One of the most notable and revealing statements ever made in terms of the relationship between exchange rate and revenue mobilisation is attributed to the then Commissioner General, Mr. Kofi Nti, reported in a GRA news bulletin: “…. between 2012 and 2014 when revenue doubled in Ghana cedi but a conversion to dollar equivalent showed a decline”.
This statement has become a point of debate between academia and policymakers in recent times, in light of the Ghana Revenue Authority (GRA) revenue target for the 2022 fiscal year. Lots of expert have on several platforms stated unequivocally that the GH₵80billion revenue target of GRA is not achievable, especially when compared with the GH₵57billion target for last year.
Ofori et al. (2018) used data from 1984 to 2014 to test how exchange rate volatility affects tax revenue generation in Ghana. The results showed there was both a short- and long-term relationship between exchange rate volatility and tax revenue. They argued it is detrimental to tax revenue generation as the volatility makes trade riskier; hence, it behoves monetary authorities to stabilise the cedi’s barter price.
Government is mostly under pressure to liberalise trade due to exchange rate volatility, and this results in reduction of taxes. This was the case when the Ghana Union Traders Association (GUTA) succeeded in lobbying government to reduce the benchmark value of selected products.
Inflation (consumer price index) measures changes over time in the general price level of goods and services that households acquire for the purpose of consumption. The reference marker was first set in 2010 and then 2018 after government’s decision to rebase the economy.
Ghana’s inflation rate has been on a steady rise in recent times, particularly after COVID-19 and now the Russia-Ukraine war. Ghana’s inflation rate has been driven mostly by commodity, food and non-alcoholic beverage prices. It is worth noting that the cumulative inflation rate in Ghana is unevenly distributed, with the northern belt experiencing a higher rate compared to the southern belt.
Ghana’s taste for foreign goods has never been in doubt, and this is evident in how the cedi has depreciated over time. This is against a weak export regime to counter, despite Ghana recording a surplus of trade balance in recent years. Ghana’s export regime is mainly spearheaded by traditional commodities including cocoa, crude oil, gold and timber. In 2007, Ghana redenominated the cedi currency to peg it with the US dollar. The redenominated cedi was not able to withstand the pressures associated with demand for foreign currency by Ghanaians and foreigners. This is due to high volatility of the Ghana cedi.
Currently, foreigners hold more than 20 percent of Ghana’s bonds – further putting enormous pressure on the fragile cedi. The cedi’s cumulative depreciation over a period of twelve years is about 700 percent.
Research hypothesis and methodology
In this simple data simulation, the hypothesis tested was the correlation between tax revenue, exchange rate and inflation from the period 2010 to 2021 using annual time series. The period was selected based on full implementation of Ghana Revenue Administration Act, 2009, (Act 791) as a result of the merging of CEPS, IRS, RAGD and VATS to form the GRA. The dependent variable, tax revenue, was obtained from annual data presented by Bank of Ghana.
A natural log was then applied to the variable before analysing. Inflation and exchange rate were measured by the end period rate as published by Ghana Statistical Service and World Development Indicators. The methodology employed was analysing the data obtained using Stata software by running descriptive statistics and linear regression analysis; employing the formula lnRevt . Where; lnRev= log Tax Revenue; Β0 = intercept; Β1Inf= Inflation rate; Β2 ExR= Exchange rate; µ= error term.
Results and analysis
The results from Table 1 indicate the maximum inflation rate recorded was 17.7 percent and the minimum was 7.13 percent; while the maximum exchange rate was 6.2 percent and 1.4 percent the minimum.
| Variable | Observation | Mean | Std. Dev. | Min. | Max. |
| Revenue | 12 | 27230.06 | 15855.19 | 6504.51 | 57230 |
| Inflation | 12 | 11.85583 | 3.485744 | 7.13 | 17.7 |
| Exchange Rate | 12 | 3.616667 | 1.690526 | 1.4 | 6.2 |
Table 1
A Pearson’s product-moment correlation was run to assess the relationship between Tax revenue, Inflation and Exchange rate from the data period. There was a strong positive correlation between exchange rate and tax revenue, r= 0.982, p< 0.01. (table 2). However, a negative correlation was observed between inflation and tax revenue, albeit not statistically significant at 1 percent.
