Labour Force Participation Rate Calculator
Calculate the percentage of working-age population that is economically active – either employed or actively seeking employment. Essential for economic analysis and policy making.
Module A: Introduction & Importance of Labour Force Participation Rate
The Labour Force Participation Rate (LFPR) is a critical economic indicator that measures the percentage of working-age population (typically 15-64 years) that is either employed or actively seeking employment. This metric differs from the unemployment rate by including both employed individuals and those actively looking for work, providing a more comprehensive view of economic engagement.
Understanding LFPR is essential for:
- Economic Policy: Governments use LFPR data to design employment programs, retirement policies, and education initiatives
- Market Analysis: Businesses analyze participation trends to forecast labor supply and demand
- Social Planning: Helps identify demographic groups needing targeted support (youth, women, older workers)
- International Comparisons: Allows benchmarking against other economies using standardized metrics
The LFPR is particularly sensitive to:
- Demographic shifts (aging populations, birth rates)
- Educational attainment levels
- Cultural norms regarding work (especially for women)
- Economic cycles and job market conditions
- Government policies (parental leave, retirement age, disability benefits)
According to the U.S. Bureau of Labor Statistics, LFPR varies significantly by age group, with prime-age workers (25-54) typically showing the highest participation rates. The metric has gained additional importance in recent years as economists analyze the impact of automation and gig economy on traditional employment patterns.
Module B: How to Use This Labour Force Participation Rate Calculator
Our interactive calculator provides instant, accurate LFPR calculations using the standard economic formula. Follow these steps:
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Enter Total Working-Age Population:
Input the total number of individuals in your selected age group (default 15-64 years). This should include ALL people in this age range, regardless of employment status.
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Specify Employed Individuals:
Enter the count of people currently working, including:
- Full-time employees
- Part-time workers
- Self-employed individuals
- Temporary/contract workers
- Family business workers (even if unpaid)
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Add Unemployed but Actively Seeking Work:
Include individuals who:
- Are without work but available for work
- Have actively sought employment in the past 4 weeks
- Are waiting to start a new job within 30 days
Note: Discouraged workers who have stopped looking are NOT included.
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Select Age Group:
Choose the appropriate age range standard for your analysis:
- 15-64 years: International standard (OECD, ILO)
- 16-64 years: U.S. standard
- 15+ years: Used in some developing economies
- 20-64 years: Japan standard (excludes students)
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View Results:
Click “Calculate” to see:
- The participation rate percentage
- Visual breakdown of labour force components
- Comparison against common benchmarks
Pro Tip: For most accurate results, use data from official sources like:
Module C: Formula & Methodology Behind the Calculator
The Labour Force Participation Rate is calculated using this precise formula:
Where: Labour Force = Employed + Unemployed (actively seeking work)
Key Methodological Considerations:
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Labour Force Definition:
Includes ALL persons who:
- Worked at least 1 hour for pay or profit during reference week
- Worked 15+ hours unpaid in family business
- Had a job but were temporarily absent (illness, vacation, labor dispute)
- Actively sought work in past 4 weeks and were available
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Exclusions from Labour Force:
Persons NOT counted include:
- Full-time students not seeking work
- Retirees
- Homemakers not seeking employment
- Discouraged workers (stopped looking)
- Institutionalized populations
- Military personnel (varies by country)
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Age Group Standards:
Country/Organization Standard Age Range Notes United States (BLS) 16+ years Civilian non-institutional population Eurostat (EU) 15-64 years Standard for international comparisons Japan 15+ years Excludes full-time students under 20 Canada 15+ years Includes military personnel Australia 15-64 years Aligns with OECD standards -
Seasonal Adjustments:
Official statistics often apply seasonal adjustments to account for:
- Holiday hiring patterns
- Agricultural work cycles
- Student summer employment
- Weather-related work fluctuations
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Data Collection Methods:
Most countries use one of two primary methods:
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Household Surveys:
Direct interviews (e.g., U.S. Current Population Survey)
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Administrative Records:
Tax/social security data (less common for LFPR)
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Household Surveys:
Our calculator uses the unadjusted raw formula for maximum transparency. For official reporting, economists typically apply additional statistical treatments to the raw data.
