Added IMPLAN and REMI comparison
This commit is contained in:
Alex Gebben Work
parent
bafc0b89d7
commit
1407b56e56
@ -9,17 +9,11 @@ lapply(2028:2035,GET_FILE_WY) %>% bind_rows()%>% rename(Income=`Labor Income`)
|
|||||||
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
||||||
DATA <- DATA %>% pivot_longer(-c(Impact,year,Region)) %>% rename(Type=Impact,Impact=name)
|
DATA <- DATA %>% pivot_longer(-c(Impact,year,Region)) %>% rename(Type=Impact,Impact=name)
|
||||||
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
||||||
|
|
||||||
return(DATA)
|
return(DATA)
|
||||||
}
|
}
|
||||||
|
|
||||||
DATA <- GET_DATA()
|
DATA <- GET_DATA()
|
||||||
TEMP <- DATA %>% filter(year==2035)
|
|
||||||
TEMP <- DATA %>% filter(year==2035)
|
|
||||||
RES <- TEMP %>% mutate(year=2036)
|
|
||||||
for(i in 2037:2060){
|
|
||||||
RES <- RES %>% rbind(TEMP %>% mutate(year=i))
|
|
||||||
}
|
|
||||||
DATA <- DATA %>% rbind(RES)
|
|
||||||
DATA$Type <- factor(DATA$Type,levels=c("Direct","Indirect","Induced"))
|
DATA$Type <- factor(DATA$Type,levels=c("Direct","Indirect","Induced"))
|
||||||
DATA
|
DATA
|
||||||
EMP_WY <- DATA %>% filter(Impact=="Employment",Region=="WY")
|
EMP_WY <- DATA %>% filter(Impact=="Employment",Region=="WY")
|
||||||
|
|||||||
2
Model_Outputs/IMPLAN/US/US_2036/direct_leakages.csv
Normal file
2
Model_Outputs/IMPLAN/US/US_2036/direct_leakages.csv
Normal file
@ -0,0 +1,2 @@
|
|||||||
|
Institutional Commodity Sales,Margin,Imports to Region
|
||||||
|
N/A,N/A,N/A
|
||||||
|
@ -0,0 +1,5 @@
|
|||||||
|
Impact,Employment,Labor Income,Value Added,Output
|
||||||
|
1 - Direct,106.09,"$15,939,474.69","$40,624,924.09","$68,764,934.26"
|
||||||
|
2 - Indirect,148.16,"$14,596,038.51","$25,133,965.67","$46,037,858.86"
|
||||||
|
3 - Induced,190.19,"$13,701,304.07","$25,742,691.35","$43,651,855.42"
|
||||||
|
,444.45,"$44,236,817.27","$91,501,581.11","$158,454,648.54"
|
||||||
|
@ -0,0 +1,529 @@
|
|||||||
|
,Display Code,Display Description,Industry Total Output,Impact Output,Percentage of Total Industry Output
|
||||||
|
1,21,Coal mining,"$40,369,797,410.22","$49,171,541.61",0.12%
|
||||||
|
2,174,Explosives manufacturing,"$3,336,015,892.42","$557,148.17",0.02%
|
||||||
|
3,418,"Data processing, hosting, and related services","$490,713,862,620.46","$22,825,655.45",0.00%
|
||||||
|
4,204,Ground or treated mineral and earth manufacturing,"$5,072,828,802.03","$200,722.47",0.00%
|
||||||
|
5,187,Rubber and plastics hoses and belting manufacturing,"$9,316,374,290.80","$175,521.73",0.00%
|
||||||
|
6,159,Nitrogenous fertilizer manufacturing,"$22,680,233,557.39","$382,011.96",0.00%
|
||||||
|
7,161,Fertilizer mixing,"$6,609,942,413.23","$74,335.18",0.00%
|
||||||
|
8,160,Phosphatic fertilizer manufacturing,"$9,646,258,713.74","$107,959.31",0.00%
|
||||||
|
9,26,Stone mining and quarrying,"$22,604,707,721.04","$250,641.45",0.00%
|
||||||
|
10,397,Rail transportation,"$92,013,918,170.42","$1,000,823.92",0.00%
|
||||||
|
11,297,"Capacitor, resistor, coil, transformer, and other inductor manufacturing","$4,022,032,100.41","$34,786.94",0.00%
|
||||||
|
12,435,Commercial and industrial machinery and equipment rental and leasing,"$163,914,676,099.25","$1,231,253.21",0.00%
|
||||||
|
13,256,Oil and gas field machinery and equipment manufacturing,"$27,836,734,479.74","$204,316.89",0.00%
|
||||||
|
14,240,"Turned product and screw, nut, and bolt manufacturing","$26,510,037,196.43","$188,323.71",0.00%
|
||||||
|
15,378,"Wholesale - Machinery, equipment, and supplies","$272,916,323,584.73","$1,763,234.74",0.00%
|
||||||
|
16,149,Petroleum lubricating oil and grease manufacturing,"$18,666,710,968.47","$113,644.46",0.00%
|
||||||
|
17,28,"Other clay, ceramic, refractory minerals mining","$1,521,594,772.12","$8,832.59",0.00%
|
||||||
|
18,436,Lessors of nonfinancial intangible assets,"$404,607,845,390.93","$2,264,368.14",0.00%
|
||||||
|
19,55,Maintenance and repair construction of nonresidential structures,"$267,609,881,754.15","$1,462,834.97",0.00%
|
||||||
|
20,414,Cable and other subscription programming,"$129,841,466,724.49","$693,447.59",0.00%
|
||||||
|
21,413,Radio and television broadcasting,"$126,652,960,389.18","$665,148.99",0.00%
|
||||||
|
22,150,All other petroleum and coal products manufacturing,"$8,428,002,939.59","$43,985.77",0.00%
|
||||||
|
23,451,Management of companies and enterprises,"$819,034,418,120.62","$3,939,239.78",0.00%
|
||||||
|
24,186,Tire manufacturing,"$25,656,100,926.70","$115,651.77",0.00%
|
||||||
|
25,16,Commercial logging,"$9,708,016,677.17","$41,034.19",0.00%
|
||||||
|
26,255,Mining machinery and equipment manufacturing,"$4,397,435,102.03","$18,468.53",0.00%
|
||||||
|
27,277,Conveyor and conveying equipment manufacturing,"$13,017,551,319.85","$49,587.24",0.00%
|
||||||
|
28,443,"Other computer related services, including facilities management","$72,014,303,860.80","$268,799.01",0.00%
|
||||||
|
29,424,Other financial investment activities,"$568,453,393,226.55","$2,103,969.86",0.00%
|
||||||
|
30,384,Wholesale - Wholesale electronic markets and agents and brokers,"$49,334,634,320.94","$179,687.06",0.00%
|
||||||
|
31,509,Federal electric utilities,"$15,278,393,331.48","$54,093.74",0.00%
|
||||||
|
32,515,Local government electric utilities,"$63,242,600,402.80","$222,744.76",0.00%
|
||||||
|
33,512,State government electric utilities,"$2,138,213,300.81","$7,518.79",0.00%
|
||||||
|
34,403,Couriers and messengers,"$147,389,575,412.04","$517,676.75",0.00%
|
||||||
|
35,39,Electric power generation - Geothermal,"$1,089,212,605.47","$3,801.12",0.00%
|
||||||
|
36,34,Electric power generation - Hydroelectric,"$11,150,299,722.30","$38,912.13",0.00%
|
||||||
|
37,36,Electric power generation - Nuclear,"$48,600,191,094.94","$169,604.12",0.00%
|
||||||
|
38,35,Electric power generation - Fossil fuel,"$160,038,429,255.06","$558,499.39",0.00%
|
||||||
|
39,40,Electric power generation - Biomass,"$3,248,354,871.06","$11,336.05",0.00%
|
||||||
|
40,38,Electric power generation - Wind,"$31,436,960,621.21","$109,708.17",0.00%
|
||||||
|
41,37,Electric power generation - Solar,"$15,183,687,778.59","$52,987.78",0.00%
|
||||||
|
42,41,Electric power generation - All other,"$598,610,063.76","$2,089.02",0.00%
|
||||||
|
43,42,Electric power transmission and distribution,"$454,802,637,163.46","$1,584,517.19",0.00%
|
||||||
|
44,382,Wholesale - Petroleum and petroleum products,"$229,944,278,945.40","$786,531.47",0.00%
|
||||||
|
45,188,Other rubber product manufacturing,"$18,947,852,104.12","$64,079.11",0.00%
|
||||||
|
46,109,Knit fabric mills,"$1,209,761,149.04","$3,991.35",0.00%
|
||||||
|
47,455,Business support services,"$98,531,422,147.59","$320,531.62",0.00%
|
||||||
|
48,292,Other communications equipment manufacturing,"$8,476,374,888.63","$27,323.44",0.00%
|
||||||
|
49,454,Employment services,"$472,021,118,180.87","$1,467,988.93",0.00%
|
||||||
|
50,447,"Advertising, public relations, and related services","$221,366,844,538.02","$687,986.98",0.00%
|
||||||
|
51,15,"Forestry, forest products, and timber tract production","$1,221,569,839.28","$3,778.72",0.00%
|
||||||
|
52,445,Environmental and other technical consulting services,"$89,248,872,652.10","$262,970.53",0.00%
|
||||||
|
53,197,Concrete block and brick manufacturing,"$7,704,656,442.20","$22,625.82",0.00%
|
||||||
|
54,508,Postal service,"$82,216,438,935.22","$234,187.56",0.00%
|
||||||
|
55,452,Office administrative services,"$100,789,973,631.90","$282,504.23",0.00%
|
||||||
|
56,420,Internet publishing and broadcasting and web search portals,"$414,801,592,441.37","$1,154,940.14",0.00%
|
||||||
|
57,146,Petroleum refineries,"$685,338,713,966.20","$1,889,833.00",0.00%
|
||||||
|
58,479,Commercial Sports Except Racing,"$62,631,985,438.99","$171,512.79",0.00%
|
||||||
|
59,444,Management consulting services,"$314,984,356,065.88","$842,599.91",0.00%
|
||||||
|
60,152,Industrial gas manufacturing,"$43,958,605,364.15","$116,263.15",0.00%
|
||||||
|
61,489,"Hotels and motels, including casino hotels","$302,713,260,503.92","$791,134.19",0.00%
|
||||||
|
62,402,Scenic and sightseeing transportation and support activities for transportation,"$104,344,680,337.25","$270,940.25",0.00%
|
||||||
|
63,29,Other nonmetallic mineral mining and quarrying,"$4,952,677,588.17","$12,825.83",0.00%
|
||||||
|
64,458,Services to buildings,"$184,887,389,840.19","$474,652.50",0.00%
|
||||||
|
65,498,Personal and household goods repair and maintenance,"$94,503,403,255.95","$237,899.69",0.00%
|
||||||
|
66,456,Travel arrangement and reservation services,"$92,038,956,694.17","$229,162.73",0.00%
|
||||||
|
67,175,Custom compounding of purchased resins,"$12,008,896,270.80","$29,538.08",0.00%
|
||||||
|
68,243,"Electroplating, anodizing, and coloring metal","$10,213,542,501.68","$25,071.76",0.00%
|
||||||
|
69,422,Securities and commodity contracts intermediation and brokerage,"$336,923,424,190.27","$821,765.04",0.00%
|
||||||
|
70,438,"Accounting, tax preparation, bookkeeping, and payroll services","$252,043,367,578.02","$609,340.00",0.00%
|
||||||
|
71,460,Other support services,"$93,493,521,065.46","$225,860.47",0.00%
|
||||||
|
72,404,Warehousing and storage,"$196,283,203,045.69","$472,400.06",0.00%
|
||||||
|
73,401,Pipeline transportation,"$77,957,430,742.25","$187,363.71",0.00%
|
||||||
|
74,497,Commercial and industrial machinery and equipment repair and maintenance,"$85,670,457,574.57","$203,494.46",0.00%
|
||||||
|
75,437,Legal services,"$482,145,097,198.44","$1,135,484.79",0.00%
|
||||||
|
76,267,Cutting tool and machine tool accessory manufacturing,"$5,551,423,774.72","$12,930.50",0.00%
|
||||||
|
77,433,General and consumer goods rental except video tapes and discs,"$42,284,280,595.86","$98,232.89",0.00%
|
||||||
|
78,241,Metal heat treating,"$6,751,197,386.48","$15,636.32",0.00%
|
||||||
|
79,423,Monetary authorities and depository credit intermediation,"$1,051,353,970,355.11","$2,420,169.75",0.00%
|
||||||
|
80,242,Metal coating and nonprecious engraving,"$23,546,385,576.93","$53,630.39",0.00%
|
||||||
|
81,421,Nondepository credit intermediation and related activities,"$368,150,305,019.85","$836,786.08",0.00%
|
||||||
|
82,406,Periodical publishers,"$28,726,880,599.05","$65,211.75",0.00%
|
||||||
|
83,408,"Directory, mailing list, and other publishers","$7,978,064,909.53","$18,074.33",0.00%
|
||||||
|
84,210,Steel wire drawing,"$6,965,034,108.99","$15,691.09",0.00%
|
||||||
|
85,432,Automotive equipment rental and leasing,"$101,150,564,838.62","$227,008.71",0.00%
|
||||||
|
86,200,Lime manufacturing,"$3,411,426,132.51","$7,629.10",0.00%
|
||||||
|
87,405,Newspaper publishers,"$23,494,267,330.25","$51,245.36",0.00%
|
||||||
|
88,145,Support activities for printing,"$3,010,426,339.58","$6,473.01",0.00%
|
||||||
|
89,481,"Independent artists, writers, and performers","$78,191,306,536.76","$167,855.09",0.00%
|
||||||
|
90,144,Printing,"$93,711,787,715.49","$200,719.54",0.00%
|
||||||
|
91,232,Ornamental and architectural metal work manufacturing,"$13,344,844,055.97","$28,501.19",0.00%
|
||||||
|
92,398,Water transportation,"$76,976,695,291.27","$161,838.89",0.00%
|
||||||
|
93,505,Business and professional associations,"$73,615,227,688.04","$154,327.30",0.00%
|
||||||
|
94,510,Other federal government enterprises,"$6,854,090,185.53","$14,287.75",0.00%
|
||||||
|
95,450,"All other miscellaneous professional, scientific, and technical services","$157,757,114,044.05","$328,047.71",0.00%
|
||||||
|
96,459,Landscape and horticultural services,"$165,786,078,305.71","$342,343.63",0.00%
|
||||||
|
97,410,Software publishers,"$481,752,923,538.80","$992,274.71",0.00%
|
||||||
|
98,482,Promoters of performing arts and sports and agents for public figures,"$104,291,578,963.74","$213,170.87",0.00%
|
||||||
|
99,25,Other metal ore mining,"$4,177,930,861.03","$8,471.79",0.00%
|
||||||
|
100,491,Full-service restaurants,"$600,936,370,418.40","$1,204,900.69",0.00%
|
||||||
|
101,457,Investigation and security services,"$87,760,959,501.87","$175,862.04",0.00%
|
||||||
|
102,367,Office supplies (except paper) manufacturing,"$3,995,757,626.34","$7,995.61",0.00%
|
||||||
|
103,399,Truck transportation,"$517,459,714,328.88","$1,033,618.98",0.00%
|
||||||
|
