The Three Hurdles of Tax Planning: How Business Context, Aims of Tax Planning, and Tax Manager Power Affect Tax Expense
Bibliographic record
Abstract
Abstract The question of why some companies pay fewer taxes than others is a widely investigated topic of interest. One of the well‐known explanations is a phenomenon called tax avoidance . We develop a grounded theory model of influences on corporate tax planning through a series of 19 in‐depth German tax expert interviews. Our research identifies three independent hurdles in the tax planning process, which can help to explain different levels of tax expense across companies. Those three hurdles sequentially address which tax planning methods are available (defined by business characteristics), desirable (given via aims of tax planning), and implementable (determined by tax manager power). A large part of previous research has estimated the influence of firm characteristics, which we incorporate in the broader term business characteristics, on tax expense, while the other influences that we identify have largely been left “out of the equation.” In the light of the current public debates on tax avoidance, we reveal two important findings: First, we find that companies vary widely in the aggressiveness of their aims of tax planning, which contrasts sharply with the picture often drawn by undifferentiated media reports. Second, tax managers can assume very different levels of power in their organization. The implementation of desirable tax planning methods varies depending on this level of tax manager power. In conclusion, our three‐hurdle grounded theory provides generalizable insights into important influences on corporate tax planning which help to explain the observed variation in tax expenses across firms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".