Received: July 10, 2023
Accepted: September 28, 2023
Purpose: This study explored the relationship between environmental scores and financial performance in Latin American firms.
Design/Methodology: Using a dataset encompassing 1 708 observations from 372 firms between 2015 and 2020, this study employed panel data analysis to investigate the relationship between environmental scores and Return on Assets (ROA).
Findings: The empirical findings indicate that the current environmental performance in Latin America has a limited impact on firms’ financial performance. However, positive results were observed in Brazil, Mexico, and Chile, where environmental practices and financial outcomes have been successfully integrated.
Conclusions: By examining the influence of Environmental, Social, and Governance (ESG) scores, particularly environmental scores, on ROA in Latin American firms, this study contributes to better understanding the complex relationship between sustainability and financial performance in the region. In addition, it underscores both the challenges and opportunities that Latin American firms face in aligning environmental performance with profitability. According to the findings, enhanced strategies and mechanisms should be developed to bridge the gap between environmental and financial outcomes. While Latin America has made progress in establishing consensus on environmental practices, there remains a pressing need to develop robust strategies that effectively integrate sustainability and profitability.
Originality: This study provides valuable insights for policymakers, investors, and firms seeking to navigate the interplay between sustainability and financial success in Latin America.
Keywords: environmental performance, Latin America, financial performance, ESG score, panel data, ROA.
JEL Classification Codes: 044, F30, O54.
Objetivo: En este estudio, se investigó la relación entre las calificaciones ambientales y el desempeño financiero de las empresas latinoamericanas.
Diseño/Metodología: Partiendo de un conjunto de datos que abarcó 1 708 observaciones de 372 empresas entre 2015 y 2020, este estudio utilizó datos de panel para analizar la relación entre las calificaciones ambientales y la rentabilidad de los activos.
Resultados: Según los hallazgos empíricos, el impacto del actual desempeño ambiental en América Latina sobre el desempeño financiero de las empresas de la región es limitado. A pesar de ello, se observaron resultados positivos en Brasil, México y Chile, donde se destaca la exitosa integración de prácticas ambientales y resultados financieros.
Conclusiones: Gracias al análisis del impacto de las calificaciones ambientales, sociales y de gobernanza—en particular las ambientales—sobre la rentabilidad de los activos de las empresas latinoamericanas, este estudio contribuye a una comprensión más profunda de la compleja relación entre la sostenibilidad y el desempeño financiero en la región. Además, destaca los retos y oportunidades que las empresas latinoamericanas enfrentan al momento de alinear su desempeño ambiental con su rentabilidad. De igual forma, pone de manifiesto la necesidad de desarrollar estrategias y mecanismos más efectivos para reducir la brecha entre los resultados en materia ambiental y financiera. A pesar de los avances logrados en América Latina en la consolidación de prácticas ambientales, persiste la apremiante necesidad de crear estrategias sólidas que integren de manera eficiente la sostenibilidad y la rentabilidad.
Originalidad: Este estudio ofrece valiosas orientaciones para los responsables del diseño de políticas, inversionistas y empresas que desean comprender la interacción entre la sostenibilidad y el éxito financiero en América Latina.
Palabras clave: desempeño ambiental, América Latina, desempeño financiero, puntuación ESG, datos de panel, rentabilidad de los activos.
Clasificación JEL: 044, F30, O54.
During the decade spanning from 2010 to 2019, the world witnessed high levels of climate change, with global temperatures being the warmest ever recorded (
In this regard, core business strategies should incorporate environmental concerns (
Furthermore, the growing sustainability mindset has led businesses to follow a positive trend that not only concentrates on economics but also on ESG matters (
Firms can create shared value in several ways, including reducing raw material costs and minimizing natural resource depletion (
Recent literature in the field has explored how investors are looking for firms capable of developing mitigation, adaptation, and climate risk strategies (
This study makes two-fold contributions to the field. First, to provide a better understanding of the relationship between financial and environmental performance, it offers an in-depth scientometric analysis that identifies research areas in the field and its evolution. Second, it provides new evidence and insights into the relationship between financial and environmental performance in Latin America, where research in this area is scarce. This highlights the growing importance of environmental issues within the core operations of Latin American firms. Also, the findings might inspire researchers and professionals to broaden their knowledge on sustainable development and criteria involving the environment as the center topic and its parameters. In addition, the findings could spur further studies focused on sustainability matters and financial performance, with an emphasis on Latin America, where research on this topic has not yet been conducted. Such new studies could also lay out roadmaps for improving the understanding of the relationship between ESG scores and firms’ performance.
