ESG Maturity and Firm Valuation in an Emerging Market: Evidence of Sectoral Heterogeneity

Abstract

This study examines the relationship between ESG governance maturity and market valuation in the context of Kazakhstan. The analysis is based on a balanced panel of 13 listed companies covering the period 2019–2024. Firm value was measured using Tobin’s Q coefficient, and ESG maturity was assessed using a specific index that describes the extent to which environmental, social, and governance practices are institutionally embedded within an organization. The results of the fixed-effects model suggest that there is a positive relationship between the aggregate ESG score and a firm’s market value, but it is not statistically significant. When considering the sectoral breakdown, a difference is observed: ESG maturity is positively and significantly associated with market valuation for companies in the financial sector, while no such relationship was found for the non-financial sector. No significant relationship was found between ESG maturity and return on equity (ROE). The results obtained show that the impact of ESG factors in the case of Kazakhstan is not equally visible in all sectors and that, at the present stage, its influence is mainly more pronounced in the financial sector.

1. Introduction

Environmental, economic, and social (ESG) practices have become increasingly important in corporate governance and capital markets worldwide. Although ESG engagement is often associated with improved reputation and risk mitigation, empirical evidence regarding its impact on firm market valuation remains mixed, particularly in emerging market contexts. In Kazakhstan, where ESG institutionalization and disclosure standards are still developing, it remains unclear whether ESG maturity is reflected in market-based valuation indicators.

At present, empirical evidence on how ESG governance maturity affects firm market valuations in emerging economies remains limited and inconclusive. In particular, there is a lack of research focused on Kazakhstan, where ESG institutionalization and disclosure practices are still developing, making it an important context for examining whether ESG maturity is reflected in market valuation indicators.

As one of the fastest-growing economies in Central Asia, Kazakhstan offers an interesting context for studying ESG practices. Thanks to its vast resources, emerging markets and increasing incentives for sustainable development, Kazakhstan’s corporate sector has begun to implement ESG principles. But many companies are still slowly integrating ESG into their business models.

Kazakhstan is an emerging market where ESG regulation and disclosure practices are still developing, and capital market depth is still limited. As such, the institutional environment may influence how ESG maturity is reflected in market valuations. As a result, the emerging market context is clearly taken into account in interpreting the empirical effects.

The aim of this study is to examine the impact of ESG governance maturity on corporate market capitalization in Kazakhstan. This study examines how ESG maturity affects the market value of companies operating in an emerging economy such as Kazakhstan.

To examine the relationship between ESG maturity and firm valuation, Tobin’s Q is used as the dependent variable representing market-based firm value. The ESG management maturity index is an index that measures the extent to which ESG practices are integrated into corporate governance and operations, allowing for a deeper understanding of the impact of ESG on a firm’s performance. The study is relevant to decision-makers in Kazakhstan and similar emerging markets. It examines the relationship between ESG maturity and firm valuation. The paper highlights the importance of sustainable business practices, which can be used to inform investment policy. The remainder of the paper is structured as follows. Section 2 reviews the relevant literature and develops the theoretical background. Section 3 describes the data, construction of the ESG maturity index, and the econometric methodology. Section 4 presents the empirical results. Section 5 discusses the findings, and Section 6 concludes the paper.

Finally, the implications of the findings are discussed. The final section of the paper provides directions for future research and practical advice for corporate managers.

Based on the literature review and the identified research gap, the following hypotheses are formulated:

H1. 

ESG management maturity is positively associated with firm market valuation.

H2. 

The association between ESG maturity and firm valuation is stronger in the financial sector than in non-financial sectors.

H3. 

ESG maturity is not significantly associated with accounting profitability (ROE).

2. Literature Review

The literature relevant to this study can be grouped into four interrelated strands: (1) studies on ESG practices and firm market valuation; (2) studies that focus on context-specificity and industry heterogeneity; (3) financial determinants of firm value, including capital structure and profitability; and (4) governance quality and reporting transparency as mechanisms that influence market valuation. Together, these strands provide a conceptual framework for examining the maturity of ESG governance as an institutional driver of firm value in emerging markets.

2.1. ESG Practices and Firm Market Valuation

In recent years, the number of studies on the relationship between ESG practices and corporate value has increased significantly. In many empirical works, Tobin’s Q is used as a predictive indicator that characterizes investors’ expectations regarding the future development prospects and risk level of a company.

The impact of ESG initiatives on financial performance is not uniform [1,2]. That is, the impact of ESG initiatives can be positive in some cases and negative in others. For example, in some cases, the impact on return on assets (ROA) may decrease, but as ESG indicators improve, Tobin’s Q may increase. This indicates that investors perceive ESG results as an indicator of a company’s long-term sustainability. In addition, it has been noted that the reliability and transparency of strategic sustainability reporting play an important role in increasing a company’s market value [3]. This is because investor perception and trust are directly related to the long-term evaluation of a company.