104,140,Paper bag and coated and treated paper manufacturing,"$30,547,994,057.47","$60,318.13",0.00%
|
||||||
|
105,221,Custom roll forming,"$3,403,758,221.65","$6,684.66",0.00%
|
||||||
|
106,427,"Insurance agencies, brokerages, and related activities","$585,130,407,048.46","$1,147,166.51",0.00%
|
||||||
|
107,129,Wood windows and door manufacturing,"$22,029,620,673.99","$43,050.51",0.00%
|
||||||
|
108,245,Plumbing fixture fitting and trim manufacturing,"$9,308,325,168.81","$18,188.96",0.00%
|
||||||
|
109,379,Wholesale - Other durable goods merchant wholesalers,"$449,293,100,012.76","$876,103.14",0.00%
|
||||||
|
110,478,Performing arts companies,"$40,958,746,144.37","$78,876.00",0.00%
|
||||||
|
111,448,Photographic services,"$18,611,681,469.69","$35,493.00",0.00%
|
||||||
|
112,514,Local government passenger transit,"$14,082,847,680.82","$26,828.60",0.00%
|
||||||
|
113,511,State government passenger transit,"$1,585,108,785.26","$3,019.72",0.00%
|
||||||
|
114,383,Wholesale - Other nondurable goods merchant wholesalers,"$498,207,099,055.25","$941,620.88",0.00%
|
||||||
|
115,196,Ready-mix concrete manufacturing,"$58,086,367,893.64","$109,448.40",0.00%
|
||||||
|
116,173,Printing ink manufacturing,"$4,197,932,161.56","$7,887.61",0.00%
|
||||||
|
117,336,"Motor vehicle steering, suspension component (except spring), and brake systems manufacturing","$31,275,001,836.88","$58,306.00",0.00%
|
||||||
|
118,440,Specialized design services,"$61,729,364,047.76","$113,144.18",0.00%
|
||||||
|
119,417,"Satellite, telecommunications resellers, and all other telecommunications","$54,450,354,517.14","$99,766.68",0.00%
|
||||||
|
120,400,Transit and ground passenger transportation,"$169,895,344,811.88","$310,805.71",0.00%
|
||||||
|
121,237,Hardware manufacturing,"$11,360,442,824.27","$20,650.84",0.00%
|
||||||
|
122,157,Synthetic rubber manufacturing,"$8,809,185,115.22","$15,998.49",0.00%
|
||||||
|
123,222,"Metal crown, closure, and other metal stamping (except automotive)","$16,762,914,724.24","$30,383.33",0.00%
|
||||||
|
124,151,Petrochemical manufacturing,"$213,898,809,710.92","$387,576.90",0.00%
|
||||||
|
125,43,Natural gas distribution,"$112,805,479,068.56","$204,020.08",0.00%
|
||||||
|
126,195,Cement manufacturing,"$16,124,794,202.42","$29,095.26",0.00%
|
||||||
|
127,20,Oil and gas extraction,"$440,054,943,164.76","$787,995.92",0.00%
|
||||||
|
128,239,Machine shops,"$58,418,188,845.25","$104,089.63",0.00%
|
||||||
|
129,131,"Other millwork, including flooring","$11,872,958,758.31","$21,040.51",0.00%
|
||||||
|
130,331,Motor vehicle electrical and electronic equipment manufacturing,"$34,158,562,770.31","$60,133.36",0.00%
|
||||||
|
131,396,Air transportation,"$328,394,890,891.02","$577,723.32",0.00%
|
||||||
|
132,493,All other food and drinking places,"$276,447,241,992.94","$484,416.49",0.00%
|
||||||
|
133,254,Construction machinery manufacturing,"$64,676,876,659.63","$113,108.81",0.00%
|
||||||
|
134,130,"Cut stock, resawing lumber, and planing","$5,556,595,473.11","$9,489.27",0.00%
|
||||||
|
135,137,Paper mills,"$44,700,830,052.02","$76,061.42",0.00%
|
||||||
|
136,416,Wireless telecommunications carriers (except satellite),"$281,219,972,666.90","$476,257.73",0.00%
|
||||||
|
137,348,Wood kitchen cabinet and countertop manufacturing,"$26,738,664,990.47","$45,130.26",0.00%
|
||||||
|
138,332,Motor vehicle transmission and power train parts manufacturing,"$56,149,762,088.25","$94,324.30",0.00%
|
||||||
|
139,494,"Automotive repair and maintenance, except car washes","$259,004,621,107.04","$431,933.72",0.00%
|
||||||
|
140,496,Electronic and precision equipment repair and maintenance,"$90,952,976,406.77","$151,118.60",0.00%
|
||||||
|
141,487,Fitness and recreational sports centers,"$40,757,208,080.88","$67,661.35",0.00%
|
||||||
|
142,138,Paperboard mills,"$37,769,326,092.36","$62,653.04",0.00%
|
||||||
|
143,486,Other amusement and recreation industries,"$73,097,118,023.77","$120,627.99",0.00%
|
||||||
|
144,185,Other plastics product manufacturing,"$119,757,914,903.54","$196,959.07",0.00%
|
||||||
|
145,426,"Insurance carriers, except direct life","$763,623,938,208.92","$1,255,212.18",0.00%
|
||||||
|
146,139,Paperboard container manufacturing,"$102,476,045,826.39","$167,828.59",0.00%
|
||||||
|
147,385,Retail - Motor vehicle and parts dealers,"$434,107,458,121.98","$703,044.31",0.00%
|
||||||
|
148,22,"Copper, nickel, lead, and zinc mining","$16,824,067,205.75","$27,007.67",0.00%
|
||||||
|
149,125,Wood preservation,"$12,385,421,188.04","$19,872.92",0.00%
|
||||||
|
150,461,Waste management and remediation services,"$177,999,302,351.73","$284,975.10",0.00%
|
||||||
|
151,490,Other accommodations,"$16,436,225,502.96","$26,223.05",0.00%
|
||||||
|
152,375,Wholesale - Motor vehicle and motor vehicle parts and supplies,"$223,214,885,088.06","$356,032.05",0.00%
|
||||||
|
153,391,Retail - Gasoline stores,"$126,195,524,793.46","$201,003.69",0.00%
|
||||||
|
154,412,Sound recording industries,"$31,525,668,537.03","$49,954.06",0.00%
|
||||||
|
155,462,Elementary and secondary schools,"$74,365,925,030.62","$117,826.21",0.00%
|
||||||
|
156,476,Child day care services,"$86,623,931,960.28","$136,876.09",0.00%
|
||||||
|
157,477,"Community food, housing, and other relief services, including rehabilitation services","$75,132,562,981.36","$118,583.74",0.00%
|
||||||
|
158,507,Private households,"$27,265,934,911.83","$42,959.12",0.00%
|
||||||
|
159,429,Other real estate,"$2,063,772,881,991.79","$3,237,956.31",0.00%
|
||||||
|
160,504,"Grantmaking, giving, and social advocacy organizations","$113,894,762,036.97","$178,591.04",0.00%
|
||||||
|
161,495,Car washes,"$35,373,724,638.09","$55,460.73",0.00%
|
||||||
|
162,475,Individual and family services,"$197,385,106,011.81","$309,430.43",0.00%
|
||||||
|
163,124,Sawmills,"$42,023,969,480.44","$65,811.93",0.00%
|
||||||
|
164,116,Other textile product mills,"$5,849,355,190.48","$9,160.42",0.00%
|
||||||
|
165,10,All other crop farming,"$22,224,392,154.07","$34,736.80",0.00%
|
||||||
|
166,503,Religious organizations,"$160,924,588,099.97","$251,438.87",0.00%
|
||||||
|
167,492,Limited-service restaurants,"$662,772,350,208.32","$1,033,274.20",0.00%
|
||||||
|
168,472,Hospitals,"$1,246,642,306,210.30","$1,940,975.50",0.00%
|
||||||
|
169,480,Racing and Track Operation,"$2,466,251,193.93","$3,836.47",0.00%
|
||||||
|
170,463,"Junior colleges, colleges, universities, and professional schools","$186,018,928,364.07","$289,074.99",0.00%
|
||||||
|
171,393,"Retail - Sporting goods, hobby, musical instrument and book stores","$61,905,238,781.01","$96,141.09",0.00%
|
||||||
|
172,431,Owner-occupied housing,"$2,353,458,000,000.00","$3,634,793.77",0.00%
|
||||||
|
173,386,Retail - Furniture and home furnishings stores,"$93,528,063,975.59","$144,413.90",0.00%
|
||||||
|
174,488,Bowling centers,"$4,651,609,193.39","$7,156.52",0.00%
|
||||||
|
175,464,Other educational services,"$150,226,479,511.36","$231,031.94",0.00%
|
||||||
|
176,483,"Museums, historical sites, zoos, and parks","$21,110,396,931.65","$32,329.73",0.00%
|
||||||
|
177,395,Retail - Miscellaneous store retailers,"$129,919,424,150.68","$198,774.56",0.00%
|
||||||
|
178,224,Nonferrous forging,"$5,015,019,698.50","$7,665.30",0.00%
|
||||||
|
179,471,Other ambulatory health care services,"$53,046,213,789.29","$80,834.43",0.00%
|
||||||
|
180,387,Retail - Electronics and appliance stores,"$41,359,701,013.28","$63,011.59",0.00%
|
||||||
|
181,377,Wholesale - Household appliances and electrical and electronic goods,"$342,854,761,705.01","$521,416.72",0.00%
|
||||||
|
182,394,Retail - General merchandise stores,"$308,393,207,557.39","$468,733.90",0.00%
|
||||||
|
183,102,Wineries,"$27,858,635,866.29","$42,244.74",0.00%
|
||||||
|
184,56,Maintenance and repair construction of residential structures,"$98,054,032,324.42","$148,324.88",0.00%
|
||||||
|
185,502,Other personal services,"$133,455,503,992.02","$201,847.42",0.00%
|
||||||
|
186,389,Retail - Food and beverage stores,"$340,025,954,447.09","$513,886.12",0.00%
|
||||||
|
187,499,Personal care services,"$99,129,280,065.60","$149,706.49",0.00%
|
||||||
|
188,155,Other basic organic chemical manufacturing,"$131,029,741,770.06","$196,194.81",0.00%
|
||||||
|
189,390,Retail - Health and personal care stores,"$203,751,544,401.25","$304,243.19",0.00%
|
||||||
|
190,392,Retail - Clothing and clothing accessories stores,"$198,706,276,487.90","$296,100.07",0.00%
|
||||||
|
191,425,Direct life insurance carriers,"$118,798,771,122.27","$176,993.54",0.00%
|
||||||
|
192,466,Offices of dentists,"$187,241,521,354.72","$278,772.00",0.00%
|
||||||
|
193,513,Other state government enterprises,"$26,495,170,772.45","$39,439.52",0.00%
|
||||||
|
194,225,"Cutlery, utensil, pot, and pan manufacturing","$6,082,978,046.85","$9,047.92",0.00%
|
||||||
|
195,179,Unlaminated plastics profile shape manufacturing,"$13,911,022,377.80","$20,646.89",0.00%
|
||||||
|
196,516,Other local government enterprises,"$353,931,726,040.53","$525,002.33",0.00%
|
||||||
|
197,469,Medical and diagnostic laboratories,"$74,051,262,622.56","$109,836.59",0.00%
|
||||||
|
198,465,Offices of physicians,"$710,425,690,758.33","$1,050,562.47",0.00%
|
||||||
|
199,467,Offices of other health practitioners,"$173,037,357,927.83","$255,385.39",0.00%
|
||||||
|
200,238,Spring and wire product manufacturing,"$14,446,923,138.19","$21,259.10",0.00%
|
||||||
|
201,411,Motion picture and video industries,"$175,387,116,345.71","$257,794.59",0.00%
|
||||||
|
202,506,Labor and civic organizations,"$81,538,720,493.49","$119,765.25",0.00%
|
||||||
|
203,103,Distilleries,"$24,706,251,736.01","$36,056.97",0.00%
|
||||||
|
204,184,Plastics bottle manufacturing,"$20,649,244,775.09","$30,030.97",0.00%
|
||||||
|
205,468,Outpatient care centers,"$254,994,924,915.48","$370,740.93",0.00%
|
||||||
|
206,428,"Funds, trusts, and other financial vehicles","$250,966,777,497.55","$364,416.10",0.00%
|
||||||
|
207,170,Polish and other sanitation good manufacturing,"$16,183,293,849.81","$23,497.27",0.00%
|
||||||
|
208,219,Ferrous metal foundries,"$23,423,417,307.88","$34,002.17",0.00%
|
||||||
|
209,470,Home health care services,"$148,884,219,821.65","$216,011.54",0.00%
|
||||||
|
210,415,Wired telecommunications carriers,"$312,303,330,075.70","$452,177.54",0.00%
|
||||||
|
211,380,Wholesale - Drugs and druggists’ sundries,"$309,662,881,498.50","$447,842.46",0.00%
|
||||||
|
212,6,"Greenhouse, nursery, and floriculture production","$22,144,501,907.28","$31,911.16",0.00%
|
||||||
|
213,142,Sanitary paper product manufacturing,"$26,241,333,823.37","$37,812.98",0.00%
|
||||||
|
214,223,Iron and steel forging,"$12,167,051,489.94","$17,515.10",0.00%
|
||||||
|
215,207,Iron and steel mills and ferroalloy manufacturing,"$149,440,127,992.66","$214,790.48",0.00%
|
||||||
|
216,58,Dog and cat food manufacturing,"$42,027,131,811.09","$60,221.28",0.00%
|
||||||
|
217,229,Plate work manufacturing,"$15,417,788,320.32","$22,083.53",0.00%
|
||||||
|
218,484,Amusement parks and arcades,"$27,154,350,236.67","$38,855.62",0.00%
|
||||||
|
219,27,Sand and gravel mining,"$15,322,656,295.20","$21,876.18",0.00%
|
||||||
|
220,485,Gambling industries (except casino hotels),"$101,991,637,088.28","$145,586.32",0.00%
|
||||||
|
221,93,Other snack food manufacturing,"$38,904,968,131.82","$55,404.83",0.00%
|
||||||
|
222,95,Flavoring syrup and concentrate manufacturing,"$19,967,854,524.95","$28,400.89",0.00%
|
||||||
|
223,335,Other motor vehicle parts manufacturing,"$82,749,766,548.59","$117,556.36",0.00%
|
||||||
|
224,193,Glass container manufacturing,"$6,929,253,311.43","$9,824.79",0.00%
|
||||||
|
225,101,Breweries,"$37,340,990,790.38","$52,903.08",0.00%
|
||||||
|
226,419,"News syndicates, libraries, archives and all other information services","$14,781,928,744.45","$20,914.26",0.00%
|
||||||
|
227,226,Handtool manufacturing,"$9,269,806,810.85","$13,105.14",0.00%
|
||||||
|
228,99,Bottled and canned soft drinks and water,"$80,995,242,643.80","$113,890.01",0.00%
|
||||||
|
229,501,Dry-cleaning and laundry services,"$34,655,282,874.23","$48,527.58",0.00%
|
||||||
|
230,163,Medicinal and botanical manufacturing,"$28,560,581,365.00","$39,970.99",0.00%
|
||||||
|
231,319,Fiber optic cable manufacturing,"$7,685,160,408.73","$10,716.57",0.00%
