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The aim of this study is to analyze the relationship between financial openness and income inequality in Sub-Saharan Africa by controlling the level of development and access to land. By applying the generalized method of moments (GMM) to a sample of 38 countries over the period 2010–2019, the main results are as follows: (i) De facto financial openness reduces income inequality, while de jure financial openness exacerbates income inequality; (ii) Access to land mitigates the effect of de jure openness on income inequalities; (iii) the income level amplifies the effect of reducing financial openness on income inequalities. It follows from these results that access to land can be an excellent instrument for reducing income inequality at the national level due to the reduction of the income gap between rural and urban areas.

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Introduction

Since the emergence of development economics, questions of development financing have occupied a fairly prominent place. In their unrelenting pursuit of development, some countries have opted for Keynesian-inspired policies. The failure of Keynesian economic solutions and the introduction of the neo-liberal political model marked a turning point in the orientation of the global economy and financial markets. Under the auspices of the Washington Consensus, economies were liberalized. These reforms were based on the ideas of MacKinnon (1973) and Shaw (1973). In its external variant, liberalization should lead to an opening of the capital account and an inflow of resources. Competitive pressure from new players in the financial system should contribute to its development and ultimately stimulate economic growth. However, it is to be feared that the much-vaunted beneficial effects of financial liberalization will fail to balance the social classes in both developed and developing countries (Piketty, 2014; Atkinson, 2015; Davis, 2024).

In this context, studies have sought to identify the main channels through which financial liberalization impacts income inequality (Obstfeld, 1998; Aghionet al., 1999). Among these studies, that of Arestis and Caner (2004) is edifying. The first mechanism they highlight involves an increase in the rate of economic growth, based on the financial liberalization hypothesis of MacKinnon (1973) and Shaw (1973). Secondly, Financial crises following financial liberalization may cause changes in macroeconomic volatility. Capital flows lead to improved access to credit and financial services, which is the third mechanism. International risk sharing is added to these channels by Furceri and Loungani (2018), along with smoothing domestic consumption and modifying labor bargaining power.

Batuo and Asongu (2015) emphasize the financial market improvement channel of financial openness and give it a prominent place. It should be pointed out that most of these studies have produced mixed results. By enhancing the efficiency of a national financial system by allowing more capital account liberalization, credit market imperfections can be reduced, credit access can be more equal, and income inequalities can be reduced (Becket al., 2007). For others, however, the poor’s access to financial services is not usually widened by financial liberalization’s improvements in the quality and range of financial services; instead of creating businesses and wealth, they enhance the quality of financial services enjoyed by the wealthy (Galor & Zeira, 1993). Empirically, Capital account liberalization is only effective in reducing income inequality when the financial system is well-developed, as demonstrated by Bumann and Lensink (2016). The results of Furceri and Loungani (2015) suggest that account liberalization results in greater income inequality in countries with weak financial institutions.

In Africa, most research has focused on the effects of financial development on income inequality (Zunguet al., 2022; Okaforet al., 2023). Beji (2019) sets his research apart by highlighting the role of institutions in the relationship between financial openness and income inequality. A potentially important aspect in explaining income disparities is access to land. Reddy (2024) reveals that farmers’ access to fishing grounds and forest resources can improve the food security of farm households. For their part, Dibet al. (2018) show that, on average, farming households have significantly higher incomes than non-farming households, who often work as agricultural workers on plantations.

For illustration, the AFBD (2021), through its “Feeding Africa” project, whose African Agricultural Transformation Program has lifted nearly 130 million Africans out of poverty1 1 https://www.afdb.org/fr/news-and-events/dialogue-de-haut-niveau-nourrir-lafrique-le-continent-africain-invite-preserver-ses-terres-arables-et-mieux-les-valoriser. One of the main challenges in implementing this project is access to financing (AFBD, 2021). We believe that financial openness through the inflow of capital can break this spiral. It’s worth pointing out that this variable is absent from the channels through which financial openness could help reduce income inequalities. On the other hand, the level of development is an undeniable factor in explaining income inequality. In this study, we examine the channel of access to land and the level of development and attempt to fill the gap in the economic literature.

Literature Review

The financial openness resulting from financial liberalization leads to a better international allocation of resources, which fosters innovation and economic growth. The free movement of capital improves individuals are able to access credit opportunities and companies facing financial difficulties and promotes the financial development of host economies (De Haan & Sturm, 2017). The consequences of inequality are not uncomplicated and, from a theoretical standpoint, could vary in any direction.

