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Fiscal multipliers in turbulent times: the case of Spain

Abstract

What are the output responses to fiscal policy? Although important contributions have been made in the literature, quantifying the size of the fiscal multiplier remains a challenge. Indeed, the challenge of estimating a unique fiscal multiplier is probably an ill-posed one. The magnitude of the multiplier may well depend on country- and time-specific characteristics of the fiscal stance under scrutiny. In this paper, we estimate state-specific multipliers for Spain depending on the state of the economy along several dimensions. The government spending multiplier is estimated to be larger during recessions and banking stress periods, but much smaller (or even negative) during periods of weak public finances. Combining these three dimensions into a single global turmoil indicator via principal component analysis, the estimated multipliers are 1.4 for crisis (or turbulent) times and 0.6 for tranquil times.

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Notes

  1. 1.

    In addition to the fiscal VARs literature, some studies focus on analyzing episodes of large fiscal adjustments and their macroeconomic consequences. Based on statistical correlations between output growth and changes in the structural primary deficit, many of these studies conclude that fiscal consolidations might be expansionary for an economy depending on the composition of the adjustment (see e.g., Alesina and Ardagna 1998). However, after accounting for reverse causality between the fiscal adjustment and economic activity, IMF (2010) as well as Hernandez de Cos and Moral-Benito (2013) concludes that fiscal consolidations per se are not expansionary in the short run.

  2. 2.

    The fixed exchange rate regime might also amplify the effects of fiscal policy in Spain; however, the lack of within-time variation in our Spanish data precludes the consideration of fiscal multiplier heterogeneity across exchange rate regimes within our econometric approach. Note that empirical studies investigating this dimension exploit cross-country variation in exchange rate regimes (see Corsetti et al. 2012; Ilzetzki et al. 2013).

  3. 3.

    From a practical point of view, within the STVAR approach all observations in the sample can be used for estimation of the parameters in both regimes.

  4. 4.

    However, they find slightly smaller spillover effects in countries sharing a fixed exchange rate in spite of the inability of those countries to offset fiscal shocks from abroad via exchange rate policy.

  5. 5.

    We only provide here a brief enumeration of the papers in this literature, for reasons of space (see the working-paper version of this paper for a more detailed discussion on the identification challenge in the fiscal VAR literature).

  6. 6.

    In particular, BP02 argue that the reduced form shock to the fiscal variable is formed by three components, namely (i) the automatic response of the fiscal variable to innovations in output (e.g., an unanticipated change in tax revenues caused by a shock to output for given tax rates); (ii) the discretionary response of fiscal policy to output shocks (e.g., a reduction in the tax rate in a recession); and (iii) the pure random shock to the fiscal variable uncorrelated with any other structural shock (i.e., the structural shock we aim to identify).

  7. 7.

    Moreover, the literature has usually focused on government spending shocks more than tax shocks. The main reason is that unexpected changes in tax revenues within a quarter may arise as a result of changes in the relationship between economic activity and tax revenues rather than changes in discretionary fiscal policy. In this respect, the reliability of tax elasticities is crucial to purge the changes in tax revenues, but these elasticities may well depend on the state of the economy which further complicates the identification of tax shocks. As recently advocated by Riera-Crichton et al. (2012), the use of narrative approaches together with tax rates as a measure of tax policy —instead of commonly used revenue-based measures—represents a promising alternative to estimate tax multipliers.

  8. 8.

    The debate on the appropriateness of the fiscal multipliers used for estimating the impact of austerity programs has been recently revived by Blanchard and Leigh (2013)—who further develop the initial analysis published Box 1.1 of the October 2012 WEO. These authors suggest than fiscal multipliers considered for forecasting have been excessively low in the aftermath of the global crisis. This conclusion follows from the negative and significant relationship between growth forecast errors and the size of the associated fiscal policy change.

  9. 9.

    Along these lines, Parker (2011) argues that it is difficult to assess the effectiveness of countercyclical fiscal policy during recessions because deep recessions are few. The lack of data is even more pronounced when estimating the effects of contractionary fiscal policy during a recession, the policy that some countries in the Eurozone are currently undertaking.

