Input-Output Model and its Application
3.7 Applications of impact studies
3.7.2 An Impact study sample
I N P U T-O U T P U T M O D E L A N D I T S A P P L I C AT I O N 73
3.7.1.5.4 Visitors ’ definition and compliance
As we will learn in detail in Chapter 5, compliance with a definition of visitors will prevent certain portions of expenditures by local residents (i.e. nonvisitors) from being included in the initial shock.
For example, estimating an impact of a local popular concert in a metropolitan area will result in overestimation of total impacts if you include all the expenditures during the event, because a substantial portion of expenditures include those by local residents. In addition, this would occur with the development of large leisure-infrastructure projects such as museums, arenas, or sports facilities in the urban setting, as much, if not all, of the expected expendi- ture would be made by local residents. An example of estimating the economic impacts of huge tourism-related facilities in or near the urban center would be Tokyo Disneyland, which opened in 1983 and attracted 10 million visitors in the first year and 21 million visitors in 2001. Because Tokyo Disneyland is located at the Tokyo Bay, it is only 10 miles to the central part of Tokyo. But according to various definitions of who can be considered as visitors, more than half of the guests who go to Tokyo Disneyland would not be considered as visitors (i.e.
leisure travelers and nonleisure travelers who travel enough long distance). So the majority of expenditures would be considered to be made by the nonvisitors or locals who spend money as part of daily lives in usual environment. This is a thriving environment, but an impact study of tourists (i.e. visitors) would be smaller because of exclusion of those expenditures by nonvisitors (i.e. local residents).
When dealing with tourism-impact-related studies, defining the tourists or visitors to the study region is important to ensure accurate estimates of their expenditures and their sub- sequent impacts. This is another reason why hospitality and tourism students and scholars have to learn about TSA, which have been predominantly led by professional economists.
3.7.1.5.5 Producers ’ price base as default setting
I-O data are recorded at the producers ’ price, while tourism expenditures data may be recorded by purchasers ’ prices. This will be discussed later.
(C1) IOCode Name
Agriculture, forestry, fishing, and hunting Mining Utilities Construction Manufacturing Wholesale trade Retail trade Transportation and warehousing Information Finance, insurance, real estate, rental, and leasing Professional and business services Educational services, health care, and social assistance entertainment, recreation, accommodation, and food services Other services, except government Government Total Final Uses (GDP) Total Commodity Output
1 Agriculture, forestry, fishing, and hunting
55 800 1 23 912 138 434 1993 258 8 11 1510 5950 603 9154 304 1551 35 794 252 306
2 Mining 386 22 476 60 507 5686 139 358 17 10 2519 1 1451 106 10 28 8 9497 61 579 180 481
3 Utilities 5958 2574 359 3078 48 427 5412 12 364 3311 4819 28 519 14 330 11 433 15 736 5937 48 192 176 990 387 440
4 Construction 895 33 5446 1014 8118 2040 4017 1452 3443 28 388 8256 9357 6248 3735 44 271 868 763 995 474
5 Manufacturing 46 582 17 781 13 808 207 916 1 257 656 40 653 57 564 60 001 69 820 80 111 78 627 114 361 99 728 57 606 194 326 1 400 908 3 797 446 6 Wholesale trade 10 432 2658 2249 23 094 221 251 23 002 7539 11 768 12 030 9909 13 264 16 767 19 517 8583 29 898 447 463 859 423
7 Retail trade 165 287 98 47 482 10 269 1780 2840 1578 541 11 085 5979 2244 2116 6726 156 907 831 1 001 177
8 Transportation and warehousing 7590 4705 24 518 15 712 117 205 13 613 17 547 71 823 9147 27 436 22 354 14 208 8812 5287 35 469 189 589 585 017 9 Information 1178 467 750 8761 38 819 13 147 15 495 9036 193 016 27 802 68 779 33 419 15 520 12 538 58 631 357 572 854 932 10 Finance, insurance, real estate,
