The primary objective of this study is to assess the effectiveness of foreign currency restrictions in developing economies by analyzing their impact on macroeconomic indicators such as GDP growth, inflation, FDI inflows, and the current account balance. Through a cross-country comparative analysis, the study aims to understand how varying degrees of currency restrictions affect economic stability and growth, providing insights that can inform policy decisions in these regions.

This study provides empirical evidence on the implications of foreign currency restrictions in developing economies. By evaluating the relationship between currency controls and key economic indicators, the research offers a nuanced understanding of how different levels of restrictions impact economic performance. The findings can help in designing more effective currency control policies that balance economic stability with growth, enhancing decision-making in the management of foreign currency flows and economic regulation.

Currency restrictions are introduced to maintain economic stability and manage exchange rate volatility. Babayev (2020) highlights the crucial role of currency markets in ensuring liquidity and stability for economic units. This is particularly important in developing economies where currency instability can lead to serious economic disruptions.

Historically, the literature on exchange rate determination has predominantly focused on models that assume free capital mobility and minimal government intervention. The monetary approach to exchange rates, which attributes fluctuations to monetary factors, has been a central theme of this body of research. However, this approach falls short when applied to economies with capital controls. Blejer (2013) addresses this gap by examining the behavior of exchange rates in countries with floating exchange rates and capital controls. He points out that black market rates, which are influenced by domestic monetary conditions and market forces, differ from official rates, shaped by government policies. This distinction highlights the importance of considering capital controls and black markets in understanding exchange rate dynamics, thereby extending the traditional monetary model.

Kriljenko (2003) further explores the flexibility of central banks in developing and transition economies, noting that they have more tools to influence exchange rates than their counterparts in developed economies. This flexibility is crucial for effectively implementing foreign exchange restrictions and managing economic fluctuations.

The impact of the removal of exchange controls is also an important area of research. Angermann (2005) analyzes South Africa’s policy shift in 2004, which aimed to boost investment by relaxing capital controls. While this deregulation improved GDP growth and currency stability, Angermann finds that it was insufficient to address deeper economic challenges such as high unemployment and low foreign direct investment. This underscores the need for a favorable investment climate beyond policy changes.

Fanelli and Straub (2021) examine the dynamics of a small open economy with partially segmented bond markets where capital flows cause excessive volatility in the real exchange rate. Their study suggests that central bank intervention can stabilize exchange rates and bond yields, but can lead to excessive reserve accumulation and too low interest rates if not carefully managed.

Márquez and Reyes (2018) argue that Mexico’s exchange rate policy has become increasingly ineffective because of currency markets globalization. Despite adopting a floating exchange rate regime, Mexico continued to struggle with exchange rate volatility exacerbated by external shocks, showing the limitations of monetary policy in a globalized financial environment.

Glick and Hutchison (2005) challenge the conventional wisdom that capital controls protect economies from currency crises. Their research suggests that fewer capital controls may actually contribute to greater currency stability, suggesting that capital market liberalization may enhance economic resilience.

Anderson (2013) examines the impact of ease of currency conversion on foreign direct investment. While an open exchange rate regime is crucial for attracting investment, Anderson acknowledges the need for some degree of regulation to balance economic stability with investment attractiveness.

This study presents a comparative analysis of foreign exchange restrictions in selected countries, including Zambia, Brazil, Chile, Colombia, Ghana, India, Indonesia, Nigeria, South Africa, and Tanzania. By categorizing these countries based on the severity of their foreign exchange restrictions - strong, moderate, or minimal - and examining the key macroeconomic indicators from 1986 to 2022, the research provides insights into the effectiveness of different levels of foreign exchange controls. The findings aim to improve understanding of how different degrees of currency restrictions affect economic performance, including GDP growth, inflation, foreign direct investment, and the current account balance. This comparative approach provides critical insights for policymakers seeking to balance economic stability and growth in developing and emerging market economies.

Countries with severe foreign exchange restrictions, such as Nigeria, Ghana, Tanzania, and Zambia, have implemented strict controls to stabilize their economies. In contrast, countries with moderate restrictions, such as India and Indonesia, seek to balance currency stability with capital mobility. Meanwhile, countries with minimal restrictions, including Brazil, Chile, Colombia, and South Africa, exemplify the results of a more liberal exchange rate regime.

This study uses data from the World Bank, which provides comprehensive economic indicators for various countries. The primary indicators analyzed include GDP growth, official exchange rates, foreign direct investment (FDI), current account balances, and inflation rates. The data cover ten countries selected for their diverse economic contexts and varying levels of foreign exchange restrictions. The analysis was conducted using Jamovi software, an open-source statistical tool designed for robust and user-friendly data analysis.

