Journal Press India^®

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This bibliometric assessment investigates the influence and scholarly discourse surrounding tax amnesty programs and their relationship to tax revenue. By examining an extensive dataset of publications, this study establishes trends in research themes, identifies key contributors to research output related to tax amnesty as well as the effects of tax amnesty on income tax and generates worldwide academic output on tax amnesty through 467 papers published from 1986 until 2024 using the Scopus database. This study used a range of bibliometric tools to analyse data on the most highly cited papers, the most frequently cited authors, the most frequently cited sources of tax amnesty information to identify thematic analysis, develop thematic maps, produce financial analyses of the aggregate scientific production of countries, develop graphs to depict year-to-date and aggregate annual scientific production, and create a word cloud, etc. Overall, it appears that the influence of tax amnesty on improving tax compliance and revenue collection has been a growing area of research interest, and there have been some notable fluctuations in research focus throughout the timeline analysed and the presence of large spatial clusters of scholarship.

Keywords

Tax amnesty scheme; Tax revenue; Bibliometric analysis; Tax compliance; Research trends; Tax administration

1. Adams, J. (2013). The fourth age of research. Nature, 497, 557–560. Retrieved from https://doi.org/10.1038/497557a
2. Aidonojie, P. A. (2023). Voluntary assets and income declaration scheme a panacea to tax evasion in Edo State, Nigeria. Administrative and Environmental Law Review, 4(1), 1–20. Retrieved from https://doi.org/10.25041/aelr.v4i1.2822
3. Alm, J. R. (2005). Tax policy analysis: The introduction of a Russian tax amnesty. Retrieved from https://doi.org/10.2139/ssrn.471321
4. Alm, J., & Beck, W. (1990). Tax amnesties and tax revenues. Public Finance Quarterly, 18(4), 433-453. Retrieved from https://doi.org/10.1177/109114219001800404
5. Alm, J., Martinez-Vazquez, J., & Wallace, S. (2009). Do tax amnesties work? The revenue effects of tax amnesties during the transition in the Russian federation. Economic Analysis and Policy, 39(2), 235–253. Retrieved from https://doi.org/10.1016/S0313-5926(09)50019-7
6. Alstadsaeter, A., Johannesen, N. & Zucman, G. (2017). Tax evasion and inequality. The National Bureau of Economic Research working Paper No. 23772, E21, H26, 1-59.
7. Andreoni, J., Erard, B. & Feinstein, J. (1998). Tax compliance. Journal of Economic Literature , 36 (2), 818-860.
8. Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. Retrieved from https://doi.org/10.1016/j.joi.2017.08.007
9. Bernardi, L., & Fraschini, A. (2005). Tax system and tax reforms in India. Department of Public Policy Choice, 1–35.
10. Bird, R. M., & Zolt, E. M. (2008). Technology and taxation in developing countries: From hand to mouse. National Tax Journal , 61(4), 791-821.
11. Bornmann, L., & Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, 66(11), 2215–2222. Retrieved from https://doi.org/10.1002/asi.23329
12. Bradford, S. C. (1934). Sources of information on specific subjects. Engineering, 137, 85–86. Retrieved from https://doi.org/10.1002/bul.1934.017
13. Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research. Scientometrics, 22(1), 155–205. Retrieved from https://doi.org/10.1007/BF02019280
14. Canavire-Bacarreza, G., Eguino, H., Heller, L., & Roman, S. (2023). When do tax amnesties work? Journal of Economic Behavior and Organization, 207, 350–375. Retrieved from https://doi.org/10.1016/j.jebo.2022.12.018
15. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. Retrieved from https://doi.org/10.1002/asi.21525
16. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146–166. Retrieved from https://doi.org/10.1016/j.joi.2010.10.002
17. Daoud, I. B. (2024). Integrating tax amnesty, CSR, and emerging technologies: Exploring ethical challenges and strategic choices. Journal of Economic Criminology, 6(June), 1–8. Retrieved from https://doi.org/10.1016/j.jeconc.2024.100107
18. Dey, S. K., & Varma, K. K. (2016). Awareness of tax saving schemes among individual assessees: Empirical evidence from the twin city of Odisha. Journal of Commerce and Management Thought, 7(4), 668-692.
19. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. Retrieved from https://doi.org/10.1016/j.jbusres.2021.04.070
20. Garfield, E. (1972). Citation analysis as a tool in journal evaluation. Science, 178(4060), 471–479. Retrieved from https://doi.org/10.1126/science.178.4060.471
21. Hajawiyah, A., Suryarini, T., Kiswanto, & Tarmudji, T. (2021). Analysis of a tax amnesty’s effectiveness in Indonesia. Journal of International Accounting, Auditing and Taxation, 44. Retrieved from https://doi.org/10.1016/j.intaccaudtax.2021.100415
22. Hallsworth, M., List, J. A., Metcalfe, R. D., & Vlaev, I. (2017). The behavioralist as tax collector: Using natural field experiments to enhance tax compliance. Journal of Public Economics , 148, 14-31.
23. Hana, P., & Vitezić, V. (2022). Tax compliance challenge through taxpayers’ typology. SSRN Electronic Journal. Retrieved from https://doi.org/10.2139/ssrn.4060768
24. Heimerl, F., Lohmann, S., Lange, S., & Ertl, T. (2014). Word cloud explorer: Text analytics based on word clouds. 2014 47th Hawaii International Conference on System Sciences, 1833–1842. Retrieved from https://doi.org/10.1109/HICSS.2014.231
25. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. Retrieved from https://doi.org/10.1073/pnas.0507655102
26. Huda, M. K., & Hernoko, A. Y. (2017). Tax amnesties in Indonesia and other countries: Opportunities and challenges. Asian Social Science, 13(7), 52. Retrieved from https://doi.org/10.5539/ass.v13n7p52
27. Ibrahim, M. A., Myrna, R., Irawati, İ. & Kristiadi, J. B. (2017). A systematic literature review on tax amnesty in 9 Asian countries. International Journal of Economics and Financial Issues, 7(3), 220-225.
28. Ipek, S., Oksuz, M., & Ozkaya, S. (2012). Considerations of taxpayers according to the situation of benefiting from tax amnesty: An empirical research department of public finance. International Journal of Business and Social Science, 3(13), 95–101.
29. Jamali, S. M., Zain, A. N. M., Samsudin, M. A., & Ebrahim, N. A. (2017). Publication trends in physics education: A bibliometric study. Retrieved from https://doi.org/10.5281/zenodo.801889
30. James, S. (2015). The ancient origins of tax amnesties and fiscal forgiveness. Journal of Economic History, 75(2), 489–512.
31. Keen, M., & Slemrod, J. (2021). Rebellion, rascals, and revenue: Taxation in the ancient world. Journal of Economic Perspectives, 35(1), 203–226. Retrieved from https://doi.org/10.1257/jep.35.1.203
32. Kleven, H. J., Knudsen, M. B., Kreiner, C. T., Pedersen, S., & Saez, E. (2011). Unwilling or unable to cheat? Evidence from a tax audit experiment in Denmark. Econometrica , 79 (3), 651-692.
33. Knaflic, S. N. (2020). Storytelling with data: Let’s practice! Wiley. Retrieved from https://doi.org/10.1002/9781119621492
34. Koch, C., & Müller, C. (2024). Tax amnesties and the insurance effect: An experimental study. Journal of Behavioral and Experimental Economics, 108(October 2023), 1–12. Retrieved from https://doi.org/10.1016/j.socec.2023.102130
35. Kumar, R., & Soumya, A. (2011). Assessment of the impact of stimulus, fiscal transparency and fiscal risk: Evidences from India. Stimulus, Fiscal Transparency and Fiscal Risk, 335. Retrieved from https://www.eria.org/uploads/media/Research-Project-Report/RPR_FY2010_1_Chapter_9.pdf
36. Langenmayr, D. (2017). Voluntary disclosure of evaded taxes — Increasing revenue, or increasing incentives to evade? Journal of Public Economics, 151, 110–125. Retrieved from https://doi.org/10.1016/j.jpubeco.2015.08.007
37. Le Borgne, M. E., & Baer, M. K. (2008). Tax amnesties: Theory, trends, and some alternatives . International Monetary Fund.
38. Leonard, H. B., & Zeckhauser, R. J. (1987). Amnesty, enforcement, and tax policy. Tax Policy and the Economy, 1(1), 55-85.
39. Leydesdorff, L., Wagner, C. S., & Bornmann, L. (2019). Betweenness and diversity in collaborative expansion of worldwide research software. Journal of Informetrics, 13(2), 670–689. Retrieved from https://doi.org/10.1016/j.joi.2019.03.006
40. Luitel, H. S., & Sobel, R. S. (2007). The revenue impact of repeated tax amnesties. Public Budgeting & Finance , 27 (3), 19-38.