|
||||||
|
232,247,Small arms ammunition manufacturing,"$5,874,067,458.05","$8,162.53",0.00%
|
||||||
|
233,199,Other concrete product manufacturing,"$20,872,805,363.99","$28,897.61",0.00%
|
||||||
|
234,178,Plastics packaging materials and unlaminated film and sheet manufacturing,"$53,048,955,141.25","$73,380.14",0.00%
|
||||||
|
235,299,Other electronic component manufacturing,"$20,043,941,097.34","$27,703.42",0.00%
|
||||||
|
236,169,Soap and other detergent manufacturing,"$39,553,819,482.76","$54,664.25",0.00%
|
||||||
|
237,44,"Water, sewage and other systems","$20,702,504,339.27","$28,591.89",0.00%
|
||||||
|
238,230,Metal window and door manufacturing,"$25,916,655,606.62","$35,669.36",0.00%
|
||||||
|
239,24,Gold ore and silver ore mining,"$14,012,282,637.55","$19,264.85",0.00%
|
||||||
|
240,474,"Residential mental health, substance abuse, and other residential care facilities","$86,746,369,311.60","$119,117.43",0.00%
|
||||||
|
241,65,Fats and oils refining and blending,"$27,186,577,576.39","$37,218.15",0.00%
|
||||||
|
242,183,Urethane and other foam product (except polystyrene) manufacturing,"$17,544,212,322.74","$23,996.28",0.00%
|
||||||
|
243,91,Tortilla manufacturing,"$6,637,815,191.50","$9,051.03",0.00%
|
||||||
|
244,100,Manufactured ice,"$1,531,542,683.93","$2,085.64",0.00%
|
||||||
|
245,209,Rolled steel shape manufacturing,"$27,311,554,207.40","$37,138.97",0.00%
|
||||||
|
246,182,Polystyrene foam product manufacturing,"$16,005,881,056.72","$21,757.18",0.00%
|
||||||
|
247,63,Wet corn milling,"$38,891,507,770.56","$52,849.51",0.00%
|
||||||
|
248,88,"Bread and bakery product, except frozen, manufacturing","$76,846,616,917.25","$104,135.27",0.00%
|
||||||
|
249,73,Frozen specialties manufacturing,"$29,906,861,739.21","$40,417.84",0.00%
|
||||||
|
250,69,Nonchocolate confectionery manufacturing,"$13,591,063,458.98","$18,357.64",0.00%
|
||||||
|
251,92,Roasted nuts and peanut butter manufacturing,"$14,211,552,199.88","$19,166.53",0.00%
|
||||||
|
252,67,Beet sugar manufacturing,"$4,964,816,518.93","$6,690.39",0.00%
|
||||||
|
253,449,Veterinary services,"$71,596,357,121.77","$96,057.55",0.00%
|
||||||
|
254,89,Cookie and cracker manufacturing,"$13,331,238,711.94","$17,867.71",0.00%
|
||||||
|
255,127,Engineered wood member and truss manufacturing,"$19,072,551,648.83","$25,553.61",0.00%
|
||||||
|
256,381,Wholesale - Grocery and related product wholesalers,"$266,898,748,905.69","$357,407.37",0.00%
|
||||||
|
257,208,"Iron, steel pipe and tube manufacturing from purchased steel","$23,851,806,079.11","$31,893.61",0.00%
|
||||||
|
258,376,Wholesale - Professional and commercial equipment and supplies,"$280,786,511,629.23","$374,143.75",0.00%
|
||||||
|
259,60,Flour milling,"$24,410,235,377.89","$32,465.54",0.00%
|
||||||
|
260,181,"Laminated plastics plate, sheet (except packaging), and shape manufacturing","$9,049,012,337.00","$12,006.70",0.00%
|
||||||
|
261,366,"Doll, toy, and game manufacturing","$6,942,729,114.53","$9,210.62",0.00%
|
||||||
|
262,3,Vegetable and melon farming,"$30,885,272,746.48","$40,959.44",0.00%
|
||||||
|
263,66,Breakfast cereal manufacturing,"$14,660,866,927.54","$19,389.45",0.00%
|
||||||
|
264,62,Malt manufacturing,"$1,609,185,168.11","$2,125.38",0.00%
|
||||||
|
265,9,Sugarcane and sugar beet farming,"$5,250,524,022.38","$6,934.36",0.00%
|
||||||
|
266,363,Dental laboratories,"$6,071,164,155.13","$8,018.09",0.00%
|
||||||
|
267,71,Confectionery manufacturing from purchased chocolate,"$13,448,763,298.64","$17,739.08",0.00%
|
||||||
|
268,439,"Architectural, engineering, and related services","$491,156,469,463.54","$645,684.17",0.00%
|
||||||
|
269,135,All other miscellaneous wood product manufacturing,"$9,849,717,250.58","$12,939.51",0.00%
|
||||||
|
270,126,Veneer and plywood manufacturing,"$13,492,156,738.87","$17,649.76",0.00%
|
||||||
|
271,90,"Dry pasta, mixes, and dough manufacturing","$16,866,934,868.06","$22,044.02",0.00%
|
||||||
|
272,83,Poultry processing,"$105,186,301,944.41","$137,459.83",0.00%
|
||||||
|
273,409,Greeting card publishing,"$620,260,994.43",$807.54,0.00%
|
||||||
|
274,82,Frozen cakes and other pastries manufacturing,"$6,457,274,620.81","$8,370.12",0.00%
|
||||||
|
275,64,Soybean and other oilseed processing,"$76,308,728,857.11","$98,865.71",0.00%
|
||||||
|
276,113,Curtain and linen mills,"$2,979,017,369.60","$3,859.29",0.00%
|
||||||
|
277,68,Sugar cane mills and refining,"$9,295,080,877.39","$12,038.24",0.00%
|
||||||
|
278,59,Other animal food manufacturing,"$65,579,824,303.67","$84,498.99",0.00%
|
||||||
|
279,128,Reconstituted wood product manufacturing,"$15,988,077,558.32","$20,569.49",0.00%
|
||||||
|
280,77,Cheese manufacturing,"$78,758,678,813.71","$100,565.43",0.00%
|
||||||
|
281,434,Video tape and disc rental,"$2,056,888,651.68","$2,619.80",0.00%
|
||||||
|
282,98,All other food manufacturing,"$57,495,650,042.31","$73,170.71",0.00%
|
||||||
|
283,97,Spice and extract manufacturing,"$19,373,537,300.45","$24,525.56",0.00%
|
||||||
|
284,328,Motor home manufacturing,"$8,213,805,405.62","$10,374.04",0.00%
|
||||||
|
285,70,Chocolate and confectionery manufacturing from cacao beans,"$7,248,602,195.05","$9,121.73",0.00%
|
||||||
|
286,322,Carbon and graphite product manufacturing,"$5,113,390,786.13","$6,431.16",0.00%
|
||||||
|
287,13,Poultry and egg production,"$78,014,200,034.51","$98,083.66",0.00%
|
||||||
|
288,72,"Frozen fruits, juices and vegetables manufacturing","$23,457,346,283.12","$29,468.39",0.00%
|
||||||
|
289,23,Iron ore mining,"$4,242,665,589.12","$5,323.72",0.00%
|
||||||
|
290,18,Commercial hunting and trapping,"$1,457,086,312.35","$1,826.39",0.00%
|
||||||
|
291,167,Paint and coating manufacturing,"$40,256,103,819.80","$50,369.65",0.00%
|
||||||
|
292,500,Death care services,"$21,907,750,073.48","$27,335.86",0.00%
|
||||||
|
293,12,Dairy cattle and milk production,"$55,960,191,839.82","$69,366.96",0.00%
|
||||||
|
294,154,Other basic inorganic chemical manufacturing,"$52,039,440,410.92","$64,477.25",0.00%
|
||||||
|
295,388,Retail - Building material and garden equipment and supplies stores,"$229,383,929,798.11","$283,314.66",0.00%
|
||||||
|
296,164,Pharmaceutical preparation manufacturing,"$251,681,058,014.10","$310,424.20",0.00%
|
||||||
|
297,172,Toilet preparation manufacturing,"$45,913,297,452.17","$56,539.15",0.00%
|
||||||
|
298,87,Seafood product preparation and packaging,"$18,709,695,060.42","$23,030.61",0.00%
|
||||||
|
299,296,Semiconductor and related device manufacturing,"$204,728,787,914.56","$251,567.42",0.00%
|
||||||
|
300,143,All other converted paper product manufacturing,"$7,484,025,289.68","$9,180.60",0.00%
|
||||||
|
301,407,Book publishers,"$38,981,960,284.47","$47,786.91",0.00%
|
||||||
|
302,96,"Mayonnaise, dressing, and sauce manufacturing","$15,142,016,019.64","$18,420.64",0.00%
|
||||||
|
303,176,Photographic film and chemical manufacturing,"$5,205,177,593.02","$6,319.82",0.00%
|
||||||
|
304,117,Apparel knitting mills,"$1,078,135,943.04","$1,306.92",0.00%
|
||||||
|
305,4,Fruit farming,"$27,048,229,916.23","$32,785.38",0.00%
|
||||||
|
306,119,Cut and sew apparel manufacturing (except contractors),"$13,153,729,012.81","$15,920.24",0.00%
|
||||||
|
307,118,Cut and sew apparel contractors,"$2,653,123,700.63","$3,210.86",0.00%
|
||||||
|
308,201,Gypsum product manufacturing,"$10,849,873,573.69","$13,058.45",0.00%
|
||||||
|
309,345,"Motorcycle, bicycle, and parts manufacturing","$4,548,983,090.03","$5,474.46",0.00%
|
||||||
|
310,79,Fluid milk manufacturing,"$58,670,165,867.62","$70,564.30",0.00%
|
||||||
|
311,236,"Metal barrels, drums and pails manufacturing","$7,563,776,109.68","$9,073.00",0.00%
|
||||||
|
312,14,"Animal production, except cattle and poultry and eggs","$40,095,044,622.69","$47,835.80",0.00%
|
||||||
|
313,110,Textile and fabric finishing mills,"$5,488,614,083.97","$6,545.23",0.00%
|
||||||
|
314,75,Canned specialties,"$12,228,701,977.18","$14,521.40",0.00%
|
||||||
|
315,473,Nursing and community care facilities,"$259,557,368,469.24","$307,063.79",0.00%
|
||||||
|
316,295,Bare printed circuit board manufacturing,"$7,296,219,609.55","$8,594.31",0.00%
|
||||||
|
317,235,Metal cans manufacturing,"$27,208,678,262.97","$31,900.63",0.00%
|
||||||
|
318,362,Ophthalmic goods manufacturing,"$7,651,490,019.34","$8,944.39",0.00%
|
||||||
|
319,442,Computer systems design services,"$372,342,526,925.07","$435,101.07",0.00%
|
||||||
|
320,453,Facilities support services,"$38,362,646,138.12","$44,820.24",0.00%
|
||||||
|
321,80,Creamery butter manufacturing,"$9,920,387,946.25","$11,574.30",0.00%
|
||||||
|
322,344,Boat building,"$16,575,494,394.55","$19,321.80",0.00%
|
||||||
|
323,115,"Rope, cordage, twine, tire cord and tire fabric mills","$1,758,938,925.32","$2,041.43",0.00%
|
||||||
|
324,122,Footwear manufacturing,"$3,007,443,476.76","$3,489.27",0.00%
|
||||||
|
325,220,Nonferrous metal foundries,"$14,956,699,164.90","$17,302.53",0.00%
|
||||||
|
326,74,Canned fruits and vegetables manufacturing,"$38,281,772,882.52","$44,220.60",0.00%
|
||||||
|
327,156,Plastics material and resin manufacturing,"$104,074,281,069.32","$120,214.44",0.00%
|
||||||
|
328,106,Broadwoven fabric mills,"$6,004,476,568.14","$6,925.64",0.00%
|
||||||
|
329,180,Plastics pipe and pipe fitting manufacturing,"$29,083,208,536.05","$33,513.60",0.00%
|
||||||
|
330,108,Nonwoven fabric mills,"$8,073,560,162.60","$9,278.85",0.00%
|
||||||
|
331,309,Manufacturing and reproducing magnetic and optical media,"$8,461,179,994.98","$9,668.25",0.00%
|
||||||
|
332,311,Lighting fixture manufacturing,"$13,551,146,025.36","$15,409.31",0.00%
|
||||||
|
333,120,Apparel accessories and other apparel manufacturing,"$2,593,466,765.65","$2,945.60",0.00%
|
||||||
|
334,76,Dehydrated food products manufacturing,"$7,575,959,466.85","$8,582.62",0.00%
|
||||||
|
335,85,Meat processed from carcasses,"$97,119,832,558.67","$109,823.50",0.00%
|
||||||
|
336,114,Textile bag and canvas mills,"$5,249,055,341.28","$5,934.74",0.00%
|
||||||
|
337,104,Tobacco manufacturing,"$54,449,721,766.50","$61,177.11",0.00%
|
||||||
|
338,78,"Dry, condensed, and evaporated dairy product manufacturing","$30,705,393,456.62","$34,403.28",0.00%
|
||||||
|
339,349,Upholstered household furniture manufacturing,"$10,755,818,252.72","$12,022.60",0.00%
|
||||||
|
340,84,"Animal, except poultry, slaughtering","$125,536,916,562.66","$139,981.67",0.00%
|
||||||
|
341,430,Tenant-occupied housing,"$685,796,968,030.48","$761,852.65",0.00%
|
||||||
|
342,350,Nonupholstered wood household furniture manufacturing,"$5,951,142,259.96","$6,606.67",0.00%
|
||||||
|
343,190,"Brick, tile, and other structural clay product manufacturing","$7,307,957,121.61","$8,103.76",0.00%
|
||||||
|
344,168,Adhesive manufacturing,"$19,417,045,098.31","$21,449.60",0.00%
|
||||||
|
345,11,"Beef cattle ranching and farming, including feedlots and dual-purpose ranching and farming","$123,976,424,596.90","$135,488.75",0.00%
|
||||||
|
346,177,Other miscellaneous chemical product manufacturing,"$36,982,132,613.79","$40,358.05",0.00%
|
||||||
|
347,357,Mattress manufacturing,"$9,419,270,908.18","$10,215.36",0.00%
|
||||||
|
348,105,"Fiber, yarn, and thread mills","$8,096,229,437.21","$8,733.97",0.00%
|
||||||
|
349,81,Ice cream and frozen dessert manufacturing,"$11,533,822,322.18","$12,430.35",0.00%
|
||||||
|
350,304,Totalizing fluid meter and counting device manufacturing,"$4,243,237,330.27","$4,558.29",0.00%
|
||||||
|
351,171,Surface active agent manufacturing,"$7,929,977,473.13","$8,493.68",0.00%
|
||||||
|
352,158,Artificial and synthetic fibers and filaments manufacturing,"$22,548,149,697.72","$24,031.27",0.00%
|
||||||
|
353,2,Grain farming,"$92,515,635,807.06","$98,507.53",0.00%
|
||||||
|
354,153,Synthetic dye and pigment manufacturing,"$8,690,491,587.81","$9,206.47",0.00%
|
||||||
|
355,329,Travel trailer and camper manufacturing,"$18,848,949,146.82","$19,955.17",0.00%
|
||||||
|
356,206,Miscellaneous nonmetallic mineral products manufacturing,"$6,427,167,874.28","$6,723.74",0.00%
|
||||||
|
357,94,Coffee and tea manufacturing,"$20,863,690,975.72","$21,701.22",0.00%
|
||||||
|
358,251,Other fabricated metal manufacturing,"$30,539,594,645.25","$31,482.61",0.00%
|
||||||
|