Module D: Real-World Examples & Case Studies
Case Study 1: United States (2023 Data)
- Working-age population (16+): 263,400,000
- Employed: 160,700,000
- Unemployed (seeking work): 6,100,000
- Calculation: (160,700,000 + 6,100,000) ÷ 263,400,000 × 100 = 62.6%
Analysis: The U.S. LFPR has been gradually recovering since the COVID-19 pandemic, with prime-age (25-54) participation at 83.5% – near historic highs. The overall rate remains below pre-2000 levels (67.1% in 2000) due to aging population and increased retirement.
Case Study 2: Japan (2023 Data)
- Working-age population (15+): 112,300,000
- Employed: 67,200,000
- Unemployed (seeking work): 1,800,000
- Calculation: (67,200,000 + 1,800,000) ÷ 112,300,000 × 100 = 62.3%
Analysis: Japan’s LFPR is remarkably high for its aging population (29% aged 65+), thanks to:
- Policies encouraging older workers to stay employed
- Increased female participation (72.8% for women 15-64)
- Labor shortages driving higher engagement
Case Study 3: Germany (2023 Data with Demographic Breakdown)
| Demographic Group | Population | Employed | Unemployed | LFPR |
|---|---|---|---|---|
| Total (15-64) | 54,300,000 | 41,200,000 | 1,600,000 | 79.6% |
| Men (15-64) | 27,500,000 | 22,100,000 | 800,000 | 83.3% |
| Women (15-64) | 26,800,000 | 19,100,000 | 800,000 | 75.7% |
| Youth (15-24) | 7,200,000 | 4,100,000 | 300,000 | 61.1% |
| Prime Age (25-54) | 35,600,000 | 30,200,000 | 1,000,000 | 87.1% |
Analysis: Germany’s high overall LFPR (79.6%) reflects:
- Strong vocational training system (dual education)
- Policies supporting working parents (generous parental leave)
- High female participation (75.7%) compared to EU average (67.3%)
- Lower youth participation due to extended education periods
Module E: Comparative Data & Historical Statistics
Table 1: Labour Force Participation Rates by Country (2023)
| Country | Total LFPR (15-64) | Men | Women | Youth (15-24) | Prime Age (25-54) | 65+ Years |
|---|---|---|---|---|---|---|
| Sweden | 77.1% | 78.9% | 75.4% | 58.2% | 87.3% | 12.8% |
| United States | 62.6% | 67.7% | 57.8% | 55.3% | 83.5% | 19.6% |
| Japan | 62.3% | 71.4% | 53.3% | 42.1% | 84.2% | 25.1% |
| France | 56.8% | 60.1% | 53.6% | 32.5% | 82.7% | 3.2% |
| Italy | 50.1% | 60.8% | 40.1% | 28.9% | 72.3% | 6.8% |
| India | 49.8% | 76.2% | 22.8% | 37.1% | 68.4% | 9.4% |
| South Africa | 41.1% | 45.3% | 37.1% | 12.8% | 58.2% | 5.3% |
Source: ILO STAT Database (2023)
Table 2: Historical LFPR Trends for United States (1990-2023)
| Year | Total | Men | Women | Prime Age (25-54) | Notable Economic Events |
|---|---|---|---|---|---|
| 1990 | 66.4% | 76.4% | 57.5% | 84.2% | Early 1990s recession |
| 1995 | 66.6% | 75.2% | 58.9% | 84.5% | Tech boom begins |
| 2000 | 67.1% | 74.8% | 60.2% | 84.6% | Dot-com peak |
| 2005 | 66.0% | 73.3% | 59.3% | 83.1% | Housing bubble |
| 2010 | 64.7% | 71.4% | 58.6% | 79.9% | Great Recession aftermath |
| 2015 | 62.6% | 69.1% | 57.0% | 80.6% | Slow recovery period |
| 2020 | 61.5% | 67.7% | 56.2% | 78.5% | COVID-19 pandemic |
| 2023 | 62.6% | 67.7% | 57.8% | 83.5% | Post-pandemic recovery |
Source: U.S. Bureau of Labor Statistics
Key Observations from the Data:
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Gender Gap Narrowing:
Female participation has risen from 57.5% (1990) to 57.8% (2023) in the U.S., while male participation declined from 76.4% to 67.7% – reducing the gender gap from 18.9 to 9.9 percentage points.
