Abstract
According to the Easterlin Paradox, richer people are happier than poorer people, but when a country becomes richer over time, its people do not become happier. There is debate on whether this paradox holds. To shed light on this controversy, we distinguish between five different versions of the paradox. They apply to either groups of countries or individual countries, and to either the long or the medium term. We argue that the long term is most appropriate for testing the paradox, and that tests of the paradox should control for an autonomous time trend. We conduct such tests by estimating country-panel equations for mean life satisfaction in 27 European countries that include trend and cyclical components of per capita GDP as regressors. Concerning groups of countries, we find a robust confirmation of the long- and medium-term versions of the paradox for a group of nine Western and Northern European countries. Moreover, we obtain a non-robust rejection of the medium-term variant of the paradox for a set of 11 Eastern European countries. Regarding individual countries, the medium-term variant of the paradox holds for the nine Western and Northern European countries, but is rejected for Greece, Ireland, Italy, Spain, Bulgaria, Lithuania, and Poland.
This is an abridged version of a longer working paper with the same title (see Kaiser and Vendrik 2018)
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Notes
- 1.
See Easterlin’s (2017 Sect. 2) distinction between short-term fluctuations and long-term trends in GDPpc.
- 2.
Layard et al. (2010) adopt a value of 9.5 for λ, but mention in their note of Table 6.5 that setting λ = 6.25 produces similar results.
- 3.
Hamilton (2017) criticizes the HP filter for introducing spurious dynamic relations in the cyclical component that have no basis in the underlying data-generating process. However, for our purposes of regressing SWB on primarily an appropriate GDPpc trend measure, the HP filter seems more suitable than the alternative filter that is presented by Hamilton (2017). Moreover, this alternative filter generates similar results. See Kaiser and Vendrik (2018) for further discussion of this.
- 4.
We do not follow Easterlin (2017, p. 312) in extending the formulation of variant EPi0 to also include the variation of happiness with income across countries. This is because EPi0 only concerns the variation of happiness with income within countries. The same holds for the individual-country variants EPil and EPim.
- 5.
Beja (2014) and Opfinger (2016) also test for the Easterlin Paradox, but in our view the dynamic model of Beja is mis-specified (missing levels of lnGDPpc), and Opfinger only uses the last two waves of the WVS, which implies an estimation period of 5–7 years that is much too short to test the Easterlin Paradox in a reliable way. Furthermore, there is no control for cyclical fluctuations in GDPpc.
- 6.
When using an HP filter with λ = ∞ for an estimation period of much less than 20 years (see Sect. 2.1), the following applies to the medium-term version EPgm.
- 7.
Because our regressors are likely not strictly exogenous, eliminating the serial correlation by a Prais-Winston or Cochrane-Orcutt transformation of the error term would not lead to consistent and efficient standard errors of the parameter estimates (Wooldridge 2003, Sects. 12.3 and 12.5).
- 8.
We here use the term “effect” rather than “correlation” because a dynamic model like Eq. 2.2 usually presupposes causality from the right-hand-side variables to the left-hand-side variable of the equation. Although testing of the Easterlin Paradox only involves correlations, dynamic-model concepts like short and long-run effects are more generally applicable to correlations as well.
- 9.
In that analysis adaptation of individual life satisfaction to income changes is modelled. In the simplified dynamics in the present paper such adaptation is implicitly and partially incorporated in the contemporaneous effects of the trend and cyclical lnGDPpc variables. See, however, the end of the next section for an extension that explicitly models adaptation of life satisfaction to medium-term changes in lnGDPpc.
- 10.
The number of years τ within which convergence for 90% takes place can be calculated as
= 1–0.9 = 0.1 or τ ln φ = ln0.1 or τ = ln0.1/lnφ. For estimates of φ between 0.1 and 0.8 this yields 1.0 < τ < 10.3 (cf. Vendrik, 2013). - 11.
See Kaiser and Vendrik (2018) for our similar approach to testing EPi0.
- 12.
This expression follows from noting that in the long-run equilibrium current and past values of all variables are equal to each other.
- 13.
This extreme growth was largely driven by an accounting trick of a number of multinational companies (Inman, 2016). Therefore, this change in GDPpc is unlikely to have had an impact on living standards. The World Bank data set records a growth of only 7%.
- 14.
Mean T is 35 for the Western European countries and 13 for the Eastern European countries.
- 15.
Here we use “EB-Standard” data.
