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Public expenditure and revenue in Italy, 1862-1993

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  • Magazzino, Cosimo

Abstract

This study examines the long-run equilibrium relationship between government expenditure and revenue in Italy from 1862 to 1993, using cointegration techniques and the direction of causality relationship in the long and short runs between the variables through integrating the Error Correction Model (ECM) into the traditional Granger causality test. A Granger non-causality test (due to Toda and Yamamoto) is also performed. Unit root tests have been applied in order to investigate the stationarity properties of the series. Moreover, three more homogeneous sub-period (1862-1913; 1914-1946; 1947-1993) have been analyzed. The nexus between public expenditure and revenue has been discussed also by Impulse Response Functions (IRFs) and Forecast Error Variance Decompositions (FEVDs). Empirical findings show how, for each sub-period, the policy adopted reflect the prevailing paradigm of public finance (neutral or orthodox finance, Keynesian finance and discretionary or compensatory finance, respectively).

Suggested Citation

  • Magazzino, Cosimo, 2010. "Public expenditure and revenue in Italy, 1862-1993," MPRA Paper 27308, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:27308
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Government expenditure; government revenue; stationarity; cointegration; causality; spend and tax; tax and spend; Italy.;

    JEL classification:

    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • H20 - Public Economics - - Taxation, Subsidies, and Revenue - - - General
    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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