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Government Debt and the Excess Sensitivity of Private Consumption to Current Income: An Empirical Analysis for OECD Countries

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  • POZZI Lorenzo
  • HEYLEN Freddy
  • DOSSCHE Maarten

Abstract

Empirical studies typically find that private consumption is much more sensitive to changes in current disposable income than is predicted by Hall's (JPE, 1978) permanent income hypothesis. Standard explanations for this "excess sensitivity" of private consumption refer to liquidity constraints and/or myopia. Elaborating on existing theoretical literature, which suggests that the incidence of liquidity constraints and the degree of myopia may be affected by the government debt ratio, this paper investigates the role of government debt in the degree of excess sensitivity. Using a panel of OECD countries in the 1990s, we estimate a consumption function with the degree of excess sensitivity depending on the government debt ratio and the degree of financial liberalisation. We find that a higher government debt leads to more excess sensitivity. This result supports the idea that a higher debt induces private lenders to tighten credit conditions, which raises the incidence of liquidity constraints. As to the effects of financial liberalisation on excess sensitivity in the 1990s, we obtain no clear evidence.
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  • POZZI Lorenzo & HEYLEN Freddy & DOSSCHE Maarten, 2010. "Government Debt and the Excess Sensitivity of Private Consumption to Current Income: An Empirical Analysis for OECD Countries," EcoMod2003 330700125, EcoMod.
  • Handle: RePEc:ekd:003307:330700125
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    More about this item

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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