The relationship between ESG factors and the financial performance of S&P 500 companies for the period 2013–2023 was studied using panel data and a fixed-effects model [4]. The results show a moderate positive relationship between ESG practices and Tobin’s Q, while the relationship with short-term returns appears weak. These results suggest that investors view ESG practices as indicators of good governance and long-term sustainability.

Companies included in the Nasdaq US Smart Pharmaceuticals Index were analyzed to assess the relationship between ESG factors, controversial indicators, and financial indicators (ROA, ROE, and Tobin’s Q) [5]. Using PLS structural modeling, ESG practices were found to be associated with improvements in all three financial indicators. In addition, controversial indicators were positively correlated with Tobin’s Q. This suggests that increasing the visibility of a company’s information may increase investor attention.

Active engagement in ESG has been shown to improve a company’s financial performance, especially in the long term [6]. Studies have shown that corporate social responsibility (CSR) practices increase competitiveness and support overall firm performance [7,8].

In addition to their direct impact on valuation metrics, a number of studies have examined the mechanisms by which ESG affects the cost of capital. Firms with high ESG performance are perceived as less risky by investors, which can lead to lower debt costs [9]. ESG disclosure has been shown to increase investor confidence by reducing uncertainty and information asymmetry, thereby contributing to higher market value [10].

Overall, the literature suggests that ESG practices can have a positive impact on a firm’s market valuation. However, empirical evidence is patchy and often depends on institutional and industry specificities. Therefore, the relationship between ESG and market valuation may vary across contexts.

2.2. Context-Dependence and Industry Heterogeneity of ESG Effects

Several studies have shown that the impact of ESG is not universal and may depend on regional and institutional characteristics. For example, the introduction of environmental taxes in China has been shown to have a negative impact on the market value of companies in high-polluting industries [11]. Using Tobin’s Q, it is found that an increase in the burden of environmental taxes is associated with a decrease in firm valuation, with differences across regions and company types.

While ESG engagement can increase a company’s market valuation in many cases, this relationship is not always uniform. Its nature may vary depending on the level of ESG integration, the existing regulatory framework, and the relevance of sustainability initiatives for a particular industry. Therefore, it is important to consider industry specificities and the institutional environment of emerging markets when analyzing the impact of ESG on valuation metrics.

2.3. Capital Structure and Financial Determinants of Firm Valuation

The impact of capital structure on firm value and financial performance has been widely discussed in the academic literature. It has been shown that different types of debt leverage affect firm performance during a crisis [12]. Evidence from emerging markets also suggests that leverage has a positive impact on market valuation (Tobin’s Q) and profitability, although the magnitude depends on the type of debt [13,14].

Financial constraints affect corporate behavior, investment decisions, and production processes [15]. Limited access to capital reduces investment, increases risk aversion, and negatively impacts long-term performance. Overall, financial fundamentals such as leverage, profitability, and access to financing remain key determinants of corporate valuation and may shape investors’ perceptions of sustainability strategies.

2.4. Governance, Reporting Quality, and Measurement of Market Valuation

Corporate governance mechanisms and transparency are important for explaining a firm’s market value. Effective governance structures are directly linked to higher market valuations [16]. Regular and transparent reporting improves investors’ understanding of a firm’s financial position and reduces uncertainty [17].

Macroeconomic conditions, including unconventional monetary policies, can also affect corporate performance and valuations during periods of instability [18].

Tobin’s Q remains one of the most widely used measures of corporate market valuation in empirical research. It measures the ratio of a firm’s market value to the replacement cost of its assets and is often used to assess how ESG and CSR practices affect market performance. Alternative constructs of Tobin’s Q have also been proposed in the literature [19].

2.5. ESG Terminology and Research Gap

In this study, it is important to distinguish between several related ESG concepts. ESG principles refer to regulatory sustainability guidelines and standards that define responsible corporate behavior. ESG practices refer to the specific actions and initiatives that firms undertake in the environmental, social, and governance areas. ESG management describes the integration of ESG issues into corporate decision-making processes and governance structures. ESG metrics refer to quantitative indicators used to measure ESG performance outcomes. In contrast, ESG maturity refers to the extent to which ESG governance mechanisms are institutionalized, strategically embedded, and systematically implemented within an organization. The ESG maturity index constructed in this study reflects this institutional dimension rather than outcome-based ESG performance indicators.

Despite the extensive literature on ESG and firm performance, several gaps remain. First, empirical evidence from emerging markets such as Kazakhstan is still limited. Second, most existing research relies on external ESG ratings or disclosure-based metrics, while few studies focus on ESG maturity as an institutional concept for governance. Third, industry heterogeneity remains understudied in the context of emerging capital markets. This study addresses these gaps by constructing an ESG maturity index and examining its relationship with firm market valuation (Tobin’s Q) in Kazakhstan over the period 2019–2024.