From 1970 to 2010, Furceri and Loungani (2018) conducted an analysis of 149 countries. It was concluded that liberalizing capital account reforms typically increase the Gini coefficient by around 0.8% in the short term and by around 1.4% in the short to medium term. This study utilizes de jure variables, but there are authors who use de facto variables. Zhang and Naceur (2019) conducted a study on 143 countries from 1961 to 2011 and discovered that a more liberal financial system raises Gini income coefficients and widens the poverty gap. In an analysis of a panel of annual data for 48 advanced and emerging economies from 1991 to 2013 by Avdjiev and Spasova (2022), they found that financial openness increases inequality.

Reforms related to financial openness are strongly linked to income inequality and financial markets despite the lack of consensus about its impact on income inequality. Some studies analyze the distribution of national income and the reasons for it through various channels instead of solely focusing on the effects of financial reforms on income inequality. Tomaskovic-Devey and Lin (2011) examine the rise in financial sector rents and their causes by examining profit as a measure of economic rents. Financial openness and global finance through financial sector rents are the cause of rising income inequality, as confirmed by them. In developing countries, where institutions are weak, and credit access is not always inclusive, the existence of strong institutions is crucial (Beji, 2019).

Ashenafi and Dong (2023) recently studied the connection between financial openness and income inequality. In 78 countries between 1980 and 2019, the authors used de jure and de facto openness, unlike the others. Three key results were obtained by the authors by using a new ‘push’ and ‘pull’ modeling framework and a GMM method with 5-year averaged data. The de facto measure of financial openness has a negative impact on income inequality and is influenced by banking crises and conflict intensity. Second, the value of equities traded in emerging market economies is boosted by the de facto measure, and domestic credit in Africa is reduced. Thirdly, the financial sector development and income inequality are influenced by the interaction between de facto measures and education and governance factors. There are certain reservations that need to be considered when analyzing the potential distributive impact of financial openness empirically. The importance of initial conditions cannot be overstated, and there are significant differences between countries. The extent to which financial openness benefits are reaped by different socioeconomic strata is determined by aspects related to economic, financial, and institutional development. Financial openness reforms have been shown to have an impact on income inequality through only a few studies. There are still fewer individuals who have examined the land-use channel.

Methodology

In this section, we specify the study model and present the variables and their sources.

Model Specification

To examine the effect of financial openness on income inequality in sub-Saharan Africa, we follow Furceriet al. (2019) and Avdjiev and Spasova (2022). While the former authors use de jure openness, the latter opt for de facto openness. Unlike their predecessors, Ashenafi and Dong (2023) use both de jure and de facto openness. In this study, both dimensions are analyzed. We therefore specify our model as follows: where GINI captures income inequality; FINOPEN financial openness, which takes two modalities, namely de jure and de facto financial openness. According to Quinnet al. (2011), researchers should be guided primarily by (1) the extent to which the coverage of the index matches that of their sample and (2) the desired degree of disaggregation. If more aggregated information is sufficient, KAOPEN covers a larger sample of countries. The alternative to de jure measures is de facto measures. These measures have the advantage of taking into account information on financial integration. While some authors use FDI as a de facto indicator, it should be stressed that FDI data generally suffer from definitional inconsistencies between countries and over time. Another more general measure was initiated by Dreher (2006) and further developed by Gygliet al. (2019). This is the financial globalization index. In its de jure version, it refers to policies and resources that enable direct interactions between people living in different countries. De facto financial globalization is measured by capital flows and stocks of foreign assets and liabilities in terms of quantity, not price.

G I N I i t = α i + α 1 G I N I i t 1 + α 2 F I N O P E N i t + α + α 3 G D P P C T A i t + α 4 L A N D P C T A i t + α 5 U R B A N i t + α 6 C O R R U P i t + e i t

LANDPCTA is the variable arable land per capita, obtained by dividing arable land by total population. It also reflects the distribution of land in the economy. GDPPCTA is per capita income. URBAN captures urbanization, which can help reduce national inequality by narrowing the gap between urban and rural areas (Maketet al., 2023). CORRUP captures corruption, which is measured by the Corruption Perception Index. Opinions on the effect of this variable are divided. The first considers that corruption exacerbates income inequality (Pedaugaet al., 2016). On the other hand, a second view suggests that corruption mitigates inequalities and increases social well-being in the face of an inefficient bureaucracy, thus acting as a lubricant (Lui, 1996).

