Role of Macroeconomic Factors Predicting Financial Performance of Commercial Banks in Zimbabwe 1990-2023

Role of Macroeconomic Factors Predicting Financial Performance of Commercial Banks in Zimbabwe 1990-2023

*Lawrence Dumisani Nyathi¹, David Kureya², Wilfred Petegumbo³

¹Department of Banking & Economic Sciences, Faculty of Business & Economic Sciences, National University of Science and Technology, Bulawayo, Zimbabwe

^2,3Graduate-Department of Banking & Economic Sciences, Faculty of Business & Economic Sciences, National University of Science and Technology, Bulawayo, Zimbabwe

DOI: https://dx.doi.org/10.47772/IJRISS.2025.905000161

Received: 28 March 2025; Accepted: 01 April 2025; Published: 04 June 2025

ABSTRACT

The financial performance of commercial banks is intricately linked to the macroeconomic environment in which they operate. In Zimbabwe, a country characterized by economic volatility, hyperinflation, and fluctuating exchange rates, understanding the role of macroeconomic factors in shaping bank performance is critical. Therefore, this study investigates the extent to which key macroeconomic variables influence the profitability, stability, and overall financial health of commercial banks.

Using a General Moments Methods (GMM) approach the study reveal that macroeconomic instability, particularly high inflation and volatile exchange rates, significantly impacts bank profitability and asset quality. Conversely, periods of economic growth and stable monetary policies are associated with improved financial performance. The study also highlights the resilience of Zimbabwean banks in navigating economic challenges, underscoring the importance of adaptive strategies and robust risk management practices.

This research contributes to the broader discourse on the interplay between macroeconomic conditions and banking performance, offering valuable insights for policymakers, bank managers, and financial analysts. Therefore, the study recommends that government of Zimbabwe should address economic problems facing the entire economy. The poor macroeconomic instability facing the country also weighs down heavily to the banking sector. Due because of the poor economic environment and perceived risk tied to the country, local commercial banks are facing significant challenges to attract fresh capital from the international market.

Keywords: Macroeconomic factors, financial performance, commercial banks, Zimbabwe, inflation, exchange rates, monetary policy, economic volatility, Return on Assets.

INTRODUCTION

Commercial banks play a critical role in the operation of an economy as they play an intermediary role of channelling funds from surplus economic units (savers) to deficit economic units (borrowers) for investment (Njoki & Nyamute, 2023). Besides mobilization of idle funds lying in the hands of economic units, commercial banks also play a vital role in overall wellbeing and socioeconomic development of a country through promotion of savings culture, forex trading, government lending, and public lending (Banda 2021). Nyathi & Petegumbo (2024) alludes that from independence all various sectors of the economy have been supported by the vibrant financial sector for growth and production. Abdullahi, (2020) posits that commercial banks promote trade both within and outside the nation through the bills of exchange acceptance and discounting.

Banking Sector in Zimbabwe

The banking sector of Zimbabwe comprised of 19 banks as of 31 August 2023 (MPS, 2023). These 19 banks include 14 commercial banks, 4 building societies, and 1 savings bank, which jointly accounted for ZW$34.4 trillion in assets, equivalent to 55 percent of GDP as of December 31, 2023 (IMF, 2024). Notably, 7 of these banks have foreign shareholding, holding a market share of over 51 percent, while the remaining banks are locally owned or state-owned (IMF 2024). The Reserve Bank of Zimbabwe (RBZ) regulates and supervises these banks using the Banking Act [Chapter 24:20] and other statutory instruments promulgated by the regulator from time to time. Commercial banks dominate the banking sector in Zimbabwe as they account for 73.36% of the total banking institutions in Zimbabwe (14 commercial banks out of 19 total banks in Zimbabwe). The banking sector remains safe, sound and continues to show resilience as reflected by adequate capital levels, satisfactory asset quality metrics, and sustained profitability. The sector continues to adapt to transforming banking operations through innovative, cost-effective and customer centric banking services and products, whilst leveraging on available opportunities to offer affordable housing finance products National, Budget, 2024).

Figure 1: Banking Sector Architecture

Source: Monetary Policy Statement (2023, P 23)

Since commercial banks accounts for 74% of total number of banks in Zimbabwe, it is therefore clear that commercial banks dominate the banking sector in Zimbabwe. Moreover, since they are closely related to economic growth it is particularly important to assess how macroeconomic factors affect commercial banks that would in turn allow parties to make informed decisions.

