Effects of Macroeconomic Variables On Performance of Listed Firms at Dar es Salaam Stock Exchange, Tanzania

Purpose: This article analysed the effect of macroeconomic variables on 21 DSE-listed firms from 2006 to 2021 due to past inconclusive results from other research across the globe. Methodology: Mixed-sequential explanatory research design was used. Secondary panel data were collected from DSE while qualitative data was collected via semi structured interviews. Random effect model and thematic analysis were utilized for data analysis. Findings: The study found that GDP, inflation, and money supply had significant positive coefficients, while interest rates and exchange rates had significant negative coefficients, indicating that macroeconomic conditions have a substantial effect on firm performance. Practical implications: The findings suggest that firms should proactively manage macroeconomic conditions to remain competitive and sustainable Originality/Value: The study's uniqueness lies in its use of qualitative data to support quantitative findings and its examination of the link between macroeconomic conditions and listed firm performance in Tanzania, where little similar research has been conducted.

exchange rate, and inflation rate (2018). According to the findings of Ismail et al. (2018), GDP and interest rates positively impact the performance of Malaysian firms.
In an African context, the effect of macroeconomic conditions on corporate performance has also been explored. Gatsi et al. (2013) investigated firm performance in Ghana and discovered that fluctuations in the country's currency rate, interest rate, and inflation rate were positively connected with firm performance. Omodero and Mlanga (2019) found a negative correlation between company performance, interest rates, and currency exchange rates in Nigeria. In their 2015 analysis, Simiyu and Ngile discovered a negative association between publicly traded enterprises in Kenya and GDP growth. In contrast, Kolapo et al. (2018) found a positive correlation between GDP and money supply and firm performance in the Nigerian economy, whereas earlier study proved the opposite. There is a paucity of study on how changes in Tanzania's macroeconomic environment affect the performance of publicly traded enterprises.
For instance, Epaphra and Salema (2018) and Gwahula (2018) analyzed stock prices and stock market performance, but their evaluations of the factors (inflation rate, GDP, money supply, and exchange rate) revealed contradictory results.
The relationship between macroeconomic conditions and firm performance is complex, as demonstrated by the inconsistent results from previous research.
Inflation, interest rates, currency exchange rates, and GDP are some of the macroeconomic factors that can significantly impact a firm's finances, which are outside the control of management. Such impact arise due to the fact that the firms operate within the vicinity of such macroeconomic conditions and they have no way to escape or manipulate them but rather they can only cope or stand to be wiped out.
As such It is crucial for firms to understand the context-specific influence of these factors and adjust their strategies accordingly. Policymakers and business leaders must comprehend the connection between macroeconomic factors and corporate performance to make informed decisions that promote a healthy economy.
Additionally, further research is needed to provide further elaboration into the inconsistencies and develop suitable macroeconomic policies Consequently, the primary objective of this article was to investigate the macroeconomic determinants influencing the performance of DSE-listed enterprises.
By comparing firm performance to macroeconomic variables such as interest rate, exchange rate, inflation rate, money supply, and GDP, the purpose was achieved. This lead to testing the subsequent hypothesis: The performance of Dar es Salaam Stock Exchange-listed companies is affected by macroeconomic conditions.

Theoretical Underpinnings of Paper
The research was guided by Open Systems Theory (Bertalanffy, 1969), which states that "organizations operate in an open context in which their activities are significantly affected by macroeconomic forces in the environment." The organization has no control over the macroeconomic forces in their entirety. Firms must contend with macroeconomic forces such as the interest rate, currency rate, money supply, inflation rate, and GDP.
This idea demonstrates that an organization cannot succeed on its own and must instead rely on the macro economy. Firms must both adapt to their environment and capitalize on the risks associated with interactions (Owolabi, 2017;Laszlo & Krippner, 1998;Buckley, 1967). Bertalanffy (1969) asserts that managers of enterprises must be cognizant of their surroundings and how it influences corporate performance. In essence, we might argue that a firm's ability to respond and adapt to an ever-changing environment is contingent on its macroeconomic environment.
The firm's problems stem from the fact that it will always play a reactive role with regard to the fluctuations in macroeconomic variables; it has no control over inflation or exchange rates, and the only option it has when such variables shift is to respond to the changes with complex solutions that are within the vicinity of its existing resources, which can ultimately have a negative impact on firm performance.
Theoretically, organizations will have a competitive edge if their organizational structure is well-aligned with their external environment. This is due to the fact that external/macroeconomic forces may always influence their performance.

