| Project/Area Number |
22K13415
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 07050:Public economics and labor economics-related
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| Research Institution | Hitotsubashi University |
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Principal Investigator |
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| Project Period (FY) |
2022-04-01 – 2026-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2023: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2022: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | tax evasion / firm network / Tax evasion / Tax capacity / Firm network / Mongolia |
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| Outline of Research at the Start |
Many developing countries struggle to raise an adequate amount of tax revenue to fund policies that are important for economic growth. This project aims to explore one of the potential explanations - corporate tax evasion. I aim to study the relationship between a firm’s tax evasion behaviour and their business network using highly detailed, confidential administrative tax data from Mongolia.
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| Outline of Annual Research Achievements |
I worked on identifying the firm clusters using machine learning algorithms based on the relation between tax audit results and information on firms’ various tax returns such as corporate income tax and VAT returns. I also improved the matching between tax data, firm ownership data and firms' GIS location information.
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| Current Status of Research Progress |
Current Status of Research Progress
4: Progress in research has been delayed.
Reason
Due to personal reasons, I had to take a temporary leave from my work and suspend this project. I plan to return to work in 2025.
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| Strategy for Future Research Activity |
I will continue to work on identifying firm clusters based on trade, ownership, and geographical networks.
Specifically, I plan to study whether tax-evading firms in Mongolia form clusters and investigate what motivates firms to join or leave such evasion-prone networks. To do so, I will use data on firm entry and exit as well as the sudden increase in the VAT threshold in 2016.
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