Estimating tax effort: new evidence from a novel dataset
Hayruni Tatul et al.
What the paper says
We provide new evidence on countries’ tax effort – the gap between collected and predicted tax revenue – based on a self-constructed panel of 114 countries, covering the period from 1995 to 2020. We apply the stochastic frontier model of Kumbhakar et al. (2014. Technical efficiency in competing panel data models: A study of Norwegian grain farming. Journal of Productivity Analysis, 41(2), 321–337.) to disentangle country-specific fixed effects from the persistent and time-varying components of tax effort. Our findings suggest that the level of development, trade volume, education, income inequality, and the ease of tax collection are important determinants of tax collection. We also find that countries with historically strong indicators of governance, rule of law, and control of corruption tend to exhibit higher levels of persistent effort. This suggests improved estimates of tax effort by 7.2–12.5 percentage points compared to specifications, where persistent trends in tax effort are attributed either to country heterogeneity or time-varying factors.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.