Measuring well-being in India

An analysis of the Gallup World Poll Surveys for India shows that any signs of reversal of policies are weak, if not missing altogether

Updated - July 27, 2023 01:47 am IST

Ragpickers search for recyclable materials as a truck unloads garbage at a dumpsite in Guwahati. File

Ragpickers search for recyclable materials as a truck unloads garbage at a dumpsite in Guwahati. File | Photo Credit: AFP

There has been euphoria over India’s economic growth accelerating to 6.1% in the March quarter, as it confirmed that the country remains one of the fastest growing emerging economies. Counterclaims followed in quick succession drawing attention to fall in private consumption, high inflation, rise in poverty, and income and wealth inequality. The rhetoric on either side has continued with growing intensity. What is missed in this debate, however, is that income is a narrow measure of well-being, as argued by Amartya Sen (1999), Angus Deaton (2008), and others. Although Sen and Deaton differ in their approach, they concur that we must look beyond income to measure well-being.

Life satisfaction and income

A close scrutiny of the relationship between life satisfaction and income based on Gallup World Poll (GWP) Surveys confirms a positive relationship between them with a slightly stronger effect in developed countries. But it is intriguing that growth of income has a negative effect on life satisfaction. It is plausible that there is a “threshold” income effect beyond which increases in income do not matter, or that there is no long-run relationship between the two. But this awaits empirical validation.

Trust in government represents the confidence of citizens in the actions of a “government to do what is right and perceived fair”. Citizen expectations influence trust in government. If citizens’ expectations rise faster than the actual performance of governments, trust and satisfaction could decline. These changes in expectations may explain more the erosion of political support rather than real government performance. Besides, citizens’ trust towards government is influenced by whether they have a positive or negative experience with service delivery. A negative experience has a much stronger impact on trust in government than a positive one (OECD, 2013).

Our analysis of the relationship between life satisfaction is based on GWP Surveys for India in 2018, 2019, 2020 and 2021. Life satisfaction is measured as suffering, struggling, and thriving. The measures of affluence used are income per capita and its growth. Trust in government is measured as whether the respondent has confidence in the government. Individual demographic and economic characteristics include age, gender, religion, caste and whether the respondents live in rural or urban areas, and income and its growth. Overall income inequality is measured along the lines of Piketty, 2014.

Several results conform with global and regional studies (notably Deaton, 2008). There is a strong negative correlation between life satisfaction and age. Among those thriving, the proportion of those aged 55 and above was barely 9% compared to the over 43% of those aged 25-45, in 2021. There is a negative correlation between life satisfaction and women. This is not surprising as women face greater discrimination when employment is sluggish and are also subject to greater male violence when law enforcement is weak. There is a consistent negative correlation between life satisfaction and minorities. The share of Hindus among the thriving rose from 85% in 2019 to 89.6% while that of Muslims fell from about 7% to 2.3%. While the share of the unreserved (including Brahmins and ‘high’ castes) among the thriving rose from over 26.2% in 2019 to 38.7% in 2021, that of OBCs declined slightly from 33% to 31.5% and that of Scheduled Castes and Scheduled Tribes declined sharply from about 41% to just under 30%.

Turning to the measures of affluence, life satisfaction has a positive correlation with per capita income, but with a marked weakening in 2020, presumably due to COVID-19, and a rebound in 2021. Life satisfaction is unrelated to growth of income.

The Piketty measure of income inequality is a ratio of the share of the top 1% of individuals in total income to that of the bottom 50%. Life satisfaction is negatively correlated with this measure of inequality over 2019-21, with a slight strengthening of the correlation (in absolute value) in 2021. The correlation (in absolute value) was lowest in 2020 presumably because life satisfaction suffered due to the COVID-19 pandemic.

Trust in government

Finally, we examine the relationship between life satisfaction and trust in government. As perceptions matter more than performance, aggressive pursuit of Hindu nationalism, promulgation of the Citizenship (Amendment) Act and subsequent outbursts of violence, lynching of Muslim and Dalit cattle traders, excessive centralisation, and suppression of media independence have left deep scars on the national psyche. A detailed analysis of the association between life satisfaction in 2019 and trust in the NDA government in 2018 (controlling for the confounders) reveals that there is a positive association between them. Among the thriving, the share of those who trusted the government fell from about 83% in 2019 to 79% in 2021. This may seem intriguing, but it is not if the thriving are more sensitive to attacks on minorities, journalists and other liberals, encounter killings, high inflation and unemployment. Among the suffering, the loss of trust was moderate. If these include mostly minorities and Dalits, their negative experiences and perceptions could lower their trust in the NDA government. In fact, trust in the NDA fell and so did well-being. In sum, any signs of reversal of policies are weak, if not missing altogether.

Raghav Gaiha is Research Affiliate, Population Aging Research Center, University of Pennsylvania; Vidhya Unnikrishnan is Lecturer in Development Economics, GDI, University of Manchester; Vani S. Kulkarni is Research Affiliate, Population Studies Centre, University of Pennsylvania

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