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Determinants of growth in Italy. A time series analysis

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  • Stefania Villa

Abstract

This paper investigates the macro-determinants of growth in Italy in a time series framework, from 1950 till 2004. The analysis of economic growth, started with the Solows (1956) and Swans (1956) famous contributions, has developed rapidly since the mid 1980s. The empirical literature follows two main approaches: growth accounting and growth regressions. In this paper the empirical approach starts with a parsimonious specification of the growth equation and then it analyses extended models. The initial specification is consistent with the standard neoclassical model and includes human capital. The extensions involve the introduction of a set of policy and institutional factors potentially affecting the Italian economic performance. In relation to econometric techniques, we use the error correction model (ECM) representation: in a time series framework, it provides evidence on the existence of a stable long-run linear relationship between growth and its determinants. The main results are the following: investment is the key source of economic growth; time series properties of the variables of interest and regression analysis provide evidence in favour of endogenous growth models in Italy and the only variable that seems to be robustly correlated with growth, according to the Extreme Bound Analysis, is government consumption, which affects negatively the growth rate.

Suggested Citation

  • Stefania Villa, 2005. "Determinants of growth in Italy. A time series analysis," Quaderni DSEMS 24-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
  • Handle: RePEc:ufg:qdsems:24-2005
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    2. Adejumo, Oluwabunmi O. & Asongu, Simplice A. & Adejumo, Akintoye V., 2021. "Education enrolment rate vs employment rate: Implications for sustainable human capital development in Nigeria," International Journal of Educational Development, Elsevier, vol. 83(C).
    3. Kais Saidi & Chebli Mongi, 2018. "The Effect of Education, R&D and ICT on Economic Growth in High Income Countries," Economics Bulletin, AccessEcon, vol. 38(2), pages 810-825.
    4. Panagiotis PEGKAS & Constantinos TSAMADIAS, 2015. "Does Formal Education At All Levels Cause Economic Growth? Evidence From Greece," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 15, pages 9-32, June.
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    6. Feyza BALAN & Seda OZEKICIOGLU & Cuneyt KILIC, 2016. "Determining the causal relationships among entrepreneurship, educational attainment and per capita GDP in high-income OECD countries," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(608), A), pages 243-256, Autumn.

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    More about this item

    Keywords

    Economic Growth; Time-Series Models.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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