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1 ( ) Development of Regional Input - Output Analysis Model( )

2 2001,

3 ( ) Development of Regional Input-Output Analysis Model ( )

4 , / / 2-22 / / ( ) ( ) ( ) / ,000 /ISBN ,.

5 ...,

6

7 ..,..,......,...,.

8 .,.., ,,, RAS. RAS < > RAS LQ, LQ,,

9 . LQ. 5,. 16,,, ,,., ,. LQ LQ. LQ < (RAS) > < % 50% 100% 500% 638 (94.4) 461 (68.2) 210 (31.1) 15 ( 2.2) 614 (90.8) 398 (58.9) 228 (33.7) 7 ( 1.0) 613 (90.7) 401 (59.3) 215 (31.8) 4 ( 0.6) 604 (89.3) 341 (50.4) 170 (25.1) 6 ( 0.9) : ( ) (%)

10 , ,,.,,,,..,. 7, (5 )

11

12 SUMMARY

13 < 2-1> 15 < 3-1> 24 < 3-2> 29 < 3-3> 32 < 3-4> ( ) 48 < 4-1> 50 < 4-2> 51 < 4-3> 67 < 4-4> 68 < 4-5> 69 < 4-6> ( ) 70 < 4-7> 73 < 4-8> 76 < 5-1> 81 < 5-2> ( ) 83 < 5-3> 86 < 5-4> 87 < 5-5> 88 < 5-6> 91 < 5-7> 1 94 < 5-8> (4 ) 96

14 < 6-1> 102 < 6-2> 104 < 6-3> 106 < 7-1> 108

15 < 2-1> 10 < 4-1> 54

16 1 C H A P T E R 1...., =

17 ) 2). 3).,.,.,... 1) (1983, 1984), (1993, 2001), (1994), (2000),. 2) (2000), (2001) (1996). 3) (1990), (1998). 2

18 ... 2.,

19 ,..,... 4

20 ...,....,., ,. 1 5

21 ., ,.....,

22 . 1...,....,,.,,

23 ... 8

24 2 C H A P T E R 1. 1) (1) (CRTS) (constant retuurns to scale). (increasing returns to scale) (decreasing returns to scale)., (fixed technical coefficient).., X 1 = a 11 X 1 + a 12 X a 1i X i a n X n + Y 1 X 2 = a 21 X 1 + a 22 X a 2 i X i a 2 n X n + Y 2. X i = a i1 X 1 + a i2 X a ii X i a i X n + Y i. X n = a n 1 X 1 + a n2 X a n i X i a n n X n + Y n (2-1). 2 9

25 (2) ( ) (isoquant) (isoquant)., 2 ( Z 1i, Z 2 i ).,. 4). < 2-1> Z 2 i Z 1i Z 2 i Z 1i 4) X Z., X j = min ( Z 1j a 1j, Z 2j a 2j (CRTS) X (isoquant) Z. ). 10

26 (3)..,.. (4) (black box)....,,. (5)..,

27 .. (6).,,.. (7),. (linear programming).,,..,..,,.., (static model), (dynamic model).. 12

28 2) 1 ( a ij ). a ij = X ij X j (2-2) ( X j j X ij i j.) (A) (X) (Y). X = AX + Y (2-3) A = a 11 a 12.. a 1i.. a 1n a 21 a 22.. a 2 i.. a 2 n a i1 a i2.. a ii.. a n a n 1 a n2.. a n.. a n n X = X 1 X 2. X i. X n Y = Y 1 Y 2. Y i. Y n. (2-3)., X = ( I - A ) - 1 Y (2-4) 2 13

29 (I - A ) - 1 (Leontief Inverse Matrix)..,., (Y) (X) (2-4)..,,,.,. 3) (open system) (closed system)... (closed input-output model). (open input-output model). (type ) (type ). type type. 14

30 < 2-1> 1 2 W1 W2 V1 V2 X1 X2 1 X11 X12 C1 Y1 X1 2 X21 X22 C2 Y2 X2 2. 1)....,. (regional I-O model) (single-region input output analysis) (inter-regional I-O model), (multi-regional I-O model)