Apart from examining the direct relationship between financial openness and income inequality, a few works have focused on channels. Beji (2019) looks at institutional variables, Tomaskovic-Devey and Lin (2011) corporate profit, Ashenafi and Dong (2023) financial development. We believe that financial openness can pass through this variable insofar as openness generates economic growth. The consequence of economic growth is an increase in income. Equation (1) is taken up again and respecified by inserting an interaction between financial openness and GDP per capita as follows:

G I N I i t = α i + α 1 G I N I i t 1 + α 2 F I N O P E N i t + α 3 G D P P C T A i t + α 4 ( F I N O P E N × G D P P C T A ) i t + α 5 L A N D P C T A i t + α 6 U R B A N i t + α 7 C O R R U P i t + ε i t

Another potentially important aspect in Africa is access to land. Dibet al. (2018) demonstrates that, on average, farms have higher incomes than non-farm households, which typically employ farm laborers on plantations. We take this variable into account by respecifying (1) as follows:

G I N I i t = α i + α 1 G I N I i t 1 + α 2 F I N O P E N i t + α 3 G D P P C T A i t + α 4 L A N D P C T A i t + α 5 ( F I N O P E N × L A N D P C T A ) i t + α 6 U R B A N i t + α 7 C O R R U P i t + ε i t

Equations (1)(3) are estimated using the system-generalized method of moments.

Data

Data are mainly from the World Bank (2022). The series was collected on a sample of 38 Sub-Saharan African countries covering the period 2010–2019. Table I presents the variables and their sources.

Variables Definition Sources
GINI The GINI index WIID (2023)
CORRUP Controlling corruption WGI (2023)
GDPPCTA GDP per capita WDI (2022)
DEFACTOOPEN De facto financial openness Financial Globalization index (2022)
DEJUREOPEN De jure financial openness Fiancial Globalization index (2022)
URBAN Urbanization rate WDI (2022)
LANDPCTA Land per capita WDI (2022)
Table I. Variables Overview

The descriptive analysis of the variables (Table II) provides information on the characteristics of the variables studied. The phenomenon explained here is the income gap between individuals in sub-Saharan African countries. It is captured by the GINI index. A high value indicates a high level of inequality. On average, African countries have a Gini index of 29.22, reflecting a relatively low level of inequality. However, there are disparities between countries. The minimum value is 9.5, and the maximum is 68.3.

Variable Mean Standard deviations Minimum Maximum Observations
GINI 29.2221 10.94618 9.5 68.3 380
CORRUP −0.6983959 0.5079744 −1.581135 0.7763005 380
GDPPCTA 1658.841 1972.458 205.7835 9512.009 380
DEFACTOOPEN 52.08199 13.66286 26.05577 85.5443 380
DEJUREOPEN 42.98879 15.52353 19.56156 84.40994 380
URBAN 40.70596 18.1204 10.642 89.741 380
LANDPCTA 0.0458322 0.072615 0.0003328 0.3885507 380
Table II. Descriptive Statistics

The data in the table also reveal that African countries are moderately financially open, both de jure and de facto. Africa is becoming increasingly urbanized if we refer to the average value of the urbanization variable. This average value is 40.70%. Some countries have high levels of urbanization (maximum value 89.7%), while others have low levels (minimum value 10.64%).

Results and Discussion

In Table III, columns 1 and 2 summarize the results of de facto and de jure openness. The results show that de facto financial openness reduces inequality, while de jure openness increases income inequality. These results are similar to those found by Ashenafi and Dong (2023). The authors exploit this channel of financial development and find that this mechanism is not verified in African countries when considering de facto openness. The authors suggest, however, that the interaction between financial openness and macroeconomic fundamentals should be examined to address issues of income inequality.

