For further analysis, these answers are coded from 4 to 1. Data taken from the WVS covered the years , , , , and Where on this ladder do you feel you personally stand at the present time? The data taken from the Gallup World Poll covered the period of — and thus spanned one decade. All things considered, how satisfied are you with your life as - a - whole now? Suppose the top of the ladder represents the best possible life for you and the bottom of the ladder the worst possible life.
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All things considered, how satisfied or dissatisfied are you with your life as - a - whole these days? Tell me how much you are satisfied or dissatisfied with your life as a whole? For the micro-level data, data were obtained from the Korean Labour and Income Panel Study KLIPS ; the data from wave 12 up to wave 17 were used because the earlier waves only surveyed urban households and are therefore not representative of the general population of South Korea.
Most studies used an ascending order for increased satisfaction, so the answer possibilities were reversed with very satisfied 5 and very dissatisfied 1. The question whether economic growth is associated with average happiness increases in South Korea was answered using a macro - level trend analysis. The question as to whether comparisons with the income of compatriots have neutralized the effects of income growth on happiness is answered in a micro - level change analysis.
Since the number of observations for all measures of happiness was rather low, outliers may have a strong influence on the results. Therefore, an additional analysis was performed to address this issue. As mentioned in Sect. In line with Stevenson and Wolfers , we tested the Easterlin Paradox using a long difference approach. According to Easterlin, in the long term there should be no systematic difference in the average happiness in a country due to a difference in real GDP per capita.
Regressing real GDP per capita on the first and last result of the different happiness measures enabled us to test this for South Korea. All the measures we used had different beginning and end years covering changes in the business cycle. Since all the measures were obtained using different questions to measure happiness with different scales of answer possibilities, we first standardized the answers to make them comparable.
Standardization of responses to answer scales of different lengths is accepted, only if the mean and standard deviation of the original data is also available.
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This is common practise when changing the length of Likert scales Colman et al. As noted, different wordings were used for all the surveys; however, it was determined that for this study all measures of happiness and life satisfaction fell within the definition of happiness used by Veenhoven Standardization is not an optimal procedure, but this approach was preferred for comparability of measures and to take advantage of the different data available. Two variables were added to Eq. Lagged household income controls for previous income and thus for changes in household income.
At the macro-level, we observed a clear correlation between economic growth and average happiness in South Korea between and At the micro-level, we observed that South Koreans whose incomes grew became happier and this gain in happiness was not neutralized by adaptation or social comparison. The macro-level analysis showed that economic growth mostly went hand in hand with a rise in average happiness in South Korea. This pattern of rising happiness appeared most clearly in the WVS data which cover the period — The GWP data showed a slightly different pattern with more fluctuations, but also showed a clear increase in happiness when looking at the total effect between and See the time graphs in Figs.
Robust standard errors are given in parentheses. Macro-relationship between happiness and economic growth in South Korea, long differences. Standard errors are given in parentheses. Economic growth measured by real GDP per capita. A limitation of this macro-approach focusing on only one individual country is that the positive trend in happiness and life satisfaction may be driven by other factors and the positive association between income and subjective well-being is spurious.
Although the original paradox only referred to the lack of a positive correlation and was not concerned with endogeneity problems, omitted variable bias poses a serious problem here see Kaiser and Vendrik Adding additional control variables would be an option here, but given the small number of observations this can only be done to a limited extent.
In addition, some control variables may mediate the effect of GDP per capita on happiness and should therefore not be included in the model. A country-panel approach Layard et al. On the micro-level, the results are more pronounced: both life satisfaction and household income increased in South Korea over the period — except for See Fig.
Dependent variable: life satisfaction. Estimates of the effects of life satisfaction on current household income: fixed effects estimation.
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Dependent variable: log of current household income. Controls included: age, age squared, employment status, health status, relationship status and education level. This effect is only significant positive for this specification of the reference group. Other definitions of the reference group do not result in significant results of the reference group income on happiness in South Korea.
However, the effect of reference household income never becomes negative and statistically significant. Hence, there is limited evidence for social comparison effects in South Korea; instead rising incomes might give people hope for a better future. Fixed effects models tackle omitted variable bias by controlling for individual characteristics that remain relatively stably over time, such as personality traits. However, a potential problem still might be that an individual whose life satisfaction has increased recently is more likely to experience an increase in income since more satisfied individuals are generally more productive De Neve and Oswald ; Oswald et al.
