Religions, Fertility, and Growth in South-East...
Transcript of Religions, Fertility, and Growth in South-East...
Religions, Fertility, and Growth in South-East Asia
David de la Croix1 and Clara Delavallade2
1IRES, Universite catholique de Louvain
2IFPRI, Washington
October 18, 2016
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements
Research Question
In most models of the long-run (Malthus, Solow, Lucas), highfertility is detrimental to growth
Many religions are supposedly pro-natalist
How big is the effect of religion on development through its effecton fertility? [measurement question]
How to identify the possible effect on fertility ?
How to go from the micro to the macro implications ?
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Literature
Microeconometric literature showing some effect of religiousaffiliation on fertility or education
Adsera (Pop. Stud. 2006), Berman et al. (NBER, 2012),Becker and Woessmann (QJE, 2009), Baudin (2014),Chabe-Ferret (2014), Lin and Pantano (2015)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 preferencesdo not identify the size of effect using microdatado not particularly focus on fertility
Growth empirics
Cross-country regressions (Barro and McCleary, AJS, 2003)are not robust (Durlauf et. al. JAE, 2012) 3 / 36
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Our approach
Full journey from micro estimates to macro simulations
a) Auxiliary model. Estimate empirical relationship betweenfertility and parental background: religion and education fromcensus data.
b) Structural model. Micro model of the household. Identifypreference parameters to fit the findings of the auxiliary model.
c) Counterfactual analysis with growth model.
6= literature (either micro-demographic estimates, or growththeories, or cross-country regressions)
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Our approach
We assume religion impacts preferences
→ introduces a wedge in the first-order conditions, modifyingbehavior
Alternatively, one can assume religion impacts householdtechnology
ex: contraception (Lin and Pantano (2015))Services to families, including education (Berman et al. 2012)
Similar wedges would be introduced in the focs. We cannot reallydistinguish between the two “explanations”.
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Our sample: South-East Asia
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Religious Composition
South-East Asia: Common geographical and cultural influencesDifferent religions present in same region of the worldBest place to distinguish country fixed effect vs religion fixed effect
Main religions in each country:No Buddh. Hindu Muslim Cath. Prot.
Cambodia 96.9 2.1 0.4Indonesia 1.1 2.4 87.1 2.3 5.8Malaysia 0.7 24.3 6.7 54.2 2.6Philippines 0.3 0.1 4.5 83.4 10.6Vietnam 80.7 10.8 0.0 5.4 0.5Thailand 0.1 95.4 3.7 0.7
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Data
Census data (IPUMS international, various years)
Complete fertility Ni of married women aged 45-70,
mother’s education E fi , father’s education Emi ,
mother’s religious affiliation Rfi
census fixed effect Cibirth 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 E fi × Emi
Seven religions Rfi : No religion, Buddhist, Hindu, Muslim,
Catholic, Protestant, Other8 / 36
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Methodology
Pooling different censuses allows to interact the educationdummies with the religion dummies→ Allows for differential effects of religion depending on theeducation level
1900 1910 1920 1930 1940 1950 1960
Cambodia
Indonesia
Malaysia The Philippines
Vietnam
Thailand
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Distribution of Education
Education Men(i) (ii) (iii) (iv) (v)
Educ. No Some Primary Secondary University TotalWomen schooling primary completed completed completed
