Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 2 https://isni.org/isni/0000000404811396, International Monetary Fund

References

  • Agnello, L., & Sousa, R. M. (2014). “How Does Fiscal Consolidation Impact on Income Inequality?”. Review of Income and Wealth, 60 (4), 702726.

    • Search Google Scholar
    • Export Citation
  • Alesina, A., & Ardagna, S. (2010). “Large changes in fiscal policy: taxes versus spending”. Tax policy and the economy, 24(1), edited by Jeffrey R. Brown. National Bureau of Economic Research, 3568.

    • Search Google Scholar
    • Export Citation
  • Alesina, A., Barbiero, O., Favero, C., Giavazzi, F., & Paradisi, M. (2017). “The effects of fiscal consolidations: Theory and evidence” (No. w23385). National Bureau of Economic Research.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alesina, A., & Perotti, R. (1997). “Fiscal adjustments in OECD countries: composition and macroe-conomic effects”. IMF Staff Papers, 44 (2), 210248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alesina, A., Ardagna, S., Perotti, R., & Schiantarelli, F. (2002). “Fiscal policy, profits, and investment”. American Economic Review, 92 (3), 571589.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ball, L. M., Furceri, D., Leigh, M. D., & Loungani, M. P. (2013). “The distributional effects of fiscal consolidation”. International Monetary Fund Working Paper, (WP/13/151).

    • Search Google Scholar
    • Export Citation
  • Bjørnskov, C., Dreher, A., & Fischer, J. A. (2007). The bigger the better? Evidence of the effect of government size on life satisfaction around the world. Public Choice, 130(3–4), 267292.

    • Search Google Scholar
    • Export Citation
  • Burkhauser, R. V., De Neve, J. E., & Powdthavee, N. (2016). “Top incomes and human well-being around the world”.(No. 66411). London School of Economics and Political Science, LSE Library

    • Search Google Scholar
    • Export Citation
  • Cameron, A.C. & Miller, D.L. (2010). “Robust inference with clustered data”. Handbook of empirical economics and finance, 106, pp.128.

    • Search Google Scholar
    • Export Citation
  • Davidson, R., & J. G. MacKinnon. 2010. “Wild bootstrap tests for IV regression”. Journal of Business & Economic Statistics 28, 128144.

  • Chinn, M. D., & Ito, H. (2006). “What matters for financial development? Capital controls, institutions, and interactions”. Journal of Development Economics, 81 (1), 163192.

    • Search Google Scholar
    • Export Citation
  • Ciminelli, G., Ernst, E., Merola, R., & Giuliodori, M. (2018). “The composition effects of tax-based consolidation on income inequality”. European Journal of Political Economy.

    • Search Google Scholar
    • Export Citation
  • Clark, A. E., & Oswald, A. J. (1994). “Unhappiness and unemployment”. The Economic Journal, 104 (424), 648659.

  • Cloyne, J. (2013). “Discretionary tax changes and the macroeconomy: new narrative evidence from the United Kingdom”. The American Economic Review, 103 (4), 15071528.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deaton, A. (2012). “The financial crisis and the well-being of Americans 2011 OEP Hicks Lecture”. Oxford Economic Papers, 64 (1), 126.

  • De Neve, J. E., Ward, G., De Keulenaer, F., Van Landeghem, B., Kavetsos, G., & Norton, M. I. (2018). “The asymmetric experience of positive and negative economic growth: Global evidence using subjective well-being data”. Review of Economics and Statistics, 100 (2), 362375.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Devries, P., Guajardo, J., Leigh, D., & Pescatori, A. (2011). “A new action-based dataset of fiscal consolidation”. International Monetary Fund Working Paper, (WP/11/128).

    • Search Google Scholar
    • Export Citation
  • Di Tella, R., & MacCulloch, R. (2006) “Some uses of happiness data in economics”. The Journal of Economic Perspectives, 20 (1), 2546.

