1. No category

Religions, Fertility, and Growth in South-East Asia
David de la Croix1 and Clara Delavallade2
1 IRES,
Universit´
e catholique de Louvain
2 IFPRI,
Washington
December 16, 2014
Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Research Question
Many religions are supposedly pro-natalist
In most models of the long-run (Malthus, Solow, Lucas), high
fertility is detrimental to growth
How big is the effect of religion on development through its effect
on fertility?
How to identify the possible effect on fertility ?
How to go from the micro to the macro implications ?
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Literature
Microeconometric literature showing some effect of religious
affiliation on fertility or education
Adsera (Pop. Stud. 2006), Berman et al. (NBER, 2012),
Becker and Woessmann (QJE, 2009), Baudin (2014),
Chab´e-Ferret (2014)
do not draw quantitative macro consequences
Growth/development models with religion
Cavalcanti et al. (2007, ET), Strulik (2014), Cervellati et al.
(2014)
Show how religious norm emerge and affect preferences
do not identify the size of effect using microdata
do not particularly focus on fertility
Growth empirics
Cross-country regressions (Barro and McCleary, AJS, 2003)
are not robust (Durlauf et. al. JAE, 2012)
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Our approach
Full journey from micro estimates to macro simulations
a) Auxiliary model. Estimate empirical relationship between
fertility and parental background: religion and education from
census data.
b) Structural model. Micro model of the household. Identify
preference parameters to fit the findings of the auxiliary model.
c) Counterfactual analysis with growth model.
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Our sample: South-East Asia
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Religious Composition
South-East Asia: Common geographical and cultural influences
Different religions present in same region of the world
Best place to distinguish country fixed effect vs religion fixed effect
Main religions in each country:
Cambodia
Indonesia
Malaysia
Philippines
Vietnam
Thailand
No
Buddh.
0.7
0.3
80.7
0.1
96.9
1.1
24.3
0.1
10.8
95.4
Hindu
2.4
6.7
Muslim
Cath.
2.1
87.1
54.2
4.5
0.0
3.7
0.4
2.3
2.6
83.4
5.4
0.7
Prot.
5.8
10.6
0.5
Growth
1950-08
2.9
3.0
3.3
1.7
2.6
4.2
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Data
Census data (IPUMS international, various years)
Complete fertility Ni of married women aged 45-70,
mother’s education Eif , father’s education Eim ,
mother’s religion Rfi
census fixed effect Ci
birth year fixed effect Bi
Five levels of education: (i) No school, (ii) Some primary, (iii)
Primary cmpl., (iv) Secondary cmpl., (v) University cmpl.
→ 25 types of couples Eif × Eim
Seven religions Rfi : No religion, Buddhist, Hindu, Muslim,
Catholic, Protestant, Other
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Methodology
Pooling different censuses allows to interact the education
dummies with the religion dummies
→ Allows for differential effects of religion depending on the
education level
Cambodia
Indonesia
Malaysia
The Philippines
Vietnam
Thailand
1900
1910
1920
1930
1940
1950
1960
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Distribution of Education
Educ.
Women
(i)
(ii)
(iii)
(iv)
(v)
Total
(i)
No
schooling
155,029
13,978
2,235
100
17
171,359
(ii)
Some
primary
89,151
109,132
16,874
1,058
117
216,332
Education Men
(iii)
(iv)
Primary Secondary
completed completed
24,542
1,392
38,078
4,930
55,567
14,065
5,234
12,779
936
3,568
124,357
36,734
(v)
University
completed
113
541
2,097
3,834
6,581
13,166
Total
270,227
166,659
90,838
23,005
11,219
561,948
Note: unweighted
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Auxiliary model
A. Benchmark:
Ni = β1A Ri + β2A Eif × Eim + β3A Bi + β4A Ci + A
i
Eif × Eim : vector of 25 categorical variables
B. Effect of religion varies by education level:
Ni = β2B Ri × Eif × Eim + β3B Bi + β4B Ci + B
i
Ri × Eif × Eim : vector of 7 × 25 = 175 categorical variables
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Estimated Fertility by Education groups
Model A - Fertility of Women born 1945 in the Philippines (No relig.
