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ABSTRACT
This study examines Ghana’s central bank’s monetary policy under Ghana’s inflation-targeting (IT) monetary policy regime since 2002. We find that Ghana’s central bank pursued a passive monetary policy under the unofficial IT monetary policy regime and hence cannot explain the decline in Ghana’s inflation rate during this period. We also find that Ghana’s central bank switched its monetary policy from passive to active under the official IT monetary policy framework, and hence cannot also explain Ghana’s rising inflation rate observed during this period. We provide evidence suggesting that Ghana’s central bank’s policy change might have been influenced by fiscal factors.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. Quarterly data provides a more detailed picture of the economy than annual data while being less noisy and more robust than monthly data.
2. Other forms of the Taylor rule exist where the central bank directly adjusts the nominal interest rate in response to changes in past and future inflation rate and output rather than the current inflation rate and output.
3. Specifically, Markov switching models enable us to estimate the probability of the central bank being in different policy regimes (such as a dovish or hawkish policy regime) at any given time and also to estimate the impact of different economic variables on the probability of switching between regimes.
4. Ignoring country-specific differences.
5. In the literature, there are other alternative ways of estimating potential output including using a linear time trend model, a Cobb Douglas production function, or a DSGE model.
6. Other variations of Equation (2) includes and
where the central bank responds to future and past inflation than current inflation rate.
7. In Carvalho, Nechio, and Tristao (Citation2019), they add the second lag of (i.e.
) to the right-hand-side of Equation (8).
8. Ghana does not have an official quarterly real GDP data.
9. Our quarterly GDP data obtained from Tahir, Ahmed, and Ahmed (Citation2018) ends at 2016Q4. Moreover, we are also able to compare our results with existing studies over the same period.
10. Bleaney et al. (Citation2020) use Bank of Ghana’s Composite Index of Economic Activity as a proxy for output, and the timing of the data is not quarterly, but the specific meeting dates of Ghana’s monetary policy committee. In this paper, however, we use quarterly data, and output is proxied by real GDP, which is preferable for quarterly policy analysis, for example, building a quarterly DSGE model using our results.
11. Note that we are imposing the number of regimes, not estimating it endogenously.
12. Note that by simulating the model (as shown above) with the residuals and the estimated parameters, we will recover the data.
13. Bleaney et al. (Citation2020) – for Ghana central bank, R. Clarida et al. (Citation1998) – for US and Japan central banks, Gorter et al. (Citation2008) – for the ECB. The inflation rate and interest rate often fail statistical stationarity tests.
14. Ghana debuted its issuance of Eurobonds in 2007 after the completion of the HIPC initiative. Currently, Ghana’s total Eurobond debt is roughly about $13–$14 billion.
Additional information
Notes on contributors
Emmanuel Ameyaw
Emmanuel Ameyaw is a trained economists and data scientist with a research interest in Money and Banking, Macroeconomics, Monetary Economics, Financial Economics, Applied Macroeconometrics, Central Banking and Financial Institutions, Development Economics, Data Analytics / Data Science in Economics and Finance. This paper was written during my doctoral studies at Tohoku University in Sendai, Japan.