Volume 21, Issue 1 (3-2026)
J. Mon. Ec. 2026, 21(1): 50-60 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Sarhadi P, Abdoli G, Barkhordari dorbash S. Investigating the Impact of Non-Fungible Tokens (NFTs) on the Economy of Art Using a Mixed Quantitative and Qualitative Approach. J. Mon. Ec. 2026; 21 (1) :50-60
URL: http://jme.mbri.ac.ir/article-1-732-en.html
URL: http://jme.mbri.ac.ir/article-1-732-en.html
1- Ph.D. Candidate in Economics, University of Tehran
2- Professor of Economics, University of Tehran,
3- Associate Professor of Economics, University of Tehran
2- Professor of Economics, University of Tehran,
3- Associate Professor of Economics, University of Tehran
Abstract: (539 Views)
This study investigates the effect of Non‑Fungible Tokens (NFTs) on the structure and dynamics of the digital art economy using a mixed quantitative–qualitative approach. Using market data from 2020 to 2024, Ordinary Least Squares (OLS), Autoregressive Distributed Lag (ARDL), Vector Autoregression (VAR), Granger causality, and Capital Asset Pricing Model (CAPM) analyses were utilized to assess relationships between NFT artwork prices, Ether (ETH) prices, trading volume, and sales counts. Results show that ETH price has a strong and statistically significant positive effect on NFT valuations in both the short and long term, while trading volume has a weaker but significant causal role and sales counts have no meaningful influence. CAPM findings indicate NFTs behave as crypto‑linked assets, bearing systematic risk without creating excess returns. Complementary thematic analysis of interviews with 52 industry experts reveals that NFTs enable decentralization, disintermediation, and greater market access for artists, while raising concerns over legal frameworks, price volatility, and market sustainability. The study concludes that NFTs play a dual role in empowering creators and reshaping market structures, yet remain vulnerable to speculative dynamics and regulatory uncertainty, offering implications for policymakers, artists, and investors navigating the evolving digital art ecosystem.
Keywords: Non-Fungible Token (NFT), digital art economy, mixed-methods analysis, Blockchain, ARDL model, Delphi method, artwork valuation.
Type of Study: Original Research - Empirical |
Subject:
Microeconomics
Received: 21 Aug 2025 | Accepted: 1 Feb 2026 | Published: 29 Mar 2026
Received: 21 Aug 2025 | Accepted: 1 Feb 2026 | Published: 29 Mar 2026
References
1. Ante, L. (2021). Non-fungible token (NFT) markets on the Ethereum blockchain: Temporal development, cointegration and interrelations. SSRN Electronic Journal. [DOI:10.2139/ssrn.3904683]
2. Anderson, J., & Rainie, L. (2022). The metaverse in 2040. Pew Research Center, 30(4), 1-203.
3. Christidis, K., & Devetsikiotis, M. (2016). Blockchains and smart contracts for the Internet of Things. IEEE Access, 4, 2292-2303. [DOI:10.1109/ACCESS.2016.2566339]
4. Cong, L. W., He, Z., & Li, J. (2021). Decentralized mining in centralized pools. The Review of Financial Studies, 34(3), 1191-1235. [DOI:10.1093/rfs/hhaa040]
5. Domínguez, M. A., & Lobato, I. N. (2004). Consistent estimation of models defined by conditional moment restrictions. Econometrica, 72(5), 1601-1615. [DOI:10.1111/j.1468-0262.2004.00545.x]
6. Dowling, M. (2022). Is non-fungible token pricing driven by cryptocurrencies? Finance Research Letters, 44, 102097. [DOI:10.1016/j.frl.2021.102097]
7. Entriken, W., Shirley, D., Evans, J., & Sachs, N. (2018). ERC-721 non-fungible token standard. Ethereum Improvement Proposal 721. https://eips.ethereum.org/EIPS/eip-721
8. Escanciano, J. C., & Lobato, I. N. (2009). An automatic portmanteau test for serial correlation. Journal of Econometrics, 151(2), 140-149. [DOI:10.1016/j.jeconom.2009.03.001]
9. Evans, T. M. (2019). Cryptokitties, cryptography, and copyright. AIPLA Quarterly Journal, 47, 219.
10. Hammi, B., Zeadally, S., & Perez, A. J. (2023). Non-fungible tokens: A review. IEEE Internet of Things Magazine, 6(1), 46-50. [DOI:10.1109/IOTM.001.2200244]
11. Kim, J. H. (2009). Automatic variance ratio test under conditional heteroskedasticity. Finance Research Letters, 6(3), 179-185. [DOI:10.1016/j.frl.2009.04.003]
12. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
13. Regner, F., Urbach, N., & Schweizer, A. (2019). NFTs in practice: Non-fungible tokens as core component of a blockchain-based event ticketing application. In Proceedings of the 40th International Conference on Information Systems (ICIS 2019), Munich, Germany.
14. Rosenfeld, M. (2012). Overview of colored coins. https://bitcoil.co.il/BitcoinX.pdf
15. Schaar, L., & Kampakis, S. (2022). Non-fungible tokens as an alternative investment: Evidence from Cryptopunks. The Journal of The British Blockchain Association, 5(1). [DOI:10.31585/jbba-5-1-(2)2022]
16. Tapscott, A. (2023). Web3: Charting the Internet's next economic and cultural frontier. Harper Business.
17. Wang, Q., Li, R., Wang, Q., & Chen, S. (2021). Non-fungible token (NFT): Overview, evaluation, opportunities and challenges. arXiv. https://arxiv.org/abs/2105.07447
18. Weron, R. (2002). Estimating long-range dependence: Finite sample properties and confidence intervals. Physica A: Statistical Mechanics and Its Applications, 312(1-2), 285-299. [DOI:10.1016/S0378-4371(02)00961-5]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
