An Economic Analysis of
the Demand for Abortions
Marchall H. Medoff
Economic Inquiry; Apr 1988; 26, 2; pg353-359
I. Introduction
• Main Research Question:
– Empirical estimation of the demand for abortions
• Literature Review: the economic model of
fertility control
– Michael, Robert “Education and the Derived
Demand for Children.” Journal of Political
Economy, 1973
II. Theoretical Model
• The economic model of fertility control: a
household choice model
– A household’s fertility control decision is based on
a comparison of the costs and benefits associated
with an additional child over time.
– If the net cost if positive, a woman will engage in
fertility control by purchasing and using goods and
time inputs to reduce the probability of
conception.
– One good (zero probability of conception) is
abortion.
II. Theoretical Model
(Regression Equation)
• Corrections to the equations in the paper
• Population regression equation: in equation (1)
Ai=b0+b1Pi+b2Yi+b3SNGLi+b4LEPi+b5CATHi+b6Wi+b7Mi+ui
• Estimated regression equation: in equation (2)
Âi=-207.78-0.942Pi+0.031Yi+4.194SNGLi+4.456LEPi
+1.207CATHi+18.287Wi+43.775Mi
II. Theoretical Model
(Regression Equation)
• Ai=b0+b1Pi+b2Yi+b3SNGLi+b4LEPi+b5CATHi+b6Wi+b7Mi+ui
– Abortion rate (the number of abortions per thousand
pregnancies) of women of childbearing age 15 to 44 in state
i during the 1980 calendar year (A)
– State average price of abortion (P): b1<0
– State average Income (Y): b2> or <0
– Percentage of unmarried women (SNGL):b3>0
– Labor force participation rate(LEP):b4>0
– Percentage of Catholic population (CATH):b5<0
– States in the far West(CA, OR, WA, NV, AZ, HW) (W):b6>0
– Medicaid funding abortions (M): b7>0
Summary Statistics
Variables
A
P
Y
SNGL
LEP
CATH
W
M
Mean
250.898
213.64
6,407.3
34.158
61.99
20.022
0.12
0.28
Standard Deviation
87.847
43.15
936.338
3.956
4.602
13.806
0.3249
0.0448
Abortion ratios and rates
• Abortion rate: number of abortions per 1,000
women aged 15-44 years
• Abortion ratio: number of abortions per 1,000 live
births
• Figure 1 and Tables:
http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5713a1.ht
m?s_cid=ss5713a1_e
• Figure at the bottom:
http://www.guttmacher.org/pubs/sfaa/texas.html
III. Empirical Results
• 2SLS (IVs) results
• Ai=-207.78-0.942Pi+0.031Yi+4.194SNGLi+4.456LEPi
(1.42) (3.22) (3.31)
(1.74)
(2.57)
+1.207CATHi+18.287Wi+43.775Mi,
(1.50)
(1.74)
(2.12)
R2=0.77, n=50
• Price elasticity of demand:
%  in Q
%  in P

Q P
P Q
 -0.942*
213.64
250.898
  0.81
III. Empirical Results (cont.)
• Compare the results to the hypothesis
– Comply with the law of demand
– Consistent except CATH
• Possible missing variables:
– Education
• may reduce the abortion by increasing the knowledge of
effective contraceptive methods
• may increase the abortion by increasing the opportunity
costs of time
– Aid to Families with Dependent Children(AFDC)
• Corr(Y,Poverty)<0, Corr(A,Y)>0, Corr(A,Poverty)<0
• The effect of income is overestimated
IV. Policy Implications
• Forbidding all Medicaid-financed abortion:
– Reduction of 44 abortions per thousand
pregnancies or a 17.5% drop (262,500/1.5 million)
in the 1980 abortion rate.
• Illegalizing all abortions (assuming the illegal
price is 50% higher) :
– 50 % Increases in P would decrease abortion rate
by 40.5 % (607,500/1.5 million).
• The annual increase in the abortion rate is
likely to be persistent due to high income, high
divorce rates, low marriage rate