Regulatory Design and Long-Term Growth: Insights from China’s Experience for Latin America

2.1. Regulatory institutions and growth in China and Lain America

Mainstream growth theory identifies institutional quality as central to sustained development, yet the Latin American experience reveals the limits of this premise when reforms lack depth and coherence. Although dynamic panel evidence links growth to macroeconomic stability and institutional credibility (Araujo et al., 2014), the commodity super-cycle demonstrated that much of the region’s convergence was externally driven and temporary, with structural regulatory weaknesses resurfacing once prices declined.

In contrast, China’s trajectory challenges the assumption that liberal-democratic institutions are necessary for efficiency gains: stochastic frontier estimates show significant improvements in productive efficiency relative to Brazil (Nazmi & Revilla, 2008), achieved within a system defined by disciplined state coordination rather than liberalization. Subsequent regulatory consolidation under Xi Jinping—marked by a structural break in 2012 and reinforced anti-corruption enforcement—suggests deliberate institutional recalibration to enhance coherence and reduce rent-seeking (Valdiglesias, 2026), with measurable governance improvements associated with stronger economic performance compared to fragmented Latin American reforms (Valdiglesias, 2025).

Sectoral evidence reinforces this asymmetry: infrastructure and electricity regulation in Latin America remain undermined by weak oversight, corruption, and limited enforcement capacity despite formal autonomy (Suárez-Alemán et al., 2019; Ravillard et al., 2010; Andres, 2014), whereas China’s coordinated regulatory approach—even in environmental policy—demonstrates how initially restrictive measures can ultimately foster green growth and productivity spillovers (Chen et al., 2024).

China’s expansion reinforced Latin America’s commodity dependence and revealed structural weaknesses in industrial and competition policy (Wise & Quiliconi, 2007; Wise, 2016). Although often framed as liberalizing reforms (Hamner, 2002), China’s model remains anchored in state coordination through SOEs and strategic planning (Hearn and León-Manríquez, 2011), diverging sharply from Latin America’s fragmented post-2009 regulatory adjustments. Ongoing deficiencies in corporate governance, investor protection, SME finance, and enforcement capacity (Chong and Lopez de Silanes, 2007; Valdiglesias, 2012; Cardoza et al., 2016) further contrast with the centralized coordination and transaction-cost efficiency observed in East Asia (OECD Development Centre, 2015).

Empirical evidence reinforces this divergence. Independent regulatory agencies with credible enforcement powers are associated with higher investment and improved infrastructure outcomes (Gutierrez and Berg, 2000). East Asian—particularly Chinese—firms operating in Latin America, such as in Peru’s mining sector, benefit from alignment between host-country openness and home-country strategic coordination (Moran et al., 2012). At the same time, East Asian investment abroad often prioritizes pragmatic market access over strict adherence to global governance norms (Dollar, 2017), highlighting a selective application of regulatory discipline. Domestically, East Asian private firms have historically navigated weak property rights and shifting policy landscapes through dense state-business networks (Ahlstrom et al., 2008; Valdiglesias, 2018), underscoring that regulatory efficiency in the region is neither purely liberal nor institutionally neutral.

China’s expanding presence in Latin America illustrates how regulation can function as an instrument of strategic statecraft. Policy banks, bilateral agreements, and coordinated investment frameworks reinforce regulatory alignment with national development objectives (Fornes and Mendez, 2018; Jenkins, 2022). Although private governance mechanisms increasingly complement formal rules (Mayer and Gereffi, 2010), their effectiveness ultimately depends on enforcement capacity—an area where many Latin American countries remain deficient. Historical privatization experiences further reveal that liberalization alone does not guarantee efficiency gains when regulatory oversight is weak or fragmented (Chong and Lopez de Silanes 2005).

Foreign direct investment from East Asia generates ambivalent outcomes in Latin America. While contributing to employment, structural change, and technological transfer (Girón, 2025; Rocha, 2025; Freites, 2024; Zambrano-Monserrate, 2025; Mazé et al., 2024), it also operates within regulatory environments characterized by limited monitoring and enforcement (Lopez and Munoz, 2020; De Barrios et al., 2023; Albright, 2025; Vieira et al., 2023). Allegations of labor and environmental violations (Irwin and Gallagher, 2013) should therefore be understood within systemic regulatory weaknesses rather than attributed solely to foreign actors. More broadly, institutional fragility tends to deter sustained productive investment, raise transaction costs, and constrain SME expansion (Chong and Lopez de Silanes, 2007; Valdiglesias, 2024; McKay et al., 2018; Vassolo et al., 2012).

Recent scholarship emphasizes that East Asia’s regulatory advantage lies in the integration of industrial policy, pilot free trade zones, coordinated oversight, and infrastructural investment (Shen et al., 2025; Sims et al., 2025). Stronger governance coherence and policy integration reduce uncertainty and facilitate long-term planning (Kastner and Pearson, 2021; Kim and Dong, 2025; Weng and Li, 2024; Zhang et al., 2022). In contrast, Latin America’s fragmented enforcement structures, informal practices, and uneven institutional quality undermine predictability and corporate decision-making (Walsh and Ferro, 2020; Stallings, 2024; Gaganis et al., 2021; Reyes, 2021; Mechelli and Cimini, 2020). Even reforms in state-owned enterprises have delivered only partial efficiency gains without resolving systemic governance constraints (Bello et al., 2023; Križić, 2021; Abreo et al., 2021).

Infrastructure and digital integration further accentuate the gap. East Asia’s coordinated investments in logistics, transportation, and digital systems enhance regulatory effectiveness and lower operational costs, whereas Latin America’s fragmented frameworks limit the developmental impact of FDI (Soto and Martinez-Cobas, 2024; Lei, 2024; Urrego-Sandoval and Pardo, 2023; Lopez and Munoz, 2020; Kastner and Pearson, 2021). Informal institutions and public perceptions also shape compliance and reputational risk differently across regions, reinforcing regulatory outcomes in East Asia while amplifying volatility in Latin America (Gaganis et al., 2021; Rousham et al., 2023; Mihut et al., 2025; Bezuidenhout et al., 2021; Wang and Feng, 2023; Albright, 2025; Zhou, 2023).

Importantly, methodological differences in the literature mirror these institutional asymmetries. Research on East Asia frequently employs longitudinal and quantitative approaches capable of identifying causal relationships between regulation and firm-level performance, whereas studies on Latin America remain more descriptive and fragmented, limiting systematic evaluation of welfare effects (Vrontis et al., 2024; Rocha, 2025; Kim and Dong, 2025; Mechelli and Cimini, 2020; Reyes, 2021; Stallings, 2024).

Taken together, the literature suggests that China—and East Asia more broadly—offers not a replicable blueprint but a benchmark illustrating how regulatory efficiency emerges from coherent governance, strategic coordination, and credible enforcement. For Latin America, strengthening institutional capacity, ensuring consistent rule application, and preventing regulatory capture are prerequisites for translating reform into sustained economic growth (Vorotnikova, 2025; Bello et al., 2023; The World Bank, 2025). The central analytical question, therefore, is not whether Latin America can imitate East Asia, but how regulatory efficiency—understood as predictable, enforceable, and strategically aligned governance—can be constructed within its distinct institutional constraints.

2.2. Theoretical framework and hypothesis

Institutional Theory provides the analytical foundation for understanding how regulatory structures shape economic outcomes. Economic performance does not emerge solely from market forces, but from the configuration of formal rules—laws, regulatory agencies, enforcement mechanisms—and informal norms that stabilize expectations and structure incentives (North, 1990; Scott, 2008). Institutions reduce uncertainty by making behavior predictable; when they fail to do so, economic actors face higher risks, shorter planning horizons, and lower incentives to invest. In developing economies, where enforcement is often uneven, informal arrangements may temporarily compensate for weak formal governance. However, such compensatory mechanisms rarely substitute for credible regulation; instead, they tend to entrench opacity, increase discretion, and elevate transaction costs. Latin America exemplifies this institutional dualism: regulatory instability, politicized oversight, and fragmented enforcement undermine predictability, discouraging long-term capital formation and innovation.

New Institutional Economics (NIE) strengthens this argument by explicitly linking institutional quality to efficiency and welfare outcomes (Williamson, 1975, 1985). Institutions determine the cost structure of economic exchange. When regulatory frameworks are coherent and consistently enforced, they lower negotiation, monitoring, and compliance costs, facilitating productive investment. Conversely, weak or inconsistently applied rules raise the cost of contracting, expand opportunities for rent-seeking, and distort resource allocation. Transaction Cost Economics (TCE) sharpens this logic by conceptualizing firms as adaptive responses to institutional constraints (Williamson, 1979, 1985). In environments characterized by regulatory unpredictability, firms internalize uncertainty through vertical integration, informal arrangements, or strategic non-compliance. While such strategies may ensure survival, they reduce aggregate efficiency and constrain productivity growth.

Within this framework, regulatory efficiency is not synonymous with deregulation. Rather, it refers to the capacity of the state to design clear rules, enforce them credibly, and coordinate policy objectives across sectors. Efficient regulation minimizes administrative burdens without sacrificing oversight, reduces discretionary enforcement, and aligns incentives between public authorities and private actors. The critical variable, therefore, is not the size of the state but its organizational coherence and enforcement credibility.