31 2) (single-region I-O model)...,. L a L L. a L L ij = z L L ij X L j (2-5) 3) (Inter- Regional I- O Model, IRIO) 2 (Inter-Regional I-O Model, IRIO). L M ( ). Z = [ Z L L Z L M ] Z M L Z M M (2-6). a MM ij = z MM ij X M j (2-7) 16

32 a L M ij = z L M ij X M j (2-8). (I - A L L ) X L - A L M X M = Y L - A M L X L + (I - A M M ) X M = Y M (2-9), I 0 {[ 0 I ]- A [ L L A L M X A ] M L A }[ L ] M M X M = [ Y L ] Y M (2-10).. 4) (Multi- regional I- O Model, MRIO) (IRIO).. n n n... (Multi-regional I-O Model, MRIO). 2 17

33 ( A L L ) ( A L ).. A L ij = Z L ij X L j (2-11).. (inter-regional trade coefficient). (C). C L M i = Z L M i T M i (2-12). 5) (single region) 1.,... 18

34 (inter-regional I-O model)..., , 296. IRIO. (Multi-regional I-O Model). MRIO., MRIO. 5). (MRIO) (IRIO). 1, ) (1998). 2 19

35 ,. IRIO. Moses-Chenery IRIO. (balanced regional model) 6). 6) Miller & Blair(1985). 20

36 3 C H A P T E R 1. (Non Survey Technique) (regional weights approach).... 7). 8) 7) Shen(1960). p18., (1998). 8) Round(1972), (2001). 3 21

37 (location quotient approach).,. (LQ) 1.. L Q R i = [ X R i / X R X N i / X N ] (3-1) i, R, N.. a R R ij = { a N ij ( L Q R i ) a N ij, L Q R i 1, L Q R i 1 (3-2), (purchase only LQ), (cross industry LQ), (expenditure LQ)., (supply demand pool approach). 9) - X R i = a N ij X R j + c N if Y f (3-3) j f c N if. 9) R. E. Miller & P. Blair, 1985, pp

38 a R R ij = { a N ij ( X R i / b i = X R i - - X a N ij - X R i ), b i 0, b i 0 R i. (3-4), (regional purchase coefficients approach). 10) R P C R i = Z R R i / ( Z R R i + Z - R R i ) (3-5) Z R R i i R R Z - R R i R., RAS.....,. 11).,.. 10) J. I. Round, (. p20 ). 11) (2000), (1992), (2000). 3 23

39 2. 1). Morrison Smith. RAS, (Simple-Location Quotient).. (< 3-1 >). 12) < 3-1> Mean Absolute Difference RAS SLQ POLQ RMOD CMOD SDP RND CILQ Correlation Coefficient RAS SDP SLQ POLQ RMOD CMOD RND CILQ Mean Similarity Index RAS SLQ POLQ SDP RMOD RND CMOD CILQ : CILQ(Cross-Industry Location Quotient) CMOD(Modified Cross-Industry Quotient) POLQ(Purchasea Only Location Quotient) RAS(RAS) RMOD(Logarithmic Cross-Industry Quotient) SDP(Supply-Demend Pool) SLQ(Simple Location Quotient) RND(Logarithmic Cross Quotient), Information Content RAS SLQ POLQ CMOD RMOD RND CILQ SDP Chi-Square RAS CMOD SLQ RMOD POLQ RND CILQ SDP 12) (1994). 24

40 ,.,.,. RAS. RAS. A. (Simple-Location Quotient). (Location Quotient)..,. 2). 3 25

41 (1) RAS RAS., non-negativity...,., RAS.. RAS.. 26

42 (2) (Locaton Quotient Method) (Locaton Quotient Method) (Location Quotient) 1. LQ 1.. LQ... LQ. LQ,,. LQ. (3) (Weighting Method) 3 27

43 ..,. RAS LQ,, RAS LQ....,..,.. 28

44 < 3-2> RAS (RAS Method) (Location Quotient Method) (Weighting Method) non-negativity,, I- O ( ) ( ) LQ ( ) ( ) 3. 1) 1936 (W. Leontief) (W. Isard), (Moses and Chenery). (Ronald E. Miller). 13).. 13) R. E. Miller & P. Blair (1985). 3 29

