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TRANSCRIPT
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An Econometric Model of Aggregate
Agricultural Supply and Demand in Taiwan
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DL= (SL + ML - EL - KL) /POP
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(:3 3, ~ PC 1-1 + (:3 a , 6 T I
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t3 {,,;PLI-1 +t3{,6T, +t3 {,7D lt +t3 4' sD t 2+ t34' 9D3I
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( 14 )
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WI ~**~MZ.lli~~~Mmm.',liJtlJ : b:.k~65.q::== 100
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63 IuIIIIV
64 I]IfirIV
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66 I]1IIIIV
67 I]IIIIIV
68 I1IIIIIV
69 IlL!IfIV
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81.7884.0686.4791.03
85.8186.3694.3996.23
92.2694.6994.8091. 70
93.6899.10
104.40 '95.23
99.04103.22101.43106.37
106.54108.86113.60118.06
127.73 ,122.34129.35136.59
59.7961.4766.4871.23
80.58 ,85.33 .
103.73105.51
110.78122.95117.06108.37 i
109.24103.5499.9799.57
105.26105.02110.13113.57 I
llR.99109.13112.22115.75
112.82110.38104.2098.38
107.07118.63129.04142.02
66.7569.2872.4872.32
79.7281.0183.6485.86
88.7989.1387.63 ,93.03
98.28 ,97.44 I
97.59106.70
115.47114.02 I
114.00 I
123.71
136.00136.57135.08142.20
141.89145.20140.31147.39 ,
154.66158.26158.05 i161.83
56.4954.4460.0874.14
89.5892.4299.00
105.00
103.15102.65103.13104.98
106.05107.40100.6898.73
102.90105.67113.61105.85
109.15117.30119.00123.15
114.41119.61124.46130.34
133.00133.58 '144.05152.22
63.2163.8366.9172.17
81.1683.63
106.74115.59
120.26127.24120.47107.50
110.40103.2797.9096.82
105.20103.95108.17112.94
118.57105.00110.93113.25
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63 I 14384489 2740745 2226117 8568 0.954][ 19015794 5252390 2411701 29954 1.392III 12487661 3312283 2408226 I - 16202 0.851IV 21879285 2466240 2792771 - 9760 1.363
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66 I 12305570 4915622 3616992 7657 1.123IT 18947813 5782153 3926435 946 1.250]If 12584535 5109273 3243323 3614 0.864IV 24055777 4852087 3625704 9192 1.506
67 I 17268551 5519262 3873147 9467 1.122H 17547042 6502861 4228682 13336 1.170111 11855627 5791515 3331947 16318 0.840]V 21224872 5343057 3187436 1119 1.366
68 I 18385132 7210798 4225721 2314 i 1.243n 21484314 7915357 4056732 1555 1.468!II 13545613 6387741 4256082 22941 0.902IV 22915228 7285311 38C6204 6349 1.514
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63 I 8729788 537275 323528 2381 0.573II 8223392 908706 495656 1561 0.550III 6383144 874159 273640 461 0.443IV 6023636 555285 99955 - 675 0.409
64 I 7476727 698103 260226 152 i 0.498II 6491323 750289 108098 2790 0.446III 6825807 943930 125124 1994 0.476IV 9408249 930943 461567 965 0.613
65 I 9885557 774288 478148 58 0.628II 9017943 880347 536835 -2813 0.575III 10032596 1014144 797917 718 0.626IV 11040086 1153221 667559 - 333 0.700
66 I 11560006 1661986 1012931 2201 0.737II 9779029 2136649 891425 3447 0.662III 12262341 1856847 961195 -1874 0.787IV 12378472 1775508 1027808 - 637 0.781
67 I 11044728 1353625 511236 189 0.705II 10915058 1980450 723815 6228 0.718III 12830646 1817842 964723 3912 0.804IV 13482504 1618347 1032627 -3381 0.822
