Factor-Based Approaches for Improved Economic Forecasting: Insights from Ghana's GDP Growth - Osei, Victor; Acheampong, Joseph (Journal of Business and Economic Options, 2021)
The focus on evaluating time series factor estimators using autoregressive models and principal component analysis for short-term forecasting of Ghana's GDP growth represents a significant contribution to economic forecasting methodologies. By leveraging early releases of monthly real sector indicators, the study aims to enhance the accuracy and timeliness of GDP growth forecasts, which are crucial for policymakers, investors, and other stakeholders. The research methodology involves applying static principal component analysis to extract factor estimators from a small set of monthly real sector indicators. These factor estimators are then used in a forecast equation to predict the conditional expectations of domestic economic activity, particularly Ghana's GDP growth. By incorporating advanced statistical techniques and utilizing high-frequency data, the study seeks to improve the precision and reliability of short-term economic forecasts. The findings of the study suggest that factor models based on principal component analysis perform well in predicting the conditional expectations of Ghana's GDP growth. This indicates the potential effectiveness of using factor-based approaches for economic forecasting, particularly in the context of emerging economies like Ghana. The ability to accurately forecast GDP growth based on early releases of real sector indicators can provide valuable insights into the state of the economy and inform policy decisions aimed at promoting economic stability and growth. Overall, the research paper contributes to the field of economic forecasting by demonstrating the efficacy of time series factor estimators and principal component analysis in predicting short-term GDP growth dynamics in Ghana. By providing empirical evidence of the performance of these forecasting techniques, the study offers valuable insights for practitioners and researchers seeking to enhance the accuracy and reliability of economic forecasts in emerging markets.