359,192,Other pressed and blown glass and glassware manufacturing,"$4,284,124,906.29","$4,407.38",0.00%
|
||||||
|
360,141,Stationery product manufacturing,"$6,277,104,685.19","$6,451.57",0.00%
|
||||||
|
361,61,Rice milling,"$4,898,466,736.87","$5,029.63",0.00%
|
||||||
|
362,86,Rendering and meat byproduct processing,"$7,413,705,803.33","$7,599.52",0.00%
|
||||||
|
363,330,Motor vehicle gasoline engine and engine parts manufacturing,"$44,564,962,980.67","$45,348.04",0.00%
|
||||||
|
364,228,Fabricated structural metal manufacturing,"$55,887,434,915.07","$56,132.53",0.00%
|
||||||
|
365,148,Asphalt shingle and coating materials manufacturing,"$24,983,112,968.20","$25,091.77",0.00%
|
||||||
|
366,216,"Copper rolling, drawing, extruding and alloying","$50,585,076,868.02","$50,545.15",0.00%
|
||||||
|
367,271,"Speed changer, industrial high-speed drive, and gear manufacturing","$4,671,209,393.65","$4,659.25",0.00%
|
||||||
|
368,351,Other household nonupholstered furniture manufacturing,"$3,278,633,911.76","$3,252.83",0.00%
|
||||||
|
369,312,Small electrical appliance manufacturing,"$7,081,471,688.66","$6,924.51",0.00%
|
||||||
|
370,19,Support activities for agriculture and forestry,"$37,292,538,567.98","$36,372.08",0.00%
|
||||||
|
371,372,"Broom, brush, and mop manufacturing","$2,791,119,810.12","$2,711.85",0.00%
|
||||||
|
372,198,Concrete pipe manufacturing,"$4,124,714,176.94","$4,002.63",0.00%
|
||||||
|
373,310,Electric lamp bulb and part manufacturing,"$2,612,186,294.02","$2,516.99",0.00%
|
||||||
|
374,111,Fabric coating mills,"$2,941,340,275.34","$2,786.22",0.00%
|
||||||
|
375,17,Commercial fishing,"$6,396,190,709.37","$6,028.53",0.00%
|
||||||
|
376,202,Abrasive product manufacturing,"$3,629,975,574.14","$3,405.47",0.00%
|
||||||
|
377,162,Pesticide and other agricultural chemical manufacturing,"$26,894,147,904.77","$24,484.86",0.00%
|
||||||
|
378,321,Wiring device manufacturing,"$23,088,452,099.69","$21,017.23",0.00%
|
||||||
|
379,369,"Gasket, packing, and sealing device manufacturing","$8,323,503,033.09","$7,546.95",0.00%
|
||||||
|
380,123,Other leather and allied product manufacturing,"$2,323,613,504.79","$2,098.19",0.00%
|
||||||
|
381,134,Prefabricated wood building manufacturing,"$7,081,171,121.71","$6,393.65",0.00%
|
||||||
|
382,214,"Other aluminum rolling, drawing and extruding","$17,883,903,441.11","$15,823.91",0.00%
|
||||||
|
383,294,Printed circuit assembly (electronic assembly) manufacturing,"$31,077,795,337.85","$27,296.10",0.00%
|
||||||
|
384,318,Battery manufacturing,"$39,581,382,532.18","$34,398.89",0.00%
|
||||||
|
385,213,"Aluminum sheet, plate, and foil manufacturing","$24,947,023,169.66","$21,532.89",0.00%
|
||||||
|
386,211,Alumina refining and primary aluminum production,"$6,769,083,305.47","$5,785.74",0.00%
|
||||||
|
387,249,"Small arms, ordnance, and accessories manufacturing","$15,107,566,913.00","$12,860.61",0.00%
|
||||||
|
388,374,All other miscellaneous manufacturing,"$31,399,033,702.70","$26,413.44",0.00%
|
||||||
|
389,212,Secondary smelting and alloying of aluminum,"$11,536,963,587.40","$9,624.88",0.00%
|
||||||
|
390,1,Oilseed farming,"$49,937,187,262.22","$40,890.88",0.00%
|
||||||
|
391,373,Burial casket manufacturing,"$823,043,789.50",$669.59,0.00%
|
||||||
|
392,107,Narrow fabric mills and schiffli machine embroidery,"$1,181,925,722.59",$950.61,0.00%
|
||||||
|
393,231,Sheet metal work manufacturing,"$38,948,717,887.18","$31,224.40",0.00%
|
||||||
|
394,263,Heating equipment (except warm air furnaces) manufacturing,"$6,313,130,515.83","$5,027.96",0.00%
|
||||||
|
395,132,Wood container and pallet manufacturing,"$20,952,157,665.21","$16,606.93",0.00%
|
||||||
|
396,194,Glass product manufacturing made of purchased glass,"$16,040,893,814.59","$12,554.44",0.00%
|
||||||
|
397,121,Leather and hide tanning and finishing,"$1,222,349,401.99",$951.90,0.00%
|
||||||
|
398,358,Blind and shade manufacturing,"$2,260,551,655.48","$1,759.47",0.00%
|
||||||
|
399,217,"Nonferrous metal, except copper and aluminum, shaping","$9,516,398,153.16","$7,278.95",0.00%
|
||||||
|
400,147,Asphalt paving mixture and block manufacturing,"$25,703,408,936.01","$19,483.92",0.00%
|
||||||
|
401,365,Sporting and athletic goods manufacturing,"$17,219,236,027.07","$13,009.43",0.00%
|
||||||
|
402,441,Custom computer programming services,"$369,576,048,122.11","$276,033.86",0.00%
|
||||||
|
403,298,Electronic connector manufacturing,"$10,285,711,165.08","$7,646.99",0.00%
|
||||||
|
404,364,Jewelry and silverware manufacturing,"$12,676,072,409.19","$9,352.72",0.00%
|
||||||
|
405,371,"Fasteners, buttons, needles, and pins manufacturing","$1,412,332,260.87","$1,008.60",0.00%
|
||||||
|
406,278,"Overhead cranes, hoists, and monorail systems manufacturing","$9,259,737,689.05","$6,410.89",0.00%
|
||||||
|
407,368,Sign manufacturing,"$16,164,025,409.21","$10,946.53",0.00%
|
||||||
|
408,244,"Valve and fittings, other than plumbing, manufacturing","$38,110,929,812.59","$25,730.27",0.00%
|
||||||
|
409,246,Ball and roller bearing manufacturing,"$7,949,180,771.09","$5,313.35",0.00%
|
||||||
|
410,165,In-vitro diagnostic substance manufacturing,"$14,414,701,108.34","$9,626.60",0.00%
|
||||||
|
411,189,"Pottery, ceramics, and plumbing fixture manufacturing","$3,667,692,330.99","$2,398.01",0.00%
|
||||||
|
412,5,Tree nut farming,"$10,840,952,356.98","$6,921.06",0.00%
|
||||||
|
413,320,Other communication and energy wire manufacturing,"$10,283,051,205.79","$6,547.77",0.00%
|
||||||
|
414,32,Metal mining services,"$2,048,448,774.82","$1,299.86",0.00%
|
||||||
|
415,347,All other transportation equipment manufacturing,"$14,559,569,846.15","$8,760.96",0.00%
|
||||||
|
416,250,Fabricated pipe and pipe fitting manufacturing,"$11,419,911,011.72","$6,623.74",0.00%
|
||||||
|
417,203,Cut stone and stone product manufacturing,"$8,077,791,340.34","$4,674.14",0.00%
|
||||||
|
418,302,Automatic environmental control manufacturing,"$3,759,012,878.80","$2,145.22",0.00%
|
||||||
|
419,274,"Measuring, dispensing, and other pumping equipment manufacturing","$16,242,066,248.06","$8,817.93",0.00%
|
||||||
|
420,313,Major household appliance manufacturing,"$31,013,443,561.11","$16,803.69",0.00%
|
||||||
|
421,273,Other engine equipment manufacturing,"$48,785,187,978.27","$25,940.51",0.00%
|
||||||
|
422,284,Fluid power cylinder and actuator manufacturing,"$5,402,475,288.93","$2,850.21",0.00%
|
||||||
|
423,234,Metal tank (heavy gauge) manufacturing,"$15,112,467,726.79","$7,845.41",0.00%
|
||||||
|
424,290,Telephone apparatus manufacturing,"$6,806,873,039.89","$3,502.94",0.00%
|
||||||
|
425,285,Fluid power pump and motor manufacturing,"$10,430,473,077.95","$5,295.21",0.00%
|
||||||
|
426,191,Flat glass manufacturing,"$5,646,246,245.84","$2,858.35",0.00%
|
||||||
|
427,272,Mechanical power transmission equipment manufacturing,"$5,107,718,597.91","$2,554.99",0.00%
|
||||||
|
428,370,Musical instrument manufacturing,"$2,442,378,807.18","$1,208.17",0.00%
|
||||||
|
429,218,Secondary processing of other nonferrous metals,"$11,203,152,448.66","$5,474.83",0.00%
|
||||||
|
430,136,Pulp mills,"$4,388,558,617.42","$2,141.25",0.00%
|
||||||
|
431,293,Audio and video equipment manufacturing,"$14,718,603,696.31","$6,931.23",0.00%
|
||||||
|
432,264,"Air conditioning, refrigeration, and warm air heating equipment manufacturing","$52,915,803,594.38","$24,867.00",0.00%
|
||||||
|
433,112,Carpet and rug mills,"$11,693,395,459.88","$5,263.54",0.00%
|
||||||
|
434,289,Computer terminals and other computer peripheral equipment manufacturing,"$16,168,226,588.98","$7,207.64",0.00%
|
||||||
|
435,360,Surgical appliance and supplies manufacturing,"$44,043,153,561.24","$19,301.84",0.00%
|
||||||
|
436,291,Broadcast and wireless communications equipment manufacturing,"$30,369,093,371.79","$12,280.92",0.00%
|
||||||
|
437,205,Mineral wool manufacturing,"$10,606,371,397.91","$4,225.85",0.00%
|
||||||
|
438,8,Cotton farming,"$5,875,423,327.42","$2,233.99",0.00%
|
||||||
|
439,269,Rolling mill and other metalworking machinery manufacturing,"$3,803,720,769.48","$1,439.30",0.00%
|
||||||
|
440,446,Scientific research and development services,"$1,205,188,770,353.59","$454,040.61",0.00%
|
||||||
|
441,317,Relay and industrial control manufacturing,"$18,288,761,968.52","$5,959.72",0.00%
|
||||||
|
442,334,Motor vehicle metal stamping,"$37,315,706,996.08","$11,285.93",0.00%
|
||||||
|
443,283,Industrial process furnace and oven manufacturing,"$3,545,708,344.05","$1,038.27",0.00%
|
||||||
|
444,333,Motor vehicle seating and interior trim manufacturing,"$37,465,954,817.18","$10,536.73",0.00%
|
||||||
|
445,265,Industrial mold manufacturing,"$7,530,247,856.23","$2,056.87",0.00%
|
||||||
|
446,227,Prefabricated metal buildings and components manufacturing,"$19,908,799,071.06","$5,414.37",0.00%
|
||||||
|
447,215,Nonferrous metal (exc aluminum) smelting and refining,"$15,920,371,219.70","$4,246.30",0.00%
|
||||||
|
448,346,"Military armored vehicle, tank, and tank component manufacturing","$5,573,869,494.74","$1,478.07",0.00%
|
||||||
|
449,7,Tobacco farming,"$938,019,405.97",$244.97,0.00%
|
||||||
|
450,356,"Showcase, partition, shelving, and locker manufacturing","$13,004,665,878.80","$3,071.75",0.00%
|
||||||
|
451,303,Industrial process variable instruments manufacturing,"$20,772,591,501.51","$4,876.67",0.00%
|
||||||
|
452,359,Surgical and medical instrument manufacturing,"$59,020,395,966.82","$13,825.77",0.00%
|
||||||
|
453,315,Motor and generator manufacturing,"$20,631,390,946.06","$4,809.08",0.00%
|
||||||
|
454,279,"Industrial truck, trailer, and stacker manufacturing","$16,640,191,926.42","$3,825.07",0.00%
|
||||||
|
455,280,Power-driven handtool manufacturing,"$5,652,316,770.11","$1,292.77",0.00%
|
||||||
|
456,288,Computer storage device manufacturing,"$9,130,764,626.37","$2,030.59",0.00%
|
||||||
|
457,31,Support activities for oil and gas operations,"$91,409,573,478.95","$18,856.20",0.00%
|
||||||
|
458,324,Automobile and light duty motor vehicle manufacturing,"$520,106,032,160.17","$106,229.18",0.00%
|
||||||
|
459,266,"Special tool, die, jig, and fixture manufacturing","$12,017,623,780.51","$2,453.42",0.00%
|
||||||
|
460,308,"Watch, clock, and other measuring and controlling device manufacturing","$25,112,606,872.12","$5,112.06",0.00%
|
||||||
|
461,342,Railroad rolling stock manufacturing,"$10,648,227,165.95","$2,078.26",0.00%
|
||||||
|
462,33,Other nonmetallic minerals services,"$3,066,411,048.87",$586.86,0.00%
|
||||||
|
463,316,Switchgear and switchboard apparatus manufacturing,"$22,869,509,385.71","$4,333.64",0.00%
|
||||||
|
464,262,Industrial and commercial fan and blower and air purification equipment manufacturing,"$11,072,077,301.97","$2,093.20",0.00%
|
||||||
|
465,287,Electronic computer manufacturing,"$59,399,365,371.42","$11,175.12",0.00%
|
||||||
|
466,361,Dental equipment and supplies manufacturing,"$5,664,537,597.07",$873.53,0.00%
|
||||||
|
467,253,Lawn and garden equipment manufacturing,"$9,758,111,228.22","$1,406.44",0.00%
|
||||||
|
468,166,Biological product (except diagnostic) manufacturing,"$32,405,003,914.07","$4,272.35",0.00%
|
||||||
|
469,281,Welding and soldering equipment manufacturing,"$7,381,471,085.53",$958.52,0.00%
|
||||||
|
470,248,"Ammunition, except for small arms, manufacturing","$5,521,477,009.35",$701.75,0.00%
|
||||||
|
471,286,"Scales, balances, and miscellaneous general purpose machinery manufacturing","$16,848,740,450.85","$2,055.51",0.00%
|
||||||
|
472,343,Ship building and repairing,"$36,749,502,389.40","$4,367.84",0.00%
|
||||||
|
473,261,Commercial and service industry machinery manufacturing,"$32,349,789,662.32","$3,512.58",0.00%
|
||||||
|
474,276,Elevator and moving stairway manufacturing,"$6,247,017,144.60",$667.16,0.00%
|
||||||
|
475,282,Packaging machinery manufacturing,"$10,093,518,599.74","$1,053.01",0.00%
|
||||||
|
476,323,All other miscellaneous electrical equipment and component manufacturing,"$19,762,635,716.97","$2,053.98",0.00%
|
||||||
|
477,57,"Maintenance and repair construction of highways, streets, bridges, and tunnels","$46,691,636,777.08","$4,113.80",0.00%
|
||||||
|
478,260,All other industrial machinery manufacturing,"$26,064,489,613.33","$2,155.00",0.00%
|
||||||
|