Eim
f
Ei
(i)
(ii)
(iii)
(iv)
(i)
4.25 + 0.91 4.78 + 0.91 4.66 + 0.91 4.54 +0.91
(ii)
4.90 + 0.91 4.82 + 0.91 4.70 + 0.91 4.33 +0.91
(iii) 4.26 + 0.91 4.65 + 0.91 4.36 + 0.91 4.09 +0.91
(iv) 4.23 + 0.91 3.89 + 0.91 3.52 + 0.91 3.42 +0.91
(v)
3.28 + 0.91 2.99 + 0.91 2.75 +0.91
+ Catholics)
4.16
3.77
3.39
3.12
2.83
(v)
+ 0.91
+ 0.91
+ 0.91
+ 0.91
+ 0.91
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Effect of Various Religions
Buddhists
Hindus
Muslims
Catholics
Protestants
Other religions
fixed effect
0.331
0.218
0.560
0.914
1.040
0.675
s.e.
(0.0725)
(0.1127)
(0.0907)
(0.0461)
(0.0803)
(0.1113)
All religions increase fertility significantly (except Hindus)
Muslims
Catholics
>
Buddhists
Protestants
>
No religion
Hindus
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Fertility according to Model B
Model B - Fertility of Women born 1945 in the Philippines (No relig. + Catholics)
Eim
f
Ei
(i)
(ii)
(iii)
(iv)
(v)
(i)
5.58 – 0.43 5.71 + 0.36 5.01 + 0.64 3.83 + 1.34
(ii)
4.92 + 0.90 5.22 + 0.69 4.72 + 1.06 4.18 + 1.13 3.67 + 0.88
(iii) 3.78 + 1.56 4.31 + 1.49 4.01 + 1.29 3.65 + 1.18 3.13 + 0.89
(iv) 5.08 – 0.27 3.37 + 1.19 3.22 + 1.13 2.88 + 1.16 2.58 + 1.21
(v)
2.40 + 1.45 2.09 + 1.42 2.43 + 0.99 2.31 + 1.01
⇒ The gradient of the relationship fertility/education depends on
religion
Catholicism prevents fertility from dropping fast when education of
parents rise.
→ accounting for interaction terms Eif × Eim × Rfi is important.
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Other religions
Model B - Philippines - Fertility of Women born 1945 (No relig. [ Catholic ] [
Buddhist ] [ Muslim ])
Eim
f
Ei
(i)
(ii)
(iii)
(iv)
(i)
5.58a [– 0.43c ] 5.71a [+ 0.36c ]
[– 0.30]
[– 0.26b ]
a
[– 0.86 ]
[– 0.44b ]
(ii)
4.92a [+ 0.90a ]
[+ 0.49b ]
[+ 0.50b ]
(v)
5.22a [+ 0.69a ]
[– 0.15c ]
[– 0.56a ]
(iii)
4.01a [ + 1.29a ]
[ + 0.37b ]
[ + 1.81a ]
3.65a [ + 1.18a ]
[ + 0.44b ]
[+ 2.41a ]
(iv)
3.22a [ + 1.13a ]
[ + 0.73a ]
[ + 1.88a ]
2.88a [ + 1.16a ]
[ + 1.16a ]
[+ 1.94a ]
Here too, the effect is more important for educated categories
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Robustness
– Check that father’s religion is correlated with mother’s religion
– Endogeneity of religion ? Use grand-mother religion instead
– Impact of religion country dependent? mean effect - jacknife
2.0e+04
0
Density Distribution of Fertility:
Frequency
4.0e+04
6.0e+04
8.0e+04
– Poisson or oprobit instead of OLS
0
10
20
30
Children ever born
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Model of the Household
max
st ,nt ,et ,atf ,atm
s.t. ct
η
ln(ct ) + σ ln(dt+1 ) + γ ln nt ht+1
= ωhtf (1 − atf nt ) + htm (1 − atm nt ) − st − et nt hT
dt+1 = Rt+1 st ,
ht+1 = µt (θ + et )ξ ,
q
1
atf atm .
nt =
φ
γ:
η:
ξ:
θ:
σ:
φ:
taste for children vs own consumption
weight of quality
return on education spending
exogenous level of public education
psychological discount factor
time cost parameter
(1)
ω: female wage
1: male wage
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Time allocation
The maximization problem can be decomposed into two steps.
First, for some given number of children, parents allocate their
time efficiently:
min (ωhtf atf + htm atm ) nt
atf ,atm
subject to (1)
This cost minimization problem leads to the following optimal rules
(for n < 1/φ):
s
s
m
htm
h
ωhft
1
t
2 2
f
m
φnt ,
>
φ
n
,
a
=
=
φn
,
a
if 2 2 >
t
t
t
t
hm
φ nt
ωhtf
ωhft
t
hm
1
if t f > 2 2 ,
atf = 1,
atm = φ2 nt2 ,
φ nt
ωht
hm
if φ2 nt2 > t f ,
atf = φ2 nt2 ,
atm = 1.
