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INDUSTRY CLASSIFICATION A-1 APPENDIX A INDUSTRY CLASSIFICATION Industry Classification Codes for Detailed Industry (4 digit) (Starting January 2014) These categories are aggregated into 52 detailed...

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INDUSTRY CLASSIFICATION A-1
APPENDIX A
INDUSTRY CLASSIFICATION

Industry Classification Codes for Detailed Industry (4 digit)
(Starting January 2014)


These categories are aggregated into 52 detailed groups and 14 major groups (see pages 10-12 of this
attachment). The codes in the right hand column are the NAICS equivalent.

These codes co
espond to Items PEIO1ICD and PEIO2ICD, in positions XXXXXXXXXXand XXXXXXXXXXof the
Basic CPS record layout in all months, except March. In the March, these codes co
espond to
PEIOIND and INDUSTRY, in positions XXXXXXXXXXand XXXXXXXXXXof the Person record.


CENSUS NAICS
CODE DESCRIPTION CODE



Agriculture, Forestry, Fishing, and Hunting

0170 Crop production 111
0180 Animal production 112
0190 Forestry except logging 1131, 1132
0270 Logging 1133
0280 Fishing, hunting, and trapping 114
0290 Support activities for agriculture and forestry 115

Mining

0370 Oil and gas extraction 211
0380 Coal mining 2121
0390 Metal ore mining 2122
0470 Nonmetallic mineral mining and qua
ying and not specified type of mining Part of 21
0490 Support activities for mining 213

Utilities

0570 Electric power generation, transmission and distribution Pt. 2211
0580 Natural gas distribution Pt. 2212
0590 Electric and gas, and other combinations Pts. 2211, 2212
0670 Water, steam, air-conditioning, and i
igation systems 22131, 22133
0680 Sewage treatment facilities 22132
0690 Not specified utilities Part of 22



CODE DESCRIPTION INDUSTRY CODE

A-2 XXXXXXXXXXINDUSTRY CLASSIFICATION
Construction

0770 ** Construction 23
(Includes the cleaning of buildings and dwellings is incidental during
construction and immediately after construction)

Manufacturing
Nondurable Goods manufacturing

1070 Animal food, grain and oilseed milling 3111, 3112
1080 Sugar and confectionery products 3113
1090 Fruit and vegetable preserving and specialty food manufacturing 3114
1170 Dairy product manufacturing 3115
1180 Animal slaughtering and processing 3116
1190 Retail bakeries XXXXXXXXXX
1270 Bakeries, except retail XXXXXXXXXXexc.
XXXXXXXXXX
1280 Seafood and other miscellaneous foods, n.e.c. 3117, 3119
1290 Not specified food industries Part of 311
1370 Beverage manufacturing 3121
1390 Tobacco manufacturing 3122
1470 Fiber, yarn, and thread mills 3131
1480 Fa
ic mills, except knitting 3132 exc.
31324
1490 Textile and fa
ic finishing and coating mills 3133
1570 Carpet and rug mills 31411
1590 Textile product mills, except carpets and rugs 314 exc. 31411
1670 Knitting mills 31324, 3151
1680 Cut and sew apparel manufacturing 3152
1690 Apparel accessories and other apparel manufacturing 3159
1770 Footwear manufacturing 3162
1790 Leather tanning and products, except footwear manufacturing 3161, 3169
1870 Pulp, paper, and pape
oard mills 3221
1880 Pape
oard containers and boxes 32221
1890 Miscellaneous paper and pulp products XXXXXXXXXX, 32223,
32229
1990 Printing and related support activities 3231
2070 Petroleum refining 32411
2090 Miscellaneous petroleum and coal products 32419
2170 Resin, synthetic ru
er and fibers, and filaments manufacturing XXXXXXXXXX
2180 Agricultural chemical manufacturing 3253
2190 Pharmaceutical and medicine manufacturing 3254
2270 Paint, coating, and adhesive manufacturing B46 3255
2280 Soap, cleaning compound, and cosmetics manufacturing 3256
2290 Industrial and miscellaneous chemicals 3251, 3259
2370 Plastics product manufacturing 3261
2380 Tire manufacturing 32621
2390 Ru
er products, except tires, manufacturing 32622, 32629