This study conducted a scientometric review of the existing theoretical and empirical literature on the relationship between financial and environmental performance. By employing social network analysis, it was possible to identify specific research trends in the field. To source research papers, the Scopus database was used given its solid reputation (
Based on the review, two clearly discernible research trends were identified and subjected to analysis. Figure 1 illustrates the interconnections among the most prominent studies into environmental and financial performance (upper part), as well as the trajectories of research in this domain (bottom part).
The first research trend revolves around the singularities of environmental performance and its impact on firms’ financial performance. In this context, the effects of a firm’s green spending have been found to be consistent and positively associated with carbon emissions and environmental performance. Furthermore,
In this same vein,
Based on the key findings in this research trend,
This first research trend is characterized by firms increasingly requiring quantitative measures to assess their environmental performance in domains such as pollution control, waste management, and natural resource management. In this respect,
Furthermore, firms seeking to enhance their environmental performance should focus on improving their environmental processes. This entails developing an environmental strategy, increasing employee awareness of environmental issues, supporting change initiatives, and ensuring staff commitment to environmental goals (
The second research trend delves into the financial implications of environmental practices and financial performance. Concerning this trend,
From this literature review it is clear that, due to the limited number of studies on the subject, this field represents a multifaceted area of research with diverse professional and academic branches. In addition, it is confirmed that there is a scarcity of studies that explain the relationship between financial and environmental performance in Latin America. Consequently, this study presents an opportunity to investigate whether environmental performance has some effect on financial performance in Latin American firms and thus fill the identified knowledge gap.
Environmental performance in Latin America
Over the last decade, there has been a growing interest in environmental performance in Latin America. Research conducted in most Latin American countries has shed light on how policies significantly impact emissions (
According to the
Nonetheless, although there is evidence that environmental planning results in improved returns on investments and a better reputation, most Latin American firms struggle to efficiently implement robust environmental policies (
The growing interest in environmental and financial performance has led to a broad field of research. Specific theories have been developed from multiple perspectives, including economic, regulatory, organizational, and behavioral approaches (
This study focused on firms headquartered in Latin America, particularly those that provided information on financial and environmental factors to the Eikon Refinitiv Thomson Reuters database for the years 2015 to 2020. Specifically, this data includes the Environmental Pillar Score (EPS), Return on Assets (ROA), total assets, country of headquarters, and the ESG score.
The Eikon Refinitiv Thomson Reuters database has been previously used in relevant research on ESG matters (
| Industries | (%) | Industries | (%) |
| Aerospace & Defense | 0.27% | Highways & Rail Tracks | 1.88% |
| Agricultural Chemicals | 0.27% | Homebuilding | 0.88% |
| Airlines | 1.61% | Independent Power Producers | 2.42% |
| Airport Operators & Services | 0.81% | Industrial Machinery & Equipment | 0.27% |
| Aluminum | 0.27% | Integrated Oil & Gas | 0.81% |
| Apparel & Accessories | 0.27% | Integrated Telecommunications Services | 2.69% |
| Apparel & Accessories Retailers | 0.81% | Investment Banking & Brokerage Services | 0.54% |
| Appliances, Tools & Housewares | 0.27% | Investment Holding Companies | 0.54% |
| Auto, Truck & Motorcycle Parts | 1.61% | Investment Management & Fund | 0.27% |
| Banks | 10.48% | Iron & Steel | 2.69% |
| Brewers | 1.08% | IT Services & Consulting | 0.27% |
| Broadcasting | 1.08% | Leisure & Recreation | 0.54% |
| Business Support Services | 1.88% | Life & Health Insurance | 1.08% |
| Commercial Printing Services | 0.27% | Managed Healthcare | 1.08% |