  10. 10.

    Indeed, the proliferation of coefficients to be estimated combined with the reduced sample size available for estimation preclude us from including additional variables in the model.

  11. 11.

    The index \(z\) is dated at \(t-1\) to avoid contemporaneous feedbacks from policy actions to the state of the economy.

  12. 12.

    Note also that, besides the STVAR approach, a threshold VAR (TVAR) can also be considered for this purpose; however, we prefer the STVAR alternative because it allows the regimes to change smoothly from one regime to another, while the TVAR impose discrete switches from one to another regime. Moreover, this implies that within the STVAR approach, all observations in the sample can be used for estimation of the parameters in both regimes.

  13. 13.

    Fiscal variables are expressed in real terms using the GDP deflator.

  14. 14.

    See De Castro et al. (2014) for an in-depth analysis of the Spanish fiscal stance over this period.

  15. 15.

    Auerbach and Gorodnichenko (2012a) consider both the GDP growth and the output gap as \(z_t\) indicators for the USA. In addition, we also consider here the change in the unemployment rate.

  16. 16.

    The volume of credit to households over disposable income is also taken from the Banco de España database.

  17. 17.

    More concretely, we follow Auerbach and Gorodnichenko (2012a) and consider the seven-quarter moving average of these variables.

  18. 18.

    Alternatively, one could also consider the level of unemployment rate. However, given the high persistence of this variable in Spain, its interpretation as a proxy of the business cycle is less clear. Also, the share of unemployed people can also be interpreted as an indicator of constrained consumers in the economy that might also affect the magnitude of the fiscal multiplier. In any event, estimates based on this indicator are in line with those based on the change in the unemployment rate. To save space, these results are not reported here, but are available upon request.

  19. 19.

    In particular, we report the impact multiplier \(\left( \frac{\Delta \hbox {GDP}_t}{\Delta G_t}\right) \), the cumulative multiplier at some horizon \(H \left( \frac{\sum _{j=0}^{H}\Delta \hbox {GDP}_{t+j}}{\sum _{j=0}^{H}\Delta G_{t+j}}\right) \), and the peak multiplier over any horizon \(H \left( \max \frac{\Delta \hbox {GDP}_{t+H}}{\Delta G_t}\right) \).

  20. 20.

    In particular, \(\gamma \) is calibrated to 5, 10, and 2 for the deficit-to-GDP ratio, the change in gross debt, and the debt-to-GDP ratio, respectively. Note that our results are robust to other calibrations of the \(\gamma \) parameter, see Sect. 4.5.

  21. 21.

    More concretely, the weights are 0.38, 0.23, 0.36, 0.43, 0.41, 0.19, 0.37, and 0.36 for GDP growth, the output gap, the change in the unemployment rate, the deficit-to-GDP ratio, the change in gross debt, the debt-to-GDP ratio, the aggregate default rate, and the flow of private credit, respectively. Note also that the sign of some indicators is modified accordingly so that low values in absolute terms are associated with “crisis” periods.

  22. 22.

    Note also that, in Fig. 13, we calibrate \(\gamma =5\) as we did for most of the individual \(z_t\) indicators in previous sections. In any case, the weights resulting from other values are very similar and also match the shaded regions.

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Correspondence to Enrique Moral-Benito.

Additional information

Special thanks are due to Francisco De Castro and Javier Perez for sharing their fiscal data, and Javier Ferri for fruitful discussion. We also thank Pablo Burriel, Jorge Martínez Pagés, Eva Ortega, Gaby Pérez Quirós, and Alberto Urtasun for helpful comments. We are also grateful to the Editor and two anonymous referees for insightful suggestions that led to a substantial improvement in the paper.

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Hernández de Cos, P., Moral-Benito, E. Fiscal multipliers in turbulent times: the case of Spain. Empir Econ 50, 1589–1625 (2016). https://doi.org/10.1007/s00181-015-0969-0

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Keywords

  • Fiscal policy
  • Fiscal multiplier
  • Spain

JEL Classification

  • E62
  • H30