If there is a problem of reverse causality, we would expect that a higher level of life satisfaction makes a higher income later on more likely. Using different lags for life satisfaction see also Chen and Van Ours and estimating our models with and without control variables, we do not find that a positive shock to life satisfaction is associated with an increase in income a year later.
Also given that none of the effects are large, we conclude that reverse causality from life satisfaction to income is not a large problem. Controls included: age, age squared, employment status, health status and education level. Controls included: age, age squared, employment status, marital status, health status and education level.
Controls included: age, age squared, employment status, marital status and health status. This first finding should be interpreted with care since there was only a small number of separated individuals in the whole sample. A few outliers might influence the effect heavily. Furthermore, there was only some evidence for a social comparison effects for married individuals and some evidence for an adaptation effect for singles.
We found that the Easterlin Paradox did not apply in South Korea. Why has Easterlin concluded otherwise? What more can we learn about the effect of economic growth on happiness?
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This study showed that the Easterlin Paradox did not apply in South Korea between and On the macro - level , we found a positive relationship between economic growth and average happiness: 2 out of 3 measures of happiness provided significant results and the long difference approach clearly showed a highly positive significant relation between economic growth on average happiness.
The latter result was most reliable because it included different measures of happiness across different time periods. This result held across different specifications and subgroups of the population in South Korea. So, using our data taken from various sources reported in the World Database of Happiness, the relative income theory did not apply in the case of South Korea. Our results on the macro-level relationship contradict the claim made by Easterlin et al. Easterlin et al. We found a positive relationship between economic growth and average happiness in South Korea, which was statistical significant.
So the difference is in the data, better data telling another story. On the basis of this same finding, Easterlin et al. We have argued that using slightly different indicators and analyses gives a significant correlation. How meaningful is statistical significance anyway in this discussion? Can we not just use effect sizes? The five observations of life satisfaction in the years , , , and can hardly be considered as an a-select sample from that population, and the sample of only 5 cases is clearly too small to demonstrate significance of a small correlation.
In short, this technique of significance testing is not well applicable in this case. The unacknowledged limitations of significance testing have also clouded our view on cross-national tests of the Easterlin Paradox. As we will discuss in more detail below, effects of economic growth on happiness are likely to vary across contexts and looking for a general tendency is therefore fruitless.
The question is not whether or not economic growth boosts happiness, but what are the conditions in which it boosts happiness in which conditions it does not. A first task for future research is to overcome our present data limitations, in particular to use longer time-series, both at the macro-level and the micro-level. A second task is to explore causality in the relation between economic growth and happiness, a third task is to explore the conditions in which the balance of effects tends to be positive, neutral or negative and a fourth task is to identify the causal mechanisms.
For our macro-level analysis, only a handful of observations was available per measure of happiness. More observations are necessary to draw more reliable conclusions. Future studies should incorporate different measures of happiness to increase reliability of the results.
Did the Easterlin Paradox apply in South Korea between and ? A case study | SpringerLink
This study should be repeated when a number of years have past to test whether the results we found still hold. Additional over-time data on the macro- and micro-levels are required because, as Easterlin argues, the Easterlin Paradox is about the long-term trend relationship between economic growth and average happiness, and the focus is not on the short-term relationship.
Economic growth in a country can affect the happiness of individuals in various ways, and the balance of effects is likely to differ across contexts. There is little point in searching for an average net effect, what we want to know is in what conditions economic growth adds to happiness and in what conditions does it not. Future research should therefore focus on separate country studies or look for contextual variation in world samples.
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We also want to know why effects of economic growth on happiness differ across times and places. In this paper, we checked one particular causal mechanism social comparison in one particular situation South Korea — Future research should consider more of the mechanisms advanced in the literature on the Easterlin Paradox, such as a negative effect of economic growth on social capital in nations, which offsets the gain in happiness produced by economic growth e.
Bartolini et al Rather than demonstrating such effects in particular situations, this research should focus on differences across time and places. Economic growth has added to happiness in South Korea since the s. This illustrates that the Easterlin Paradox is not a general law, but rather a contextual phenomenon. Skip to main content Skip to sections. Advertisement Hide. Download PDF.
International Review of Economics pp 1—27 Cite as. Did the Easterlin Paradox apply in South Korea between and ? A case study.