Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: When are Google data useful to nowcast GDP? An approach via
  pre-selection and shrinkage   Alternative data sets are nowadays widely used for macroeconomic nowcasting
together with new Machine Learning-based tools which often are applied without
having a complete picture of their theoretical nowcasting properties. Against
this background, this paper proposes a theoretically-funded nowcasting
methodology allowing to incorporate alternative Google Search Data (GSD) among
the predictors and combining targeted preselection, Ridge regularization and
Generalized Cross Validation. Breaking with most of the existing literature
that focuses on asymptotic in-sample theoretical properties, we establish the
theoretical out-of-sample properties of our methodology, that are supported by
Monte-Carlo simulations. We apply our methodology to GSD in order to nowcast
GDP growth rate of different countries during various economic periods. Our
empirical findings support the idea that GSD tend to increase nowcasting
accuracy, even after controlling for official variables, but that the gain
differs between periods of recessions and of macroeconomic stability.

7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess