The impact of trade openness and ICT on technical efficiency of township economies in South Africa

Mazorodze, Brian Tavonga Article The impact of trade openness and ICT on technical efficiency of township economies in South Africa Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Mazorodze, Brian Tavonga (2025) : The impact of trade openness and ICT on technical efficiency of township economies in South Africa, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 5, pp. 1-22, https://doi.org/10.3390/economies13050125 This Version is available at: https://hdl.handle.net/10419/329405 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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The Impact of Trade Openness and ICT on Technical Efficiency of Township Economies in South Africa. Economies, 13(5), 125. https://doi.org/10.3390/ economies13050125 Copyright: © 2025 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article The Impact of Trade Openness and ICT on Technical Efficiency of Township Economies in South Africa Brian Tavonga Mazorodze Department of Accounting and Economics, Faculty of Economic and Management Sciences, Sol Plaatje University, Kimberley 8301, South Africa; [email protected] Abstract: While the impact of trade openness on economic growth has been widely studied, its effect on township economies remains underexplored. In view of this empirical gap, this study examines the impact of trade openness proxied by export intensity on the technical efficiency of five major township economies in South Africa—Soweto, Khayelitsha, Alexandra, Tembisa, and Soshanguve—while considering the moderating role of information and communication technology (ICT). This aim speaks to the ongoing quest to unravel factors limiting the transformation of South African townships since the advent of democracy in 1994. The analysis uses an instrumental variable stochastic frontier model and annual panel data covering the 1995–2023 period. On average, the five townships were found to have operated 19% below their full potential during the sampling period, with Soweto being the least efficient. Holding constant factors peculiar to township economies, such as crime rates and informality, the main results show that ICT plays a positive moderating role in reducing trade-related technical inefficiencies of these townships. This finding underscores the importance of targeted policy interventions, such as investments in digital infrastructure and digital literacy programs, to ensure that township economies benefit from global markets and achieve their full potential. Keywords: trade openness; technical efficiency; townships 1. Introduction Township economies in South Africa have long been characterized by informality, constrained market access, and limited integration into the broader national and global economy. Historically marginalized under apartheid-era spatial planning, these economies continue to face structural barriers that hinder their growth and competitiveness. Despite various policy interventions aimed at fostering inclusive economic development, townships remain economically isolated, with low levels of formal investment and technological adoption. Given these persistent challenges, trade openness and information and communication technology (ICT) present two avenues for enhancing productivity and efficiency in these underdeveloped areas that the majority of the country’s poor people call home. Trade openness has the potential to unlock new market opportunities for township businesses by facilitating access to international markets, fostering competition, and encouraging innovation. The theoretical and empirical literature suggests that increased trade exposure can drive economic growth by improving resource allocation and enabling firms to benefit from economies of scale. However, it is argued that the extent to which township economies can capitalize on trade liberalization depends on their ability to overcome structural inefficiencies and leverage complementary factors such as technological adoption. In this regard, information and communication technology (ICT) plays a crucial role in Economies 2025,13, 125 https://doi.org/10.3390/economies13050125 Economies 2025,13, 125 2 of 22 modernizing production processes, improving access to market information, and reducing transaction costs. Digital platforms, mobile banking, and e-commerce solutions have the potential to integrate township enterprises into regional and global value chains, mitigating the disadvantages of geographical and economic marginalization. Despite the growing recognition of trade openness and ICT as key drivers of economic development, limited empirical research has examined their combined effects within the context of township economies. Most existing studies focus either on the impact of trade openness at a national or sectoral level or on ICT adoption in urban and formal business settings. Consequently, there is a gap in understanding how these factors interact in the unique setting of township economies, where informality, infrastructure deficits, and institutional constraints present unique challenges. This study seeks to fill this gap by probing the moderating role of ICT in the relationship between trade openness and economic growth in five major township economies in South Africa: Khayelitsha, Soshanguve, Soweto, Alexandra, and Tembisa. Prominent studies on the growth effects of international trade (Dollar,1992;Frankel & Romer,1999) have largely demonstrated a positive and significant impact of trade openness on economic growth. While the evidence is, to a large extent, supportive of a positive link between openness and growth, the extent to which the benefits of trade openness accrue to township economies remains underexplored. In addition, very few studies have considered the moderating effect of ICT, which is surprising given the growing prominence of digitalization and its potential role in increasing market access. Against this background, this study contributes to the empirical evidence by examining the impact of trade openness on the technical efficiency of township economies in South Africa while considering the moderating role of ICTs. It defines technical efficiency as the ability of townships to produce at full potential. Examining the impact of trade openness on the technical efficiency of township economies in South Africa and understanding the moderating role of ICTs is important for several reasons. First, township economies have failed to transform into cities since the advent of democracy in 1994 despite South Africa being a more open economy today than it was thirty years ago. It is generally understood from the literature that township economies face a myriad of factors that inhibit them from achieving their full potential (Moos & Sambo,2018). Second, the majority of previously disadvantaged populations reside in township economies, where key drivers of economic activity—such as informal businesses, shebeens, and Spaza shops—operate on the margins of global markets due to poor connectivity and limited network coverage (Bvuma & Marnewick,2020b). It is necessary, against this background, to shed light on whether improvements in ICT infrastructure can help township economies integrate into the global economy and reap the benefits of international trade. Drawing from existing literature, there is strong evidence to suggest that trade openness and ICT adoption can serve as catalysts for economic transformation by enhancing access to global markets and fostering growth within townships. Trade openness and ICTs can particularly enhance the competitiveness of township economies by reducing transaction costs and enhancing access to information. It is additionally argued that digital technologies facilitate trade participation by lowering entry barriers, enabling e-commerce, and improving market linkages. Despite this potential, the extent to which ICTs moderate the trade-growth relationship in these economies is less known, and understanding this link could be key to unlocking the growth potential of township economies. This paper specifically tests the hypothesis that low ICT infrastructure may impede the ability of township economies to capitalize on trade opportunities. Economies 2025,13, 125 3 of 22 The study contributes to the literature in the following four ways. First, it provides empirical evidence on the link between trade openness and technical efficiency in township economies, an area that remains underexplored in the existing literature. Second, it assesses the role of ICT as a potential enabler of efficiency gains, shedding light on the importance of ICT investments and their implications for township development. Third, given the current absence of a model that addresses both heterogeneity endogeneity and idiosyncratic endogeneity, this study uses an ad hoc procedure in which a within transformation is applied on frontier inputs based on the Karakaplan (2022) model. This procedure yields inefficiency scores that are not contaminated with unobserved factors specific to each township while at the same time circumventing the bias in frontier and inefficiency specifications. Fourth, it offers policy insights into how township economies can harness globalization and technological progress to enhance their competitiveness. Given South Africa’s ongoing efforts to promote economic transformation and digital inclusion, the findings of this study have important implications for policymakers. In addition, townships are characterized by high levels of poverty and economic stagnation, exacerbated by geographical marginalization. Therefore, targeting these areas from a research perspective could yield policies that may help the government to achieve Sustainable Development Goals (SDGs) 1 (No Poverty) and 2 (Zero Hunger). Within the literature, this study is closely related to two strands of inquiry. The first strand comprises studies focusing on factors that hinder the growth and development of township economies (Mbonyane & Ladzani,2011;Moos & Sambo,2018;Bvuma & Marnewick,2020b;Wiid & Cant,2021). A central conclusion reached in these studies is that township economies are constrained by the lack of government support, poor infrastructure, and lack of access to funding. The second strand of the literature comprises studies focused on the impact of trade openness on cities (Karayalcin & Yilmazkuday,2015;Munir & Ameer,2018;Fang et al.,2020). A common finding in these studies is that trade openness is associated with the expansion of cities and urbanization. While these conclusions shed important insights, they do not reveal much about how trade openness and ICTs affect the growth and development of township economies. This study, therefore, differs from the first strand of the literature by specifically focusing on the impact of trade openness and limited access to global markets. It differs from the second strand of the literature by exclusively focusing on township economies whose place in the trade-growth literature is yet to receive its fair share of scholarly attention. The primary objective of this study is to empirically examine whether trade openness improves the technical efficiency of township economies in South Africa and whether ICT moderates this relationship. The specific problem motivating this analysis is the persistence of structural inefficiencies in township economies despite decades of economic liberalization. Specifically, the analysis poses the following question: do township economies benefit from trade openness, and can ICT help them overcome the structural barriers to global integration? This analysis seeks to contribute to the literature by combining trade, ICT, and efficiency analysis at a township level, which is a terrain rarely addressed in the existing literature. The results corroborate the notion that township economies in South Africa operate below their full potential. On average, a typical township is found to have operated 19% below its full potential between 1995 and 2023. Evidence demonstrates the critical role of ICT in