41. Malik, A. S., & Schwab, R. M. (1991). The economics of tax amnesties. Journal of Public Economics, 46(1), 29–49. Retrieved from https://doi.org/10.1016/0047-2727(91)90063-8
42. Mikesell, J. L., & Ross, J. M. (2012). Fast money? The contribution of state tax amnesties to public revenue. National Tax Journal, 65(3), 529–562. Retrieved from https://doi.org/10.17310/ntj.2012.3.03
43. Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus. Scientometrics, 106(1), 213–228. Retrieved from https://doi.org/10.1007/s11192-015-1765-5
44. Mujahid, A., & Siddiqui, D. A. (2019). The effect of tax amnesties programs on tax collection and economic performance: A global macro-economic analysis. International Journal of Social and Administrative Sciences, 4(2), 108–128. Retrieved from https://doi.org/10.18488 /journal.136.2019.42.108.128
45. Musimenta, D. (2020). Knowledge requirements, tax complexity, compliance costs and tax compliance in Uganda. Cogent Business and Management, 7(1), 1–19. Retrieved from https://doi.org/10.1080/23311975.2020.1812220
46. Nurkhin, A., Novanty, I., Muhsin, M., & Sumiadji, S. (2018). The influence of tax understanding, tax awareness and tax amnesty toward taxpayer compliance. Jurnal Keuangan Dan Perbankan, 22(2), 240–255. Retrieved from https://doi.org/10.26905/jkdp.v22i2.1678
47. OECD. (2010). Understanding and influencing taxpayers’ compliance behaviour. OECD Publishing. Retrieved from https://doi.org/10.1787/9789264099044-en
48. Organisation for Economic Co-operation and Development. (2019). Tax morale: What drives people and businesses to pay tax? OECD Publishing. OECD Tax Morale Report
49. Organisation for Economic Co-operation and Development. (2019). Tax administration 2019: Comparative information on OECD and other advanced and emerging economies . OECD Publishing. OECD Tax Administration 2019
50. Panda, A. K., & Nanda, S. (2020).  Receptiveness of effective tax rate to firm characteristics: an empirical analysis on Indian listed firms. Journal of Asia Business Studies, 15(1), 198-214.
51. Parle, W. M., & Hirlinger, M. W. (1986). Evaluating the use of tax amnesty by state governments. Public Administration Review, 46(3), 246. Retrieved from https://doi.org/10.2 307/3110440
52. Pohan, C. A., Kusuma, M., & Arimbhi, P. (2019). Evaluation of tax amnesty policy. An Effort To Increase Tax Revenue. 6(1), 30–37. Retrieved from https://doi.org/10.31334/reformasi.v6i1.330
53. Price, D. J. (1965). Networks of scientific papers. Science, 149(3683), 510–515. Retrieved from https://doi.org/10.1126/science.149.3683.510
54. Rao, M. G. (2005). Tax system reform in India: Achievements and challenges ahead. Journal of Asian Economics, 16(6), 993-1011.
55. Sa’Adah, N. (2018). Tax amnesty policy as an effort to improve state revenues and investment growth. IOP Conference Series: Earth and Environmental Science, 175(1). Retrieved from https://doi.org/10.1088/1755-1315/175/1/012206
56. Said, L. (2018). Implementation of tax amnesty and its impact on Indonesia economics. Reports on Economics and Finance, 4(1), 45–56. Retrieved from https://doi.org/10.129 88/ref.2018.815
57. Sayidah, N., & Assagaf, A. (2019). Tax amnesty from the perspective of tax official. Cogent Business and Management, 6(1), 1–12.
58. Stella, P. (1991). An economic analysis of tax amnesties. Journal of Public Economics, 46(3), 383–400. Retrieved from https://doi.org/10.1016/0047-2727(91)90013-R
59. van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. Measuring Scholarly Impact, 285–320. Retrieved from https://doi.org/10.1007/978-3-319-10377-8_13
60. Wagner, C. S., Whetsell, T. A., & Leydesdorff, L. (2017). Growth of international collaboration in science: Revisited. Scientometrics, 110(3), 1535–1552. Retrieved from https://doi.org/10.1007/s11192-016-2230-9
61. Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391. Retrieved from https://doi.org/10.1016/j.joi.2016.02.007
62. Zhu, J., & Liu, W. (2020). A tale of two databases: The use of Web of Science and Scopus in academic papers. Scientometrics, 123(1), 321–335. Retrieved from https://doi.org/10.10 07/s11192-020-03387-z
63. Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. Retrieved from https://doi.org/10.1177/1094428114562629