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OCR for page 34
~ ~ ~ Is ~ ~
designing ~ Isis of
manage, and Brsl ad second bind Abed the allowing:
. .
~ wbal types of models ~ A~i~me palings of s~i~mpTe counts of events,
~i~ AWNS ~ ~ - ~ ~ ~S~ ~$ ~ ~
~C
,
boa 10 i~n1~5 time patents of change, enter Conic ~1~ into
models. and control ~r secular cabbies Abe Smithy ~C1 file demos
Magic outcomes; ad
~ Bathe ~ 0011~0 control far individual cbar~1eri~stics off Women ad
chlld~n.
Each of obese mnics is addressed bellow.
at.
Tb~is chapter also desscribe$ the
Noses of mandate and f~rtilil~y and of mo!~al~ily and discusses hypothesis
~R ~ _ ~
~
TYPES OF MODELS
Tb~id~nt:ity 1be~sbort-ru~n enacts of economic variation on demographic
out!come,, He would ideally use long time series of both economic and
demographic data and a11e~mpllO ascertain sim~il~ri1:ie~s~i~n patterns of charge.
TVe~ba~eindeed been able 10 assemble lime series ofeconom~ici~nfonnal~ios
Agatha shadow levelfb, our seven study counties (see Appendix A),bulin
most developing countr~ie$,and in sub-Saba:ran A Urchin p~icular.reliable
time series are not available on~marr~ia~es, bidbs, or deaths Vi1~1Fegistra
OCR for page 35
tion systems 1ba1 decoy Saab demographic events ~ ~none~isenl~ or operate
only plainly' and 1~ baas not gem periodic Surveys or censuses of
su~sci~en~tly good quells and I ~pp~~pd~ queEsti0~s ~r us lo piece
10~e~r lime Writes.
6~u~n~e~ly, ~tbe Demog~b!ic add H~e~1b Sues (DOSS) conducted lion
1bb late Pesos in Bee coun~ies~th~e brave cb~os$en ~r sandy Decide sump
ciao i~i~v-iduAl~l~e~el~ Ion. so Bat He cab ~1~ in time ~ Ins
5fS~1 m~iage~ beg Chilean $ births, ad bar chl~l~n'~s degas ~ In base
surveys, women aged 15-49 Pierre asked i~ut~tbe~i~r dews softens into [~1
manta union, Eta dales of Me bibs of ~ ~eir~i~chil~n, able ages gala Edema of
such as education. ~Sucb survey dare on ~i~ali~E~odr~p~os~es. groove
1bi.ng, only a limited number of de~ogr~h#d ~so~utc~s scats be s~ludi~d~; for
example, no iron is av~l.ible on adult morality. also, We ~ am
.~, . ~
acted by flee ~usu<~ problems Of Calls. c~rs.~.~s~soci~l~d limb ~t~~sreclive
dale. popover is Dame Ois~s~s. the c~o~mro~sl~on 01 women an~ c~lluren Elan
.. . ^
1be Consoled awe sexes abodes soss~ must use ~ multi ap-
~ac~b tab tams imp c~0~s~i~io#~tbc~expos~u~e~bf ~e~0~= or child to
Me risk of Me demonic outcome fiats Barb c~e~d~ Scrod. Stab ~ mu~l~-
v~^ ~~b also bag Me idv~~e Of ~ ~ov~id~i~q anion on Me
The basic appnDac~b~e~se~sfor~!lfb~r~of~fhesdd~mo&~aph~ic~ou$~io~6s~i~s
estimate 11~ tables widb Regressor
Obese regressors~i~nclude the Scot
nomadic vadable~s of conce~i,~as~el1 As~con~o~l~s for~samplcEcon~po~s11ion,
Limb ~ili~be discussed later ~For~maniage~,~rsl bi ~ ,~a~d~second bi age
me analyze file probibi.lib~e-s~sof events~oc~ni~g by 6~in~gsa d!i~scne~1ime
bazerd~ modd
OCR for page 36
*
go
aged ~ yam.
