Entrepreneurship and urban growth: dimensions and empirical models
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Résumé
Purpose The purpose of this paper is to look at various dimensions of entrepreneurship and the empirical models that try to explain the relationship between entrepreneurship and growth in cities for both developed (USA and Europe) and developing countries. Design/methodology/approach This paper provides an in‐depth and extensive review of the existing literature on entrepreneurship and economic growth in cities. In most empirical studies, the growth rate of employment or unemployment rate is used as the dependent variable to analyze the effect of entrepreneurship on development. The important independent variables other than entrepreneurship (new start‐ups) are localization, urbanization, level of education, age, industry structure (specialization vs competition), monopoly or competition. The economic units considered for cities are labor market areas (LMAs), standard metropolitan areas (SMAs) and consolidated metropolitan statistical areas (CMSAs). The majority of studies have utilized discrete dependent variable models such as Tobit or Probit to calculate the probability of the effect of entrepreneurship on economic growth. Other studies have applied ordinary least squares estimation to find the cross‐sectional variation of employment growth that accounts for entrepreneurial activities. Panel data are employed in a number of models to control for region‐specific and country‐specific fixed effects. Findings In this paper, four important dimensions of entrepreneurship are identified. First, for entrepreneurial studies on economic growth, cities are considered to be appropriate economic units rather than states or countries. Second, there are several definitions and measurements of entrepreneurship available in the literature. Hence, empirical models and their results may vary depending on the model specification. Third, the relationship between employment growth (a proxy for economic growth) and innovative activity is dynamic in nature and thus the problem of endogeneity needs to be addressed. And, finally, entrepreneurship has a spatial dimension and that characteristic must be incorporated into the urban and regional models of entrepreneurship. Three different types of urban models are chosen to reflect these four central dimensions of entrepreneurship. All three urban models confirm the hypothesis that there exists a statistically significant and positive relationship between entrepreneurship and growth in cities. However, the causality of the relationship is not well established. Originality/value A critical and in‐depth summary of existing quantitative work on entrepreneurship and economic growth in different cities is the original contribution of the paper.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle