Happiness Has a Gender

The full numbers

The 2022 GNH Survey produced gender-disaggregated GNH Index values for the first time at the level of statistical significance:

• Male GNH: 0.814
• Female GNH: 0.762
• Gap: 0.052 points (≈6.4% relative) — flagged as “highly significant” (p < 0.001) Within the 9 domains, women score lower on: Education (lower mean schooling years), Time Use (more unpaid domestic and care work), Living Standards (lower assets and ownership), Knowledge (lower civic-literacy measures), and Government Performance (lower trust scores). Women score equal or higher on: Health, Community Vitality, Cultural Participation, Spirituality, and Ecological Diversity. The gap is not a single-domain artefact — it shows up across multiple domains that map to known structural inequalities: education access, asset ownership, time use, and civic participation.

Imagine this

A 34-year-old mother in Punakha rises at 5:30 AM to start the kitchen fire, prepare breakfast for her three children, pack lunches, walk the younger two to school, return to feed the cattle, work three hours on the family vegetable plot, prepare lunch for her mother-in-law, do the laundry, prepare dinner, help the children with homework, clean up, and turn off the lights at 10:30 PM. She has worked 17 hours. She earns no salaried income. Her husband, who drives a taxi in Thimphu, earns the household income. When the GNH survey reaches her, she scores low on Time Use, low on Living Standards (assets in her husband’s name), low on Education (Class 8), and high on Spirituality and Community Vitality (she leads the weekly puja rotation). Net: she lands below the national average GNH. Her husband — same household, same village, same family — scores higher on Living Standards (formal vehicle ownership), higher on Time Use (formal work hours with breaks), higher on Education (Class 12), and similar on Spirituality. Net: he lands above the national average GNH. The household is the same. The country’s own happiness measure assigns them different scores. The lower score belongs to the person who works more hours.

Where this came from

The 0.052 gap reflects long-standing structural inequalities that have been slowly compressed but not closed. Women’s primary-school enrolment caught up with men’s in the early 2000s; tertiary enrolment is now near parity. Asset ownership remains skewed toward men (land titles, vehicle ownership, business registration).

Time use remains heavily skewed toward women carrying unpaid care work. Workforce participation: female labour-force participation ~57% vs male ~73% (NSB 2022). In the micro and small enterprise sector — over 90% of Bhutan’s businesses — women own only 35.53% of registered MSEs (NSB Businesswomen Study, 2018); the binding constraint cited by 62% of women entrepreneurs is lack of access to financial capital, not social stigma (only 0.3% cited male domination as a challenge).

The Royal Civil Service achieved near-parity in headcount (women ~47% of civil servants — CSS 2025), but senior positions remain skewed toward men (~33% of Senior Executive-grade positions held by women). Political representation: ~15% of National Assembly and National Council seats held by women.

Why this matters now

The gender GNH gap shows up just as Bhutan’s demographic transition demands maximum labour-force participation. The country can no longer afford to under-utilise half its working-age population. The same female population that scores lower on the GNH today is the population whose labour-force participation determines whether the demographic transition is manageable. Closing the GNH gap and closing the workforce-participation gap are the same project.

The 13th FYP includes gender-equity commitments, but the targets remain modest and the institutional infrastructure (childcare, maternity leave outside civil service, asset-ownership norms) lags peer countries.

What it should be

A gender GNH gap that closes by 2030 — from 0.052 to under 0.02. Operationally: universal accessible childcare (currently virtually absent); maternity-leave parity across civil service and private sector; asset-ownership reform (defaulting joint title on family land and housing); senior-leadership pipeline targets in civil service and SOEs; mandatory unpaid-work measurement in NSB labour surveys so the invisible work shows up in official data.

How others do it

• Iceland — top of the World Economic Forum’s Gender Gap Index for 14 consecutive years; mandatory equal-pay certification; near-equal parental leave
• Norway — board-quota law (40% gender on listed company boards); workforce-participation gap < 4%
• Rwanda — gender parity in parliament; mandatory women’s-representation quotas
• Sweden — universal childcare from age 1; gender pay gap < 6%
• Bhutan: GNH framework measures the gap; institutional design has not yet closed it

The question we should be sitting with

If half our population scores lower on the country’s own measurement of wellbeing, and the gap is statistically certain, what kind of GNH are we measuring? If GNH is universal by definition, why does our index have a male and a female number?