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# load the data set and get an overview
library(AER)## Loading required package: car## Loading required package: carData## Loading required package: lmtest## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric## Loading required package: sandwich## Loading required package: survivaldata("CigarettesSW")
library(tidyverse)## -- Attaching packages --------------------------------- tidyverse 1.2.1 --## v ggplot2 3.1.0 v purrr 0.2.5
## v tibble 2.1.3 v dplyr 0.8.3
## v tidyr 0.8.2 v stringr 1.3.1
## v readr 1.3.1 v forcats 0.3.0## Warning: package 'tibble' was built under R version 3.5.3## Warning: package 'dplyr' was built under R version 3.5.3## -- Conflicts ------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
## x dplyr::recode() masks car::recode()
## x purrr::some() masks car::some()CigarettesSW<-as.data.frame(CigarettesSW)
CigarettesSW## state year cpi population packs income tax price
## 1 AL 1985 1.076 3973000 116.48628 46014968 32.50000 102.18167
## 2 AR 1985 1.076 2327000 128.53459 26210736 37.00000 101.47500
## 3 AZ 1985 1.076 3184000 104.52261 43956936 31.00000 108.57875
## 4 CA 1985 1.076 26444000 100.36304 447102816 26.00000 107.83734
## 5 CO 1985 1.076 3209000 112.96354 49466672 31.00000 94.26666
## 6 CT 1985 1.076 3201000 109.27835 60063368 42.00000 128.02499
## 7 DE 1985 1.076 618000 143.85114 9927301 30.00000 102.49166
## 8 FL 1985 1.076 11352000 122.18112 166919248 37.00000 115.29000
## 9 GA 1985 1.076 5963000 127.23462 78364336 28.00000 97.02517
## 10 IA 1985 1.076 2830000 113.74558 37902896 34.00000 101.84200
## 11 ID 1985 1.076 994000 103.01811 11577261 25.10000 102.89933
## 12 IL 1985 1.076 11401000 123.20848 176786352 28.00001 104.44025
## 13 IN 1985 1.076 5460000 137.63737 71751616 26.50000 96.18000
## 14 KS 1985 1.076 2428000 116.68040 34784360 32.00000 98.92291
## 15 KY 1985 1.076 3695000 186.03519 42703144 19.00000 87.00125
## 16 LA 1985 1.076 4409000 127.55727 53431900 32.00000 108.39400
## 17 MA 1985 1.076 5881000 115.67760 98328688 42.00000 112.20834
## 18 MD 1985 1.076 4414000 120.97871 74851664 29.00000 91.96667
## 19 ME 1985 1.076 1163000 128.11694 14575292 36.00000 107.04750
## 20 MI 1985 1.076 9077000 128.00485 133728040 37.00000 104.91417
## 21 MN 1985 1.076 4185000 112.90323 63152360 34.00000 113.64967
## 22 MO 1985 1.076 5001000 130.37393 69341920 29.00000 99.33817
## 23 MS 1985 1.076 2588000 117.04018 25678534 27.58333 105.29333
## 24 MT 1985 1.076 822000 104.25790 9785230 32.00000 99.29166
## 25 NC 1985 1.076 6255000 155.28377 79104656 18.00000 84.96799
## 26 ND 1985 1.076 677000 105.46529 8672948 34.00000 106.80800
## 27 NE 1985 1.076 1585000 107.38171 21778072 34.00000 104.60667
## 28 NH 1985 1.076 997000 197.99399 15767469 33.00000 95.50000
## 29 NJ 1985 1.076 7566000 116.52128 133549208 41.00000 110.41666
## 30 NM 1985 1.076 1439000 88.74218 17258916 28.00000 102.77800
## 31 NV 1985 1.076 