reducing inefficiencies associated with the participation of township economies in global trade. In particular, in the absence of adequate ICT infrastructure, exporting is associated with higher technical inefficiencies, highlighting the need for digital transformation for townships to maximize the benefits of participating in global markets. This conclusion aligns with endogenous growth theory, which emphasizes the role of technology Economies 2025,13, 125 4 of 22 and knowledge diffusion in enhancing efficiency when participating in global trade. From a policy perspective, the results raise the need for targeted interventions such as the expansion of digital infrastructure, subsidies for ICT adoption, and digital literacy programs aimed at enhancing the integration of township economies into global markets. The rest of the study is organized as follows. Section 2reviews the theoretical and empirical literature. Section 3provides the methodology. Section 4presents and interprets the empirical results. Section 5discusses the findings, while Section 6provides the conclusion and policy implications and suggests areas for further study. 2. Literature Review Township economies in South Africa have their roots in the country’s apartheid era when racially segregated urban areas were created to enforce spatial inequality. They were primarily established as residential areas for black South Africans, who were denied access to better opportunities in productive cities. As a result, township economies remained underdeveloped, with limited infrastructure and resources. The apartheid government’s policy of economic exclusion meant that these areas were largely isolated from global markets, with the majority of businesses being small, informal, and reliant on local demand. In the post-apartheid period, where trade liberalization and market access have opened new avenues for growth, township economies are still struggling to compete on an international scale due to persistent barriers such as low productivity, inadequate infrastructure, and a lack of skills. Global market forces, coupled with the challenges of operating in a highly competitive environment, have made it difficult for township businesses to break into international supply chains. The lack of digital infrastructure and the slow adoption of ICTs have further hindered their ability to engage with global markets, leaving many township economies at the margins of South Africa’s broader economic growth and limiting their capacity to benefit from globalization. This section reviews the existing literature on three key areas: (1) the impact of trade openness on economic growth and efficiency, with a focus on developing and marginalized economies; (2) the role of ICT in economic transformation, particularly in improving productivity and market integration; and (3) the intersection of trade openness and ICT in driving economic development. 2.1. Theoretical Framework This study is grounded in endogenous growth theory, particularly the models developed by Romer (1990) and Grossman and Helpman (1991), which emphasize the role of technological progress and knowledge diffusion in driving long-term economic growth. Romer’s (1990) framework posits that technological advancements, facilitated by knowledge spillovers and innovation, enhance productivity and efficiency. In the context of township economies, ICTs serve as a conduit for these spillovers by enabling firms to access, absorb, and implement new knowledge and production techniques. The adoption of digital technologies reduces transaction costs, facilitates market access, and improves business processes, all of which improve technical efficiency. However, the extent of these efficiency gains may be contingent upon the level of digital infrastructure and firms’ ability to leverage ICTs effectively. Grossman and Helpman’s (1991) open economy endogenous growth model further provides a theoretical lens through which to examine the role of trade openness in shaping efficiency outcomes. Their framework suggests that exposure to international markets enhances productivity by fostering technology diffusion, competitive discipline, and learning-by-doing effects. In township economies, trade openness creates opportunities for firms to integrate into global value chains, adopt foreign technologies, and improve Economies 2025,13, 125 5 of 22 their production efficiency. However, without adequate ICT adoption, these benefits may not be fully realized, as firms may struggle to engage in digital trade, optimize supply chains, or absorb external knowledge efficiently. The interaction between ICTs and trade openness is thus conceptualized as a moderating mechanism that determines the extent to which township firms can enhance their technical efficiency. This study, therefore, situates itself within the broader discourse on endogenous growth and technological diffusion, examining how the synergistic effects of ICTs and trade openness shape efficiency dynamics in township economies. In line with these theories, this study assumes that township economies produce output ( Y ) using capital stock ( K ), labor ( L ), and human capital ( H ). Further assumed is that, as a result of inefficiencies, the actual observed output deviates from the potential frontier output. The production function is specified as Y=AF(K,L,H)(1) where A represents total factor productivity proxying efficiency in the use of K,L, and H. Assuming a Cobb–Douglas technology, we have Y=AKαLβHθ(2) where α , β , and θ are output elasticities with respect to capital stock, labour, and human capital. Trade openness and ICT are hypothesized to affect Yindirectly by influencing technical inefficiency. With this hypothesis, Acan be specified as A=ev−u(3) where v captures deviations of observed output from potential frontier output due to factors beyond the control of township economies, and u is a term capturing deviations of observed output due to technical inefficiency. The final specification is given by u=f(z)(4) where z captures the sources of