(i) 155,029 89,151 24,542 1,392 113 270,227(ii) 13,978 109,132 38,078 4,930 541 166,659(iii) 2,235 16,874 55,567 14,065 2,097 90,838(iv) 100 1,058 5,234 12,779 3,834 23,005(v) 17 117 936 3,568 6,581 11,219Total 171,359 216,332 124,357 36,734 13,166 561,948
Note: unweighted
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Auxiliary model
A. Benchmark:
Ni = βA1 Ri + βA2 E fi × Emi + βA3 Bi + βA4 Ci + εAi
E fi × Emi : vector of 25 categorical variables
B. Effect of religion varies by education level:
Ni = βB2 Ri × E fi × Emi + βB3 Bi + βB4 Ci + εBi
Ri × E fi × Emi : vector of 7× 25 = 175 categorical variables
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Estimated Fertility by Education groups
Model A - Fertility of Women born 1945 in the Philippines (No relig. + Catholics)Emi
E fi (i) (ii) (iii) (iv) (v)
(i) 4.25 + 0.91 4.78 + 0.91 4.66 + 0.91 4.54 +0.91 4.16 + 0.91(ii) 4.90 + 0.91 4.82 + 0.91 4.70 + 0.91 4.33 +0.91 3.77 + 0.91(iii) 4.26 + 0.91 4.65 + 0.91 4.36 + 0.91 4.09 +0.91 3.39 + 0.91(iv) 4.23 + 0.91 3.89 + 0.91 3.52 + 0.91 3.42 +0.91 3.12 + 0.91(v) 3.28 + 0.91 2.99 + 0.91 2.75 +0.91 2.83 + 0.91
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Effect of Various Religions
fixed effect s.e.Buddhists 0.331 (0.0725)Hindus 0.218 (0.1127)Muslims 0.560 (0.0907)Catholics 0.914 (0.0461)Protestants 1.040 (0.0803)Other religions 0.675 (0.1113)
All religions increase fertility significantly (except Hindus)
CatholicsProtestants
>MuslimsBuddhists
>No religionHindus
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Fertility according to Model B
Fertility of Philip. Women born 1945 – No relig. [Catholic] [Buddhist] [Muslim]
(i) (ii) (iii) (iv)
(i) 5.58a – 0.43c 5.71a + 0.36c
– 0.30 – 0.26b
– 0.86a – 0.44b
(ii) 4.92a + 0.90a 5.22a + 0.69a
+ 0.49b – 0.15c
+ 0.50b – 0.56a
(iii) 4.01a + 1.29a 3.65a+ 1.18a
+ 0.37b + 0.44b
+ 1.81a + 2.41a
(iv) 3.22a + 1.13a 2.88a+ 1.16a
+ 0.73a + 1.16a
+ 1.88a + 1.94a
⇒ Gradient fertility–education depends on religions. They seem toprevent fertility from dropping fast when parents’ education rises. 14 / 36
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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
– Poisson or oprobit instead of OLS
Density Distribution of Fertility:
02.
0e+
044.
0e+
046.
0e+
048.
0e+
04F
requ
ency
0 10 20 30Children ever born
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Model of the Household
maxst ,nt ,et ,aft ,a
mt
ln(ct) + σ ln(dt+1) + γ ln nthηt+1
s.t. ct = ωhft (1− aft nt) + hmt (1− amt nt)− st − etnthT
dt+1 = Rt+1st ,
ht+1 = µt(θ + et)ξ,
nt =1
φ
√aft amt . (1)
γ: taste for children vs own consumptionη: weight of qualityξ: return on education spendingθ: exogenous level of public educationσ: psychological discount factor ω: female wageφ: time cost parameter 1: male wage 16 / 36
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Time allocation
The maximization problem can be decomposed into two steps.First, for some given number of children, parents allocate theirtime efficiently:
minaft ,a
mt
(ωhft aft + hmt a
mt ) nt subject to (1)
This cost minimization problem leads to the following optimal rules(for n < 1/φ):
if1
φ2n2t
>hmtωhft
> φ2n2t , aft =
√hmtωhft
φnt, amt =
√ωhfthmt
φnt,
ifhmtωhft
>1
φ2n2t
, aft = 1, amt = φ2n2t ,
if φ2n2t >
hmtωhft
, aft = φ2n2t , amt = 1.
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Solution to household problem
If ωhft hmt >
(θhT
2φηξ
)2
then
Interior solution:
et =2φηξ
√ωhft h
mt − θhT
(1− ηξ)hT,
nt =(1− ηξ)γ(ωhft + hmt )
1 + σ + γ
2φ√ωhft h
mt + θhT
4φ2ωhft hmt − θ2hT2
.
else, Corner solution:
et = 0,
nt =γ(ωhft + hmt )
2(1 + σ + γ)φ√ωhft h
mt
.
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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): ורבו פ�רו
Pro-birth (η ↓): leads people to put more weight on numberchildren vs. other goods.