~~c ~ ~ S#-~ 3~
in Abut years Bob up of e!xpo$u~ Bar each coma.
gad ~ ~ ~ I I, ad
he use ~ di~6c~~dme~ b=~d!~del ~ pastime ~ eats of m~~congmic
#~ ~ massage, ~ ~o discuss ~ ~ nex1 secd~-
Tbc ~ co-~ilali!on is e~s$en~1~y Me Same Try We =ilys~i~$ of 5TS1 and
acted births; but Air Me analysis of child Mali me usse moan as Me
unit of anaJy!sis ad cb~ac~= children by! tbei~ge~s I months badge
risks of modify cue c~sider~l~y amp many ~: mocha inane ~{S1 year
of life- using monlb~s to !~asu.= both caged lime and 1be length of
exposure to Me risk off dying in He Mission remission models. of child
modality tab beg fit allows us ~ loams more accu~1ely bold eels
Boom to ~e ad of do fin gland veals aging ~h~:~cb cconomsl5c
ECONO~lC Vi~1ABLES AND S~C[LA~ THREADS
In boa 1~ d1~sc~ti~ baas ad Me Poisson models, 1~0 poaches
graphic events and 10 e~stima~ ~1~1ionsb!i~ps bang these Seals Aced Sacs
tUalIonS in mac~ec~omlc 1n~1ca10rs: (l) Time enacts area estimated using
dummy variables 6~ eabb calendar yew gel ~ a lined #ends Id (2) Scot
comic indicators Me Feted directly imp Me ~~s$i~on~s 1b~1 alto ~.:nclude a
are cozened bbob1 C0!~Ol,l~!ng Bar Bed ~d cease Ace do clot
~110 confuse oboe venisons in Me pollen of ove:~ts or sb~o~-1e~.
C~ct$ of economic conditlon$ son these events Aim long cbs~e$ an
society Id Me economy Act do pot die fly ever idle our Koalas. ~ use
only a l~i.n~ mad Aver ~ ~ bi~e~c~o~g~ar~ion b=~= Her bevy
go stung e~oc~li~^ bboul Me owe and Use g:~.v~on 1be co~p~le~il, of
our models, i~nl,~ucin~ ~ bile lea sword fir limit our: ~:re~y
limited Agrees of Madam.
we same ecso~o~mic bibles ~ used far analysis ~ ~mard~s, b:~:~bs,
aged child deaths (see Able 4~1 ~r a list).
devi~io~f~ land ~ y~arfofa do~ a Edge ~ ]~ vita often
economic v~dabie~.:n yearr(~nol~g~, Me p~v:iousyear7-~1~14g one),~nd
the yearbefo:re ~ ~ ~ 2(lagt~o). Tb~is:mod!elisesl~i~m~d separably F
each de~mog:raphic variable,cach economic v~dable,eacb LOUD and,for
as may count -sable.
~_ _ _ ~_ _ _ ~_ _ _ ~_ _ _ ~_ ~r _ ~_ ~
~ ~= ~ ~ ~b## ~t
de Dally (~993) ~ ~ discussion.
praise ti~i~gofu~iO~ ~atk~ in Afica See
OCR for page 37
TABLE:4-1 Economic Variables Usedin
or~li~ An~y~se$ ~ Seven! Subs Icy Counties
~7
,. . .
`~01c
Boned Ghana Kenya ~ Seam Ago Luanda
R~1 COP
~( CAPE
. .
(CDP) X ~X X X X
4_ ~
~X ~X X X X
Was of
to) X X ~ ~X ~%
~08 Output
~ ~X
(^I~')S X
C^oa~OC) ~X
Cog X ~\ X
C6~ (~C=) X
G~uddd ~gas
(~) '^ .X
P~=lcum
~0~)
P~ha ~
(WPP~) X X
~X ~ ~
~ ~ . <
P^8
,
~oa(~OC) X ~X X
,^
~ ,o:~~hd~
~p~.
. ~ ~ ~
~: ~~nl~iq<~ of y~d~l~< ~d $pu~e$ gf -< ~ ~iv~ i~ Sp~ix A.
i~cs~lyp~ic~al~Iy yields be~er ~ts end bec~iuse ~ecoefisc~ichlson ~eecon~i~c
-v~~i~bles can beinte~p~ ed as el~asb~ities,~:i~enibelog~ithm~i!c~nal!~ o~f
~VS di$cu~s~stbis~ ~ _ rin~later!secl:io~ of-tbi~s
. ~. , ~, ~ . ~e ~. _~ ~_ ~^_^~
chap~r
,
, ,
we use1aggea valueS of ~eco~som~ic variables for tbc t~o pre~vi~ous
years, as ~el~1 as ~e Cu~en~t value. because tbc bis~rio~ li~te~u~ and
com mon sense~s~ug~gesiLb~lchangesinlbe~macroeconomy may not tee per
ceived or experieng~d atibe mic~o lev~el for s;~ e time (see Cbap~r 3~.