ωht
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Solution to household problem
st =
If
σ
(ωhtf + htm )
1+σ+γ
ωhtf htm
et
nt
>
=
=
θhT
2φηξ
2
then
2φηξ
p
ωhtf htm − θhT
,
(1 − ηξ)hT
p
(1 − ηξ)γ(ωhtf + htm ) 2φ ωhtf htm + θhT
.
1+σ+γ
4φ2 ωhtf htm − θ2 hT 2
else
et
= 0,
nt
=
γ(ωhtf + htm )
p
.
2(1 + σ + γ)φ ωhtf htm
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Identification
Rise in γ
Drop in η
n
n
5.5
5.5
5.0
5.0
4.5
4.5
4.0
4.0
3.5
1.0
1.2
1.4
1.6
1.8
hf
3.5
1.0
1.2
1.4
1.6
1.8
hf
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Possible effects of religion
∃ 2 effects we can identify by looking at fertility
Pro-child (γ ↑): leads people to put more weight on children
(number & quality) . vs. own consumption.
be fruitful and multiply (Gen 1,28):
‫ּפŸרּו ּורְבּו‬
Pro-birth (η ↓): leads people to put more weight on number
children vs. other goods.
Abraham, father of a multitude
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Spending on Quantity and Quality
A pro-child religion (high γ) leads to more spending of the two
types, while a pro-birth religion (low η) redirects spending from
quality towards quantity:
γηξ
et nt hT
=
for θ = 0
f
m
1+γ+σ
ωht + ht
p
γ(1 − ηξ)
2φ ωhtf htm n
=
for θ = 0
1+γ+σ
ωhtf + htm
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Structural estimation - Parameters fixed ex ante
1 period = 30 years
hT : f, secondary completed
Wages by education level: estimation for the Philippines (Luo &
Terada)
hf
hm
(i)
1
1
ξ
ω
φ
σ
(ii)
1.035
1.065
(iii)
1.07
1.13
(iv)
1.46
1.37
0.33
0.75
0.075
0.99120 = 0.3
(v)
2.16
1.86
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Min. distance estimation
XX
min
θ,γz ,ηz
z
ˆi,j,z − n? [θ, γz , ηz , hf (i), hm (j)])2 .
pi,j,z (N
i,j
No relig.
θ
Model B
Catholic Buddhist
0.053
Muslim
(0.0021)
γz
ηz
0.684
0.763
0.659
0.702
(0.0107)
(0.0771)
(0.0554)
(0.0094)
2.105
1.918
1.902
1.707
(0.0513)
(0.0598)
(0.0528)
(0.0711)
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Pro-birth and Pro-child Religions
0.25
Pro-child (D+g)
0.2
g (1-h x)
weight
on
quantity
Pro-birth (D- h)
Muslims
0.15
Catholics
Buddhists
Non religious
0.1
0.1
0.15
0.2
g h x: weight on quality
0.25
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Macro Model
Effect of these differences in preferences on long-run growth ?
BGP:
ht = htf = htm = hT
Externality:
µt
hˆt
= µ hˆtκ (1 + ρ)(1−κ)t ,
= htτ hT
1−τ
.
Allows for endogenous growth (κ = 1) and exogenous growth
(κ < 1)
Production:
Yt = AKtε L1−ε
t
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Equilibrium
Lt
=
√
√
ωht (1 − φn/ ω) + ht (1 − φn ω) − et nt hT Pt ,
Pt+1 = Pt nt /2,
Kt+1 = Pt st .
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Corner regime
When human capital ht is low, economy is in corner regime with
et = 0.
Proposition. [Religion in the corner regime]
In the corner regime, a pro-child religion (∆+ γ) has a negative
effect on income per capita. A pro-birth religion (∆− η) has no
effect beyond making the corner regime more likely.
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Interior regime - growth
Proposition. [Growth in the interior regime]
If
√
2ηφξ ω > θ
the long-run growth factor of gdp per capita is:
√
2ηφξ ω − θ
g =µ θ+
1 − ηξ
if κ = 1, and g = 1 + ρ otherwise.
Corollary. [Religion in the interior regime]
A pro-child religion (∆+ γ) has no effect on long-run growth. A
pro-birth religion (∆− η) permanently affects the long-run growth
rate in the endogenous growth case (κ = 1).
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Interior regime - income
Proposition.[Religion and income]
When growth is exogenous(κ < 1):
A pro-child religion (∆+ γ) lowers the long run income per person
ˆ A pro-birth religion
yˆt through physical capital accumulation k.