68 I 10590203 1746341 558556 538 0.800n 12048934 ! 2267914 833442 4372 0.780III 15394426 2576781 1105102 1836 0.972IV 16510568 2767307 1000782 -2602 1.048
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.KliJTft~{~·H~~ !m*{¥ifff{l~m~1 ~ ;lilLlI i!z~ [4ij%lJifMfilffii£li! 4ij A §T j!} I A rJ65if.=100. i 4if.Jl2jS.~J:f(It'ii f:i:: 1{*I~.rR
• .~ ,f.', i Ii 1'f g~ i65if.= 100 ! (x) (=f3i:"%~). (x) (=fA)
(PDC) I (PDL) ! (PG) (WG) (IN) (IC)--- ~---------~--'-_.~-~--_._----------~
I62 I 62.09 59.53 100.00 3135.66 2.78 586.81 15315
II 63.95 63.28 100.00 3071.33 3.02 619.39 15384]I 66.45 66.71 115.38 3188.66 2.70 662.49 15452IV 73.23 79.61 115.38 3398.33 3.31 772.21 15526
63 I 84.87 103.93 192.30 4036.33 2.95 861.79 15603II 91.31 102.31 192.30 4224.33 4.03 883.82 15674][ 99.73 116.74 192.30 4640.00 2.82 849.49 15740IV 102.39 128.14 192.30 4793.00 4.44 873.30 15818
64 I 102.89 134.29 221.15 5308.66 2.41 849.77 15890II 102.82 150.74 221.15 5154.00 2.51 893.12 15961]11 103.02 153.05 221.15 5186.33 1.55 914.29 16025IV 103.94 145.31 221.15 5337.33 2.77 918.95 16111
65 I 100.57 107.41 221.15 5617.00 2.75 1002.47 16194II 100.45 103.90 221.15 5578.33 3.21 1049.73 16269III 99.77 95.94 221.15 5763.33 3.09 1073.98 16356IV 99.19 92.66 221.15 5868.66 3.19 1137.97 16465
66 I 99.07 92.51 221.15 6146.66 2.28 1130.06 16556II 97.59 89.05 221.15 6068.00 3.94 1205.60 16633][ 96.80 97.02 221.15 6759.33 2.64 1216.97 16706IV 96.73 103.13 221.15 6541.00 3.38 1315.74 16788
67 I 99.05 112.89 221.15 4895.66 4.01 1302.65 16856II 101.41 116.94 221.15 6830.00 4.06 1395.00 16929]I 102.06 118.76 221.15 7409.00 3.14 1466.08 17009IV 103.74 127.08 221.15 7525.00 3.60 1536.78 17103
68 I 106.26 128.88 240.38 8286.66 5.47 1557.70 17182II 110.91 135.56 240.38 7825.33 4.79 1665.11 172591II 112.51 126.42 269.23 8597.00 4.40 1715.72 17343IV 113.61 119.83 269.23 8695.00 5.53 1789.67 17427
69 I 119.99 135.46 278.84 9659.67 4.75 1906.88 17526II 123.05 148.04 278.84 9058.33 5.36 1997.79 17598n 125.96 162.28 319.23 10114.33 4.63 2065.71 17676IV 127.14 166.05 319.23 10472.66 5.00 2196.32 17751
1{:M*~: .B;~ft+0fr:rt~JIik-~i\ll~+011HJcifj·J:lW.' ~fI#~iIi!<!f.f±~t~; m*ft!illf{fll;jllHiilt-:a~~m~fl1C;il"
~~,~~~~!f.f~~~;~~~~~~JlI1{-~¥B;~*Ifl1C~J:lW.'ffili!<~±~~;~%~~
~oo£li~f:i::1{*~.rR~-~*~.rRn:~¥B;mmB;m1~'~~OO£li:~fI#.*if.ffi'.~~~!f.f.
i*!! ; ~A.JiJf1~-~¥B;1I11B;1iJT1lJ}, D·iIi!<~±f.itt« ; AO-~'i¥F;~~B;)jIf1J}, D'~~±m-Jti1 0
( 21 )
- 63 -
=F5C '~.8JjiJl1*\i( I tj:J~ml"Jl$lJX.§T1~" D~~'±~I·~!
------------ -----
J:
1--------- --------- - -- ---------- -----
J:
---- - -- ---- -------------- ---------- -----.
IPI J:------------
[j'j) J: I
------------~-I-------I~~
[j'j) 1: I_____1 _
!. ~J.lJjJJI1~ I,
i -------1 ----------- ----------
.. ' il=~£f¥j{ijiJull: i =f-5G(KC) (KL) I
__ _. 1_- . _
~;JF.~_$r~ftJ5ttl:l II TJC(EXC) (EXL)----- -- --1----
IPI 1: 1:
- -- - - -------------------- ---------- ----------
1:
-----------1---- --- ---------
---- ----- ------------
A r::t(POP)
( 23 )
j.:)'1:j\;15J§22)Z. RJ"BinJ(;LfJ.,lth:\~rrr :
aY+/3X=V
RC t_ 2
PDC t_ 2
RL t_:
PDLt_s
PC t_ 1
PC t _ :
PL t _1
IN t
SCt SL t_: VlSL t DS t Vs
PCt DB 0
PL t n., 0Y= X= V=
DC t D3t VsDL t T t VsRC t IC t V7RL t PF t VR
MC t
EC t
KC t
ML t
EL t
KL t
WG t
PG t
( 25 )
-65-
- 66-
/,.