3. Materials and Methods

3.1. Research Design

This study adopts a firm-level panel research design to examine the relationship between ESG management maturity and firm market valuation in Kazakhstan over the period 2019–2024. The panel structure allows the analysis to exploit both cross-sectional and, more importantly, within-firm variation over time. The ESG management maturity index constructed in this study is explicitly designed as a time-varying measure. It captures the gradual institutionalization and governance embedding of ESG practices within firms, reflecting annual changes in policies, oversight mechanisms, and implementation structures rather than static disclosure levels. Accordingly, the primary source of identification in the empirical models derives from within-firm changes in ESG maturity across years.

The empirical strategy therefore employs firm fixed-effects (within) estimation. This approach controls for unobservable, time-invariant firm characteristics—such as ownership structure, corporate culture, management traditions, and industry positioning—that may simultaneously influence ESG practices and firm valuation. By focusing on within-firm variation, the fixed-effects specification isolates how incremental improvements in ESG management maturity are associated with changes in market valuation over time, consistent with established methodological standards in corporate finance research [20].

Panel data methods have been successfully used in prior studies examining ESG and firm performance. For example, the impact of ESG disclosures on firm performance in Saudi Arabia has been estimated using panel techniques [21]. This method allows for control over firm-specific characteristics such as ownership structure, which is particularly important when analyzing ESG practices in emerging markets such as Kazakhstan. Similarly, panel data models have been used to estimate the impact of eco-innovation on firm financial performance, applying Tobin’s Q as a measure of firm market value [22].

To address potential heteroskedasticity and within-firm serial correlation, all regression models in this study are estimated using robust standard errors clustered at the firm level. This approach follows established recommendations for panel data analysis in corporate finance [23] and ensures statistically reliable inference in settings characterized by a limited number of firms and relatively short time dimensions.

ESG practice among large listed companies is often reduced to compliance with formal requirements without significant changes in management processes and decision-making mechanisms. Taking into account the institutional context of developing economies, the study gives priority to the depth of measurement of institutional interpretation and the introduction of management methods, rather than obtaining statistical results by expanding the sample size. The quality of the analysis is more important than the number of observations.

Although the empirical design exploits within-firm variation and controls for time-invariant heterogeneity through fixed effects, potential endogeneity concerns cannot be fully ruled out. Firms with higher market valuation may possess greater financial capacity or external pressure to institutionalize ESG governance structures, giving rise to possible reverse causality. While the fixed-effects framework mitigates bias from unobserved firm characteristics, future research could further address this issue using instrumental variables or quasi-experimental designs.

3.2. Sample and Market Context

The sample is selected based on four specific criteria, resulting in a balanced panel of 13 companies with 78 firm–year observations over the six-year period from 2019 to 2024.

First, companies should consistently disclose ESG-related information throughout the observation period. This requirement ensures long-term consistency in ESG measurements. While this criterion may introduce a selection bias toward more proactive and transparent firms, it is essential for constructing a balanced panel and ensuring the longitudinal reliability of the ESG assessment.

Secondly, firms needed to have sufficient financial and market data to calculate Tobin’s Q and the control variable. In particular, it required the availability of accounting statements, information on financial results, and data on prices and the number of outstanding shares. Companies for which these data were systematically missing during the observation period were excluded from the sample. Third, the sample is limited to firms with relatively stable trading activity and sufficient liquidity in the market. Since market valuation methods are based on informative price signals, firms characterized by constant illiquidity or irregular trading operations have been excluded to reduce market valuation interference.

Fourth, companies experiencing serious financial difficulties or the risk of restructuring or delisting during the observation period were excluded to prevent distortion of the estimate due to excessive emissions. This ensures that the results reflect the real relationship between ESG and the valuations of existing businesses, rather than the price dynamics caused by the crisis.

Although the study does not cover the entire population of listed firms in Kazakhstan, it focuses on the largest, financially stable, and actively traded entities. Consequently, while the external validity of the findings to smaller or less transparent firms may be limited, focusing on these systemically important entities ensures that the research captures the segment where ESG integration is most mature and market-driven price signals are most informative.

While one firm in the sample is not listed on the Kazakhstan Stock Exchange (KASE), it is a publicly traded entity listed on a major international exchange (NASDAQ). Its inclusion is justified by its predominant operational and economic footprint in Kazakhstan, combined with the availability of high-quality, continuous market-driven price signals required for an accurate calculation of Tobin’s Q. By including this internationally listed firm, the study ensures that the sample captures systemically important entities that form the backbone of the national economy but attract international capital. This approach maintains econometric consistency by utilizing transparent trading data from highly liquid international platforms, which often provide even more robust valuation signals than local venues in emerging market contexts.

3.3. Building the ESG Management Maturity Index

3.3.1. Conceptual Framework

We have developed our own ESG management maturity index. In the presented study, instead of using ESG ratings from third-party suppliers, the results of which may not match each other, we decided to rely on our own tool. It is carried out on the basis of manual content analysis of corporate reports, annual reports, sustainability reports, and integrated company reports are used as data sources.