45 . W. Isard. Isard(1951) Kuenne(1953), Miller(1957) (1967) (1967), (1969) (non-survey method), (partial survey method) (dynamic).. 2).. (H. Richardson, 1985). 14). (regional weights method), RAS, LQ (location quotient method) (commodity balance approach), 14) (1998),. 30

46 (regional purchase coefficient method). (short-cut method). 15) 16), (comprehensive general equilibriummodel) 17).... 3).... (1983, 1984), (1994, 2001), (1995), KDI(2000), (2001).. (1994), (1994), (2000)... 15) (2000).. 16) ). :

47 < 3-3> K. Han (1963) ,, (1983) : LQ, RAS :, (1984) : survey, RAS :, (1990) ,,,, : (1993) , : MRIO( ) (1993) , MRIO KRIO, KMRIO 26, LQ (1995) : (1998) ,, : : H. Ji(1999) : :, ( ) (2000) RAS (2000) (2000) (2001) RAS LQ 32

48 4. 1) (1).,.....,,....,. 3 33

49 ... (2),,, LQ..,... (Inter-Regional I-O Model) (Multi-Regional I-O Model)... (W. Isard). 34

50 .,... Isard ). Chenery Moses 19) Chenery-Moses. L M i M i, (Regional trade coefficient). M M. 20). C L M i = Z L M i T M i (3-6) Zi LM : L M i Ci L M : Ti M : Z i 1M + Z i 2M Z i L M Z i p M ( M i ) 18) ) 20) Chenery(1953), Moses(1955). 3 35

51 i. M i M i 0.1 j i i 0.1 j+1 i i 0.1. i......,,,, RAS., -,.,.. 21) 36

52 .,.,... x m ij = K m X m i Y m j f m ( d m ij ) (3-7) x m ij K m : i j m ( : ) : X m i : i ( ) ( :, Y m j ) : j ( ) ( :, ) f m ( d m ij ) : i j m : i : j :, 21) Wilson, A. G., Entropy in Urban and Regional Modelling. London: Pion Ltd. pp

53 .,.,....,.,.,. 22). (forecasting dilemma). (3-7) X m i 2 Y m j ) 22) Senior, M. L., From Gravity Modelling to Entropy Maximizing: A Pedagogic Guide. Progress in Human Geography. Vol. 3 No2. pp (, (MRIO). pp33-34 ) 23) Wilson,. p16. 38

54 .,.,.,...,.. 2. ( ). (3-8) - (3-9), m. m i j i. m i j j. (3-10).., 3 39

55 . xij m = Xi m (3-8) j xij m = Yj m (3-9) i xij m cij m = C m (3-10) i j xij m m i j Xi m i m Yj m j m cij m m i j C m m m W({xij m })= ij T! T ij! m {xij }. {xij m } Lagrangian. 24) = ln W+ i ( 1) i ( X i - j x ij ) + j ( 2) j ( Y i - i x ij ) + ( C - i j x ij c ij ) (3-11) xij m xij m 0 ( ).,.., 24) Wilson,. pp

56 . 25) (LQ) LQ 2. LQ. LQ. LQ. LQ LQ 1, LQ 1. LQ.,,.,. 2 3 LQ., 2, LQ 1, LQ 1. LQ 1 LQ 1. 25),. p

57 ) 4.. LQ. 27)...,.,.,,.. 26) A, B, C 3, LQ 6., A>1, B>1, C<1,, A>1, B<1, C<1,, A>1, B<1, C>1,, A<1, B>1, C<1,, A<1, B>1, C>1,, A<1, B<1, C>1.., C A B LQ ) 4 LQ 1 LQ 1 LQ

58 2).,,, , ) (1996). 29).,.,.. (1998),,,, LQ 28), :. pp ), pp

59 . 30)..,,,,, LQ. LQ, 3. LQ, LQ LQ 1, LQ 1. LQ, 1 LQ 1 LQ, LQ 1 LQ.. ) A I LQ 0.31, B I LQ 1.3, C I LQ 1.7 A 0.31, B 1.00, C 1.00 B- >A = (1.3/( ))*( ) C->A = (1.7/( ))*( ) 30), MRIO.. pp