rental, and leasing
14 229 17 657 8448 29 222 100 451 37 975 69 142 30 251 59 948 570 465 111 938 115 665 57 455 39 889 75 169 1 877 909 3 215 812
11 Professional and business services 4767 14 160 10 680 77 411 310 604 83 443 122 422 50 723 119 131 239 495 279 027 127 013 48 998 43 689 197 095 384 383 2 113 039 12 Educational services, health care, and
social assistance
9 107 633 105 2 605 700 517 510 2519 955 2129 11 565 600 842 31 559 1 401 975 1 457 327
13 Arts, entertainment, recreation, accommodation, and food services
395 840 1221 2018 18 959 4737 5866 4049 15 270 22 726 28 512 21 189 20 529 4172 20 478 577 658 748 618
14 Other services, except government 3259 287 917 10 189 44 013 7095 7806 8554 13 854 22 132 22 201 11 078 7695 6172 28 486 383 720 577 457
15 Government 113 28 398 1167 3232 3247 4473 1172 4594 9147 13 182 14 200 3218 3746 9607 1 646 870 1 718 393
Total Value Added 98 616 105 593 201 644 464 853 1 351 630 622 864 765 804 294 878 483 972 2 125 736 1 220 153 793 132 371 515 253 712 1 326 717 10 480 820 – Total Industry Output 250 491 190 550 331 777 899 129 3 852 724 869 537 1 094 575 567 444 1 000 982 3 223 070 1 901 251 1 296 479 687 227 454 007 2 128 664 – 18 747 908
Source: Calculated by author based on data from BEA, US Department of Commerce.
Table 3-11 A-matrix of the US data .
Standardized Matrix A Matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
IOCode Name
Agriculture Mining Utilities Construction Manufacturing Wholesale Retail trade Transportation Information Finance, insurance Professional Educational Arts, entertainment Other services Government
1 Agriculture, forestry, fishing, and hunting
0.22276 0.00001 0.00007 0.00101 0.03593 0.00229 0.00024 0.00001 0.00001 0.00047 0.00313 0.00047 0.01332 0.00067 0.00073 2 Mining 0.00154 0.11795 0.18237 0.00632 0.03617 0.00002 0.00001 0.00444 0.00000 0.00045 0.00006 0.00001 0.00004 0.00002 0.00446 3 Utilities 0.02379 0.01351 0.00108 0.00342 0.01257 0.00622 0.01130 0.00583 0.00481 0.00885 0.00754 0.00882 0.02290 0.01308 0.02264 4 Construction 0.00357 0.00017 0.01641 0.00113 0.00211 0.00235 0.00367 0.00256 0.00344 0.00881 0.00434 0.00722 0.00909 0.00823 0.02080 5 Manufacturing 0.18596 0.09331 0.04162 0.23124 0.32643 0.04675 0.05259 0.10574 0.06975 0.02486 0.04136 0.08821 0.14512 0.12688 0.09129 6 Wholesale trade 0.04165 0.01395 0.00678 0.02568 0.05743 0.02645 0.00689 0.02074 0.01202 0.00307 0.00698 0.01293 0.02840 0.01890 0.01405 7 Retail trade 0.00066 0.00151 0.00030 0.05281 0.00267 0.00205 0.00259 0.00278 0.00054 0.00344 0.00314 0.00173 0.00308 0.01481 0.00007 8 Transportation and
warehousing
0.03030 0.02469 0.07390 0.01747 0.03042 0.01566 0.01603 0.12657 0.00914 0.00851 0.01176 0.01096 0.01282 0.01165 0.01666 9 Information 0.00470 0.00245 0.00226 0.00974 0.01008 0.01512 0.01416 0.01592 0.19283 0.00863 0.03618 0.02578 0.02258 0.02762 0.02754 10 Finance, insurance, real
estate, rental, and leasing
0.05680 0.09266 0.02546 0.03250 0.02607 0.04367 0.06317 0.05331 0.05989 0.17699 0.05888 0.08921 0.08360 0.08786 0.03531 11 Professional and business
services
0.01903 0.07431 0.03219 0.08610 0.08062 0.09596 0.11184 0.08939 0.11901 0.07431 0.14676 0.09797 0.07130 0.09623 0.09259 12 Educational services,
health care, and social assistance
0.00004 0.00056 0.00191 0.00012 0.00068 0.00081 0.00047 0.00090 0.00252 0.00030 0.00112 0.00892 0.00087 0.00185 0.01483
13 Arts, entertainment, recreation,
accommodation, and food services
0.00158 0.00441 0.00368 0.00224 0.00492 0.00545 0.00536 0.00714 0.01526 0.00705 0.01500 0.01634 0.02987 0.00919 0.00962
14 Other services, except government
0.01301 0.00151 0.00276 0.01133 0.01142 0.00816 0.00713 0.01507 0.01384 0.00687 0.01168 0.00854 0.01120 0.01359 0.01338 15 Government 0.00045 0.00015 0.00120 0.00130 0.00084 0.00373 0.00409 0.00207 0.00459 0.00284 0.00693 0.01095 0.00468 0.00825 0.00451
Source: Calculated by author based on data from BEA, US Department of Commerce.
