No. C2004010 2004-7 No. C2004010 2004 7 16 1
No. C2004010 2004 7 16 2000 1990 1990 2000 ( ),, 2
/ 2000 1990 1990 2000 ( ),, (1952-) 100871 It is not Appropriate to Remove the Birth Spacing Policy Now, and China Needs a Smooth Transition to the Two -Child Plus Spacing Policy Zeng Yi China Center for Economic Research of Peking University and Center for Demographic Studies and Department of Sociology of Duke University Abstract This paper first reviews and analyze the demographic impacts of changes in fertility timing on population growth. Based on the decomposition analysis, we show that the most important factor that contributed to the large decrease in TFR between 1990 and 2000 is increase in age at first marriage and births. Based on these analysis, we discus from four aspects that the loses would be much larger than the benefits to be gained if the birth spacing policy were removed right now, as three provinces did recently. The most serious lose is that once the birth spacing policy is removed now, it would cause heavy obstacles for relaxing the current one-child policy in the near future because allowing the long-time-cumulated and huge number of one-child couples to have the second birth with no-spacing would create new baby boom, which is not acceptable by the policy makers. Furthermore, removing now the spacing policy which is applicable only to couples who are allowed to have two children (which is minority of the population), but the majority -- one-child couples who are sacrificed the most -- will have no 3
benefits; this is unfair. We believe that birth spacing is like a lever, that is useful to move the heavy weight of the current one-child policy. More specifically, the two-child plus spacing policy is the optimal choice of China to modify the current one-child policy. We also discuss our recommendations concerning the smooth transition to the two-child plus spacing policy. Key Words : Birth spacing; Late childbearing lever; Two-child policy 46%-55% 2001 2003 ; ; 1990 2000 22 23 20 20 1.0 21 22, 20 22 20 21 40 22 23 40 2.0 23 24, 23 23 0 4
20 60 (, Ryder, 1964;Keilman, 1994;, 1993 37-40 ) 1998 73 1918-1990 16 1978-1993 - Bongaats and Feeney, 1998; 2000; 2004 0.05 0.1 0.15 0.2 5% 10% 15% 20% (Bongaarts, 1999) 1986 19.0% (2000) - 1997 1987 1989 1990 7.6% 1992-1996 17.8% 2003 2001 1997 1999 11.0% 1991 1984-1987 1987 1984 4.55 32.3% 1991 6 2.6 1995 1990 1992 1992 1990 0.115 35% 1995 2.1-2.2 1.7-1.8 26.5 2050 29 2000 2020 2050 1400 4500 6800 1994 1990 5-6 t i TFRi* ( t) t i ri ( t) t i TFRi () t 1998 * TFR ( t ) i ( r TFR i ( t ) = i t ) < 1 1 r ( t ) i r () t * * * i ( ) i ( ) i ( )(1 i ()) i ( ) * * TFR i ( t ) TFR i ( t) i TFR t TFR t TFR t r t TFR t = = r ( t ) i r () t i 0.1 i 10% i 5 i
A B A B A A B A B 1991 21 2075 2100-6 2075 2092 1991 6-7 1990 2000 1 1990 22.0 23.6 2 2000 30 1990 1 1999 2000 1 2 3+ 1989 1990 N.Keyfitz Applied Mathematical Demography dr r = r u 2 du u rσ 2 σ 2 σ r r 6
32 31.2 30 29.1 29.8 28 26 24 23.6 23.2 24.8 26 22 22 20 1 2 3+ 1989 1990 1999 2000 1. 1989 1990 1999 2000 1 2 3+ 2. 1990 2000 2000 1999 2000 1.22 2000 2003 1999 2000 1989 1990 2000 1990 2000 1990 Preston etc.,2001, 28 1993 31-32 1999 2000 1989 1990 1999 2000 2003 2000 2002 2002 2004 7
1999 2000 1.6 1.7 1989 1990 2.3 1 2000 1989 1990 1. 1989 2000 1999-2000 1999-2000 1989-1990 1.6-0.65-0.4769 73.38% -0.1735 26.68% 1.7-0.55-0.4929 89.61% -0.0576 10.46% 1989 1990 2.3 1999 2000 1.6 1.7 1990 2000 73.4% 89.6% 26.6% 10.4% 2000 1990 1990 2000 1 1999 2000,1989 1990 2.3, 1990-2000 0.05 0.1 0.15 0.2 5% 10% 15% 20% 5% 10% 15% 20% 50%-60% 70%-80% 004 8
, 28 35 (35 34 33 28 ; 2004) 35+ 34 33 28 10+ 9 8 4 35+ ( ) 10+ 9 8 4,, 420 9
35.4% 53.6% 9.7% 1.3% 63.1% 35.6%, 1.3% (, 2003) 63.1% 37.6% ; 62.4% 37.6%,, ( ), 13 15 24150 24-34 24-34 153 0.54 4.27 6.91 2.82 10
700 0.2 6 6 700 20% 140 6 840 840 6 840 840 28 2000 804 0.8595 1.70 1 2 3+ 0.95 0.72 0.03 889 700 11
2006 35 2014 2018 28 2004 8 12 t1 t 2 TFR 2 TFR 1 t2 t 1 2000 1990 g ( x) g ( x) 2 1 t2 t 1 m ( x) m ( x) 2 1 t2 t 1 t 1 t 2 t1 t 2 Preston Heuveline Guillot 2001 28 1993 32-33 12
TFR TFR = g ( xm ) ( x) g ( x) m( x) 2 1 2 2 1 1 x x g2( xm ) 2( x) g2( xm ) 2( x) g1( xm ) 1( x) g1( xm ) 1( x) x x x x = + 2 2 2 2 g2( x) m1( x) g2( xm ) 1( x) g1( xm ) 2( x) g1( xm ) 2( x) x x x x + + 2 2 2 2 m ( x) + m ( x) m ( x) + m ( x) = [ g ( x) ] [ g ( x) ] x 2 1 2 1 2 1 2 x 2 g2 ( x) + g1( x) g2( x) + g1( x) + [ m2( x) ] [ m1 ( x) ] x 2 x 2 m ( x) + m ( x) g ( x) + g ( x) = [( g ( x) g ( x)) ] + [( m ( x) m ( x)) ] x 2 1 2 1 2 1 2 1 2 x 2 = + *.2003. 1991 2000 2003 2.2000.,Vol. 24, No. 1..2002. 2002 3.2003.1990 2000 2003 4.2002. 3.2004. 1990 2004 3, 2003. 2003 5 13
2004..2004. 21. 2004. 2004 1.. 1990. 1990 2.. 1991. 1991 1.2003.. 2003 9. 1993. 1993 Bongaarts, J. 1999. The Fertility Impact of Changes in the Timing of Childbearing in the Developing World. Population Studies 53: 277-289. Bongaarts, John and Griffith Feeney. 1998. On the Quantum and Tempo of Fertility. Population and Development Review, 24 (2): 271-291. Keilman, N. 1994. Translation Formulae for Non-Repeatable Events. Population Studies 48: 341-357. Ryder, N. B. 1964. The Process of Demographic Translation. Demography 1: 74-82. Ryder, N. B. 1980. Components of Temporal Variations in American Fertility. Pp. 15-54 in Demographic Patterns in Developed Societies, edited by R. W. Hiorns. London: Taylor Francis. Zeng, Yi and K. C. Land. 2001. A Sensitivity Analysis of the Bongaarts-Feeney Method for Adjusting Bias in Observed Period Total Fertility Rates. Demography 38 (1): 17-28. 14