China represents a benchmark case of regulatory consolidation within a state-led model. Its institutional architecture integrates bureaucratic discipline, strategic coordination, and policy continuity, reducing uncertainty and transaction costs despite limited political liberalization. Regulatory predictability—particularly in licensing, property formalization, and industrial policy—creates stable expectations that support investment and long-term planning. In contrast, many Latin American economies exhibit fragmented regulatory regimes in which formal reforms coexist with weak enforcement and politicized implementation. This disjunction generates higher compliance costs, regulatory volatility, and diminished investor confidence, ultimately constraining productivity and per capita growth.

Building on these theoretical foundations, this study advances the proposition that regulatory efficiency—understood as institutional coherence, credible enforcement, and reduced transaction costs—constitutes a decisive determinant of economic performance. Where regulatory systems provide stability and predictability, they enable capital accumulation, entrepreneurial expansion, and sustained growth. Where they remain fragmented and inconsistent, they amplify uncertainty and limit development potential.

Hypotheses

Central Hypothesis (H₀)

Differences in regulatory efficiency—reflected in administrative costs, procedural complexity, and overall business-environment quality—are systematically associated with differences in GDP per capita growth between China and selected Latin American economies, with China’s more efficient regulatory framework linked to superior growth performance.

3.1 Econometric model

Dependent variable:

GDP growth_it = Annual GDP growth for country i in year t.

Treatment variable:

Regulatory Efficiency_it = The 5 variables of Doing Business.

Control variables:

The fixed-effects model accounts for time-invariant country characteristics, denoted as α_i. In this specification, i = 1, …,7 represents the countries in the sample, t = 2003, …,2019 represents the time period, and u_it is the idiosyncratic error term. By using this approach, the model isolates the effect of within-country variation over time, effectively controlling for all time-invariant factors that might otherwise bias the estimates.

The random-effects model assumes that the country-specific effects, denoted as μ_i, are uncorrelated with the regressors. These effects are modeled as normally distributed with mean zero and variance σ_μ², while the idiosyncratic error term u_it is also normally distributed with mean zero and variance σ_u². The μ_i term captures unobserved heterogeneity across countries. When this assumption of no correlation holds, the random-effects model is more efficient than the fixed-effects model, providing more precise estimates:

Hausman test

In this context, β̂{FE} and β̂{RE} represent the vectors of estimated coefficients from the fixed-effects and random-effects models, respectively, and k denotes the number of regressors. The Hausman test evaluates the null hypothesis (H₀) that the random-effects estimator is consistent, which requires that the country-specific effects (μ_i) are uncorrelated with the regressors. A p-value greater than 0.05 indicates that the random-effects model is preferred, while a p-value below 0.05 favors the fixed-effects specification. This test ensures that the selected model produces unbiased and consistent coefficient estimates.

3.2 Sources and causal identification

The analysis uses data from the World Bank’s WDI and WGI (2003–2019), including GDP growth, inflation, trade openness, gross capital formation, and Rule of Law. Regulatory indicators—construction permit costs and scores, ease of doing business, and property registration procedures—come from Doing Business ( Table 2). These standardized sources ensure consistent, comparable measures across the seven countries.

Causal inference is ensured through several strategies. The treatment variable—days required to start a business—is lagged by one year to reduce simultaneity bias. Fixed-effects models control for unobserved, time-invariant country characteristics, while standard errors are clustered at the country level to address heteroskedasticity and within-country correlation. Counts of Doing Business reforms are used as quasi-exogenous shocks to regulatory quality, strengthening identification.

4.1. Descriptive analysis

Table 3 presents key macroeconomic and institutional indicators for selected Latin American countries and China for the period 2003–2019. The indicators include annual GDP growth, inflation rates, trade openness (as a percentage of GDP), gross capital formation growth, and rule of law percentile ranks. These measures capture both economic performance and institutional quality, highlighting structural differences between China and Latin American economies.

The data shows that China consistently exhibits higher GDP growth, more stable macroeconomic conditions, and stronger governance indicators, while Latin American countries display greater variability and lower rule-of-law scores. The sources for these data are the World Bank’s World Development Indicators and the Worldwide Governance Indicators, which provide standardized, cross-country comparable measures for macroeconomic and institutional analysis.

Figure 1 presents the analysis of GDP growth and macroeconomic controls. The figure illustrates that China exhibits strong growth alongside higher rule-of-law scores, lower inflation volatility, and more stable investment patterns, whereas Latin American countries show greater dispersion in economic performance and governance quality. This variation highlights the structural differences in institutional and macroeconomic environments.

Figure 1. Graphic analysis of economic growth and control variables.

Note: Visual comparison of macroeconomic performance and governance indicators. China exhibits stable growth and high rule-of-law scores, while Latin American countries display dispersed economic and institutional outcomes, emphasizing regional heterogeneity.

