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Nichaphat Surawattananon (Nicha)

March 8th, 2022

Break the bias to improve women’s wellbeing

0 comments | 5 shares

Estimated reading time: 5 minutes

Nichaphat Surawattananon (Nicha)

March 8th, 2022

Break the bias to improve women’s wellbeing

0 comments | 5 shares

Estimated reading time: 5 minutes

This post has been written by Nichaphat (Nicha) Surawattananon, studying MSc Behavioural Science at LSE. The post forms part of a series for International Women’s Day 2022. Read all the posts in the series here.

Every year, 8 March marks International Women’s Day and we have been fighting against discrimination to achieve gender equality. However, this year is a bit different. There have been two long years of the COVID-19 pandemic during which the inequalities felt before the pandemic have worsened.

One of the inequities that is worsening is the mental health gap. According to the World Happiness Report 2021, women have suffered from mental health issues more than men during the pandemic. However, gross domestic product – or GDP – is the main indicator used to measure the country’s economic health. But how about how has health has been impacted by the policy responses during the pandemic, particularly women’s?

Women’s wellbeing in review: evidence from the pandemic

According to the Mental Health Foundation, women were three times more likely to experience common mental illnesses than men even before the pandemic. The underlying factors include domestic violence and abuse, sexual violence, physical and sexual abuse, economic disadvantage, and their roles as caregivers. However, the policy responses to mitigate the pandemic such as the lockdown and social distancing have exacerbated these factors, especially domestic abuse and economic disadvantage.

The UK’s Office for National Statistics has reported that domestic abuse-related offences have increased by approximately 12% in May 2020 compared to May 2019. The analysis from McKinsey & Company also reveals that there are disparities in the impact of the pandemic in the labour market. Since women’s jobs are concentrated in sectors negatively affected by the pandemic such as accommodation and food services, women are 19% more at risk to lose their jobs compared to men. 23% of women with children under 10 years old have left the workforce while it is only 13% for men because of the increase in childcare burden among women. The report also reveals that women have felt pressured to work more than men, leading to a higher level of exhaustion and burnout. According to the OCED’s How’s Life? 2020 report, women in OECD countries work half an hour longer every day, both for paid and unpaid work, but they still earn 13% less than men.

Consequently, these factors aggravate the existing inequalities in women’s wellbeing.

According to the World Happiness Report 2021, the General Health Questionnaire (GHQ-12), which measures mental problems over weeks, shows that women suffer more mental issues than men. The COVID-19 Social study conducted by University College London has revealed that women in the UK have been experiencing higher levels of depression, anxiety, COVID-19 stress, financial stress and loneliness than men since the first lockdown. Levels of depression and anxiety were at their worst in August 2020 and their impacts have resulted in the lowest level of life satisfaction and happiness in January 2021 which are 5 months lagged. And of course, women have reported a lower level of life satisfaction and happiness than men, however, the trends from both genders are converging in August 2021, which is the latest data available in the report. 

Why do wellbeing indicators deserve more attention from policymakers?

According to the IMF, GDP calculates the value of final goods and services in monetary value. It factors in the outputs within the country’s market exchange. Though this could reflect the “economy’s health”, it somehow overlooks “people’s health”. The policy responses during the pandemic have led to consequences beyond economic impact. For example, the pandemic has brought about income shocks to many people, particularly women, who have been experiencing the gender pay gap, and this would eventually lead to financial pressure and emotional burden on women.

Moreover, GDP could be “biased” since not “all activities” that are generated by “all players” in the economy is counted. From the TedTalk “The Unpaid Work that GDP Ignores – and Why It Really Counts” by Marilyn Waring, GDP disregards the unpaid work by women such as breastfeeding and housework. Women are recognized as “nonprimary producers” whose outputs are “of little or no value”.  It is also emphasized that the unpaid sector is one of the largest sectors in many countries. For instance, the combination of manufacturing and retailing sectors is equal to unpaid work in the UK.

Policy advocacy – It is not just about the gender pay gap anymore. It is also about the mental health and wellbeing gap.

The situation during the pandemic now raises several questions. Can GDP reflect people’s true happiness and wellbeing, especially in women? Is it appropriate that the growth of investment in the industry that eventually harms people’s wellbeing in the future is valued more than “women’s unpaid jobs”? How would policymakers deliver the right policy priorities when the measurement of a country’s economic development does not include every aspect of players and activities that happen in “real life” not just in the “market exchange”?

To answer those questions, governments should take the measurement of people’s wellbeing and happiness more seriously. The common measurement that has been adopted is the measure of subjective well-being (SWB) which asks people to evaluate their life satisfaction or happiness. For example, Dolan and Metcalfe (2012) suggested that the questions could be, “overall, how satisfied are you with your life nowadays?” or “overall, how happy did you feel yesterday?”. According to OECD, subjective wellbeing reflects mental state and experiences in life. A study by Layard et. al. (2014) found that the most important factor that directly predicts life satisfaction, measured at the age of 34, is emotional health, not income. Thus, these show that life satisfaction could indicate the living conditions beyond income from people’s perspectives.

