African Development Bank applauds Ghana’s macroeconomic modeling progress amidst challenges

Addressing the imperative of strengthening capacity in macroeconomic modeling, Professor Urama highlighted its critical role in informing decision-making, enhancing the formulation of policies, and facilitating effective implementation, monitoring, and evaluation.

In the latest report on Benchmark Macroeconomic Models for Effective Policy Management in Africa, the African Development Bank (AfDB) has commended Ghana’s strides in macroeconomic modeling. The report, unveiled at the 2023 Africa Economic Conference in Addis Ababa, Ethiopia, serves as an inventory of the macroeconomic models employed across African countries, shedding light on their features and predictive capabilities.

While acknowledging some limitations in Ghana’s macroeconomic modeling, the AfDB predicts a resurgence in economic activity in the country. Improved global macroeconomic conditions, robust domestic demand, and growth in capital expenditure are cited as factors contributing to the positive outlook.

Professor Kevin Chika Urama, Chief Economist and Vice President of the AfDB, underscored the significance of macroeconomic models in understanding and predicting economic behavior. He emphasized that these models play a crucial role in analyzing policy responses, evaluating outcomes, and guiding implementation, monitoring, and evaluation. However, he noted that models are simplifications of reality, subject to specific assumptions, contexts, and realities.

Addressing the imperative of strengthening capacity in macroeconomic modeling, Professor Urama highlighted its critical role in informing decision-making, enhancing the formulation of policies, and facilitating effective implementation, monitoring, and evaluation.

The country report on Ghana within the survey findings revealed a suite of macroeconomic tools employed by the Central Bank of Ghana. This includes the Quarterly Projection Model (QPM), various statistical models such as VAR, ARIMA, and Dynamic Factor Models, and Machine Learning for nowcasting inflation and GDP. Despite continuous technical support and training from the IMF, challenges persist, primarily related to occasional significant revisions of GDP figures and the evolving macroeconomic structure in Ghana.

In conclusion, the report suggests that while macroeconomic modeling in Ghana is progressing positively, there is room for improvement in enhancing staff capacity for adapting to the changing economic landscape and addressing challenges associated with GDP data revisions.

Source:norvanreports

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