Research Methodology
This report is based on a study employing a mixed research approach with an explanatory sequential layout. This strategy includes tools for qualitative and quantitative data collection, analysis, and interpretation (Creswell & Plano Clark, 2011). The concept of multiple approaches was chosen since it yields more dependable and valid findings than a single method (Bentahar & Cameron, 2015). Using a combined research technique, however, makes it easy to verify data from both methods (Creswell, 2013). Using this strategy, a researcher collects both quantitative and qualitative data. In the second step of data collection, the researcher collects qualitative data after acquiring quantitative data for validation. The quantitative data gathered during the initial phase of data collection are related to the qualitative data collected during subsequent phases. (Bryman & Bell, 2015).

Model Specification and Data Analysis
Multiple linear regression was performed in order to undertake an analysis of the data.
Based on the study questions, an interview guide was prepared for qualitative analysis.
In order to make sense of and utilize the acquired data, theme analysis was applied to the data analysis process. The process of thematic analysis involves identifying, analyzing, and presenting a comprehensive account of the collected and identified topics (Braun & Clarke, 2006). Previous research on the macroeconomic variables that influence firm performance yielded five pre-established themes. The topics covered exchange rate, interest rate, inflation rate, money supply and GDP.

Data Type and Sources
For qualitative data collection, semi-structured interviews were used. It is thought that the strategy is adaptable and compatible with numerous data-analysis techniques.
Using this method, the researcher conducted interviews with a subset of participants and allowed them to respond freely to the interview questions (Bryman, 2016 (Baltagi, 2005). Panel data were used because they may combine cross-sectional and time series dimensions, eliminate measurement challenges caused by omitted and unobservable variables, and produce more trustworthy and generalizable conclusions than cross-sectional and time series data alone (Biorn, 2017;Woodridge, 2002

Sampling and Sample Size
Nine respondents, including two regulators(R) named R1 and R2 and one broker (B) sampled purposively and named B1, participated in semi-structured interviews. In addition, data was collected from six listed firms (F) acquired from two clusters, namely four from the MIM window out of sixteen firms (called F1, F2, F3, and F4), and two from the EGM window out of five listed firms that were available during the data collection period (named F5 and F6). Due to the considerable information, experience, and skills that the sampled respondents have regarding the issue of the study, a diverse group was sampled to provide key informants. In conducting interviews, ethical problems and methods that protected the anonymity, privacy, and dignity of interviewees were taken into account (Bryman, 2016).
The researcher selected firms to participate in the study using a census-like method in which all locally listed businesses were considered for inclusion. This is because there were just a few of companies listed on the DSE, and deleting some of them would lower the quantity of observations, so calling into doubt the veracity of the conclusions.
Therefore, the sampling frame includes all 21 local enterprises that were trading on the DSE at the end of 2021.

Several financial indicators, including Return on Assets (ROA), Return on Equity
(ROE), Return on Sales (ROS), and Sales Growth (SG), have been used to analyze firm's perfomance (Tangen, 2003). In this study, the ratio of ROA to firm performance served as the dependent variable. This is due to the fact that ROA is the most commonly used financial ratio to evaluate performance, since it measures the ability of corporate managers to use firm assets to generate profits for the organization (Liargovas and Skandalis, 2010). Other academics have utilized ROA as a way for measuring firm performance (Issah and Antwi, 2017;Kanwal and Nadeem, 2013). Equation (ii) contains the utilized ROA formula =

………………………………………………………………………………………………. (ii)
According to the World Bank Report (2019) and Ngowi (2015), the macroeconomic variables that have the greatest influence on company performance are the exchange rate, the GDP, the interest rate, the inflation rate, and the money supply. In this study, these variables, as well as firm size, age, and business diversification, served as control variables. Table 1 depicts the variables and their projected values. Profit before tax/ Total Assets Dependent

Gross Domestic Product (GDP)
Final output of goods and services. Independent (+/-)

Interest Rate (IR)
Interest rate during the year computed by Bank of Tanzania (BOT)

Inflation Rate (IFR)
Consumer Price Index (CPI) annual percentage changes.

