The model for measurment of the impact concerning the economic policy uncertainty on the tax capacity of e-commerce

Document Type : Research Paper


1 Department of Accounting, Faculty of Economics and Accounting. South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Accounting, Faculty of Management and Accounting, Imam Khomeini Memorial Unit, Islamic Azad University, Tehran, Iran


The role of the capital market in the economy of all countries is fundamental and decisive. It has a significant effect in aggregating and moving resources towards production and economic activities. According to the existence of such markets, the collection of small and large financial resources from the members of the society is facilitated. Therefore, this research is aimed at providing a model for measuring the impact of economic policy uncertainty on the tax capacity of e-commerce. In this research, 40 variables affecting economic policy uncertainty were included in the model. Finally, using the Bayesian averaging model approach, the most important variables affecting this index were determined. According to the results of the BMA model, the most important variables affecting the economic policy uncertainty index are the real interest rate, government debt to the central bank, liquidity (M2), inflation, current expenditures, land price index in urban areas, unofficial exchange rate, real exchange rate, Economic growth and oil revenues were determined. Based on the principal components approach, we calculated the economic policy uncertainty index using the most important variables affecting this variable. Then, by using the GARCH model, we extracted the uncertain part of the economic policy uncertainty index, and finally, by using the powerful non-linear TVPFAVAR model, we analyzed the shock caused by the economic policy uncertainty variable on the tax capacity in the field of e-commerce in the research period. We analyzed. The results indicated the fact that the shock caused by the variable fluctuation of economic policy uncertainty has increased the tax capacity in the field of e-commerce in recent years.


[1] Z. Abdali, M. Monahan, S. Jowett, Th. Pinkney, P. Brocklehurst, D.G. Morton, and T.E. Roberts, Surgical site infection and costs in low-and middle-income countries: A systematic review of the economic burden, PloS one 15 (2020), no. 6, e0232960.
[2] I. Abu-Nouri and A.H. Nikpour, The effect of tax burden indicators on the size of the hidden economy in Iran, Economic Growth and Development Res. 5 (2013), no. 17, 75–90.
[3] Sh. Arbabian and S.K. Tayyebi, Informal employment and competitiveness of low-technology industries, Monetary Financ. Econ.17 (2011), no. 34.
[4] J.M. Argil-Bosch, A. Somoza, D. Ravenda, and J. Garcja-Blandon, An empirical examination of the influence of e-commerce on tax avoidance in Europe, J. Int. Account. Audit. Tax. 41 (2020), 100339.
[5] A. F. Burns and W. C. Mitchell, The basic measures of cyclical behavior, Measuring Business Cycles, NBER, 1946, pp. 115–202.
[6] E-commerce Development Center of the Ministry of Security, Tropics and economic development: an empirical investigation, World Dev. 25 (1997), no. 9, 1443–1452.
[7] L. Dai and Ph. Ngo, Political uncertainty and accounting conservatism, Eur. Account. Rev. 30 (2021), no. 2, 277–307.
[8] D.N. Damanik, Taxation policy on e-commerce transactions, Proc. Int. Seminar, vol. 1, 2020, pp. 20–24.
[9] Ch. Dang, F. Wang, Z. Yang, H. Zhang, and Y. Qian, Evaluating and forecasting the risks of small to medium-sized enterprises in the supply chain finance market using blockchain technology and deep learning model, Oper. Manag. Res. 15 (2022), no. 3-4, 662–675.
[10] D. Dang, H. Fang, and M. He, Economic policy uncertainty, tax quotas and corporate tax burden: Evidence from China, China Econ. Rev.56 (2019), 101303.
[11] M. Del-Negro and Ch. Otrok, Dynamic factor models with time-varying parameters: measuring changes in international business cycles, FRB New York Staff Rep. (2008), no. 326.
[12] R. Dell’Anno and A.A. Davidescu, Estimating shadow economy and tax evasion in Romania: A comparison by different estimation approaches, Econ. Anal. Policy 63 (2019), 130–149.
[13] A. Divandarri, Monetary and Banking Research Institute (MBRI), Macroecon. Financ. Econ. 33 (1990), no. 12, 1443–1452.
[14] C. Doz, D. Giannone, and L. Reichlin, A quasi–maximum likelihood approach for large, approximate dynamic factor models, Rev. Econ. Statist. 94 (2012), no. 4, 1014–1024.