)4o~ove~ d~ may beso~l.agassocia~d wi~ abiologicalorbob~vior~
~x~e ~)a ~ en ecoeon~csbock;~ e ~s ~and
OCR for page 38
As
~5~ - '?~ ~
~ ges~:~] Be: of ~:~:~e month~s 1:~v tha
inevitably' be I-~:~d'.
~'~,l'lltv wIll almOs:t
I~ ~ ~ Ia~ stmeture ~er ~d000S the de=~es
0t ~ i~ t5~ =~$, SO \\YO d~ec:~d :o =~o t~y 0?~ t~0 ~s m~r
~ y~ and to m~e no I: to test ~r the X: of I'm that
t5->? ~; 091~$ ~6 j0~S l~ ttC CCO~> 636 0~? tS 0t t60 $~0
I?. 3~ :? $) ~n
0~ ~ ~ be: ~ ~ 0~ :0 ~ ~ :0 ~-id 86 i ~ ~ ~ 6 ~ ~ ~ :8 ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ t~ ~ ~ ?9 t ~0:~0 it:
model, rathe~r to= I~c,1~l,~= seVera.l 'economic 1~s at -~: and a!~
_ A:
i~= t~ t~ 00~.~0 ~ l60 p~.~.~\ ~?~ ~ ~ t58t to ~.~: t~.~?5
mp ~ 4c t! ~ m ?-~ ~ :~:~ ~ ar; ~ :~ ~ m a:?~ ;y ~ ase ~ ~ ~ ~ ~ ~ ~ ~ o~ ~ ate d. ~ 5?0
t0~pt tO-Od10?O 0~?8 ~= ~= woul6 5e t??~" ~ 538t
03~ ~ ~: ~l ~$ is: t58t t50~ ~ ~0 0~ ~?0 t: it? ~ ~6 =)
e~:~8 ~ 6390 i08~.6 8:~gK
~{ 870~0 0[ ~?- 000?~: 9-~ 6~3 ~?0~ ~Ot 3~C ~; ~C
=0 ?~t t~t ~ ~:~ - ~6 tt~ 3~??~3 536 t~ 50 ~?~6 ~= ~ 3~\ $~3 0[
0 6~8 6sta ~-r t:he 25 -~?~ pwce6~ng tt~e co?~?7s 0~5
~ ~ ~ ~ ;:;~e :m ~ ;~!: -t ~? ~ ~ ~ ~ ~ ~ ~ ~e pe:~: od ?~: ~ ~ ~ ~ ~ W
were ~m ~ 970 to tt~ V~= t:~ t~0 ?~:~ - ~?\ i~ 0-?~5 00~ - y ~ ~t'W ~$
816~0· iD t5C t36~05 l~ ~t ~ t~3t pt?W?~t ~ {~?~- $~?- t{~0
~=) 0~ [~{ 0305 98~t 0; t~0 .~$ ~6 03~ 0.~?~: :~
CONTROt, VAR:~:~-~S
3l g0~[8l g00?8~ {~ j~0i~g ~0 =:~)?5~5 pi3~ ~?~3 ~60~Wt ?~0
;~:! [~r - - ha:~c t~wr~ st:~c ~ of the ~? ome:~r ~ ~ a?~:~! W i> tt~ \: 880 7 ~ '~ 3~ ~ 0?0
(??~ 0t [~)7 0~?~?~-=6 ~; 0?~= 't0~§~:~W~ 0; ~0 05~¢~[ 0x
amp~1 ~ the~r ag~ - b~:~ o~ ~ - leng~ of pmv ~ ?.~X?5 6~t }~ ~..
~ have contro!~d ~ ~?Wl07$ ~3t a~ct 5a'=~9iW 0~0$?tt 0~?.`
~ &'0 ?~: ~ ~ ~ ~ ~ ~ ~ tt:0 =~? ?~} ~ ~ 8~ ~ ~ ~ ~ ~ t~ ~0 8) ~ $? ~ ~ * ~ ~ ~ ~ ~ ~ :~ ~? ~ ~0 ~ 0??, ~ _
: - {? w : f -fi~cts of~?. th-e probetf:)S?tIe~ o: >urv:~n ~ s~: :~
~ ~ ~e ~ ~ ~ ~ ~ re t: ~ ~ ~ ~ ~ ~ ~ ?~:\ ~ -~l SOr ~ ~: ~ ~ ~ ~ ~ 3~ ~) ? - ~ ~ ~ ~ t~ ~ to ~ 073t ;) ~ ~ 0 ~
~ ~ ~ ~' ?~= ~ tt W 7.~:~ 0[ tt:0 d~m ~ r~h~: ~ ev ~ c~t ~ ~r~ 5~ 00 ?~6 6: ~ ~ ~ tt~ {: ~ t~(
.? ~) ?8i~.(0 0ts>t 61nt~, -?~34.~,6 ~) Ct i);6 ~Or(~))t~9~ ttC ~= ?',,? Ot ~¢ C~t1~~ )(~(
~?~8f33$ =~6 0; *6)ft* 62~$f* tt:33 3,'£~-0 ~[ tl~j~ ~it°£~.= 5079gr33~$ ~2~$` {;S~C,5(S 3),50 ~
O1Nxen cfu*r~ ~;*~:xest \n ec-onom;?0 e~ctS*> some ~o wt~t m~r ~ ~;t* ~ mo~
~ 3?6K3~> t~ ~=, 0t =,; 5i, 873335~ ~ ~ ~\ ~ ~$of 0?~: =~3r.~ : $:~ ?3xt40~\ .~.
~ ~ *l 8~ 64 =.* . ?~) :Sf ?~.~) ~ ~ ~: tf ~ tt t - Y p' C, ~ ~ [. ?= ~ ~ ~ ~ :~ :S .~ ~ ~ C?:~ pOf ~ ~ It; ~ ~ 8S ~ ~ t? ~
cussed I.~.l .
}:~ ~C =~$~:S p~:~6 ~:~ ?~¢ ?~f ~ ~ ~ Q'~:~,: ~f: ~ ~ ~ 6~, ~f:t ~
4~??X g.~? ~S?~~? ~,~f~?-f~; ?~ff ~?~??'.) t??'.x ~i ?~X~*~X i4988~ 8:~ ~y$?¢ at~ ;~7i:,2?~f-$i~= ~; ~0f~
t `~ ??
OCR for page 39
By
:~ ^
tolled ~r any- other actors. ~ experi~ment~d Mob owes c~0~1~1~s tab am
Queenly i~clu~d in models of ~e demographic outcry ~c~onside~d beg.
but Hair inclusion had only m~ina1 enacts on 1be resells about time pal-
te~=s or economic Is. any dramatic dl^re~ce$ in results yielded by
^~ Is.
O~erw~isc, ~t Me sag of Pimp, the results a~ not pond.
He con1~ls Aide Blob we se~pe~m.e~lod ~1~ into 1:WO~ basic scEa16
ries: 1bose tab change slowly over time and Eloise abut may ~ cb=ge rapidly.
IN tbe c~1e~g~0f contra Cage Lowly over times IS On~::1b~ ~3)
Eta education off He
It the Hand in all ~ the demonic ou$c~omes~:~
over age airs all of He study obu~t~ie~s~,~ Omen gab exposure ~ risk of
events in chief edgy yes if abeam ~ply~si~ss~o~ld be d~i~sp~opo~ison~a~l~y leash
changers in tbc demonic bebav:~ors$ kayoed He inclusion o1- a gene
. . · .
violable 1~ our analyses.