technical inefficiency, including trade openness, ICT, and their interaction. It is hypothesized that ICT facilitates the benefits of participating in global trade; hence, townships that invest more in ICT are expected to benefit more from trading in global markets. This hypothesis is plausible given the widely documented role of ICT as a complement to international trade. ICT facilitates trade by reducing transaction costs, improving market access, and enhancing business productivity through digital platforms. In township economies, where structural impediments such as poor infrastructure and limited financial access constrain growth, ICT serves as a catalyst for local economic growth. Theoretically, as derived from open economy endogenous growth theories, ICT can enhance the benefits of trade openness by improving firms’ ability to integrate into broader markets, access price information, and optimize production. In the context of this study, the interaction between ICT and trade openness is therefore expected to influence the technical efficiency of township economies, as firms that leverage ICT are likely to overcome traditional barriers to market entry and global competition. 2.2. Empirical Literature Empirical studies examining the relationship between trade openness, ICT, and technical efficiency have largely focused on either macro, sectoral, or firm-level effects. A substantial body of literature highlights the role of trade openness in enhancing firm-level productivity by exposing producers to competitive pressures, encouraging technological Economies 2025,13, 125 6 of 22 upgrading, and facilitating knowledge spillovers from international markets (Yasin,2022; Mazorodze,2020;Wenlong et al.,2023). Similarly, research on the use of ICT emphasizes its contribution to efficiency gains through improved information flows, reduced transaction costs, and enhanced production processes (Adeleye et al.,2021;Ndubuisi et al.,2022). However, the combined effect of trade openness and ICT on technical efficiency, particularly within the context of township economies, remains less understood. Given the structural constraints and historical legacies of township economies, understanding how ICT adoption moderates the efficiency gains from trade openness is critical. Some studies suggest that ICTs enhance the absorptive capacity of producers, allowing them to capitalize on trade-induced efficiency gains (Suatmi et al.,2017), while others indicate that the benefits of trade liberalization may be limited in the absence of sufficient digital infrastructure (Adeleye et al.,2021). In addition, research has shown that factors such as crime and informality can also hamper the ability of townships to achieve their full potential. The following subsections review key empirical findings on these relationships, with a focus on studies that analyze their implications in developing economies and marginalized areas. 2.2.1. Trade Openness and Growth A significant strand of the literature examines the relationship between trade openness and economic growth at a macro-economic level, with early contributions such as Dollar (1992) and Frankel and Romer (1999) demonstrating a positive and sizeable effect of trade openness on economic growth. Dollar (1992) argues that trade openness enhances growth by improving resource allocation and facilitating technology diffusion. Using cross-country data, he finds outward-oriented policies facilitating growth compared to restrictive trade policies. Similarly, Frankel and Romer (1999) provide empirical evidence that greater trade integration leads to higher income, primarily through increased specialization, economies of scale, and knowledge spillovers using an instrumental variable approach to pin down causality. These studies largely suggest that trade liberalization promotes economic growth by expanding market access, encouraging investment, and accelerating technological progress. However, the magnitude of these effects depends on complementary factors such as institutional quality, infrastructure, and human capital. While trade openness creates opportunities for efficiency improvements, its benefits are not automatic, particularly in economies with structural constraints. Recent studies supportive of a positive causal effect of trade openness on economic growth include but are not limited to Jalil and Rauf (2021), Ibrahim and Abdulmalik (2023), and Abdulkarim (2023). A key methodological caveat raised and addressed in these studies relates to the endogeneity of trade openness. Most studies in this area use the panel Generalized Method of Moments (GMM), which uses lagged values of endogenous regressors as instruments. 2.2.2. ICT and Growth Several studies have explored the impact of ICT on economic growth. These studies emphasize the role of ICT in enhancing productivity, innovation, and knowledge diffusion. Early studies, such as Röller and Waverman (2001), establish a positive relationship between ICT infrastructure and economic performance, arguing that digital connectivity facilitates efficiency gains by reducing transaction costs and improving access to information. More recently, using the partial least squares, Fernández-Portillo et al. (2020) similarly demonstrate that ICT contributes positively to economic growth, particularly in developed economies where digital adoption is widespread. Economies 2025,13, 125 7 of 22 Some of the studies, including Pradhan et al. (2021), have differentiated between long-run and short-run effects. Pradhan et al. particularly focus on the role played by ICT in economic growth using data on 20 Indian states observed between 1991 and 2018. The results from their analysis demonstrated a causal effect of ICT on economic growth. This result is similarly documented in D. Wang et al. (2021), Dumor et al. (2024), and Saba et al. (2024). Particularly confirmed by Dumor et al. (2024) is that ICT and infrastructural growth have provided the East African Community (EAC) with opportunities to boost intra-regional trade. These findings, therefore, collectively suggest that ICTs are a catalyst for economic growth and could be vital for township economies where the participation of firms in global markets is impeded by structural barriers and geographical marginalization. 