CODE DESCRIPTION INDUSTRY CODE

INDUSTRY CLASSIFICATION A-3

Durable Goods Manufacturing

2470 Pottery, ceramics, and related products manufacturing XXXXXXXXXX
2480 Structural clay product manufacturing 32712
2490 Glass and glass product manufacturing 3272
2570 Cement, concrete, lime, and gypsum product manufacturing 3273, 3274
2590 Miscellaneous nonmetallic mineral product manufacturing 3279
2670 Iron and steel mills and steel product manufacturing 3311, 3312
2680 Aluminum production and processing 3313
2690 Nonfe
ous metal, except aluminum, production and processing 3314
2770 Foundries 3315
2780 Metal forgings and stampings 3321
2790 Cutlery and hand tool manufacturing 3322
2870 Structural metals, and tank and shipping container manufacturing 3323, 3324
2880 Machine shops; turned product; screw, nut and bolt manufacturing 3327
2890 Coating, engraving, heat treating and allied activities 3328
2970 Ordnance XXXXXXXXXXto
XXXXXXXXXX
2980 Miscellaneous fa
icated metal products manufacturing 3325, 3326,
3329 exc.
XXXXXXXXXX, 332993,
XXXXXXXXXX, 332995
2990 Not specified metal industries Part of 331
and 332
3070 Agricultural implement manufacturing 33311
3080 Construction, mining and oil field machinery manufacturing 33312, 33313
3095 Commercial and service industry machinery manufacturing 3333
3170 Metalworking machinery manufacturing 3335
3180 Engines, tu
ines, and power transmission equipment manufacturing 3336
3190 Machinery manufacturing, n.e.c. Part of 333
3365 Computer and peripheral equipment manufacturing 3341
3370 Communications, audio, and video equipment manufacturing 3342, 3343
3380 Navigational, measuring, electromedical, and control instruments manufacturing 3345
3390 Electronic component and product manufacturing, n.e.c. 3344, 3346
3470 Household appliance manufacturing 3352
3490 Electrical lighting, equipment, and supplies manufacturing, n.e.c. 3351, 3353,
3359
3570 Motor vehicles and motor vehicle equipment manufacturing 3361, 3362,
3363
3580 Aircraft and parts manufacturing XXXXXXXXXXto
XXXXXXXXXX
3590 Aerospace products and parts manufacturing XXXXXXXXXX,
XXXXXXXXXX, 336419
3670 Railroad rolling stock manufacturing 3365
3680 Ship and boat building 3366
3690 Other transportation equipment manufacturing 3369
CODE DESCRIPTION INDUSTRY CODE

A-4 XXXXXXXXXXINDUSTRY CLASSIFICATION
3770 Sawmills and wood preservation 3211
3780 Veneer, plywood, and engineered wood products 3212
3790 Prefa
icated wood buildings and mobile homes XXXXXXXXXX,
XXXXXXXXXX
3875 Miscellaneous wood products 3219 exc.
XXXXXXXXXX, 321992
3895 Furniture and related product manufacturing 337
3960 Medical equipment and supplies manufacturing 3391
3970 Toys, amusement, and sporting goods manufacturing XXXXXXXXXX, 33993
3980 Miscellaneous manufacturing, n.e.c XXXXXXXXXXexc.
33992, 33993
3990 Not specified manufacturing industries Part of 31, 32, 33

Wholesale Trade
Durable Goods Wholesale

4070 Motor vehicles, parts and supplies, merchant wholesalers 4231
4080 Furniture and home furnishing, merchant wholesalers 4232
4090 Lumber and other construction materials, merchant wholesalers 4233
4170 Professional and commercial equipment and supplies, merchant wholesalers 4234
4180 Metals and minerals, except petroleum, merchant wholesalers 4235
4195 Electrical goods, merchant wholesalers 4236
4265 Hardware, plumbing and heating equipment, and supplies, merchant wholesalers 4237
4270 Machinery, equipment, and supplies, merchant wholesalers 4238
4280 Recyclable material, merchant wholesalers 42393
4290 Miscellaneous durable goods, merchant wholesalers 4239 exc.
42393

Nondurable Goods Wholesale

4370 Paper and paper products, merchant wholesalers 4241
4380 Drugs, sundries, and chemical and allied products, merchant wholesalers 4242, 4246
4390 Apparel, fa
ics, and notions, merchant wholesalers 4243
4470 Groceries and related products, merchant wholesalers 4244
4480 Farm product raw materials, merchant wholesalers 4245
4490 Petroleum and petroleum products, merchant wholesalers 4247
4560 Alcoholic beverages, merchant wholesalers 4248
4570 Farm supplies, merchant wholesalers 42491
4580 Miscellaneous nondurable goods, merchant wholesalers 4249 exc.
42491
4585 Wholesale electronic markets, agents and
okers 4251
4590 Not specified wholesale trade Part of 42

