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Does Ricardian equivalence hold in Australia? A revision based on testing super exogeneity with impulse-indicator saturation

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Following the 2008–2009 Global Financial Crisis, many countries, including Australia, enacted fiscal stimulus packages in the hope of reviving their economies by encouraging aggregate demand. For the success of these efforts, it is vital that fiscal policies have some positive impact on the real economy. However, tax reductions and cash handouts are virtually ineffective if consumers are Ricardian and internalise the intertemporal budget constraint of the government. This paper aims to test the Ricardian equivalence hypothesis for Australia from 1960 to 2011 by exploiting the links between (1) Ricardian equivalence and the Lucas critique; (2) the Lucas critique and super exogeneity, and (3) testing for super exogeneity with impulse-indicator saturation. As there is no evidence of a structural break in the conditional model for the growth rate of per capita real gross domestic savings, we conclude that policy-regime shifts did not lead to substantial changes in the estimated relationship, so the Lucas critique does not apply. Consequently, our results indicate that during the past half-century Ricardian equivalence held in Australia. This implies that tax and cash bonuses of the government may not lead to the desired economic outcomes as Ricardian-type consumers tend to offset the dissaving of the government by saving more and leaving household consumption unchanged.

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  1. The details and results of these tests are not reported in the paper.

  2. About the Lucas critique, its applicability and testability see e.g. Favero and Hendry (1992).

  3. As an example, see Bergeijk and Berk (2001).

  4. See Ericsson and Irons (1994) for a literature review on testing exogeneity.

  5. These two conditions basically mean that the exact specification of the marginal density is irrelevant and inference on \(\theta \) conditional on \(x_{t}\) involves no loss of information because \(\lambda _{2t}\) are nuisance parameters. Hence, even if \(\lambda _{2t}\) were known, this information would not help estimate \(\lambda _{1t}\) over any period during which \(\lambda _{2t}\) and \(\lambda _{1t}\) are both constant.

  6. Variation free and invariance are two different concepts. If \(\lambda _{1t}=\varphi \lambda _{2t}\) (for all \(t)\), then \(\lambda _{1t}\) is not invariant with respect to \(\varphi \lambda _{2t}\), but they are variation free because over periods of \(\lambda _{2t}=\lambda _{2}\) there is no information in \(\lambda _{2}\) which could help estimating \(\lambda _{1}\). On the other hand, if \(\lambda _{1}=\varphi _{t}\lambda _{2t}\) (for all \(t\)), then \(\lambda _{1}\) is both variation free and invariant to \(\lambda _{2}\).

  7. Although for the sake of simplicity, we keep assuming that there is only one conditioning variable, this procedure can be straightforwardly generalised for more conditioning variables.

  8. Hendry et al. (2008) show that more than two, or even unequal, splits are also possible and they affect neither the retention rate under the null, nor the simulation-based sampling distributions.

  9. RE fails in model 2 because of distortionary taxation, in model 3 because of finite horizons and in model 4 for both reasons.

  10. All calculations were performed with EViews 7.2 and OxMetrics 6.

  11. We rely on the following diagnostic tests: Breusch–Godfrey LM test for residual autocorrelation, Breusch–Pagan–Godfrey LM test for heteroscedasticity; autoregressive conditional heteroscedasticity LM test, Jarque-Bera test for normality and Ramsey regression specification error test. See the details in the Note of Table 4.

  12. In marginal models (4) and (5) all variables are stationary. Marginal model (6) has a mixture of I(0) and I(1) variables but the bounds test fails to detect a level relationship between them. Marginal model (7) has an I(0) variable on the left side and an I(1) variable on the right side, so it is clearly unbalanced. However, each of these marginal models can be estimated in the first differences of the variables.

  13. We followed the advice of Castle et al. (2012, p. 240) and set the target size \(\alpha \) approximately equal to 1/\(K\), where \(K\) is the number of included regressors. At this target size the retention rate of irrelevant variables (called gauge) is about \(\alpha \).

  14. These potential break dates correspond with the end of a severe draught (1965–1966) and the expansionary budget policies in 1967; the mining boom, inflationary pressures and rising unemployment during 1967–1971; the extra government funds for states to curb inflation and unemployment, the reduction in income taxes and the federal elections in 1972; the oil crisis during 1973-1974; the 10 % reduction of government administrative expenditures and the devastation of Darwin by cyclone Tracy in 1975; the long-lasting draught in 1982; the federal election and floating of Australian dollar in 1983, the Gulf War in 1991; and the post-financial crisis period of 2009.


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We are grateful for the helpful comments of two anonymous referees of this journal.

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Correspondence to László Kónya.



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Kónya, L., Abdullaev, B. Does Ricardian equivalence hold in Australia? A revision based on testing super exogeneity with impulse-indicator saturation. Empir Econ 49, 423–448 (2015).

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