Religions, Fertility, and Growth in South-East Asia David de la Croix 1 and Clara Delavallade 2 1 IRES, Universit´ e catholique de Louvain 2 IFPRI, Washington October 18, 2016
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Research Question In most models of the long-run (Malthus, Solow, Lucas), high fertility is detrimental to growth Many religions are supposedly pro-natalist How big is the effect of religion on development through its effect on fertility? [measurement question] How to identify the possible effect on fertility ? How to go from the micro to the macro implications ? 2 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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), 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 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) 3 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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 . � = literature (either micro-demographic estimates, or growth theories, or cross-country regressions) 4 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Our approach We assume religion impacts preferences → introduces a wedge in the first-order conditions, modifying behavior Alternatively, one can assume religion impacts household technology 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 really distinguish between the two “explanations”. 5 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Our sample: South-East Asia 6 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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: No Buddh. Hindu Muslim Cath. Prot. Cambodia 96.9 2.1 0.4 Indonesia 1.1 2.4 87.1 2.3 5.8 Malaysia 0.7 24.3 6.7 54.2 2.6 Philippines 0.3 0.1 4.5 83.4 10.6 Vietnam 80.7 10.8 0.0 5.4 0.5 Thailand 0.1 95.4 3.7 0.7 7 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Data Census data (IPUMS international, various years) Complete fertility N i of married women aged 45-70, mother’s education E f i , father’s education E m i , mother’s religious affiliation R f i census fixed effect C i birth year fixed effect B i Five levels of education: (i) No school, (ii) Some primary, (iii) Primary cmpl., (iv) Secondary cmpl., (v) University cmpl. → 25 types of couples E f i × E m i Seven religions R f i : No religion, Buddhist, Hindu, Muslim, Catholic, Protestant, Other 8 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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 9 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Distribution of Education Education Men (i) (ii) (iii) (iv) (v) No Some Primary Secondary University Total Educ. Women 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 11,219 Total 171,359 216,332 124,357 36,734 13,166 561,948 Note: unweighted 10 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Auxiliary model A. Benchmark: N i = β A 1 R i + β A 2 E f i × E m + β A 3 B i + β A 4 C i + ǫ A i i E f i × E m i : vector of 25 categorical variables B. Effect of religion varies by education level: N i = β B 2 R i × E f i × E m + β B 3 B i + β B 4 C i + ǫ B i i R i × E f i × E m i : vector of 7 × 25 = 175 categorical variables 11 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Estimated Fertility by Education groups Model A - Fertility of Women born 1945 in the Philippines (No relig. + Catholics) E m i E f (i) (ii) (iii) (iv) (v) i (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 12 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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) Catholics > Muslims > No religion Protestants Buddhists Hindus 13 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Fertility according to Model B Fertility of Philip. Women born 1945 – No relig. [Catholic] [Buddhist] [Muslim] (i) (ii) (iii) (iv) 5.58 a – 0.43 c 5.71 a + 0.36 c (i) – 0.26 b – 0.30 – 0.86 a – 0.44 b 4.92 a + 0.90 a 5.22 a + 0.69 a (ii) + 0.49 b – 0.15 c + 0.50 b – 0.56 a 4.01 a + 1.29 a 3.65 a + 1.18 a (iii) + 0.37 b + 0.44 b + 1.81 a + 2.41 a 3.22 a + 1.13 a 2.88 a + 1.16 a (iv) + 0.73 a + 1.16 a + 1.88 a + 1.94 a ⇒ Gradient fertility–education depends on religions. They seem to prevent fertility from dropping fast when parents’ education rises. 14 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements 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 8.0e+04 6.0e+04 Frequency 4.0e+04 Density Distribution of Fertility: 2.0e+04 0 0 10 20 30 Children ever born 15 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Model of the Household ln( c t ) + σ ln( d t +1 ) + γ ln n t h η max t +1 s t , n t , e t , a f t , a m t ω h f t (1 − a f t n t ) + h m t (1 − a m t n t ) − s t − e t n t h T s.t. c t = d t +1 = R t +1 s t , µ t ( θ + e t ) ξ , = h t +1 1 � a f t a m n t = t . (1) φ γ : taste for children vs own consumption η : weight of quality ξ : return on education spending θ : exogenous level of public education σ : psychological discount factor ω : female wage φ : time cost parameter 1: male wage 16 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Time allocation The maximization problem can be decomposed into two steps. First, for some given number of children, parents allocate their time efficiently: ( ω h f t a f t + h m t a m min t ) n t subject to (1) a f t , a m t This cost minimization problem leads to the following optimal rules (for n < 1 /φ ): � � > h m h m ω h f 1 t > φ 2 n 2 a f t a m t if t , t = φ n t , t = φ n t , φ 2 n 2 h m ω h f ω h f t t t t if h m 1 t t = φ 2 n 2 a f a m > , t = 1 , t , ω h f φ 2 n 2 t t t > h m if φ 2 n 2 t a f t = φ 2 n 2 a m , t , t = 1 . ω h f t 17 / 36
Introduction Auxiliary Structural Counterfactuals Further implications Conclusion Supplements Solution to household problem � θ h T � 2 If ω h f t h m t > then 2 φηξ Interior solution: � ω h f t h m t − θ h T 2 φηξ e t = , (1 − ηξ ) h T � (1 − ηξ ) γ ( ω h f t + h m ω h f t h m t + θ h T t ) 2 φ = t − θ 2 h T 2 . n t 1 + σ + γ 4 φ 2 ω h f t h m else, Corner solution: e t = 0 , γ ( ω h f t + h m t ) n t = . � ω h f t h m 2(1 + σ + γ ) φ t 18 / 36
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