rr-package
easi package on R studio 4.0
the easi package (exact affine stone index model) is a bit old, but still useful for my purposes. Has anybody managed to install it on Rstudio 4 considering it was built on R 2.15.3? Thanks
Solution
I forked the github repository and updated the source code to fix the Error in class(ff) <- "formula" : attempt to set an attribute on NULL error @MarioF. The example from the vignette now runs to completion. I'm not certain that the answers are correct, as I don't have anything to compare them to, but based on the source code it looks fine to me. If you've run easi in the past, perhaps you could re-run it using this updated version and see if the results are the same.
You can install the updated easi package using devtools::install_github("https://github.com/jpmam1/easi", dependencies = TRUE), e.g.
devtools::install_github("https://github.com/jpmam1/easi", dependencies = TRUE)
#> Downloading GitHub repo jpmam1/easi@HEAD
#>
#> * checking for file ‘/private/var/folders/gf/3p_ynkts411bs238rtw3y0b40000gn/T/RtmpIVvyAO/remotes920f6a08f9/jpmam1-easi-1c90fed/DESCRIPTION’ ... OK
#> * preparing ‘easi’:
#> * checking DESCRIPTION meta-information ... OK
#> * checking for LF line-endings in source and make files and shell scripts
#> * checking for empty or unneeded directories
#> * building ‘easi_0.2.tar.gz’
library(easi)
data(hixdata)
#******* Budget shares Matrix ************
shares_HIX=hixdata[,2:10]
#******* price Matrix (in logarithms) ****
log.price_HIX=hixdata[,11:19]
#******* Demographic matrix **************
var.soc_HIX=hixdata[,21:25]
#******* logarithm of total expenditure **
#******* (here divised by a price index) *
log.exp_HIX=hixdata[,20]
#******* Estimation... *******************
est <- easi(shares=shares_HIX,log.price=log.price_HIX,
var.soc=var.soc_HIX,log.exp=log.exp_HIX)
#>
#> *** Please wait during the creation of final instruments... ***
#> iteration = 1
#> crit_test = 0.0132835
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Creation of final instruments successfully completed... ***
#>
#> *** Please wait during the estimation... ***
#> iteration = 1
#> crit_test = 0.000129
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Estimation successfully completed ***
#******* Coefficients ********************
coef(est)
#> Estimate Std. Error t value Pr(>|t|)
#> eq1_Constante 1.338565e-01 2.369823e-03 56.48376336 0.000000e+00
#> eq1_y^1 -6.191417e-02 4.024952e-03 -15.38258649 0.000000e+00
#> eq1_y^2 7.204632e-03 4.051263e-03 1.77836669 7.535151e-02
#> eq1_y^3 -5.431856e-03 4.554815e-03 -1.19255232 2.330521e-01
#> eq1_z1 1.271748e-03 8.724567e-05 14.57663475 0.000000e+00
#> eq1_z2 -1.132559e-02 1.965138e-03 -5.76325256 8.313371e-09
#> eq1_z3 1.792113e-02 2.234399e-03 8.02056136 1.110223e-15
#> eq1_z4 -6.937697e-05 3.847325e-04 -0.18032519 8.568982e-01
#> eq1_z5 1.138257e-02 2.681374e-03 4.24504945 2.190544e-05
#> eq1_ps1 1.589244e-03 2.153198e-02 0.07380854 9.411631e-01
#> eq1_ps2 1.999501e-02 1.821433e-02 1.09776281 2.723149e-01
#> eq1_ps3 1.204415e-02 1.194709e-02 1.00812378 3.134013e-01
#> eq1_ps4 -2.036881e-02 1.314895e-02 -1.54908326 1.213699e-01
#> eq1_ps5 6.430660e-02 1.789467e-02 3.59361758 3.265234e-04
#> eq1_ps6 2.736144e-03 1.342038e-02 0.20387973 8.384486e-01
#> eq1_ps7 -2.617399e-02 1.049025e-02 -2.49507691 1.259712e-02
#> eq1_ps8 -4.267075e-02 1.706035e-02 -2.50116548 1.238263e-02
#> eq2_Constante 1.007420e-01 2.336590e-03 43.11496556 0.000000e+00
#> eq2_y^1 3.902061e-02 3.836550e-03 10.17075381 0.000000e+00
#> eq2_y^2 -7.944056e-03 3.861890e-03 -2.05703858 3.968921e-02
#> eq2_y^3 -1.024568e-02 4.341767e-03 -2.35979428 1.829001e-02
#> eq2_z1 -4.310734e-04 8.314643e-05 -5.18450900 2.176728e-07
#> eq2_z2 -3.307872e-02 1.872796e-03 -17.66274360 0.000000e+00
#> eq2_z3 9.510982e-03 2.133540e-03 4.45784203 8.302140e-06
#> eq2_z4 -2.282785e-03 4.791944e-04 -4.76379778 1.906713e-06
#> eq2_z5 -1.336479e-02 2.558504e-03 -5.22367336 1.763154e-07
#> eq2_ps1 1.999501e-02 1.821433e-02 1.09776281 2.723149e-01
#> eq2_ps2 3.768766e-02 2.352883e-02 1.60176508 1.092157e-01
#> eq2_ps3 -7.950078e-03 1.317920e-02 -0.60322912 5.463598e-01
#> eq2_ps4 3.483069e-02 1.225491e-02 2.84218238 4.482930e-03
#> eq2_ps5 -6.409116e-02 2.007544e-02 -3.19251592 1.411520e-03
#> eq2_ps6 -6.061289e-02 1.550821e-02 -3.90843934 9.305247e-05
#> eq2_ps7 -3.616433e-03 1.076989e-02 -0.33579105 7.370303e-01
#> eq2_ps8 2.174694e-02 1.949804e-02 1.11533982 2.647118e-01
#> ...
