Bibliographic record
Abstract
Economic freedom indexes, especially the Fraser Institute/Cato Institute Economic Freedom of the World (EFW) index and the Heritage Foundation/Wall Street Journal Index of Economic Freedom, are becoming increasingly important as researchers seek to explore the link between economic freedom and prosperity. The consistent finding is that nations with more economic freedom--as indicated by security of property rights, free trade, limited government, low marginal tax rates, and so forth--enjoy higher per capita incomes and general living conditions compared with countries that are less free. (1) In a less aggregated study, Karabegovic et al. (2003) find that differences in economic freedom across U.S. states and Canadian provinces are significantly and positively related to differences in the level and growth of economic activity across states and provinces. Various researchers have used the Economic Freedom of North America (EFNA) index, published by the Fraser Institute (Karabegovic, McMahon, and Mitchell 2005), to address questions of income differentials between states, income growth, and entrepreneurship. (2) Scholars have also used the EFNA index to study migration. Ashby (2007), not surprisingly, finds that people tend to move from less free to more free areas. In this article, we apply the EFNA index to the question of business formation, similar to Kreft (2003) and Kreft and Sobel (2005). Specifically, we ask whether the governmental, judicial, and social activities observed in the index are significantly related to net business formation among the states. We posit that greater economic freedom results in higher income levels for state residents because such freedom increases the opportunities to pursue entrepreneurial activities. Thus, such freedom should be positively and significantly correlated to net business formation, as measured by the net change in the number of businesses as a percentage of total businesses by state. Consistent with our expectations, we find that there is a strong positive relationship between economic freedom in a state and net business formation, after controlling for state population, income, median age, federal intergovernmental revenue, minority percentage in the population, and commercial lending. Our results are qualitatively consistent with the arguments advanced by Sobel, Clark, and Lee (2007), Clark and Lee (2006), and Kreft and Sobel (2005): When economies become politicized, effort is channeled away from wealth creation and into securing protection from market forces. Consistent with our empirical results, states with less economic freedom--and therefore more intrusive government--experience a lower rate of business formation because the benefits of private, for-profit entrepreneurial activity decline relative to other forms of economic and political activity. Entrepreneurship, Economic Freedom, and Economic Performance Promoting entrepreneurship has emerged as a significant policy tool for regional economic growth and job creation (Friar and Meyer 2003; Laukkanen 2000; Rosa, Scott, and Klandt 1996). Indeed, Maillat (1998) argues that economic development policy has shifted to promoting endogenous economic growth via entrepreneurship and away from competitive growth via attracting businesses from elsewhere. The relevant policy question becomes how best to promote entrepreneurship. One answer repeatedly championed in the literature is to increase economic freedom, conceptualized as follows: Policies are consistent with economic freedom when they provide an infrastructure for voluntary exchange, and protect individuals and their property from aggressors seeking to use violence, coercion, and fraud to seize things that do not belong to them. However, economic freedom also requires governments to refrain from actions that interfere with personal choice, voluntary exchange, and the freedom to enter and compete in labor and product markets [Gwartney and Lawson 2002: 5]. …
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".