  • Di Tella, R., MacCulloch, R. J., & Oswald, A. J. (2003). “The macroeconomics of happiness”. Review of Economics and Statistics, 85 (4), 809827.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ferrer-i-Carbonell, A. (2005). “Income and well-being: an empirical analysis of the comparison income effect”. Journal of Public Economics, 89 (5), 9971019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frey, B. S., & Stutzer, A. (2000). “Happiness, economy and institutions”. The Economic Journal, 110 (466), 918938.

  • Giavazzi, F., & Pagano, M. (1990). “Can severe fiscal contractions be expansionary? Tales of two small European countries”. NBER Macroeconomics Annual, 5, 75111.

    • Search Google Scholar
    • Export Citation
  • Guajardo, J., Leigh, D., & Pescatori, A. (2014). “Expansionary austerity? International evidence”. Journal of the European Economic Association, 12 (4), 949968.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jordà, Ò., & Taylor, A. M. (2016). “The time for austerity: estimating the average treatment effect of fiscal policy”. The Economic Journal, 126 (590), 219255.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kahneman, D., & Krueger, A. B. (2006). “Developments in the measurement of subjective well-being”. The Journal of Economic Perspectives, 20 (1), 324.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kezdi, G. (2003). “Robust standard error estimation in fixed-effects panel models”. Available at SSRN 596988.

  • Keefer, P. (2010). “Database on Political Institutions (DPI2010)”. Development Research Group, (Washington: The World Bank).

  • Kleven, H. J. (2014). “How can Scandinavians tax so much?”. The Journal of Economic Perspectives, 28 (4), 7798.

  • Kleven, H. J., & Schultz, E. A. (2014). “Estimating taxable income responses using Danish tax reforms”. American Economic Journal: Economic Policy, 6 (4), 271301.

    • Search Google Scholar
    • Export Citation
  • Layard, R. (2006). “Happiness and public policy: A challenge to the profession”. The Economic Journal, 116(510), C24C33.

  • Lucas, R. E. & Gohm, C. L. (2000). “Age and sex differences in subjective well-being across cultures”. Culture and subjective well-being, 3 (2), 91317.

    • Search Google Scholar
    • Export Citation
  • Mulas-Granados, C. (2005). “Fiscal adjustments and the short-term trade-off between economic growth and equality”. Hacienda Pública Española/Revista de Economia Pública, 172 (1), 6192.

    • Search Google Scholar
    • Export Citation
  • Nichols, A., & Schaffer, M. (2007). “Clustered errors in Stata.” In United Kingdom Stata Users’ Group Meeting.

  • Oishi, S., Schimmack, U., & Diener, E. (2012). “Progressive taxation and the subjective well-being of nations”. Psychological science, 23 (1), 8692.

    • Search Google Scholar
    • Export Citation
  • Oswald, A. J. (1997). “Happiness and economic performance”. The Economic Journal, 107 (445), 18151831.

  • Oswald, A. J., & Wu, S. (2010). “Objective confirmation of subjective measures of human well-being: Evidence from the USA”. Science, 327(5965), 576579.

    • Search Google Scholar
    • Export Citation
  • Ponticelli, J., & Voth, H. J. (2017). “Austerity and anarchy: Budget cuts and social unrest in Europe, 1919–2008”.

  • Ram, R. (2009). “Government spending and happiness of the population: additional evidence from large cross-country samples”. Public Choice, 138(3–4), 483490.

    • Search Google Scholar
    • Export Citation
  • Romer, C. D., & Romer, D. H. (2010). “The macroeconomic effects of tax changes: estimates based on a new measure of fiscal shocks”. The American Economic Review, 100 (3), 763801.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, B. (2015). “The resource curse exorcised: Evidence from a panel of countries”. Journal of Development Economics, 116, 5773.

  • Stevenson, B., & Wolfers, J. (2008). “Economic Growth and Subjective Well-Being: Reassessing the Easterlin Paradox”. Brookings Papers on Economic Activity, 187.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stiglitz, J., A. Sen & J. Fitoussi (2009), “Report by the Commission on the Measurement of Economic Performance and Social Progress, Commission on the Measurement of Economic Performance and Social Progress”, http://ec.europa.eu/eurostat/documents/118025/118123/Fitoussi+Commission+report (accessed on 02 February 2019).

