Forecasting and Nowcasting Emerging Market GDP Growth Rates: The Role of Latent Global Economic Policy Uncertainty and Macroeconomic Data Surprise Factors

47 Pages Posted: 2 Jan 2019

See all articles by Oguzhan Cepni

Oguzhan Cepni

Government of the Republic of Turkey - Central Bank of the Republic of Turkey

Ibrahim Guney

Government of the Republic of Turkey - Central Bank of the Republic of Turkey

Norman R. Swanson

Rutgers University - Department of Economics; Rutgers, The State University of New Jersey - Department of Economics

Date Written: December 10, 2018

Abstract

In this paper, we assess the predictive content of latent economic policy uncertainty and data surprises factors for forecasting and nowcasting GDP using factor-type econometric models. Our analysis focuses on five emerging market economies, including Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse-race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models (DFMs) that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies.

Suggested Citation

Cepni, Oguzhan and Guney, Ibrahim and Swanson, Norman Rasmus and Swanson, Norman Rasmus, Forecasting and Nowcasting Emerging Market GDP Growth Rates: The Role of Latent Global Economic Policy Uncertainty and Macroeconomic Data Surprise Factors (December 10, 2018). Available at SSRN: https://ssrn.com/abstract=3298924 or http://dx.doi.org/10.2139/ssrn.3298924

Oguzhan Cepni

Government of the Republic of Turkey - Central Bank of the Republic of Turkey ( email )

Istiklal Cad. 10 Ulus
06100 Ankara, Ankara 06050
Turkey

Ibrahim Guney

Government of the Republic of Turkey - Central Bank of the Republic of Turkey ( email )

Istiklal Cad. 10 Ulus
06100 Ankara, Ankara 06050
Turkey

Norman Rasmus Swanson (Contact Author)

Rutgers University - Department of Economics ( email )

NJ
United States

HOME PAGE: http://econweb.rutgers.edu/nswanson/

Rutgers, The State University of New Jersey - Department of Economics ( email )

75 Hamilton Street
New Brunswick, NJ 08901
United States
848-932-7432 (Phone)

HOME PAGE: http://econweb.rutgers.edu/nswanson/

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
123
Abstract Views
705
Rank
402,572
PlumX Metrics