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40 At thi s stago, a graphical description of how R and K affect Lhe shap of the u (t) curve by age may fac litate further clarification of our argument. For this purpose, wa need not consider 0 because its ro e is only for achieving consistency between the ui I t) values and the overall u(t) , and not for changing the shape of the u ( tI curve. In fi IjJre 4.1, the base-year u [0) values have the shape of an inverted U-distribution, with its peak in the age-group 30-34. For R=0, t he target year ui ( tI valuns are on a higher curve which is parallel Lo the base year curve. uft) For R = ------ 1, each value of u (0] is multiplied by I+R, u (01 which means that the highest va lues in the base year attain a new high peak, due to proportionate increase in the target year. Such a new high peak may be' neither necessary nor feasible, but wo show it as a limiting case. For R -1, all u t] values become equal. Now, the role of K is to change the shape of the u.[0] curve and tilt it in favour of the age-groups 20-24 and 25 29 in the target year. Such a transformation in tha shape of the curve cannot be achieved by R, because R takes for granted the shape of the u (0) curve with its peak corresponding to age 30-34. Contrary to this, K favours those a ge-g raupe in which age-specific natural ferti lity rates are the highest. Only by such a shift can " e hope to achieve new u 1 (t) values whicI can reduce the number of bi rths at a faster rate than would be otherwise possible. Of course, all such shifts have to be within Limits of feasibility,
j.. :,~ [. it-iftI I. f: urI ier-zCe c Je-.-,i,.:F F:s 0.5 1..5- 1 "9 E .-- , 5 -31 -4 4 5- 9 .4 e= 1 .v"....-/ ,. - . 15i- ' 3'C4 ' 4 i Ul. " % jer 4 1 "jb 1 ' 2,.zCIA F%,,: 3F -k
Page 2 and 3: ~Ty~AD!DhkI Re fe rffc ce LibL1 t-,
Page 4 and 5: 1. INTRODUCTION A dynamic rcLations
Page 6 and 7: 5 rate, and there is no possibi Lit
Page 8 and 9: 5 course, the inputs have to be sui
Page 10 and 11: 7 Age-group 15-29 20-24 25-29 30
Page 12 and 13: 9 Si mi larly, C varies From one ag
Page 14 and 15: 11 This formula enables us to estim
Page 16 and 17: n tura LLy temptes t0 fIx a low CBR
Page 18 and 19: 15 mathematical space, then alL vaL
Page 20 and 21: F iq]u.- r-e .3 1: -FFi . . a,-, -I
Page 22 and 23: 18 possib le, and theoretically pre
Page 24 and 25: 20 Extensive studies made by Coole,
Page 26 and 27: 22 f3 Re lative values of age-speci
Page 28 and 29: 24 Step-1 Use CPS-1901 to derive
Page 30 and 31: 0.84, va Lues for ago-groups be Ir.
Page 32 and 33: aving taken 1981 as tho bae year, w
Page 34 and 35: 30 1 C (0) C (0) C [0) C (0] TFR(t)
Page 36 and 37: 32 As regards the inputs () , the o
Page 38 and 39: 34 would not be fulfi lLed. We can
Page 40 and 41: .36 desirable. However, it is usefu
Page 42 and 43: 38 we hnve chosen a function of thi
Page 46 and 47: 141 which correspond to the ranges
Page 48 and 49: 43 5. APPLICATIO1t TO BANGLADESH AN
Page 50 and 51: 45 Corresponding to each pattern of
Page 52 and 53: 47 for which the relevant formula i
Page 54 and 55: J49 (f] Usa-effectiveness of cont r
Page 56 and 57: 51 At this st ago it would be conve
Page 58 and 59: 53 1986 1991 1996 2001 Total natura
Page 60 and 61: 55 that a fulfi Lmant of the TFR ta
Page 62 and 63: 57 Four patterns of natural fertili
Page 64 and 65: 59 parameter K ha been introducod w
Page 66 and 67: 61 roach 0.9. (vi) Age-specific con
Page 68 and 69: 65 The main conclusions that we can
Page 70 and 71: -r/\rps t- E
Page 72 and 73: +4 Table A.2 Inputs(Natural fertili
Page 74 and 75: Table A.4 Inputs(Natural fertility
Page 82 and 83: Table A.12 lnputs(Natural fertility
Page 84 and 85: Table A.14 Inputs(Natural {ertility
Page 86 and 87: Table A.16 ]nputs(Natural fertility
Page 92 and 93: ,A,.-:, FF7R . qe I:1..' Pafi. 'rr,
Page 94 and 95:
4.5. - I tr-t. :_- -, rl '-: ':1i
Page 96:
10. Join, A. K. and J. B ongaarts,
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