Information Asymmetry, Return and Market Structure in Petrochemical Companies: A Dynamic Spatial Panel Method

Shamsoddini, Mostafa

doi:10.22050/pbr.2025.522080.1391

Information Asymmetry, Return and Market Structure in Petrochemical Companies: A Dynamic Spatial Panel Method

Document Type : Original Article

Author

Mostafa Shamsoddini

Department of Economics, Faculty of Management, Economics and Accounting, University of Hormozgan, Bandar Abbas, Iran

https://doi.org/10.22050/pbr.2025.522080.1391

Abstract

This study uses spatial econometric and dynamic analyses to examine the temporal and spatial effects on three performance indicators of petrochemical companies active in the Tehran Stock Exchange: price performance, retained earnings, and total performance. The target population comprises all petrochemical companies listed on the Tehran Stock Exchange that have been active since the beginning of 2013 to the end of 2024. The findings suggest that, while information asymmetry positively influences companies' retained earnings, it simultaneously has a negative impact on price and total performance. Additionally, an examination of the H-index revealed that the market structure of this industry is monopolistic. However, monopolistic behavior is observed in the distribution of retained earnings, which can be attributed to the centralized structure governing the management of the Iranian petrochemical industry. Findings concerning financial structure suggest that elevated financial leverage and financing costs negatively impact returns, while investment in physical assets has the most favorable impact. Furthermore, identifying significant spatial effects corroborates the idea that proximity and spillover effects between companies are substantial. This study provides substantial empirical evidence that enhancing information transparency, optimizing financial structures, and reforming corporate governance mechanisms could increase market returns and improve stock returns in the petrochemical industry.

Highlights

While information asymmetry in petrochemical companies has a positive but limited effect on observed retained earnings, it has a significant negative effect on price return and total stock return.
In terms of returns, the Iranian petrochemical industry follows a monopolistic competitive pattern; However, monopolistic behavior is observed in the area of dividend policy.
Under conditions of information asymmetry, investors are more cautious, especially in response to price returns, but companies can accumulate more profits to compensate for this uncertainty.
Financial decisions in the petrochemical industry are influenced by the past performance of companies as well as the behavior of nearby competitors.

Keywords

Information Asymmetry

Price Return

Dividend

Market Structure

Dynamic Spatial Panel

Subjects

Oil and Gas Economics and Management

Ahern, K. R. (2020). Do proxies for informed trading measure informed trading? Evidence from illegal insider trades. The Review of Asset Pricing Studies, 10(3), 397–440. https://doi.org/10.1093/ rapstu/raaa004

Ahmed, Y. (2023). Corporate Governance Disclosure Quality: Signaling Theory Insights and a Related UK-Egypt Empirical Analysis and Evaluation, Doctoral dissertation, London South Bank University. https://doi.org/10.18744/lsbu.951vx

Akerlof G. A. (1970). The market for lemons: quality uncertainty and the market mechanism. The Quarterly Journal of Economics, 84(3), 488–500. https://doi.org/10.2307/1879431

Akhtar, M. H., & Asif, M. (2017). Evaluating managerial efficiency of petrochemical firms in Saudi Arabia. Benchmarking: An International Journal, 24(1), 244–256. http://dx.doi.org/10.1108/BIJ-06-2014-0057

Al Janabi, M. A. (2024). Unlocking the microstructure of liquidity risk: understanding interactions with other financial risks and best practices in oversight and governance. In Liquidity Dynamics and Risk Modeling (pp. 79–167). Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-71503-7_2

Al Mestneer, R., & Bollino, C. A. (2024). Long-Term Forecasting Models of Oil Demand Emerging from the Global Petrochemical Sector. Energies, 17(20), 5046. https://doi.org/10.3390/ en17205046

Alimoradi, A., & Rajabdorry, N. (2018). The Effect of Petrochemical Industry on Relationship between Information Asymmetry about Investment Risk and Financing Choice. Petroleum Business Review, 2(2), 28–37. https://doi.org/10.22050/pbr.2018.91318