Macroeconomic Concept

Zimbabwe’s commercial banking sector has experienced significant challenges and transformations due to persistent macroeconomic instability, particularly in the last two decades. Between 2000 and 2008, hyperinflation eroded the value of deposits and loans, leading to a sharp decline in public confidence in the formal banking sector. The adoption of the multi-currency system in 2009, dominated by the US dollar, initially stabilized the economy, restored price predictability, and improved deposit mobilization (Mlambo et al., 2015). However, ongoing macroeconomic challenges such as liquidity shortages, inconsistent monetary policies, and economic stagnation continue to constrain the sector’s performance.

Since 2020, the reintroduction of the Zimbabwean dollar and exchange rate volatility have exacerbated liquidity mismatches and heightened credit risks. Commercial banks face increased pressure to manage deposit volatility, maintain capital adequacy, and adapt to regulatory changes implemented by the Reserve Bank of Zimbabwe (RBZ). Despite technological advancements in banking services, such as the growth of mobile banking, economic uncertainties and public mistrust persist, limiting the sector’s ability to support economic growth. Recent studies emphasize that macroeconomic stability, particularly in inflation control and exchange rate management, is critical for rebuilding confidence and enhancing the resilience of Zimbabwe’s banking sector (RBZ, 2021; IMF, 2021).

The post-2020 period highlights that without consistent economic policies and structural reforms, Zimbabwe’s commercial banks remain vulnerable to external shocks. Addressing fiscal deficits, ensuring exchange rate stability, and fostering economic growth are vital steps for restoring the sector’s stability and strengthening its role in the economy (Mambondiani, 2020; IMF, 2021).

LITERATURE REVIEW

Theoretical Literature Review  

Deflation Theory

The current study follows the deflation theory as outlined by Irvine Fischer 1933. According to Fischer (1933), the deflation theory view the decrease in general price levels to bring about depreciation in the net value of businesses and investments, which further lowers profitability, thereby triggering bankruptcies and other forms of business collapses. Therefore, interest rates which move hand in hand with price levels are characterized by various fluctuations which bring about loss of value of money. These fluctuations and volatility of profitability determinants as regarded as forces within the external (operating) environment and internal environment which exert influence on the degree of over indebtedness between creditors and debtors which ultimately result in default in loan repayment. This default in turn hampers on bank profitability and its financial performance at large. Higher inflation leads to higher profitability when it is well anticipated as interest rate is quickly adjusted and vice versa. In view of this study, the theory postulates that decreased inflation brings about reduced revenue of banks and ultimately reduced bank profitability which eventually lead to banks running into bankruptcy. This varies with the expectation that higher inflation (that is price levels) leads to losses in the purchasing power of money and increase in operating costs and further the interest rates in the banking industry and economy at large. As a result of this loss of purchasing power of money and reduced value of money, the growth of the country’s economy is hampered and thus, hence negatively impacting on GDP growth of the country (Pandey, 2009).

Interest rate Parity Theory

While on the same note, the study is underpinned by the Interest rate Parity Theory which propounded by John Menard Keynes (1936). The theory is of the notion that the variations in the rate of interests between one nation’s currency and that of its counterparts in other countries who trade across borders account for the fluctuations in the nominal rate of interest. The theory rests on the notion of the differences in interest rates of other economies and the local economy. Parity condition rests on the idea that the differences in interest rate for 2 different currencies is accounted by a discount or premium for the forward rate of exchanges on the foreign currency whereby there is no trading activity as regarding selling and buying of currency in the market (Bhole & Dash, 2002).

This theory relates the existence of parity which performs a vital function in banking transactions. Banks charge interest on loans to make profits to sustain market share and perform their role of intermediation efficiently. Thus, the financial performance banks is often affected by the rate of interest charge on loans. Increased interest rates lead to higher profitability while decreased interest rates leads to lower profitability and hence poor financial performance of banks.

Empirical Studies of Macroeconomic Factors on Financial Performance  

This review examines existing studies on the impact of macroeconomic factors on financial performance across different regions. By analysing the findings of these studies, this review aims to identify common trends, highlight discrepancies in results, and unearth gaps in the current knowledge base, particularly how macroeconomic factors are affecting financial performance of Zimbabwean’s commercial banks.