According to OECD, countries with a higher level of wellbeing tend to be more equal. To successfully ‘Break The Bias’ governments around the world should prioritise wellbeing as part of their GDP equation. In addition to the consumption, investment, government expenditure and international trade, the GDP might need to be adjusted with people’s wellbeing to include the cost of the GDP growth. For example, labour productivity leads to an increase in outputs, but high levels of productivity could also relate to the high level of stress. The lower outputs in the economy during the pandemic does not always mean people work less. In the case of women, they actually work more but in unpaid work. The bottom line here is that policymakers need to start establishing the “inclusive” data collection and methodology to deliver a more inclusive policy.

The hope is that the impact of the pandemic on women’s inequality, much of it faced for centuries, could bring more attention and advocacy to women’s wellbeing in policy. And the 8th of March 2022 could mark the moment of change for better women’s wellbeing in the near future.

Notes:

  • This post expresses the views of the author and not the Department of Psychological and Behavioural Science, nor the LSE.
  • This post is part of a series for International Women’s Day 2022. Read all the posts in the series, written by students from the Department of Psychological and Behavioural Science, here.
  • Image sourced via Canva.

References

Anu Madgavkar, White, O., Krishnan, M., Mahajan, D., & Azcue, X. (2020, July 15). COVID-19 and gender equality: Countering the regressive effects. McKinsey & Company; McKinsey & Company. https://www.mckinsey.com/featured-insights/future-of-work/covid-19-and-gender-equality-countering-the-regressive-effects

Banks, J., Fancourt, D., & Xu, X. (2021). Mental health and the COVID-19 pandemic. Worldhappiness.report. https://worldhappiness.report/ed/2021/mental-health-and-the-covid-19-pandemic/

Callen, T. (2020). Finance & Development. Finance & Development | F&D. https://www.imf.org/external/pubs/ft/fandd/basics/gdp.htm

Dolan, P., & Metcalfe R. (2012). Measuring Subjective Wellbeing: Recommendations on Measures for use by National Governments. Journal of Social Policy, 41(2), 409–427. https://doi.org/10.1017/s0047279411000833

Gao, F., Luo, N., Thumboo, J., Fones, C., Li, S.-C., & Cheung, Y.-B. (2004). Health and Quality of Life Outcomes, 2(1), 63. https://doi.org/10.1186/1477-7525-2-63

Havard, T. (2021, May 11). Domestic abuse and Covid-19: A year into the pandemic. House of Commons Library. https://commonslibrary.parliament.uk/domestic-abuse-and-covid-19-a-year-into-the-pandemic/

Layard, R., Clark, A. E., Cornaglia, F., Powdthavee, N., & Vernoit, J. (2014). What Predicts a Successful Life? A Life-Course Model of Well-Being. The Economic Journal, 124(580), F720–F738. https://doi.org/10.1111/ecoj.12170

McKinsey & Company. (2021, March 8). Seven charts that show COVID-19’s impact on women’s employment. McKinsey & Company; McKinsey & Company. https://www.mckinsey.com/featured-insights/diversity-and-inclusion/seven-charts-that-show-covid-19s-impact-on-womens-employment

Mental Health Foundation. (2015, August 7). Women and mental health. Mental Health Foundation. https://www.mentalhealth.org.uk/a-to-z/w/women-and-mental-health

Mental Health Foundation. (2017). While your back was turned: How mental health policymakers stopped paying attention to the specific needs of women and girls.

OECD. (2020). How’s Life? 2020: Measuring Well-being. Oecd-Ilibrary.org. https://www.oecd-ilibrary.org/sites/9870c393-en/1/3/8/index.html?itemId=/content/publication/9870c393-en&_csp_=fab41822851fa020ad60bb57bb82180a&itemIGO=oecd&itemContentType=book

Office for National Statistics. (2020, November 25). Domestic abuse during the coronavirus (COVID-19) pandemic, England and Wales. Ons.gov.uk; Office for National Statistics. https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice/articles/domesticabuseduringthecoronaviruscovid19pandemicenglandandwales/november2020

TED. (2019, August). The unpaid work that GDP ignores — and why it really counts. Www.ted.com. https://www.ted.com/talks/marilyn_waring_the_unpaid_work_that_gdp_ignores_and_why_it_really_counts?language=en

About the author

Nichaphat Surawattananon (Nicha)

Before I joined the programme, I was working as an economist at the Bank of Thailand. During my work there, many policy challenges were emerging, and they have inspired me to pursue the MSc in Behavioural Science at LSE. I am particularly interested in the application of behavioural science to improve people’s wellbeing, foster sustainability, and enhance public policy effectiveness.

Posted In: International Womens Day | MSc Behavioural Science

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