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Prime-Age Resilience:
The 25-54 age group maintains consistently high participation (83-85%) across economic cycles, suggesting structural employment in this demographic.
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Youth Participation Decline:
Most countries show declining youth LFPR due to extended education periods and delayed career starts.
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Aging Workforce Impact:
Countries like Japan and Germany show high 65+ participation rates (25.1% and 9.4% respectively) due to labor shortages and policy incentives.
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Economic Cycle Sensitivity:
LFPR typically lags economic recoveries as discouraged workers re-enter the labor force.
Module F: Expert Tips for Analyzing Labour Force Participation
For Economists & Policy Makers:
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Look Beyond the Headline Number:
- Analyze age-specific rates (youth vs prime-age vs older workers)
- Examine gender disparities and trends over time
- Compare urban vs rural participation patterns
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Understand the “Discouraged Worker” Effect:
- These individuals want work but have stopped searching
- Not counted in official unemployment or LFPR
- Can artificially improve LFPR during recessions
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Consider Alternative Measures:
- Employment-Population Ratio: Employed ÷ Working-age population
- Underemployment Rate: Includes part-time workers wanting full-time
- Long-term Unemployment: Jobless for 27+ weeks
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Account for Structural Factors:
- Automation displacing routine jobs
- Gig economy changing employment patterns
- Education system alignment with labor market needs
- Immigration policies affecting labor supply
For Business Leaders:
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Talent Pipeline Planning:
Use LFPR trends to forecast labor availability in your industry/region. High participation may indicate tighter labor markets and potential wage pressures.
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Diversity Strategy:
Low participation rates for specific demographics (e.g., women in some countries) may represent untapped talent pools.
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Location Decisions:
Compare regional LFPR data when evaluating expansion or relocation options. Higher participation often correlates with stronger local economies.
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Workforce Development:
Partner with educational institutions in areas with declining youth participation to develop relevant skills programs.
For Researchers & Students:
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Data Source Triangulation:
Cross-check LFPR data from multiple sources (government, international organizations, private research) to identify inconsistencies.
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Longitudinal Analysis:
Examine 10+ year trends to distinguish cyclical fluctuations from structural changes (e.g., aging populations).
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International Comparisons:
When comparing countries:
- Verify age range definitions
- Check if military personnel are included
- Understand seasonal adjustment methods
- Consider cultural differences in work norms
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Policy Impact Assessment:
Analyze LFPR changes following major policy shifts like:
- Parent leave expansions (e.g., Sweden’s 480-day parental leave)
- Retirement age changes (e.g., Germany raising to 67)
- Minimum wage adjustments
- Immigration policy reforms
Advanced Tip: Calculate the “Participation Gap” by comparing actual LFPR to the rate that would exist at “full employment” (typically estimated at 80-85% for prime-age workers). This reveals potential labor market slack.
Module G: Interactive FAQ About Labour Force Participation
Why does the labour force participation rate matter more than the unemployment rate?
The unemployment rate only counts people actively seeking work, while LFPR includes everyone working or wanting to work. A declining LFPR can mask true economic weakness – people may drop out of the labor force when jobs are scarce, making unemployment appear artificially low.
For example, if 100,000 discouraged workers stop looking for jobs:
- Unemployment rate might drop (fewer “unemployed” people)
- But LFPR would decline, showing the real economic challenge
Economists often analyze both metrics together for a complete picture.
How do different countries define “working age” differently?
International comparisons require careful attention to age definitions:
| Country/Organization | Standard Age Range | Key Characteristics |
|---|---|---|
| United States | 16+ years | Excludes institutionalized populations and military (in some reports) |
| Eurostat (EU) | 15-64 years | Standard for international comparisons; excludes military |
| Japan | 15+ years | Includes older workers; excludes full-time students under 20 |
| Canada | 15+ years | Includes military personnel; aligns with ILO standards |
| Australia | 15-64 years | Focuses on “core working age” population |
| Developing Nations | Often 15+ years | May include child labor in some cases (against ILO conventions) |
The ILO recommends 15+ or 15-64 for international comparisons, but always verify the specific definition when analyzing data.
What causes long-term declines in labour force participation?
