data and it is 47.8 percent more accurate in-sample and 38.3 percent more accurate for the one month ahead nowcasts in terms of relative root mean square errors (RMSE). We also show via Harvey, Leybourne, and Newbold (1997) modification of the Diebold-Mariano test that models with Google search query data indeed perform statistically better than the benchmark.
|Date of creation:||2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (90 312) 507 5000
Fax: (90 312) 507 5640
Web page: http://www.tcmb.gov.tr
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:tcb:wpaper:1218. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ozlem Ekmekciler Ramalho Rocha)or (Ilker Cakar)
If references are entirely missing, you can add them using this form.