[15] M. Faezi and H. Nowrozi, Investigating factors influencing customers’ willingness to buy from virtual stores (case study: Al digital virtual store), Bus. Strategy. 22 (2014), no. 5, 85–102.
[16] A. Fallahati, Sh. Fatahi, S. Abbaspour, and M. Nazifi-Nayini, Estimating the country’s tax capacity using neural networks, Tax Res. J. 28 (2009), no. 8, 25–53.
[17] Z. Ftiti and S. Hadhri, Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? a multi-scale perspective, Pacific-Basin Finance J. 53 (2019), 40–55.
[18] J. Giles, D. Benjamin, and L. Brandt, The evolution of income inequality in rural China, Econ. Dev. Cultur. Change 53 (2005), no. 4, 769–824.
[19] A.S Goldberger, Heritability, Economica 46 (1979), no. 184, 327–347.
[20] Y. Guan, G.J. Lobo, A. Tsang, and X. Xin, Societal trust and management earnings forecast, Account. Rev. 95 (2020), no. 5, 149–184.
[21] E. Hadian and A. Tadari, Identifying factors affecting tax evasion in Iran’s economy, Program Budget Quart. 2 (2012), 39–58.
[22] O. Hajati, H. Farazman, S.M. Afagheh, and S.A. Armen, Estimation of income elasticity and tax capacity with concentration on the components of tax revenues in Khuzestan Province, Plann. Budget. 24 (2020), no. 4, 97–124.
[23] E. Hajibabaei and A. Ghasemi, Flood management, flood forecasting and warning system, Int. J. Sci. Engin. Appl. 6 (2017), no. 2, 33–38.
[24] M. Kabiri, M. Zolfaghari, and H. Saadatmanesh, Impact of socio-economic infrastructure investments on income inequality in Iran, J. Policy Model. 42 (2020), no. 5, 1146–1168.
[25] S. Karimi, M.M. Khan-Mohammadi, and M. Jafari, Presenting and evaluating the tax compliance model of legal entities based on the views of tax experts using the underlying theory in the Iranian tax system, J. Manag. Account. Audit. Knowledge 10 (2021), no. 38, 345–360.
[26] S.M. Khamsi, Investigating the effect of political uncertainty on the total index of the Tehran Stock Exchange and the dollar rate in Iran, Int. J. Bus. Econ. Manag. 6 (2017), no. 21, 46–67.
[27] T. Khosravi and J. Pezhoyan, The impact of corporate tax on private sector investment using the banks approach, Financ. Econ. Quart. 7 (2012), no. 25, 121–195.
[28] V. Klaric, Estimating the size of non-observed economy in Croatia using the mimic approach, Financ. Theory Practice 35 (2011), no. 1, 59–90.
[29] G. Koop and S. Potter, Forecasting in large macroeconomic panels using Bayesian model averaging, FRB NY Staff Report No. 163, Available at SSRN: or
[30] D. Korobilis, Var forecasting using Bayesian variable selection, J. Appl. Economet. 28 (2013), no. 2, 204–230.
[31] M. Mahmoudzadeh and M. Hasanzadeh, E-commerce tax: An introduction to the drafting of the e-commerce tax law in Iran, Econ. Policy Res. Quart. 14 (2006), no. 37, 85–117.
[32] G.S. Majoral, F. Gasparin, and S. Sauri, Application of a tax to e-commerce deliveries in Barcelona, Transport. Res. Record 2675 (2021), no. 10, 642–655.
[33] S. Marcelino-Sadaba, A. Perez-Ezcurdia, A.E.E. Lazcano, and P. Villanueva, Project risk management methodology for small firms, Int. J. Project Manag. 32 (2014), no. 2, 327–340.
[34] M. Mateen-Fard and A.A. Chahar-Mahali, Investigating the effect of economic uncertainty on cash non-deposit, Sci. Res. Quart. J. Invest. Knowledge 11 (2022), no. 41, 42–62.
[35] M. Mehrara, A. Haghnejad, J. Dehnavi, and F. J. Meybodi, Dynamic causal relationships among GDP, exports, and foreign direct investment (FDI) in the developing countries, Int. Lett. Soc. Human. Sci. 14 (2014), no. 3, 1–19.
[36] B. Misri, I. Dev, and V. Singh, Socio-economic profile of migratory graziers and participatory appraisal of forage production and utilization of an alpine pasture in north-west Himalaya, ENVIS Bull. 11 (2005), no. 2.