0 0 0 0 0 0 0 ~
0 0 0 0 0 0 ~ 0
0 0 0 0 ~ ~ 0 ~
0 0 0 0 ~ 0 ~ 0
...0 0 0 .... 0 ~ 0 0
.,
0 0 .... 0 ~ ~ 0 0
0..... 00...-0 t! 0 ..... 0 0 0 0I
0...0P-.-~ 0 ..... 0 0 0 0 0I
\", /II~
( 26 )
- 67-
.. .. ..... ... ....,Q:1.. Q:1.. c 0.0 Q:1.. 0 0
.,' ... ...... ... ... , "-~ Q:1.. 0 0 0 Q:1.. 0 0 ....
... ... ...... .... ...0 0 0 0 0 0 Q:1.. 0
Q:1.. Q:1.. 0 0 0 Q:1.. 0 0 .. .... ..<:>...
0 0 0 0 0 0 Q:1.. Q:1..
Q:1.. 0 0 0 0 0 0 0 0-
8.......0 0 0 r1 0 0 0 0I
0 Q:1.. 0 0 0 0 0 00-00-......
0 0 0 r1 0 0 0 0Q:1.. 0 0 c 0 0 0 0 I
0-00-......
0 0 0 0 0 Q:1.. 0 0 0 0 0 r1 0 0 0 0I
0-s......0 Q:1.. 0 0 0 0 0 0 0 0 7 0 0 0 o· ,0
0-00-......
0 0 0 0 Q:1.. 0 0 0 0 0 r1 0 0 0 0 0I
0-
8.......0 Q:1.. c c 0 0 0 0 0 0 ..... 0 0 0 0 0I
.. .... ... ...Q:1.. Q:1.. c c c 0 0 c 0 0 0 0 Q:1.. Q:1.. 0 0
~...Q:1.. 0 0 0 c 0 0 c 0 0 0 0 Q:1.. Q:1.. 0 c
... .. ... .. .. ..... ... ... ... ... ...Q:1.. 0 0 0 0 0 O' 0 Q:1.. Q:1.. 0 0 Q:1.. Q:1.. Q:1.. Q:1..
",
11
Q:1..
( 27)
- 68-
~a~~a~~URm'~~~•• 'M.~~~fi&.~~~~X.'M)Jr:ff~!'~a37C~:ltatE±~P1~(main diagonal) z""f1J' Mnlt-1~t::;fi:JM®JB
Ml (triangular matrix) , ~~tlft* ; mJ~A 15~ 16, 19~ 20, '& 21~
~~~S~~ffi~®m~.'~~~~.~~E.H'~M~A.~••••(classical nomaI linear regression) 1l.~~~ (~1) *~.~I!~f*.~
~'1t (homoskedasticity) a3f1!:i~:t'nlt.TI:' ffij~~m:t';fI.'I/Ula3m.(seemingly
unrelated regression) , m~~m:t';j{jlUlz~JilfA®~ill~Xffirm~~m (~
8) 'fflmfi•••~.~.~~~~U.~®~
O.lH
-0.223
O.~O
~T1l!m-H.~t1:'tlAJfl~U1UljU'~.;j.,fl;t~J5EZI!j;j~~!*ffl~tt(l~AZ
jt~ e (~2) ~J~).m:,j".1J,*~~i£~*mrF :
~~I!j;j~:
A15' In SC=15.5314+0,4510 In RC,_2-0.1026 In PDC,_z -(20.35)***(1.41)* (-0.28)
0.1253 In RL'_2+0.063 In IN, +0.2508 Dlt+(-0.84) (0.83) (6.74)***
0.3777 Du+0.5574 Ds,-0.0141 DSt-0.0928/nTt(9.69)*** (14.03)*** (-0.46) (-1.85)
R3=O.93, R2 = O.90 , DW=1.33
tll:~~m~~.~E~~~~r:
(11~:1f'::rJJ:er~1itt!!\:meo
(21~:1f':J1tLfS.l2.Jlk:~~'~p E(ED= 0(31~~~~~f*~~~~~ (homskedasticity)(4)~:1f':J1i1!!t,rJ;7JJ,f§riR(auto-correlation) .11./1 E(el' eJ)= 0 , ( i ~ j )
[5)~~lX X, ~:1I'M~ (non-stocastic) ~~, tEf±fiiItfZ;;;I>:r'n
1 ~ (XI-X)2 t!t~~~~~~1ffR.f'oni=l
ll2 : ;;;I>:!iffJE1H'\'Q{lf«t:li!~j,jHfffjlj • m.~.t~slE::Y~:m!~ • ~f,i)!l1i:-{~m 0