Table 4 reports regulatory efficiency indicators, including costs and scores for construction permits, ease of doing business, and property registration procedures. China consistently demonstrates lower costs, higher scores, and fewer procedures, highlighting a more efficient business environment, whereas Latin American countries face higher costs, lower scores, and more administrative complexity. These contrasts establish China as a benchmark for regulatory efficiency and underscore the institutional gaps facing Latin American firms. (See Table 4).

Figure 2 illustrates these regulatory indicators. China emerges as a clear benchmark with minimal procedural delays, lower costs, and higher scores across all measures. Latin American countries display higher administrative burdens, more costly procedures, and lower scores, confirming a persistent efficiency gap. These descriptive patterns form the basis for subsequent econometric analysis linking regulatory efficiency to economic performance.

Figure 2. Graphic analysis of variables of regulatory efficiency.

Note: Graphical analysis of regulatory efficiency indicators, including construction permit costs and scores, ease of doing business, and property registration procedures. China serves as a benchmark with minimal procedural delays, lower costs, and higher scores, whereas Latin American countries face higher administrative burdens, more costly procedures, and lower regulatory efficiency. Data are primarily from the World Bank’s Doing Business database, complemented by the World Bank Enterprise Surveys.

4.2. Regression results

To assess the impact of regulatory efficiency on economic performance, we conducted panel-data regressions covering China and selected Latin American countries. Both fixed-effects (FE) and random-effects (RE) models were used to account for country-specific and temporal heterogeneity. The regression analysis focuses on key indicators of regulatory efficiency: construction permit costs, construction permit scores, ease of doing business, and property registration procedures (score and number of steps). These variables reflect administrative burdens, procedural complexity, and the overall conduciveness of the business environment.

The results, summarized in Table 5, indicate that higher regulatory efficiency is consistently associated with stronger GDP growth. In the FE specifications, lower construction permit costs and higher ease-of-doing-business scores positively correlate with growth, while in the RE specifications, fewer property registration procedures are linked to better economic performance. China consistently displays lower administrative burdens, higher regulatory scores, and fewer required procedures, which positions it as a benchmark for an efficient regulatory environment compared with the Latin American countries in the sample.

Macroeconomic control variables behave as expected. Gross capital formation contributes positively to GDP growth across all models, while inflation shows a generally negative effect. Trade openness presents mixed results but is significant in certain specifications. Rule of Law percentile ranks generally have a positive or modest effect, highlighting the relevance of institutional quality alongside regulatory efficiency.

To determine the appropriate panel-data specification, we conducted a series of Hausman tests comparing FE and RE models across different model specifications. The Hausman test evaluates whether the RE estimator is consistent by testing the null hypothesis that the individual effects are uncorrelated with the regressors.

As shown in Table 6, Tests 1 and 2 yield Chi² values of 2.30 and 2.31, with p-values exceeding 0.80, indicating no evidence to reject the null hypothesis. These results suggest that, for these specifications, the random-effects estimator is both consistent and efficient. Test 3, with a Chi² of 11.02 and a marginal p-value of approximately 0.05, suggests caution: while the RE model may still be acceptable, fixed effects could also be considered depending on robustness checks. In contrast, Tests 4 and 5 produce highly significant results (Chi² = 24.19 and 23.78, p < 0.001), leading to rejection of the null hypothesis and indicating that fixed-effects models are required for these specifications.

These results highlight the heterogeneity of the data structure across models and confirm that model selection must be guided by both statistical tests and theoretical considerations. For most specifications with high p-values, RE is adequate, but for those with significant Hausman tests, FE better accounts for correlation between the individual effects and regressors, ensuring unbiased and consistent coefficient estimates.

To further assess the differential impact of regulatory and institutional conditions on economic performance, we conducted a panel-data analysis using dummy variables to distinguish China from selected Latin American countries. Table 7 reports the results across four specifications: three random-effects models (columns 1–3) and one fixed-effects model (column 4). The dummy variables are coded as 1 for Latin American countries and 0 for China, using China as a benchmark for efficient regulatory practices and institutional quality.

The results in Table 7 show that China consistently achieves more favorable growth outcomes relative to Latin America. Coefficients for the Latin American dummies are generally negative or smaller than the baseline (China), with column 3 reaching statistical significance at the 1% level (−27.82), underscoring the substantial gap in growth performance linked to differences in regulatory efficiency, institutional quality, and governance structures.

Control variables behave as expected: gross capital formation remains positively and strongly associated with growth, trade and Rule of Law show mixed but coherent effects, and inflation has a modest negative effect in the FE specification. Overall, these findings confirm that China serves as a practical benchmark in the region, with lower administrative burdens, more predictable regulatory processes, and stronger governance translating into more stable and higher per capita growth compared to Latin America.