[37] M. Motallebi, M. Alizadeh, and S. Faraji-Dizaji, Estimating shadow economy and tax evasion by considering the variables of government financial discipline and behavioral factors in Iran’s economy, Iran. Econ. Rev.24 (2020), no. 2, 515–544.
[38] R.A. Musgrave, Cost-benefit analysis and the theory of public finance, J. Econ. Liter. 7 (1969), no. 3, 797–806.
[39] V. Nagar, J. Schoenfeld, and L. Wellman, The effect of economic policy uncertainty on investor information asymmetry and management disclosures, J. Account. Econ. 67 (2019), no. 1, 36–57.
[40] M. Rabiei and F. Esmail-Nia-Kitabi, Estimating tax capacity and effort and its relationship with oil income in the economy of Iran and some selected Opec member countries, Financ. Econ. 7 (2012), no. 22, 49–69.
[41] S. Ranjbar and G. Amanollahi, The effect of financial distress on earnings management and unpredicted net earnings in companies listed on Tehran Stock Exchange, Manag. Sci. Lett. 8 (2018), no. 9, 933–938.
[42] X. Salai-Martin, J. Blanke, M.D. Hanouz, Th. Geiger, I. Mia, and F. Paua, The global competitiveness index: Prioritizing the economic policy agenda, Glob. Compet. Rep. 2009 (2008), 3–41.
[43] A.H. Samadi and N. Sajedianfard, Tax evasion in oil-exporting countries: The case of Iran, Iran. Econ. Rev. 21 (2017), no. 2, 241–267.
[44] A.J. Samimi, S. Sadeghi, and S. Sadeghi, Tourism and economic growth in developing countries: P-var approach, Middle-East J. Sci. Res. 10 (2011), no. 1, 28–32.
[45] M.R. Schneider, C. Schulze-Bentrop, and M. Paunescu, Mapping the institutional capital of high-tech firms: A fuzzy-set analysis of capitalist variety and export performance, J. Int. Bus. Stud. 41 (2010), 246–266.
[46] H. Shamsuddini and S.M.Gh. Nejad, The effect of firm size and inflation rate on capital cost and financial health of companies accepted in Tehran Stock Exchange and Bombay Stock Exchange, QUID: Invest. Cien. Tecnol. (2017), no. 1, 221–234.
[47] M.S. Sheikh and H. Mirzaei, investigate the effect of economic policy uncertainty on the tax burden of companies listed on the Tehran Stock Exchange, Econ. Strategy 7 (2018), no. 24, 95–119.
[48] J. Slocum, H.K. Downey, and D. Hellriegel, Environmental uncertainty: The construct and its application, Admin. Sci. Quart. 20 (1975), no. 4, 613–629.
[49] J.H. Stock and M.W. Watson, Heteroskedasticity-robust standard errors for fixed effects panel data regression, Econometrica 76 (2008), no. 1, 155–174.
[50] K. Udomvitid, The E-Commerce Sales Tax: A Case Study of Thailand, Colorado State University, 2003.
[51] L. Wasserman, Bayesian model selection and model averaging, J. Math. Psycho. 44 (2000), no. 1, 92–107.
[52] W. Wu, Ch. Wu, Ch. Zhou, and J. Wu, Political connections, tax benefits and firm performance: Evidence from China, J. Account. Public Policy 31 (2012), no. 3, 277–300.
[53] M. Zahed-Gharavi, A. Falahi, M. Toghyani, and H. Asaiesh, Testing the effects of exchange rate jumps and global financial crisis using the overshooting dornbusch model for the financial stability of the state banking system of Iran’s economy, J. Asset Manag. Financ. 10 (2022), no. 1, 117–140.
[54] A. Zellner, Bayesian and non-bayesian analysis of the log-normal distribution and log-normal regression, J. Amer. Statist. Assoc.66 (1971), no. 334, 327–330.
[55] L. Zhang and R.H. Xang, Analysis model design on the impact of foreign investment on China’s economic growth, Sci. Programm. 2022 (2022).
[56] J. Ziegler, J. Ware, J. Dethmer, and F. Skinner, High Performing Investment Teams: How to Achieve Best Practices of Top Firms, Wiley Online Library, 2006.
Volume 15, Issue 3
March 2024
Pages 275-297
  • Receive Date: 10 December 2022
  • Revise Date: 27 December 2022
  • Accept Date: 15 February 2023