Due to differences in coverage, weighting methods, and approaches used, ESG ratings from third-party organizations often show significant discrepancies [24]. For example, the presence of declarative statements about the company’s adherence to environmental or social principles does not in itself indicate a high level of ESG governance. It is much more important that such positions are anchored in concrete institutional content. In particular, the presence of a structural unit or authorized person responsible for ESG issues, the introduction of a system of measurable indicators, and the integration of ESG factors into risk management and strategic planning processes are crucial.

In addition, the systematic consideration of ESG reporting at the board level indicates that governance is being implemented in practice, not in a formal manner. In this regard, the assessment of ESG maturity should be based not only on published statements but also on the actual existence of appropriate mechanisms and their institutionalization within the organization.

These limitations are particularly noticeable in emerging markets. Their data coverage remains fragmented, and disclosure standards vary significantly. In such ratings, the degree of completeness of information disclosure is often confused with the quality of management. This reduces their applicability for institutional analysis [25].

The index focuses not on the results of ESG activities, but on how sustainably and systematically ESG is integrated into the company’s management to avoid the limitations of existing ESG ratings. This approach reflects the growing interest in ESG as a management tool rather than solely as a reporting practice. The internationally recognized ESG system was used to develop the index. This ESG system includes the Global Reporting Initiative (GRI), the Accounting Standards Board for Sustainable Development (SASB), and the United Nations for Responsible Investment (UN PRI) [26,27].

3.3.2. Indicator System and Scoring Methodology

The ESG management maturity index consists of 18 indicators evaluated on a 0–4 scale: (0) no disclosure; (1) symbolic or descriptive; (2) formal policy adoption; (3) operationalized system with partial KPIs; and (4) fully institutionalized system with board-level oversight and continuous improvement. To ensure replicability and minimize subjectivity, a two-stage verification protocol was employed. First, a standardized coding template was used to perform an initial structured extraction of evidence and score assignment across all firm–year observations. Second, a comprehensive manual audit was conducted by the researcher to cross-reference all scorers with original report excerpts. In cases of ambiguity—particularly in distinguishing between ‘symbolic’ and ‘formal’ levels—a reconciliation rule was applied, requiring a targeted deep-dive into sustainability disclosures to validate the final score. This ‘human-in-the-loop’ process ensures high internal consistency and eliminates potential misinterpretations. All coding, verification, and final score assignments were conducted by the research team.

Table 1. ESG Management Maturity Index.

Dimension	Indicator	Description	Scoring Logic (0–4)
E	E1	Environmental management system (ISO 14001) [28]	Policy–System–Board oversight
E	E2	Climate/low-carbon strategy	Commitment–Targets–Governance
E	E3	Environmental risks management	Ad hoc–ERM integration
E	E4	Energy efficiency and emissions control	Measures–KPIs
E	E5	Resource and waste management	Programs–Monitoring
E	E6	Environmental audit and improvement	Internal–External audit
S	S1	Employee training and development	Programs–Quantified KPIs
S	S2	Occupational health and safety (ISO 45001) [29]	Compliance–Zeroinjury systems
S	S3	Employee rights and diversity	Principles–Measurable outcomes
S	S4	Community engagement	Philanthropy–Strategic engagement
S	S5	Supply chain responsibility	Codes–Audited compliance
S	S6	Grievance mechanisms	Informal–Institutionalized
G	G1	Board-level ESG oversight	None–Dedicated committee
G	G2	ESG integration into strategy	Isolated–Strategic embedding
G	G3	Anticorruption framework	Policy–Risk-based system
G	G4	Compliance training	Limited–Systemwide
G	G5	Whistleblowing mechanisms	Internal–Independent channels
G	G6	ESG-ERM integration	Fragmented–Fully integrated

shows the complete structure of the ESG management maturity index, including detailed measurements, indicators, and scoring logic.

3.4. Financial Variables and Data Sources

3.4.1. Market Value and Tobin Ratio

The company’s market capitalization is estimated using the Tobin coefficient, which is calculated using the standard approximation [30]:

$${TQ}_{(\mathrm{i}\mathrm{t})}={\displaystyle \frac{Market {Capitalization}_{(\mathrm{i}\mathrm{t})} + Total {Liabilities}_{(\mathrm{i}\mathrm{t})}}{Total {Assets}_{(\mathrm{i}\mathrm{t})}}}$$

(1)

When replacement cost data are unavailable, this approximation is widely used in corporate finance research [31].

Year-end stock price is operationalized as the closing price on the last trading day of each calendar year, since stock exchanges are not necessarily open on 31 December.

3.4.2. Sources of Market Prices

To ensure the econometric robustness of the Tobin’s Q calculation, the study utilized a strictly balanced panel with no missing observations across the selected variables. This data integrity was achieved through the ex-ante exclusion of firms with incomplete financial or market records during the sample selection phase (as detailed in Section 3.1). Market price data were primarily sourced from the Kazakhstan Stock Exchange (KASE) and supplemented by official international exchange disclosures (e.g., NASDAQ and LSE) for dual-listed entities. To maintain longitudinal continuity and eliminate potential reporting noise, we employed a data triangulation approach using StockAnalysis.com (2024) as a secondary verification tool. Crucially, a strict no-imputation policy was maintained; no synthetic gap-filling methods, such as linear interpolation or mean substitution, were applied to the stock price series. All data points represent authentic, market-driven closing prices, ensuring that the results reflect real market dynamics rather than artificial volatility caused by data estimation.

As we can see in

Table 2. Data Sources.

Data Source	Description	Link	Usage
Kazakhstan Stock Exchange (Primary source)	Historical trading data and issuer disclosures	KASE Official Listing Data	Used for year-end stock prices, trading activity, and issuer-level disclosures for firms listed on the KASE.
NASDAQ (Foreign listings)	Historical stock prices and trading data for firms primarily traded on U.S. exchanges	Nasdaq Official Market Records	Used for year-end closing prices of firms primarily traded on U.S. exchanges.
Supplementary Market Data (Gap-Filling only)	Historical stock price data used exclusively as a supplementary source to cross-validate historical price data	StockAnalysis Financial Database	Used exclusively to cross-validate historical price data when official exchange-level disclosures were incomplete.
Exchange Rates	Official year-end USD/KZT exchange	National Bank of Kazakhstan (NBK) Statistical Database	Used for year-end USD/KZT exchange rates to ensure consistent currency conversion across firms and years.

, the following data sources were used, including data descriptions, relevant references, and specific applications to the study.

3.4.3. Outstanding Shares and Firm-Specific Treatments

Market capitalization is defined as the product of the share prices at the end of the year and the number of ordinary shares outstanding, defined as issued shares except for own shares, which is based on IFRS standards. If the number of shares outstanding under IFRS was not explicitly indicated, the number of shares was used for comparability with the market price in accordance with the listing rules on the stock exchange. For companies whose number of ordinary shares in did not change during the reporting period, the number of outstanding shares in our case was assumed to be unchanged.

3.4.4. Financial Year Consistency

For entities with a 31 March fiscal year-end, such as Freedom Holding Corp. (Almaty, Kazakhstan), data are aligned with the preceding 31 December calendar year-end to maintain longitudinal consistency across the sample. While this 90-day misalignment could theoretically introduce measurement error, a robust sensitivity assessment was performed. By comparing total assets reported in Q3 (31 December) against the subsequent fiscal year-end (31 March) for the 2019–2024 period, we observed a stable variance (averaging 5–10% annually) without significant volatility or structural breaks. This suggests that the alignment strategy preserves the informational integrity of the Tobin’s Q calculation while ensuring that accounting disclosures are fully incorporated into market prices by the valuation date.

It is important to note that the same matching rule applies uniformly to all companies, ensuring that no company is treated asymmetrically.

3.5. Econometric Model Specification

The basic empirical model is specified as follows:

$$Tobin’s Q_{\left\{it\right\}}= {\beta }_0+ {\beta }_{1}ESG\_Maturit{y}_{\left\{it\right\}}+ \sum {\beta }_{k}Control{s}_{\left\{it\right\}}+ {\alpha }_i+ {\delta }_t+ {ϵ}_{\left\{it\right\}}$$

(2)

where $i$ denotes the firm and $t$ represents the year. The control variables include firm size, measured as the natural logarithm of total assets; leverage, defined as the ratio of total liabilities to total assets; and profitability, proxied by ROA. Firm fixed effects (${\alpha }_i$) are included to control for time-invariant unobserved heterogeneity across firms. In addition, year fixed effects (${\delta }_t$) are explicitly incorporated to capture macroeconomic shocks and common time trends affecting all firms. To validate the model specification, several diagnostic tests were conducted. The Hausman test ($p<0.05$) indicates that the fixed-effects (FE) model is preferred over the random-effects model for this sample. Furthermore, the Modified Wald test and the Wooldridge test reveal the presence of heteroscedasticity and serial correlation, respectively. Accordingly, all regressions are estimated using firm-level clustered robust standard errors to ensure consistent and reliable statistical inference.

In addition, the inclusion of year fixed effects serves an important econometric role by absorbing common macroeconomic shocks, regulatory changes, and country-level institutional dynamics that may simultaneously affect firm valuation across all firms each year. By capturing such time-specific effects, year fixed effects mitigate potential cross-sectional dependence in the regression residuals, which is a common concern in single-country panel studies of listed firms.

3.6. Heterogeneity and Robustness of Industry Identification

To examine industry-specific effects, interaction terms between ESG governance maturity and a financial sector indicator (banking and financial services) are introduced. As industry classification is time-invariant at the firm level, the industry dummy is absorbed by firm fixed effects, while the interaction term remains identified through within-firm variation in ESG governance maturity over time.