951000 141.95584 14581495 31.00000 114.18850
## 32 NY 1985 1.076 17794000 116.66292 297728512 37.00000 109.99783
## 33 OH 1985 1.076 10736000 127.59874 153455776 30.00000 100.42374
## 34 OK 1985 1.076 3272000 127.13937 43395580 34.00000 101.46808
## 35 OR 1985 1.076 2673000 119.45380 36205164 35.00000 97.03333
## 36 PA 1985 1.076 11772000 117.70303 170033840 34.00000 109.07401
## 37 RI 1985 1.076 967000 132.78178 14229156 39.00000 100.94167
## 38 SC 1985 1.076 3304000 127.20944 38536176 23.00000 90.64125
## 39 SD 1985 1.076 698000 106.59026 8340000 31.00000 97.08334
## 40 TN 1985 1.076 4716000 129.83459 57749668 29.00000 101.94550
## 41 TX 1985 1.076 16275000 115.10293 231003152 35.25000 107.38000
## 42 UT 1985 1.076 1643000 68.04626 19462380 28.00000 110.19584
## 43 VA 1985 1.076 5716000 134.00980 87361632 18.50000 91.61533
## 44 VT 1985 1.076 530000 145.28302 6887097 33.00000 100.98334
## 45 WA 1985 1.076 4401000 96.22813 64846548 39.00000 129.46109
## 46 WI 1985 1.076 4748000 107.87700 65732720 41.00000 114.59000
## 47 WV 1985 1.076 1907000 112.84740 20852964 33.00000 108.91125
## 48 WY 1985 1.076 500000 129.39999 7116756 24.00000 93.46667
## 49 AL 1995 1.524 4262731 101.08543 83903280 40.50000 158.37134
## 50 AR 1995 1.524 2480121 111.04297 45995496 55.50000 175.54251
## 51 AZ 1995 1.524 4306908 71.95417 88870496 65.33333 198.60750
## 52 CA 1995 1.524 31493524 56.85931 771470144 61.00000 210.50467
## 53 CO 1995 1.524 3738061 82.58292 92946544 44.00000 167.35001
## 54 CT 1995 1.524 3265293 79.47219 104315120 74.00000 218.28050
## 55 DE 1995 1.524 718265 124.46660 18237436 48.00000 165.60001
## 56 FL 1995 1.524 14185403 93.07455 333525344 57.90000 187.71718
## 57 GA 1995 1.524 7188538 97.47462 159800448 36.00000 156.57307
## 58 IA 1995 1.524 2840860 92.40160 60170928 60.00000 190.89000
## 59 ID 1995 1.524 1165000 74.84978 22868920 52.00000 179.63751
## 60 IL 1995 1.524 11884935 83.26508 304767456 68.00001 198.47617
## 61 IN 1995 1.524 5791819 134.25835 126525008 39.50000 154.53375
## 62 KS 1995 1.524 2586942 88.75344 56626672 48.00000 175.21001
## 63 KY 1995 1.524 3855248 172.64778 74079712 27.00000 145.97968
## 64 LA 1995 1.524 4327978 105.17613 84572688 44.00000 167.79535
## 65 MA 1995 1.524 6062335 76.62064 170051568 75.00000 217.10501
## 66 MD 1995 1.524 5023650 77.47355 135115456 60.00000 186.03375
## 67 ME 1995 1.524 1237438 102.46978 25045934 61.00000 197.23065
## 68 MI 1995 1.524 9659871 81.38825 231594240 99.00000 240.84967
## 69 MN 1995 1.524 4605445 82.94530 113216856 72.00000 220.34866
## 70 MO 1995 1.524 5324610 122.45028 117639672 41.00000 157.23009
## 71 MS 1995 1.524 2690788 105.58245 46241956 42.00000 169.22940
## 72 MT 1995 1.524 868522 87.15957 16296835 42.00000 156.21667
## 73 NC 1995 1.524 7185403 121.53806 157633568 29.00000 149.99400
## 74 ND 1995 1.524 641548 79.80697 12243384 68.00000 192.24867
## 75 NE 1995 1.524 1635142 87.27071 36293064 58.00000 182.17500
## 