~ He camp of Locals ~ ~- City Her time ~ Avow
me Died airs He amorality an~ly-sis. Ogre lathe suit of the previous child
bow to He Sober of Age child ~i~g~!c~on~s~id~re~d~ ~1 may Alps remove
in~1e~0usebold~ heterogeneity and abuts make ~ ~pI~usi~bl~e our a$~sumpcion
of the i~depe~ndc~n~cC of morlili~ of chi~l~d=n of He shame ~mo~ Anon is
be lends ~ Ale p~v~io~s big integer, Ibid cooler He ecus of
0 on child >~
Suppose. for ewe, tbateconom~i~c variables
tc~t~mo~al~ily~i~nd!is~clly~(by~i~!Oue~ncinG~lbsO~durat:ion of be ~p~e~vious~b~b
in~
OCR for page 40
=~ =~ By: sw-~ ~
't'bC ~d~0~t N?r2tK1.~l,;3 Th'0 b38t,0 =~l Crijtt;~S ~C iOg ~
oc£iu,=3,~g, as ~4 ~ ~ 8,
|~ _ At;: ~ ~,~ ~ {N ~ ~ ~ By; i<
~ rS.:i a~ I,
tow ,.0 tt~ 03$g -by =3m3.~ :~ ].8 t~0-~l,]~\ tt3~t ]~6,*~-\t~3,]
6 ~ gamy ~ 'g{\t0~ ~t Char {.8 ~6 3t ~ 8~ ~ ~ * ~ ~t
6 ~ ~S ~ ~ C~ junC ·~0 C[ y03 ~ 3~6 ~ 0~' \~ t~8 ~ ~;0t 0t
~ ~ ~ ~ ~ ~t)~;~ 8~ 03;~0
~ ~ · ~ ,~ ~ ~ Or ~ 0[ 0~Cr10;~ 3880C Hi ~
0~ ~ Sp=~C I;-~t03[5 806~ its ~0 en-Ct O ~C t=06
Tn ~ second s~e :~: ~ =~'ysl's t~ :~:~s of economic tndIcat~
gig :~ ~ ~ ~ trait ~ ~ ~ ~ ~ =~ ~ ~.5 ~ t] ~ Char ~t 0. 0~8 0:[
r "x .x ~
specie ~.~c caten,0=' yearly
:~:s
The ~:~t At- Iast te~ ::n the ~e entail
l~t :~*t
~ ~'0~
~<.~= ~ ~ ~ ts ~e tog=~m ~ ~e firm of ~e =~C x, 1,;~n, dvea..~*
it; ~ I; jilt /~ ~6,205 ~gg¢~ ~= ~ ~ ~ ~ ~ ~ ~ ~ <~ ~
O=~¢ Raw MA ,,,`
~ ~ As mo~l ~,61~h 1S knows as ~ diSc~'=~e ha,73~ =,~}
$; $* l982~ =6 -I Ct ~ I* 35;~;~S ~ ~ ~ apt
:~¢ ;^S 1S 6~y0~ -it ~ ~06~-id* {~60er65, t50 ti=C ~=
x~ a~ assumed ~ heve ~e same e~.~s on ~e Iog owls of ma=~e .a,!
$'~ - ~o seems reaso.~ ALEX- -~e
~$ OO ~ C~tS ~ ~1C l~tS ~8t 8~ ttC=~S p0~
^) ~ 00 ~t 00t ~ ~ ~ ~ Axe x~ ~ Bet ~ ~ ~ ~ ~ 0~6 ~ ~ ~ ~ ~ :~:g~r~, aft: ~ ~g ~ ~
~e p=~m of mam~3,~$ ~ =e unt,1~.ic1,~ to 6,0~ VC3~ ~~xVg ~ ~ (w~r
~ t~ Craft 07 Axe t~x~x=-Di3~ xx; Ax Alp; r(~r°~< t$;3r**~= $~ 3~0 ~ ~t 306 ~t=~=
(~9 ~J¢) Amp ~6 t~\ I'm ttig t~;~[x~) 63,806 ~ tt~ A<< ~ ~$j cc~ ?- 0
: i* A :* 7A* * 3'X'A:*A] 26~30 >0A~.*X*8* ~ i~39 Gil rS C$~* ~t tt ~ 3~A3~\ SO ~ O;; ~ 53-$ x t60
~ ~ ~ ~ ~ ~p $ ~Exit ~ ~x~ ~ (x~ ~ ~ ~ ~ ~ }Cr ~ ~ ~ ~ ok* ~ =6 ~ ~ fix ~ Em* S) ~ O~ ~ SC~ A 76
b(o~h-tnteo~t3;l ;dcr~mom)*
OCR for page 41
~SG,
Tb:i.s modal is es~ma~d using ~ ~eigb~d~ l~o~is~1ic~ areas
~7
~ pi~e~ise~linear age
Seamed fs~ Promos hi. Ulna 1bc maw u~s~ual~app~~b~ 1be c~clent on the
. . .
~1~C! 1,
co~s~nd~n~g dummy (ample for all age ~~ can ~ indexed as Abe
levels of ~ Saks Of meat me co~sspondi.n~ ages. It dons, Aeon
pi~e~:~se~-l~l~ne~!~8bles ~ used eat Client can ~ sited as
the salad ~ Me Edgy dads! Of me me ~b~~ in tba1 d~tio~. Tb~e
~. ~
a~v~nt~e of 1~l!ss~ Repros over me u!sLhI ox lass ~at, abhor 1h~ assuming ~
C~O~S~1 bawd in cabs We categoric tbo hawk -is Rioted 1os incise (~or
~onibl!v by assumed lo base ~6beh Soled beam ~S time of Came
c~b=~ds~dcs of able gown at me time of to sexy But ~ Ads 1~1e
TO Insults Mom models
gu=an~lee that it Has ~levan1 Air past Capes
including educ~l~.on as ~ cony He Spoked only Ruben Hey am subsl~-
A~s mentioned Elmer wage Sable, 1be Isis Ads done steely
far ad ~1~ Gotten. Eileen b~ intense i) the dial ems of
. ~
.. ~ . ~ ~ ~ ., I,
economic amps in tbe~se God.