Once you have created the A-matrix the next step is to create the I-matrix of the identical size in rows and columns as shown in Table 3-12 .
Then subtract the A-matrix from the I-matrix. The result will be shown in the matrix with the same size in rows and columns as shown in Table 3-13 .
Now, you have to create an inverse of the (I A)-matrix as shown in Table 3-14 to create (I A) 1 .
By adding the column sum, you may calculate type-I output multipliers for each indus- trial sector. But here, we should proceed to conduct an impact studies.
Recall the basis for an impact study is equation 3-10. The only difference now is that we are dealing with larger matrix of 15 15.
( )
( ) ( ) ( )
( )
I A
Leontief inverse matrix
1
15 15 15 1 15 1
Y X
(
) (
change in final demand shown as column vector change iin total output shown as column vector)
If you want to study the increase in final demand for construction sector in the US, say of
$100 million, you will create a final demand column vector such as in Table 3-15 .
Once the change in final demand is expressed as a column vector, you can calculate the multi- plication of matrices using MS-Excel so that the results will be shown in the column vector format.
In the example used here, X has been positioned next to the Y, as shown in Table 3-16 . 3.7.3 Interpretation of the results
After the multiplication of the Leontief inverse matrix by the final demand column vector, you will have the total output column vector. This shows change in total outputs in each sector in response to the initial shock, the change in final demand column vector. Given the initial shock of $100 million increases for the final demand for the construction sector, the manufacturing sector receives the larger increase in their intermediate goods than any other sectors, with the
$39.36 million increase in total output. Construction activities surely require materials, such as steel, concrete, copper wiring, lifts, air-conditioners, security systems, carpets, etc. Professional and business services sector receives the second largest stimulation through the indirect shock, indicating that the construction sector requires substantial services from this sector. Why is that?
We have to think about how the construction sector functions as it requires architects, structural engineers, attorneys, and accountants when they build a multistory high-rise complex. In this way, you can see that the total output in response to the direct (initial) shock of $100 million will be $193 million after adding up the numbers in the total output column vector.
For the sake of comparative policy analyses, you can calculate more than two different events to the same I-O with the same total amount of the final demand column vector to com- pare the patterns of two total outputs. In Table 3-17 , two direct shocks (policy 1 and 2), both for $100 million and resulting changes in total output are shown next to each other. While the
INPUT-OUTPUTMODELANDITSAPPLICATION77 Table 3-12 I-matrix.