| Commercial REITs | 0.54% | Marine Freight & Logistics | 0.27% |
| Commodity Chemicals | 1.08% | Marine Port Services | 1.08% |
| Construction & Engineering | 1.61% | Miscellaneous Educational Service | 0.81% |
| Construction Materials | 2.15% | Multiline Insurance & Brokers | 0.54% |
| Construction Supplies & Fixtures | 0.54% | Natural Gas Utilities | 2.15% |
| Consumer Goods Conglomerates | 0.81% | Non-Alcoholic Beverages | 1.34% |
| Consumer Lending | 0.54% | Oil & Gas Exploration and Production | 1.61% |
| Corporate Financial Services | 0.81% | Oil & Gas Refining and Marketing | 2.42% |
| Department Stores | 2.42% | Oil & Gas Transportation Services | 0.27% |
| Discount Stores | 0.27% | Online Services | 0.27% |
| Distillers & Wineries | 0.54% | Paper Products | 1.34% |
| Diversified Chemicals | 0.54% | Passenger Transportation, Ground | 0.81% |
| Diversified Mining | 1.08% | Personal Products | 0.54% |
| Drug Retailers | 0.27% | Pharmaceuticals | 0.81% |
| Electric Utilities | 6.99% | Professional & Business Education | 0.54% |
| Electrical Components | 0.27% | Property & Casualty Insurance | 0.54% |
| Financial & Commodity Service | 1.61% | Real Estate Rental Development | 5.38% |
| Fishing & Farming | 1.88% | Reinsurance | 0.27% |
| Food Processing | 5.38% | Restaurants & Bars | 0.81% |
| Food Retail & Distribution | 2.42% | Schools, Colleges & Universities | 0.54% |
| Footwear | 0.81% | Software | 0.54% |
| Forest & Wood Products | 0.54% | Specialty Mining & Metals | 1.88% |
| Gold | 0.27% | Tobacco | 0.27% |
| Ground Freight & Logistics | 1.08% | Water & Related Utilities | 1.34% |
| Healthcare Facilities & Services | 0.81% | Wireless Telecommunications Services | 0.62% |
| Heavy Machinery & Vehicles | 0.81% |
In light of the identified knowledge gap, the following research question was formulated: How is the EPS related to the financial performance of firms in Latin America? Given the lack of consensus in the existing literature regarding a statistically significant inverse effect of the EPS on financial performance, the following null hypothesis (H0) and alternative hypothesis (H1) were proposed to address the research question:
Null hypothesis (H0): The EPS does not significantly affect the ROA of firms in Latin America.
Alternative hypothesis (H1): The EPS does have a significant effect on the ROA of firms in Latin America.
Data and variables
Dependent variable: In this study, the variable of interest was Return on Assets (ROA), which is a financial ratio that indicates how profitable a firm is concerning its total assets (
Independent variable: This study employed the Environmental Pillar Score (EPS), calculated using the Eikon Refinitiv Thomson Reuters database. This score encapsulates several aspects, including emissions, waste management, biodiversity, environmental supply chain, and water and energy resource utilization. These aspects enable market participants to make informed decisions about a low-carbon transition. The EPS is part of a suite of social and governance indicators, which comprise the ESG pillar scores.
Control variables: To identify the variables that can significantly impact ROA, a literature review was conducted (
Moderating variable: The country of headquarters was used in this study as a moderating variable to assess the importance of analyzing the Latin American countries under study individually or the region as a whole (
Before analyzing the relationship between the EPS and ROA, it is crucial to examine the current status of the EPS in the countries in the sample. Given the number of firms in each country, the data for 2020 reveals varying mean EPS values for the different countries. Brazil, which is the one with the most firms, boasts a mean EPS of approximately 40.8, while Mexico records 43.3, Argentina 28.8, Chile 42.4, Peru 33.9, Colombia 52.7, Puerto Rico 10.6, Panama 34.2, and Uruguay 73.3, as reported in Table 2. These results suggest that, in Latin American countries, updating EPS results for companies is not a common practice. Interestingly, the country with the highest EPS is Colombia, followed by Mexico. In the case of Colombia, this could mean that the firms reporting their EPS have high scores, which leads to these results. In contrast, in the case of Mexico, which includes a total of 60 firms, the EPS value is significant and indicates that these firms have an actual good EPS. Furthermore, there is a notable difference between the EPS values of firms in Argentina and Mexico, despite both countries having almost the same number of reports made by firms in 2020.