Prior to analysis, the dataset was cleaned to remove missing values and ensure consistency across indicators. Outliers were identified and managed to maintain the integrity of the dataset. The key variables for this study included GDP growth (annual percentage) as the dependent variable and inflation rate (annual percentage), current account balance (USD million), net FDI inflows (USD million), and official exchange rate (local currency units per USD) as independent variables. Foreign exchange restrictions were categorized into three levels: moderate, none, and severe.

Descriptive statistics were computed for each economic indicator to provide a comprehensive overview of the economic conditions in each country. Measures of central tendency (mean) and dispersion (standard deviation) were calculated for GDP growth, official exchange rates, net FDI inflows, current account balances, and inflation rates. For example, Brazil’s mean GDP growth was observed to be 2.28% with a standard deviation of 2.94%, indicating moderate economic growth with notable fluctuations. Inflation rates and other indicators were similarly analyzed to understand their distribution and variability across the ten countries.

Both Spearman’s rank correlation and Pearson’s correlation coefficients were computed to examine the relationships among economic variables. Spearman’s rho was used for nonparametric analysis to identify monotonic relationships between inflation, current account balance, FDI inflows, GDP growth, and official exchange rate. Pearson’s r was computed to assess linear relationships among these variables. This dual approach allowed for a comprehensive understanding of the relationships, revealing significant non-linear patterns and highlighting the complexity of economic dynamics across countries.

A linear regression model was specified with GDP growth as the dependent variable and inflation, current account balance, net FDI inflows, official exchange rate, and foreign exchange restrictions as independent variables. The overall fit of the model was assessed using R-squared and adjusted R-squared values, which indicate how well the predictors explain the variance in GDP growth. The significance of the model was assessed using the F-statistic. Individual predictors were examined using t-tests to determine their significance and impact on GDP growth. The coefficients for inflation, current account balance, FDI inflows, official exchange rate, and currency restrictions were analyzed to understand their contributions to GDP growth. Significant predictors such as the official exchange rate and currency restrictions were identified, while others showed varying degrees of impact.

The statistical analysis was conducted using Jamovi, a user-friendly open-source software for performing descriptive statistics, correlation analysis, and regression modeling. The software’s capabilities allowed for effective handling of the data set and interpretation of the results, ensuring a thorough examination of the economic indicators and their relationships. The software has been widely used by different researchers in different studies (see Yangailo, 2024a, 2024b; Abbasnasab Sardareh et al., 2021; Yangailo & Chambani, 2023; Hassen & Ramakrishna, 2020; Yangailo, 2023; Şahin & Aybek, 2019).

To ensure the reliability and validity of the findings, the study employed triangulation. This approach helps to corroborate the findings and provides a more nuanced understanding of the relationship between macroeconomic indicators.

Consistency of the data was checked through cross-verification with multiple sources, including government reports and international databases (World Bank Data base).

Countries with moderate foreign exchange restrictions have a relatively low average inflation rate of 7.92%, with moderate variability as indicated by a standard deviation of 6.79%. The inflation distribution is highly right-skewed (skewness = 5.83), suggesting that while most inflation rates are low, there are occasional spikes, as evidenced by the maximum value of 58.5%. The extreme kurtosis of 42.6 further emphasizes the presence of significant outliers in inflation rates. In contrast, countries with no restrictions have an exceptionally high mean inflation rate of 81.1%, accompanied by extreme volatility, as shown by a standard deviation of 363%. The high skewness (5.92) and kurtosis (37.3) indicate frequent and severe inflation spikes, with the maximum reaching an astronomical 2,948%. Meanwhile, countries with severe restrictions have an average inflation rate of 22.6%, which is higher than countries with moderate restrictions but significantly lower than countries with no restrictions. Inflation in these countries is moderately volatile, with a standard deviation of 26.1%, and exhibits significant, though less extreme, fluctuations (skewness = 3.62, kurtosis = 16.6).

Regarding the current account balance, countries with moderate restrictions show an average deficit of -10,988 million US dollars, with considerable variability (standard deviation = 21,456 million US dollars). The left-skewed distribution (-1.64) indicates that large deficits are common, as reflected by the minimum value of USD -91,471 million. Countries without restrictions have a similar mean deficit of -$10,855 million, but with slightly less variability (standard deviation = $20,340 million). The distribution here is even more negatively skewed (-2.67), highlighting the prevalence of significant deficits. In contrast, countries with severe restrictions have a slightly positive average current account balance of USD 756 million, with lower variability (standard deviation = USD 6,921 million). The positive skewness (2.96) suggests that some countries have significant surpluses, although the minimum value of USD -15,986 million shows that deficits still occur.

