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Time-series properties and empirical evidence of growth and infraestructure: revised version


  • Issler, João Victor
  • Ferreira, Pedro Cavalcanti


After more than forty years studying growth, there are two classes of growth models that have emerged: exogenous and endogenous growth models. Since both try to mimic the same set of long-run stylized facts, they are observationally equivalent in some respects. Our goals in this paper are twofold First, we discuss the time-series properties of growth models in a way that is useful for assessing their fit to the data. Second, we investigate whether these two models successfully conforms to U.S. post-war data. We use cointegration techniques to estimate and test long-run capital elasticities, exogeneity tests to investigate the exogeneity status of TFP, and Granger-causality tests to examine temporal precedence of TFP with respect to infrastructure expenditures. The empirical evidence is robust in confirming the existence of a unity long-run capital elasticity. The analysis of TFP reveals that it is not weakly exogenous in the exogenous growth model Granger-causality test results show unequivocally that there is no evidence that TFP for both models precede infrastructure expenditures not being preceded by it. On the contrary, we find some evidence that infras- tructure investment precedes TFP. Our estimated impact of infrastructure on TFP lay rougbly in the interval (0.19, 0.27).

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  • Issler, João Victor & Ferreira, Pedro Cavalcanti, 1998. "Time-series properties and empirical evidence of growth and infraestructure: revised version," FGV/EPGE Economics Working Papers (Ensaios Economicos da EPGE) 336, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  • Handle: RePEc:fgv:epgewp:336

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    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Maddison, Angus, 1983. "A Comparison of Levels of GDP Per Capita in Developed and Developing Countries, 1700–1980," The Journal of Economic History, Cambridge University Press, vol. 43(01), pages 27-41, March.
    4. Neusser, Klaus, 1991. "Testing the long-run implications of the neoclassical growth model," Journal of Monetary Economics, Elsevier, vol. 27(1), pages 3-37, February.
    5. Hendry, David F & Mizon, Grayham E, 1978. "Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England," Economic Journal, Royal Economic Society, vol. 88(351), pages 549-563, September.
    6. Spiros Bougheas & Panicos O. Demetriades & Theofanis P. Mamuneas, 2000. "Infrastructure, specialization, and economic growth," Canadian Journal of Economics, Canadian Economics Association, vol. 33(2), pages 506-522, May.
    7. Alwyn Young, 1995. "The Tyranny of Numbers: Confronting the Statistical Realities of the East Asian Growth Experience," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 641-680.
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    Cited by:

    1. Ferreira, Pedro Cavalcanti & Nascimento, Leandro Gonçalves do, 2005. "Welfare and growth effects of alternative fiscal rules for infrastructure investment in Brazil," FGV/EPGE Economics Working Papers (Ensaios Economicos da EPGE) 604, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
    2. Ferreira, Pedro Cavalcanti & Pereira, Ricardo A. de castro, 2008. "Efeitos de Crescimento e Bem-estar da Lei de Parceria Público-Privada no Brasil," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 62(2), October.
    3. Vahid, Farshid & Issler, Joao Victor, 2002. "The importance of common cyclical features in VAR analysis: a Monte-Carlo study," Journal of Econometrics, Elsevier, vol. 109(2), pages 341-363, August.

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