Alimoradi, A., Khademvatani, A., & Gholami, F. (2020). The Relationship between Stock Liquidity (from Corporate Governance and Informational Efficiency Points of View) and Default Risk in Iran's Petrochemical Industry and Oil Products Companies. Petroleum Business Review, 4(1), 13–34. https://doi.org/10.22050/pbr.2020.104108

Alrashidi, A. M. (2022). Market failures and costs of intermediation cause obstacles to the delivery of transactions: a critical discussion on the impact of information asymmetries and conflicts of interest on contractual relationships. International journal of health sciences, 6(S1), 9830–9837. https://doi.org/10.53730/ijhs.v6nS1.7294

Al-Samhan, M., Al-Fadhli, J., Al-Otaibi, A. M., Al-Attar, F., Bouresli, R., & Rana, M. S. (2022). Prospects of refinery switching from conventional to integrated: An opportunity for sustainable investment in the petrochemical industry. Fuel, 310, 122161. https://doi.org/10.1016/ j.fuel.2021.122161

Anselin, L. (1988). Spatial econometrics: methods and models (Vol. 4). Springer Science & Business Media. https://doi.org/10.1007/978-94-015-7799-1

Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies, 58(2), 277–297. https://doi.org/10.2307/2297968

Bercovici, G. (2015). Petrobrás: state monopoly and competition policy. In State-Initiated Restraints of Competition (pp. 40–54). Edward Elgar Publishing. https://doi.org/10.4337/9781784714987. 00011

Berk, I., & Çam, E. (2020). The shift in global crude oil market structure: A model-based analysis of the period 2013–2017. Energy Policy, 142, 111497. https://doi.org/10.1016/j.enpol.2020.111497

Bhatti, A. A., Patoli, A. Q., & Kumar, T. (2023). Dividend Policy and its Impact on Market Price: An Empirical Study of Chemical Sector. Journal of Development and Social Sciences, 4(2), 316–326. https://doi.org/10.47205/jdss.2023(4-II)28

Blondeel, M., & Bradshaw, M. (2022). Managing transition risk: Toward an interdisciplinary understanding of strategies in the oil industry. Energy Research & Social Science, 91, 102696. https://doi.org/10.1016/j.erss.2022.102696

Cai, C. W. (2023). Filling the gap and moving forward: a review of analytical and empirical studies of disclosure and cost of capital. Journal of Accounting Literature, 45(1), 130–153. https://doi.org/ 10.1108/JAL-08-2022-0083

Chen, X., Wang, H., Zhu, X., & Zhang, X. (2025). Spatial-temporal characteristics of agricultural economic resilience and spatial spillover effects of driving factors: evidence from provincial panel data in China. Frontiers in Environmental Science, 13, 1437018. https://doi.org/10.3389/ fenvs.2025.1437018

Chhajer, P., Mehta, V., & Gandhi, V. (2020). Factors influencing stock returns: Evidence from national stock exchange, India. International Journal of Management, 11(5), 631–643. https://ssrn.com/ abstract=3630891

Daadaa, W. (2021). Bid-ask spread, corporate board and stock liquidity in emergent markets. African Journal of Economic and Management Studies, 12(4), 531–542. https://doi.org/10.1108/AJEMS-04-2021-0175

David, P., Dharwadkar, R., & Duru, A. (2022). Financial reporting choices, governance structures, and strategic assets: a transaction cost perspective. Academy of Management Review, 47(4), 579–599. https://doi.org/10.5465/amr.2019.0105

Easley, D., & O'Hara, M. (2004). Information and the cost of capital. The journal of finance, 59(4), 1553–1583. https://doi.org/10.1111/j.1540-6261.2004.00672.x

Fama, E. F. (1970). Efficient capital markets. Journal of finance, 25(2), 383–417. https://doi.org/ 10.2307/2325486

Frésard, L., & Phillips, G. M. (2024). Product markets, competition and corporate finance: A review and directions for future research. Handbook of Corporate Finance, 591–646. https://doi.org/ 10.4337/9781800373891.00026