Name (I-Matrix)
Agriculture Mining Utilities Construction Manufacturing Wholesale Retail trade Transportation Information Finance, insurance Professional Educational Arts, entertainment Other services Government
1 Agriculture, forestry, fishing, and hunting 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
2 Mining 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
3 Utilities 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
4 Construction 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
5 Manufacturing 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
6 Wholesale trade 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
7 Retail trade 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
8 Transportation and warehousing 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
9 Information 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
10 Finance, insurance, real estate, rental, and leasing 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
11 Professional and business services 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
12 Educational services, health care, and social assistance 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
13 Arts, entertainment, recreation, accommodation, and food services 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
14 Other services, except government 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
15 Government 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
Name: (I A) Matrix
Agricultur Mining Utilities Construction Manufacturing Wholesale Retail trade Transportation Information Finance, insurance Professional Educational Arts, entertainment Other services Government
1 Agriculture, forestry, fishing, and hunting
0.77724 0.00001 0.00007 0.00101 0.03593 0.00229 0.00024 0.00001 0.00001 0.00047 0.00313 0.00047 0.01332 0.00067 0.00073 2 Mining 0.00154 0.88205 0.18237 0.00632 0.03617 0.00002 0.00001 0.00444 0.00000 0.00045 0.00006 0.00001 0.00004 0.00002 0.00446 3 Utilities 0.02379 0.01351 0.99892 0.00342 0.01257 0.00622 0.01130 0.00583 0.00481 0.00885 0.00754 0.00882 0.02290 0.01308 0.02264 4 Construction 0.00357 0.00017 0.01641 0.99887 0.00211 0.00235 0.00367 0.00256 0.00344 0.00881 0.00434 0.00722 0.00909 0.00823 0.02080 5 Manufacturing 0.18596 0.09331 0.04162 0.23124 0.67357 0.04675 0.05259 0.10574 0.06975 0.02486 0.04136 0.08821 0.14512 0.12688 0.09129 6 Wholesale trade 0.04165 0.01395 0.00678 0.02568 0.05743 0.97355 0.00689 0.02074 0.01202 0.00307 0.00698 0.01293 0.02840 0.01890 0.01405 7 Retail trade 0.00066 0.00151 0.00030 0.05281 0.00267 0.00205 0.99741 0.00278 0.00054 0.00344 0.00314 0.00173 0.00308 0.01481 0.00007 8 Transportation and
warehousing
0.03030 0.02469 0.07390 0.01747 0.03042 0.01566 0.01603 0.87343 0.00914 0.00851 0.01176 0.01096 0.01282 0.01165 0.01666 9 Information 0.00470 0.00245 0.00226 0.00974 0.01008 0.01512 0.01416 0.01592 0.80717 0.00863 0.03618 0.02578 0.02258 0.02762 0.02754 10 Finance, insurance,
real estate, rental, and leasing
0.05680 0.09266 0.02546 0.03250 0.02607 0.04367 0.06317 0.05331 0.05989 0.82301 0.05888 0.08921 0.08360 0.08786 0.03531
11 Professional and business services
0.01903 0.07431 0.03219 0.08610 0.08062 0.09596 0.11184 0.08939 0.11901 0.07431 0.85324 0.09797 0.07130 0.09623 0.09259
12 Educational services, health care, and social assistance
0.00004 0.00056 0.00191 0.00012 0.00068 0.00081 0.00047 0.00090 0.00252 0.00030 0.00112 0.99108 0.00087 0.00185 0.01483
13 Arts, entertainment, recreation, accommodation, and food services
0.00158 0.00441 0.00368 0.00224 0.00492 0.00545 0.00536 0.00714 0.01526 0.00705 0.01500 0.01634 0.97013 0.00919 0.00962
14 Other services, except government
0.01301 0.00151 0.00276 0.01133 0.01142 0.00816 0.00713 0.01507 0.01384 0.00687 0.01168 0.00854 0.01120 0.98641 0.01338 15 Government 0.00045 0.00015 0.00120 0.00130 0.00084 0.00373 0.00409 0.00207 0.00459 0.00284 0.00693 0.01095 0.00468 0.00825 0.99549
Table 3.14 (I A) 1 -matrix .
