Explaining the Informal Economy: an Exploratory Evaluation of Competing Perspectives
Bibliographic record
Abstract
The aim of this paper is to conduct an exploratory analysis of the wider economic and social conditions associated with larger informal economies. To do this, three competing perspectives are evaluated critically which variously assert that cross-national variations in the size of the informal economy are associated with: under-development (modernization perspective); high taxes, corruption and state interference (neo-liberal perspective), or inadequate state intervention to protect workers (political economy perspective). Analyzing the variable size of the informal economy across 33 developed and transition economies, namely 28 European countries and five other OECD nations (Australia, Canada, Japan, New zealand and the USA), the finding is that larger informal economies are associated with under-development as measured by lower levels of GNI per capita, employment participation rates, average wages and the institutional strength and quality of the bureaucracy, higher levels of perceived public sector corruption, lower levels of expenditure on social protection and labour market intervention to protect vulnerable groups, but also restrictions on the use of temporary employment contracts and TWAs. The outcome is a tentative call to combine a range of tenets from all three perspectives in a new more nuanced and finer-grained understanding of how the cross-national variations in the size of the informal economy are associated with broader economic and social conditions. The paper concludes by discussing the implications for theory and policy, including the need for further analysis of the different impacts on the size of the informal economy of a wider range of indicators of modernization, corruption, taxation and types of state intervention.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".