Definition
The dependency ratio is a demographic measure that compares the number of people typically not in the labor force (dependents) to the number of people in prime working ages. Dependents are usually defined as children aged 0–14 and older adults aged 65 and over. The working-age population is conventionally those aged 15–64.
Why it matters (brief)
The ratio gives a quick sense of the potential economic burden on the working population: a higher ratio suggests more dependents per worker and can signal greater pressure on public budgets for pensions, health care and education, and on households who support non‑workers.
Core formulas
– Total dependency ratio = (Number of dependents [0–14 and 65+] ÷ Population aged 15–64) × 100
– Youth dependency ratio = (Population aged 0–14 ÷ Population aged 15–64) × 100
– Elderly dependency ratio = (Population aged 65+ ÷ Population aged 15–64) × 100
Interpretation rule of thumb
– If total dependency ratio = 50%, there are 50 dependents for every 100 working‑age people, or on average 0.5 dependents per working‑age person.
– If total dependency ratio = 100%, there is one dependent for every working‑age person.
Worked numeric example
Suppose a small country has:
– Children (0–14): 250
– Working‑age (15–64): 500
– Elderly (65+): 250
Calculate:
– Youth dependency = 250 ÷ 500 = 0.50 → 50%
– Elderly dependency = 250 ÷ 500 = 0.50 → 50%
– Total dependency = (250 + 250) ÷ 500 = 1.00 → 100%
Interpretation: each working‑age person supports, on average, one dependent.
Checklist: how to compute and interpret a dependency ratio
1. Obtain population counts by age groups (0–14, 15–64, 65+).
2. Compute youth and elderly dependency ratios separately, then total dependency.
3. Express results as percentages for easy comparison.
4. Compare the ratio:
– over time for the same country (trend analysis);
– across countries or regions (benchmarking).
5. Consider complementary measures (labor force participation, unemployment rates, median age) to refine interpretation.
6. Note policy implications: pensions, taxes, health care spending, immigration and labor policies.
What a “good” ratio means
Lower dependency ratios are generally preferable because relatively more people are of working age to support dependents. However, a low ratio is not universally “good” without context: productivity, labor force participation, wage levels and public policy determine how easily dependents can be supported.
Examples and recent context
– Some countries with very low dependency ratios have large numbers of working-age migrants and small child/elderly populations; others with high ratios may have high birth rates or rapidly aging societies.
– Reported figures (2022 examples): the United Arab Emirates had among the lowest total dependency ratios (~20.6), while Niger was among the highest (~105.1). The United States’ total dependency ratio was around 54.1. (Source data can vary by year and methodology—always check the original dataset.)
What affects the dependency ratio
– Birth and fertility rates (more births raise the youth dependency ratio in the short term).
– Aging and life expectancy (longer life raises the elderly dependency ratio over time).
– Migration and immigration policies (inflows of working-age people can lower the ratio).
– Retirement ages, labor market participation, and prevalence of informal work.
Limitations — what the ratio does not tell you
– It treats everybody 15–64 as “potential workers” even though many in that group may not work (students, unemployed, disabled, caregivers, discouraged workers).
– It ignores productivity differences: a small working population can still support many dependents if productivity (output per worker) is high.
– It does not capture differences in public vs private support, savings behavior, or fiscal structures (tax rates, pension design).
– Age cutoffs (15 and 64) are conventional and may not reflect actual labor market norms in every country.
Practical steps for deeper analysis
– Combine dependency ratios with labor force participation rates and employment/unemployment data to estimate the active support base.
– Look at old-age support ratios (working-age population
to retirees) as well as the child vs. old components separately. That lets you see whether support pressures come mainly from more children (short-term schooling and childcare costs) or from an ageing population (pensions, long‑term care, health care).
Formulas and simple calculations
– Definitions
– Young dependents = population aged 0–14.
– Working‑age population = population aged 15–64 (the conventional cutoff).
– Old dependents = population aged 65+.
– Total dependency ratio (TDR) = (Young + Old) / Working‑age × 100.
– Child dependency ratio = Young / Working‑age × 100.
– Old‑age dependency ratio = Old / Working‑age × 100.
Adjustments for a more realistic “support burden”
– Use employed workers rather than the entire 15–64 group. Employed = Working‑age × Labor force participation rate (LFPR) × (1 − unemployment rate).
– Adjusted dependency ratio = (Young + Old) / Employed × 100.
– Account for productivity: convert employed workers into “effective workers” by multiplying employed by average productivity per worker (output per worker) relative to a baseline.
– Productivity‑adjusted ratio = (Young + Old) / (Employed × Productivity index) × 100.
– Alternatively, compute dependents per employed worker = (Young + Old) / Employed (a ratio, not percent).
Worked numeric example
– Given: Young = 30 million, Working‑age = 120 million, Old = 20 million.
– TDR = (30 + 20) / 120 × 100 = 50 / 120 × 100 = 41.67%.
– Old‑age ratio = 20 / 120 × 100 = 16.67%. Child ratio = 30 / 120 × 100 = 25%.
Now account for labor market participation:
– Suppose LFPR = 65% and unemployment = 6%.
– Employed = 120m × 0.65 × (1 − 0.06) = 120m × 0.65 × 0.94 = 73.32 million.
– Adjusted dependency ratio = 50 / 73.32 × 100 = 68.2% (shows a higher burden once non‑workers are excluded).
Now account for productivity:
– If average productivity per worker is 1.4× the baseline, effective workers = 73.32 × 1.4 = 102.65 million.
– Productivity‑adjusted ratio = 50 / 102.65 × 100 = 48.7%.
Interpretation pointers (practical checklist)
– Check age cutoffs: many analyses use 15–64, but local retirement ages and child-labour norms may suggest different bands.
– Prefer employed population or “effective workers” to raw 15–64 counts.
– Combine ratios with: LFPR trends, unemployment, hours worked, and occupational composition (part‑time vs full‑time).
– Include fiscal measures: public pension expenditure (% of GDP), health spending by age cohort, and pension system design (pay‑as‑you‑go vs funded).
– Consider demographics drivers: fertility, mortality, and net migration. Small changes in migration can materially affect working‑age supply.
– Use productivity scenarios: productivity growth can offset demographic pressures; test low/medium/high productivity paths.
– Look at household balance sheets and private savings; public ratios show fiscal exposure but households also self‑insure.