Sharif (2023) examined the impact of macroeconomic variables on the financial performance of Islamic banks, using Return on Equity (ROE) as the performance measure. The study found that 83% of the variations in financial performance were attributed to changes in macroeconomic factors such as economic growth, public debt growth, inflation, foreign direct investment, and balance of payments. The remaining 17% of the variations were explained by other factors not included in the model.

While on the same note, Ali (2020) explored the influence of macroeconomic factors, including GDP, interest rates, inflation, exchange rates, and money supply, on the profitability of commercial banks in Pakistan from 2006 to 2018. Using panel data estimation techniques and profitability measures like ROA and ROE, the study revealed that these macroeconomic factors had a negligible impact on the financial performance of banks.

Moving on, Gautam and Gautam (2021) investigated the predictive power of macroeconomic indicators such as GDP, interest rates, inflation, and unemployment on the financial performance of Nepalese commercial banks over a ten-year period. The study employed OLS estimation and found that GDP significantly influenced ROE but had no significant effect on ROA. Other factors, except for unemployment, also demonstrated a meaningful impact on financial performance.

Another research by Jackson, Barrie, and Johnson (2021) analysed the impact of inflation and exchange rates on commercial bank performance in Sierra Leone using ARDL models. Their findings indicated that inflation positively affected banking sector performance, whereas exchange rate fluctuations had a destabilizing contagion effect on the economy.

Merko and Habili (2023) assessed the impact of interest rates, exchange rates, and inflation on the financial performance of commercial banks in Albania, focusing on ROA as a dependent variable. The study, which utilized monthly data from 2015 to 2022, concluded that exchange rate variability negatively affected ROA, while interest rate changes had a significant positive influence. Inflation, however, showed no measurable independent effect on performance.

Idawati, Pangestu, and Bambang (2023) then conducted a literature review to evaluate the relationship between macroeconomic variables such as interest rates, inflation, exchange rates, and economic growth and the profitability of Indonesian commercial banks. The review emphasized the significant influence of interest rates, inflation, and economic growth on bank profitability.

Moyo and Turgut (2020) examined the effects of inflation and exchange rates on the financial performance of the largest four commercial banks in South Africa between 2003 and 2019. Using ARDL, FMOLS, and DOLS models, the study found an inverse relationship between inflation and ROE, while the exchange rate showed a weak impact on financial performance.

Sukana, Manga, and Abubakar (2022) investigated the impact of inflation on the ROE of commercial banks in Nigeria from 1999 to 2018. The study employed ARDL models and found an insignificant yet positive relationship between inflation and ROE, indicating limited influence of inflation on bank performance during the study period.

Ndungu, Mwangi, and Githinji (2022) examined the relationship between macroeconomic factors and the financial performance of commercial banks in Kenya from 2009 to 2018. Their research revealed that interest rates and exchange rates significantly influenced bank performance, while GDP and inflation had a minimal impact on financial outcomes.

Sarkar and Rakshit (2024) examined the role of unemployment in influencing the performance commercial banks in India that were operating from 2001 to 2017. The study employed the GMM estimation method, and their study concluded that unemployment has a significant positive association with financial performance of commercial banks in India.

Tuffa (2018), undertook research to examine the effect of change in exchange rate on the financial performance (ROE) of private commercial banks in Ethiopia, using a sample of eight (8) private commercial banks over a fifteen-year period (2002-2016). Regression analysis was used to quantitatively examine the data. The results showed that exchange rate fluctuations have statistically significant positive impact on financial performance of private commercial banks in Ethiopia.

In their Collaborative research, Hossin and Mondol (2020), examined the effects of exchange rate fluctuations on financial performance state owned commercial banks in Bangladesh. The research additionally incorporated inflation and interest rates as independent variables and measures of central tendency were used as descriptive statistics to describe the data. described using measures of central tendency. The research concluded that exchange rate fluctuations and financial performance had a weak negative association while having a positive association between inflation and financial performance of commercial banks in Bangladesh.