76 NH 1995 1.524 1145604 156.33675 28649564 49.00000 166.64166
## 77 NJ 1995 1.524 7965523 80.37137 233208576 64.00000 203.08717
## 78 NM 1995 1.524 1682417 64.66887 31716160 45.00000 176.14624
## 79 NV 1995 1.524 1525777 93.52612 39377292 59.00000 206.59917
## 80 NY 1995 1.524 18150928 70.81732 503163328 80.00000 221.85800
## 81 OH 1995 1.524 11155493 111.38010 255312928 48.00000 165.89125
## 82 OK 1995 1.524 3265547 108.68011 63333300 47.00000 170.13499
## 83 OR 1995 1.524 3141421 92.15575 71209312 62.00000 190.30000
## 84 PA 1995 1.524 12044780 95.64309 285923232 55.00000 176.16316
## 85 RI 1995 1.524 989203 92.59980 23786644 80.00000 224.45924
## 86 SC 1995 1.524 3699943 108.08275 72050072 31.00000 152.81874
## 87 SD 1995 1.524 728251 97.21923 14454129 47.00000 168.03799
## 88 TN 1995 1.524 5241168 122.32005 114259984 37.00000 167.06700
## 89 TX 1995 1.524 18679706 73.07931 402096768 65.00000 198.20233
## 90 UT 1995 1.524 1976774 49.27220 37278220 50.50000 180.97626
## 91 VA 1995 1.524 6601392 105.38687 161441792 26.50001 166.66125
## 92 VT 1995 1.524 582827 122.33475 12448607 44.00000 175.63875
## 93 WA 1995 1.524 5431024 65.53092 129680832 80.50000 239.10934
## 94 WI 1995 1.524 5137004 92.46635 115959680 62.00000 201.38126
## 95 WV 1995 1.524 1820560 115.56883 32611268 41.00000 166.51718
## 96 WY 1995 1.524 478447 112.23814 10293195 36.00000 158.54166
## taxs
## 1 33.34834
## 2 37.00000
## 3 36.17042
## 4 32.10400
## 5 31.00000
## 6 51.48333
## 7 30.00000
## 8 42.49000
## 9 28.84183
## 10 37.91700
## 11 29.05767
## 12 28.91526
## 13 31.08000
## 14 34.88125
## 15 23.14292
## 16 36.16900
## 17 42.00000
## 18 29.00000
## 19 41.09750
## 20 37.83083
## 21 40.43300
## 22 29.85484
## 23 33.54333
## 24 32.00000
## 25 21.26800
## 26 38.10800
## 27 38.02333
## 28 33.00000
## 29 41.00000
## 30 31.95300
## 31 37.46350
## 32 37.88117
## 33 34.78208
## 34 34.82642
## 35 35.00000
## 36 40.17400
## 37 39.00000
## 38 27.31625
## 39 31.00000
## 40 34.77050
## 41 39.38000
## 42 34.23750
## 43 22.02367
## 44 33.00000
## 45 47.46942
## 46 46.45667
## 47 38.18625
## 48 24.00000
## 49 41.90467
## 50 63.85917
## 51 74.79082
## 52 74.77133
## 53 44.00000
## 54 86.35550
## 55 48.00000
## 56 68.52551
## 57 37.43142
## 58 69.09000
## 59 60.55417
## 60 79.23450
## 61 46.85875
## 62 56.34333
## 63 35.26300
## 64 50.45367
## 65 85.33833
## 66 68.85875
## 67 72.16400
## 68 112.63300
## 69 86.41534
## 70 42.38842
## 71 53.07108
## 72 42.00000
## 73 34.76900
## 74 78.88200
## 75 66.67500
## 76 49.00000
## 77 75.49550
## 78 53.38792
## 79 72.51583
## 80 88.53300
## 81 55.89958
## 82 55.10167
## 83 62.00000
## 84 64.97150
## 85 94.68425
## 86 38.27708
## 87 53.46300
## 88 49.37533
## 89 76.21900
## 90 59.11792
## 91 34.43626
## 92 52.36375
## 93 96.14267
## 94 71.58958
## 95 50.42550
## 96 36.00000?CigarettesB ## Variable Description## starting httpd help server ...