2.2.3. Trade Openness, ICT and Growth Recent studies have considered the moderating effect of ICT on trade openness. These studies are mainly premised on the notion that ICTs improve trade efficiency by reducing information asymmetries, lowering transaction costs, and expanding market access. These effects are particularly pronounced in developing economies, where digital infrastructure enables producers to integrate into global supply chains and capitalize on international trade opportunities. Notable studies include Awad and Albaity (2022), who cite openness as one of the factors through which ICT penetration indirectly promotes per capita income growth. Others include Clarke and Wallsten (2006) and Freund and Weinhold (2004). Within this literature, common proxies for ICT include internet penetration, mobile phone subscriptions, fixed broadband subscriptions, ICT investment, telecommunication infrastructure, and ICT service exports. 2.2.4. Summary and Empirical Gap From the above brief review, it is clear that a well-established body of literature has explored the relationship between trade openness and economic growth, with seminal studies such as Dollar (1992) and Frankel and Romer (1999) demonstrating that trade liberalization enhances economic performance. Parallel to this, the role of ICT in economic growth has been widely examined, with studies such as Röller and Waverman (2001) and Fernández-Portillo et al. (2020) highlighting ICT’s ability to reduce transaction costs, enhance productivity, and foster innovation. Additionally, growing research explores how ICT moderates the trade-growth nexus, arguing that digital infrastructure strengthens the efficiency gains from trade, particularly in developing economies (Clarke & Wallsten,2006; Awad & Albaity,2022). Despite these insights, little attempt has been made to examine the relationship between trade openness, ICT, and economic efficiency at the township level, where structural constraints may limit firms’ ability to fully capitalize on trade liberalization. Existing studies primarily focus on macro or industry-level analyses, overlooking the unique challenges and opportunities within township economies. This study extends the approach of Abdulkarim (2023) by incorporating an inefficiency term to account for deviations from frontier output due to technical inefficiency. By applying a stochastic frontier model, this research provides a more nuanced understanding of how ICT and trade openness jointly influence efficiency in township economies, something that has been overlooked in the literature. 3. Methodology The empirical framework of this study uses the stochastic frontier model pioneered by Aigner et al. (1977). This approach is preferred over its alternative, the data envelopment approach (DEA), due to its ability to separate random noise from technical inefficiencies (Aigner et al.,1977). Township economies are generally confronted by adverse environ- Economies 2025,13, 125 8 of 22 mental factors that are beyond their control, making the stochastic frontier analysis (SFA) more appealing. The analysis follows Abdulkarim (2023), who extended a Cobb-Douglas specification to accommodate the effect of trade openness. This study improves Abdulkarim’s specification by adding an inefficiency term within a stochastic frontier framework to suit the context of the analysis. The application of a stochastic frontier model in analyzing township economies is particularly justified by the need to measure not only the productive capacity of these economies but also the extent of inefficiency that hinders their growth. Township economies operate in unique environments characterized by resource constraints and systemic inefficiencies. Unlike the traditional production function model applied in Abdulkarim (2023), which assumes that all deviations from the frontier are purely random, the stochastic frontier model explicitly accounts for inefficiency, making it a suitable framework for assessing productivity in these settings. By decomposing output deviations into inefficiency and statistical noise, the model allows for a more nuanced understanding of the constraints faced by township economies. In addition, given the role of ICT and trade openness as potential drivers of efficiency, the chosen framework provides a relevant empirical approach to analyze how these environmental factors interact with inefficiency. 3.1. Model Specification Building on the theoretical framework presented earlier, the starting point empirically is specifications that take the following form: Yit =f(Xitβ)+εit (5) εit =vit −uit uit =f(zit)(6) where subscripts i and t denote township and year, respectively, Y is output, X is a vector of inputs (labour, human capital, and physical capital stock), β is a vector of frontier parameters, and εit is an error term composed of the random component ( vit ) and the inefficiency term ( uit ). The inefficiency term ( uit ) specifically measures the distance between each township’s level of output and its full potential. Equation (6) is then specified to identify the sources of inefficiency. In this equation, z is a vector of variables that affect efficiency. With the actual variables, the econometric specifications in this study take the following form. log(y)i,t=γ0+γ1log(L)i,t+γ2log(K)i,t+γ3EDUi,t+εi,t(7) ui,t=α0+α1OPi,t+α2log(ICT)i,t+α3OPi,t×log(ICT)i,t+α4log(C)i,t +α5INFi,t+ϵii,t (8) i=1, . . . , 5; t=1995, . . . , 2023 where yi,tis the level of local GDP in township iyear t;Lis labor captured by the number of employed workers; K is fixed capital stock; EDU is education, which is the share of literate population capturing the quality of labor; OP signifies trade openness; ICT captures the stock of information and communication technologies; C captures crime measured by the total number of