Money Supply (MS)
Volume of Tanzania Shillings in the economy Independent (+/-)

Exchange rate (EXR)
Exchange rate during a year between USD and TZS Independent (+/-)

Firm Size (FS)
Natural logarithm of total assets in the period

Firm Age (FA) Geographical diversification (GDiver)
Number of years since incorporated till the period of study 1 for some diversification; 0 for none Control Control

Diagnostic Tests
The null hypotheses of normality, multicollinearity, heteroscedasticity, and autocorrelation were examined using diagnostic tests. These tests were conducted before the regression analysis to determine whether or not the data satisfied the requirements for the regression analysis. (Kennedy, 2008;Bryman & Cramer, 2001).
Normally distributed data are said to have a skewness of 0 with an acceptable range of 5, the results of this study indicated that the skewness of ROA was within the acceptable range of skewness (-0.72) and that the kurtosis value was also within the acceptable range (2.74), favoring normality and other variables falling within the acceptable range for skewness and kurtosis respectively.

Multicollinearity Test
Using a Pearson correlation matrix, the multicollinearity hypothesis was examined.
When the correlation coefficients between variables are either 0.90 or 0.90, multicollinearity is presumed to occur. (Field, 2013). When two variables are highly correlated, multicollinearity axioms are violated. Since both variables measure the same effect, one must be deleted to reduce redundancy. Table 2 displays the Pearson correlation matrix for the variables under investigation.

Table 2: Pearson Correlation matrix for independent and dependent variables
Since there was no reason to be concerned about multicollinearity between the variables in Table 2, all of them were preserved. This was demonstrated by correlation coefficients that were within the allowed range (+0.9 or -0.9). Moreover, Variance Inflation Factors (VIFs) were utilized to assess multicollinearity. As seen in Table 3, multicollinearity was not an issue, as the VIF values were less than 10. This result is supported by Gikombo and Mbugua (2018). According to them, VIF must exceed 10 if there is a multicollinearity concern.
Variables ROA

Heteroscedasticity Test
In addition, heteroscedasticity was evaluated by searching for residuals with constant variance. The Breach-Pagan/Cook-Weisberg test was used to determine whether or not this assumption was valid. According to Biorn, the heteroscedasticity assumption is met when the p-value is greater than 0.05. (2017). the chi2-statistic p-value for ROA (3.68), which was 0.0652, exceeded the significance level of 0.05. Therefore, the null hypothesis was correct, and ROA did not have an issue with heteroscedasticity.

Autocorrelation test
In addition, autocorrelation was investigated. The autocorrelation assumption is satisfied when the values of identical variables do not vary in the same way across time (Pallant, 2010). This demonstrates that historical values cannot be used to predict the future. Using the Wooldridge (2002) test, this assumption's validity was determined.
If the p-value is more than 0.05, the hypothesis is valid. In this investigation, the pvalue of the F-statistic (0.182) was 0.6739, which exceeded the significance threshold of 0.05 for ROA. Therefore, the validity of the null hypothesis was confirmed. As a result, ROA experienced no issues with first-order autocorrelation.

Hausman test
The Hausman Specification Test was utilized to pick between the Random Effect (RE) model and the Fixed Effect (FE) model during data analysis. The RE model implies the group's average score is randomly selected from the population, whereas the FE model believes the group's average score is fixed.  The difference between Prob>chi2 and the alpha level threshold of 0.05 is 0.9321, which is greater than the significance level of 0.05, as shown in Table 4. This suggests that the null hypothesis (Ho) was true and that coefficient differences were not consistent. This demonstrates that each company's faults were distinct, ad hoc, and unrelated to its performance. Therefore, it was found that the random effect model was adequate for our investigation.

