Innovation, Socio-institutional Conditions and Economic Growth in the Italian Regions

Abstract

D'Agostino G. and Scarlato M. Innovation, socio-institutional conditions and economic growth in the Italian regions, Regional Studies. An explanatory investigation is carried out into the relationship between social and institutional contextual factors and economic growth in the Italian regions. A three-sector semi-endogenous growth model with negative externalities related to the social and institutional variables affecting the innovative capacity of regional economic systems is constructed. The empirical investigation confirms the presence of non-linearities that depend on the socio-institutional conditions constituting constraints on the translation of innovation into economic growth. The paper suggests that policies targeting the enhancement of local socio-institutional conditions have major repercussions for the innovation capacity and economic growth of the lagging southern regions.

D'Agostino G. and Scarlato M. 意大利区域的创新、社会制度条件与经济成长，区域研究。本研究将对意大利区域中的社会、制度脉络因素和经济成长之间的关联性进行解释性的探讨。本研究将建立一个三部分的半内生成长模型，该模型纳入与影响区域经济系统创新能力的社会及制度变因有关的负面外部性。经验探讨确认了取决于社会—制度条件的非线性存在，这些条件构成了将创新转换为经济成长的限制。本文指出，针对提昇地方社会—制度条件的政策，对于落后的南方区域的创新能力与经济成长有着重要的影响。

D'Agostino G. et Scarlato M. L'innovation, les conditions socio-institutionnelles et la croissance économique dans les régions italiennes, Regional Studies. On a fait une analyse explicative du rapport entre les facteurs contextuels socio-institutionnels et la croissance économique dans les régions italiennes. On construit un modèle de croissance semi-endogène à trois secteurs avec des externalités négatives relatives aux variables socio-institutionnelles qui influent sur la capacité novatrice des systèmes économiques régionaux. L'analyse empirique confirme la présence des non-linéarités qui nécessitent que les conditions socio-institutionnelles constituent des constraintes sur le passage de l'innovation à la croissance économique. L'article suggère que les politiques visant l'amélioration des conditions socio-institutionnelles locales ont d'importantes répercussions pour la capacité d'innovation et la croissance économique des régions méridionales en perte de vitesse.

D'Agostino G. und Scarlato M. Innovation, sozio-institutionelle Bedingungen und Wirtschaftswachstum in den italienischen Regionen, Regional Studies. Die Beziehung zwischen gesellschaftlichen und institutionellen Kontextfaktoren und dem Wirtschaftswachstum in den italienischen Regionen wird einer erklärenden Untersuchung unterzogen. Wir entwickeln ein auf drei Sektoren beruhendes, semi-endogenes Wachstumsmodell mit negativen Externalitäten in Bezug auf die gesellschaftlichen und institutionellen Variablen, die sich auf die Innovationskapazität von regionalen Wirtschaftssystemen auswirken. Bei der empirischen Untersuchung bestätigt sich die Präsenz von Nicht-Linearitäten, die von den sozio-institutionellen Bedingungen abhängen, was die Umsetzung von Innovation in Wirtschaftswachstum behindert. Der Beitrag legt den Schluss nahe, dass Politiken, die auf eine Verbesserung der lokalen sozio-institutionellen Bedingungen abzielen, wichtige Konsequenzen für die Innovationskapazität und das Wirtschaftswachstum der rückständigen südlichen Regionen haben.

D'Agostino G. y Scarlato M. Innovación, condiciones socioinstitucionales y crecimiento económico en las regiones italianas, Regional Studies. Llevamos a cabo una investigación explicativa sobre la relación entre los factores de contexto sociales e institucionales y el crecimiento económico en las regiones italianas. Construimos un modelo de crecimiento semiendógeno de tres sectores con factores externos negativos relacionados con las variables sociales e institucionales que repercuten en la capacidad innovadora de los sistemas económicos regionales. La investigación empírica confirma la presencia de no linealidades que dependen de las condiciones socioinstitucionales que impiden que la innovación se traduzca en crecimiento económico. En este artículo sugerimos que las políticas que abordan la mejora de las condiciones socioinstitucionales de ámbito local tienen importantes repercusiones en la capacidad de innovación y el crecimiento económico de las regiones del sur menos desarrolladas.

• Technological change
• Economic growth
• Regional disparities
• Econometric modelling
• Regional policy

• 技术变革
• 经济成长
• 区域差异
• 计量经济模型
• 区域政策

• Mutation technologique
• Croissance économique
• Disparités régionales
• Modélisation économétrique
• Politique régionale

• Technologische Änderungen
• Wirtschaftswachstum
• Regionale Disparitäten
• Ökonometrische Modelle
• Regionalpolitik

• Cambio tecnológico
• Crecimiento económico
• Desigualdades regionales
• Modelo econométrico
• Política regional

JEL classifications:

• C50
• O30
• O41
• R11

Acknowledgements

Early versions of this paper were presented at the Workshop on Advances in Business Cycles and Economic Growth Analysis, Rimini Centre for Economic Analysis, May 2011, and at the 52nd Annual Conference of the Italian Economic Association, October 2011. The authors are grateful to the participants and discussants at those sessions for their comments. In particular, the authors are grateful to Philippe Aghion, Costas Azariadis, Riccardo Crescenzi, Leo Kaas, Raffaele Paci, Luca Pieroni, Pietro Reichlin and Joseph Zeira for their suggestions and helpful comments. Finally, the authors would like to acknowledge the insightful comments of two anonymous reviewers.

Notes

1. This property depends on the assumption that the firms producing final goods operate in conditions of perfect competition and are characterized by constant returns to scale.

2. It is important to note that because the SR&D is perfectly competitive and the function has constant returns to scale, the parameters j and l can be interpreted in terms of the elasticity of factors in relation to technology, when constant returns are assumed.

3. Using the version of the budget constraint in terms of factor prices makes it possible to rewrite the equation as:

4. For an analytical derivation of the parameters used to construct the system with scaled variables applying the social planner's solution to the problem of the inter-temporal optimization of the representative consumer, see Steger (2005a).

5. Statistically, the authors define x_it as a predetermined variable when the error term at time t has some feedback on the subsequent realizations of x_it. Hence, for predetermined variables:

6. Because the production function does not include blueprint prices, they are omitted from the specification of the growth equation (11).

7. The results presented by Soto (2009) use a complete set of instruments (that is, thirty-one instruments in a sample of thirty-five cross-sectional units) and the instrument matrix is different when first-difference and system GMM estimators are simulated. Consequently, the results from Monte Carlo simulations may be partially driven by the hypotheses under the simulation design. Moreover, the use of Blundell and Bond's system GMM estimator (Blundell and Bond, 1998) is particularly suitable in the case of non-stationary time-series but requires an increasing amount of instruments when the level instruments are included.

8. The results are available from the authors upon request.

9. The significance level of this variable crucially depends on the Mezzogiorno area, where the technological level is extremely low compared with the full sample from the Italian regions.

10. Standard errors (not reported) are obtained by 10 000 bootstrap replications.