Given the relatively limited number of firms in the sample, particular attention is paid to inference reliability. Accordingly, all interaction models are estimated using firm-level clustered robust standard errors, which provide valid statistical inference in the presence of heteroskedasticity and within-firm serial correlation and are commonly applied in small-N, short-T panel settings.

3.7. Limitations

The analysis focuses on a limited number of systematically important and liquid companies that reflect the structure of the capital market in Kazakhstan. Although this limits statistical power, it allows for a more accurate and institutionally sound assessment of ESG governance maturity in an emerging market setting.

4. Results

4.1. Descriptive Statistics

Table 3. Descriptive Statistics of Main Variables (N = 78).

Variable	Mean	Std. Dev.	Min	Max
ESG Total Score	2.774	0.764	1.25	3.94
Tobin’s Q	1.209	1.055	0.195	6.657
ROA	0.0776	0.0529	0.0066	0.2641
Leverage	0.538	0.287	0.103	0.995
Firm Size (In assets)	14.186	1.582	10.908	16.757

shows the statistical data of the main variables in the panel regressions. The resulting balanced panel was composed of 78 company–year data from 13 publicly traded companies between 2019 and 2024.

This dataset allows for a robust analysis of the relationship between environmental, social and corporate governance (ESG) performance, and company performance.

The sample shows significant heterogeneity in company valuations, with Tobin’s Q ranging from 0.19 to 6.66. This reflects differences in market perceptions of companies. The skewness of Tobin’s Q to the right (skewness = 2.61) indicates that companies with low validation are clustered together. That is, companies with weak market valuations are closely clustered, with characteristics that are inherently flawed and unreliable. ESG indicators show significant interfirm variation, which suggests the use of fixed-effects estimators to investigate how ESG maturity impacts market valuations.

4.2. Baseline Fixed-Effects Results: ESG and Firm Value

Table 4. ESG Performance and Tobin’s Q (Fixed Effects).

Variables	(1) Tobin’s Q
ESG Total	0.264 (0.222)
In (Size)	−0.473 (0.439)
Leverage	−0.881 (2.137)
ROA	0.787 (1.509)
Constant	7.604 (6.200)
Firm FE	Yes
Year FE	Implicit
Clustered SE	Firm
Observations	78
Firms	13
Within R2	0.116

Note: Coefficient estimates are reported, with values in parentheses representing firm-level clustered robust standard errors. The covariance matrix estimation accounts for heteroskedasticity and within-firm serial correlation.

shows the results of a main fixed-effects regression that examines the relationship between ESG indicators and company value, as measured using Tobin’s Q. The model includes company-specific factors, such as size, leverage, and ROA.

The ESG baseline coefficient is positive but statistically insignificant. The reported coefficients represent point estimates, with robust standard errors clustered at the firm level shown in parentheses, accounting for potential within-firm serial correlation over time. No statistically significant association is observed between ESG maturity and firm market valuation in the baseline specification.

These results suggest that, while ESG indicators are a stable factor, their impact on market valuations is significantly dependent on characteristics such as a company’s industry, institutional context, and the stage of ESG implementation. Further research and analysis are needed to examine the impact of industry influences and institutional factors in shaping the relationship between ESG and valuation.

It is important to note that the relatively low within R² values reported in the fixed-effects specifications are consistent with standard findings in firm-level panel studies, particularly in emerging market contexts. Fixed-effects models rely exclusively on within-firm variation over time, while firm valuation indicators such as Tobin’s Q are largely driven by persistent cross-sectional differences and market-wide factors. As a result, within R² values are typically modest and should not be interpreted as indicating poor model fit. Instead, they reflect the conservative nature of within estimators in isolating incremental effects of time-varying governance characteristics.

4.3. ESG Sub-Dimensions and Tobin’s Q (Fixed Effects)

To further analyze the relationship between ESG and valuation,

Table 5. ESG Pillars and Tobin’s Q (Fixed Effects).

Variables	(2) Tobin’s Q
Environmental Score	0.735 (0.699)
Social Score	−0.544 (0.775)
Governance Score	−0.021 (0.497)
In (size)	−0.579 (0.499)
Leverage	−0.744 (1.807)
ROA	1.181 (1.430)
Constant	9.669 (7.546)
Firm FE	Yes
Observations	78
Firms	13
Within R2	0.153

Note: Coefficient estimates are reported, with values in parentheses representing firm-level clustered robust standard errors. The covariance matrix estimation accounts for heteroskedasticity and within-firm serial correlation.

breaks down the overall ESG metric into its environmental (E), social (S), and governance (G) components. This approach allows us to identify the different impacts of specific ESG aspects on company value.