( 28 )
- 69-
jU6' In SL=1.5763+0.5157 In RL,_~-0.0055 In PDLt_~-
(1.25) (-0.02)
0.4491 In PCt_~ +0.8731 In SL t_2+0.1375 D 1 , -
(-0.85) (3.14)*** (1.61)*
0.0209 n., +0.1448 D3t +0.0458 In T t(-0.24) (1.58)* (0.27)
R~ =0.72 • R =0.64. DW = 1.54
m~~l#ii
;>'\17' DC=(SC+MC-EC-KC)/POP
;>'\18' DL=(SL+ML-EL-KI,.)/POP
~3i<f§~
;>'\19' In PCt =0.4752-0.341 In DC, +0.1900 In PLt+(0.74) (-0,94) (1.80)**
0.5477 in IC, -0.4996 In PFt +0.3969 In PC'_l(4.40)*** (-3.21)*** (2.73)***
+0.0457 In T t(1.15)
R2=0.97' R2=0.97, DW=2.16
5'\:20' tn PL, =2.9826-0.3598 In DL t -0.1260 in DC, +(2.51)***(-4.30)*** (-1.03)
0.1581 In IC t +0.1794 tn PFt+0.6147 In PLt_ 1
(1.15) (0.88) (5.34)***
+0.0457D 1 , +0.0109D2t +0.0517D 3 t -0.2897 In Tt
(1.18) (0.19) (0.73) (0.48)
R2=0.96 R 2=0.95 DW =1.88
511$11*;>:\21' tn RC, =0.2165+0.9768 In PCt -0.0707 In WG+
(052) (6.14)*** (-1.88)**
0.1081 In PG+0.0104 In r.(1.18) (0.44)
R2=0.98. R °=0.98' DW=1.2
;>'\22' in RL, =-0.4750+1.2272 In PL t -0.0489 In WG,-(-1.35)* (21.4)*** (-1. 70)**
0.608 In T t(-3.16)
R2=0.97' R2=0.97' DW=1.82
( 29 )
- 70-
llltf\!;J&~
A23' FRC = SC x RC
5'\24' FRL=SLxRL
*25' TFR=FRC+FRL
l'J:~f'frJ&~
~26' NRC=FRC-EXC
*27' NRL = FRL - EXL
~28' TNR=NRC+NRL
~\:IfIff.,rHi5iMlflmt {if[ , *** 11.a =0.025 lJ-;¥JFlf ' ** 11.a =0.05If.fm~
, *~a =0.10If.fm~ 0 R :m!}?lJ~ff,f{ , R3m~IE~l'U~BU~ 0 DW~Durbin
Waston Statistic 0
m~~*IfI*~~~~~~~~~mm.~w~~~~~ft®m~,~~~
,rot~M~~~m~,m~~AW~'~._Z~~~~~~~~m~'~~T
~ii: &1t*Mt-AZ!flJ~ ff._ R 3 t({l£ (0.72) ?f.' J't~~:l?10.9 J:J.l: ' Jtm-~AZf.amUJIHtsMt-'fti;fj"1J®3Z:f:f 0 l'U/lfi DWfji (Durbin-Waston Value) lIUfet:
£ ••mm&~.~•••m~~.~ffm~~'~.~.~MM••~E"~H::ff1f ~ rrmlUJ (autocorrelation) , &.tf:tiZJtM ~ ffmlUJz~$'t/i
- 71-
0.451
0.516 4.064
~ ,~
t~r ~
;;j;( jil! -IIi ,rJlJ
• ~
-0. 0341( -29.32)
-0.359(- 2.786)
-0.033 (-30.303)
-0.44(- 2.27)
-0.056( -17 .86)
-0.93 (-1.075)
-O.055(-18.182)
-1.141(0.876)
~.t : (1H;Sli!i!i;tP~{$,~(Hg-:{*~Z.{f~~. llrJW,j*~~l1tl:z.r·~.it
1..,\~,:<>.~m7"CiltR!rjl""",~n;.tI,e j(l'!.PC)._ vr; d(ln PL) ft"-cl" 19' 1:1 20' .+. l~m"o IjJ'2Ij'~"-"-ml ·FfBI_t"i'1:;;II'.'~ d(ln DC) »; d(ln DL) • ,~JO" IX. ... n