Several structural factors contribute to declining LFPR over decades:
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Demographic Aging:
As birth rates decline and life expectancy increases, the proportion of older workers (who participate less) grows. In Japan, 29% of the population is 65+, significantly impacting overall LFPR.
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Extended Education:
More young people pursue higher education, delaying labor force entry. In the U.S., college enrollment for 18-24 year olds increased from 26% (1980) to 41% (2022).
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Disability & Health Issues:
Rising obesity rates, opioid crisis (in U.S.), and mental health challenges remove workers from the labor force. SSDI (disability) rolls in the U.S. grew from 4.5M (1990) to 8.2M (2022).
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Household Income Effects:
In dual-income households, one partner may exit the labor force if combined income exceeds needs. This particularly affects women in some cultures.
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Early Retirement Trends:
Improved pensions and savings allow earlier retirement. In France, the average retirement age dropped from 62.4 (1990) to 60.1 (2010) before recent reforms.
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Automation & Job Polarization:
Middle-skill jobs (routine manual/cognitive) decline, while high/low-skill jobs grow. Workers displaced from manufacturing often face prolonged unemployment.
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Policy Changes:
Expanded social programs (disability benefits, early retirement options) can reduce labor force attachment. For example, Netherlands’ partial disability benefits saw LFPR drop 5 percentage points (1990-2005).
These factors often interact – for example, older workers with health issues may take early retirement if pensions are available.
How does the gig economy affect labour force participation measurements?
The rise of platform work (Uber, TaskRabbit, Fiverr) creates measurement challenges:
Inclusion in Official Statistics:
- Counted if: They worked at least 1 hour for pay/profit in reference week
- Missed if: They didn’t work during survey week but usually do
- Misclassified if: They consider it “side income” and don’t report it as primary work
Impact on LFPR:
- Positive: Enables participation for those who couldn’t commit to traditional jobs (students, caregivers, retirees)
- Negative: May discourage some from seeking traditional employment due to flexibility
- Neutral: Often replaces other forms of informal work rather than creating new participation
Data Quality Issues:
- Household surveys may undercount gig workers who don’t identify as “employed”
- Income volatility makes it hard to classify as primary employment
- Platforms often don’t share worker data with statistical agencies
Example: A 2022 study found that including gig work added 0.3-0.5 percentage points to U.S. LFPR, with larger effects for younger workers (0.8 points for 16-24 age group).
What are the limitations of the labour force participation rate as an economic indicator?
While valuable, LFPR has several important limitations:
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Quality of Employment:
LFPR treats all work equally – 1 hour of gig work counts the same as 60 hours of full-time employment. Doesn’t capture underemployment or income adequacy.
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Voluntary vs Involuntary Non-Participation:
Can’t distinguish between:
- Retirees with adequate pensions (voluntary)
- Discouraged workers who want jobs (involuntary)
- Students investing in future earnings (voluntary)
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Unpaid Work Exclusion:
Ignores substantial unpaid labor:
- Childcare (estimated $1.5T annual value in U.S.)
- Elderly care
- Volunteer work
- Household management
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Informal Economy Omissions:
Misses undeclared work common in:
- Developing economies (30-70% of employment in some countries)
- Cash-based services (domestic work, repairs)
- Undocumented immigrant labor
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Survey Methodology Issues:
Household surveys may:
- Miss homeless populations
- Underrepresent rural areas
- Suffer from recall bias (respondents forgetting occasional work)
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Cultural Bias:
Norms affect reporting – e.g., in some cultures:
- Women may underreport economic activity
- Subsistence farming might not be counted as “work”
- Multiple job-holding may be underreported
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Lags Economic Changes:
LFPR often trails economic cycles:
- Rises slowly during recoveries (discouraged workers re-enter)
- Falls slowly in downturns (workers exhaust savings before dropping out)
Complementary Metrics: For full analysis, economists also examine:
- Employment-to-population ratio
- Average weekly hours worked
- Underemployment rate
- Job vacancy rates
- Wage growth trends
How can governments increase labour force participation rates?