60 LQ,.,, LQ. 31) (1995),. 32). 15,.,,,,.. r s logz ij r = logg + logp i s + loge j + logd r s r s + ij Zij rs : r i s j G : Pi r Ej s D rs : r i : s j : r s a, b, c: log 31), pp ), pp

61 .., 1990 I-O.. 33),, (1994)... 3),.,,. LQ, LQ.. LQ LQ 33),. pp

62 LQ 1 LQ (, ). LQ., LQ..,,...,.... ( : 3 )

63 ..,... LQ.. < 3-4> ( ) ( : 3 ),, 48

64 4 C H A P T E R 1. 1) )... 34) (1998), (2000). 4 49

65 ,. 2),.. 3,, < 4-1> (,,,,,,,,,,,, ) 50

66 .,. (code28) < 4-2> Code (28 ) Code (77 ) Code (26 ) ,

67 ( ) Code (28 ) Code (77 ) Code (26 ) , ,

68 2. 1) (open system).... ( ). 2.,... 1, 2.. RAS. RAS,. 5. LQ. LQ. LQ. (Multi-regional I-O). MRIO 4 53

69 RAS LQ,.. RAS-LQ, RAS-. RAS-LQ ) (1) RAS.,.. RAS. < 4-1> U ( ) V ( ) 54

70 , A(o), U,. V A 1 = R 1 A ( O) R 1 = [ U ( 1) ][ U 1 ] - 1 (4-1) S 1 = [ V ( 1) ][ V 1 ] - 1 (4-2) 2 A Matrix, A 2 = R 1 A ( o) S 1 (4-3) R S n A 2n = [ R n.... R 1 ] A ( o)[ S S n ]. (2). LQGE 4 55

71 (Location Quotient-Gravity-Entropy Model). LQ. LQ LQ 1 LQ 1., LQ , Chenery-Moses..,, 56

72 .. 35).,. LQ,,. LQ,,..... LQ, 4. LQ. 3. 4,.. LQ LQ. 35), pp63-69.,,. pp23-25.,,. p

73 6.,,,,,.. LQ. LQ LQ 1, LQ 1, 1. 36) LQ, LQ. LQ. LQ,. LQ. S r i I r i = X r it - X r tt * ( W i W t ) 36) Isserman, A. M., "Estimating Export Activity in Regional Economy: A Theoretical and Empirical Analysis of Alternative Methods". International Regional Science Review. 5(1980). pp ,, p19.,, pp

74 S r i : X r it - X r tt * ( I r i : X r it - X r tt * ( W i W t ) > 0 W i W t ) < 0 X r it X r tt Wi Wt : r i : r : i :..,.,.,,,.,. 37) 37),,,,. 4 59

75 logz rs = logg + logp r + loge s + logd rs + r s Z r s : r s G : P r E s D rs : r : s : r s a, b, c:..,.....,.. 60

76 r i i,. r i s, s s i, r i. r. s. r r. s s..,... S ir C r = O irs (4-4) S ir : I [ S i1, S i2 S ir S in ] C r : [ C 1, C 2 C r C n ] O irs : 4 61

77 O i11 O i12 O i1n O i21 O i22 O i2n : O n 1 O n2 O in n I is = I is + n s = 1 O irs (4-5) I is i [ I i1, I i2 I is I in ] If I is 0, T hen C r = 0 Other wise C r = C r S ir = S ir - n r = 1 O irs (4-6) If A ll S ir = 0, T hen en d Go To (4-4).... LQ 62

78 1. LQ 1 LQ 1. LQ 1. E r it = E r tt * ( W i W t ) E r it : r i E r tt Wi Wt : r : i :. i z.. Chenery- Moses. 3 (3-6). (3-6) 4 63