## doneYou can also embed plots, for example: Base R calc ##CigarettesSW\(rprice <- with(CigarettesSW, price / cpi) # compute the sales tax #CigarettesSW\)salestax <- with(CigarettesSW, (taxs - tax) / cpi) but we are doing using dplyr # check the correlation between sales tax and price cor(CigarettesSW\(salestax, CigarettesSW\)price) # generate a subset for the year 1995 c1995 <- subset(CigarettesSW, year == “1995”)
# compute real per capita prices
CigarettesSW<- CigarettesSW %>% mutate(rprice=price/cpi)
CigarettesSW<-CigarettesSW %>% mutate(salestax=(taxs-tax)/cpi)
CigarettesSW## state year cpi population packs income tax price
## 1 AL 1985 1.076 3973000 116.48628 46014968 32.50000 102.18167
## 2 AR 1985 1.076 2327000 128.53459 26210736 37.00000 101.47500
## 3 AZ 1985 1.076 3184000 104.52261 43956936 31.00000 108.57875
## 4 CA 1985 1.076 26444000 100.36304 447102816 26.00000 107.83734
## 5 CO 1985 1.076 3209000 112.96354 49466672 31.00000 94.26666
## 6 CT 1985 1.076 3201000 109.27835 60063368 42.00000 128.02499
## 7 DE 1985 1.076 618000 143.85114 9927301 30.00000 102.49166
## 8 FL 1985 1.076 11352000 122.18112 166919248 37.00000 115.29000
## 9 GA 1985 1.076 5963000 127.23462 78364336 28.00000 97.02517
## 10 IA 1985 1.076 2830000 113.74558 37902896 34.00000 101.84200
## 11 ID 1985 1.076 994000 103.01811 11577261 25.10000 102.89933
## 12 IL 1985 1.076 11401000 123.20848 176786352 28.00001 104.44025
## 13 IN 1985 1.076 5460000 137.63737 71751616 26.50000 96.18000
## 14 KS 1985 1.076 2428000 116.68040 34784360 32.00000 98.92291
## 15 KY 1985 1.076 3695000 186.03519 42703144 19.00000 87.00125
## 16 LA 1985 1.076 4409000 127.55727 53431900 32.00000 108.39400
## 17 MA 1985 1.076 5881000 115.67760 98328688 42.00000 112.20834
## 18 MD 1985 1.076 4414000 120.97871 74851664 29.00000 91.96667
## 19 ME 1985 1.076 1163000 128.11694 14575292 36.00000 107.04750
## 20 MI 1985 1.076 9077000 128.00485 133728040 37.00000 104.91417
## 21 MN 1985 1.076 4185000 112.90323 63152360 34.00000 113.64967
## 22 MO 1985 1.076 5001000 130.37393 69341920 29.00000 99.33817
## 23 MS 1985 1.076 2588000 117.04018 25678534 27.58333 105.29333
## 24 MT 1985 1.076 822000 104.25790 9785230 32.00000 99.29166
## 25 NC 1985 1.076 6255000 155.28377 79104656 18.00000 84.96799
## 26 ND 1985 1.076 677000 105.46529 8672948 34.00000 106.80800
## 27 NE 1985 1.076 1585000 107.38171 21778072 34.00000 104.60667
## 28 NH 1985 1.076 997000 197.99399 15767469 33.00000 95.50000
## 29 NJ 1985 1.076 7566000 116.52128 133549208 41.00000 110.41666
## 30 NM 1985 1.076 1439000 88.74218 17258916 28.00000 102.77800
## 31 NV 1985 1.076 951000 141.95584 14581495 31.00000 114.18850
## 32 NY 1985 1.076 17794000 116.66292 297728512 37.00000 109.99783
## 33 OH 1985 1.076 10736000 127.59874 153455776 30.00000 100.42374
## 34 OK 1985 1.076 3272000 127.13937 43395580 34.00000 101.46808
## 35 OR 1985 1.076 2673000 119.45380 36205164 35.00000 97.03333
## 36 PA 1985 1.076 11772000 117.70303 170033840 34.00000 109.07401