| Country | Number of firms | Mean EPS | Std. Dev. |
| Argentina | 57 | 28.80923 | 22.85525 |
| Brazil | 142 | 40.85563 | 28.71411 |
| Chile | 46 | 42.48882 | 28.24260 |
| Colombia | 24 | 52.72974 | 23.02632 |
| Mexico | 60 | 43.37536 | 27.13688 |
| Panama | 3 | 34.32742 | 43.88247 |
| Peru | 34 | 33.95512 | 24.98384 |
| Puerto Rico | 5 | 10.61919 | 13.52407 |
| Uruguay | 1 | 73.34465 |
A robust perspective on the ROA and the EPS across different industries was adopted in this study. To understand the relationship between the EPS and firms’ performance in the sample, a core model was tested twice, with one iteration incorporating the ESG score as a control to account for the overall impact. The core model is outlined as follows:
Model 1: ROA ~ EPS + ESG score
Additionally, the following are the models that included country of headquarters as a moderating variable and total assets:
Model 2: ROA ~ EPS + ESG score + Country of headquarters
Model 3: ROA ~ EPS + ESG score + Total assets
Model 4: ROA ~ EPS + ESG score + Country of headquarters + Total assets
Model 5: ROA ~ EPS + ESG score + Country of headquarters with robustness
Model 6: ROA ~ EPS + ESG score + Country of headquarters + Total assets with robustness
As observed, Model 5 corresponds to Model 2 with added robustness. Similarly, Model 6 corresponds to Model 4 with added robustness.
Furthermore, the analysis of the mean EPS for the study periods reveals that, in the majority of the countries, the mean EPS is above 30, with a standard deviation greater than 20, as reported in Table 3. This suggests that over the last years, Latin American firms have seen an increase in the number of them reporting their EPS, as well as an improvement in the EPS results. Importantly, these results are not that statistically significant, given the number of firms that were included in the analysis. However, it seems that the firms have managed to maintain their EPS levels, as shown in Figure 2.
| Country | Mean EPS | Std. Dev. |
| Argentina | 24.48426 | 22.172061 |
| Brazil | 42.73941 | 28.246418 |
| Chile | 38.39381 | 28.986128 |
| Colombia | 49.95961 | 22.787308 |
| Mexico | 40.66443 | 27.676959 |
| Panama | 30.22822 | 31.536349 |
| Peru | 24.28769 | 22.471003 |
| Puerto Rico | 9.44255 | 11.219519 |
| Uruguay | 58.32705 | 9.418768 |
Variables | ROA | EPS | ESG scores | Total assets |
(1) ROA | 1 | |||
(2) EPS | 0.03 [0.2691] | 1 | ||
(3) ESG score | 0.01 [0.5452] | 0.72*** [0.0000] | 1 | |
(4) Total assets | 0.03 [0.1812] | 0.12*** [0.0000] | 0.13*** [0.0000] | 1 |
| p-value in brackets. ***p-value < 0.001, ** p-value < 0.01, * p-value < 0.05 H0: Zero Pearson correlation | ||||
Although there is evidence of the positive effects on firm performance resulting from improved environmental performance (
As shown in Table 5, the results of the multicollinearity test using the Variance Inflation Factor (VIF) indicate that none of the variables exhibited a VIF value higher than 10. This means there is no problem in employing these variables in the regression models. The resulting VIF values can thus be interpreted as suggesting a moderate correlation between the variables. According to the R documentation, taking the square root of the VIF reveals how big the standard error of the estimated coefficient is when the predictor is independent of the other variables (
Multicollinearity with the EPS - |
||
VIF test |
||
ESG score | Total assets | ROA |
1.016617 | 1.017465 | 1.001406 |
Best model |
|
H0: multiple regression vs. H1: fixed-effects regression |
|
F-test for individual effects |
|
p-value | 0.03084 |
Model 1 (MLR + ROA) | Model 2 (Fixed effect + ROA) |
|
EPS | 4.016e-05 [0.334] (4.159e-05) | 7.9554e-06 [0.8529941] (4.2926e-05) |
ESG score | -6.514e-07 [0.781] (2.346e-06) | -3.3740e-07 [0.8856222] (2.3452e-06) |
Brazil | 8.9598e-03*** [0.0007228] (2.6453e-03) |
|
Chile | 8.8542e-03** [0.0049085] (3.1435e-03) |
|
Colombia | 7.0128e-03 [0.0695792] (3.82621e-03) |
|
Mexico | 1.2399e-02*** [3.588e-05] (2.9924e-03) |
|
Panama | 9.5205e-04 [0.9137354] (8.7873e-03) |
|
Peru | 2.8210e-03 [0.4172865] (3.4770e-03) |
|
Puerto Rico | -2.0589e-04 [0.9768414] (7.0916e-03) |
|
Uruguay | 3.5104e-03 [0.81438221] (1.4950e-02) |
|
Observations | 1,705 | 1,708 |
Residual sum of squares square | 0.03311 | 18.599 |
R2 | 0.000761 | 0.014295 |
p-value | 0.5226 | 0.006561 |
Moreover, the results of regression model 2 suggest that there is no significant relationship between the EPS and firm performance for Latin American firms based on the analyzed data. Nonetheless, there was a slight increase in the ROA of the three countries under study as the years passed by. Importantly, ROA and the EPS in the correlation matrix were lower than those in regression model 2. Furthermore, as mentioned by
Just as with the Model 1, a test was carried out for the models that incorporated the total assets variable. According to the results, which are presented in Table 8, Model 4 was the best performing model.