Descriptive statistics on macroeconomic variables and performance of firms
The purpose of the study was to examine the effect of macroeconomic conditions on the performance of publicly traded companies. Both dependent and independent variables were examined. To provide a thorough overview of the variables, a descriptive analysis was performed, which included the computation of means, standard deviations, minimum and maximum values. Table 5 contains descriptive data for the dependent variable (ROA), the independent factors (GDP, interest rate, inflation rate, money supply, and exchange rate), and the control variables (firm size, firm age, and geographic diversity).

Table 5: Descriptive results on independent and dependent variables
The average value of the dependent variable (ROA) in Table 5

Regression analysis results on macroeconomic variables and firm performance
The researcher conducted a regression analysis utilizing the Random Effect model as a reference point to estimate the impact of macroeconomic conditions on the performance of DSE-listed enterprises. Three estimations, labelled 1, 2, and 3, were conducted to determine the reliability of the model's results. To see if the findings remained unchanged, control variables were subtracted from each estimation. Table 6 provides a summary of the results of the analyses. Standard errors in parentheses Key: * Significant at 10%, ** significant at 5%, *** significant at 1% Regarding Gross Domestic Product (GDP), Table 6 The findings given in Table 6 indicate that interest rate (IR) has a substantial negative connection with company performance. In all three estimates of the baseline model, the outcomes were consistent. The findings suggest that as interest rates rise, investors gravitate toward fixed-interest investments (treasury bills and bonds) in the context of capital markets (share). In addition, an increase in the interest rate raises the cost of borrowing for businesses, which reduces their profit margins and, ultimately, their performance. These results are consistent with those of other researchers (Alibabaee & Khanmohammadi, 2016;Ismail et al., 2015). On the other hand, the results contradict the findings of Ismail et al. (2018) and Gatsi et al. (2013), who demonstrated that interest rate had a considerable beneficial effect on business performance. This discrepancy may be attributable to varying economic policies in the nations where study was conducted.
Similar to these findings, a number of interviews with various key informants revealed that the rise and fall of IR has both positive and negative effects on the firm's performance, in the sense that when interest rates rise, it encourages investors to switch to fixed investments, which reduces the firms' liquidity. In addition, an increase in IR on borrowing raises corporate borrowing costs, causing firms to use a portion of their profits to repay bankers, so reducing their performance. In support of this, a senior official from a publicly traded company was quoted as saying, "The higher the interest rate, the higher the cost of borrowing, which can have a detrimental impact on a company's growth and consequently its performance" (Firm representative, December, 2021).
According to the findings presented in Table 6, IFR had a favorable and statistically significant influence on business performance. The results were consistent across all three estimations of the baseline model. The data suggest that inflation expectations increase money supply. Consequently, as inflation is anticipated, an increase in prices would also boost earnings, leading firms to pay more dividends and thereby increasing the price of shares, which will result in an overall improvement in firm performance. As a means of validating these findings, interview sessions with several key informants indicated the same trends, namely that inflation rate damaged the performance of enterprises since it pushed up high expenses quicker than firms could pass them on to customers. This could have a detrimental effect on company earnings. In addition, Table 6's findings regarding money supply reveal that money supply had a favorable effect on business performance, and the results were consistent across all three estimations. The results indicate that an increase in money supply has cascading consequences on the economy. As the money supply grows, it produces a rise in the demand for money and the expansion of economic activity, as well as an increase in cash flows that leads to a rise in stock values. In a similar manner, economic expansion coming from increasing stock money growth causes firms to expand their operations, resulting in larger sales and profitability, and subsequently a higher dividend payout, which is indicative of improved firm performance. The outcomes concur with those reported by Haider et al (2018).
The results of Exchange Rate (EXR) as shown in Table 6 suggest that EXR rate had a significant negative effect on firm performance, and this pattern was observed in all three estimations conducted with the baseline model. The findings suggest that currency stability has a bigger impact on business performance in the sense that it attracts international capital market investors. And vice versa, the greater the influx of foreign investors, the more stable the currency. Similarly, the higher the EXR, the weaker the performance of local enterprises engaged in international trade. These results parallel those of Rehman (2016), Gatsimbazi et al. (2018), andZeitun et al (2007). In contrast, Alibabaee & Khanmohammadi (2016) and Ismail et al. (2015) discovered a favorable association between exchange rate and company performance.
The results of interviews with key informants revealed the same patterns. As an example, one of them was cited as saying:

Robustness check for the effect of macroeconomic variables on firm performance
To assess the robustness and consistency of the results obtained from the baseline model employing the random effect model, the researcher conducted additional study using the two windows accessible at DSE. The MIM window, which had sixteen firms, and the EGM window, which had five firms, are the windows (DSE, 2018). In this analysis, the researcher employed variables identical to those in Table 6's baseline model. ROA was used as the dependent variable as a proxy for firm performance, whereas GDP, IR, IFR, MS, and EXR were employed as treatment variables. In addition, business size, age, and geographical diversity served as control factors. The results of this analysis are shown in Table 8. Standard errors in parentheses Key: * Significant at 10%, ** significant at 5%, *** significant at 1% to more public participation in the equity market which enhances an increase in firm performance.

Recommendations
In line with the findings obtained and the above conclusions, the following recommendations are given. Since GDP has a positive effect on firm performance, it is recommended that the government; through the Ministry of Finance and Planning, Bank of Tanzania and other regulatory bodies; should ensure that they create friendly policies, regulations and environment that will increase productivity of individual firms in the country. Such increase will foster GDP growth and hence promote firm performance. Interest rate was observed to have a negative but significant effect on firm performance. This implies that the higher the interest rate, the lower the firm performance. In this regard, it is recommended to the Central Bank (BoT) to ensure that interest rate is not high as higher rates may be exploitative and may not stimulate growth of specific firm performance. Similarly, firm managers are urged to consider interest rates in making borrowing decisions lest tremendous losses occur to their firms.
The government, through the Ministry of Finance and Planning and BOT, should ensure that inflation rate is under control so that it brings positive impact on firm operations and performance. Arresting inflation rate in the country will have positive contribution to individual firms and to the country's economy. This could be arrested by enacting policies and strategies that control money supply in the economy.
Exchange rate was observed to have a negative effect on firm performance. Thus, it is recommended to the Bank of Tanzania (BoT) to ensure that the country's currency is stable. This means that the exchange rate will be stable as well. In this regard, the country will help firms which have maximum power of securing resources from foreign markets. Similarly, a stable exchange rate will attract foreign investors in the capital market thereby influencing firm performance. Management boards of listed firms are urged to take serious initiatives to study and forecast the behaviour of macroeconomic variables that surround their firms. By so doing, the managers will design effective strategies to evade these factors thereby maximizing their firms' performance.
Lastly we recommend that higher learning institutions should put more emphasis in designing curricular that will equip the future firm managers with adequate knowledge of the macroeconomic variables since the immensely complicated functioning of the modern economy can be better understood with the help of studying macroeconomics. With such studies firm managers will gain better knowledge of how the economy as a whole works and how the level of national revenue and employment is determined by the amount of aggregate demand and aggregate supply and then they can think and ponder on the various ways it might affect their businesses and how to employ such variables to their advantage. By gaining a deep understanding of the elements that have a role in the expansion of a nation's economy and analysing the means by which the most expansion can be accomplished and maintained firm managers might sharpen the competitive edge and enhance firm performance. But all that can only be perfectly done with a proper theoretical base which can be obtained from higher learning institutions. This study was limited as it focused on Dar es Salaam Stock Exchange-listed companies only thus making the generalization of the results impractical. Apart from that the study did not investigate the impact of other potential variables such as political instability, market competition, or technological advancements, which may also affect firm performance. Management of Firms are urged to be proactive in handling the impact of macroeconomic conditions in order to remain competitive and sustainable in the long run. They should also pay close attention to the domestic economic context in which they operate, as the influence of macroeconomic factors on firm performance can be context-specific