79 ) A L = a ( L 11 a L 12, A a ) M = a L 21 a ( M 11 a M 12 ) L 22 a M 21 a M 22 C LL = c ( L L 1 0, 0 c ) L L 2 C LM = c ( L M c ) L M 2 C M L = c ( ML 1 0, 0 c ) ML 2 C M M = c ( MM c ) MM 2 C LL A L = c ( L L 1 a L 11 c L L 1 a L 12, c ) L L 2 a L 21 c L L 2 a L 22 C LM A M = c ( L M 1 a M 11 c L M 1 a M 12 c ) L M 2 a M 21 c L M 2 a M 22 C M L A L = c ( ML 1 a L 11 c ML 1 a L 12, c ) ML 2 a L 21 c ML 2 a L 22 C M M A M = c ( MM 1 a M 11 c MM 1 a M 12 c ) MM 2 a M 21 c MM 2 a M 22 C LL A L, C M M A M L M. C LM A M, C M L A L. 38), I. :. pp

80 ,.,. 3. 1) RAS,,., (A(o)). r i (V) (X) (Q)., V r i = X r i - Q r i.. (X) (Y) (U)..,,,,,

81 . ( : KDI ).,,, ).,...,. < 4-3> < 4-4>. 66

82 < 4-3> ( : ) 1 836, ,702 2,038,653 11,527, , , , , ,866,599 2,937,530 8,305,230 17,968, ,650, ,350 7,030,482 13,053, ,535 1,314,709 3,907,656 5,843,957 6, 4,811,784 77, , , ,517,737 44,764 15,676, ,172,704 2,749,113 11,486,281 39,949, , ,829 3,194,035 8,039, ,834 4,521,822 3,454,120 25,092, ,167 1,771,322 3,948,951 6,742, ,247 3,676,836 5,582,942 12,685, ,537,843 2,759,067 32,849,761 26,186, , , ,166 1,549, ,105 5,203,645 7,706,295 30,550, ,413 1,761,724 2,165,135 1,559, ,042 1,497,790 2,732,872 7,730, ,070,453 5,099,117 14,083,059 37,853, ,911,156 2,821,935 4,863,490 15,582, ,568,026 1,395,536 3,371,131 11,374, ,593,773 3,167,303 1,069,415 15,881, ,009,353 1,094, ,128 2,998, ,833,944 1,321,856 1,809,205 5,960, ,198,531 2,753,694 3,544,555 10,148, ,270, ,054 1,040,416 3,444, ,010,949 2,674,570 3,568,171 13,465,

83 < 4-4> 1 323, ,786 4,184,228 30,634, ,898 59, ,860 1,347, ,245,714 2,376,014 11,491,930 24,339, ,221, ,450 9,993,625 18,857, , ,546 5,444,462 8,311,366 6, 2,693,012 48,021 1,100, , ,928,966 67,537 19,087, ,728 1,916,014 18,142,039 54,771, , ,502 4,913,186 11,662, ,415 3,589,400 4,430,379 33,438, ,506 1,203,826 5,872,653 10,430, ,037 2,663,265 8,307,270 18,520, ,064,911 1,983,093 49,250,703 36,635, , ,599 1,474,974 2,297, ,034 3,379,677 10,376,548 42,496, ,907 1,226,483 3,217,345 2,240, , ,793 4,602,413 15,041, ,868,327 2,851,580 23,911,899 65,438, ,456,201 1,491,169 9,047,064 34,546, ,452,163 1,117,181 4,753,281 16,412, ,497,653 1,959,812 2,658,503 26,903, ,593, ,310 1,725,204 7,873, ,812, ,610 4,689,450 15,633, ,149, ,323 11,548,727 29,454, ,854, ,786 2,899,431 11,504, ,342, ,748 10,413,990 37,163,964 68

84 2) (1) (,, ) (2)..,,. < 4-5> ( ), ( ), ( ) ( ), ( ), ( ) ( / ) ( ), ( ) ( ), ( ), ( ) 4 69

85 ,... KDI 70 29, 28, ). < 4-6> ( ),,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 39),. pp

86 . 40). (3). (X) (VA).., = (X)- (VA)"..,., ) (1980), (1998). 4 71

87 , GDP.,.... 3).....,.. 72

88 . 100%..... < 4-7>. < 4-7> ( : ) 1 711, ,862 3,558,493 26,053, ,099 1,481,829 3,938,293 18,119, , ,931 3,321,110 7,034, ,959, ,768 3,865,686 7,294, ,967 1,505,380 6,234,067 9,516,755 6, 3,984,950 64, , , ,158,124 57,891 16,361, ,162,648 2,725,539 17,986,470 54,301, , ,177 5,816,160 13,806,449 ( ) 4 73