METHODOLOGY

Model Specification

To examine the relationships between Return on Equity and macroeconomic factors a dynamic panel data model was adopted from Makumbe et al (2020). The model was then estimated using the difference Generalised Methods of Moments (GMM) approach originated by Hansen (1982), which was improved by Holtz- Eakin et al., (1988), Arrelano and Bover (1995) and Blundell and Bond (1998). Dynamic panel data are most preferred since it is not arbitrary but based on the sample size. Unlike static models, dynamic panel data models express a data generating process (DGP) that depends on its past values and current and past values of explanatory variables that are not strictly exogenous. The inability to incorporate past realizations on current values makes the static panel data model weak for inference Makumbe et al (2020). In general, a dynamic panel data is expressed as:

logπ_it=γy_i,t-1+X_it β+α_i+v_it……………………………….1

Where.

X_it is the vector of regressors

α_i is the individual specific effects

v_it is the error term with zero mean constant variance and uncorrelated with time and individuals

γy_i,t-1 is correlated with  since the past values already depend on individual effects

The GMM estimated model therefore becomes.

logπ_i1=γ_πi,t-1+β₁ log_^inft+β₂ log^gdp_t-1+β₃ log^fer_t+β₄ loglir_t+β₅ logune_t+v_it…………………………….2

Financial performance of any organization is proper utilization of its financial resources to generate revenue. To achieve this, it is relied upon comparison between individual financial variables with other industry benchmarks and other macro-economic variables Anshu & Gakhar (2019). Financial performance for this study was represented by return on Assets (ROA) obtained from the commercial banks audited and published financial statements. Return on Assets was chosen as a key measure of financial performance of commercial banks                       due to its established importance supported by extensive usage in economic and financial literature and widespread usage in field research of banking. Return on Assets as financial performance measure is driven by its ability to show how management effectively shareholder’s funds and it quantifies the rate of return going to the bank’s shareholder’s and the net benefit the shareholders get from investing their capital in the bank Sukana, Manga, & Abubakar (2022).

Meanwhile, in this study will make use of macroeconomic factors which are Inflation, Gross Domestic Product, Exchange rate, Unemployment, and Interest rate as explanatory variables. Macroeconomic circumstances and interventions adopted by any government & its central bank can stimulate profitability of banks. To monitor the financial stability central bank focus on macroeconomic and various FSIs (Financial stability indicators). Therefore, the performance of banks in any nation’s economy plays a significant role in its growth (Maria et al.,2002, 2004, 2007 cited by Anshu & Gakhar, 2019).

Sources of Data collection

Table 1: Data description and sources

Financial performance of any organization is proper utilization of its financial resources to generate revenue. To achieve this, it is relied upon comparison between individual financial variables with other industry benchmarks and other macro-economic variables Anshu & Gakhar (2019). Financial performance for this study was represented by return on assets (ROA) obtained from world bank data indicators, ROA is the major ratio that presents the profitability position of a bank. It is calculated as a ratio of Income to its total asset (Khrawish, 2011). It also indicates the ability of the bank management. Banks generate income by utilizing company assets at their disposal. In other words, it shows how banking sector is efficiently earning with the proper utilization of its assets. Wen (2010) stated that a higher ROA indicates that the company is more efficient in using its resources. In the present study we have measured the financial performance in terms of ROA.

Meanwhile, in this study will make use of macroeconomic factors which are Inflation, Gross Domestic Product, Exchange rate, and Interest rate as explanatory variables. Macroeconomic circumstances and interventions adopted by any government & its central bank can stimulate profitability of banks. To monitor the financial stability central bank focus on macroeconomic and various FSIs (Financial stability indicators). Therefore, the performance of banks in any nation’s economy plays a significant role in its growth (Maria et al.,2002, 2004, 2007 cited by Anshu & Gakhar, 2019).

Diagnostic Tests

• Serial correlation: Breusch- Godfrey Serial Correlation to check serial correlation.
• Heteroscedasticity: Breusch-Pagan-Godfrey test is used to check the Heteroskedasticity in time series.
• Autocorrelation Test: Durbin-Watson Test is the most applied test for the existence of autocorrelation between
• Stationarity Test: Augmented Dickey Fuller test for the panel root test

RESULTS AND FINDINGS

Descriptive statistics

Summary statistics and correlation matrix are reported in Tables 2 and 3 respectively.