Gao, A., Sun, M., & Wen, W. (2024). Uncovering the spillover effects between the new energy industry and eleven economic sectors in China: Evidence based on stock data. Energy, 301, 131671. https://doi.org/10.1016/j.energy.2024.131671

Ghazanfari Shabankareh, M., Shesh Bulookii, A., & Kord, M. (2024). Examining the methods of converting the threats caused by sanctions on Iran’s petrochemical industry to economic opportunities and investigating the growth rate of Iran’s petrochemical industry during sanction. International Journal of Energy Sector Management, 18(6), 2357–2378. https://doi.org/10.1108/ IJESM-01-2024-0002

Goldstein, I. (2023). Information in financial markets and its real effects. Review of Finance, 27(1), 1–32. https://doi.org/10.1093/rof/rfac052

Gyapong, E., & Afrifa, G. A. (2019). The simultaneous disclosure of shareholder and stakeholder corporate governance practices and their antecedents. International Journal of Finance & Economics, 24(1), 260–287. https://doi.org/10.1002/ijfe.1661

Jansen, M. (2020). Resolving information asymmetry through contractual risk sharing: The case of private firm acquisitions. Journal of Accounting Research, 58(5), 1203–1248. https://doi.org/ 10.1111/1475-679X.12335

Jensen, M. C., & Meckling, W. H. (1976). Theory of the Firm. Journal of Financial Economics, 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X

Khodadad Kashi, F., Mosavi Jahromi, Y., Norani Azad, S., & Eshaghi Gorji, M. (2024). Evaluating the degree of Monopoly in Iran's Large-Scale Industries: Stochastic Frontier Function Approach. The Journal of Economic Policy, 16(31), 81–116. https://doi.org/10.22034/epj.2024.20630.2498

Kumar, N., & Choudhary, P. (2024). Structure conduct and performance in industrial organization: A contemporary examination of causal relationships. Empirical Economics Letters, 23(2), 33–52. https://doi.org/10.5281/zenodo.11040230

LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC. https://doi.org/10.1201/9781420064254

Liang, T. (2024). Innovating Regional Policy Frameworks in China: The Strategic Zone+ Type Zone Model for Sustainable Growth. Journal of the Knowledge Economy, 1–42. https://doi.org/10.1007/ s13132-024-02022-8

Mazaraki, N., Gerasymenko, A., & Kovtun, V. (2020). Information asymmetry as a determinant of competition. Natsional'nyi Hirnychyi Universytet. Naukovyi Visnyk, (2), 148–152. https://doi.org/ 10.33271/nvngu/2020-2/148

Mohanasundaram, T., Rizwana, M., Sathyanarayana, S., & Singh, P. (2024). Structural change, information asymmetry and volatility in Indian stock market: evidence from pre-and-post-COVID-19 outbreak. Afro-Asian Journal of Finance and Accounting, 14(3), 412–431. https://doi.org/10.1504/AAJFA.2024.138390

Otieno, B. A. (2024). Public debt, investment and economic growth dynamics: Do geographical proximity and spatial spillover effects matter? Regional Science Policy & Practice, 16(6), 100059. https://doi.org/10.1016/j.rspp.2024.100059

Otto, P., Doğan, O., & Taşpınar, S. (2024). Dynamic spatiotemporal ARCH models. Spatial economic analysis, 19(2), 250–271. https://doi.org/10.1080/17421772.2023.2254817

Panda, A. K., Nanda, S., & Ravi, R. (2016). A mathematical explanation of Panzar-Rosse model and its implication in Indian banking industry. Indian Journal of Economics & Business, 15(1), 75–98. https://www.researchgate.net/publication/305316221

Panzar, J. C., & Rosse, J. N. (1987). Testing for" monopoly" equilibrium. The journal of industrial economics, 443–456. https://doi.org/10.2307/2098582