Explained variable GINI
(1) (2) (3) (4) (5) (6)
DEFACTOPENO −0.016*** (0.005) −0.027 (0.018) −0.019** (0.007)
DEFACTOOPENGDPPCTA 0.00003*** (5.90e−06)
DEFACTOOPENLANDPCTA 0.229 (0.404)
DEJUREOPEN 0.008* (0.005) −0.005 (0.011) 0.060*** (0.018)
DEJUREENGDPCTA 0.002*** (4.66e−06)
DEJUREOPENLANDPCTA −1.846** (1.091)
LANDPCTA −14.598 (27.921) −71.692*** (20.714)
CORRUP −0.443*** (0.161) −0.961*** (0.204) 0.137 (0.239) −0.814*** (0.240) −0.777* (0.457) −0.455 (0.326)
GDPPCTA 0.0005*** (0.00005) 0.0006*** (0.00005) −0.001*** (0.0003) −0.0002 (0.0002) 0.0004*** (0.00004) 0.005***(0.0004)
URBAN −0.033*** (0.003) −0.039*** (0.004) −0.035 (0.003) −0.032*** (0.004) −0.037*** (0.004) −0.031*** (0.0055)
CONS 5.578*** (0.224) 4.301*** (0.233) 7.527*** (0.978) 4.748*** (0.572) 5.677*** (0.504) 1.960* (1.091)
Observations 341 341 341 341 341 341
Autocorrelation test AR (1) −3.320*** (0.001) −3.303*** (0.001) −3.2697*** (0.001) −3.275*** (0.001) −3.2788*** (0.001) −3.3610***(0.0008)
AR (2) 1.6788 (0.0932) 1.6442 (0.1001) 1.6467 (0.0996) 1.6368 (0.1017) 1.6683 (0.0953) 1.8634 (0.0624)
Hansen’s J-test 28.6364 (0.9965) 31.4139 (0.9894) 24.1799 (0.9995) 24.9959 (0.9992) 23.6322 (0.9994) 32.0741 (0.9771)
Table III. Estimations Results

This led us to check the interactions between financial openness and income inequality, taking into account the level of development and land endowments of African populations (columns 3 and 4 for level of development and columns 5 and 6 for land per capita). The estimation results indicate that when de facto openness leads to a reduction in income inequality, the level of income and access to land favorably affect this effect. In other words, an increase in income and access to land amplifies the reduction capacity of de facto openness.

Access to land reduces the exacerbating effect of de jure openness on income inequality in sub-Saharan Africa. The uniform increase in land ownership reduces income inequality. The effectiveness of agrarian reform in reducing income inequality necessarily depends on the distribution of land ownership. Inequality can certainly be reduced under these conditions, but inequality can increase if the richest farmers are able to control more resources. The coefficient on the LANDPCTA variable has a negative sign, reflecting the effect of equal access to land in reducing income inequality. These results are in line with the work of Dibet al. (2018).

In all the columns, it appears that the level of income increases with income inequality in African countries. This result is contrary to that of Davis (2024). However, we are still in the phase of the rising inequality hypothesis. This result might be attributed to the movement of labor from one sector to another developed sector. Indeed, the movement of labor from the agricultural sector to other sectors of the economy leads to an increase in the per capita income of these people, as their skills are in demand in these sectors. Those who remain in agriculture continue to earn low incomes, increasing income inequality during this phase.

Controlling corruption increases income inequality. This result implies that the authorities’ efforts to regulate corruption are in vain in Africa. This counter-intuitive result can be explained by Lui’s (1996) work. According to him, corruption attenuates inequalities and increases social well-being in the face of an inefficient bureaucracy, thus acting as a lubricant. Bardhan (1997) argues that by helping to overcome bureaucratic rigidities, corruption helps to maintain an efficient allocation of resources when bribers are competing for the same service. Consequently, corruption is a bargaining mechanism where bribes are the only compensatory payment, which helps to reduce inequalities (Boyckoet al., 1995).

Urbanization reduces income inequality in Sub-Saharan African countries. Indeed, urbanization can help reduce national inequality by narrowing the gap between urban and rural areas. According to Maketet al. (2023), urbanization can alleviate pressure on rural resources, increasing the land/labor ratio. This, in turn, increases rural per capita income. Urbanization generates transfers of funds from urban to rural areas, directly increasing average rural incomes.

Conclusion

The issue of income inequality is widely addressed in economic literature. In recent years, one strand of the literature has focused on the financial sources of income inequality reduction. As previous work has produced mixed results, another current is interested in the channels through which financial impulses are transmitted to income inequality. It is in this context that we have analyzed the income and land access channel of financial openness. Applying the generalized method of moments to a sample of 38 countries, the main results are as follows: (i) de facto financial openness reduces income inequality, while de jure financial openness exacerbates income inequality; (ii) access to land attenuates the effect of de jure openness on income inequality; (iii) income level amplifies the reducing effect of financial openness on income inequality. It follows from these results that access to land can be an excellent instrument for reducing income inequality at the national level by narrowing the income gap between rural and urban areas.

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