Table 1: Normality Test

Source: E views 12

Table 2: Descriptive Statistics

Source: Author Compilation

From table 2 above all the mean and median of all variables are statistically significant. The difference between the maximum and minimum values of each variable indicates that the time series data for the variables fluctuates dramatically. LGDP have a JB statistic of 0.780734, an exceedingly high value indicating that the observed JB statistic is entirely consistent with the residuals being normally distributed. The results show convincing evidence that the residuals are normally distributed. The same applies to LEXR, LINF, LIR, LROA and LUNE. The extremely high values of Jarque-Bera statistic suggest that LROA is likely to be normally distributed. Furthermore, Kurtosis is above 3 on most occasions and the absolute value of skewness is close to greater than 1 indicating that the data have steep distribution. Since the p-value is much higher than the common significance levels (0.05 or 0.01), we fail to reject the null hypothesis of normality for LROA.

Table 3: Correlation Matrix

The results of the correlation analysis are presented in the table above. Among the variables, GDP emerges as a central factor, displaying moderate to strong relationships with several other indicators—most notably, Interest Rates and Inflation. Interest Rates show a consistent negative correlation with key economic and financial performance metrics such as GDP and Return on Assets (ROA), suggesting that higher rates may dampen both growth and profitability. Unemployment is negatively correlated with both the Exchange Rate and ROA, potentially indicating underlying macroeconomic weaknesses. Inflation exhibits a mixed pattern of association, showing moderate links with both economic growth and interest rates.

Augmented Dick Fuller Test

The Augmented Dickey-Fuller (ADF) test checks for stationarity. If the test statistic is more negative than the critical values, we reject the null hypothesis (which states that the variable has a unit root). A p-value less than 0.05 also indicates stationarity.

Table 5: Unit Root of Stationarity Levels

N.B.: *, **, and *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

Source: Author’s computations from E-views 12

In table 5 above specifies stationarity of each variable can be observed. The variables LROA, LINF and LGDP were stable at 1% significance level after the first-order difference. The variables are all integrated to order one I (1) with p-values less than 0.05. Further, table 4 below shows the outcomes of the unit root test under the null hypothesis that there is a unit root. We reject the null hypothesis that there is a unit root if the Augmented Dickey Fuller (ADF) statistic exceeds the test critical values or if the p value is less than 0.05 at the specified level of significance; otherwise, we fail to reject. Under the null hypothesis that there is a unit root problem against the alternative hypothesis of variable stationarity, this study used the Augmented Dickey Fuller test to determine the stationarity levels of the variables in the model. The results reveal that only LUNE and LEXR were stationary at level at 10 % significance level, with p-value above 0.05. Meanwhile, LIR was stationary at 5 percent.

Ramsey-Reset Test

The Ramsey Regression Equation Specification Error Test (RESET) is used to detect functional form misspecification in a linear regression model. It tests whether non-linear combinations of the fitted values help explain the dependent variable, suggesting potential omitted variable bias or incorrect functional form. Therefore, results are discussed as follows:

DISCUSSION OF REGRESSION RESULTS

Macroeconomic Determinants:

1. Exchange Rate (LEXR):

• Negative and significant (p = 0.025): Suggests depreciation of the local currency is detrimental to bank performance.
• May reflect increased foreign liabilities or cost of imports for banks.

2. GDP (LGDP):

• Positive and significant (p = 0.011): A growing economy supports bank profitability, likely through increased lending, investment, and reduced default rates.

3. Inflation (LINF):

• Negative coefficient, marginally significant (p = 0.059): High inflation could erode real returns or disrupt credit markets.

4. Lending Rate (LLR):

• Positive but insignificant (p = 0.131): High rates might signal risk premiums, but also increased income from interest – unclear net effect here.

5. Unemployment (LUNE):

• Strongly negative and significant (p = 0.010): High unemployment harms financial performance, potentially through increased loan defaults and reduced demand for banking services.

Overall Model Evaluation:

• R² = 0.878: The model explains nearly 88% of the variation in bank performance – an excellent fit for macroeconomic data.
• F-statistic (p = 0.034): Model is statistically significant as a whole.
• Durbin-Watson = 2.43: Suggests no autocorrelation in residuals.
• FITTED² term: Included for RESET test, not significant, but highlights potential model nonlinearity.