Raei, R., Mohammadi, S., & Ajam, A. (2022). Development of the model of factors affecting stock returns. Journal of Asset Management and Financing, 10(3), 119–142. https://doi.org/10.22108/ amf.2023.136130.1774

Saci, F., Jasimuddin, S. M., & Hasan, M. (2022). Performance of socially responsible investment funds in China: a comparison with traditional funds. Sustainability, 14(3), 1476. https://doi.org/ 10.3390/su14031476

Salman, K. R. (2023). Exploring moral hazard and adverse selection in profit sharing contract. International Journal of Professional Business Review, 8(3), e0955. https://doi.org/10.26668/ business review/2023.v8i3.955

Sanchez-Cartas, J. M. (2020). The Panzar–Rosse H statistic and monopoly. Issues on its use as a market power measure. The BE Journal of Economic Analysis & Policy, 20(4), 20200193. https://doi.org/ 10.1515/bejeap-2020-0193

Shamsoddini, M. & Akhlaghi Yazdinejad, E. (2024). The effect of environmental and currency uncertainty on stock return volatility in the petrochemical and petroleum products supplier's companies. Petroleum Business Review, 8(1), 61–75. https://doi.org/10.22050/pbr.2023. 418353.1318

Shamsoddini, M., Shahiki Tash, M.N., & Khodadad Kashi, F. (2017). Measuring the probability of informed trading (pin) and its relationship with daily return variation in selected firms in the Tehran Stock Exchange. Journal of Economic Research and Policies, 25(83), 285–309. [In Persian] http://qjerp.ir/article-1-1476-en.html

Sohail, M., Idrees, M., & Majeed, M. T. (2024). Analysis of Industrial Sector Competitiveness of Pakistan: An Application of Panzar-Rosse (PR-H) Statistic. Journal of Asian Development Studies, 13(1), 383–401. http://dx.doi.org/10.62345/jads.2024.13.1.33

Spence, M. (1973). Job market signaling. Quarterly Journal of Economics, 87, 354–374. https://doi.org/ 10.2307/1882010

Tekin, H., & Polat, A. Y. (2020). Agency theory: A review in finance. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(4), 1323–1329. https://doi.org/10.18506/anemon.712351

Tilsted, J. P., & Bauer, F. (2024). Connected we stand: Lead firm ownership ties in the global petrochemical industry. Ecological Economics, 224, 108261. https://doi.org/10.1016/j.ecolecon. 2024.108261

Ullah, M., Lakhan, G. R., Channa, A., & Gul, S. (2021). Game Theory and Stock Investment. Multicultural Education, 7(6), 40–44. https://doi.org/10.5281/zenodo.4900016

Üslü, S. (2019). Pricing and liquidity in decentralized asset markets. Econometrica, 87(6), 2079–2140. https://doi.org/10.3982/ECTA14713

Wang, S., Wang, H., Wang, J., & Yang, F. (2020). Does environmental information disclosure contribute to improve firm financial performance? An examination of the underlying mechanism. Science of the Total Environment, 714, 136855. https://doi.org/10.1016/j.scitotenv.2020.136855

Xia, Y., & Liu, P. (2021). The effects of bank competition on firm R&D investment: an inverted-U relationship. Chinese Management Studies, 15(3), 641–666. https://doi.org/10.1108/CMS-04-2020-0126

Yu, J., & Lee, L. F. (2012). Convergence: A spatial dynamic panel data approach. Global Journal of Economics, 1(01), 1250006. https://doi.org/10.1142/S2251361212500061

Zarei, S. (2020). Analyzing the Asymmetric Effects of Inflation and Exchange Rate Misalignments on Petrochemical Stock Index: The Case of Iran. International Journal of Economics, Management and Accounting, 28(2), 457–482. https://doi.org/10.31436/ijema.v28i2.788

Zhang, L., & Sok, S. (2025). The impact of government open data platform construction on corporate capital market performance: Evidence from stock liquidity. Pacific-Basin Finance Journal, 90, 102667. https://doi.org/10.1016/j.pacfin.2025.102667