DC ;m In DL z.{l{~. :l!U\JHYM't~ i;~:J!S{if~/ (1-;1\lD~{-f:$;) • ;1r,if!:{f~
ftp~ In PC t _ 1 ffl In PL t _ 1 Z.f,f,Jj( 0
(3)"" c;,:. 0 ""'J_".~-fJ.-'7{Ih."'·"I,,-n;1If,!·e d(ln RC) _ d(ln RC) X d(ln PC) -t-,~1i><1'F_1l1l1~ {~IIJ .t1!j-L ~"~B 'j:n:",j,~ - d(ln DC) - -d(ln PC) d(ln DC) • 7'"
:R~J!S{$tf~f~:{l{lt':~:!~a't~rijJ~HiH~{~lmfiJ:{H#JI~-~2}~~g-(ftPA: 21' tP 'In
PC (l{~) z.*~ ;*iWl'ii',1Ji:fll-f$IrI'JH\l!J';z.ifj-~~~.~,f,',rl'i.l 0
.ffiJl1~l¥i~Jl1jtj1f$~iJi1=.~ib • 1!,\~~iHM1t~T j!;••~Jl1z1:.~.71- ' ~t
.~wZ~~$a~~*ffilli~~(tt3) ol¥i.Jl1~~.~~~~~E•• •ill~W~~*~~.o~ffiJl1~~lliU~~*R~-*a~,~*m~=$'~
( 31 )
- 72-
3~.~;••BM~.~~&.-$.~'.~$&.=$.~'~~••~m!l$tf-1L...TJR!}' 0 .liB®~*~iJ~y.®,,~ , Jt±.~fZSl~~j:J1!!illifll~J~
~,.~~~~~.~m.W'~mM~.~Z"~·
2.f1l~1Joo :~.WM~&._f1l~~~*'~UH.W.Wm.&.J1!!m.~.*&m
~1$~~f*.~t1S*ij!J~ 0
~lO~.~.~Z~~~m~f*~'~~M~.~~z~~.~~~~~~
~~~~'m~.~M~~~zM•••*ij!J~zT.'#W.*~~.*~~~~fj'(fMEjJ~~ff..z(ftl.(Houck' 1965) ,tt,ut&tZ.*~~~~iWj~,
~~~*~••~oA~~~U*~fj'(.T~._m.'~.ffi~~J1!!m.z~*~~&••wm.a~o••£.wm~z.*~~~*~mam*~~'~N-'ft.*M'~o
rtf #i;
• ~ 0.5477 0.9081
l'7i ~ 0.1581 0.4103
rtf l!'l;
• iff. 0.5350 0.8870
1'B iffi. 0.1940 0.5035
~ll.m~f$t.fii~ f*lltW?jj-~~ffl: 0 m~{$~ffl:ff.~z~~.m~~iV} 1%,~~~~®s~~o~*M~,~a®m~~m~~*~mao.ffi£~wm
~mfff$~~/J':Jn.J1!!m. ' jfjjllit€£nf1[§iJi&ff.f1*mflmtt~J1!!m.t8Tffl 'a~m~~.~*~••~m••~o
~ 19' !'Ji!~ 20' *' 1ti.£1Jl~J:i.1Jl-l1%Jr.fi~••&tzlJl-m-J:i.1Jl-l 0.19% ;~jfjjll~I1'1lZ.*:S-!i.1J1l1 %' 1ti.I1'1lS9IJl~Jmlm!}'0.126%, ,\ilt1f,•••&tra':n1iffittit®lSfiIff. 0 *lUb®IJl~.1J1l 1% Jr.fne••JhIJl-m-fi.1J1l 0.1794%' m.t;pae:'HH?:rffl.T~0.499&%, Jt.~iif~N;;m~lt**~ttitMc*' #~ug-*
( 32 )
-73 -
~~~~r~~'~~*~~~*~vu'm~*~~m~r~~~mm~~~,
a.~~~*~~~'A~~.~H~~*~~Rti.~~~$~'~~.~~
~~*&~~*~~~~r~W~~.~~m~~*~~~m~n~~~o
5'\ 21' ,22' $~f!Htijj)~~J::* 1% Jlt~'U'i~rfltz~~~~~7JIjl:*
0.9768% 7Jl.. 1.2272%' W3tm~~~Ij(~~1JU 1%:m~••~~~jlg{Rm~!jr 0.71%:& 0.049%' wl\iji'l~r~,~~~ ' .~~~~~~~r~~.~'.~~M~J::*~~~'li~**••m.l:*1%m~.~~.~.ml:*0.W8%0=~m5'\Zm.~1J
:lll:~Mft~~m5'\zritft ' Jt;a:±'~~Jfl.Jlt):rfEffimg (forecast) **~.
~~~, ~~!jr~~~moo=Z~~~~':&m.ftm.~Z~*' WW~~
~Z~IT7Jl..~5E 0 lotl: , ffl~g (forecast) :&ffitJIU (prediction) ~~m.