From the linear regression analysis provided in table 3, the two variables collectively explained about 97 percent of variation in revenue collected over the period. In terms of their respective contributions, a unit increase in exchange rate would result in revenue increasing by GH₵9,244.15m. Diagnostic test results from the DW test, normality test, Breusch-Godfrey serial correlation test, Breusch-Pagan-Godfrey heteroskedasticity test have validated the accuracy and robustness of the parameter estimates.
| ExR | Inf | Rev | ||
| ExR | Pearson Correlation | 1 | .079 | .982** |
| Sig. (2-tailed) | .808 | .000 | ||
| N | 12 | 12 | 12 | |
| Inf | Pearson Correlation | .079 | 1 | -.010 |
| Sig. (2-tailed) | .808 | .976 | ||
| N | 12 | 12 | 12 | |
| Rev | Pearson Correlation | .982** | -.010 | 1 |
| Sig. (2-tailed) | .000 | .976 | ||
| N | 12 | 12 | 12 | |
| **. Correlation is significant at the 0.01 level (2-tailed).
Table 2 |
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Model
| Variable | Coefficient | Std. Error | t-Statistic | Prob. |
| Inf | -415.0261 | 255.1736 | -1.626446 | 0.1383 |
| ExR | 9244.145 | 526.1496 | 17.56942 | 0.0000 |
| C | -1282.446 | 3602.829 | -0.355955 | 0.7301 |
| R-squared | 0.971733 | Mean dependent var | 27230.06 | |
| Adjusted R-squared | 0.965451 | S.D. dependent var | 15855.19 | |
| S.E. of regression | 2947.063 | Akaike info criterion | 19.02732 | |
| Sum squared resid | 78166642 | Schwarz criterion | 19.14855 | |
| Log likelihood | -111.1639 | Hannan-Quinn criter. | 18.98244 | |
| F-statistic | 154.6939 | Durbin-Watson stat | 1.748575 | |
| Prob(F-statistic) | 0.000000 | |||
| Table 3 | ||||
Model Diagnostic Tests
Normality Test
| Breusch-Godfrey Serial Correlation LM Test: | ||||
| F-statistic | 0.418548 | Prob. F (2,7) | 0.6734 | |
| Obs*R-squared | 1.281744 | Prob. Chi-Square (2) | 0.5268 | |
| Heteroskedasticity Test: Breusch-Pagan-Godfrey | ||||
| F-statistic | 2.445541 | Prob. F (2,9) | 0.1418 | |
| Obs*R-squared | 4.225228 | Prob. Chi-Square (2) | 0.1209 | |
| Scaled explained SS | 3.488271 | Prob. Chi-Square (2) | 0.1748 | |
This analysis confirms what Mr. Kofi Nti elucidated: that the exchange rate has a direct repercussion on tax revenue. What accounts for the increase in tax revenue is the exchange rate volatility; but in terms of real revenue growth, which is tax to GDP, there will be a decline as analysed by Ofori et al. (2018). Government in setting revenue targets for GRA must focus on tax to GDP as against a straight line percentage over the previous year.
Conclusion
In conclusion, the ambitious target of GRA is achievable looking at the recent increase in exchange rate, projected economic growth rate and modernisation of revenue administration. It is believed Customs revenue will be boosted as well as taxes and royalties paid by entities in the upstream oil sector and mining companies due to upward volatilities in the exchange rate.
Government should therefore be able to reduce the budget deficit to a single rate and increase capital expenditure in the country. Tax education and sensitisation on voluntarily compliance must be rigorously embarked on by GRA to rope-in more taxpayers to the tax net.
Future analysis should explore the effect of economic growth rate on tax revenue mobilisation in Ghana.
References
- https://www.bog.gov.gh/economic-data/government-operations/ retrieved on 27th April, 2022.
- https://www.statsghana.gov.gh/Economics.php?category=NjA3MDAyNjY4LjY1OTU=/webstats/3psp748376 retrieved on 27th April, 2022.
- GRA news bulletin; April 2017, Issue no. 12
- Ofori I.K., Obeng C.K. & Armah M.K. (2018). Exchange rate volatility and tax revenue: Evidence from Ghana. Cogent Economics & Finance; vol 6, no. 1, pages 1-16.
Credit: Francis Mawuli Abude (PhD*). An economist/statistician at the monetary policy and strategy− Research department, Bank of Ghana for great input in analysing the data.
>>>The author holds an MSc (Economic Policy), from CITG and is a staff of GRA at the Accra West Area office. Email: [email protected]