89 ( : ) ,705 5,213,277 5,107,851 38,552, ,458 1,469,517 4,872,047 8,653, ,060 2,721,841 6,149,599 13,710, ,519,588 1,753,531 31,301,392 23,283, , ,356 1,377,543 2,146, ,691 2,068,857 4,125,491 16,895, , ,315 1,156, , ,078 1,265,889 3,889,828 12,712, ,909, ,993 2,841,753 7,776, ,169, ,267 3,065,773 11,706, ,170,529 1,556,228 1,306,233 13,218, ,583, ,848 1,128,180 5,148, ,624, ,329 3,516,864 11,724, ,394,205 2,082,075 8,732,020 22,270, ,649, ,431 2,104,278 7,509,448 74

90 4) ,. 41) 41)

91 < 4-8> , ,

92

93

94

95 5 C H A P T E R (A(0)) RAS < 5-1> RAS LQ, LQ,, 5 81

96 2. 1) RAS ,,..,,

97 < 5-2> ( ) , ,

98 ,

99 ,

100 2),.. 50% 12 10% < 5-3>

101 . 4,,,,.,,, ) < 5-4> ( : ) , : 26 42)

102 .,.,. 3) RAS % 10% 30% 100%.. < 5-5> < 10% 50% 100% 500% (94.4) 461 (68.2) 210 (31.1) 15 (2.2) (90.8) 398 (58.9) 228 (33.7) 7 (1.0) (90.7) 401 (59.3) 215 (31.8) 4 (0.6) (89.3) 341 (50.4) 170 (25.1) 6 (0.9) : ( ) 88

103 3. 1).,... LQ. LQ LQ LQ 1 LQ (, ). LQ.,. LQ. LQ,. LQ. LQ. 5 89

104 2) ,.. 43). 16, (1) < 5-6> LQ 4.,,.. 15,,, 1, 43), p54. 90

105 10, ,,. < 5-6> ( : ) -6,692,164-1,457,895-2,313,619 10,463, ,445 24,320-36, ,720-5,047, ,900 2,183,849 1,897, ,675-1,099, , ,709-2,176, ,564 1,581,703 46,925 3,702, , ,804-2,952,834-4,054,329 1,336,379-3,450,848 6,168,793-11,772, ,257 1,800,494 10,719,472-2,640, , ,375 1,882, ,710,247 2,191,690-3,800,640 9,319,195-2,828, ,872 1,322, ,911-4,770,912 1,982, ,123 1,822,341-10,784,220-1,681,562 20,992,687-8,526, , , , ,832-10,475,681 2,184,372-1,715,125 10,006, ,970 1,289,743 1,057,629-1,842,

106 ( ) -3,633, , ,600 2,693,643-6,958, ,735 4,034,656 3,733,932 18,756,571-1,579,584-5,759,544-11,417,447 2,873, ,241-1,025,282-1,525,599 4,733, ,231-5,852, ,360 3,320, ,205-1,458,683-2,010,101 15,149,112-1,163,076-3,669,803-10,316,241 22,704,475-1,734,926-3,550,888-17,418,663 1,007, , ,013 82,052 7,744,875-1,242,395-2,762,591-3,739,887 (2) 1,..,. 44),. 44),. pp

107 logz rs = log Pr log Es logD rs + rs ( ) ( ) (8.0758) ( ) ( ) t, R 2 = ( pp ). (3) < 5-6>. 4,. 1. LQ 1,,,,,,....,. 5 93

108 < 5-7> < 5-7> ,117, ,558 18, ,854 5, , , , ,854 32, , , , ,062 55, ,174, , , ,181 75,083 4,233, ,343, , , ,044 81, ,266 30, ,705 12, ,710, ,800,640 1,765, , ,799 94

109 ( ) ,899 22,774 27,420 10, ,191, ,628 60,095 32,021 47, , , ,190 92,396 49,508 73, ,333 1,974, , , , , ,923 3,590, , , , , ,344 9,068, ,272 9,634 3,797 10, , , , , , , ,899 17,907,500 (3) < 5-7>,., 1 LQ LQ ,. 5 95