479,300,Electromedical and electrotherapeutic apparatus manufacturing,"$36,751,960,582.09","$3,000.10",0.00%
|
||||||
|
480,233,Power boiler and heat exchanger manufacturing,"$9,489,887,943.40",$752.02,0.00%
|
||||||
|
481,268,Machine tool manufacturing,"$14,689,449,094.47","$1,116.26",0.00%
|
||||||
|
482,257,Semiconductor machinery manufacturing,"$20,914,542,877.68","$1,585.33",0.00%
|
||||||
|
483,306,Analytical laboratory instrument manufacturing,"$20,585,041,242.85","$1,364.81",0.00%
|
||||||
|
484,326,Motor vehicle body manufacturing,"$27,031,285,117.11","$1,770.49",0.00%
|
||||||
|
485,258,Food product machinery manufacturing,"$8,325,550,800.97",$512.30,0.00%
|
||||||
|
486,270,Turbine and turbine generator set units manufacturing,"$11,150,738,907.66",$650.14,0.00%
|
||||||
|
487,339,Other aircraft parts and auxiliary equipment manufacturing,"$37,075,802,192.26","$1,959.56",0.00%
|
||||||
|
488,259,"Sawmill, woodworking, and paper machinery","$4,374,785,678.28",$225.04,0.00%
|
||||||
|
489,305,Electricity and signal testing instruments manufacturing,"$18,139,369,071.43",$903.24,0.00%
|
||||||
|
490,252,Farm machinery and equipment manufacturing,"$52,179,714,218.33","$2,400.53",0.00%
|
||||||
|
491,354,Custom architectural woodwork and millwork,"$6,542,805,074.05",$295.88,0.00%
|
||||||
|
492,341,Propulsion units and parts for space vehicles and guided missiles manufacturing,"$11,739,712,802.20",$429.49,0.00%
|
||||||
|
493,352,Institutional furniture manufacturing,"$6,520,456,951.78",$192.09,0.00%
|
||||||
|
494,314,"Power, distribution, and specialty transformer manufacturing","$14,573,198,398.89",$352.83,0.00%
|
||||||
|
495,275,Air and gas compressor manufacturing,"$11,295,952,281.20",$244.22,0.00%
|
||||||
|
496,338,Aircraft engine and engine parts manufacturing,"$66,913,582,637.98","$1,363.06",0.00%
|
||||||
|
497,301,"Search, detection, and navigation instruments manufacturing","$67,509,855,149.42","$1,041.16",0.00%
|
||||||
|
498,355,"Office furniture, except wood, manufacturing","$8,957,646,094.95",$131.16,0.00%
|
||||||
|
499,307,Irradiation apparatus manufacturing,"$11,336,061,543.92",$151.80,0.00%
|
||||||
|
500,133,Manufactured home (mobile home) manufacturing,"$12,105,996,109.20",$151.33,0.00%
|
||||||
|
501,327,Truck trailer manufacturing,"$18,669,883,339.14",$210.22,0.00%
|
||||||
|
502,353,Wood office furniture manufacturing,"$4,581,758,413.14",$49.97,0.00%
|
||||||
|
503,337,Aircraft manufacturing,"$153,008,468,478.69","$1,434.57",0.00%
|
||||||
|
504,325,Heavy duty truck manufacturing,"$40,717,164,048.65",$369.07,0.00%
|
||||||
|
505,30,Drilling oil and gas wells,"$11,827,333,275.53",$53.72,0.00%
|
||||||
|
506,340,Guided missile and space vehicle manufacturing,"$51,616,538,537.19",$100.38,0.00%
|
||||||
|
507,518,* Not an industry (Scrap),$0.00,$0.00,0.00%
|
||||||
|
508,50,"Construction of new commercial structures, including farm structures","$275,811,043,324.58",$0.00,0.00%
|
||||||
|
509,45,Construction of new health care structures,"$75,998,269,520.47",$0.00,0.00%
|
||||||
|
510,525,"* Employment and payroll of local govt, hospitals and health services","$101,165,041,589.85",$0.00,0.00%
|
||||||
|
511,527,"* Employment and payroll of federal govt, military","$406,908,485,446.64",$0.00,0.00%
|
||||||
|
512,528,"* Employment and payroll of federal govt, non-military","$533,466,577,701.41",$0.00,0.00%
|
||||||
|
513,519,* Not an industry (Rest of world adjustment),$0.00,$0.00,0.00%
|
||||||
|
514,47,Construction of new power and communication structures,"$170,018,484,831.53",$0.00,0.00%
|
||||||
|
515,52,Construction of new single-family residential structures,"$432,030,318,830.85",$0.00,0.00%
|
||||||
|
516,517,* Not an industry (Used and secondhand goods),$0.00,$0.00,0.00%
|
||||||
|
517,46,Construction of new manufacturing structures,"$200,634,656,467.69",$0.00,0.00%
|
||||||
|
518,49,Construction of new highways and streets,"$209,000,810,877.06",$0.00,0.00%
|
||||||
|
519,522,"* Employment and payroll of state govt, hospitals and health services","$78,395,980,781.69",$0.00,0.00%
|
||||||
|
520,520,* Not an industry (Noncomparable foreign imports),$0.00,$0.00,0.00%
|
||||||
|
521,524,"* Employment and payroll of local govt, education","$742,013,924,260.96",$0.00,0.00%
|
||||||
|
522,53,Construction of new multifamily residential structures,"$153,968,102,198.51",$0.00,0.00%
|
||||||
|
523,51,Construction of other new nonresidential structures,"$160,786,345,780.64",$0.00,0.00%
|
||||||
|
524,523,"* Employment and payroll of state govt, other services","$245,854,325,914.06",$0.00,0.00%
|
||||||
|
525,521,"* Employment and payroll of state govt, education","$246,752,494,971.48",$0.00,0.00%
|
||||||
|
526,54,Construction of other new residential structures,"$408,260,208,291.85",$0.00,0.00%
|
||||||
|
527,48,Construction of new educational and vocational structures,"$145,790,898,060.18",$0.00,0.00%
|
||||||
|
528,526,"* Employment and payroll of local govt, other services","$521,978,892,625.75",$0.00,0.00%
|
||||||
|
5
Model_Outputs/IMPLAN/US/US_2036/tax_results.csv
Normal file
5
Model_Outputs/IMPLAN/US/US_2036/tax_results.csv
Normal file
@ -0,0 +1,5 @@
|
|||||||
|
Impact,Sub County General,Sub County Special Districts,County,State,Federal,Total
|
||||||
|
1 - Direct,"$655,087.03","$655,119.49","$435,429.29","$2,051,999.49","$4,469,917.02","$8,267,552.31"
|
||||||
|
2 - Indirect,"$359,296.84","$354,085.12","$236,961.56","$1,192,941.11","$3,536,972.14","$5,680,256.77"
|
||||||
|
3 - Induced,"$419,568.31","$418,600.10","$279,139.59","$1,330,403.15","$3,424,496.28","$5,872,207.43"
|
||||||
|
,"$1,433,952.18","$1,427,804.71","$951,530.44","$4,575,343.75","$11,431,385.43","$19,820,016.51"
|
||||||
|
@ -0,0 +1,16 @@
|
|||||||
|
,Display Code,Display Description,Industry Total Output,Impact Output
|
||||||
|
1,21,Coal mining,"$40,369,797,410.22","$49,171,541.61"
|
||||||
|
2,174,Explosives manufacturing,"$3,336,015,892.42","$557,148.17"
|
||||||
|
3,418,"Data processing, hosting, and related services","$490,713,862,620.46","$22,825,655.45"
|
||||||
|
4,204,Ground or treated mineral and earth manufacturing,"$5,072,828,802.03","$200,722.47"
|
||||||
|
5,187,Rubber and plastics hoses and belting manufacturing,"$9,316,374,290.80","$175,521.73"
|
||||||
|
6,159,Nitrogenous fertilizer manufacturing,"$22,680,233,557.39","$382,011.96"
|
||||||
|
7,161,Fertilizer mixing,"$6,609,942,413.23","$74,335.18"
|
||||||
|
8,160,Phosphatic fertilizer manufacturing,"$9,646,258,713.74","$107,959.31"
|
||||||
|
9,26,Stone mining and quarrying,"$22,604,707,721.04","$250,641.45"
|
||||||
|
10,397,Rail transportation,"$92,013,918,170.42","$1,000,823.92"
|
||||||
|
11,297,"Capacitor, resistor, coil, transformer, and other inductor manufacturing","$4,022,032,100.41","$34,786.94"
|
||||||
|
12,435,Commercial and industrial machinery and equipment rental and leasing,"$163,914,676,099.25","$1,231,253.21"
|
||||||
|
13,256,Oil and gas field machinery and equipment manufacturing,"$27,836,734,479.74","$204,316.89"
|
||||||
|
14,240,"Turned product and screw, nut, and bolt manufacturing","$26,510,037,196.43","$188,323.71"
|
||||||
|
15,378,"Wholesale - Machinery, equipment, and supplies","$272,916,323,584.73","$1,763,234.74"
|
||||||
|
224
REMI_Visuals.r
Normal file
224
REMI_Visuals.r
Normal file
@ -0,0 +1,224 @@
|
|||||||
|
library(tidyverse)
|
||||||
|
library(janitor)
|
||||||
|
#install.packages("paletteer")
|
||||||
|
|
||||||
|
library(scales)
|
||||||
|
library(paletteer)
|
||||||
|
DATA_DIR <- 'Exports/'
|
||||||
|
OUTPUT_DIR <- './Results/Tables_and_Figures/'
|
||||||
|
dir.create(OUTPUT_DIR,recursive=TRUE,showWarnings=FALSE)
|
||||||
|
######################Employments
|
||||||
|
EMPLOY <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Employment.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
||||||
|
|
||||||
|
EMPLOY_NUM <- EMPLOY %>% filter(Units!="Proportion") %>% select(-Units,Employment=value) %>% filter(Year>=2027) %>% mutate(Employment=Employment*1000)
|
||||||
|
|
||||||
|
|
||||||
|
EMPLOY_NUM$Category <- gsub(" Employment","",EMPLOY_NUM$Category)
|
||||||
|
EMPLOY_NUM$Category <- factor(EMPLOY_NUM$Category,levels=rev(c("Direct","Indirect","Induced","Total")))
|
||||||
|
#EMPLOY_NUM %>% filter(Employment=='Direct')
|
||||||
|
#EMPLOY_NUM
|
||||||
|
#EMPLOY_NUM %>% filter(Category=='Total',Employment!=0)%>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Employment=mean(Employment))
|
||||||
|
#EMPLOY_NUM %>% filter(Category=='Total')%>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Employment=mean(Employment))
|
||||||
|
#EMPLOY_NUM %>% filter(Category=='Total') %>% print(n=100)
|
||||||
|
|
||||||
|
|
||||||
|
COLORS <- rev(paletteer_d("fishualize::Alosa_fallax",n=4,direction=1)[-2])
|
||||||
|
MAX_VAL <- round(max(EMPLOY_NUM$Employment))
|
||||||
|
#MAX_VAL
|
||||||
|
COOL_DOWN <- as.numeric(EMPLOY_NUM[5,3])
|
||||||
|
#EMPLOY_NUM
|
||||||
|
EMPLOY_GRAPH_DATA <- EMPLOY_NUM %>% filter(Category=='Total') %>% mutate(Category=ifelse(Employment<0,"Negative","Positive"))
|
||||||
|
TEMP <- EMPLOY_NUM %>% filter(Category=='Total') %>% filter(Employment<0) %>% mutate(Employment=0,Category="Positive")
|
||||||
|
EMPLOY_GRAPH_DATA <- rbind(EMPLOY_GRAPH_DATA ,TEMP)
|
||||||
|
TEMP2 <- EMPLOY_GRAPH_DATA[max(which(EMPLOY_GRAPH_DATA$Employment<0)),] %>% mutate(Year=Year+1,Employment=0)
|
||||||
|
EMPLOY_GRAPH_DATA <- rbind(EMPLOY_GRAPH_DATA ,TEMP2)
|
||||||
|
rm(TEMP,TEMP2)
|
||||||
|
|
||||||
|
JOB_PLOT <-ggplot(EMPLOY_GRAPH_DATA ,aes(x=Year,y=Employment))+geom_area(position = "stack",aes(fill=Category,group=Category))+theme_bw()+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(-250,10000,by=500)) +scale_fill_manual(values=c("red","blue3"))+theme(legend.position = "none")
|
||||||
|
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"Job_plot.png" ) , units = "in", width = 11, height = 8, res = 600)
|
||||||
|
JOB_PLOT
|
||||||
|
dev.off()
|
||||||
|
#JOB_PLOT
|
||||||
|
###################Output graph
|
||||||
|
OUTPUT <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Output.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
||||||
|
OUTPUT_NUM <- OUTPUT %>% select(-Units,Output=value) %>% filter(Year>=2028) %>% mutate(Output=Output*1000)
|
||||||
|
OUTPUT_NUM
|
||||||
|
|
||||||
|
OUTPUT_NUM$Category <- gsub(" Output","",OUTPUT_NUM$Category)
|
||||||
|
OUTPUT_NUM$Category <- factor(OUTPUT_NUM$Category,levels=rev(c("Direct","Indirect","Induced","Total")))
|
||||||
|
OUTPUT_PLOT <- ggplot(OUTPUT_NUM %>% filter(Category!="Total"),aes(x=Year,y=Output))+geom_area(position = "stack",aes(fill=Category,group=Category))+theme_bw()+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_fill_manual(values=COLORS)+geom_line(data=OUTPUT_NUM%>% filter(Category=="Total"),linewidth=1)+theme(text = element_text(size = 20),legend.position = "top")+scale_y_continuous(labels = scales::comma,breaks=seq(0,10000,by=250))+ylab("Economic Output (Million USD)")
|
||||||
|
OUTPUT_PLOT
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"Output_plot.png"), units = "in", width = 10, height = 8, res = 600)
|
||||||
|
OUTPUT_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
####GDP and Output
|
||||||
|
GDP <- read_csv(paste0(DATA_DIR,"Gross Domestic Product - By Region - GDP by Region.csv" ),skip=5) %>% pivot_longer(c(-Region,-Units),names_to="Year",values_to="GDP") %>% mutate(Year=parse_number(Year),GDP=GDP*1000) %>% select(-Units)
|
||||||
|
GDP <- GDP %>% filter(Region !='All Regions')
|
||||||
|
GDP$Region <- gsub(" County","",GDP$Region)
|
||||||
|
KEY_REGIONS <- GDP %>% group_by(Region) %>% summarize(GDP = median(GDP)) %>% arrange(desc(GDP)) %>% filter(GDP>0.5) %>% pull(Region)
|
||||||
|
KEY_REGIONS
|
||||||
|
OTHER_GDP <- GDP %>% filter(!(Region %in% KEY_REGIONS)) %>% group_by(Year) %>% summarize(Region="Other Counties",GDP=sum(GDP)) %>% ungroup
|
||||||
|
GDP <- rbind(GDP %>% filter(Region %in% KEY_REGIONS),OTHER_GDP)
|
||||||
|
GDP$Region <- factor(GDP$Region,levels=rev(c("Other Counties",KEY_REGIONS)))
|
||||||
|
GDP <- GDP %>% filter(Year>=2027)
|
||||||
|
sum(GDP$GDP)
|
||||||
|
OUTPUT_NUM %>% pull(Output) %>% sum
|
||||||
|
GDP <- GDP %>% group_by(Year) %>% summarize(GDP=sum(GDP)) %>% filter(Year>2027) %>% arrange(Year) %>% pull(GDP)
|