(simulation)~-:m!0 m.ff-m-m~ft1.if!l~~~tf!M (mathmatic solu
tion) 0 JlttsITMr~'7i-1:.~lt~.~@:RAm~$ffij*~I~1:.t!ltA9@:' ~zf~
iltlJ (prediction) '*lm#i~tMra'Z~*~**A9{iKt\::AJlIJ~fJtiltlJ(forecast)
'W~~RA~*~m~~**'~~~~7i-1:.~~ff~~~5E@:~~m.o
mJ 5 RJt..HUl]a{mf.l~ffiiJIJJ (prediction) ~ m~1J (forecast) 7k.~IHfJIR(*
(Pindyck and Rubinfeld s 1978)
1~1I 5 ~ ~ Z a:!j: ffl' ~ it
j.i]~fJi~lJ~iH~~.~~IM~M:~mllll .~ffitJIU I $lliJfliltlj
(backcast) (ex post or historical I(ex post (Ex antesimulation) simulation) forecast)
• .• 0' ---»
-M~l';tf~Ll:mAt~H~~1JRJJfl m.@:w.~@:zr~U~llliB'~7d'*~'1j1T 0 E1J
~.lliJfJitJIU~~M~MA9.~a.!jr~Jfl'Wj.i]~fJi~M~Jt;*.~!jr~Jfl~~
jf~Jfl*11j1T~~zm.M§1J 0 w.1&m. (ex-post simulation) 7Jl..4H~fJiiltlj
(ex-post forecast) zl({{iK~.~JI'L~Ji:j'?Hrm.' ~*)(mAZ#iHMr~,~
~~ 62if.~ 69if.' EI3~ 69if.t)~Z~~j{M~*~f*' ~*lff'1E~~'fl:~fJi&l
(prediction) @:*~'ljlim~zm.fJl§1J0
{fijJl:m.ft!!W.~@:~~*/j, , ~~1Ijm~fI%Z~Jl:ni'Mng, , tkitJt;$
( 33 )
- 74-
~~::t~ff.iatffl~1t'IBro:J.£' :(l)~lfilPF~bYi. (Theil-inequallty coefficients) 0 ~4'i!Pf~~f*.1tPN:fi
J :rltJ-Ul' Ua5t}]ll~ir-mJl':
~29 Ui~/± (,6.Pi--D.Ai;/1±D.Pi:~ I±~~i:'=1 ,=1 t=1
; OS;Ul:::; 1
JtlfrD.Pi =Pi -Ai_I; D.Ai =Ai -Ai- 1
Ai ~.~Mi' Pi ~~.Mi
U1 = O~7f-D.PI=D.Ai' $M PI=AI, ~~%~fJ9~.0 itt:Ul'~~~ (}
~lf-tl~fm1.l~{t , ffii U 1 = 1 fJ91'Jli17L:ffjiij;jl , ;j't-m,.6.P i =Ai-'l ,fjz.1ll the
naive no-change model ; 7j-fifilf?£~~.Mi~.~fiMa~fJ9Jt$H* (Leuthod , 1975)
1E~~.@m.~1.J.lt the .nalve no-change model ~~ , {!:lmU1bYil!f(1'
••7f-W*'~~~.-~.~bYi~:
J!:30 U2~ It-~:~ -~~i): / I± (.6.A i Y ; O$U2:::; cot=l t=l
U2=O~*.J!:~••*~%~'(}<U2<1*7f-.~~~*~~~m~naive no-change model~16- ; U 2 = 1 *If-l!t~~~naive no-change mcdel
-tl' ;s:U2 > 1 RUJt naive no-change model ~l£' 1E~~WJ~~bYirx:1'm
tE.~Mi~••f1ifJ9§!! 11;;\" jTiI~FIZMi*:!1t ' ~~~fi~••MJiIi!.~fri!fJ9~~~JG
m *Jt~=-Frq].~z.••flli1.l' fffjR~~Uf~.Mi89~{t~tIUiHiU@{tJ¥.JHbYi 0
~Ht{t1!'r~~Jtftl!~1i!im.fii~.~Mir~'~~l¥J71~' RMSP (W~1IttiUfl8971
1.* 0 (RMSP ff~tmf~O
(2)~71~~1¥:85tl\( (root mean square percent error, RMSP)/ ----_.~..,-
5\:31 RMSP=V 1 ± (_Pi-::AI~)2' i =1.2···, TT ,=1 AI
O:::;RMSPS;oo
~ 4 -'-171fl Pi m••rtilJ AI'm.~M' Tm••Mr~, ~ (tJ.rJ'il)" RMSP~tE~it.j~Ul!Jt(simulated variable) ;fIl.~BtFr~,n~.~8985}$,RMSP
J¥.Jfi~:t!!/J\ , Rrrt~.Mi~lUi€fi1!z.ZjS~~~t{/J\ , $gD.~Z.~.~1]t{itli 0
~fffj~lfiIJf,firx:;fIl RMSP 89ni*~~fmU!lf-{t1!'~~~~1'.89,*~JiIi!m1it~~
I1Jt).qt~ 0 riRi{t1!'~#ffjl'ti15}M MSE 89717* 0
(3)~71~ (mean square error' MSE) l¥J5tfiR
( 34 )
- 75-