- 16.
In Kaiser and Vendrik (2018) we extensively discuss the results of our tests when setting λ = 6.25 which more closely corresponds to tests of EPgm. These results are very similar to those for λ = ∞, the main difference being slightly more reliably significant coefficients for sets of Eastern European countries.
- 17.
In this study we call an estimate (strongly) significant when its p-value in a two-tailed t test is below 0.05 (0.01), and marginally significant when its p value in a two- or one-tailed t test is higher than 0.05, but lower than 0.10. In the latter case we mention the p value in parentheses, which refers to a two-tailed t test unless it is explicitly stated that it refers to a one-tailed t test.
- 18.
The coefficient of cyclical lnGDPpc is insignificant for this group of countries as well, so even cyclical fluctuations in GDPpc were not associated with changes in average life satisfaction in these countries.
- 19.
Given this extremely low number of effective observations, we also run a robustness regression of Eq. 2.1 for this group of countries without cyclical lnGDPpc. This yields a coefficient of 1.66 with a standard error of 1.11 (p = 0.23), which is close to marginally significant in a one-tailed t test.
- 20.
The second-order serial correlation is significant for most groups, but relatively small (at most 0.16). We do not explicitly correct for that in the following.
- 21.
- 22.
In Eq. 2.2 such omitted variables work via changes in the error term which in the next year are reinforced via the lagged life satisfaction term. This reinforcement also picks up the effects of positive serial correlation in time-varying omitted variables. See Vendrik (2013) for a deeper dynamic analysis.
- 23.
For example, economic reforms in a country and globalization may lead to both higher long-term economic growth and lower inflation.
- 24.
When using an HP filter with λ = 6.25 we obtain somewhat larger and slightly more significant estimates for this group of countries. Our rejection of EPgm is nevertheless non-robust in this case, too. See Kaiser and Vendrik (2018) for an extended discussion.
- 25.
In Kaiser and Vendrik (2018) we also present tests of EPi0 (non-positive long-term time trend in happiness) for Western European countries (plus East Germany). There we show that EPi0 is robustly confirmed for Austria, Belgium, Greece, the Netherlands, Portugal, and West Germany, but robustly violated for Denmark, Finland, France, Great Britain, Italy, and Sweden. For the other countries the results are not robust. In the case of the Eastern European countries the limited observation period does not allow for reliable tests of a long-term non-positive time trend in happiness. Among these countries, we obtain (marginally) significant and positive medium-term time trends for Bulgaria, Hungary, Lithuania, Latvia, Poland, and Romania.
- 26.
These regressions include only two significant dummies for the preceding questions. The first dummy controls for a question on which political party the respondent supports (1979 and 1983 waves). The second dummy concerns a question on the share of friends appreciating talk about politics (1998 wave). These dummies have long-run effects averaged across countries of −0.06 and − 0.07, respectively.
- 27.
We include East Germany here because East Germany has an estimation period that is much closer to the Western European country group. See Kaiser and Vendrik (2018) for more explanation.
- 28.
See Kaiser and Vendrik (2018) for a more extensive discussion of these robustness results.
- 29.
Note that this limitation also holds for other international data sets for life satisfaction and happiness. Examples are the World Values Survey (up to six observations) and the Gallup World Poll (13 observations for 2005–2017).
= 1–0.9 = 0.1 or τ ln φ = ln0.1 or τ = ln0.1/lnφ. For estimates of φ between 0.1 and 0.8 this yields 1.0 < τ < 10.3 (cf. Vendrik, References
Angeles, L. (2011). A closer look at the Easterlin Paradox. The Journal of Socio-Economics, 40, 67–73.
Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton: Princeton University Press.
Bartolini, S., & Sarracino, F. (2014). Happy for how long? How social capital and economic growth relate to happiness over time. Ecological Economics, 108(Suppl. C), 242–256.
Bartolini, S., Bilancini, E., & Pugno, M. (2013a). Did the decline in social connections depress Americans’ happiness? Social Indicators Research, 110, 1033–1059.
Bartolini, S., Bilancini, E., & Sarracino, F. (2013b). Predicting the trend of well-being in Germany: How much do comparisons, adaptation and sociability matter? Social Indicators Research, 114(2), 169–191.
Beja, E. L. (2014). Income growth and happiness: reassessment of the Easterlin Paradox. International Review of Economics, 61(4), 329–346.