## 37 RI 1985 1.076 967000 132.78178 14229156 39.00000 100.94167
## 38 SC 1985 1.076 3304000 127.20944 38536176 23.00000 90.64125
## 39 SD 1985 1.076 698000 106.59026 8340000 31.00000 97.08334
## 40 TN 1985 1.076 4716000 129.83459 57749668 29.00000 101.94550
## 41 TX 1985 1.076 16275000 115.10293 231003152 35.25000 107.38000
## 42 UT 1985 1.076 1643000 68.04626 19462380 28.00000 110.19584
## 43 VA 1985 1.076 5716000 134.00980 87361632 18.50000 91.61533
## 44 VT 1985 1.076 530000 145.28302 6887097 33.00000 100.98334
## 45 WA 1985 1.076 4401000 96.22813 64846548 39.00000 129.46109
## 46 WI 1985 1.076 4748000 107.87700 65732720 41.00000 114.59000
## 47 WV 1985 1.076 1907000 112.84740 20852964 33.00000 108.91125
## 48 WY 1985 1.076 500000 129.39999 7116756 24.00000 93.46667
## 49 AL 1995 1.524 4262731 101.08543 83903280 40.50000 158.37134
## 50 AR 1995 1.524 2480121 111.04297 45995496 55.50000 175.54251
## 51 AZ 1995 1.524 4306908 71.95417 88870496 65.33333 198.60750
## 52 CA 1995 1.524 31493524 56.85931 771470144 61.00000 210.50467
## 53 CO 1995 1.524 3738061 82.58292 92946544 44.00000 167.35001
## 54 CT 1995 1.524 3265293 79.47219 104315120 74.00000 218.28050
## 55 DE 1995 1.524 718265 124.46660 18237436 48.00000 165.60001
## 56 FL 1995 1.524 14185403 93.07455 333525344 57.90000 187.71718
## 57 GA 1995 1.524 7188538 97.47462 159800448 36.00000 156.57307
## 58 IA 1995 1.524 2840860 92.40160 60170928 60.00000 190.89000
## 59 ID 1995 1.524 1165000 74.84978 22868920 52.00000 179.63751
## 60 IL 1995 1.524 11884935 83.26508 304767456 68.00001 198.47617
## 61 IN 1995 1.524 5791819 134.25835 126525008 39.50000 154.53375
## 62 KS 1995 1.524 2586942 88.75344 56626672 48.00000 175.21001
## 63 KY 1995 1.524 3855248 172.64778 74079712 27.00000 145.97968
## 64 LA 1995 1.524 4327978 105.17613 84572688 44.00000 167.79535
## 65 MA 1995 1.524 6062335 76.62064 170051568 75.00000 217.10501
## 66 MD 1995 1.524 5023650 77.47355 135115456 60.00000 186.03375
## 67 ME 1995 1.524 1237438 102.46978 25045934 61.00000 197.23065
## 68 MI 1995 1.524 9659871 81.38825 231594240 99.00000 240.84967
## 69 MN 1995 1.524 4605445 82.94530 113216856 72.00000 220.34866
## 70 MO 1995 1.524 5324610 122.45028 117639672 41.00000 157.23009
## 71 MS 1995 1.524 2690788 105.58245 46241956 42.00000 169.22940
## 72 MT 1995 1.524 868522 87.15957 16296835 42.00000 156.21667
## 73 NC 1995 1.524 7185403 121.53806 157633568 29.00000 149.99400
## 74 ND 1995 1.524 641548 79.80697 12243384 68.00000 192.24867
## 75 NE 1995 1.524 1635142 87.27071 36293064 58.00000 182.17500
## 76 NH 1995 1.524 1145604 156.33675 28649564 49.00000 166.64166
## 77 NJ 1995 1.524 7965523 80.37137 233208576 64.00000 203.08717
## 78 NM 1995 1.524 1682417 64.66887 31716160 45.00000 176.14624
## 79 NV 1995 1.524 1525777 93.52612 39377292 59.00000 206.59917
## 80 NY 1995 1.524 18150928 70.81732 503163328 80.00000 221.85800
## 81 OH 1995 1.524 11155493 111.38010 255312928 48.00000 