−
(∆ η) lowers the long run income per person yˆt through human
ˆ
capital accumulation h.
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Macro parameters
Parameters
τ
κ
ρ
µ
ε
A
1/10
0 or 1
2%
g = 1.0230
1/3
(1 − ε)AKtε L−ε
t =1
Initial conditions: ht /hT = 0.3
Kt such that capital/labor ratio = steady state
30 / 36
Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Hypothetical countries - endogenous growth
t=1
t=6
nt
θ + et (% gdp)
st /((1 + ω)ht wt )
Lt /(Pt ht )
yt
annual growth
nt
θ + et (% gdp)
st /((1 + ω)ht wt )
Lt /(Pt ht )
yt
annual growth
No religious affil.
5.36
4.14%
15.10%
1.15
1.28
3.07%
3.73
10.5%
15.10%
1.18
42.50
2.25%
Catholics
5.75
4.39%
14.52%
1.10
1.21
2.96%
4.36
9.53%
14.52%
1.12
24.88
1.84%
Buddhists
5.23
4.06%
15.29%
1.16
1.31
3.11%
4.00
8.05%
15.29%
1.17
26.38
1.81%
Muslims
5.45
4.20%
15.04%
1.14
1.26
3.05%
4.67
5.50%
15.04%
1.14
15.48
1.44%
NB: only difference across hypothetical countries is η and γ
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Hypothetical countries - exogenous growth
t = 1 (et = 0)
nt
yt
annual growth
No relig.
4.57
0.95
2.04%
Catholics
5.09
0.89
1.92%
Buddhists
5.23
0.96
2.06%
Muslims
5.45
0.92
1.98%
t = 6 (et > 0)
nt
yt
annual growth
3.12
29.75
2.14%
4.11
23.98
2.09%
3.93
26.17
2.08%
4.54
21.79
2.04%
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
Countries’ growth
countries’ growth rates
data
1950-80
1980-2010
endogenous
t=1
t=2
t=3
growth gaps
ThaInd-Phi
-Phi
Tha-Ind
Ind
Mal
Phi
Vie
Tha
Vie-Ind
2.85
3.09
2.88
3.44
2.69
0.81
0.47
4.94
3.87
4.43
-2.38
1.85
1.18
3.62
0.15
2.28
1.02
1.34
growth
3.04 3.06
2.17 2.21
1.80 1.86
2.97
2.30
2.04
3.07
2.52
2.32
3.11
2.34
2.05
0.02
0.35
0.53
0.13
0.04
0.01
0.07
-0.13
-0.25
0.07
0.17
0.26
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
1950-80
countries’ growth rates
growth gaps
ThaInd-Phi
-Phi
Tha-Ind
Ind
Mal
Phi
Vie
Tha
Vie-Ind
2.85
2.88
2.69
0.47
3.87
-2.38
1.18
0.15
1.02
endogenous growth
t=1
3.04 3.06
2.97
3.07
3.11
0.02
0.13
0.07
0.07
data
1950-80
Matches relative performance countries (but Vietnam).
10% to 50% of magnitude is explained by religion.
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Introduction
Auxiliary
Structural
Counterfactuals
Conclusion
1990-2010
countries’ growth rates
growth gaps
ThaInd-Phi
-Phi
Tha-Ind
Ind
Mal
Phi
Vie
Tha
Vie-Ind
3.09
3.44
0.81
4.94
4.43
1.85
3.62
2.28
1.34
2.21
1.86
2.30
2.04
2.52
2.32
2.34
2.05
0.35
0.53
0.04
0.01
-0.13
-0.25
0.17
0.26
data
1980-2010
endogenous growth
t=2
t=3
2.17
1.80
Religion explains – lead of Vietnam ( 1/5 of the difference)
– domination of Thailand over Muslims countries (1/6 of the gap)
Failure: cannot explain the bad performance of the Philippines
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Introduction
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Structural
Counterfactuals
Conclusion
Conclusion
Pro-natalist religions can or cannot damage growth, depending on
– the stage of growth
– whether they are pro-child (∆+ e, n) or pro-birth (∆− e, ∆+ n)
One can identify these effects by looking at how religion and
education interact in explaining fertility
From South-East Asian censuses, Islam is the most pro-birth while
Catholicism is the most pro-child
Account for 10% to 50% of cross-country growth over 1950-80,
and 15% of the gap between buddhists and muslims countries over
1980-2010.
With secularization, one may think that these effects will be
weaker in the future
36 / 36