Bruno, G. S. (2005a). Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models. Economics Letters, 87(3), 361–366.
Bruno, G. S. F. (2005b). XTLSDVC: Stata module to estimate bias corrected LSDV dynamic panel data models, Statistical Software Components S450101, revised 08 Sep. 2005. Boston: Boston College Department of Economics.
Bundesagentur für Arbeit. (2017). Arbeitslose und Unterbeschäftigung. Retrieved November 10, 2017, from https://statistik.arbeitsagentur.de/nn_217700/Statischer-Content/Rubriken/Arbeitslose-und-gemeldetes-Stellenangebot/Arbeitslose/Arbeitslosigkeit-in-Deutschland-seit-1950-Monats-Jahreszahlen.html
Burns, A. F., & Mitchell, W. C. (1946). Measuring business cycles. New York: National Bureau of Economic Research.
Cameron, A. C., & Miller, D. L. (2015). A practitioner’s guide to cluster-robust inference. The Journal of Human Resources, 50(2), 317–372.
Clark, A. E. (2011). Income and happiness: Getting the debate straight. Applied Research in Quality of Life, 6, 253–263.
Clark, A. E., Flèche, S., & Senik, C. (2014). The great happiness moderation. In A. E. Clark & C. Senik (Eds.), Happiness and economic growth: Lessons from developing countries (pp. 32–139). Oxford: Oxford University Press.
Deaton, A. (2008). Income, health, and well-being around the world: Evidence from the Gallup World Poll. Journal of Economic Perspectives, 22(2), 53–72.
Destatis. (2017a). Bruttoinlandsprodukt, Bruttowertschöpfung in den Ländern. Retrieved July 2, 2017, from https://www.destatis.de/DE/Publikationen/Thematisch/VolkswirtschaftlicheGesamtrechnungen/VGRderLaender/VGR_LaenderergebnisseBand1.html
Destatis. (2017b). Publikation – Preise – Verbraucherpreisindex für Deutschland – Lange Reihen ab 1948. Retrieved November 10, 2017, from https://www.destatis.de/DE/Publikationen/Thematisch/Preise/Verbraucherpreise/VerbraucherpreisindexLangeReihen.html
Diener, E., Inglehart, R., & Tay, L. (2013a). Theory and validity of life satisfaction scales. Social Indicators Research, 112(3), 497–527.
Diener, E., Tay, L., & Oishi, S. (2013b). Rising income and the subjective well-being of nations. Journal of Personality and Social Psychology, 104(2), 267–276.
Easterlin, R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. Nations and Households in Economic Growth, 89, 89–125.
Easterlin, R. A. (1995). Will raising the incomes of all increase the happiness of all? Journal of Economic Behavior & Organization, 27(1), 35–47.
Easterlin, R. A. (2005). Feeding the illusion of growth and happiness: A reply to Hagerty and Veenhoven. Social Indicators Research, 74(3), 429–443.
Easterlin, R. A. (2009). Lost in transition: Life satisfaction on the road to capitalism. Journal of Economic Behavior & Organization, 71(2), 130–145.
Easterlin, R. A. (2015). Happiness and economic growth: The evidence. In W. Glatzer, L. Camfield, V. Møller, & M. Rojas (Eds.), Global handbook of quality of life (pp. 283–299). International Handbooks of Quality-of-Life. Dordrecht: Springer.
Easterlin, R. A. (2017). Paradox lost? Review of Behavioral Economics, 4(4), 311–339.
Easterlin, R. A., & Sawangfa, O. (2010). Happiness and economic growth: Does the cross section predict time trends? Evidence from developing countries. In E. Diener & D. Kahneman (Eds.), International differences in well-being (pp. 166–216).
Easterlin, R. A., McVey, L. A., Switek, M., Sawangfa, O., & Zweig, J. S. (2010). The happiness-income paradox revisited. Proceedings of the National Academy of Sciences, 107(52), 22463–22468.
Feenstra, R. C., Inklaar, R., & Timmer, M. P. (2015). The next generation of the Penn World Table. The American Economic Review, 105(10), 3150–3182.
Gruen, C., & Klasen, S. (2013). Income, inequality, and subjective well-being: an international and intertemporal perspective using panel data. Jahrbuch Für Wirtschaftsgeschichte / Economic History Yearbook, 54(1), 15–35.
Hamilton, J. D. (2017). Why you should never use the Hodrick-Prescott filter. Review of Economics and Statistics, Just accepted MS, available online, https://doi.org/10.1162/REST_a_00706, 1–25.