165.89125
## 82 OK 1995 1.524 3265547 108.68011 63333300 47.00000 170.13499
## 83 OR 1995 1.524 3141421 92.15575 71209312 62.00000 190.30000
## 84 PA 1995 1.524 12044780 95.64309 285923232 55.00000 176.16316
## 85 RI 1995 1.524 989203 92.59980 23786644 80.00000 224.45924
## 86 SC 1995 1.524 3699943 108.08275 72050072 31.00000 152.81874
## 87 SD 1995 1.524 728251 97.21923 14454129 47.00000 168.03799
## 88 TN 1995 1.524 5241168 122.32005 114259984 37.00000 167.06700
## 89 TX 1995 1.524 18679706 73.07931 402096768 65.00000 198.20233
## 90 UT 1995 1.524 1976774 49.27220 37278220 50.50000 180.97626
## 91 VA 1995 1.524 6601392 105.38687 161441792 26.50001 166.66125
## 92 VT 1995 1.524 582827 122.33475 12448607 44.00000 175.63875
## 93 WA 1995 1.524 5431024 65.53092 129680832 80.50000 239.10934
## 94 WI 1995 1.524 5137004 92.46635 115959680 62.00000 201.38126
## 95 WV 1995 1.524 1820560 115.56883 32611268 41.00000 166.51718
## 96 WY 1995 1.524 478447 112.23814 10293195 36.00000 158.54166
## taxs rprice salestax
## 1 33.34834 94.96438 0.7884121
## 2 37.00000 94.30762 0.0000000
## 3 36.17042 100.90962 4.8052211
## 4 32.10400 100.22058 5.6728627
## 5 31.00000 87.60842 0.0000000
## 6 51.48333 118.98234 8.8135073
## 7 30.00000 95.25248 0.0000000
## 8 42.49000 107.14684 5.1022322
## 9 28.84183 90.17209 0.7823728
## 10 37.91700 94.64870 3.6403345
## 11 29.05767 95.63135 3.6781287
## 12 28.91526 97.06344 0.8506048
## 13 31.08000 89.38662 4.2565056
## 14 34.88125 91.93579 2.6777403
## 15 23.14292 80.85618 3.8502953
## 16 36.16900 100.73792 3.8745342
## 17 42.00000 104.28284 0.0000000
## 18 29.00000 85.47088 0.0000000
## 19 41.09750 99.48653 4.7374535
## 20 37.83083 97.50388 0.7721501
## 21 40.43300 105.62237 5.9786234
## 22 29.85484 92.32172 0.7944550
## 23 33.54333 97.85626 5.5390327
## 24 32.00000 92.27850 0.0000000
## 25 21.26800 78.96654 3.0371745
## 26 38.10800 99.26394 3.8178455
## 27 38.02333 97.21809 3.7391585
## 28 33.00000 88.75465 0.0000000
## 29 41.00000 102.61772 0.0000000
## 30 31.95300 95.51859 3.6737911
## 31 37.46350 106.12314 6.0069713
## 32 37.88117 102.22846 0.8189297
## 33 34.78208 93.33062 4.4443139
## 34 34.82642 94.30119 0.7680446
## 35 35.00000 90.17968 0.0000000
## 36 40.17400 101.36990 5.7379181
## 37 39.00000 93.81196 0.0000000
## 38 27.31625 84.23908 4.0113847
## 39 31.00000 90.22615 0.0000000
## 40 34.77050 94.74489 5.3629185
## 41 39.38000 99.79554 3.8382910
## 42 34.23750 102.41249 5.7969325
## 43 22.02367 85.14436 3.2747830
## 44 33.00000 93.85069 0.0000000
## 45 47.46942 120.31700 7.8712061
## 46 46.45667 106.49629 5.0712502
## 47 38.18625 101.21863 4.8199339
## 48 24.00000 86.86493 0.0000000
## 49 41.90467 103.91821 0.9216975
## 50 63.85917 115.18538 5.4850193
## 51 74.79082 130.31989 6.2057067
## 52 74.77133 138.12643 9.0363074
## 53 44.00000 109.80972 0.0000000
## 54 86.35550 143.22868 8.1072834
## 55 48.00000 108.66143 0.0000000
## 56 68.52551 123.17401 6.9721155
## 