110 4 4, < 5-8>. < 5-8> (4 ) ,

111

112 , 0. 98

113 ..... LQ 1 LQ 1.., LQ 1,.,. LQ 1,, ). RAS. 5 99

114 , 104 ( ) 0,,., LQ 1. ( pp ). 100

115 6 C H A P T E R 1.. 1, (output multiplier), (income multiplier), (employment multiplier).,,., ij ( O j )

116 O j = n i = 1 ij (6-1), (column). 4 < 6-1>.. 1,,, < 6-1>

117 ( ) j (simple houshold income multiplier) - H j. - H j = n + 1 i = 1 a n + 1, i ij (6-2) a, ( w) (x). Ȳ j

118 - Y j = - H j a n + 1, i (6-3),,,.. ( ) ( ). 45) < 6-2> )

119 .,.,,,,.. 4. ( E j ) ( ) ( w).. E j = n i = 1 W n + 1, i ij (6-4) ,,,, ,

120 < 6-3>

121 7 C H A P T E R 1..,. (Regression analysis) (Econometrics). (constant returns to scale), (isoquant).. RAS LQ

122 .,. 3. < 7-1> 1 RAS,, 2 LQ, LQ 3 1 RAS, 2 (location quotient). 3. RAS. (3 ) ( ) (5 ),, 108

123 .... (6 ), ( LQ). 2.. RAS LQ.,. RAS

124 ,

125 : : : : : : :., , , , Gravity : : : 111

126 : : : MRIO : : MRIO : : : : : : : : : : : (MRIO). : ( ). :. 112

127 : : : ( ). : : , Afrasiabi, Ahmad, and Stephen D Casler "Product Mix and Technological Change within the Leontief Invers". Journal of Regional Science Bullard, Clark W., and Anthony V. Sebald "Effect of Paramatric Uncertainty and Technological Change on Input-Output Model". The Reviwe of Economics and Statistics. 59, "Monte Carlo Senvitivity Analysis of Input-Output Models". The Reviwe of Economics and Statistics, Casler, Stephen and B. Hannon "Readjustment Potentials in Industrial Energy Effciency and Structure". Journal of Environmental Economis nd M anagement Chenery, H., 1953 "Regional Analysis". Chenery, H & P. Clark(eds), The Structure and Growth of the Italian Economy. U. S M utual Security Agency. Feldman, Stanley J., Daniel Mclain, and Karen Palmer "Sources of Structural Change in United State, : An Input-Output Perspective " The Reviwe of Economics and Statistics, 69,

128 Han, Ki Chun "A Stuty of Interregional Economics of Korea". Ph. D., Dessertation. Boston University. Hewings, Geoffrey J. D "The Role of Prior Information in Updating Regional Input-Output Models". Scocio-Economic Planning Sciences, Isard, W., 1951, "Interregional and Regional Input-Output Analysis: A Model of a Space Economy". Review of Economics and Statistics. Vol. 33. Isserman, A. M., 1980, "Estimating Expert Activity in Regional Economiy: A The oretical and Empircal Analysis of Alternative Methods", International Regional Science Review, 5, pp Lahr, Micheal L "A Review of the Literature Supporting the Hybrid Approach to Costructing Regional Input-Output Models". Economic Systems Research Miller, R., and P. Blair "A Canadian Regional General Equilibrium Model," Journal of Urban Economics, Vol. 25. Moses, L., "The Stability of Interregional Trading Patterns and Input-Output Analysis". A merican Economics Review., L., A General Equilibrium Model of Production, Interregional Trade, and Location of Industry". Review of Economics and Statistics. Vol. 42. Polenske, K., "An Empirical Test of Interregional Input-Output Model : Estimate of 1963 Japanese Production". A merican Economics Review. Vol. 60. Round, J., "Regional Input-Output Models in the U. K. : An Reappraisal of Some Techniques". R egional Studies. 6. Senior. M.L., 1970, "Gravity Modeling to Entropy Maximmizing: A Pedagogic Guide ", Progress in Human Geographiy, Vol. 3, No 2, pp

