Original Research | NSRI-J-2026-0054

Carbon Risk and Firm Valuation in an Emerging Market Emissions Trading System: Evidence from Kazakhstan

Authors: Kenges Yerdaulet

Affiliation: National school of Physics and Mathematics

Publication date: 2026-06-03

Publication pathway: Journal Publication

Collection: NSRI Student Research Journal

NSRI Student Research Journal
Online ISSN: 3143-5653

Volume: 1 Issue: 1 Pages/article: Article 0054

PDF: Open PDF/manuscript

Abstract

This paper examines whether Kazakhstan's Emissions Trading System (KazETS), introduced in 2013, generated a measurable causal reduction in the market valuation of high-emission industrial firms. Using an unbalanced panel of 52 publicly listed firms observed over 2008 to 2022, a difference-in-differences framework exploits cross-sectional variation in pre-policy carbon intensity to identify the effect on Tobin's Q. High-emission firms experienced a statistically significant decline of approximately 0.39 points in Tobin's Q relative to low-emission peers following policy implementation, a finding robust to firm and year fixed effects, industry-by-year interactions, staggered DiD estimators, propensity score matching, and placebo tests. The valuation discount is largest in mining and energy and is amplified for firms with higher institutional ownership. The results provide the first rigorous evidence that financial markets price regulatory climate risk in an emerging Central Asian economy, with direct implications for investors, corporate managers, and policymakers. Keywords: carbon risk, emissions trading system, firm valuation, Tobin's Q, difference-in-differences, Kazakhstan, emerging market

Keywords

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Citation

Kenges Yerdaulet (2026). Carbon Risk and Firm Valuation in an Emerging Market Emissions Trading System: Evidence from Kazakhstan. NSRI Student Research Journal. 1(1). Article 0054. NSRI-J-2026-0054.

Publication Details

ISSN: Online ISSN: 3143-5653

License: Author-retained; open access display by NSRI unless a separate article license states otherwise.

Peer review status: NSRI uses editorial and scholarly review. When appropriate, manuscripts may undergo blinded review by reviewers with relevant subject knowledge.

AI disclosure: No AI disclosure is attached to this public record unless stated in the manuscript.

Conflict of interest statement: No conflict of interest statement is attached to this public record unless stated in the manuscript.

References

References are available in the manuscript PDF when provided.