~ .
.. . , ,,., , , . , a, , , . . ma,
Careen age 10 -Ibsen He Assam exposure lo abbe IS oat mammae also
. . , . at ~!,~ ~ ~ . . ,~ at. ~ ' I ~ ~ , sat !! ~ '! S ~ ~! ~ ~ ~ :!,: A, S~:~,.~!s,
blah braid, add tbb~ti gas of~.~or brsl or$econd~0 add. because
n)~don b.is~ori~es gem nolcollec~d assay of He ARES, He use ~ goings
.. ^
esi~densce atone 12to $pl~itlbe ~lsimplei~to urban and rurhIs ~ pies of
Omen. C~l~e~dy His vocable is impeder as ~ proxy for He ~oman'~s
silence ~1tbe~1imes of male gad ~e-~:rslt~o bibs, butit ads the
U~nfo~u~nale~ly, even tb~is in~fo~nnal~io~ gas not
For He His of facility we consider Sly Best and second blabs
c=~e~umbe=~ofbi~bsdec~line ~pi~dl~y~$bi~nbo~of~:is~n~ascs,and
cau$eof~e$eve~condilion~ilycons~:nts~plied~bi~#o~rbi~b~s
(far en ~ ale. only ~ Roman Ho bas already bad exactly too climbs can
early years of our analysis, ~e~dys~1960$, Abe oldest DIPS response
dC01S, ag~d~45~49 Time of be surveys, Gould bee been onlyin their
sepa~1e~ly because me
.for
early twenties. EVE an~y~ze Brat and second~bi~b~s
~'-
. .
113, . .y
Essex
OCR for page 42
I:?
=~ ^~O ~ ail- ~ ~.
Alerts O D OLO GY FOR AN A~LYS1S O~F~C~HlED!\lO RTALlTY
The procedure ~sedibra~lyzi~g abed mo~ili;l~y.Po~is~so~n ~re~ssion,is
broad S1po~surp~isnE1b~is caso ~n ~gg~gToup~ptchildren~. lain
oar ~odel,~th~e~1~r~l~og~~1~s~0f Be v~r~bb)es ~ <~ assum~d~not ~ vary
Dim at.
TO expected noun Roof evens orders ~6 observed ~r !~ndiv~idu~s
Tab ~ p<~i~gu~l~r set off cb.ar<~leri<1icsin dg~atio~-opexposurc campy a.
mill be 1be buzzed mult~i~pTied be ice c\~osurel~i~e o~fs~ascb i~ndi~id<~{isin
gee mu.
~...
~: . E S .: ~
expels ~ Cameos Ha. ~ f·~ ~ Yields
= ~
. ~ . ~
, ~ a
.~ ,~
as. Ha.
=~ ~ ~ ~ - ~
. ~ ~ ,
co.~rlerlsllcss ~
Then ~i~nclocadthm$add sub+~cl:ing1be Frst~lehn on ~erigbt~ ^~m~botb
. . , ,
SHIM yes Yates .~$:
=+,
The lo~thm of the ~~ tam a.
~ ^ '~ refaced lo as thee
-wet,' wbic~b S1~nsd~rdizesc~ellcount:stb~varyi~ng e!xpos!u!~tim~e~s.
1~ our application, me aroi~nle~sled pd~m~dly in vadal:ions ov~e~r1~i~me.
Tb~u$tbe voidable ofineresliscalendar1:ime;
model to 2110~ for vadalions
Hotbed faders ~l~m~ig~bl conceal or
OCR for page 43
I
cod the unde~dying rel~:ion.Sbi~ps
summed as
bus the model can be
-:= +~7 +
.+~
far ~i~dividuils of cool cbaracleri~stig~s ~ Id age ~ in cale~nd.ac ye a,
obese f iS conti~u~s time to Septum as constant relet of change 1h ~ second
sop of Me ~alysi.s. 1be exacts of to cal~ndar~ye~ dummies. if, me go
Spliced by t~ ems of 1h.c currant Id lagged values of pee of ~tbe eco-
no~n~ic indicalors,as~i~ndi~c ^ d in tab discussion oftbosanal~ysi~s of~nd~ge
^
and ~1e~ili~y.