Best model with the total assets variable |
|
H0: multiple regression vs. H1: fixed-effects regression |
|
F-test for individual effects |
|
p-value | 0.02761 |
Model 3 (MLR + ROA) | Model 4 (Fixed effect + ROA) |
|
EPS | 4.300e-05 [0.302] (4.162e-05) | 1.0763e-05 [0.8020856] (4.2932e-05) |
ESG score | -4.619e-07 [0.844] (2.349e-06) | -1.0316e-07 [0.9649576] (2.3478e-06) |
Total assets | -1.515e-08 [0.141] (1.029e-08) | -1.7684e-08 [0.0856514] (1.0282e-08) |
Brazil | 9.1623e-03*** [0.0005492] (2.6464e-03) |
|
Chile | 9.1662e-03** [0.0036296] (3.1469e-03) |
|
Colombia | 7.1206e-03 [0.0652804] (3.8604e-03) |
|
Mexico | 1.2478e-02*** [3.175e-05] (2.9910e-03) |
|
Panama | 9.7136e-04 [0.9119421] (8.7822e-03) |
|
Peru | 2.8402e-03 [0.4138531] (3.4750e-03) |
|
Puerto Rico | 1.3382e-04 [0.9849443] (7.0902e-03) |
|
Uruguay | 3.3850e-03 [0.820827] (1.4942e-02) |
|
Observations | 1,691 |
|
Residual sum of squares square | 18.301 |
|
R2 | 0.016016 |
|
p-value | 0.0040313 |
Model 5 (FE + R + ROA) | Model 6 (FE + R + ROA) |
|
EPS | 0.0000079554 [0.8955] (0.0000575520) | 0.00001076258 [0.8595] (0.0000577236) |
ESG score | -0.0000003374 [0.8849] (0.0000022155) | -0.00000010316 [0.9642] (0.00000218892) |
Total assets | -0.00000001768 [0.3654] (0.00000001777) |
|
Brazil | 0.0089597756* [0.0306] (0.0030011402) | 0.00916231881* [0.0327] (0.00312785997) |
Chile | 0.0088542411* [0.0416] (0.0032515683) | 0.00916617788* [0.0377] (0.00326686126) |
Colombia | 0.0070127911 [0.0695] (0.0030446913) | 0.00712061083 [0.0685] (0.00307651023) |
Mexico | 0.0123991722* [0.0104] (0.0031080913) | 0.01247782183* [0.0105] (0.00313345614) |
Panama | 0.0009520532 [0.9140] (0.0083833061) | 0.00097136339 [0.9122] (0.00837380107) |
Peru | 0.0028209817 [0.3469] (0.0027178157) | 0.00284020444 [0.3444] (0.00272092610) |
Puerto Rico | -0.0002058921 [0.9309] (0.0022592753) | 0.00013381676 [0.9594] (0.00249956029) |
Uruguay | 0.0035104480 [0.8894] (0.0239983402) | 0.00338496515 [0.8938] (0.02410701986) |
Residual standard error | 0.03292 | 0.0329 |
F-statistic (full model) p-value | 0.003079 | 0.001922 |
F-statistic (proj. model) p-value | 0.301 | 0.3584 |
Cluster error in parenthesis - [p-value] |
||
***p-value < 0.001, **p-value < 0.01, *p-value < 0.05 |
||
Model 1 (OLS + ROA) | Model 2 (FE + ROA) | Model 3 (OLS + ROA + TA) | Model 4 (FE + ROA + TA) | Model 5 (FE + R + ROA) | Model 6 (FE + R + ROA + TA) |
|
EPS | 0.00004 (0.00004) | 0.00001 (0.0004) | 0.00004 (0.00004) | 0.00001 (0.0004) | 0.00001 (0.0001) | 0.00001 (0.0001) |
ESG score | 0.00000 (0.0000) | -0.0000 (0.0000) | 0.00000 (0.0000) | -0.0000 (0.0000) | -0.0000 (0.0000) | -0.0000 (0.0000) |
Total assets | 0.00000 (0.0000) | -0.0000* (0.0000) | -0.0000 (0.0000) |
|||