Difference GMM Estimation Results

This section presents and discusses the estimated results, starting with difference-GMM estimates and then related diagnostic tests.

Table 6: Difference GMM Estimation Results

Source: Author Compilation Eviews 12

Interest rates are usually a driver to profitability amongst banks across the globe. Zimbabwe commercial banks have experienced a positive relationship with a coefficient of 23.98527 which is statistically significant at 1% towards financial performance of commercial banks in Zimbabwe. High interest rates deter borrowing to finance the productive sectors of the economy. Zimbabwean economy has been punctuated with high inflationary periods that had driven interest rates to rise thus hurting consumption and production expenditure. The finding aligns with the results reported by Arkangelo et al, (2021), where interest had a positive and significant impact on the performance commercial banks in South Sudan. Meanwhile, (Ally, 2022; Noorani, 2022, Mehta, 2019) found out that in ideal cases interest rates usually have a negative relationship with financial performance. This is largely driven by stable macroeconomic factors which promote investment, production and consumption expenditure to grow the economy.

Furthermore, the results revealed that inflation has a negative relationship to financial performance of commercial banks in Zimbabwe. Inflation variable was -0.180418 with a significant probability test of 0.10068.  Inflation hurts growth in any sector and in Zimbabwe for the past three decades has led to capital flight and less foreign direct investment in the domestic economy. The persisting high inflationary environment has contributed to closure of banks in local economy. Due because of inflation banking products have been elusive for Zimbabweans making them unattractive even for local investors. Moyo & Turgut (2020) also found out that inflation led to an inverse relationship with financial performance of commercial banks in South Africa. However, Jackson et al, (2021) found out that inflation was positively associated with financial performance of commercial banks in Indonesia. Similar findings were also reported by Hossin & Mondol (2020), who found a positive relationship between inflation financial performance of commercial banks in Bangladesh.

LGDP has a positive coefficient of 1.248235 with a probability t-statistic of 0.0173 indicating a positive relationship with financial performance. However, in Zimbabwe there has been an unprecedented economic decline due to a lot of macroeconomic instability and popular policies which neglected growth overall. Similarly, Gikombo & Mbugua, (2018), who examined the effect of selected macroeconomic variables on performance of listed commercial banks in Nigeria concluded that there was a positive relationship between GDP and financial performance of listed commercial banks in Nigeria.

The research shows there is a negative relationship between exchange rate volatility and financial performance of commercial banks in Zimbabwe with a coefficient of -2.144145. Zimbabwe has been plugged with fluctuating exchange rate which is inflationary thus affecting profitability of banks. This result is consistent with findings from other researchers like Haile, (2019) who also found an inverse relationship between exchange and financial performance of commercial banks in Ethiopia. Nguku (2019), also found a negative relationship between exchange rate and financial performance of commercial banks listed on Nairobi Stock Exchange. This also appears to be the same result shown by Njagi & Nzai, (2022), who also concluded that exchange rate had an adverse effect on financial performance of commercial banks in East African Community. However, research conducted by Tuffa, (2018), on the effect of exchange rate on the financial performance of private commercial banks in Ethiopia, has shown that exchange rate had positive impact.

Lastly, unemployment showed negative relationship towards financial performance with a negative coefficient of -12.98291, which is statically significant at 1%.  The poor economy which has been prevailing since mid-1990s during the chaotic implementation of the ESAP led to gradual collapse of the formal economy. Closure of companies and relocation of major companies across all sectors has contributed to unemployment growth over the years. It has been worsening by populist policies that government has pursued over the years thus enhancing the informal sector to grow predominantly and the elevated levels of informality in Zimbabwe have become detrimental to inclusive and sustainable development. Commercial banks have faced unbankable public and a dominant informal sector which transact on cash basis excluding the banking sector thus affecting profitability overall. The above results are consistent with Haile, (2019), who found an inverse relationship between unemployment and financial performance of commercial banks in Ethiopia. However, a study carried out by Sarkar & Rakshit (2024), have shown that unemployment has significant positive impact on the performance of commercial banks in India.