:P:;33 =(p-a)2+(Sp-Sa)2+ 2( l-r) SpSa:P:;34 =(p-a)2+(Sp-rSa)3+( 1 -r2)Sa3
;it9=' Pi=(Pi -Ai-I)/Ai_lai =(A i -Ai-l)/A i_lS, , Sa 51 }JIJ~ Pi ;fU a, l¥JIU\l~~'
r ~ Pi f1l ai l¥J,mIUd!*_f{ 0
El31t-':P:;34~Jm:lt~r1J~51fWnx:fl\l\~~ ..mm~RBUL~ , ffii~1It!lJJ:!ltil'~~fW~
~flflit.l~iH[[rf'l,z~~:&;itm~m~~1Jrf'l,zlUl{'f: ' *JIt)jt~JfI~34l¥J51fW-ni'*
*IDtOO 0 Jm~34jifM~\lij'; MSE 'JlIJ~r~:
~35: UM+UR+Uo= 1
~9=' UM=iPtvi~a~~- (~~~.l-t:¢)
U R = (~~M~~)2- (mm~!tt¥)
(1 -r 2 )Sa2 •Uo= - - MSE---- (tf~L~!tt¥)
~34)l.rtJf;£~36~~11~J·it.~flliL~IUl!*_~~:iiIj~M::P:;36 Ai=a+,8Pi+ei
#a = 0 1Ni' ~7f-El3m~m~rm~l¥J Pi ~.~fl Ai (fH~!liil (unbiased)1i!i~tfl' JltINi UM= 0 ; ffii,8 = 1J1.U~7f-m.fj~mjjUJ!~1!UI' W Ai J!lIliiiltltlc#titE Pi J::-f (&:Z$~)' TIii;;r:*~ Pi z*,j'ffif~. Pi flit s, z~llE'
J1tINiUR=o;m~fjR.~fl~ZIUl!*_,\lij';aflit,8~,~~~~~ei~.7f
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( 35 )
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t191!1.lrJjt~ltit , ;tt~~!J1\~* 0
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~ naive uo-change model i!~ 0 Jt~ RM5P 2.*/J' '~U~!lm:1fl!~z
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eSC)
i'iJ: ill rPtr {tH~ 0.4951 1.0176 0.0003 0.0027 0.2891 0.7082CSL)
m!~ij?,~Et;.{rWl 0.3154 0.5776 0.0005 0.0016 0.0002 0.9982(PC)
lI::jff,fr','.fif#f{l{til 0.3067 0.5622 0.0016 0.0002 0.0005 0.992(PL)
.,~,\T,~tI~{JHIl 0.2316 0.4716 0.00002 0.0002 0.0967 0.9031CRC)
li'":~,Pr,~fiHm'~ 0.1693 0.3249 0.0015 0.00006 0.0084 0.9915(RL)
*1if:¥t::#j"tB~M~~f1!~Mtfl::a(;m.' *Pitmm~J1:l~~~fj:1fitJiitJi~/J,
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and scillations) , m~ltE~jS*Bltit.~A~~~~m* 0 :r.:Rf1!m.JmE8~JtE, m~r&;~~~~/J' , {ljPJff~~1f ' ;r;~f'F*.JmE8.m~ , nljrmJ#f.m5't1Jl1t)afI:~
o afI:~EfJJJ'$~f1af1:fM.m~J1:lE8~~ , :l*m;ttftlHIH'i (estimate) 1]$ (tm)ifjl1\b{~
Ij'lJS1i$ '25L5) 'iiemMfrJj~?U.mA Ctm ARIMA .m~'D ' j}.xtk~~afI:*.rr~
~~~~~~orn~~~&Mf~m~'*X~f'F~~-~E8~~o
( 36 -;
- 77-
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B9m~*~~o*~$*~m~m.~U~m~+li~~~~,m*~~~lf(:Ii
MUW.~~~+li~Z.W!.~~~o~~~~~.uw.m~~~Z.o,
i±lO:&ff~Z.M,aU~.z.Mf\;;Ao
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ffl1nfJUllUo ~A?llU~~*PJTH¥J:z.~J1#U£i~tl:~ 0.451 , ~~&1Z~mW3~Mi~tl:5t51IJ~ 4.064 :& 0.516 ; ~.rf1tz~mM'fi*~tl:~~.rti~5} 51IJ 1.075:&2.786, ~~W!m~f{U5}51IJ~0.876:&2.27 ; mll.J1z*~1Wi)j(~l1:~i'i:i~Z~~,m~.~J1Z~~~~~~(;!;}~.-$~.Z~W!o
~ffl*fiifYt;m-.~zm~PJ~~~~i6c.~.:&m.ZIAo~~.~&.
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( 37 !