||||||
|
sum(GDP)
|
||||||
|
length(GDP)
|
||||||
|
sum(GDP*(1.09)^-(0:32))
|
||||||
|
|
||||||
|
GDP_SUB_REGION_PLOT <- ggplot(GDP %>% filter(Region!='Lincoln'),aes(x=Year,y=GDP,fill=Region))+geom_area(position='stack')+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=100))+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+ylab("GDP (Million USD)")+scale_fill_manual(values=paletteer_d("PNWColors::Shuksan2"))
|
||||||
|
GDP_SUB_REGION_PLOT
|
||||||
|
png(paste0(OUTPUT_DIR,"GDP_Other_Counties.png"), units = "in", width = 10, height = 8, res = 600)
|
||||||
|
GDP_SUB_REGION_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
|
||||||
|
GDP_REGION_SUMMARY <- GDP %>% mutate(Region=factor(ifelse(Region=='Lincoln','Lincoln','Rest of Wyoming'),levels=rev(c('Lincoln','Rest of Wyoming')))) %>% group_by(Region,Year) %>% summarize(GDP=sum(GDP)) %>% ungroup
|
||||||
|
GDP_PLOT <- ggplot(GDP_REGION_SUMMARY ,aes(x=Year,y=GDP,fill=Region))+geom_area(position='stack')+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=25))+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+ylab("GDP (Million USD)")+scale_fill_manual(values=c(paletteer_d("PNWColors::Shuksan2")[c(5)],paletteer::paletteer_d("calecopal::lupinus")[2]))
|
||||||
|
#paletteer::paletteer_d("calecopal::lupinus")[3]
|
||||||
|
png(paste0(OUTPUT_DIR,"GDP_Region_Plot.png"), units = "in", width = 10, height = 8, res = 600)
|
||||||
|
GDP_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
###################
|
||||||
|
INDUSTRY_JOBS <- read_csv(paste0(DATA_DIR,'Employment- By Industry - Employment by Industry.csv'),skip=5) %>% pivot_longer(c(-Industry,-Units),names_to="Year",values_to="Jobs") %>%mutate(Year=parse_number(Year)) %>% filter(Industry!='All Industries') %>% select(-Units) %>% filter(Year>=2029)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Data processing, hosting, and related services; Other information services',"Data processing",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Professional, scientific, and technical services',"Technical services",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Administrative and support services',"Administrative services",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='State and Local Government',"Government",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Food services and drinking places',"Restaurants",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Other transportation equipment manufacturing',"Equipment manufacturing",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Repair and maintenance',"Maintenance",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Utilities',"Energy Production",INDUSTRY_JOBS$Industry)
|
||||||
|
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Ambulatory health care services',"Hospitals",INDUSTRY_JOBS$Industry)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
INDUSTRY_JOBS <- INDUSTRY_JOBS %>% group_by(Year) %>% mutate(Rank=rank(-Jobs)) %>% mutate(Rank=ifelse(Rank>10,11,Rank),Industry=ifelse(Rank==11,"Other",Industry)) %>% group_by(Year,Industry,Rank) %>% summarize(Jobs=sum(Jobs)) %>% ungroup(Industry,Rank) %>% arrange(Year,Rank) %>% ungroup
|
||||||
|
#INDUSTRY_JOBS %>% pull(Industry) %>% unique
|
||||||
|
|
||||||
|
ORDER <- c(INDUSTRY_JOBS %>% filter(Industry!='Other') %>% group_by(Industry) %>% summarize(MEAN=mean(Jobs)) %>% arrange(desc(MEAN)) %>% pull(Industry) %>% unique,"Other")
|
||||||
|
INDUSTRY_JOBS$Industry <- factor(INDUSTRY_JOBS$Industry,levels=ORDER)
|
||||||
|
#INDUSTRY_JOBS
|
||||||
|
|
||||||
|
JOB_TYPE_PLOT <- ggplot(INDUSTRY_JOBS ,aes(x=Year,y=Jobs,fill=Industry))+geom_bar(stat='identity')+ paletteer::scale_fill_paletteer_d("colorBlindness::Blue2DarkRed18Steps",name="")+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+guides(fill=guide_legend(nrow=4,byrow=TRUE)) +scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=500))
|
||||||
|
png(paste0(OUTPUT_DIR,"Job_Dist_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
||||||
|
JOB_TYPE_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
JOB_FACET_DATA <- INDUSTRY_JOBS %>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period,Industry) %>% summarize(Jobs=mean(Jobs)) %>% ungroup
|
||||||
|
JOB_FACET <- ggplot(JOB_FACET_DATA,aes(x=Period,y=Jobs,fill=factor(Period)))+geom_bar(stat='identity',width=0.99)+facet_wrap(.~Industry,nrow=5)+theme_bw()+labs(x = NULL)+theme(text=element_text(size=20),legend.position="top",palette.colour.discrete=c("darkslategray1","darkorchid1" ),axis.text.x = element_blank())+scale_fill_discrete(name = "") +scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=100))
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"Job_Facet_Plot.png"), units = "in", width = 11, height = 11, res = 600)
|
||||||
|
JOB_FACET
|
||||||
|
dev.off()
|
||||||
|
##################GDP
|
||||||
|
read_csv(paste0(DATA_DIR,'Gross Domestic Product - By Component - GDP Components.csv'),skip=5)
|
||||||
|
GDP_TOTAL <- read_csv(paste0(DATA_DIR,'Gross Domestic Product - By Component - GDP Components.csv'),skip=5)%>% select(-Units) %>% pivot_longer(c(-Category),names_to="Year") %>% mutate(value=value*1000,Year=parse_number(Year)) %>% filter(Year>=2029)
|
||||||
|
|
||||||
|
GDP_TOTAL <- GDP_TOTAL %>% filter(Category %in% c('Gross Domestic Product (GDP)','Consumption','Investment','Change in Private Inventories','Net Trade','Government Spending','Exogenous Final Demand'))
|
||||||
|
GDP_TOTAL <- GDP_TOTAL %>% filter(Category=='Gross Domestic Product (GDP)') %>% select(-Category) %>% rename(GDP=value)
|
||||||
|
GDP_PLOT <- ggplot(GDP_TOTAL ,aes(x=Year,y=GDP))+geom_line(linewidth=1,color='slateblue')+theme_bw()+theme(text=element_text(size=20),legend.position="top")+ylab("Wyoming GDP (Million USD)")+scale_x_continuous(breaks=c(seq(2030,2060,by=2)))+scale_y_continuous(breaks=seq(0,500,by=25))
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"GDP_Time_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
||||||
|
GDP_PLOT
|
||||||
|
dev.off()
|
||||||
|
################Personal Income
|
||||||
|
PERSONAL_INCOME <- read_csv(paste0(DATA_DIR,'Personal Income - By Region - Personal Income by Region.csv'),skip=5)%>% select(-Units) %>% pivot_longer(c(-Region),names_to="Year") %>% mutate(value=value*1000,Year=parse_number(Year)) %>% filter(Year>=2029) %>% rename(Income=value)
|
||||||
|
|
||||||
|
TOTAL_PERSONAL_INCOME <- PERSONAL_INCOME %>% filter(Region=='All Regions') %>% select(-Region)
|
||||||
|
#TOTAL_PERSONAL_INCOME
|
||||||
|
|
||||||
|
TAXES <- read_csv("Results/Tax_PI/Revenues.csv",skip=5) %>% clean_names() %>% filter(!is.na(revenue))
|
||||||
|
colnames(TAXES) <- gsub("fy","",colnames(TAXES))
|
||||||
|
TAXES <- TAXES %>% pivot_longer(c(-revenue,-units),names_to='year',values_to='Taxes') %>% mutate(Taxes=Taxes*1000) %>% select(-units)
|
||||||
|
TAXES$revenue <- gsub('State Sales & Use Taxes - ','Sales Tax: ', TAXES$revenue)
|
||||||
|
TAXES <- TAXES %>% filter(year>2028,!is.na(revenue))
|
||||||
|
TAXES <- TAXES %>% filter(Taxes>0)
|
||||||
|
TAXES$revenue[!grepl("Sales",TAXES$revenue)] <- 'Other Taxes'
|
||||||
|
TAXES <- TAXES %>% rename(Revenue='Taxes','Tax'=revenue,'Year'=year) %>% select(Year,Tax,Revenue)
|
||||||
|
TAXES <- TAXES %>% group_by(Year,Tax) %>% summarize(Revenue=sum(Revenue))
|
||||||
|
TOTAL_TAXES <- TAXES %>% group_by(Year) %>% summarize('Million (USD)'=sum(Revenue)/10^6,Metric='Tax Revenue') %>% mutate(Year=as.numeric(Year))
|
||||||
|
#TOTAL_TAXES
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
DOLLAR_VALUES <- rbind(OUTPUT_NUM %>% filter(Category=='Total') %>% select(-Category) %>% mutate(Metric='Economic Output') %>% rename('Million (USD)'=Output),
|
||||||
|
GDP_TOTAL %>% mutate(Metric='GDP') %>% rename('Million (USD)'=GDP),
|
||||||
|
TOTAL_TAXES,
|
||||||
|
TOTAL_PERSONAL_INCOME %>% mutate(Metric='Wages') %>% rename('Million (USD)'=Income))
|
||||||
|
FACET_INDICATORS_PLOT <- ggplot(DOLLAR_VALUES, aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+facet_wrap(.~Metric,nrow=2)+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=50))+theme(legend.position = "top",text=element_text(size=20))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus") )
|
||||||
|
#DOLLAR_VALUES
|
||||||
|
|
||||||
|
DIRECT_TAX <- c(10.408,22.355,24.647,58.221,55.835,53.449,51.062,48.676,46.290,43.904,41.518,39.132,37.318,35.766,34.214,32.662,31.110,29.557,28.005,26.453,24.901,23.349,21.797,20.244,18.692,17.140,15.588,14.036,12.484,10.931,9.379)
|
||||||
|
DIRECT_TAX <- cbind(2030:2060,DIRECT_TAX ) %>% as_tibble
|
||||||
|
|
||||||
|
colnames(DIRECT_TAX) <- c("Year","Tax")
|
||||||
|
#DOLLAR_VALUES
|
||||||
|
DOLLAR_VALUES[DOLLAR_VALUES$Metric=='Tax Revenue','Million (USD)'] <- DOLLAR_VALUES[DOLLAR_VALUES$Metric=='Tax Revenue','Million (USD)'] + c(0,DIRECT_TAX$Tax)
|
||||||
|
|
||||||
|
TAX_PLOT <- ggplot(DOLLAR_VALUES %>% filter(Metric %in% c('Tax Revenue')), aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=5))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus")[4],name="" )+theme(legend.position = "top",text=element_text(size=20))+ guides(fill = "none")
|
||||||
|
#TAX_PLOT
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"Total_Tax_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
||||||
|
TAX_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
FACET_INDICATORS_PLOT <- ggplot(DOLLAR_VALUES , aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+facet_wrap(.~Metric,nrow=2)+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=50))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus") )+theme(legend.position = "top",text=element_text(size=20))
|
||||||
|
#FACET_INDICATORS_PLOT
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
png(paste0(OUTPUT_DIR,"Facet_Indicator_Plot.png"), units = "in", width = 11, height = 10, res = 600)
|
||||||
|
FACET_INDICATORS_PLOT
|
||||||
|
dev.off()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
#############
|
||||||
|
Period_Indicator_Summary <- rbind(OUTPUT_NUM %>% filter(Category=='Total') %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='Economic Output','Average'=mean(Output),Max=max(Output)),GDP %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='GDP',Average=mean(GDP),Max=max(GDP)),EMPLOY_NUM %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='Employment',Average=mean(Employment),Max=max(Employment)))
|
||||||
|
Period_Indicator_Summary[,c(3:4)] <- round(Period_Indicator_Summary[,c(3:4)],0)
|
||||||
|
#Period_Indicator_Summary
|
||||||
|
|
||||||
|
write_csv(Period_Indicator_Summary,paste0(OUTPUT_DIR,"Economic_Summary_Indicator.csv" ),col_names=TRUE)
|
||||||
|
GDP_SUMMARY <- GDP %>% group_by(Year) %>% summarize(GDP=sum(GDP),NPV_3=(GDP/((1+0.03)^(Year-2029))),NPV_5=(GDP/((1+0.05)^(Year-2029))),NPV_7=(GDP/((1+0.07)^(Year-2029)))) %>% ungroup
|
||||||
|
NPV_3 <- GDP_SUMMARY %>% pull(NPV_3) %>% sum
|
||||||
|
NPV_5 <- GDP_SUMMARY %>% pull(NPV_5) %>% sum
|
||||||
|
NPV_7 <- GDP_SUMMARY %>% pull(NPV_7) %>% sum
|
||||||
|
NPV_SUMMARY <- round(t(c(NPV_3,NPV_5,NPV_7)),0) %>% as_tibble
|
||||||
|
#NPV_SUMMARY
|
||||||
|
colnames(NPV_SUMMARY) <- c('3%','5%','7%')
|
||||||
|
write_csv(NPV_SUMMARY,paste0(OUTPUT_DIR,"GDP_Net_Present_Value.csv" ))
|
||||||
|
|
||||||
|
#######################
|
||||||
|
TAX <- DOLLAR_VALUES %>% filter(Metric=='Tax Revenue') %>% select(Year,Tax=`Million (USD)`)
|
||||||
|
#TAX %>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Mean_Tax=mean(Tax),Max_Tax=max(Tax))
|
||||||
|
|
||||||
|
TAX_SUMMARY <- TAX %>% group_by(Year) %>% summarize(Tax=sum(Tax),NPV_3=(Tax/((1+0.03)^(Year-2029))),NPV_5=(Tax/((1+0.05)^(Year-2029))),NPV_7=(Tax/((1+0.07)^(Year-2029)))) %>% ungroup
|
||||||
|
NPV_3 <- TAX_SUMMARY %>% pull(NPV_3) %>% sum
|
||||||
|
NPV_5 <- TAX_SUMMARY %>% pull(NPV_5) %>% sum
|
||||||
|
NPV_7 <- TAX_SUMMARY %>% pull(NPV_7) %>% sum
|
||||||
|
NPV_TAX_SUMMARY <- round(t(c(NPV_3,NPV_5,NPV_7)),0) %>% as_tibble
|
||||||
|
#NPV_TAX_SUMMARY
|
||||||
|
colnames(NPV_TAX_SUMMARY) <- c('3%','5%','7%')
|
||||||
|
write_csv(NPV_TAX_SUMMARY,paste0(OUTPUT_DIR,"Tax_Net_Present_Value.csv" ))
|
||||||
|
|
||||||
|
|
||||||
22
Scripts/Load_IMPLAN.r
Normal file
22
Scripts/Load_IMPLAN.r
Normal file
@ -0,0 +1,22 @@
|
|||||||
|
#Function to load IMPLAN Yearly data.