Brazil | 0.009*** (0.003) | 0.009*** (0.003) | 0.009** (0.003) | 0.009** (0.003) |
||
Chile | 0.009*** (0.003) | 0.009*** (0.003) | 0.009** (0.003) | 0.009** (0.003) |
||
Colombia | 0.007* (0.004) | 0.007* (0.004) | 0.007* (0.003) | 0.007* (0.003) |
||
Mexico | 0.012*** (0.003) | 0.012*** (0.003) | 0.012** (0.003) | 0.012** (0.003) |
||
Panama | 0.001 (0.009) | 0.001 (0.009) | 0.001 (0.008) | 0.001 (0.008) |
||
Peru | 0.003 (0.003) | 0.003 (0.003) | 0.003 (0.003) | 0.003 (0.003) |
||
Puerto Rico | -0.0002 (0.007) | -0.0001 (0.007) | -0.0002 (0.002) | 0.0001 (0.002) |
||
Uruguay | 0.004 (0.015) | 0.003 (0.015) | 0.004 (0.024) | 0.003 (0.024) |
||
Constant | 0.029*** (0.002) | 0.029*** (0.002) | ||||
Observations | 1708 | 1,708 | 1,708 | 1,708 | 1,708 | 1,708 |
R2 | 0.001 | 0.014 | 0.002 | 0.016 | 0.02 | 0.022 |
Adjusted R2 | -0.0004 | 0.006 | 0.0003 | 0.007 | 0.011 | 0.012 |
Model 1 vs. Model 2 | Model 3 vs. Model 4 |
|
p-value | 0.01087 | 0.9489 |
ChiSq | 9.0432 | 0.35713 |
According to the results of the Breusch–Pagan heteroscedasticity test shown in Table 13 (where the null hypothesis suggests homoscedasticity), the p-value of Model 1 and Model 3 was greater than 0.05; therefore, the null hypothesis was not rejected.
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 |
|
BP | 2.4279 | 35.087 | 2.9534 | 34.654 | 35.087 | 34.654 |
p-value | 0.297 | 0.0001206 | 0.3989 | 0.0002826 | 0.0001206 | 0.0002826 |
Based on the results of the endogeneity and heteroscedasticity tests presented in Tables 12 and 13, respectively, Model 1 and Model 3—which followed the OLS method—were found to be the most appropriate ones. Model 1 explained 60.25% of the variation in the dependent variable ROA. Model 3, in turn, accounted for 65.75% of the variation and raised the adjusted R-squared value to 64.3%. These results indicate that the ESG score is a statistically significant predictor of the dependent variable ROA.
In summary, the analysis of Model 1 and Model 3 demonstrates that the ESG score emerges as a highly relevant predictor of the dependent variable. Nevertheless, it is worth noting that Model 3 explained a greater proportion of the variation in the dependent variable and presented a higher adjusted R-squared value compared to that of Model 1.
This paper examined the relationship between ROA and the EPS for firms headquartered in Latin America. Empirical evidence suggests that environmental performance had minimal impact on firms’ financial performance for the six years under analysis. In addition, this study found that although Latin American firms and countries have reached an agreement on environmental practices, their strategies still fall short when it comes to funding projects that prioritize environmental performance with profitable results.