    • Search Google Scholar
    • Export Citation
  • Wolfers, J. (2003). “Is Business Cycle Volatility Costly? Evidence from Surveys of Subjective Well-Being”. International Finance, 6 (1), 126.

    • Search Google Scholar
    • Export Citation

Appendix

Table A1

Summary statistics

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Table A2

The well-being consequences of fiscal policy shocks in Europe : Controlling for year effects

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Notes: The dependent variable is individual life satisfaction. All specifications include country fixed effects and country-specific trends. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A3

Baseline estimates (Ordered Probit)

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Notes: The dependent variable is individual life satisfaction. All specifications include country fixed effects and country-specific trends. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A4

Baseline estimates (Predicted life satisfaction)

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Notes: The dependent variable is the predicted value of life satisfaction derived from an ordered probit regression of life satisfaction on individual control variables with country fixed and year effects. All specifications include country fixed effects and country-specific trends. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A5

Additional controls estimates (Ordered Probit)

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Notes: The dependent variable is individual life satisfaction. All specifications include country fixed effects and country-specific trends. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A6

Heterogeneity effects (Ordered Probit)

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Notes: The dependent variable is individual life satisfaction. Exchange rate (LCU-USD) measures the units of local currency per USD. An increase in Exchange rate (LCU-USD) captures a depreciation. EMU is a dummy capturing the European Monetary Union starting in 1999. ALMP is Active Labor Market policy expenditures as % of GDP. All specifications include country fixed effects and country-specific trends. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A7

Dynamic effects of fiscal shocks: Event study approach

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Notes: The dependent variable is the country level average of individual life satisfaction. All specifications include country fixed effects, country-specific trends and all macroeconomic controls . The identification comes from omitting the 1–2 years before the event. An event is defined as the fiscal consolidation of the largest size over the period (largest tax hike or largest spending cut) within country over the period. The number of observation corresponds to a regression over 9 years period (4 years period before consolidation and 5 years period after). Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
Table A8

Description of variables.

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We thank the participants of the EUR department seminars (Andrea Schaechter, Borja Gracia, Cheikh Gueye, Iva Petrova, Karina Garcia and Philippe Wingender) for their comments and suggestions. We are grateful to Professor Martino Pelli for helpful comments. We also thank participants to the CIREQ PhD conference, the Canadian Economic Association conference, the ADED-DBA colloquium and the TEPP conference. The views expressed in this paper do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

1

Source: https://www.rt.com/news/austerity-protests-eu-solidarity-727/ More recently, in November 2018, a fuel tax increase has triggered the so-called yellow vest movement in France.

3

In this paper we use interchangeably the terms ‘individual well-being’ and ‘individual life satisfaction’. The literature also refers to this measure as a happiness measure. See for instance Frey and Stutzer (2000).

4

Note however that our findings are subject to caveats related to the use of a subjective indicator in general.

5

We also have suggestive evidence in this line as we find that country-years with high level of subjective well-being are negatively correlated with protests against the government. Given the aim of this paper, these results are not included but available upon request.

6

Note that negative values arise in the data when a temporary consolidation measure expires. For instance a one year increase in tax of $1 has a budgetary impact of $1 in the first year and -$1 in the next year followed by no impact (Devries et al., 2011; Guajardo et al., 2014).

7

This implies that for Finland, Sweden and Austria, data is available since 1995. While for Spain and Portugal, no observation is available until 1985. Eurobarometer is the only survey, to the best of our knowledge, to have annual data on subjective well-being over a long period.

8

We use the European weights in order to adjust each national sample in proportion to its share in the total population of the European Union. European weights include also the post-stratification sample weighting factors. See Eurobarometers for more detail. Further, we do not cluster our standard errors as we have only 13 countries in our sample. Using cluster-robust standard errors for small number of clusters may lead to a worst statistical inference (see for instance Nichols and Schaffer, 2007 and, Cameron and Miller, 2010). Indeed, the cluster-robust standard errors converge to the true standard error when the number of clusters tends to infinity. It has been shown that more than 50 clusters are reasonable to use cluster-robust inference (Nichols and Schaffer, 2007 and, Kezdi, 2004). Further, as we use country-specific trends that allows to take care of serial correlation in the error term, our standard errors should be less affected by autocorrelation. Finally, our results are robust to using the wild cluster bootstrap developed for the case of small number clusters (Davidson and Mackinnon, 2010) but this routine does not allow the use of weighted OLS.

