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The study aims to investigate the role of monetary policy in encouraging economic growth through bank loans, as well as estimating the optimal monetary policy rate (MPR), which may be damaging to Ghana's economic growth if exceeded.

Using annual data spanning from 1990 to 2017, the authors used Autoregressive Distributed Lag (ARDL) econometric approach to investigate the impact of monetary policy on economic growth. Lind and Mehlum (2010) U test estimation technique is used in determining the threshold level.

The empirical findings demonstrated that the monetary transmission mechanism through the credit channel is poor in the long run, and the effectiveness of monetary policy is dependent on the financial sector's performance. A non-monotonic relationship between monetary and economic growth was also discovered in the study. As a result, the Monetary Policy Committee (MPC) should not adopt an interest rate for monetary policy that surpasses 23.7%.

Because of the non-monotonic link between MPR and economic growth, it is necessary to expand the financial market and ensure that the policy rate does not exceed the threshold level.

To the best of the authors' knowledge, this is one of the first studies to look at the MPR as a potential source of negative economic growth. The paper's findings could aid the MPC in determining the MPR. A MPR that is too high could eventually damage the financial sector and lead to economic disasters.

The purpose of this paper is to emphasize the risks involved in modeling inflation volatility in the context of macroeconomic policy. For countries like Ghana that are always battling economic problems, accurate models are necessary in any modeling endeavor. We estimate volatility taking into account the heteroscedasticity of the model parameters.

The estimations considered the quasi-maximum likelihood-based GARCH, stochastic and Bayesian inference models in estimating the parameters of the inflation volatility.

A comparison of the stochastic volatility and Bayesian inference models reveals that the latter is better at tracking the evolution of month-on-month inflation volatility, thus following closely the data during the period under review.

The paper looks at the effect of parameter uncertainty of inflation volatility alone while considering the effects of other key variables like interest and exchange rates that affect inflation.

Economists have battled with accurate modeling and tracking of inflation volatility in Ghana. Where the data is not well-behaved, for example, in developing economies, the stochastic nature of the parameter estimates should be incorporated in the model estimation.

Estimating the parameters of inflation volatility models is not enough in a perpetually gyrating economy. The risks of these parameters are needed to completely describe the evolution of volatility especially in developing economies like Ghana.

This work is one of the first to draw the attention of policymakers in Ghana towards the nature of inflation data generated in the economy and the appropriate model for capturing the uncertainty of the model parameters.

The purpose of the paper is to investigate the quantitative effect of import liberalization on tariff revenue in Ghana.

In an attempt to achieve the objective of the paper, a robust decomposition analytical approach was used to examine how different components of the sources of change in import tax contribute to changes in import tax revenue in Ghana.

The paper concludes that Ghana suffered some revenue loss from the liberalization by reducing the level of average official duty rates, but gained in revenue as a result of real currency depreciation.

It has been suggested that public policy should aim at determining and targeting the optimum level of the average official import duty rates, focus on the identification of the major sources of duty revenue leakage, and substitute sales taxes for tariffs to improve tax revenue sufficiently.

This paper makes explicit the contribution of alternative import policy features to changes in import tax revenue in Ghana.