Draft- Final Paper

Analyzing the Influence of Legal & Governmental Structures’ on Corporate ESG Reporting

By Niki Linganur

Introduction

As Environmental, Social, and Governance (ESG) enters its third decade of prominence, institutions driving sustainability reporting must contend with varying market contexts. While ESG as a concept first gained mainstream notability in 2004 through a United Nations Environmental Program report, the organizations driving ESG compliance today are disproportionately in advanced economies (UNEP FI, 2004). While there have been many disparate efforts to consolidate these, there is not one uniform framework for ESG reporting globally. The most widely used international frameworks (GRI, SASB, etc.) are typically developed and maintained by institutions registered in the United States or Western Europe.

It is unclear how ESG reporting as a concept will fare as it continues to grow beyond the borders of the countries that have been the primary drivers. A wider variety of country contexts will introduce a complex distribution of factors that could impact the willingness and ease of companies to comply. Research is limited on what factors determine a country’s corporate ESG reporting rate. Most of this existing research tends to exclusively focus on European and Western markets. However, the majority of the world population lives in emerging markets with significantly different institutional factors than the developed markets where these ESG standards have primarily been designed. Countries where ESG standards have been set typically tend to be wealthier, foster stronger rule of law, have resource-rich firms, and have a reputation for more robust support of public institutions for business. Intuitively then, it could be possible that ESG reporting requirements might be easier to fulfill in countries with wealthier firms and better institutional support. 

There is a rich and growing literature that attempts to understand what drives ESG reporting among firms. Yet, most of this literature is concentrated on advanced EU economies. A large cross-section of literature examines how national-level institutional factors can influence a firm’s likelihood to comply with sustainability reporting requirements. Villiers et al. also found in their 2016 study that higher levels of disclosure are typically more pronounced in countries with higher levels of democracy, government effectiveness, regulatory quality, and press freedom. Helfaya et al research further elaborates on this by demonstrating that firms are influenced by the country-level governance factors as firm behavior tends to be in line with social norms, economic patterns, and investor protection of that country (Helfaya et al., 2023). Both studies connect their finding to the role of institutions in promoting stakeholder pressure on firms. According to Milton Freeman’s definition stakeholder theory emphasizes an organization’s accountability to various stakeholders influencing its operations and value creation, including investors, consumers, suppliers, employees, local government, and the larger community (Del Gesso and Lodhi, 2024). 

Data:

To ascertain the rate of sustainability reporting I will use KPMG’s Sustainability Reporting Rates Data from 2022. 

KPMG researchers collected sustainability reporting data across 58 countries from the largest 100 companies in each country, surveying a total of 5,800 companies. They surveyed; 1) the Rate of sustainability reporting, 2) the number of companies that include ESG sustainability information in their annual reports, 3) the number of companies that link business activities and SDGs in their annual report across each country, and put together a weighted rate of reporting for each country across the 100 companies in each country. This dataset will serve as the dependent variable. 

The remaining World Bank indicators were taken from the 2022 survey. Hours of Senior Management Time Spent on Government Regulations measures the time spent dealing with the requirements of government regulations is the proportion of senior management’s time, in a typical week, that is spent dealing with the requirements imposed by government regulations (e.g., taxes, customs, labor regulations, licensing, and registration, including dealings with officials, and completing forms).

Descriptive Statistics:

Table 1 details the descriptive statistics for my analysis. 

Table 1:

options(repos = c(CRAN = "https://cran.rstudio.com/"))
install.packages("readxl")

The downloaded binary packages are in
    /var/folders/yd/c2zm5hrx3z9f72991hsqsbqh0000gn/T//Rtmpb7mWjW/downloaded_packages

library(readxl)
library(knitr)
# Load the dataset
data <- read_excel("/Users/nikhila/Desktop/KPMG World Bank Data.xlsx")
summary_stats <- summary(data)
kable(summary_stats, caption = "Descriptive Statistics Table")

Descriptive Statistics Table

	Country	Rate of Sustainability Reporting	Rule of law score (-2.5 to 2.5)	Hour per week spent dealing with the requirements of government regulations (% of senior management time)
	Length:210	Min. :0.1400	Length:210	Min. : 2.00
	Class :character	1st Qu.:0.4200	Class :character	1st Qu.: 9.00
	Mode :character	Median :0.5900	Mode :character	Median :16.80
	NA	Mean :0.5793	NA	Mean :14.77
	NA	3rd Qu.:0.7450	NA	3rd Qu.:20.00
	NA	Max. :0.9700	NA	Max. :28.67
	NA	NA’s :170	NA	NA’s :170

Results & Findings: ** **

** **Model 1:

Rate of Sustainability Reporting = 0.550 + 0.054 * Rule of Law score (-2.5 to 2.5)

• Intercept (0.550): The intercept represents the expected Rate of Sustainability Reporting when the Rule of Law score is zero. In this case, it suggests that when the Rule of Law score is zero, the expected Rate of Sustainability Reporting is 0.550.