|
||||||
|
GET_IMPLAN_DATA <- function(){
|
||||||
|
GET_FILE_US <- function(YEAR){read_csv(paste0("Model_Outputs/IMPLAN/US/US_",YEAR,"/economic_indicators_by_impact.csv")) %>% mutate(Year=YEAR) %>% filter(!is.na(Impact))%>% mutate(Region="US") }
|
||||||
|
GET_FILE_WY <- function(YEAR){read_csv(paste0("Model_Outputs/IMPLAN/Wyoming/WY_",YEAR,"/economic_indicators_by_impact.csv")) %>% mutate(Year=YEAR) %>% filter(!is.na(Impact))%>% mutate(Region="WY") }
|
||||||
|
DATA <-rbind(lapply(2028:2036,GET_FILE_US) %>% bind_rows()%>% rename(Income=`Labor Income`) %>% mutate(Income=parse_number(Income),`Value Added`=parse_number(`Value Added`),Output=parse_number(Output)) ,
|
||||||
|
lapply(2028:2036,GET_FILE_WY) %>% bind_rows()%>% rename(Income=`Labor Income`) %>% mutate(Income=parse_number(Income),`Value Added`=parse_number(`Value Added`),Output=parse_number(Output)))
|
||||||
|
|
||||||
|
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
||||||
|
DATA <- DATA %>% pivot_longer(-c(Impact,Year,Region)) %>% rename(Type=Impact,Impact=name)
|
||||||
|
DATA$Impact <- gsub("3 - ","",gsub("2 - ","",gsub("1 - ","",DATA$Impact)))
|
||||||
|
DATA <- DATA %>% mutate(Source='IMPLAN') %>% select(Type,Year,Region,Impact,Source,value)
|
||||||
|
######Append
|
||||||
|
TEMP <- DATA %>% filter(Year==2036)
|
||||||
|
RES <- TEMP %>% mutate(Year=2037)
|
||||||
|
for(i in 2038:2060){
|
||||||
|
RES <- RES %>% rbind(TEMP %>% mutate(Year=i))
|
||||||
|
}
|
||||||
|
DATA <- DATA %>% full_join(RES) %>% unique
|
||||||
|
|
||||||
|
return(DATA)
|
||||||
|
}
|
||||||
|
|
||||||
37
Scripts/Load_REMI.r
Normal file
37
Scripts/Load_REMI.r
Normal file
@ -0,0 +1,37 @@
|
|||||||
|
GET_REMI_DATA <- function(DATA_DIR='Model_Outputs/REMI/'){
|
||||||
|
#DATA_DIR='Model_Outputs/REMI/'
|
||||||
|
######################Employments
|
||||||
|
EMPLOY <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Employment.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
||||||
|
EMPLOY
|
||||||
|
MULTIPLIER <- EMPLOY[(grepl("Multiplier",EMPLOY$Category)),]
|
||||||
|
EMPLOY <- EMPLOY[!(grepl("Multiplier",EMPLOY$Category)),]
|
||||||
|
EMPLOY$value<- ifelse(grepl("Thousands",EMPLOY$Units),1000*EMPLOY$value,EMPLOY$value)
|
||||||
|
EMPLOY$value<- ifelse(grepl("Million",EMPLOY$Units),10^6*EMPLOY$value,EMPLOY$value)
|
||||||
|
EMPLOY$value<- ifelse(grepl("Billion",EMPLOY$Units),10^9*EMPLOY$value,EMPLOY$value)
|
||||||
|
|
||||||
|
EMPLOY$Category <- str_replace(EMPLOY$Category," Employment","" )
|
||||||
|
EMPLOY <- EMPLOY %>% filter(Category!='Total') %>% select(-Units) %>% rename(Type=Category) %>% mutate(Region="WY") %>% mutate(Impact="Employment",Source="REMI") %>% select(Type,Year,Region,Impact,Source,value)
|
||||||
|
EMPLOY
|
||||||
|
######Output
|
||||||
|
OUTPUT <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Output.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
||||||
|
OUTPUT_NUM <- OUTPUT %>% select(-Units,Output=value) %>% filter(Year>=2028) %>% mutate(Output=Output*1000)
|
||||||
|
OUTPUT <- OUTPUT[!(grepl("Multiplier",OUTPUT$Category)),]
|
||||||
|
OUTPUT$value<- ifelse(grepl("Thousands",OUTPUT$Units),1000*OUTPUT$value,OUTPUT$value)
|
||||||
|
OUTPUT$value<- ifelse(grepl("Million",OUTPUT$Units),10^6*OUTPUT$value,OUTPUT$value)
|
||||||
|
OUTPUT$value<- ifelse(grepl("Billion",OUTPUT$Units),10^9*OUTPUT$value,OUTPUT$value)
|
||||||
|
OUTPUT$Category <- str_replace(OUTPUT$Category," Output","" )
|
||||||
|
OUTPUT <- OUTPUT %>% filter(Category!='Total') %>% select(-Units) %>% rename(Type=Category) %>% mutate(Region="WY") %>% mutate(Impact="Output",Source="REMI") %>% select(Type,Year,Region,Impact,Source,value)
|
||||||
|
|
||||||
|
|
||||||
|
######Value ADded
|
||||||
|
GDP <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced - Value-Added.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
||||||
|
|
||||||
|
GDP$value<- ifelse(grepl("Thousands",GDP$Units),1000*GDP$value,GDP$value)
|
||||||
|
GDP$value<- ifelse(grepl("Million",GDP$Units),10^6*GDP$value,GDP$value)
|
||||||
|
GDP$value<- ifelse(grepl("Billion",GDP$Units),10^9*GDP$value,GDP$value)
|
||||||
|
GDP$Category <- str_replace(GDP$Category," Value-Added","" )
|
||||||
|
GDP <- GDP %>% filter(Category!='Total') %>% select(-Units) %>% rename(Type=Category) %>% mutate(Region="WY") %>% mutate(Impact="Value Added",Source="REMI") %>% select(Type,Year,Region,Impact,Source,value)
|
||||||
|
|
||||||
|
REMI_DATA <- full_join(EMPLOY,OUTPUT) %>% full_join(GDP)
|
||||||
|
return(REMI_DATA)
|
||||||
|
}
|
||||||
234
Visuals.r
234
Visuals.r
@ -1,224 +1,22 @@
|
|||||||
library(tidyverse)
|
library(tidyverse)
|
||||||
library(janitor)
|
|
||||||
#install.packages("paletteer")
|
|
||||||
|
|
||||||
library(scales)
|
library(scales)
|
||||||
|
library(janitor)
|
||||||
library(paletteer)
|
library(paletteer)
|
||||||
DATA_DIR <- 'Exports/'
|
|
||||||
OUTPUT_DIR <- './Results/Tables_and_Figures/'
|
|
||||||
dir.create(OUTPUT_DIR,recursive=TRUE,showWarnings=FALSE)
|
|
||||||
######################Employments
|
|
||||||
EMPLOY <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Employment.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
|
||||||
|
|
||||||
EMPLOY_NUM <- EMPLOY %>% filter(Units!="Proportion") %>% select(-Units,Employment=value) %>% filter(Year>=2027) %>% mutate(Employment=Employment*1000)
|
source("Scripts/Load_IMPLAN.r")
|
||||||
|
source("Scripts/Load_REMI.r")
|
||||||
|
|
||||||
EMPLOY_NUM$Category <- gsub(" Employment","",EMPLOY_NUM$Category)
|
IMPLAN <- GET_IMPLAN_DATA()
|
||||||
EMPLOY_NUM$Category <- factor(EMPLOY_NUM$Category,levels=rev(c("Direct","Indirect","Induced","Total")))
|
REMI <- GET_REMI_DATA()
|
||||||
#EMPLOY_NUM %>% filter(Employment=='Direct')
|
DATA <- full_join(IMPLAN,REMI)
|
||||||
#EMPLOY_NUM
|
|
||||||
#EMPLOY_NUM %>% filter(Category=='Total',Employment!=0)%>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Employment=mean(Employment))
|
TEST <- DATA %>% group_by(Year,Region,Impact,Source) %>% mutate(value=sum(value)) %>% filter(Region=='WY') %>% ungroup
|
||||||
#EMPLOY_NUM %>% filter(Category=='Total')%>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Employment=mean(Employment))
|
ggplot(TEST ,aes(x=Year,y=value,color=Source))+geom_line()+facet_wrap(~Impact)
|
||||||
#EMPLOY_NUM %>% filter(Category=='Total') %>% print(n=100)
|
|
||||||
|
TEST2 <- DATA %>% group_by(Year,Region,Impact,Source) %>% mutate(value=sum(value)) %>% filter(Source=='IMPLAN') %>% ungroup %>% group_by(Year,Impact) %>% summarize(DIFF=max(value)/min(value))
|
||||||
|
ggplot(TEST2 ,aes(x=Year,y=value,color=Region))+geom_line()+facet_wrap(~Impact)
|
||||||
COLORS <- rev(paletteer_d("fishualize::Alosa_fallax",n=4,direction=1)[-2])
|
TEST3 <- DATA %>% group_by(Year,Region,Impact,Source) %>% mutate(value=sum(value)) %>% filter(Source=='IMPLAN') %>% ungroup %>% group_by(Year,Impact) %>% summarize(DIFF=(max(value)-min(value))/min(value))
|
||||||
MAX_VAL <- round(max(EMPLOY_NUM$Employment))
|
|
||||||
#MAX_VAL
|
ggplot(TEST3 ,aes(x=Year,y=DIFF))+geom_line()+facet_wrap(~Impact)
|
||||||
COOL_DOWN <- as.numeric(EMPLOY_NUM[5,3])
|
|
||||||
#EMPLOY_NUM
|
|
||||||
EMPLOY_GRAPH_DATA <- EMPLOY_NUM %>% filter(Category=='Total') %>% mutate(Category=ifelse(Employment<0,"Negative","Positive"))
|
|
||||||
TEMP <- EMPLOY_NUM %>% filter(Category=='Total') %>% filter(Employment<0) %>% mutate(Employment=0,Category="Positive")
|
|
||||||
EMPLOY_GRAPH_DATA <- rbind(EMPLOY_GRAPH_DATA ,TEMP)
|
|
||||||
TEMP2 <- EMPLOY_GRAPH_DATA[max(which(EMPLOY_GRAPH_DATA$Employment<0)),] %>% mutate(Year=Year+1,Employment=0)
|
|
||||||
EMPLOY_GRAPH_DATA <- rbind(EMPLOY_GRAPH_DATA ,TEMP2)
|
|
||||||
rm(TEMP,TEMP2)
|
|
||||||
|
|
||||||
JOB_PLOT <-ggplot(EMPLOY_GRAPH_DATA ,aes(x=Year,y=Employment))+geom_area(position = "stack",aes(fill=Category,group=Category))+theme_bw()+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(-250,10000,by=500)) +scale_fill_manual(values=c("red","blue3"))+theme(legend.position = "none")
|
|
||||||
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"Job_plot.png" ) , units = "in", width = 11, height = 8, res = 600)
|
|
||||||
JOB_PLOT
|
|
||||||
dev.off()
|
|
||||||
#JOB_PLOT
|
|
||||||
###################Output graph
|
|
||||||
OUTPUT <- read_csv(paste0(DATA_DIR,"Direct, Indirect, and Induced -Output.csv" ),skip=5) %>% pivot_longer(c(-Category,-Units),names_to="Year") %>% mutate(Year=parse_number(Year))
|
|
||||||
OUTPUT_NUM <- OUTPUT %>% select(-Units,Output=value) %>% filter(Year>=2028) %>% mutate(Output=Output*1000)
|
|
||||||
OUTPUT_NUM
|
|
||||||
|
|
||||||
OUTPUT_NUM$Category <- gsub(" Output","",OUTPUT_NUM$Category)
|
|
||||||
OUTPUT_NUM$Category <- factor(OUTPUT_NUM$Category,levels=rev(c("Direct","Indirect","Induced","Total")))
|
|
||||||
OUTPUT_PLOT <- ggplot(OUTPUT_NUM %>% filter(Category!="Total"),aes(x=Year,y=Output))+geom_area(position = "stack",aes(fill=Category,group=Category))+theme_bw()+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_fill_manual(values=COLORS)+geom_line(data=OUTPUT_NUM%>% filter(Category=="Total"),linewidth=1)+theme(text = element_text(size = 20),legend.position = "top")+scale_y_continuous(labels = scales::comma,breaks=seq(0,10000,by=250))+ylab("Economic Output (Million USD)")
|
|
||||||
OUTPUT_PLOT
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"Output_plot.png"), units = "in", width = 10, height = 8, res = 600)
|
|
||||||
OUTPUT_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
####GDP and Output
|
|
||||||
GDP <- read_csv(paste0(DATA_DIR,"Gross Domestic Product - By Region - GDP by Region.csv" ),skip=5) %>% pivot_longer(c(-Region,-Units),names_to="Year",values_to="GDP") %>% mutate(Year=parse_number(Year),GDP=GDP*1000) %>% select(-Units)
|
|
||||||
GDP <- GDP %>% filter(Region !='All Regions')
|
|
||||||
GDP$Region <- gsub(" County","",GDP$Region)
|
|
||||||
KEY_REGIONS <- GDP %>% group_by(Region) %>% summarize(GDP = median(GDP)) %>% arrange(desc(GDP)) %>% filter(GDP>0.5) %>% pull(Region)
|
|
||||||
KEY_REGIONS
|
|
||||||
OTHER_GDP <- GDP %>% filter(!(Region %in% KEY_REGIONS)) %>% group_by(Year) %>% summarize(Region="Other Counties",GDP=sum(GDP)) %>% ungroup
|
|
||||||
GDP <- rbind(GDP %>% filter(Region %in% KEY_REGIONS),OTHER_GDP)
|
|
||||||
GDP$Region <- factor(GDP$Region,levels=rev(c("Other Counties",KEY_REGIONS)))
|
|
||||||
GDP <- GDP %>% filter(Year>=2027)
|
|
||||||
sum(GDP$GDP)
|
|
||||||
OUTPUT_NUM %>% pull(Output) %>% sum
|
|
||||||
GDP <- GDP %>% group_by(Year) %>% summarize(GDP=sum(GDP)) %>% filter(Year>2027) %>% arrange(Year) %>% pull(GDP)
|
|
||||||
sum(GDP)
|
|
||||||
length(GDP)
|
|
||||||
sum(GDP*(1.09)^-(0:32))
|
|
||||||
|
|
||||||
GDP_SUB_REGION_PLOT <- ggplot(GDP %>% filter(Region!='Lincoln'),aes(x=Year,y=GDP,fill=Region))+geom_area(position='stack')+scale_x_continuous(breaks=c(2027,seq(2030,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=100))+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+ylab("GDP (Million USD)")+scale_fill_manual(values=paletteer_d("PNWColors::Shuksan2"))
|
|
||||||
GDP_SUB_REGION_PLOT
|
|
||||||
png(paste0(OUTPUT_DIR,"GDP_Other_Counties.png"), units = "in", width = 10, height = 8, res = 600)
|
|
||||||
GDP_SUB_REGION_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
|
|
||||||
GDP_REGION_SUMMARY <- GDP %>% mutate(Region=factor(ifelse(Region=='Lincoln','Lincoln','Rest of Wyoming'),levels=rev(c('Lincoln','Rest of Wyoming')))) %>% group_by(Region,Year) %>% summarize(GDP=sum(GDP)) %>% ungroup
|
|
||||||