Abraham, father of a multitude
A pro-child religion (high γ) leads to more spending of the twotypes, while a pro-birth religion (low η) redirects spending fromquality towards quantity
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Identification
Rise in γ Drop in η
1.0 1.5 2.0 2.5 3.0hf
3.5
4.0
4.5
5.0
5.5
n
1.0 1.5 2.0 2.5 3.0hf
3.5
4.0
4.5
5.0
5.5
n
→ corner regime is key (but well documented, Vogl 2015)
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Spending on Quantity and Quality
A pro-child religion (high γ) leads to more spending of the twotypes, while a pro-birth religion (low η) redirects spending fromquality towards quantity:
etnthT
ωhft + hmt=
γηξ
1 + γ + σfor θ = 0
2φ√ωhft h
mt n
ωhft + hmt=γ(1− ηξ)
1 + γ + σfor θ = 0
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Structural estimation - Parameters fixed ex ante
1 period = 30 years
hT: f, secondary completed
Wages by education level: estimation for the Philippines (Luo &Terada)
(i) (ii) (iii) (iv) (v)
hf 1 1.035 1.07 1.46 2.16hm 1 1.065 1.13 1.37 1.86
ξ 0.33ω 0.75φ 0.065σ 0.99120 = 0.3
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Min. distance estimation
Some parameters are fixed a priori
minθ,γz ,ηz
∑z
∑i ,j
pi ,j ,z(Ni ,j ,z − n?[θ, γz , ηz , hf (i), hm(j)])2.
Model BNo relig. Catholic Buddhist Muslim
θ 0.055(0.0012)
γz 0.674 0.746 0.621 0.704(0.0378) (0.0152) (0.0737) (0.0092)
ηz 2.114 1.943 1.872 1.751(0.0519) (0.0309) (0.0555) (0.0552)
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Pro-birth and Pro-child Religions
Non religious
Catholics
Buddhists
Muslims
0.08
0.18
0.28
0.08 0.18 0.28
g (1-h x)
/(1+s+g)
weight
on
quantity
g h x/(1+s+g): weight on quality
Pro-child (D+g)
Pro-birth (D- h)
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The corner regime
Parameter θ determines the threshold at which parents shift fromno spending in quality of children, to facing a trade-off betweenquantity and quality if children.
Ex: a couple with same human capital, no religion:
h >θ
2√ωφηξ
hT =0.055
2√
0.75 0.065× 2.114× 0.333hT = 0.69hT.
Hence, only couples with human capital at least equal to 69% ofthe human capital of the teacher will invest in education.
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Macro Model
Effect of these differences in preferences on long-run growth ?
BGP: ht = hft = hmt = hT
Externality (here, endo. growth. For exo. growth, see paper):
µt = µ hτt hT1−τ
.
Production:Yt = AK ε
t L1−εt
Equilibrium:
Lt =[ωht(1− φn/
√ω) + ht(1− φn
√ω)− etnth
T]Pt ,
Pt+1 = Pt nt/2,
Kt+1 = Ptst .26 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements
Theoretical results
In the corner regime (no education),A pro-child religion (∆+γ) has a negative effect on income percapita (≈ Solow).A pro-birth religion (∆−η) has no effect beyond making the cornerregime more likely.
In the interior regime (with endogenous growth),A pro-child religion (∆+γ) has no effect on long-run growth.A pro-birth religion (∆−η) permanently affects the long-rungrowth rate.
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Macro parameters
Parameters
τ 1/10κ 0 or 1ρ 2%µ g = 1.0230
ε 1/3A (1− ε)AK ε
t L−εt = 1
Initial conditions: ht/hT = 0.3
Kt such that capital/labor ratio = steady state
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Hypothetical countries - endogenous growth
Initial conditions are such that ht/hT = 0.3. Start in the corner
regime
Only difference across hypothetical countries is η and γ
No relig. affil. Catholics Buddhists Muslims
t = 1 nt 5.31 5.67 5.03 5.46θ + et (% gdp) 4.26% 4.49% 4.08% 4.35%st/((1 + ω)htwt) 15.17% 14.64% 15.59% 15.03%annual growth 3.06% 2.97% 3.15% 3.02%
t = 6 nt 3.93 4.40 4.04 4.69θ + et (% gdp) 8.91% 8.68% 6.42% 5.44%st/((1 + ω)htwt) 15.17% 14.64% 15.59% 15.03%annual growth 2.24% 1.85% 1.71% 1.48%
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Uncertainty surrounding the estimates
10
20
30
40
50
Non
religious
Catholics Buddhists Muslims Non
religious
Catholics Buddhists Muslims
Endogenous growth Exogenous growth
GDP per cap. in the Hypothetical Economies after 6 Periods:Confidence Intervals 30 / 36
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Countries: 1950-80
countries’ growth rates growth gapsVie- Tha- Ind- Tha-
Ind Mal Phi Vie Tha -Ind -Phi -Phi -Ind
data
1950-80 2.85 2.88 2.69 0.47 3.87 -2.38 1.18 0.15 1.02
endogenous growth
t=1 3.02 3.06 2.97 3.07 3.14 0.04 0.17 0.05 0.12
Matches relative performance countries (but Vietnam).10% to 30% of magnitude is explained by religion.