Heske, G. (2009). Volkswirtschaftliche Gesamtrechnung DDR 1950-1989. Daten, Methoden, Vergleiche. Historical Social Research/Historische Sozialforschung, Supplement, 21, 1–356.
Hodrick, R. J., & Prescott, E. C. (1997). Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1), 1–16.
IMF. (2016). World economic outlook database. Retrieved July 2, 2017, from http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx
Inman, P. (2016, July 12). Irish economy surges 26% as revised figures take in foreign investment. The Guardian, Business. Retrieved June 29, 2017, from https://www.theguardian.com/business/2016/jul/12/irish-economic-growth-revised-figures-foreign-investment-aircraft
Kaiser, C. W., & Vendrik, M. C. M. (2018). Different versions of the Easterlin Paradox: New evidence for European countries. IZA DP No. 11994. Bonn: IZA.
Layard, R., Mayraz, G., & Nickell, S. J. (2010). Does relative income matter? Are the critics right? In E. Diener, J. Helliwell, & D. Kahneman (Eds.), International differences in wellbeing (pp. 139–165). Oxford: Oxford University Press.
OECD. (2017). Level of GDP per capita and productivity. Retrieved July 2, 2017, from https://stats.oecd.org/Index.aspx?DataSetCode=PDB_LV#
Opfinger, M. (2016). The Easterlin paradox worldwide. Applied Economics Letters, 23(2), 85–88.
Proto, E., & Rustichini, A. (2013). A reassessment of the relationship between GDP and life satisfaction. PLoS One, 8(11), 1–10.
Ravn, M. O., & Uhlig, H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. The Review of Economics and Statistics, 84(2), 371–376.
Sacks, D. W., Stevenson, B., & Wolfers, J. (2012). Subjective well-being, income, economic development and growth. In P. Booth (Ed.), The pursuit of happiness: Well-being and the role of government (pp. 59–97). London: The Institute of Economic Affairs.
Sacks, D. W., Stevenson, B., & Wolfers, J. (2013). Growth in income and subjective well-being over time. Mimeo.
Stevenson, B., & Wolfers, J. (2008). Economic growth and subjective well-being: Reassessing the Easterlin Paradox. Brooking Papers on Economic Activity, 2008(1), 1–87.
UNCTAD. (2017). Gross domestic product: Total and per capita, current and constant (2005) prices, annual, 1970–2015. Retrieved July 2, 2017, from http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=96
Veenhoven, R. (2011). Trend average happiness in nations 1946–2010: How much people like the life they live. Trend Report Average Happiness. World Database of Happiness, Happiness in Nations. Rotterdam: Erasmus University.
Veenhoven, R., & Hagerty, M. (2006). Rising happiness in nations 1946—2004: A reply to Easterlin. Social Indicators Research, 79(3), 421–436.
Veenhoven, R., & Vergunst, F. (2014). The Easterlin illusion: economic growth does go with greater happiness. International Journal of Happiness and Development, 1(4), 311–343.
Vendrik, M. C. M. (2013). Adaptation, anticipation and social interaction in happiness: An integrated error-correction approach. Journal of Public Economics, 105, 131–149.
Wooldridge, J. M. (2003). Introductory econometrics; A modern approach (2nd ed.). Mason: South-Western Thomson Learning.
World Bank. (2017). World Development Indicators. Retrieved July 2, 2017, from http://databank.worldbank.org/data/reports.aspx?source=2
Acknowledgements
We thank Erik de Regt for econometric advice, Marta Golin for advice on using Stata, Guy Mayraz and Ruut Veenhoven for sending us their data sets, Daniel Sacks and Justin Wolfers for information about their research, and John Barkley Rosser Jr., Robert Dur, Richard Easterlin, Ari Kapteyn, Maurizio Pugno, Mariano Rojas, Francesco Sarracino, and other participants of the International Conference on Policies for Happiness and Health in Siena, March 19–21, 2018, and the USC Happiness Conference at the occasion of the retirement of Richard Easterlin in Los Angeles, April 6, 2018, for helpful comments.
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Kaiser, C.F., Vendrik, M.C.M. (2019). Different Versions of the Easterlin Paradox: New Evidence for European Countries. In: Rojas, M. (eds) The Economics of Happiness. Springer, Cham. https://doi.org/10.1007/978-3-030-15835-4_2
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