57 37.43142 102.73824 0.9392491
## 58 69.09000 125.25591 5.9645648
## 59 60.55417 117.87239 5.6129718
## 60 79.23450 130.23371 7.3717176
## 61 46.85875 101.40010 4.8285759
## 62 56.34333 114.96720 5.4746290
## 63 35.26300 95.78719 5.4219166
## 64 50.45367 110.10194 4.2346896
## 65 85.33833 142.45736 6.7836835
## 66 68.85875 122.06940 5.8128280
## 67 72.16400 129.41644 7.3254606
## 68 112.63300 158.03785 8.9455406
## 69 86.41534 144.58574 9.4588827
## 70 42.38842 103.16935 0.9110344
## 71 53.07108 111.04292 7.2644905
## 72 42.00000 102.50438 0.0000000
## 73 34.76900 98.42127 3.7854339
## 74 78.88200 126.14743 7.1404228
## 75 66.67500 119.53741 5.6922595
## 76 49.00000 109.34493 0.0000000
## 77 75.49550 133.25931 7.5429785
## 78 53.38792 115.58153 5.5038825
## 79 72.51583 135.56376 8.8686559
## 80 88.53300 145.57612 5.5990797
## 81 55.89958 108.85253 5.1834529
## 82 55.10167 111.63714 5.3160537
## 83 62.00000 124.86877 0.0000000
## 84 64.97150 115.59263 6.5429771
## 85 94.68425 147.28298 9.6353350
## 86 38.27708 100.27477 4.7749900
## 87 53.46300 110.26116 4.2408147
## 88 49.37533 109.62402 8.1202969
## 89 76.21900 130.05403 7.3615501
## 90 59.11792 118.75083 5.6548009
## 91 34.43626 109.35778 5.2075138
## 92 52.36375 115.24853 5.4880255
## 93 96.14267 156.89590 10.2642194
## 94 71.58958 132.13994 6.2923785
## 95 50.42550 109.26325 6.1847109
## 96 36.00000 104.02996 0.0000000cor(CigarettesSW$salestax,CigarettesSW$price)## [1] 0.6141228c1995<-CigarettesSW %>%
filter(year=="1995")Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
# perform the first stage regression
cig_s1 <- lm(log(rprice) ~ salestax, data = c1995)
coeftest(cig_s1, vcov = vcovHC, type = "HC1")##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.6165463 0.0289177 159.6444 < 2.2e-16 ***
## salestax 0.0307289 0.0048354 6.3549 8.489e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# inspect the R^2 of the first stage regressio
summary(cig_s1)$r.squared## [1] 0.4709961# store the predicted values
lcigp_pred <- cig_s1$fitted.values
# run the stage 2 regression
cig_s2<-lm(log(c1995$packs)~lcigp_pred)
coeftest(cig_s2,vcov=vcovHC)##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.71988 1.70304 5.7074 7.932e-07 ***
## lcigp_pred -1.08359 0.35563 -3.0469 0.003822 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1coeftest(cig_s2, vcov = vcovHC)##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.71988 1.70304 5.7074 7.932e-07 ***
## lcigp_pred -1.08359 0.35563 -3.0469 0.003822 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# perform TSLS using 'ivreg()'
#cig_ivreg <- ivreg(log(packs) ~ log(rprice) | salestax, data = c1995)
cig_ivreg<-ivreg(log(packs)~log(rprice)|salestax,data = c1995)
coeftest(cig_ivreg, vcov = vcovHC, type = "HC1")##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.71988 1.52832 6.3598 8.346e-08 ***