129 Casler S. D. and Hadlock D., "Contributions to change in the Input-Output Model: the Search for Inverse Important Coefficients", Journal of R egional Science, Vol. 37. Shen, T. Y., "An Input-Output Table with Regional Weight". Pap ers of Regional Science Association, 6. Sonis, Micheal, and Geoffrey J. D. Hewings, "Error and Sensitivisity Input-Output Analysis: A New Approach",in Adam Rose, Karen R. Polenske, and Ronald E. Miller(eds), Frontier of Inp ut-outp ut A naly sis, New York: Oxf ord University Press. pp "Coefficient Change in Input-Output Models: Theory and Applications". Economic Sy stems R esearch Wilson,A. G., Entropy in Urban and Regional M odeling. London: Pion Ltd. Xu, Songling, and Moss Madden "The Concept of Important Coefficients in Input-output Models". in John H. L. Dewhurst, Geoffrey J. D. Hewings, and Rodney C. Jensen(eds). R egional Inp ut-outp ut M odelling. A ldershot: Avebury

130 SUMMARY Development of Regional Input- OutputAnalysis Model( ) Sang - Woo Park, Jong - Y eol L ee The regional input-output table performs a crucial role in identifying the industrial relationships and predicting the effect of investment in an industrial sector on other sectors including itself. The usefulness of the table has induced significant effort to produce more stable and accurate input-output coefficients at regional level. The regional input-output table has, however, been produced only intermittently by several organizations and researchers for their own purposes becau se to produce a table is an expensive and time-consuming task at regional level as well as for nation. There is necessity to improve a method to facilitate regional input-output analysis. The fundamental goal of this research is to develop a regional input-output model that provide a region with a table of input-output coefficients with less effort than previous models. The coefficients should describe accurate relationships between inputs and outputs for a particular economy. This research also aims to carry out experimental SUMMARY 117

131 regional input-output table based on the model suggested in thisresearch to examine its' practicability. This research has seven chapters. Following the introductory material in Chapter One, Chapter Tw o summarized the theoretical background, and some of more widely used general approaches were examined. Overall procedures of regional input-output table construction w ere explored. Chapter Three reviewed previous researches. Individual approaches for technical coefficients or regional trade were explored. Besides this, the characteristics of regional input-output analysis were discussed to compare with national input-output analysis. Chapter Four proposed a new model combining RAS, Location qu otient, Gravity, and Entropy (LOGE) model. In the absence of an input and output table at regional level, one has to depend on the national coefficients. RAS method was suggested to adapt a national coefficients for a different economy at regional level to produce regional technical coefficients with simplifying input data. The surplu s or deficiency of product in each industrial sector at each region was assessed u sing LQ. The measurement of surplus in a region was distributed into regions that had deficiencies by regional trade rate. The interregional trade was constrained by the amount of surplus or deficiency in each sector at each region. The results of regional trade were aggregated to generate regional trade coefficients with adding internal trade of each region. Finally, regional input and output coefficients were produced according to the result that the regional technical coefficients were adjusted by the regional trade coefficients. Chapter Five examined the su ggested model in the previous chapter. The regions for experimental input-output table were composed of four such as Seoul, Incheon, Kyounggi and other. The industrial sectors in this experiment were classified into 26. The national input-output coefficients were adjusted into four regions' technical coefficients with RAS method. The result was modified by LOGE model suggested in this 118

132 study to estimate regional input-output coefficients. In Chapter Six, the stability and the reasonableness of experimental input-output coefficients were tested for four regions by several ways. Finally, Chapter Seven gives the overall conclusions and suggestions for future studies of regional input-output analysis. This research produced a new method of regional input-output analysis specifically designed for a non survey method. An important part of this work is to improve the RAS method that is adaptive with much less information. This method makes possibility to save a lot of time and effort, and activate regional input-output analysis study. LOGE model results in progress at reflecting regional trade on input-output analysis. It takes the advantages for LQ and entropy approaches and eliminates the limits of them partially. The new method results in reasonable result. How ever, the research represents a method in developing regional input-output analysis specifically non-survey method. Future work should consider several issues to improve results, such as more accurate regional technical coefficients, and regional trade, etc. SUMMARY 119

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