reported crimes; and INF is informality measured as the number of informal workers as a share of total employment proxying the informal sector. The inclusion of the interaction term (OP ∗ ICT) is motivated by the hypothesis that the impact of trade openness on technical efficiency in township economies is conditional upon the level of ICT infrastructure. That is, while trade openness theoretically enhances efficiency through exposure to global markets and technology spillovers, these benefits may not materialize Economies 2025,13, 125 15 of 22 Table 8. Trade openness, ICT, and technical efficiency. Frontier Equation Model EX Model EN Dependent var = Log Output Log Labour 0.489 *** 0.418 *** (0.067) (0.114) Log Capital 0.055 0.031 (0.054) (0.068) Literacy (%) 0.003 *** 0.004 *** (0.0004) (0.0004) Inefficiency equation Dependent var: ln σ2 u Constant 17.227 *** 15.384 *** (2.727) (2.035) Log ICT −1.183 *** −1.196 *** (0.116) (0.107) Exports/Output (%) 0.101 *** 0.046 ** (0.029) (0.023) Exports/Output (%) ×Log ICT −0.027 *** −0.018 *** (0.006) (0.004) Informal workers/total employment (%) 0.011 0.014 (0.011) (0.012) Log Crime −1.277 *** −1.021 *** (0.235) (0.172) Dependent var = Dependent var: ln σ2 v Constant −7.555 *** (0.122) Dependent var = Dependent var: ln σ2 w Constant −7.989 *** (0.125) Eta1 (Log ICT) −0.288 *** (0.042) Eta2 (Exports/Output (%)) −0.019 *** (0.005) Eta3 (Log Labour) 0.047 (0.151) Eta4 (Log Capital) 0.848 *** (0.315) Observations 140 140 Log Likelihood 312.91 1275.33 Mean Technical Efficiency 0.8318 0.8089 Median Technical Efficiency 0.8786 0.8580 *** and ** denote significance at 1% and 5%, respectively. Figures in parentheses are standard errors. In the specification, labor, capital, OP, and ICT are treated as endogenous, and they are instrumented by their first lag (i.e., t −1). With respect to the control variables, the evidence shows no significant link between informality and technical inefficiencies. Worrisomely, the crime variable is significantly negative, suggesting that criminality has a positive effect on economic activity in these Economies 2025,13, 125 16 of 22 townships. The average technical efficiency based on the preferred model is 0.8089, suggesting that a typical township municipality produced about 81 percent of its potential output. Thus, a typical township economy operated about 19 percent below its full potential. When decomposed by township, Soweto was found to be the least efficient, operating 21% below its full potential. This illustrates a sizeable scope for economic transformation in these townships. It is necessary to mention that the trend variable was excluded from the specification to avoid unnecessary model overfitting, as it turned out to be highly insignificant. Its insignificance demonstrated the absence of technical changes or frontier shifts, which is not surprising given the low levels of innovation at the township level. Diagnostic Tests This subsection presents the results from diagnostic tests conducted to ensure the reliability of the results presented above. It was necessary to justify the Cobb–Douglas functional form in particular compared to its flexible counterpart, the Translog specification. It was also necessary to test the presence of technical inefficiencies as their absence would reduce the stochastic frontier model into a normal production function estimable using the standard ordinary least squares method. Lastly, the analysis tested for endogeneity as an instrumental variable approach when the variables are exogenous can be worse than the OLS method (Sturm,1998). Accompanying this was a test for weak instruments. Table 9presents the results from functional form and inefficiency tests. The likelihood (LR) test statistic that compares the restricted OLS regression and the unrestricted stochastic frontier model is significant at a 1% level. This implies that the townships are technically inefficient and that a stochastic frontier model is justified over the standard OLS regression with normal errors. The Wald test was performed to determine the joint significance of interactions and higher-order terms in the frontier specification. As Table 9shows, the test yielded an insignificant probability value, suggesting that the Cobb–Douglas specification was an adequate representation of the data. Table 10 presents the skewness of the residuals generated from an OLS regression. For a production-type stochastic frontier model, the presence of inefficiencies is normally reflected in negatively skewed residuals (Kumbhakar et al.,2015). The results in Table 6validate this proposition, lending further support to a stochastic frontier model over a normal OLS regression. Table 11 presents the results of an endogeneity test. The test returns a low probability value, justifying the correction of endogeneity in the model. This result confirms that the true-fixed effects of Greene (2005) and other stochastic frontier models that ignore idiosyncratic endogeneity would be biased. Table 9. Pre-estimation tests. Test Test Statistic Conclusion LR Test for technical inefficiencies −2×(H0) −L(Ha) = 2218 *** uit =0 Functional Form (Wald test) Chi2= 3.52, p-value = 0.1724 Cobb–Douglas *** denotes significant at 1%. Table 10. Skewness of OLS residuals. Variables Obs Mean Std. Dev. Min Max Skew. Kurt. OLS residuals 145 0 0.077 −0.22 0.203 −0.135 3.336 Table 11. Endogeneity and weak instrument test. Test Test Statistic p-Value eta Endogeneity Test X2= 64.89 0.000 Weak instrument test Chi2= 478 0.000 Economies 2025,13, 125 17 of 22 Lastly, to test the strength of the instruments, the study applied the approach proposed by Karakaplan (2022). In Stata 17, this is achievable through the command est res ModelEN followed by the command test iv, where iv is a vector of instruments used in the model. As Table 11 shows, the corresponding probability of the test is low, which, as argued by Karakaplan (2022), suggests that the instruments are not weak. In summary, the diagnostic tests justify the methodology used in the study. The LR test confirms the presence of technical inefficiency, validating the use of a stochastic frontier model over a conventional OLS regression. The Wald test for functional form adequacy reveals that the Cobb–Douglas specification is a suitable representation of the data, as higher-order terms and interactions were found to be statistically insignificant. Additionally, the skewness of OLS residuals aligns with the expectations of a productiontype stochastic frontier model, reinforcing the choice of model. The endogeneity test reveals significant evidence of endogeneity, justifying the use of an instrumental variable approach to avoid biased estimates, while the weak instrument test confirms that the instruments employed are valid. Overall, the baseline results presented in this study can be deemed reliable based on these diagnostic checks. 