Jugs as in ~$ physics, we sag slot Instep primarily in the come
cients on 1b~ v~esc10r of ~cpot~} v~ibl~~su~ cb=ges.
1~n our modify morals, we have assumed 1bat the exacts of 1be ecus
Comic and other c-~1 vari~le$ me pr^-i~on~ amass
explore 1be Bestial ~im~rlance of
damp ~ children.
^,~.
aces groups.
consign, me hoe Bled 1be m~-
OCR for page 44
6~C ~~ ~ S~-~\ ~
Wily models sep~=lely far aspic age Sups to He Obeyer 1be ~la~on-
ships bulb economic cb=ge drier by age Soups
They Enemy do n~
guilty, so only the ~ results by He Hat am s~ig~n~i~.c~t and of
interest He Mooned in Cater i.
All noted Lyle He end ~ including ~ number of conl~bl
Me cb=~eri$tics of the child and
then motbe~cs tbat Bean included bean selec~1e~d by ~lti~ng ago pre~li~
OCR for page 45
TABLE 4~2 I~ividuaI-~vel Y=ibbles Used mien He ~ortili~ An~y~sis
for Seven Subs Arcs Coasts
sub
Bo:~a O~b~a Kcoy~a Bipeds
ma. .
USA
~ ~X X X
Old Her X
BE -~
` ~v ~
^ ^ ^
2-4' {bob
p~VlO~S
inl~v~
i+- ~
pi0V!~S
~1
.
X ~X X
~-# ~
^ ^ ^ ^ ^ ^ ^
X X X X X X ~X
2~*4 ~ :m~um
~vious
in~31 ~X~
5+. med~i~m
p=Sv~io~s
i~l~1
:~4 ~
-
^ ^ .^
p=~:lOUS
. .
tbild di~d X X ~X X ~X X ~X
5+ ~
<~io~.s
c~b~ild di~d X X X ~X X X X
~o~caJon ~X ~X X X X X
~m~~
X X
X ~ X X X
~dsti ~X X ~X~
. :
~bnici~
S^b#- X
A~ac~e X
RQ~ ~,
^~ (mon~s~)
^ ~v ~v ~v ~
~^ ^ ^ ^ ^ ^ ^
1~3 ~x X x ~x x ~
<-9 X \ ~X \ ~x ~x
i~li ~ x
10~S X X ~X
s ~ ^^ `, ~
1 ~^ ^ .
~-35 x ~x ~x x x ~x x
3-~47 x x x x x x x
48~39 x ~x ~x ~X x ~x
~ ~gi-.
OCR for page 46
~ R6~ ~ S~-~ ~^
not dir s~ubst~tially ~l~e~e~n ~modeI:s Limb and about these con-1 vari-
~les. Me ~ cams in which hey do ~ Coned in ~ 5.
sis Ale ~ i~nleres~d ill Me di~=ntia1 enacts of economic togs its urban
and ~ra1 Baas. ACCOFdinG1/ abed possible (cabana, ~Nig~da. Send and
~go), He at models SC1S IA~ Tbe nulltypolb~sis~is~not~nd.8
2. Tbejoints~ig~Oc~nco of~ncludib~lh~especiC~ccilenda~ye~ref~cls
butnot~.d Ace. Tbe nullbypotbes~lsis no year-lo-~yearvariat~ion.
3. The joint sign~iOcan.ce of~ncJudis~ 1be your eD>c1$ when 1be good
term is also incl~uded.7 Tag nullhypo~esI$is no year~10~year V~d~li~O~ net
of He hand
.
Tbe estimated trend coefficient and 1be probability values for tbe above
~ree~signi~c~nce test a=~pres.en1~-d in He ~rstlibl~e for each comely in
Cbapte~r3.
Also presenled~cm 1be ~rststag~e of He analysis arc graphs for scab
~,~ ~.^~-
cha~ He y-~to-year variation in He patted values of to dependent:
vadab~le of He particu1areq~uatl~on,based onlbe models used 10 COndUC1~ 1h~
~c ~c~$ of our albeit is on v=~1ion around mad anger ~n the mad itself Us, He
. , .
trend cs~ti~a~s silver i~n this ream s~bould :no1 n~$sz~1y ~ if &$ ~$1 retime of
un~rl~y~ing d~Eog~=phic oboe. Sag ^p~nd:ix B air a discussion off tab data quality i$S~CS
. . .
