What territories can do for SMEs and how do SMEs gives them a lot back - Nadine Levratto
0 likes195 views
The document discusses the relationship between SMEs and local characteristics, emphasizing that local conditions significantly influence firm robustness and job creation rates. It highlights the importance of educational levels and the presence of high-tech SMEs in enhancing resilience and growth within regions. The analysis indicates that entrepreneurship is a key driver of economic development, with varying influences depending on regional characteristics.
More Related Content
Similar to What territories can do for SMEs and how do SMEs gives them a lot back - Nadine Levratto (20)
![[Challenge:Future] NLY solution: Network Growth Pole](https://cdn.slidesharecdn.com/ss_thumbnails/challengefuture-nly-solution-network-growth-pole4494-130228145807-phpapp02-thumbnail.jpg?width=560&fit=bounds)
What territories can do for SMEs and how do SMEs gives them a lot back - Nadine Levratto
- 1. What territories can do for SMEs and how do SMEs give them a lot back ? OECD conference on SMEs and the Urban Fabric 15-16 April 2019, Trento Nadine Levratto EconomiX – CNRS – University Paris Nanterre [email protected] 1
- 2. Outline A triple perspective on the relationship between SMEs and local characteristics SMEs soundness and regional context : a regional perspective Employment growth rate in SMEs in French employment areas Local resilience and firm entry 2
- 3. Firm situation Firm’s trajectories topic has been widely investigated under different aspects. 1. firm-specific factors (Altman, 1968; Mueller & Stegmaier, 2014) 2. industrial-specific factors: market evolution, intra-industry diversification (Agarwal & Gort, 1996; Ilmakunnas & Topi, 1999) 3. location-specific factors: the financial context (Arcuri & Levratto, 2018), agglomeration economies (Glaeser & Kerr, 2009), and, generally, local conditions (Karlsson, Klaesson, & Öner, 2015) 3
- 4. 1. Firm robustness Local conditions matter in explaining firm robustness and the probability of failure 4
- 5. Z score: SMEs operating in the manufacturing industry (Average 2010-2015) Source: Abdel Fattah et al. (2019) on AMADEUS dataset • 22,079 SMEs operating in the manufacturing industry, located in 4 European countries (Italy, France, Germany, Belgium), observed during the period 2010-2015 • Unbalanced panel of 86,839 observations Altman Z’’-Score (1983) calculated by Discriminant Analysis Z” score : 3.25+ 6.56 X1 + 3.26 X2 + 6.72 X3 +1.05 X4 X1 = Working Capital/Total Assets (WC/TA) X2 = Retained Earnings/Total Assets (RE/TA) X3 = Earnings Before Interest and Taxes/Total Assets (EBIT/TA). X4 = Book Value of Equity/Book Value of Total Liabilities (BVE/TL)
- 6. MAIN RESULTS The mix of individual and regional levels characteristics explains firm soundness more accurately than individual features only Location matters Estimations with a Multilevel Model for Panel Data 12.4% of the firm robustness is explained by local conditions Robustness of SMEs enhanced when : A higher level of education (Population aged 25-64 with a tertiary education) and A higher rate of HT SMEs (knowledge spillovers) Especially in Low knowledge and Medium knowledge intensive regions No significant effect of Density (agglomeration effect) GDP per capida (income effect)
- 7. 2. Job creation in French employment areas 7
- 8. Employment growth rate in France (2009-2015) 8 Empirical analysis SMEs are more likely to create jobs in areas with : - a lower share of manufacturing industries - a higher rate of SMEs - a lower share of business groups - a higher density, - a higher demand French employment areas (304 spatial units in mainland France)
- 10. What about regional economic resilience? Martin,2012
- 11. Recovery measure : rebound end of period 11 Recovery corresponds to employment growth rate between the choc (2009) and the current year (2015) The French local devide: • Better results in south-west, along the Rhône river, in Britany and along the Atlantic, • A visible macro-regional effect, • Spatial clustering. Estimations: - Estimated equation Rebound = f(LnDens_07, Indus_07, HHI_07, Krugman_07, Qualif_07, EffLoc_Etab_07, EmpPubl_07) - Method : quantile regression - Empirical results: - Negative influence of the share of manufacturing industry (NS for the most dynamic areas) - Increasing positive influence of an entrepreneurial differential effect Source
- 12. Conclusions 1. Local context drives SMEs growth rate 2. Local resilience significantly and positively driven by: The entrepreneurial orientation 3. Density, specialisation, concentration and other co-variates have a lower influence on regional recovery 4. The determinants of recovery differ according the area and the employment growth rate 5. Entrepreneurship leads economic growth, development, and prosperity (Schumpeter, 1911; Aghion and Howitt, 1992; Wennekers and Thurik, 1999; Carree and Thurik, 2003; Audretsch et al., 2006; Friis et al., 2006)
- 13. Source: Authors’ elaboration based on the Eurostat Dataset Levels of Education (Mean values 2010-2015) Levels of Employment in HT (Mean values 2010-2015)
- 14. 14 Thanks for your attention!
- 15. NUTS2 Regions by clusters Source: Authors’ elaboration based on the Eurostat Dataset
- 16. Recovery measure : rebound end of period