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The effect of real-time fiscal policy on sovereign interest rates in OECD countries


The aim of this study is to investigate the effect of real-time projections of fiscal policy stances on government bonds long-term interest rates using a panel of 20 OECD countries between 1992 and 2008. To deal with endogeneity arising from forecasts of fiscal balances the paper exploits instrumental variables and GMM estimators together with the variation in real-time primary balances. The study shows how a static specification that does not include the one-period lag of the interest rate is prone to serial correlation and to downward bias in standard errors. To correct the bias, a dynamic specification with the lagged interest rates used as explanatory variable should be used due to the intrinsic persistent behavior of the interest rates. Results show that when the persistency of the interest rates is taken into account, it corrects the bias in standard errors of the estimates, and the correlation between fiscal policy variables and sovereign rates disappears: the inertia of the behavior of interest rates is the only variable affecting the relation.

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  1. For the U.S. the Congressional Budget Office (CBO) and the Office of Management and Budget (OMB) provide such long-term independent projections (up to ten year ahead). For other countries the situation is more demanding since no long-term projections exist, hence researchers have adopted near-term projections (up to two year ahead) of the OECD, and, in the case of European countries the near-term projections of the European Commission Note that the data availability is one of the main obstacles in attempting comparisons of empirical results between U.S. and other countries.

  2. For a VAR detailed survey, see Gale and Orszag (2003; 2004).

  3. All Ardagna et al. (2007) data are revised and are from the OECD Economic Outlook n.73 2003.

  4. However, the choice of including the mid-year June edition of forecasts is susceptible to criticism. Indeed government future budgetary plans are discussed after June, usually in September-October, and therefore OECD forecasts of fiscal stances for the following year will be most presumably recalculated and updated in the December’s edition, once the new fiscal policy framework is approved.

  5. Indeed, the change in the long-term interest rate as the dependent variable is simply a stricter restriction (the coefficient of the lagged long-term interest rates is assumed to be 1) on the estimation equation than the inclusion of the lagged long-term interest rate among regressors where the long-term interest rates is allowed to enter with a coefficient different from 1.

  6. The countries are: Australia, Austria, Belgium, Canada, Germany, Denmark, Spain, Finland, France, Great Britain, Greece, Ireland, Italy, Japan, Norway, Netherland, New Zeeland, Portugal, Sweden and U.S.

  7. The analysis adopts the GDP deflator as a proxy for inflation. The reason is that long-time series (from the 1992) of the projections of inflation are not available in the OECD December Economic Outlooks.

  8. The short term interest rates as explanatory variable could lead to underestimate the impact of government expenditure on long-term interest rate mainly due to the feedback effect that fiscal policy could have on short-term interest rates through the monetary policy reaction function (Canzoneri et al. 2002. However, when fiscal variables are regressed on short-term interest rate no significant effect at 10 % confidence level is found suggesting little evidence of fiscal policy effect on short term rates.

  9. In a variant of the baseline static regression also primary balances are used as regressors to the end to estimate the autonomous effect of government fiscal balances.

  10. This result is in line with the empirical evidence on OECD countries (Ardagna et al. 2007; Reinhart and Sack 2000).

  11. The latter could be interpreted as a symptom of a-cyclical monetary policy notwithstanding the fact that the dependent variable is the long-term interest rate and not the short-term rate.

  12. For instance, Ziliak (1997) and Wooldrige (2001) demonstrated that the adoption of Anderson-Hsiao (AH) and Arellano-Bond (AB) estimators within a macro dataset could strongly bias the results.

  13. A similar conclusion was pushed forward also by Barth et al. (1991) which emphasized that most of the empirical literature on fiscal policy effects on long-term interest rates becomes futile if the lagged dependent variable is introduced in reduced form regressions.

  14. A note of caution is however necessary. The twice lagged dependent variable can be used as instrument for ∆IRL i,t-1 only if the error term does not have a serial correlation of second order. When there is a second order serial correlation the twice lagged dependent variable will be still correlated with the error term and therefore the estimates will be biased. As such, in the case of second order serial correlation within the difference equation, the third lag of the dependent variable becomes the first valid instrument.


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I would like to thank Prof. Massimo Giuliodori for his intellectual support and insight during the preparation of this paper, the participants at the INFER conference of the University of Coimbra and the anonymous referees therein, Mara Pirovano and one anonymous referee for their constructive comments.

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Correspondence to Ernest Dautovic.

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Dautovic, E. The effect of real-time fiscal policy on sovereign interest rates in OECD countries. Int Econ Econ Policy 14, 167–185 (2017).

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  • Real-time fiscal policy
  • Primary fiscal balance
  • Government debt
  • Long-term interest rate
  • OECD projections
  • Dynamic panel data

JEL Classification

  • C2
  • E6
  • H6
  • G1