None of the ESG indicators—environmental, social, or governance factors—showed a statistically significant impact on Tobin’s Q. This result suggests that market participants cannot assess individual aspects independently or that the impact of each component may vary depending on the industry structure and other characteristics of the company at different times. Additionally, this finding may reflect the early stages of the ESG integration process in Kazakhstan, where companies may not yet fully incorporate these practices into their operations and management.

This highlights the need for deeper research into how specific areas of the institutional environment influence the impact of individual ESG components on company valuation.

4.4. ESG and Accounting Performance: ROE

Table 6. ESG and ROE.

Variables	(5) ROE
ESG Total	0.603 (0.442)
In (Size)	−1.033 (0.839)
Leverage	19.153 (7.938)
Constant	3.139 (9.311)
Firm FE	Yes
Observations	78
Firms	13
Within R2	0.649

Note: Coefficient estimates are reported, with values in parentheses representing firm-level clustered robust standard errors. The covariance matrix estimation accounts for heteroskedasticity and within-firm serial correlation.

presents the results of the fixed-effects regression where return on equity (ROE) is the dependent variable. The model examines the association between ESG maturity and accounting profitability as measured using ROE.

The results indicate that financial leverage is positively and statistically significantly associated with ROE. In contrast, ESG maturity does not exhibit a statistically significant association with ROE in this specification. These findings suggest that, within this model, no statistical evidence supports a relationship between ESG maturity and accounting profitability as measured using ROE.

It also shows that companies with strong ESG practices are likely to be valued higher by investors considering their long-term growth opportunities, even if these practices do not immediately impact traditional profitability metrics.

4.5. Summary of Key Findings

Overall, the empirical analysis provides three main conclusions:

First, the results of the fixed-effects model (Table 4) show a positive relationship between the level of ESG maturity and the market valuation of a company, but this relationship is not statistically significant. Even when ESG indicators are broken down into components (Table 5), none of the environmental, social and governance dimensions show a significant effect individually. This means that the direct impact of ESG factors on market valuation is not clear in the period under review.

Second, ESG maturity did not have a significant impact on the accounting profitability indicator—ROE (Table 6). At the same time, the stability analysis using logarithmic Tobin’s Q (

Table 7. ESG and Ln (Tobin’s).

Variables	Ln (Tobin’s Q)
ESG total	0.095 (0.102)
Ln (Size)	−0.199 (0.163)
Leverage	0.397 (0.718)
ROA	1.893 * (0.657)
Constant	2.126 (2.216)
Firm FE	Yes
Observations	78
Firms FE	13
Within R2	0.101

Note: Coefficient estimates are reported, with values in parentheses representing firm-level clustered robust standard errors. The covariance matrix estimation accounts for heteroskedasticity and within-firm serial correlation. Statistical significance is indicated by * p < 0.10.

) showed that ROA remains an important factor in firm value. This suggests that the market valuation of firms during the period under study is largely dependent on traditional financial indicators.

Third, the analysis taking into account industry differences (

Table 8. ESG, financial sector, and Tobin’s Q.

Variables	Ln (Tobin’s Q)
ESG total	0.004 (0.130)
Financial × ESG	0.929 ** (0.371)
Ln (Size)	−0.802 * (0.408)
Leverage	−0.803 (1.449)
ROA	−0.101 (2.098)
Constant	12.078 * (5.741)
Firm FE	Yes
Observation	78
Firms	13
Within R2	0.371

Note: Coefficient estimates are reported, with values in parentheses representing firm-level clustered robust standard errors. The covariance matrix estimation accounts for heteroskedasticity and within-firm serial correlation. Statistical significance is indicated by * p < 0.10, ** p < 0.05.

) shows some heterogeneity. The interaction variable (Financial × ESG) characterizing ESG maturity and belonging to the financial sector turned out to be positive and statistically significant. Therefore, a higher level of ESG in the financial sector may be associated with a higher market valuation of a company. For non-financial companies, the ESG maturity indicator does not reach statistical significance.

In conclusion, the impact of ESG is not equally evident in all industries and its impact is currently most pronounced in the financial sector.

5. Discussion

5.1. Robustness Check

This study yielded a skewed distribution of Tobin’s Q, necessitating a robustness check. Logarithmic transformations were used to mitigate the influence of critical outliers and better stabilize the variance of residuals within the regression model. The results, presented in Table 7, indicate that while ESG remains statistically insignificant, ROA becomes statistically significant and positively correlates with Tobin’s Q. This suggests that profitability metrics are more indicative of company value when accounting for extreme market valuations. This result is consistent with the findings showing that financial performance metrics such as ROA tend to dominate when assessing company value in the context of ESG engagement [32]. It has also been noted that although ESG engagement does not always have an immediate impact, profitability remains a key determinant of market value [33]. The low relevance of ESG in the context of Kazakhstan may be due to the early stage of ESG integration in the country [34]. The results of the above study showed that in developing countries where ESG practices are still immature, financial indicators play a more important role in assessing firm value than sustainability factors. While we acknowledge the inferential limitations inherent in a small sample size (N = 13), the persistence of the ROA effect across both linear and log-linear specifications suggests that our findings are not driven by functional form. The results underscore the significant importance of considering financial indicators over sustainability factors in the reality of developing countries like Kazakhstan.

