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Is the Aggregate Size of Government in Canada Too Large?

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  • J. Stephen Ferris
  • Marcel-Cristian Voia

Abstract

This paper asks whether consolidated government in Canada is too large in relation to its effect on economic performance. Rather than impose a parametric shape, nonparametric methods are used to motivate the nonlinear form that best describes this relationship. Using data from 1929 through 2014 and controlling for the different time-series characteristics of the variables, the bias in standard errors that can be expected from correlations arising across time, and the presence of Wagner's-law-type endogeneity in the relationship running between government size and private performance, we find evidence consistent with government size peaking in its effect on private output at roughly 32 percent of GDP.

Suggested Citation

  • J. Stephen Ferris & Marcel-Cristian Voia, 2017. "Is the Aggregate Size of Government in Canada Too Large?," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 173(4), pages 723-752, December.
  • Handle: RePEc:mhr:jinste:urn:sici:0932-4569(201712)173:4_723:itasog_2.0.tx_2-6
    DOI: 10.1628/093245617X14860182052097
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    Cited by:

    1. J Stephen Ferris & Stanley L. Winer, 2018. "Political Competitiveness and Fiscal Structure: A Time Series Analysis. Canada, 1870 - 2015," CESifo Working Paper Series 7220, CESifo.

    More about this item

    JEL classification:

    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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