However, positive results were observed in Brazil, Mexico, and Chile, which may be explained by three main factors: First, the EPS of firms in each country exhibited low variability, making it difficult to assess its effect on ROA. Second, the potential for firms to increase profitability by implementing environmental practices, and the positive relationship between environmental and financial performance are not considered when evaluating firms’ performance. Third, these countries have superior business development in comparison to other Latin American countries, as evidenced by the results of all the models. Therefore, these three countries are setting a new standard for environmental and financial performance, paving the way for other firms in Latin America. As a result, firms can improve their environmental performance while increasing or maintaining their profitability.
A study conducted by
Although the null hypothesis (H0) was not rejected for most countries, it would be useful to better classify the EPS sub-variables (i.e., emissions, waste, biodiversity, environmental management systems, product innovation, green revenues, use of water resources, energy, sustainable packaging, and environmental supply chain) to identify the leading Latin American firms in terms of environmental practices. Moreover, the evidence shows that the level of the EPS varies between countries, with Brazil leading the way, followed by Mexico and Chile, considering the number of firms in each country.
Contrary to what was expected, the analysis revealed that the region has experienced a slight increase in the EPS. Even though the data demonstrates that the EPS in most countries does not have a positive relationship with firms’ ROA, ROA was not found to be affected by the EPS in Latin American firms. This could be attributed to the fact that the analysis grouped all environmental factors and firms together, without distinguishing between industries or sectors.
This study contributes to a better understanding of the relationship between the environmental and financial performance of Latin American firms. It shows that firms in the region are increasingly adopting environmental practices although, so far, they appear to have no significant impact on profitability. In addition, it is reasonable to consider that the economic benefits from introducing environmental practices may affect Latin American firms’ decision making regarding whether they should follow the example of European or East Asian firms.
In general terms, the evidence is consistent with the current status of the EPS in the region, but highlights the need for further monitoring firms’ future environmental performance and profitability. In this context, the EPS in Latin America does not have a strong positive correlation with firms’ financial performance. Therefore, the control variables included in the model seem insignificant for firms in this region. In addition, the sub-variables composing the EPS were not classified in the database for a thorough analysis of their correlation with ROA. Nonetheless, an important contribution of this study is that it enhanced the understanding of the EPS in a region with enormous resources and economic potential, while also addressing a key matter: In Latin America, environmental regulations are still under development, and firms have not been required to take progressive actions. Consequently, to establish a positive and significant relationship between the EPS and ROA, it is essential to standardize environmental criteria across the region to better interpret the parameters included in the data.
The growth of the green bond market in the region is expected to maximize the impact of environmental performance on financial outcomes. Therefore, similar results to those observed in Brazil, Chile, and Mexico can be anticipated. Despite the valuable contributions of this study, some limitations should be acknowledged. Although efforts have been made to encourage both large and small firms to report their ESG results, it is imperative for more firms to establish disclosure mechanisms as part of their corporate strategy and accountability to stakeholders, especially investors.
Finally, the results of the study reveal a limited data classification, which constitutes a starting point for further research. Thus, to broaden the scope of the present study, data could be grouped by sectors and the EPS sub-variables. Furthermore, future studies should also examine the environmental compensation regulations and practices that Latin American firms need to adopt by country, focusing on how environmental performance can impact a firm’s capital structure. It would also be interesting to analyze the relationship among a firm’s return on equity, ROA, and the EPS. This approach could have great impact on small and medium-sized firms, where research on ESG issues is limited.
The authors declare no conflict of financial, professional, or personal interests that may inappropriately influence the results that were obtained or the interpretations that are proposed here.
In this study, all the authors made a significant contribution, as follows:
Camila Ospina-Patiño: She participated in the design and development of the research. As well as in the analysis and interpretation of the results, writing of the text, and final revision of the manuscript.
Juan David González-Ruiz: He participated in the conception, design, and development of the research. As well as in the analysis and writing of the text and final revision of the manuscript.
Nini Johana Marín-Rodríguez: She participated in the development of the research. As well as in the analysis and final revision of the manuscript.
We wish to express our gratitude to the editorial team and the anonymous reviewers for their invaluable contribution to enhancing the quality of this paper. Their thorough review, constructive feedback, and insightful suggestions have played a pivotal role in substantially raising the value of our study.