In terms of FDI, countries with moderate restrictions enjoy a relatively high average FDI inflow of $13,678 million, with significant variability (standard deviation = $16,377 million). The positive skewness (1.12) indicates that while most FDI inflows are moderate, there are occasional large inflows, as evidenced by the maximum value of $64,362 million. Countries with no restrictions have a slightly higher average FDI inflow of $13,837 million, but exhibit greater variability (standard deviation = $21,298 million). The higher skewness (2.40) and kurtosis (5.29) suggest that FDI inflows are more variable and prone to extreme values. However, in countries with strict restrictions, the mean FDI inflow drops significantly to USD 1,311 million, with much lower variability (standard deviation = USD 1,755 million). The skewness (2.22) and kurtosis (5.50) indicate that while most FDI inflows are small, there are occasional large inflows, although these are less frequent and less extreme than in countries with no or moderate restrictions.

The average GDP growth rate in countries with moderate restrictions is 5.42%, with moderate variability (standard deviation = 3.22%). The negative skewness (-3.35) and high kurtosis (16.1) suggest that while positive growth is common, there are occasional periods of significant negative growth. In contrast, countries without restrictions have a lower average GDP growth rate of 3.17%, with similar variability (standard deviation = 3.12%). The distribution is slightly negatively skewed (-0.470), indicating a balance between periods of positive and negative growth, although the skewness is less pronounced than in countries with moderate restrictions. Meanwhile, countries with severe restrictions have an average GDP growth rate of 4.64%, which is slightly lower than in countries with moderate restrictions, but higher than in countries with no restrictions. The standard deviation is 3.13% and the distribution is slightly negatively skewed (-0.416), indicating that most growth rates are positive, with occasional periods of negative growth.

Finally, in terms of the official exchange rate, countries with moderate restrictions have an average exchange rate of 4,039 local currency units (LCU) per US dollar, with high variability (standard deviation = 5,180 LCU). The positive skewness (0.865) suggests occasional periods of significant currency depreciation. In contrast, countries without restrictions have a much lower mean exchange rate of 606 LCU per US dollar, with lower variability (standard deviation = 944 LCU). The higher skewness (1.88) indicates that while most exchange rates are stable, there are occasional periods of significant depreciation. Countries with severe restrictions have the lowest mean exchange rate at 300 LCU per US dollar, with moderate variability (standard deviation = 579 LCU). The positive skewness (2.25) suggests that while most exchange rates are stable, there are occasional periods of substantial depreciation, although these are less extreme than in countries with moderate or no restrictions.

In summary, the data suggest that countries with moderate foreign exchange restrictions tend to experience moderate inflation, significant current account deficits, and high FDI inflows, with relatively stable GDP growth. Countries with no restrictions, on the other hand, experience extreme inflation volatility, persistent current account deficits, and highly volatile FDI inflows, coupled with lower GDP growth. On the other hand, countries with severe restrictions tend to have moderate inflation and current account balances, significantly lower FDI inflows, and stable GDP growth, albeit slightly lower than countries with moderate restrictions. Exchange rate variability is highest in countries with moderate restrictions, suggesting that while exchange rate controls can stabilize exchange rates, they can also reduce FDI inflows and potentially increase inflationary pressures.

Table 3 presents the correlation matrix, which provides detailed insights into the relationships between inflation, the current account balance, net FDI inflows, GDP growth and the official exchange rate.

First, inflation is negatively associated with net FDI inflows, with a Spearman’s rho of -0.604 (p < 0.001), indicating a strong non-linear relationship. This suggests that higher inflation tends to reduce FDI inflows. However, Pearson’s r is -0.072 (p = 0.169), which is weak and insignificant, indicating that the linear relationship between inflation and FDI is less pronounced. Similarly, inflation has a moderate negative relationship with the official exchange rate (Spearman’s rho = -0.413, p < 0.001), indicating that as inflation increases, the local currency tends to depreciate. The Pearson’s r is -0.063 (p = 0.225), which is weak and insignificant, indicating a less clear linear relationship. For GDP growth, the Pearson correlation is -0.122 (p = 0.019), indicating a weak but significant negative linear relationship between inflation and GDP growth. The Spearman’s rho is -0.066 (p = 0.206), indicating an insignificant non-linear relationship.