• Rule of Law score (-2.5 to 2.5) (0.054): The coefficient for Rule of Law score represents the change in the Rate of Sustainability Reporting for a one-unit change in Rule of Law score while holding other variables constant. In this case, a one-unit increase in the Rule of Law score is associated with a 0.054 increase in the Rate of Sustainability Reporting. However, the p-value associated with this coefficient is 0.218, which is greater than the conventional significance level of 0.05. Therefore, we fail to reject the null hypothesis that there is no relationship between Rule of Law score and the Rate of Sustainability Reporting at the 5% significance level.

# Convert Rule of law score (-2.5 to 2.5) to numeric
data$`Rule of law score (-2.5 to 2.5)` <- as.numeric(data$`Rule of law score (-2.5 to 2.5)`)

options(repos = c(CRAN = "https://cran.rstudio.com/"))

install.packages("broom")

The downloaded binary packages are in
    /var/folders/yd/c2zm5hrx3z9f72991hsqsbqh0000gn/T//Rtmpb7mWjW/downloaded_packages

install.packages("knitr")

The downloaded binary packages are in
    /var/folders/yd/c2zm5hrx3z9f72991hsqsbqh0000gn/T//Rtmpb7mWjW/downloaded_packages

library(broom)
library(knitr)

# Run linear regression
regression_model <- lm(`Rate of Sustainability Reporting` ~ `Rule of law score (-2.5 to 2.5)`, data=data)

# Tidy the regression results
tidy_results <- tidy(regression_model)
# Print tidy results as a table
kable(tidy_results, align = "c")

term	estimate	std.error	statistic	p.value
(Intercept)	0.5503036	0.0420464	13.088002	0.0000000
Rule of law score (-2.5 to 2.5)	0.0537827	0.0429380	1.252567	0.2180173

Model 2:

Rate of Sustainability Reporting = 0.150 - 0.005 * Rule of Law score (-2.5 to 2.5) + 0.029 * Hour per week spent dealing with government regulations (%)

• Intercept (0.150): Similar to Model 1, the intercept represents the expected Rate of Sustainability Reporting when both Rule of Law score and Hours per week spent dealing with government regulations are zero.

• Rule of Law score (-2.5 to 2.5) (-0.005): In this model, the coefficient for Rule of Law score is negative (-0.005), indicating that a one-unit increase in Rule of Law score is associated with a 0.005 decrease in the Rate of Sustainability Reporting. However, the p-value associated with this coefficient is 0.764, suggesting that it is not statistically significant.

• Hour per week spent dealing with government regulations (%) (0.029): The coefficient for Hours per week spent dealing with government regulations is positive (0.029), indicating that a one-unit increase in the percentage of senior management time spent dealing with government regulations is associated with a 0.029 increase in the Rate of Sustainability Reporting. This coefficient is statistically significant with a p-value of < 0.001.

# Run linear regression
regression_model <- lm(`Rate of Sustainability Reporting` ~ `Rule of law score (-2.5 to 2.5)`+ `Hour per week spent dealing with the requirements of government regulations (% of senior management time)`, data=data)

# Tidy the regression results
tidy_results <- tidy(regression_model)
# Print tidy results as a table
kable(tidy_results, align = "c")

term	estimate	std.error	statistic	p.value
(Intercept)	0.1495362	0.0316724	4.7213442	0.0000333
Rule of law score (-2.5 to 2.5)	-0.0051610	0.0170717	-0.3023145	0.7641053
Hour per week spent dealing with the requirements of government regulations (% of senior management time)	0.0292882	0.0019867	14.7424300	0.0000000

Discussion & Conclusion:

In conclusion, based on these regression results, it appears that the Hours per week spent dealing with government regulations has a significant positive relationship with the Rate of Sustainability Reporting. However, there is insufficient evidence to conclude that the Rule of Law score has a statistically significant relationship with the Rate of Sustainability Reporting in the studied countries.

# Load necessary libraries
library(ggplot2)

# Create scatter plot
ggplot(data, aes(x = `Hour per week spent dealing with the requirements of government regulations (% of senior management time)`, y = `Rate of Sustainability Reporting`)) +
  geom_point() +
  labs(x = "Hour per week spent dealing with the requirements of government regulations (% of senior management time)", y = "Rate of Sustainability Reporting") +
  ggtitle("Rate of Sustainability Reporting vs. Hours spent with Gov. Regulations")

It is possible that companies who feel highly burdened by regulation perceive voluntary disclosure as a potential risk mitigation from further regulatory burdens. Corporate executives likely perceive that despite not always being obliged to disclose ESG information, it will ultimately save their companies time. Firm leadership could be looking at the total amount of time needed to engage with government institutions. They might perceive that much of the time engaging with the government is disproportionately focused on unexpected requests for data or investigations. If instead, firms send a comprehensive document that details a wide variety of firm data concerning ESG categories they might ultimately spend less time engaging with the government. This preemptive disclosure can minimize data requests, data collection, and the government’s perception of the need to regulate. At the very least, firms may perceive that disclosures in high regulatory burden markets at least make the relationship with governments more predictable.