Name: [I A]^ 1 [Inverse of (I A) matrix]
Agriculture Mining Utilities Const ruction Manufacturing Wholesale Retail trade Transportation Information Finance, insurance Professional Educational Arts, entertainment Other services Government
1 Agriculture, forestry, fishing, and hunting 1.306451 0.009988 0.006893 0.020632 0.073747 0.008633 0.006513 0.011385 0.009584 0.004903 0.01036 0.010102 0.031369 0.013151 0.010698 2 Mining 0.027875 1.146573 0.214653 0.026418 0.07029 0.006714 0.008287 0.01786 0.010127 0.006736 0.007533 0.010935 0.018359 0.014581 0.019189 3 Utilities 0.040348 0.021697 1.008521 0.013281 0.02675 0.010737 0.0162 0.013598 0.012896 0.013974 0.013374 0.015734 0.031915 0.02104 0.029096 4 Construction 0.008667 0.003498 0.018619 1.004666 0.006684 0.00469 0.006394 0.006082 0.007774 0.012335 0.007569 0.01087 0.013278 0.012149 0.024026 5 Manufacturing 0.408434 0.194697 0.132227 0.393636 1.564453 0.102606 0.112917 0.220797 0.17387 0.072906 0.107062 0.17778 0.274746 0.239088 0.186892 6 Wholesale trade 0.0847 0.031862 0.022431 0.055032 0.101402 1.036801 0.017587 0.041773 0.030551 0.011227 0.01863 0.028869 0.05201 0.038956 0.030925 7 Retail trade 0.004064 0.003812 0.003033 0.055742 0.006471 0.003719 1.004493 0.005609 0.003285 0.005832 0.005375 0.004309 0.006188 0.017793 0.003228 8 Transportation and warehousing 0.069052 0.04608 0.099601 0.042419 0.067914 0.027191 0.028633 1.160002 0.026722 0.019055 0.024747 0.026576 0.034702 0.030623 0.034298 9 Information 0.023587 0.016584 0.013681 0.030041 0.034849 0.029776 0.029592 0.036977 1.255492 0.021674 0.059549 0.046482 0.04392 0.050171 0.048103 10 Finance, insurance, real estate, rental,
and leasing
0.130576 0.155637 0.078708 0.085119 0.094842 0.077583 0.102396 0.107554 0.124565 1.235151 0.104509 0.141409 0.141854 0.144281 0.078359 11 Professional and business services 0.108678 0.146653 0.0957 0.175106 0.194394 0.145314 0.165579 0.169959 0.2177 0.126976 1.212217 0.166184 0.149525 0.173787 0.158838 12 Educational services, health care, and
social assistance
0.000878 0.001208 0.002498 0.000946 0.001765 0.001345 0.00105 0.001724 0.003866 0.000785 0.001893 1.00981 0.001722 0.002739 0.015696 13 Arts, entertainment, recreation,
accommodation, and food services
0.008798 0.010625 0.008821 0.009509 0.014145 0.010142 0.010523 0.014381 0.02579 0.012183 0.021714 0.023058 1.037379 0.01631 0.015888 14 Other services, except government 0.026677 0.008448 0.008752 0.021215 0.024955 0.013296 0.01267 0.024478 0.024466 0.012143 0.018389 0.01585 0.020135 1.021987 0.020573 15 Government 0.002988 0.002274 0.002785 0.004026 0.004029 0.005614 0.006124 0.004755 0.008388 0.004875 0.009556 0.013495 0.00731 0.010964 1.006935
Table 3-15 Final demand column vector .
Change in FD delta Y 1 Agriculture, forestry, fishing, and hunting 0
2 Mining 0
3 Utilities 0
4 Construction 100.00
5 Manufacturing 0
6 Wholesale trade 0
7 Retail trade 0
8 Transportation of warehousing 0
9 Information 0
10 Finance, insurance, real estate, rental, and leasing 0
11 Professional and business services 0
12 Educational services, health care, and social assistance 0 13 Arts, entertainment, recreation, accommodation, and food services 0
14 Other services, expect government 0
15 Government 0
sizes of the total output appear to be similar, the distribution of indirect shock looks different over the two total outputs.
In Table 3-17 , the same amounts of direct (initial) shocks are given to two different indus- trial sectors. Policy 1 is to assume an increase in final demand for the construction sector for
$100 million, and policy 2 is to assume increase in final demand for the information sector for $100 million. Do you see different patterns of distributions of indirect impacts over two policies? If you are the manufacturing sector, which one do you prefer to see assuming you would be happier with higher numbers? How about the case that you are working in the pro- fessional and business services sector? What you see is the magnitude of interdependencies among the different industrial sectors. No industrial sectors exist in isolation, even though some people may only be interested in learning the particular industry of their concern. I-O modeling can show you such intricate interdependencies among industrial sectors.