Happiness Flashcards
(12 cards)
Identify and explain the seven factors Richard Layard identified as affecting adult happiness.
- Family relationships (divorce/separation reduces happiness).
- Financial situation (income drops reduce happiness).
- Work (unemployment/job insecurity lowers happiness).
- Community/friends (lack of trust/community ties reduce happiness).
- Health (chronic pain/mental illness significantly lower happiness).
- Personal freedom (lack of political freedom/war reduces happiness).
- Personal values (lack of religious faith/internal comfort lowers happiness)
What six factors does the UN Happiness Report link to national happiness?
- Real GDP per capita.
- Healthy life expectancy.
- Having someone to count on.
- Perceived freedom to make life choices.
- Freedom from corruption.
- Generosity.
Key Insight: Mental health is the single largest factor affecting happiness globally.
Explain the Easterlin paradox and its implications for economic policy.
Paradox: Rising GDP in wealthy nations (e.g., US in the 1960s) does not correlate with increased happiness.
Key Findings:
- Relative income: Happiness depends on income relative to others (comparison effect).
- Adaptation: People adapt to higher incomes, making gains temporary.
Policy Implication: Governments may need to prioritize non-income factors (e.g., mental health, community) over GDP growth.
Provide examples of objective and subjective wellbeing measures.
- Objective: Life expectancy, unemployment rates, GDP per capita.
- Subjective: Self-reported life satisfaction, anxiety levels, fear of crime.
Case Study: The UK’s ONS uses both (e.g., life expectancy + “satisfaction with life” surveys).
Explain PPP adjustment and why it reduces income inequality gaps between countries.
PPP Adjustment: Accounts for cost-of-living differences (e.g., $1 buys more in India than Norway).
Why Gaps Shrink: PPP reflects actual purchasing power, so nominal income disparities (e.g., Norway vs. Burundi: 543x) fall to 206x when adjusted.
Why does rising income per capita improve quality of life more in developing countries?
- Developing nations: Income growth meets basic needs (food, shelter, healthcare).
- Developed nations: Income gains focus on relative status (comparison effects dominate)
Example: DRC citizens gain more from $1,000 GDP/capita than Luxembourg citizens.
Why did life satisfaction fall in Greece and Spain (2007–2012)?
Key Factors:
- Severe unemployment (10%+ declines in employment rates).
- Job insecurity/involuntary part-time work.
- Economic crisis reducing perceived financial stability.
Data Point: Greece saw a 25% drop in “very satisfied” respondents.
Evaluate arguments for shifting policy focus from GDP to happiness.
For:
- Happiness policies target mental health, equality, and community (e.g., UK’s green space investments).
- Easterlin paradox shows GDP growth ≠ happiness in wealthy nations.
Against:
- GDP growth still correlates with job creation and reduced poverty.
- Happiness metrics are subjective and harder to measure.
Case Study: London (wealthiest UK region) has low wellbeing due to poor work-life balance.
How might happiness-focused policies conflict with GDP growth?
- Example 1: Reducing geographical labor mobility preserves community ties but limits GDP growth.
- Example 2: Mental health funding diverts resources from infrastructure (short-term GDP cost).
- Example 3: Progressive taxation reduces inequality but may discourage entrepreneurship
Why might happiness studies be flawed?
Subjectivity: Self-reported data varies by culture/individual.
Adaptation: People overreport resilience (e.g., “hedonic treadmill”).
Non-monetary factors: Hard to quantify (e.g., “freedom from corruption”).
What additional wellbeing data would assess life satisfaction in crisis-hit countries?
- Mental health access rates.
- Income inequality (Gini coefficient).
- Work-life balance metrics.
- Trust in government/institutions.
What are the aims and methods of the UK’s wellbeing programme?
- Aim: Track progress via 10 domains (e.g., health, environment) and 38 indicators.
- Methods: Mix objective (e.g., unemployment) and subjective (e.g., life satisfaction surveys) data.