The current account balance has a strong negative relationship with net FDI inflows, with a Pearson’s r of -0.758 (p < 0.001) and a Spearman’s rho of -0.503 (p < 0.001). This means that, as the current account balance improves, FDI inflows tend to decrease significantly. In contrast, the current account balance has weak or insignificant correlations with GDP growth and the official exchange rate. Specifically, Pearson’s r for GDP growth is 0.037 (p = 0.483) and Spearman’s rho is 0.013 (p = 0.802), indicating no significant relationship. For the official exchange rate, Pearson’s r is 0.020 (p = 0.708) and Spearman’s rho is -0.062 (p = 0.236), both weak and insignificant.

Net FDI inflows show a significant negative correlation with the current account balance, reinforcing the inverse relationship observed. The Spearman’s rho for the official exchange rate is 0.239 (p < 0.001), indicating a moderately positive non-linear relationship, suggesting that as FDI inflows increase, the value of the local currency tends to appreciate against the US dollar. The Pearson’s r for FDI inflows and the official exchange rate is 0.037 (p = 0.472), which is weak and insignificant, indicating that the linear relationship is not as strong. FDI inflows have weak and insignificant correlations with GDP growth, with Pearson’s r at -0.084 (p = 0.107) and Spearman’s rho at 0.044 (p = 0.402).

Finally, GDP growth shows a moderate non-linear positive relationship with the official exchange rate, with Spearman’s rho of 0.175 (p < 0.001), indicating that higher GDP growth is associated with a stronger local currency. Pearson’s r is -0.002 (p = 0.969), reflecting a negligible linear relationship.

In summary, these correlations show that while inflation and FDI inflows exhibit significant non-linear patterns, linear relationships are often weaker or insignificant. The results underscore the complexity of the interactions between these economic variables and suggest that non-linear relationships may provide a more accurate picture of the economic dynamics at play.

The linear regression results provide a detailed examination of the relationship between GDP growth and several predictor variables, including inflation, current account balance, net FDI inflows, official exchange rate, and foreign exchange restrictions.

The overall model fit is assessed with an R2R^2R2 of 0.0995 and an adjusted R2R^2R2 of 0.0846, indicating that approximately 9.95% of the variance in GDP growth is explained by the model, with the adjusted figure taking into account the number of predictors and the sample size. The model is statistically significant with an F-value of 6.68 (df1 = 6, df2 = 363, p < 0.001), indicating that the combination of predictors provides a significant explanation for the variation in GDP growth.

Looking at the individual predictors, the omnibus ANOVA test shows different levels of significance. For inflation (consumer prices, annual %), the sum of squares is 35.87 (F = 3.682, p = 0.056), which is close to the significance threshold, indicating a marginally significant effect. The current account balance contributes 4.32 to the sum of squares (F = 0.443, p = 0.506), indicating an insignificant effect on GDP growth. Similarly, net FDI inflows contribute 18.05 to the sum of squares (F = 1.853, p = 0.174), also showing an insignificant effect. The official exchange rate has a sum of squares of 43.39 (F = 4.453, p = 0.036), which is significant, indicating that changes in the official exchange rate have a significant impact on GDP growth. Currency restrictions have a sum of squares of 291.29 (F = 14.949, p < 0.001), which is highly significant, indicating that the degree of currency restrictions has a strong impact on GDP growth.

The model coefficients provide detailed relationships between the predictors and GDP growth. The intercept is estimated to be 6.19853 (SE = 0.485, t = 12.778, p < 0.001). Inflation has a coefficient of -0.00137 (SE = 7.12e-4, t = -1.919, p = 0.056) with a standardized estimate of -0.0971, indicating a marginally significant negative relationship with GDP growth. The current account balance has a coefficient of -9.54e-6 (SE = 1.43e-5, t = -0.666, p = 0.506) with a standardized estimate of -0.0513, indicating an insignificant effect. Net FDI inflows have a coefficient of -2.10e-5 (SE = 1.54e-5, t = -1.361, p = 0.174) and a standardized estimate of -0.1063, indicating an insignificant negative effect on GDP growth. The official exchange rate has a coefficient of -1.44e-4 (SE = 6.81e-5, t = -2.110, p = 0.036) with a standardized estimate of -0.1237, indicating a significant negative relationship with GDP growth.

Regarding foreign exchange restrictions, the coefficient for the “None - Moderate” category is -2.64717 (SE = 0.504, t = -5.252, p < 0.001) with a standardized estimate of -0.8114, and for “Severe - Moderate” the coefficient is -1.44604 (SE = 0.536, t = -2.699, p = 0.007) with a standardized estimate of -0.4432. Both categories show significant negative effects, indicating that more severe foreign exchange restrictions are associated with lower GDP growth.