The presented data confirm the robustness of the constructed model and supports the idea that company profitability, rather than the sophistication and depth of ESG factors, is a more appropriate and relevant component of assessing a company’s sustainability, especially in markets such as Kazakhstan. Such markets are distinguished by the fact that ESG practices are still in their infancy and, therefore, require adapted assessment methodologies. This conclusion is consistent with numerous findings from similar studies and underscores the significant importance of considering financial indicators over sustainability factors in the reality of developing countries.

5.2. Industry Heterogeneity: Financial and Non-Financial Companies

In this study, it was important to understand how the relationship between ESG and company valuation may vary across sectors and types of companies. To this end, an interaction variable was introduced between ESG indicators and a dummy variable for the financial sector (banking and financial services). Table 8 below presents data demonstrating that the interaction variable is positive and statistically significant. This allows us to highlight that ESG indicators contribute to company valuation in the financial sector but are insignificant and much less influential for companies in the non-financial sector.

The obtained results show that ESG indicators are currently particularly important for financial sector companies in Kazakhstan. Theoretically, these indicators may serve as important trust signals, thereby potentially impacting risk mitigation in the face of strong market regulators. This is logical, as financial sector companies often face higher pressure regarding the implementation of ESG principles due to the considerable attention from both regulators and potential investors, who prefer to work with companies that share the principles of sustainability and business transparency. Meanwhile, non-financial sector companies are slower to implement ESG principles in their practices, not seeing any clear benefits or opportunities in doing so and are at an earlier stage.

This finding is consistent with evidence showing that ESG disclosures have a stronger impact on firms in the financial sector, especially compared to non-financial companies in Saudi Arabia [35]. Similarly, it has been shown that ESG engagement is driven by governance structures, making it particularly important in markets where governance quality affects firm performance [36].

It is worth noting that the interaction term remains statistically significant even after applying the bootstrap method to estimate standard deviations (1000 iterations), which reduces bias due to the small sample size and supports the robustness of the results. A general conclusion can be drawn that the relationship between ESG indicators and company values depends significantly on industry characteristics, with financial sector companies appearing more advanced in implementing sustainability practices than other industries. This observation is consistent with findings reporting a positive impact of ESG practices on financial performance in the Saudi Arabian context [37].

The applicability of these findings to other contexts depends on institutional and market characteristics. The findings may be relevant to emerging economies with similar characteristics, such as the development of ESG regulatory frameworks, relatively limited time horizons for ESG disclosure, concentrated ownership structures, and emerging capital markets. However, caution should be exercised in generalizing the findings due to country-specific institutional conditions and limited sample size.

6. Conclusions

In line with the stated research objective, this paper aims to empirically analyze the relationship between ESG governance maturity and market valuation of firms in Kazakhstan in an emerging economy.

The results obtained allow us to draw a number of important conclusions. First, the main fixed-effects model shows a positive, but statistically insignificant, relationship between the aggregate ESG maturity indicator and Tobin’s Q. Similarly, the separate analysis of ESG components shows that they do not have a statistically significant impact on the market valuation of a firm. These results indicate that no statistically significant relationship was observed in the baseline characteristics during the period under review.

Second, the results highlight industry heterogeneity. The interaction model shows that ESG maturity is positively and statistically significantly associated with market valuation in the financial sector, while no such relationship is observed in the non-financial sector. This suggests that the market relevance of ESG governance may be related to industry-specific and institutional characteristics.

Third, no statistically significant effect of ESG maturity on return on equity (ROE) was found. Furthermore, ROA appears as a statistically significant variable in the logarithmic Tobin’s Q model. This suggests that traditional financial indicators play an important role in explaining market valuations at this stage of ESG development in Kazakhstan.

Overall, the results suggest that ESG maturity is not uniformly reflected in market valuations across industries, but may be more important in certain cases, particularly in the financial sector.

From a policy perspective, these findings suggest that institutional development and the regulatory environment in emerging markets may influence investors’ perceptions of ESG governance. However, given the limited sample size and country-specific institutional characteristics, caution should be exercised in generalizing the results.

Despite these contributions, the study has certain limitations. The analysis included 13 firms from 2019 to 2024, which may limit statistical power and external validity. Future studies could broaden their geographical scope or extend their time horizon to further explore longer-term dynamics. In addition, re-examining ESG maturity indicators using alternative data sources could increase empirical reliability.

Furthermore, although firm fixed effects are used, potential identification issues, including a reverse causal relationship between firm valuation and ESG maturity, cannot be completely ruled out. Furthermore, the ESG maturity index is based on a manual content analysis of corporate disclosures, which may introduce measurement bias regardless of the coding procedures used. These methodological issues should be taken into account when interpreting the results.