-78 -
.~~~~*~~~~*z~MW.~~~~ffi,~~~.~m~z~.;~~
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tl2!.1t#t;fli.P:;Z~n:a9lit~jtm:~tE&A~'ffi.1Jlltl2!. (aggregate) a9~*
~,f!tM7JIJ§f&1rl'l'~J!f{(f]1L113~.&~~fljHiutJ/f>11I3' miffit&~1L113~.(f]J1t~~* ' ~lIttf~*1JIl~(f]~fU&f,it~&:'Jm1ii~I1I3Rm~gU<'i ' m~~i*flt~ 0 l&~
re~/f>~am~/f>~~OO(f]fli~'.~~~./f>~••~~~(f]~~.P:;~~~1JIl1l(f]~.&lYlkala9~lt~W:~fli~0 J1t71-' tE~ft~~ffl1JllmmAIJi!j' ~~i1
Xf.~l!raJ9~.~-~*~. ~flj *71- ' "$~~!I~~1J1lNl!a9i11'1~HJffiUU5mllJ~
~~a9fJ'li. ' ffi.1JIlIl(f]*ii*~~~~M§t(f]m!~m.~tE~~ rd:l1Lmm~mi~;;r-~~~*.~.~~*~ffi~••~~~~~~m~&~m~W:1t-~~M§tm!~:OO~:&.ii~&1~-~~tEo
a.'*~"$.~aMtE~~a.m•••z~'.~!I~•••$M.~ffif~3!~~.'~fUffl~~/f:;jq]fJjI1t~fJ'lifln(j{J1.Jll!fl.j--\~M211~~~.A' ~ma ••~z.~'~••a.~~.zm~~.~.&Mlito
~.~'~1113* ~~~m~.*~.~m.~~~m~,.m.,~~*'
1975 c
~.~'J "1.i~Jl'!{tzIfMuI;tiU\tfi::t~.~~L1Wj~!I!i!tt'" ±itt~Iii;J7IJ '5 (16) (1968) : 13-290
"j!1}fj~*.~rfb&.fflrrMi'H~llH?J5t1fr" ,±il!H'iZ~~flj,11 (4)
(1974) : 57-690
**~ret "i1f:Ii!t±:'~ll~rPufi"lftzRU!\~I!t".m~fl] , 26 (4) (1975) : 145-1610
m~* ••~.m*Mm.~@.~~~~~m~·~ft*~*••~*,19800
BRMiI! ..~1lt~fHHNll*~~~~.'" !Hlt~~~3tW~' 16 (1981) : 27-500
( 38 )
- 79-
~~,'it', "1fEJ!t~*mJDtzH:l:7ttIT'" IH'U~~.JtlUI'16 (1981) : 51680
~mff ~~,~~~~,~~~~,~~~_&~~~m~'~ft~~*~~
~fj~ , ~~I'f~*1f9=J.c..,~fj , 19730
~.M'F~ •••~11~' -~~{I~.~m~ZfJf~, 1Il~\t ' nb~* ' 19810
.~••••$~M~~.m~~fi-~.ft~~$~~~,~ft~.*~.~*, 19730
Arzac, Enrique R. and Maurice Wilkinson, "An Econometric Model of
United States Livestock and Feed Grain Markets and Some
of Its Policy Implications." AJAE, 61(1979); 297-308.
Blandford, David and Seon Lee., "Quantitative Evaluation of Stabiliza
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( 39 )
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( 41 )
- 82-
An Econometric Model of AggregateAgricultural Supply and Demand
in Taiwan
by
Chang-Ju Huang
Summary
The purpose of this paper is to build up an econometric
model of aggregate agricultural supply and demand which can be
used for better understanding of Taiwan's aggregate agricultural
economy, for forecasting, and for policy simulation.
The agricultural products are divided into two groups, i. e. ,
crop and livestock, For each group, functions of supply, demand
and price are constructed and estimated seperately. However,
the interretations between these two groups both in demand and
production are considered.
Since the lagged price variable is treated as explanatory in
the supply function and the current price as dependent variable
in the demand function, and with market clear condition the whole
structure constituted a recursive type, Therefore the ordinary
least square techniques can be applied for estimating individual
function. A function of marketing margin is explicetly set for
linking prices in various market levels. Finally, the product of
estimated production and farm price for both product groups
decided the level of farmer's income.
The reseach period includes data from 1973 to 1980, the
prices are deflated at the 1976's level.
From the model, the elasticities and flexibility coefficients
are calculated, The supply elasticity of crop is 0.451. The short
and long run supply elasticities of livestock are 0.516 and 4.064
respectively. And the short and long run demand elasticities of
( 42 )
- 83-
livestock are 2.786 and 1.075 at wholesale market and 2.27 and
0.876 at farm market respectively. Price f1exibilities for the
crop are also estimated for reference.
( 43 )