~nvo~ve~.
9Wbcn t~ wand is lncl~d~d, one of :~he c~l~n~yc~ dummy v~ri~lo$ is omitted
OCR for page 47
second 1estlisled above. These Diced values are no~nilized
~7
~ as_ .~ ~ ~ _ _ ~ ~ ~ ~
Is ~ #2 -~~ Van ^~ ~ ~ ~ ~ Its
zero. Similar grabs of Me ye=~lo-ye~ variation of Me novelized values
of Me log~i.~ms of Thai gross domestic product (ODP) per coin am pa
sensed far Web county, so ~ a visual comp~i~son of v~alion of Me
economic i~ndic~10r Andy of 1be .dem~o~ic ou~dmes can be ma~de.l° lain
, ~ ~ e ~ ~ ~ . ~
gel cases of mat and Jollily. in blab We priced values a~ of the
log odds ofibe events occupies, positive con~1~lon of tile palmers is
expec~d~tbatis,i~provome~1sin economic conditions a~ expec~dio be
assoc~i~d ~ inc~asesintb~ probabilities otgelling manded and giving
birth. In 1be case of mo~i~,in Blob the p~di~cted values ~ of the
Iogar~i~ m off the dig of dying, Relive con~l~d~os As expected, tba1:is,
i~p~ovem~nts~i~n 1be economy sod be ss~soc~i~d Aim declinesin child
morud~i1~
In ~esecondstage ofeacb oflhe ~neIys~e~s,~l~ogadlDmsofeconom:ic
~ind~lc~ors and ~e~irlagged values ~ substituted for He c~end~yeareL
ICES in He ~g~s$~ions,~b~1~bconli~n~uctolnc~lude Ace ~nOv~i~b~l~e. Sepa-
~1eequalio~ns ~e~stim~ed fo~reac~b de~mograpb~ic oulcomeine.acb county
byeac~becon~omic~i~nd.icalor Tile j~Oi:~1 signi~canceoflhecoefi~cie~ntsof1be
c~un~nt ~dl~ed~al~es~:of~eacb economic~E~dible bow asa~no;up~hOin
Also~nepo~d each of He coe~l~c~l~e~nlsson :~e~cun~n~1 ~o Egged
econ~om~i~c:indica10rs, Whetter or~nol~the~y are 1~nJ~lv-xC~u~ly slgnlTl~n~1y~
fluent from zero, and file sum of the three coetEcie~nls. The individual
coeficien~lesti~m~ssbould be inle~p~e~te!d limb p:~1care becausetbe esti-
mate~s ~eli~kely 10 benegativel~ycod~l~ted ~i1beocb otber.giventbe~ strong
autocon~l~ioni~nibetimespripsofthpeconomi~c variables. \~eve~beless,
some expl.an~ion of 1be melt of ib~cooficie~ntsisin older. I~nibecase~s
of marriage~nd~:rst~and~second~bi~b~s ~fbre~x~a~pl~e,~ coeficientof~o~o!
~ould~i~!di~c~t:A 100 pe~en!l~in~c=~$e~i~n~e~conomicindic~te~sults
in a 5~oe~ebl~inc~asein ~es~odd$Eof~e~1~orridd origins bir~.l-2 In
{VS gun Dam ~co~-~by^co~n~y ~v~is~ sof~Eec~onomlc conditions
s . , ^ . e ,~^ . , :^ ^ _ __
ore andlbeprese~ta11~0n olive Desalts 01~EOUr 8081yS~ls.
1~r cues tar fib =$uil$ ~ gad \r -6 ad ~!1 spas. as wc11 as ~r
c tall pa, tat As of ~r comity UPS aSt ~ ~ ~ C0~!1~ 'a 811 gags,
. .
1 it could ~ tab ~c epoch Yes Could baa sit ~1$. ovEen if ~c a~ loo
celend~r-ye~ Oat.
^
~Su~o~ ~1 q~ the ~o~babil~ity of 1#vid=~1 ~ aging Mind in byte i, is .10~. Tan
tbc Ads [~/(I ~ if,)] am 0.~111~1 A ~ ~:1 ~ in Be odds to 01167 implies
}misuse ~1 He =~lity ~ IS 6~; = .01~, Den 6~: Could ire to .010~5.
Representative terms from entire chapter:
magic outcomes