GDP_PLOT <- ggplot(GDP_REGION_SUMMARY ,aes(x=Year,y=GDP,fill=Region))+geom_area(position='stack')+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=25))+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+ylab("GDP (Million USD)")+scale_fill_manual(values=c(paletteer_d("PNWColors::Shuksan2")[c(5)],paletteer::paletteer_d("calecopal::lupinus")[2]))
|
|
||||||
#paletteer::paletteer_d("calecopal::lupinus")[3]
|
|
||||||
png(paste0(OUTPUT_DIR,"GDP_Region_Plot.png"), units = "in", width = 10, height = 8, res = 600)
|
|
||||||
GDP_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
###################
|
|
||||||
INDUSTRY_JOBS <- read_csv(paste0(DATA_DIR,'Employment- By Industry - Employment by Industry.csv'),skip=5) %>% pivot_longer(c(-Industry,-Units),names_to="Year",values_to="Jobs") %>%mutate(Year=parse_number(Year)) %>% filter(Industry!='All Industries') %>% select(-Units) %>% filter(Year>=2029)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Data processing, hosting, and related services; Other information services',"Data processing",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Professional, scientific, and technical services',"Technical services",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Administrative and support services',"Administrative services",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='State and Local Government',"Government",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Food services and drinking places',"Restaurants",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Other transportation equipment manufacturing',"Equipment manufacturing",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Repair and maintenance',"Maintenance",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Utilities',"Energy Production",INDUSTRY_JOBS$Industry)
|
|
||||||
INDUSTRY_JOBS$Industry <- ifelse(INDUSTRY_JOBS$Industry=='Ambulatory health care services',"Hospitals",INDUSTRY_JOBS$Industry)
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
INDUSTRY_JOBS <- INDUSTRY_JOBS %>% group_by(Year) %>% mutate(Rank=rank(-Jobs)) %>% mutate(Rank=ifelse(Rank>10,11,Rank),Industry=ifelse(Rank==11,"Other",Industry)) %>% group_by(Year,Industry,Rank) %>% summarize(Jobs=sum(Jobs)) %>% ungroup(Industry,Rank) %>% arrange(Year,Rank) %>% ungroup
|
|
||||||
#INDUSTRY_JOBS %>% pull(Industry) %>% unique
|
|
||||||
|
|
||||||
ORDER <- c(INDUSTRY_JOBS %>% filter(Industry!='Other') %>% group_by(Industry) %>% summarize(MEAN=mean(Jobs)) %>% arrange(desc(MEAN)) %>% pull(Industry) %>% unique,"Other")
|
|
||||||
INDUSTRY_JOBS$Industry <- factor(INDUSTRY_JOBS$Industry,levels=ORDER)
|
|
||||||
#INDUSTRY_JOBS
|
|
||||||
|
|
||||||
JOB_TYPE_PLOT <- ggplot(INDUSTRY_JOBS ,aes(x=Year,y=Jobs,fill=Industry))+geom_bar(stat='identity')+ paletteer::scale_fill_paletteer_d("colorBlindness::Blue2DarkRed18Steps",name="")+theme_bw()+theme(text = element_text(size = 20),legend.position = "top")+guides(fill=guide_legend(nrow=4,byrow=TRUE)) +scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=500))
|
|
||||||
png(paste0(OUTPUT_DIR,"Job_Dist_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
|
||||||
JOB_TYPE_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
JOB_FACET_DATA <- INDUSTRY_JOBS %>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period,Industry) %>% summarize(Jobs=mean(Jobs)) %>% ungroup
|
|
||||||
JOB_FACET <- ggplot(JOB_FACET_DATA,aes(x=Period,y=Jobs,fill=factor(Period)))+geom_bar(stat='identity',width=0.99)+facet_wrap(.~Industry,nrow=5)+theme_bw()+labs(x = NULL)+theme(text=element_text(size=20),legend.position="top",palette.colour.discrete=c("darkslategray1","darkorchid1" ),axis.text.x = element_blank())+scale_fill_discrete(name = "") +scale_y_continuous(labels = scales::comma,breaks=seq(0,1000,by=100))
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"Job_Facet_Plot.png"), units = "in", width = 11, height = 11, res = 600)
|
|
||||||
JOB_FACET
|
|
||||||
dev.off()
|
|
||||||
##################GDP
|
|
||||||
read_csv(paste0(DATA_DIR,'Gross Domestic Product - By Component - GDP Components.csv'),skip=5)
|
|
||||||
GDP_TOTAL <- read_csv(paste0(DATA_DIR,'Gross Domestic Product - By Component - GDP Components.csv'),skip=5)%>% select(-Units) %>% pivot_longer(c(-Category),names_to="Year") %>% mutate(value=value*1000,Year=parse_number(Year)) %>% filter(Year>=2029)
|
|
||||||
|
|
||||||
GDP_TOTAL <- GDP_TOTAL %>% filter(Category %in% c('Gross Domestic Product (GDP)','Consumption','Investment','Change in Private Inventories','Net Trade','Government Spending','Exogenous Final Demand'))
|
|
||||||
GDP_TOTAL <- GDP_TOTAL %>% filter(Category=='Gross Domestic Product (GDP)') %>% select(-Category) %>% rename(GDP=value)
|
|
||||||
GDP_PLOT <- ggplot(GDP_TOTAL ,aes(x=Year,y=GDP))+geom_line(linewidth=1,color='slateblue')+theme_bw()+theme(text=element_text(size=20),legend.position="top")+ylab("Wyoming GDP (Million USD)")+scale_x_continuous(breaks=c(seq(2030,2060,by=2)))+scale_y_continuous(breaks=seq(0,500,by=25))
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"GDP_Time_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
|
||||||
GDP_PLOT
|
|
||||||
dev.off()
|
|
||||||
################Personal Income
|
|
||||||
PERSONAL_INCOME <- read_csv(paste0(DATA_DIR,'Personal Income - By Region - Personal Income by Region.csv'),skip=5)%>% select(-Units) %>% pivot_longer(c(-Region),names_to="Year") %>% mutate(value=value*1000,Year=parse_number(Year)) %>% filter(Year>=2029) %>% rename(Income=value)
|
|
||||||
|
|
||||||
TOTAL_PERSONAL_INCOME <- PERSONAL_INCOME %>% filter(Region=='All Regions') %>% select(-Region)
|
|
||||||
#TOTAL_PERSONAL_INCOME
|
|
||||||
|
|
||||||
TAXES <- read_csv("Results/Tax_PI/Revenues.csv",skip=5) %>% clean_names() %>% filter(!is.na(revenue))
|
|
||||||
colnames(TAXES) <- gsub("fy","",colnames(TAXES))
|
|
||||||
TAXES <- TAXES %>% pivot_longer(c(-revenue,-units),names_to='year',values_to='Taxes') %>% mutate(Taxes=Taxes*1000) %>% select(-units)
|
|
||||||
TAXES$revenue <- gsub('State Sales & Use Taxes - ','Sales Tax: ', TAXES$revenue)
|
|
||||||
TAXES <- TAXES %>% filter(year>2028,!is.na(revenue))
|
|
||||||
TAXES <- TAXES %>% filter(Taxes>0)
|
|
||||||
TAXES$revenue[!grepl("Sales",TAXES$revenue)] <- 'Other Taxes'
|
|
||||||
TAXES <- TAXES %>% rename(Revenue='Taxes','Tax'=revenue,'Year'=year) %>% select(Year,Tax,Revenue)
|
|
||||||
TAXES <- TAXES %>% group_by(Year,Tax) %>% summarize(Revenue=sum(Revenue))
|
|
||||||
TOTAL_TAXES <- TAXES %>% group_by(Year) %>% summarize('Million (USD)'=sum(Revenue)/10^6,Metric='Tax Revenue') %>% mutate(Year=as.numeric(Year))
|
|
||||||
#TOTAL_TAXES
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
DOLLAR_VALUES <- rbind(OUTPUT_NUM %>% filter(Category=='Total') %>% select(-Category) %>% mutate(Metric='Economic Output') %>% rename('Million (USD)'=Output),
|
|
||||||
GDP_TOTAL %>% mutate(Metric='GDP') %>% rename('Million (USD)'=GDP),
|
|
||||||
TOTAL_TAXES,
|
|
||||||
TOTAL_PERSONAL_INCOME %>% mutate(Metric='Wages') %>% rename('Million (USD)'=Income))
|
|
||||||
FACET_INDICATORS_PLOT <- ggplot(DOLLAR_VALUES, aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+facet_wrap(.~Metric,nrow=2)+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=50))+theme(legend.position = "top",text=element_text(size=20))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus") )
|
|
||||||
#DOLLAR_VALUES
|
|
||||||
|
|
||||||
DIRECT_TAX <- c(10.408,22.355,24.647,58.221,55.835,53.449,51.062,48.676,46.290,43.904,41.518,39.132,37.318,35.766,34.214,32.662,31.110,29.557,28.005,26.453,24.901,23.349,21.797,20.244,18.692,17.140,15.588,14.036,12.484,10.931,9.379)
|
|
||||||
DIRECT_TAX <- cbind(2030:2060,DIRECT_TAX ) %>% as_tibble
|
|
||||||
|
|
||||||
colnames(DIRECT_TAX) <- c("Year","Tax")
|
|
||||||
#DOLLAR_VALUES
|
|
||||||
DOLLAR_VALUES[DOLLAR_VALUES$Metric=='Tax Revenue','Million (USD)'] <- DOLLAR_VALUES[DOLLAR_VALUES$Metric=='Tax Revenue','Million (USD)'] + c(0,DIRECT_TAX$Tax)
|
|
||||||
|
|
||||||
TAX_PLOT <- ggplot(DOLLAR_VALUES %>% filter(Metric %in% c('Tax Revenue')), aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=5))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus")[4],name="" )+theme(legend.position = "top",text=element_text(size=20))+ guides(fill = "none")
|
|
||||||
#TAX_PLOT
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"Total_Tax_Plot.png"), units = "in", width = 11, height = 8, res = 600)
|
|
||||||
TAX_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
FACET_INDICATORS_PLOT <- ggplot(DOLLAR_VALUES , aes(x=Year,y=`Million (USD)`,fill=Metric))+geom_area()+facet_wrap(.~Metric,nrow=2)+theme_bw()+scale_x_continuous(breaks=c(2029,seq(2035,2060,by=5)))+scale_y_continuous(labels = scales::comma,breaks=seq(0,3000,by=50))+scale_fill_manual(values=paletteer::paletteer_d("calecopal::lupinus") )+theme(legend.position = "top",text=element_text(size=20))
|
|
||||||
#FACET_INDICATORS_PLOT
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
png(paste0(OUTPUT_DIR,"Facet_Indicator_Plot.png"), units = "in", width = 11, height = 10, res = 600)
|
|
||||||
FACET_INDICATORS_PLOT
|
|
||||||
dev.off()
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
#############
|
|
||||||
Period_Indicator_Summary <- rbind(OUTPUT_NUM %>% filter(Category=='Total') %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='Economic Output','Average'=mean(Output),Max=max(Output)),GDP %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='GDP',Average=mean(GDP),Max=max(GDP)),EMPLOY_NUM %>% mutate(Period=ifelse(Year<=2033,"Construction","Operation")) %>% group_by(Period) %>% summarize(Metric='Employment',Average=mean(Employment),Max=max(Employment)))
|
|
||||||
Period_Indicator_Summary[,c(3:4)] <- round(Period_Indicator_Summary[,c(3:4)],0)
|
|
||||||
#Period_Indicator_Summary
|
|
||||||
|
|
||||||
write_csv(Period_Indicator_Summary,paste0(OUTPUT_DIR,"Economic_Summary_Indicator.csv" ),col_names=TRUE)
|
|
||||||
GDP_SUMMARY <- GDP %>% group_by(Year) %>% summarize(GDP=sum(GDP),NPV_3=(GDP/((1+0.03)^(Year-2029))),NPV_5=(GDP/((1+0.05)^(Year-2029))),NPV_7=(GDP/((1+0.07)^(Year-2029)))) %>% ungroup
|
|
||||||
NPV_3 <- GDP_SUMMARY %>% pull(NPV_3) %>% sum
|
|
||||||
NPV_5 <- GDP_SUMMARY %>% pull(NPV_5) %>% sum
|
|
||||||
NPV_7 <- GDP_SUMMARY %>% pull(NPV_7) %>% sum
|
|
||||||
NPV_SUMMARY <- round(t(c(NPV_3,NPV_5,NPV_7)),0) %>% as_tibble
|
|
||||||
#NPV_SUMMARY
|
|
||||||
colnames(NPV_SUMMARY) <- c('3%','5%','7%')
|
|
||||||
write_csv(NPV_SUMMARY,paste0(OUTPUT_DIR,"GDP_Net_Present_Value.csv" ))
|
|
||||||
|
|
||||||
#######################
|
|
||||||
TAX <- DOLLAR_VALUES %>% filter(Metric=='Tax Revenue') %>% select(Year,Tax=`Million (USD)`)
|
|
||||||
#TAX %>% mutate(Period=ifelse(Year>2033,"Operating","Construction")) %>% group_by(Period) %>% summarize(Mean_Tax=mean(Tax),Max_Tax=max(Tax))
|
|
||||||
|
|
||||||
TAX_SUMMARY <- TAX %>% group_by(Year) %>% summarize(Tax=sum(Tax),NPV_3=(Tax/((1+0.03)^(Year-2029))),NPV_5=(Tax/((1+0.05)^(Year-2029))),NPV_7=(Tax/((1+0.07)^(Year-2029)))) %>% ungroup
|
|
||||||
NPV_3 <- TAX_SUMMARY %>% pull(NPV_3) %>% sum
|
|
||||||
NPV_5 <- TAX_SUMMARY %>% pull(NPV_5) %>% sum
|
|
||||||
NPV_7 <- TAX_SUMMARY %>% pull(NPV_7) %>% sum
|
|
||||||
NPV_TAX_SUMMARY <- round(t(c(NPV_3,NPV_5,NPV_7)),0) %>% as_tibble
|
|
||||||
#NPV_TAX_SUMMARY
|
|
||||||
colnames(NPV_TAX_SUMMARY) <- c('3%','5%','7%')
|
|
||||||
write_csv(NPV_TAX_SUMMARY,paste0(OUTPUT_DIR,"Tax_Net_Present_Value.csv" ))
|
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user