CODE DESCRIPTION INDUSTRY CODE

INDUSTRY CLASSIFICATION A-5

Retail Trade

4670 Automobile dealers 4411
4680 Other motor vehicle dealers 4412
4690 Auto parts, accessories, and tire stores 4413
4770 Furniture and home furnishings stores 442
4780 Household appliance stores XXXXXXXXXX
4795 Radio, TV, and computer stores 443112,
44312
4870 Building material and supplies dealers 4441 exc.
44413
4880 Hardware stores 44413
4890 Lawn and garden equipment and supplies stores 4442
4970 Grocery stores 4451
4980 Specialty food stores 4452
4990 Beer, wine, and liquor stores 4453
5070
Answered 2 days After Dec 06, 2021

Solution

Mohd answered on Dec 09 2021
119 Votes
C9
C9
-
12/7/2021
# Import li
aries
li
ary(tidyverse)
li
ary(lspline)
li
ary(cowplot)
li
ary(huxtable)
li
ary(stargazer)
li
ary(modelsummary)
li
ary(readr)
li
ary(magrittr)
li
ary(dplyr)
li
ary(ggplot2)
li
ary(rmarkdown)
li
ary(skimr)
Topic 4
Chapter 09
CH09A Estimating gender and age differences in earnings
using the cps-earnings dataset
——————————————————————————————————
SET UP
It is advised to start a new session for every case study
CLEAR MEMORY
m(list=ls())
m(list=ls())
#import data
li
ary(readr)
data_all <- read_csv("~/data/morg-2014-emp.csv")
set working directory
#SELECT OCCUPATION # keep only two occupation types: Market research analysts and marketing specialists #and Computer and Mathematical Occupations
data_all <- data_all %>%
mutate(sample=ifelse(occ2012==0735,1,ifelse(data_all$occ2012>=1005 & data_all$occ2012<=1240,2,0)))
data_all<- data_all %>% filter(sample==1 | sample==2)
tabulate(data_all$sample)
## [1] 281 4740
#gen female variable
#gen wage variables
data_all <- data_all %>% mutate(female=as.numeric(sex==2)) %>%
mutate(w=earnwke/uhours) %>%
mutate(lnw=log(w)) %>%
mutate(agesq=age^2)
#SET SAMPLE - Choose one of the occupations!
#Market research analysts and marketing specialists -1
#Computer and Mathematical Occupations-2
i=1
subdata <- data_all %>% filter(sample==i)
write_csv(subdata, "earnings_inference.csv")
#DISTRIBUTION OF EARNINGS #######################
subdata %>% dplyr::select(earnwke,uhours,w) %>% summary()
## earnwke uhours w
## Min. : 40 Min. : 5.00 Min. : 7.25
## 1st Qu.: 700 1st Qu.:40.00 1st Qu.:17.79
## Median :1096 Median :40.00 Median :25.95
## Mean :1206 Mean :40.15 Mean :29.06
## 3rd Qu.:1538 3rd Qu.:40.00 3rd Qu.:37.02
## Max. :2885 Max. :80.00 Max. :84.60
subdata %>% filter(w>=1) %>% dplyr::select(earnwke,uhours,w) %>% summary()
## earnwke uhours w
## Min. : 40 Min. : 5.00 Min. : 7.25
## 1st Qu.: 700 1st Qu.:40.00 1st Qu.:17.79
## Median :1096 Median :40.00 Median :25.95
## Mean :1206 Mean :40.15 Mean :29.06
## 3rd Qu.:1538 3rd Qu.:40.00 3rd Qu.:37.02
## Max. :2885 Max. :80.00 Max. :84.60
tabulate(subdata$female)
## [1] 172
table(subdata$occ2012,subdata$female)
##
## 0 1
## 735 109 172
#linear regressions ##############################
First, look at them one by one
female binary
# plain SE
eg1<-lm(lnw~female,subdata)
summary(reg1)
##
## Call:
## lm(formula = lnw ~ female, data = subdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.23545 -0.36310 0.02556 0.35946 1.23611
##
## Coefficients:
## Estimate Std. E
or t value Pr(>|t|)
## (Intercept) 3.31489 0.04804 69.004 <2e-16 ***
## female -0.11306 0.06140 -1.841 0.0666 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard e
or: 0.5015 on 279 degrees of freedom
## Multiple R-squared: 0.01201, Adjusted R-squared: 0.008465
## F-statistic: 3.39 on 1 and 279 DF, p-value: 0.06664
# with robust SE (Stata) IT AS SOME PROBLEM DON'T RUN!
#install.packages("estimatr")
The model with lnw as dependent variable and female as independent variable was developed. we have F(1,279)=3.39 | P value >0.05...
SOLUTION.PDF

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