## log(rprice) -1.08359 0.31892 -3.3977 0.001411 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# add rincome to the dataset
CigarettesSW <- CigarettesSW %>% mutate(rincome=income / population / cpi)
c1995<-CigarettesSW %>% filter(year=="1995")
# estimate the model
cig_ivreg2 <- ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + salestax, data = c1995)
coeftest(cig_ivreg2, vcov = vcovHC, type = "HC1")##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.43066 1.25939 7.4883 1.935e-09 ***
## log(rprice) -1.14338 0.37230 -3.0711 0.003611 **
## log(rincome) 0.21452 0.31175 0.6881 0.494917
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# add cigtax to the data set
CigarettesSW<-CigarettesSW %>% mutate(cigtax=tax/cpi)
c1995<-CigarettesSW %>% filter(year=="1995")
# estimate the model
cig_ivreg3 <- ivreg(log(packs) ~ log(rprice) + log(rincome) |
log(rincome) + salestax + cigtax, data = c1995)
coeftest(cig_ivreg3, vcov = vcovHC, type = "HC1")##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.89496 0.95922 10.3157 1.947e-13 ***
## log(rprice) -1.27742 0.24961 -5.1177 6.211e-06 ***
## log(rincome) 0.28040 0.25389 1.1044 0.2753
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# subset data for year 1985
c1985 <- CigarettesSW %>% mutate(year == "1985")
# define differences in variables
packsdiff <- log(c1995$packs) - log(c1985$packs)
pricediff <- log(c1995$price/c1995$cpi) - log(c1985$price/c1985$cpi)
incomediff <- log(c1995$income/c1995$population/c1995$cpi) -
log(c1985$income/c1985$population/c1985$cpi)
salestaxdiff <- (c1995$taxs - c1995$tax)/c1995$cpi - (c1985$taxs - c1985$tax)/c1985$cpi
cigtaxdiff <- c1995$tax/c1995$cpi - c1985$tax/c1985$cpi
# estimate the three models
cig_ivreg_diff1 <- ivreg(packsdiff ~ pricediff + incomediff | incomediff + salestaxdiff)
cig_ivreg_diff2 <- ivreg(packsdiff ~ pricediff + incomediff | incomediff + cigtaxdiff)
cig_ivreg_diff3 <- ivreg(packsdiff ~ pricediff + incomediff | incomediff + salestaxdiff + cigtaxdiff)
# robust coefficient summary for 1.
coeftest(cig_ivreg_diff1, vcov = vcovHC, type = "HC1")##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0074733 0.0047300 -1.5800 0.1175
## pricediff -1.0639421 0.1716869 -6.1970 1.558e-08 ***
## incomediff -0.0406767 0.2506843 -0.1623 0.8715
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# gather robust standard errors in a list
rob_se <- list(sqrt(diag(vcovHC(cig_ivreg_diff1, type = "HC1"))),
sqrt(diag(vcovHC(cig_ivreg_diff2, type = "HC1"))),
sqrt(diag(vcovHC(cig_ivreg_diff3, type = "HC1"))))
library(stargazer)##
## Please cite as:## Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.2. https://CRAN.R-project.org/package=stargazer# generate table
stargazer(cig_ivreg_diff1, cig_ivreg_diff2,cig_ivreg_diff3,
header = FALSE,
type = "LaTex",
omit.table.layout = "n",
digits = 3,
column.labels = c("IV: salestax", "IV: cigtax", "IVs: salestax, cigtax"),
dep.var.labels.include = FALSE,
dep.var.caption = "Dependent Variable: 1985-1995 Difference in Log per Pack Price",
se = rob_se)