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Countries: 1990-2010
countries’ growth rates growth gapsVie- Tha- Ind- Tha-
Ind Mal Phi Vie Tha -Ind -Phi -Phi -Ind
data
1980-2010 3.09 3.44 0.81 4.94 4.43 1.85 3.62 2.28 1.34
endogenous growth
t=2 2.16 2.19 2.29 2.51 2.29 0.34 0.00 -0.12 0.12
t=3 1.78 1.81 2.00 2.25 1.93 0.47 -0.07 -0.22 0.15
Religion explains – lead of Vietnam ( 1/5 of the difference)– domination of Thailand over Muslims countries (10% of the gap)Failure: cannot explain the bad performance of the Philippines
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Savings
st =σ
1 + σ + γ(ωhft + hmt ),
γ assumed religion specific, σ assumed constant across religions
A) Do differences in γ as identified from the fertility behaviorinfluence the savings behavior?
House ownership as a Function of Theoretical Savings st :
Linear probability modelCoef. Std. Err. t P > |t|
st .6526 .1765 3.70 0.014
Note: N = 510994, R2 = 0.85, Std. Err. clustered by country, Census & yearfixed effects included 33 / 36
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Savings (2)
B) was it reasonable to assume that σ (thrift) does not depend onreligious affiliation?
Linear probability modeldependent variable: residual of house ownership regression
Coef. Std. Err. t P > |t|buddhist -.0768 .0160 -4.81 0.005muslim -.0390 .0280 -1.39 0.223catholic -.0296 .0208 -1.42 0.214
Note: N = 510994, R2 = 0.02, Std. Err. clustered by country, Census &year fixed effects included, Reference group includes individuals with no religiousaffiliation
→ Buddhists are saving less than expected34 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements
Quality of education
Country Math. PISA 2012 Science PISA 2012 et at t = 4Vietnam 511 528 5.8Thailand 427 444 5.1Malaysia 421 420 4.8Indonesia 375 382 4.8Cambodia NA NA 5.1Philippines NA NA 6.4
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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 andeducation interact in explaining fertility
From South-East Asian censuses, Islam is the most pro-birth whileCatholicism is the most pro-child
Account for 10% of the gap between buddhists and muslimscountries over 1980-2010
With secularization, one may think that these effects will beweaker in the future
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Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements
Hypothetical countries - exogenous growth
No relig. Catholics Buddhists Muslims
t = 1 (et = 0) nt 4.62 5.07 5.56 5.1yt 0.95 0.89 0.98 0.92
annual growth 2.03% 1.91% 2.09% 1.95%
t = 6 (et > 0) nt 3.16 4.01 3.77 4.49yt 29.21 23.74 25.52 21.56
annual growth 2.22% 2.13% 2.11% 2.07%
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Robustness to other measures of return to schooling
Country year male femaleprim. sec. tert. prim. sec. tert.
Cambodia 2004 5 3.1 14 11.8 4 16.6Indonesia 2010 9.6 8.7 12.6 12.7 12 12.9Malaysia 2010 7.6 9.3 21.8 6.8 12.3 23.1Philippines 2011 7 6.4 20.1 3.7 6.1 29.4Thailand 2011 2.7 4.6 16.6 1.4 5.9 19.2Vietnam NA
(i) (ii) (iii) (iv) (v)
hf 1 1.21 1.48 2.23 3.76hm 1 1.26 1.60 2.70 4.82
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Pro-birth and Pro-child Religions with High Returns toSchooling
Non religious
Catholics
Buddhists
Muslims
0.08
0.18
0.28
0.08 0.18 0.28
g (1-h x)
/(1+s+g)
weight
on
quantity
g h x/(1+s+g): weight on quality
Pro-child (D+g)
Pro-birth (D- h)
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