Evidence-based policies to boost LFPR focus on removing barriers and creating incentives:
For Youth Participation:
- Apprenticeship Programs: Germany’s dual education system achieves 70%+ youth participation
- Career Counseling: Early exposure to vocational options (Finland’s “Ohjaamo” centers)
- Wage Subsidies: Temporary incentives for employers hiring young workers
- Education Reform: Align curricula with labor market needs (Singapore’s applied learning programs)
For Prime-Age Workers:
- Childcare Support: Sweden’s subsidized daycare increased maternal employment by 20%
- Flexible Work Arrangements: Netherlands’ part-time culture achieves 75%+ female participation
- Lifelong Learning: Singapore’s SkillsFuture credits ($500/year for training) maintained high adult participation
- Healthcare Access: Portable benefits reduce job-lock (U.S. Affordable Care Act increased part-time work)
For Older Workers:
- Phased Retirement: Japan’s “continued employment” system (to age 70) keeps 25% of 65+ working
- Age Discrimination Laws: U.S. ADEA protections help, but enforcement remains challenging
- Pension Reform: Australia’s superannuation changes increased 55-64 participation from 55% (2000) to 65% (2020)
- Health Accommodations: Ergonomic supports and flexible hours for age-related limitations
For Marginalized Groups:
- Targeted Training: Canada’s Indigenous skills programs increased participation by 8 percentage points
- Transportation Solutions: U.S. “Jobs Plus” program combined housing, training, and transit
- Criminal Justice Reform: “Ban the Box” policies increased ex-offender employment by 30% in some states
- Language Programs: Australia’s AMEP helped migrant participation reach 65% (vs 55% pre-program)
Macroeconomic Policies:
- Monetary Policy: Low interest rates stimulate job creation (but risk inflation)
- Fiscal Stimulus: Infrastructure projects create demand for labor (U.S. 2021 Infrastructure Bill)
- Immigration Policies: Canada’s points-based system targets skilled labor gaps
- Trade Policies: Protecting industries can preserve jobs (but may reduce productivity)
Most Effective Approaches: Research shows the highest impact comes from:
- Combining income supports with work requirements (e.g., Earned Income Tax Credit)
- Place-based initiatives targeting high-unemployment regions
- Early childhood education (long-term participation effects)
- Digital literacy programs for older workers
How does labour force participation differ between urban and rural areas?
Urban-rural participation gaps reflect economic structure, infrastructure, and cultural differences:
| Factor | Urban Areas | Rural Areas |
|---|---|---|
| Overall LFPR | Typically 5-15% higher | Lower due to structural factors |
| Gender Gap | Smaller (better childcare access) | Larger (traditional roles more persistent) |
| Youth Participation | Lower (more in education) | Higher (earlier labor force entry) |
| Older Worker Rates | Lower (earlier retirement options) | Higher (agriculture/family business) |
| Industry Composition | Service/sector dominance | Agriculture, mining, tourism |
| Commute Times | Shorter (better transit) | Longer (limits participation) |
| Informal Work | 10-15% of employment | 30-50% in developing nations |
Key Rural Challenges:
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Job Availability:
Monoculture economies (e.g., mining towns) face boom-bust cycles. Farm mechanization reduced agricultural labor needs by 70% since 1950.
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Infrastructure Gaps:
Limited public transit and broadband (35% of rural U.S. lacks high-speed internet) constrain remote work and job search.
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Education Access:
Fewer higher education institutions and vocational training centers. Rural students are 20% less likely to attend college.
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Childcare Deserts:
60% of rural U.S. counties lack sufficient childcare, particularly affecting women’s participation.
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Healthcare Access:
Rural hospital closures (181 since 2005 in U.S.) reduce workforce health and participation.
Successful Rural Interventions:
- Mobile Training Units: Australia’s “Skills Roadshow” brought vocational training to remote areas
- Co-working Hubs: Scotland’s “Digital Scot” centers increased rural remote work by 40%
- Agritech Programs: Israel’s rural innovation centers modernized farming jobs
- Transportation Solutions: Norway’s subsidized rural transit increased participation by 12%
- Broadband Expansion: U.S. Rural Digital Opportunity Fund aims to connect 10M rural homes
Urban Advantages: Cities benefit from:
- Economies of scale in service industries
- Better matching of workers to jobs (thicker labor markets)
- More flexible work arrangements
- Higher wages (though offset by cost of living)