Globalisation, capital mobility and convergence of effective tax rates
Bibliographic record
Abstract
This paper explicitly addresses the issue of international capital mobility and convergence of effective tax rates. After reviewing the existing econometric literature on the relation between tax burden and economic integration, the paper updates the approach of effective tax rates (ETRs) introduced by Mendoza et al. (1994) introducing a distinction between ETRs on mobile capital and ETRs on immobile capital. This fills a gap of the empirical literature, usually compounding taxes on corporations and taxes on immovable property under the same heading of ‘capital tax rates’, even though the expected reactions of these two forms of ‘capital’ to economic integration might be significantly different. An econometric analysis relating ‘tax burden’ and some measures of trade openness and capital mobility is performed. Evidence is provided that capital mobility affects the convergence of tax rates on mobile capital, making more difficult for countries to differentiate taxes on mobile tax bases. Far from being support for the race-to-the-bottom hypothesis, the paper argues that there is a significant push towards the homogeneity of tax burdens on mobile capital, which is – to some extent – support for a milder version of the ‘efficiency hypothesis’. \nThe econometric analysis is carried out including the main European countries, Japan, the United States, Australia and Canada. These latter countries are particularly important for the perspective adopted in this paper, as they experienced a liberalisation of capital flows before its introduction in Europe at the beginning of the Nineties. \nRather than to a race-to-the-bottom, taxes on mobile tax bases may race-to-some-average, indicating that the main effect of capital mobility could be that of preventing significant differentiation of effective tax rates rather than driving them to zero. \nInstead of using the levels of effective tax rates, this study uses their coefficient of variation across countries for each given year (CVAR). In alternative, the absolute value of the difference between each country’s effective tax rate and the corresponding average (DIFF) will also be used. \nBoth measures pick the main feature of tax competition, which, if any, is that of making differentiation costly, as large tax differentials may give rise to move capital across borders. \nThe robustness of our regression to alternative methods and, in particular, the strong evidence that the most recent period is particularly valuable to test the effects of tax competition adds to this literature in the expected direction, i.e. that economic integration makes more difficult for countries involved to differentiate the effective tax burden on mobile capital. \nWhile the convergence of effective tax rates on mobile capital is partly driven by economic integration, relatively more immobile tax bases should not be affected by openness. In particular, there is no particular reason to expect that taxes on immobile capital should converge across countries as, by definition, immobile capital cannot easily move from one country to another. The same line of reasoning may apply, to some extent, to labour (at least unskilled) and consumption. Conversely, if any, intense tax competition on one tax base might induce more dispersion of other tax bases, if countries act under a tax revenue constraint. This would lead to a either a positive or no relation of the coefficient of variation of immobile capital, labour and consumption with capital mobility. \nResults suggests that countries that cannot differentiate the tax burden on capital (because of its mobility) may more easily succeed to differentiate the tax burden on labour (which is a relatively immobile factor). \nIndirect support to this conclusion also comes from the irrelevance of outward FDI in driving the convergence of taxes on both immobile capital and consumption. The more plausible explanation is that both taxes on immobile capital and consumption may constitute a sort of backstop to the convergence of tax rates on capital. In the case of consumption, it must be also considered that effective tax rates on consumption are already more homogenous across countries, compared with capital and labour, and this leaves much less space to converge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".