2016•Applied EconomicsRequires access

GDP nowcasting: application and constraints in a small open developing economy

Ashwin Madhou, Tayushma Sewak, Imad A. Moosa, Vikash Ramiah

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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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What this paper is about

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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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Nowcasting, Unavailability, Small open economy, Economics, Econometrics, Bayesian probability, Autoregressive model, Real gross domestic product

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