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Does Government Make People Happy?: Exploring New Research Directions for Government’s Roles in Happiness

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Our study aims to explore new directions for researches on government’s role in enhancing quality of life (QOL). Although government can influence, to the greatest extent, people’s happiness, very few studies have systemically examined the quantitative or qualitative attributes of government in happiness enhancement, compared with the large volume of studies on economic, political, and cultural factors’ impact on QOL. Related to government’s role in happiness, we suggest ‘nine new research directions,’ all of which can generally be related with its’ quantitative and qualitative attributes. Even though much existing researches have focused on a part of quantitative sides of government, there are still many remaining attributes to be highlighted. Moreover, we expect that new, composite and nonlinear quality attributes of government will provide bountiful research topics in the future. Also, cross-boundary comparisons and mixtures between quality and quantity, as well as the conditional macro-context for government’s role, suggest new ideas for QOL studies.

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  1. Scully (2001) defined general government consumption as the public spending that directly absorbs resources and used a percent of national output in the World Development Report 1997 to derive it. Then, he multiplied it by the PPP estimate of GNP per capita to get government consumption expenditure per capita, G, which ranges from $44.8 to $5307.5 (Scully, 2001, p. 129). He obtained the PPP estimate of the GNP per capita in 1995 from 112 countries. To index, he divided G by $5307.5, the highest value of government consumption expenditure per capita and multiplied by 100, i.e. IG = (G/5307.5)*100. He put the highest G as 100. His measure of indexing G as well as the other variables is to unify it as a single metric unit.

  2. An interesting thing to note is the maximal level derived from Gompertz equation. The marginal benefit (MB) curve of government expenditure per capita from Gompertz equation shows v-shaped and reveals no interior solution. But it converges to zero at 78.86 (or $8178.58). The MB curve from logistic equation shows a very similar pattern to that from Gompertz equation and did not report here. However, it can be provided from the authors upon request.

  3. Albeit we used the similar methodology to derive the index of government size (IGS) from Scully (2001), the output is different from him. Such results reflect differences between Scully (2001) and our data. We used Government size (GS), which is a percent of Government Consumption Share of PPP Converted GDP Per Capita at current prices in Penn World Table (vs. General government consumption as a percent of national output in the world development out in the World Development Report 1992 in Scully 2001). To derive per capita government expenditure, we used the PPP Converted GDP Per Capita, G-K method, at current prices in Penn World Table from 2000 to 2008 among 190 countries (vs. the PPP estimate of GNP per capita in Scully 2001). Next, we multiplied government size by the GDP per capita and obtained government size per capita (GS) whose range is $11.926–$10371.01. To make IGS, we divide GS by $10371.01, the highest government size per capita, and then multiplied it by 100. IGS is an index and represents relative government expenditure per capita from 1 to 100 scale. Scully (2001) used 112 country samples but we used 138 ones.

  4. In case of replacing three qualitative variables of government in Table 7, next variables are statistically significant; Confidence in government (β = 1.087, P value = 0.005, NV: Name of Variables = wvs_e069_11), satisfaction with the people in national office (β = 1.075, P value = 0.010, NV: wvs_e125), failed state (β = −0.013, P value = 0.032, NV: ffp_fsi), professional public administration (β = 0.441, P value = 0.071., NV: qs_proff), transparent government (β = 0.128, P value = 0.059, NV: ti_cpi), good governance(β = 0.574, P value = 0.047, NV: kk_gg). All data come from The Quality of Government Dataset, version 6 Apr 11 (see, Teorell et al. 2011).

  5. Such group categories based on mean scores which come from politics and economy variables in Table 1.


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This research was supported by research grant from The Guwon Scholarship Foundation. I thank Dr. Whang Pillsang, a founder of the foundation, for his thoughtful consideration for Ajou University.

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Correspondence to Seoyong Kim.



See Tables 7 and 8.

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Kim, S., Kim, D. Does Government Make People Happy?: Exploring New Research Directions for Government’s Roles in Happiness. J Happiness Stud 13, 875–899 (2012).

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