Missing Women and the Price of Tea in China
The Question
Do sex imbalances in developing countries reflect poverty itself — or do they reflect who controls income inside the household?
Why This Matters
Amartya Sen estimated 30–70 million women are “missing” from Asian populations.[2] The conventional explanation blamed poverty. Qian shows it’s not about how much money a household has — it’s about who earns it.[1]
This reframes the entire policy debate. If total household income isn’t the mechanism, then poverty reduction alone won’t fix sex imbalances. Programs must target who earns the marginal dollar.
Figure 1
Fraction of surviving children that are female, by birth cohort
Stylized from Qian (2008) Figure IIIb. Hover over data points to compare values. Before reform, tea counties had fewer surviving girls. After reform raised returns to tea — a female-labor crop — the fraction female rose sharply. This is the DID.
The Identification Strategy
Why This Is Gold Standard
After post-Mao agricultural reforms (1978–1980), returns to cash crops increased. Tea is picked by women. Orchards are tended by men. Different regions had different agro-climatic suitability for each crop. This creates exogenous, geographically determined variation in sex-specific income.[1]
Who Picks What
Source: RCRE National Fixed Point Survey (1993). Hover for details.
56% of tea laborers are female. Tea bushes are 2.5 feet tall — picking requires careful plucking of tender leaves. Women have absolute and comparative advantage.
62% of orchard laborers are male. Sowing requires digging holes 3 feet deep. Height and strength yield a comparative advantage for men.
The Crucial Separation
Because suitability is determined by geography and climate — not household behavior — Qian gets variation in female income (holding male income constant) and male income (holding female income constant). This separation is everything. It’s a differences-in-differences design using reform timing interacted with crop suitability.
Results
Holding total income constant:
Figure 2
Effect of $7.70 income increase on child outcomes, by gender of earner
Stylized from Qian (2008) Tables III–V. Hover over each row for interpretation. The asymmetry is the entire finding: it’s not about how much — it’s about who earns it.
When Female Income Rises
Survival rates for girls increase
Education for all children increases
When Male Income Rises
Survival rates for girls decrease
Education for girls decreases
No effect on boys’ education
Increasing annual adult female income by US$7.70 (10% of average rural annual household income) while holding male income constant increased the fraction of surviving girls by one percentage point and improved educational attainment by approximately 0.5 years (Qian 2008, Tables III–V).[1] Critically, an increase in the value of all cash crops — those not especially favoring male or female labor — had no effect on sex-specific survival or educational attainment. The effect operates through the change in relative income shares, not total household income.
Method & Data
Design
Differences-in-Differences
Pre/post reform cohorts, between tea-planting and non-tea counties. County and cohort fixed effects.
Data
1990 Population Census
RCRE National Fixed Point Survey (1993) for labor patterns. Ministry of Agriculture for crop data. Cohorts born 1970–1986.
Instrument
Hilliness of terrain
Tea grows on warm, semi-humid hilltops. 2SLS specification uses geographic suitability as an IV for tea planting.
Key Assumptions & Why They Hold
No pre-trends. Figure IIIb shows tea counties had more boys before reform, fewer after. The DID captures the reversal, not pre-existing differences.
Migration controlled. Migration was strictly restricted in post-Mao China. People couldn’t sort into tea regions in response to reforms.
No sex-selective abortion. Ultrasound technology was unavailable to rural populations during this period. The mechanism is differential neglect, not prenatal selection.
No spillovers. Tea planting had no effect on sex ratios for non-agricultural households in tea counties, ruling out county-level confounders.
The Elephant in the Room
Why Not Infanticide?
The phrase “missing women” inevitably raises the question of infanticide — sex-selective killing of newborns, historically documented in China and elsewhere.[3] It’s the right instinct. But Qian’s paper isolates a different channel: differential neglect.
Infanticide
Active decision at birth. Binary: keep or kill. Historically documented but not what Qian’s identification strategy captures.
Sex-Selective Abortion
Prenatal decision. Ruled out — ultrasound technology was unavailable to rural Chinese populations during the study period (cohorts born 1970–1986).
Differential Neglect ✓
Pattern of resource allocation over early childhood: less food, later medical care, fewer investments in girls. This is the margin Qian identifies.
Post-reform income changes affect survival rates over the first years of life — consistent with nutrition and healthcare allocation, not a binary decision at birth. The smooth cohort trends in the data (see chart above) show gradual convergence, not a step function. The paper doesn’t argue infanticide didn’t happen in China. It identifies a different, policy-actionable margin: incremental household resource allocation that shifts when women control more income.
This distinction is what makes the finding powerful. Infanticide is a moral horror that’s difficult to address with economic policy. Differential neglect responds to economic incentives. That’s the margin where policy has leverage — and where Qian’s identification strategy has traction.
What Would Falsify This
Evidence that reforms changed attitudes toward girls independently of income effects
Gender-neutral cash crops showing the same survival pattern (they don’t — Qian tests this)
Pre-reform trends in sex ratios differing between tea and non-tea counties (they don’t)
Non-agricultural households in tea counties showing the same effect (they don’t)
Migration patterns explaining the sorting of households into tea regions post-reform
Availability of sex-selective abortion during the study period undermining the neglect channel
The Craft
Why This Paper Is Brilliant
It separates total income from control of income
Earlier arguments said poor families discriminate against girls. Qian shows it’s not about poverty — it’s about who earns the marginal dollar. That reframes the entire debate.
It uses geography as an instrument without being clever
She didn’t construct a mathematical trick. She used agro-climatic variation, reform timing, and traditional labor patterns. It’s rooted in how tea is actually grown, who harvests it, and who earns from it. Field understanding, not just econometrics.
The question is simple. The implication is massive.
Do women’s earnings affect the survival of girls? One question that bridges development economics, gender economics, demography, and political economy. All through one design.
It produces policy insight without moralizing
It doesn’t argue culturally. It doesn’t lecture. It shows: if women control more income, girls survive at higher rates. Devastatingly powerful.
Craft Rating
Identification
5/5
Measurement
4/5
Clarity
5/5
Portability
5/5
So What
The Portable Insight
Economic structure shapes demographic outcomes. Macro distortions arise from micro incentives at the margin. The world is shaped not by how much income exists, but by who controls it.
This logic applies wherever intra-household (or intra-institutional) bargaining determines resource allocation:[4] education spending in developing countries, elder care decisions in aging societies, or investment patterns within firms. The question is never just “how much?” — it’s always “who decides?”
The Clean Takeaway
Complexity is not a flex. Insight is the flex. A deceptively simple question, clean exogenous variation, real institutional grounding, and implications disproportionate to the design — that is the craft.
Source
Primary Paper
[1]Qian, Nancy. “Missing Women and the Price of Tea in China: The Effect of Sex-Specific Earnings on Sex Imbalance.” The Quarterly Journal of Economics, Volume 123, Issue 3, August 2008, Pages 1251–1285.
Foundational References
[2]Sen, Amartya. “More Than 100 Million Women Are Missing.” The New York Review of Books, December 20, 1990.
nybooks.com →Author
Nancy Qian is the James J. O’Connor Professor of Managerial Economics & Decision Sciences at Northwestern University’s Kellogg School of Management.
Faculty page →