GDP nowcasting: application and constraints in a small open developing economy
Ashwin Madhou, Tayushma Sewak, Imad A. Moosa, Vikash Ramiah
Abstract
Ashwin Madhou, Tayushma Sewak, Imad A. Moosa, Vikash Ramiah
Abstract
Despite data limitations, an attempt is made to find out if a GDP nowcasting model can provide reliable forecasts for a small open economy. Two competing Bayesian vector autoregressive models are tested rigorously to obtain the optimal model by minimizing in-sample forecasting errors. The main finding of this study is that GDP nowcasting can produce reliable results for a small open economy despite the unavailability of sufficient data sets and the lack of high frequency indicators.
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Despite data limitations, an attempt is made to find out if a GDP nowcasting model can provide reliable forecasts for a small open economy. Two competing Bayesian vector autoregressive models are tested rigorously to obtain the optimal model by minimizing in-sample forecasting errors. The main finding of this study is that GDP nowcasting can produce reliable results for a small open economy despite the unavailability of sufficient data sets and the lack of high frequency indicators.
Key concepts: Nowcasting, Unavailability, Small open economy, Economics, Econometrics, Bayesian probability, Autoregressive model, Real gross domestic product