Uncertainty in a Disaggregate Model: A Data Rich Approach Using Google Search Queries

73 Pages Posted: 26 Nov 2019 Last revised: 30 Nov 2019

See all articles by Kalvinder Shields

Kalvinder Shields

Department of Economics, University of Melbourne

Trung Duc Tran

The University of Sydney; University of Melbourne - Department of Economics

Date Written: November 25, 2019

Abstract

This paper estimates the impact of uncertainty shocks in a disaggregate model featuring state-level unemployment and uncertainty, which is measured using Google search data. We show that the disaggregate model captures important spillover effects which a model using aggregate data would overlook resulting in significantly different peak responses and time dynamic effects. We find the effect of uncertainty shocks on state-level unemployment is recessionary and heterogeneous. The importance of national factors in propagating the effect of uncertainty is also heterogeneous across states, and overall less relevant than state-level factors. These heterogeneous effects are found to be related to state-specific industry compositions and the fiscal position.

Keywords: Google Trends uncertainty, uncertainty shocks, regional effects

JEL Classification: C32, E32

Suggested Citation

Shields, Kalvinder and Tran, Trung Duc, Uncertainty in a Disaggregate Model: A Data Rich Approach Using Google Search Queries (November 25, 2019). CAMA Working Paper No. 83/2019, Available at SSRN: https://ssrn.com/abstract=3492817 or http://dx.doi.org/10.2139/ssrn.3492817

Kalvinder Shields

Department of Economics, University of Melbourne ( email )

185 Pelham Street
Carlton
Carlton, Victoria 3053
Australia

Trung Duc Tran (Contact Author)

The University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

University of Melbourne - Department of Economics ( email )

Melbourne, 3010
Australia

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