CONCLUSION

This paper provides new econometric based evidence on role of macroeconomic factors on performance of commercial banks in Zimbabwe. The study is revealing that macroeconomic factors have had impact on overall performance of the banking sector in Zimbabwe. The empirical outcomes, inflation is said to manifest positive effect on banking sector performance, while the effect on Exchange Rate is negative on the overall economy. Equally, even though Inflation acts as a drag on performance, banks are normally compelled to shift resources from more productive activities in a bid to focus on profit and losses from currency inflation. Meanwhile, a volatile exchange rate affects profitability of banks. A non-functioning economy has ripple effects towards the uptake of the financial products and overall performance of the banking sector.  A toxic macroeconomic environment chases away foreign direct investment, off shore capital and it also makes working capital for the productive sector very expensive. Further the study reveals that high inflation rates and high interest rates poses danger to collapse the entire economy and limits borrowing.

Therefore, the study makes the following recommendations;

First and foremost, government of Zimbabwe has to solve the challenges that are facing the entire economy. The poor macroeconomic instability facing the country also weighs down heavily to the banking sector. Due because of the poor economic environment and perceived risk tied to the country local commercial banks are facing significant challenges to attract fresh capital from the international market.

Secondly, government of Zimbabwe needs to solve inflation and exchange rate fluctuates that continue to hurt the entire economy. Since inflationary pressures are common occurrence to an economic system, which normally influence the performance of commercial banks, this indicate that both the monetary authorities the Reserve Bank of Zimbabwe (RBZ) and Ministry of Finance and Economic Development (MoFED) should endeavor to address exchange rate crisis as a way of harnessing the potential of the banking system to contribute meaningfully to stable economic growth. In this regard, effort must be made to build national capacity towards stabilizing and improving confidence of the local currency as well as ramping up production of essential goods and services, which on the whole, will reduce high demand for exchange rate in settlement of meeting huge import bills and their rapid pass-through effect to prices, which ultimately leads to inflationary pressure in the domestic economy.

Macroeconomic instability for the past decades have led to accumulation of debt due to inability of the country to pay for production loans to World Bank, IMF and the Pairs Club. This debt overhang for the country has negatively affected the financial sector of the country as it was unable to borrow fresh capital to finance, investment, production and infrastructure development. Currently, the debt is sitting on USD21 billion (National Budget, 2025). According to IMF (2017) Zimbabwe is in debt distress, and its total public and external debt is unsustainable. With longstanding external arrears, foreign financing has been scarce, and large fiscal deficits are lately being financed through domestic borrowing. Domestic debt, which was negligible for a very long time period, has increased sharply to more than 25 percent of GDP, and is on an unsustainable trajectory. Therefore, there is need for the country to decisively address the debt overhang which is engulfing the whole country. Attaining debt sustainability would require sharp fiscal consolidation and external support from the international community. Therefore, the government of Zimbabwe needs to address the debt crisis facing the entire economy.

Going forward, the unprecedented economic decline due to macroeconomic instability and popular policies has neglected growth gradually. High inflation, exchange rates, interest rates led to decline in production and company closures and leading to increased levels of unemployment.  The gradual growth of unemployment has negatively impacted the entire economy hence the informalisation of the economy. Almost above 80 percent of economic activities are being performed by the informal economy. A large informal sector is debilitating towards the banking sector because it doesn’t have bank accounts, they also doesn’t make use of financial products to enhance financial inclusion and chief most setback is that it prefers to sell and trade exclusively in US dollar and South African Rand. Government of Zimbabwe should address the informalisation of the economy with immediate effect. For government of Zimbabwe to attain its vision and sustainable economic development there is need for them to put together sustainable policies that propel the formal sector upwards.

While on the same note, government has to solve high unemployment levels being experienced across all sectors of the economy. Zimbabwe is perceived to have high unemployment rates above 80 percent. Generally the bulk of the economically active Zimbabweans are unbanked. By opening the economy through implementing sustainable policies that encourage foreign direct investment and opening of closed industries will boost employment. A working class usually has a positive effect towards the uptake of banking sector products.

Lastly, a robust study using Panel Data Econometrics should also be pursued, where individual banks are assessed so as to give an accurate picture of the macroeconomic factors to their performances with respect to profits and associated risks. In this regard, panel data econometrics will reveal insulation measures that individual banks adopted to proof themselves against risks tied to the decaying economy. This will serve as a complement to regular stress testing operations carried out in address risks to the country’s financial system.

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