9

Table A2 in the Appendix shows results of the baseline while controlling for common shocks. Table A3 shows the results using a weighted Ordered Probit to account for the nature of the data on subjective well-being. In Table A4 also in the Appendix, we present weighted OLS estimates using predicted values of life satisfaction. Overall these tables show that our results are robust both to using an alternative estimator and to the rescaling of the dependent variable.

10

See Table A3 in the Appendix for the results using weighted Ordered Probit.

11

We also test for the effect of the level of debt following Sutherland (1997) but we do not find any statistically significant effect. We do not include this result as we are primarily interested in policy tools that can help mitigate the well-being cost of fiscal consolidations. This result is however available upon request.

12

Giavazzi and Pagano (1990) highlight the role of exchange rate policies that accompanied the fiscal consolidations. Both countries, by pegging their exchange rate to a low inflation currency (the German mark), have induced a sharp reduction in nominal and real interest rates. This effect stems from the fact that the credibility of the fixed exchange rate regime led domestic nominal interest rates to move toward the lower level of foreign nominal rates. In addition, the convergence of nominal rates occurred faster than the convergence of inflation because price rigidity prevented the goods market from adjusting at the same speed as the financial markets. Also, the response of foreign interest rates was accelerated by the removal of capital controls. It follows that real interest rates fell along with nominal rates. Finally in both cases, these consolidations were led by conservative parties.

13

Table A3 in the Appendix shows similar results using a weighted Ordered Probit estimator.

14

Our approach is similar to Smith (2015).

15

See Alesina et al (2017) for more detail on the fiscal components.

16

We have also investigated the heterogeneous effect of announced fiscal consolidations versus unexpected ones on subjective well-being taking advantage of the dataset developed by Alesina et al (2017). Unexpected fiscal consolidations are those announced and implemented at the same time while the announced ones are those with a delay between the announcement and the implementation. First, we find that announced fiscal consolidations have a larger negative effect on individual subjective well-being than unexpected ones. Second, looking at the composition of fiscal consolidations, tax hikes have a large negative effect on subjective well-being when they were announced while unexpected spending cuts are those with a large negative effect. This finding is interesting and may reflect the (income) loss aversion related to tax hikes while in the context of spending cuts it may reflect the unexpected loss in public services that are valued by individuals.

17

Financial Times, Survey on Ireland, September, 24, 1987; quoted by Giavazzi and Pagano (1990).

18

We take the following information from the deficit-driven fiscal consolidation database (Devries et al., 2011): In Ireland, the fiscal consolidations of 1987 and 1988 are based on spending cuts of the sizes of 1.12% and 1.95% of GDP respectively. In Denmark, the fiscal consolidations of 1983, 1984 and 1985 are based on spending cuts of the sizes of 1.85%, 1.71% and 0.77% of GDP respectively. In addition, the other fiscal consolidations recorded in the database are based on tax hikes.

19

Note also that the average well-being recovered as the size of fiscal consolidation decreases in Denmark. In addition, while there was also a tax component, the expenditure component was dominant which makes the previous literature focused on the latter. See also our discussion on the low elasticity of taxable income in Denmark.

20

Note that in the Irish case, based on data from Alesina et al. (2017), fiscal consolidations were based mainly on public consumption and public investment cuts).

21

Over the period 1980–2007, the average tax revenues were respectively 45% of GDP and 31.7% of GDP in Denmark and Ireland. The average in OECD countries over the period is 32.6% of GDP. Source: OECD Stat (Data accessed on 23rd November 2018).

22

While the results may bear more historical contribution as the two countries may have changed significantly since the 1980s, they suggest that the effect of fiscal consolidation on subjective wellbeing is complex.

The (Subjective) Well-Being Cost of Fiscal Policy Shocks
Author: Kodjovi M. Eklou and Mamour Fall