5. Discussion The main hypothesis of this study was that low ICT infrastructure may limit the ability of township economies to capitalize on trade opportunities. The evidence supports this claim as the interaction between ICT and export intensity is significantly negative. As argued in the literature, township businesses typically operate in localized and informal markets, limiting their ability to integrate into regional or global trade networks. ICT facilitates market expansion by enabling firms to access market information, connect with international buyers, and optimize supply chain logistics. This enhanced market access allows township firms to capitalize on export opportunities and reduce inefficiencies associated with exporting. The positive coefficient of export intensity is not surprising as it suggests that exporting is associated with technical inefficiencies when ICT is held constant. This result demonstrates the important complementary role of ICT if township economies are to take advantage of global market opportunities and achieve their full potential. With respect to other variables, the weak positive effect of literacy on local output can be explained by the lack of employment opportunities for skilled workers in townships. The insignificant link between capital stock and local output, on the other hand, may reflect a suboptimal allocation of capital in townships, which limits the productivity of capital. This explanation is plausible considering Cant’s (2017) proposition that South Africa’s townships are confronted by suboptimal infrastructure. The negative effect of crime on technical inefficiency suggests that criminality drives economic activity in townships. Although surprising at first glance, this result is consistent with the notion that criminality can be a source of livelihood when income inequality is high, and the labor market has limited employment opportunities. Therefore, crime may act as an informal livelihood strategy in contexts where formal employment is scarce. In such cases, illicit economic activity, although undesirable from a legal and ethical standpoint, might support household income and enable continued economic participation, thereby masking inefficiencies at the aggregate level. Another potential interpretation lies in the entrepreneurial resilience of township economies. In high-crime environments, firms may be compelled to adopt efficiency-enhancing practices (e.g., digital payment systems, security infrastructure, and localized supply chains). These adaptations may inadvertently improve productivity. A third possible explanation may relate to data limitations. Crime reporting is often higher in better-resourced areas due to stronger institutional capacity, which are also the townships with relatively better economic activity. In this view, the Economies 2025,13, 125 18 of 22 negative relationship may be spurious, reflecting administrative efficiency rather than a causal economic link. To explore this further, a sensitivity analysis was conducted using the one-year lag of crime to reduce the possibility of reverse causality. The direction and statistical significance of the coefficient remained robust, reinforcing the observed relationship. Nevertheless, given the complexity of crime’s socio-economic impacts, this result should be interpreted with caution, and future research is encouraged to unpack this relationship more closely. The finding that informality does not have a statistically significant effect on technical inefficiency is noteworthy, especially given the centrality of informal economic activity in township economies. One possible explanation is the heterogeneity within the informal sector. Informal businesses range from micro-enterprises with high entrepreneurial capacity to survivalist operations. These divergent characteristics may offset each other in aggregate analysis, resulting in no net effect on inefficiency. A second consideration relates to measurement challenges. Informality is proxied by the share of informal workers in total employment, which may not fully capture the intensity or productivity of informal enterprise activity. Moreover, informality statistics often underreport actual activity due to definitional ambiguities and data collection constraints. Lastly, it is plausible that informal businesses operating outside formal regulatory frameworks may already be operating near their efficiency frontier, constrained by limited capital, low overheads, and simplified production processes. In such cases, while these businesses may be small in scale, they might still exhibit technical efficiency within their operational context. These interpretations highlight the complexity of the informal sector’s role in local productivity dynamics and suggest that a micro-econometric approach that distinguishes between types of informal activity may be needed in future research. From a theoretical perspective, the main results of the study align with endogenous growth theory (Romer,1990;Grossman & Helpman,1991), which highlights the role of technological progress and knowledge diffusion in driving productivity and economic growth. ICT adoption facilitates knowledge spillovers, reduces transaction costs, and