Forecasting the GDP of a small open developing economy: an application of FAVAR models

Authors

Ashwin Madhou
Tayushma Sewak
Imad Moosa
Vikash Ramiah, University of Wollongong DubaiFollow

RIS ID

139933

Publication Details

Madhou, A., Sewak, T., Moosa, I. & Ramiah, V. 2019, 'Forecasting the GDP of a small open developing economy: an application of FAVAR models', Applied Economics,

Abstract

2019, 2019 Informa UK Limited, trading as Taylor & Francis Group. GDP forecasting remains a challenge for a small open developing economy. Faced with insufficient and low-frequency data, central bank forecasters cannot project GDP reliably for the purpose of monetary policy decision-making. An attempt is made to forecast GDP using a factor-augmented vector autoregressive (FAVAR) model for a small open developing economy. The forecasting accuracy of the FAVAR model is examined through sequential forecasts and benchmarked against a Bayesian vector autoregressive (BVAR) model. The main finding of this study is that a FAVAR model can generate consistent GDP projections for a small open developing economy despite data inadequacy.