In summary, while the overall model is statistically significant, individual predictors vary in their impact on GDP growth. The official exchange rate and foreign exchange restrictions are significant, while inflation, the current account balance, and net FDI inflows show varying degrees of insignificance.

The study shows remarkable differences in inflation rates between countries with different levels of foreign exchange restrictions. Countries with moderate restrictions tend to have more controlled inflation than countries with severe restrictions or no restrictions at all. This finding supports the view that moderate restrictions can stabilize inflation by reducing excessive currency fluctuations and speculative pressures (Friedman, 1968). Conversely, countries without currency controls often experience high inflation volatility because the absence of such controls allows for greater currency fluctuations, which generate inflationary pressures, especially in economies vulnerable to external shocks (Mundell, 1961).

Moderate currency restrictions are associated with larger current account deficits, indicating a tendency toward trade imbalances. This suggests that moderate controls may create a less predictable environment for international transactions, potentially leading to higher deficits (Obstfeld & Rogoff, 1995). Conversely, countries with high restrictions tend to have more stable current account balances, likely due to a more predictable currency environment that reduces trade balance volatility. However, this stability often comes at the cost of reduced international trade competitiveness (Krugman, 2000). Countries without restrictions show high variability in current account balances, reflecting the dual impact of currency fluctuations on trade dynamics.

The study finds that FDI inflows are significantly higher in countries with moderate currency restrictions than in countries with severe restrictions or no restrictions. Moderate restrictions appear to offer a balance of currency stability that attracts foreign investors while avoiding the restrictive environments that can deter investment (Alfaro et al., 2004). On the other hand, severe restrictions tend to reduce FDI inflows due to concerns about capital mobility and barriers to profit repatriation (Hines, 1995). Countries without restrictions show variable FDI inflows, suggesting that while the absence of controls may attract investors seeking flexibility, it also introduces uncertainty that may affect investment decisions (Gordon & Hines, 2002).

The relationship between currency restrictions and GDP growth is nuanced. Countries with severe restrictions generally experience somewhat lower GDP growth than countries with moderate or no restrictions. The restrictive environment may limit economic expansion and reduce the efficiency of resource allocation (Lucas, 1988). In contrast, countries with moderate restrictions often show more robust GDP growth, reflecting a balanced approach that supports economic stability and investment. Higher growth rates in countries with no restrictions could be attributed to greater freedom of capital movement and trade, although this is often associated with increased economic volatility and inflationary pressures (Barro & Sala-i-Martin, 1995).

The analysis shows that countries with strict restrictions tend to have lower inflation and current account volatility, suggesting a more stable economic environment. This stability is beneficial for long-term planning and investment, but may reduce attractiveness to foreign investors and introduce potential inefficiencies (Edwards, 1999). In contrast, countries without restrictions experience higher economic volatility, leading to unpredictable inflation and fluctuating current account balances. This volatility can create a more dynamic economic environment, but at the cost of increased risk and instability (Calvo & Reinhart, 2002).

The results suggest that the optimal level of currency restrictions depends on the context. Moderate restrictions appear to provide a favorable trade-off by providing economic stability and attracting foreign investment while controlling inflation and current account imbalances. However, their effectiveness depends on the overall economic context, including institutional quality, external conditions, and the specific design of currency control measures (Rodrik, 1998).

This study has several limitations. It relies on historical data, which may not fully reflect recent economic changes or policy shifts (Krugman & Obstfeld, 2006). Variations in data accuracy and reliability across countries, inconsistent reporting standards, and the limited sample of ten countries may affect the generalizability of the findings. In addition, focusing solely on macroeconomic indicators may overlook other important factors such as political stability and the regulatory environment (North, 1990). Future research should expand geographically to include a larger and more diverse set of countries and examine the long-term effects of currency restrictions. Longitudinal studies could provide insights into how the effects of currency controls evolve over time. Examining the effects on specific sectors or firms and incorporating qualitative research through interviews with policymakers and business leaders could provide a more nuanced understanding of the real-world effects of currency controls (Ghosh et al., 2001).

In a nutshell, while this study provides valuable insights into the economic effects of currency restrictions, addressing its limitations and exploring new avenues of research will enhance our understanding of how such policies affect economic stability and growth. Tailored policy approaches based on these findings are essential for designing effective economic strategies in different contexts.