improves coordination, thereby increasing the efficiency of exporting firms in township economies. Empirically, the main results agree with Bvuma and Marnewick (2020a), whose results demonstrated the need to address ICT issues with SMMEs operating in South African townships. Makena et al. (2015) also highlight the positive role of ICT usage on businesses in township economies in the context of Zambia. The complementary role of ICT in exporting is in line with previous studies such as those of Kneller and Timmis (2016) and Adeleye et al. (2021). The analysis of Adeleye et al. (2020) particularly found that ICT enhances the impact of trade on growth in Africa. The current study has contributed to this understanding by presenting estimates drawn at the township level. Such a granular approach is important as it provides localized insights that are more applicable to the realities of townships, bridging the gap between macroeconomic findings and micro-level experiences. It is important to mention the limitations of this study at this stage. First, the modeling approach employed in this analysis ignored spatial effects. Townships are not isolated economic units and may potentially interact with each other through supply chains, migration, and shared infrastructure. It is possible that technical efficiency improvement in one township could have positive externalities for nearby townships. Neglecting such spatial dependence may, therefore, paint an incomplete picture of inefficiency dynamics in townships. A mitigating factor, however, is that the five townships included in this analysis are hardly close to each other, making spatial spillovers arising from geographical proximity less problematic. In addition, incorporating spatial effects within a stochastic frontier framework remains a developing area of research, and the properties of many emerging Economies 2025,13, 125 19 of 22 spatial stochastic frontier estimators are not yet well understood. Another limitation of the study relates to data constraints on some of the key challenges affecting the transformation of township economies, such as income inequality and limited access to funding. Lastly, the study was based on a relatively small sample, which might hinder generalization beyond the five townships analyzed in this study. This sample reflected the best possible number of observations given current data availability and the need to focus on major townships. Township-level annual economic data are only systematically available from 1995 onwards, and extending the sample period further was not feasible. Similarly, data coverage across townships is highly uneven, and only five major township economies had sufficiently complete data to support the analysis. While recognizing the sample size limitation, the use of small-N panel econometric techniques and diagnostics tests performed provides reasonable confidence in the validity of the empirical findings. Future research could expand the scope as more township-level data become available over time. 6. Conclusions This study set out to examine the impact of trade openness on the technical efficiency of township economies in South Africa and to assess whether ICT acts as a moderating factor in this relationship. Using an instrumental variable stochastic frontier model applied to a balanced panel of five major townships from 1995 to 2023, the results provide clear empirical support for the hypothesis that ICT significantly enhances the efficiency benefits of trade openness. The findings of this study particularly provide strong empirical evidence that inadequate ICT infrastructure constrains township economies from fully capitalizing on trade opportunities. The significant negative interaction between ICT and export intensity underscores ICT’s critical role in facilitating market access, optimizing logistics for townships, and reducing inefficiencies. Without sufficient ICT infrastructure in place, exporting is linked to technical inefficiencies, highlighting the urgent need for digital transformation to maximize the benefits of trade liberalization. This conclusion aligns with endogenous growth theory, which emphasizes technology and knowledge diffusion as key drivers of efficiency and long-term economic growth. These findings contribute to economic theory by extending the application of endogenous growth models to subnational township economies, a domain typically excluded from the macro trade-growth empirical literature. The study introduces new empirical insights to understand productivity dynamics in marginalized urban contexts by demonstrating that the interaction between ICT and trade openness significantly affects technical efficiency. From a practical perspective, the results carry important implications for policymakers. Targeted interventions to expand digital infrastructure, promote digital literacy, and subsidize ICT adoption can unlock significant efficiency gains in township economies, particularly by enabling informal and small businesses to engage more effectively with global markets. The results essentially highlight the pressing need for policies that strengthen ICT infrastructure in South African townships to ensure that firms reach the full potential of global market participation. Given that ICT mitigates inefficiencies associated with exporting, government interventions may need to, as alluded to shortly above, focus on expanding digital access, subsidizing ICT adoption for small businesses, and implementing digital literacy programs. These initiatives would empower township enterprises to integrate more effectively into regional and global markets, improving efficiency and boosting local economic output. A key limitation of this study is its inability to account for spatial dependencies, which may influence efficiency spillovers across township economies. Future research could explore recent advancements in spatial stochastic frontier models to capture the potential interdependence of township economies. 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