# Summary
summary(est)
#>
#> systemfit results
#> method: 3SLS
#>
#> N DF SSR detRCov OLS-R2 McElroy-R2
#> system 38776 38668 158.669 0 0.280103 0.242627
#>
#> N DF SSR MSE RMSE R2 Adj R2
#> s1 4847 4830 21.64543 0.004481 0.066944 0.309899 0.307613
#> s2 4847 4830 19.65986 0.004070 0.063799 0.168230 0.165474
#> s3 4847 4830 51.76049 0.010716 0.103520 0.310185 0.307900
#> s4 4847 4830 7.97288 0.001651 0.040629 0.110327 0.107380
#> s5 4847 4830 11.03250 0.002284 0.047793 0.123788 0.120886
#> s6 4847 4830 11.22150 0.002323 0.048201 0.268442 0.266019
#> s7 4847 4830 16.20021 0.003354 0.057914 0.455128 0.453323
#> s8 4847 4830 19.17577 0.003970 0.063009 0.192375 0.189700
#>
#> The covariance matrix of the residuals used for estimation
#> eq1 eq2 eq3 eq4 eq5
#> eq1 4.47448e-03 -1.09828e-03 -0.00173277 -3.30061e-05 -2.67632e-04
#> eq2 -1.09828e-03 4.06524e-03 -0.00172840 -2.51369e-04 -4.33163e-04
#> eq3 -1.73277e-03 -1.72840e-03 0.01070944 -1.08355e-03 -1.10554e-03
#> eq4 -3.30061e-05 -2.51369e-04 -0.00108355 1.65633e-03 -3.00605e-05
#> eq5 -2.67632e-04 -4.33163e-04 -0.00110554 -3.00605e-05 2.28601e-03
#> eq6 -3.28393e-04 -1.06748e-05 -0.00142407 -1.18782e-04 -6.13193e-06
#> eq7 -3.86588e-04 -1.76507e-04 -0.00148981 -2.79601e-05 -3.26869e-04
#> eq8 -5.46867e-04 -3.79785e-04 -0.00173404 -1.71792e-04 -1.12276e-04
#> eq6 eq7 eq8
#> eq1 -3.28393e-04 -3.86588e-04 -0.000546867
#> eq2 -1.06748e-05 -1.76507e-04 -0.000379785
#> eq3 -1.42407e-03 -1.48981e-03 -0.001734042
#> eq4 -1.18782e-04 -2.79601e-05 -0.000171792
#> eq5 -6.13193e-06 -3.26869e-04 -0.000112276
#> eq6 2.32137e-03 -2.81616e-04 -0.000366797
#> eq7 -2.81616e-04 3.35286e-03 -0.000588504
#> eq8 -3.66797e-04 -5.88504e-04 0.003967409
#>
#> The covariance matrix of the residuals
#> eq1 eq2 eq3 eq4 eq5
#> eq1 0.004481456 -1.10511e-03 -0.00173530 -3.39720e-05 -2.68323e-04
#> eq2 -0.001105107 4.07036e-03 -0.00172900 -2.50759e-04 -4.37042e-04
#> eq3 -0.001735298 -1.72900e-03 0.01071646 -1.08676e-03 -1.09946e-03
#> eq4 -0.000033972 -2.50759e-04 -0.00108676 1.65070e-03 -3.02961e-05
#> eq5 -0.000268323 -4.37042e-04 -0.00109946 -3.02961e-05 2.28416e-03
#> eq6 -0.000328667 -5.49536e-06 -0.00143105 -1.14912e-04 -5.66993e-06
#> eq7 -0.000388075 -1.77368e-04 -0.00149217 -2.97562e-05 -3.25903e-04
#> eq8 -0.000545727 -3.78073e-04 -0.00173896 -1.71989e-04 -1.10871e-04
#> eq6 eq7 eq8
#> eq1 -3.28667e-04 -3.88075e-04 -0.000545727
#> eq2 -5.49536e-06 -1.77368e-04 -0.000378073
#> eq3 -1.43105e-03 -1.49217e-03 -0.001738959
#> eq4 -1.14912e-04 -2.97562e-05 -0.000171989
#> eq5 -5.66993e-06 -3.25903e-04 -0.000110871
#> eq6 2.32329e-03 -2.84649e-04 -0.000363633
#> eq7 -2.84649e-04 3.35408e-03 -0.000591536
#> eq8 -3.63633e-04 -5.91536e-04 0.003970139
#>
#> The correlations of the residuals
#> eq1 eq2 eq3 eq4 eq5 eq6
#> eq1 1.0000000 -0.25874870 -0.250403 -0.0124904 -0.08386578 -0.10185775
#> eq2 -0.2587487 1.00000000 -0.261789 -0.0967399 -0.14333193 -0.00178701
#> eq3 -0.2504027 -0.26178923 1.000000 -0.2583893 -0.22222295 -0.28679858
#> eq4 -0.0124904 -0.09673985 -0.258389 1.0000000 -0.01560230 -0.05867860
#> eq5 -0.0838658 -0.14333193 -0.222223 -0.0156023 1.00000000 -0.00246129
#> eq6 -0.1018577 -0.00178701 -0.286799 -0.0586786 -0.00246129 1.00000000
#> eq7 -0.1000967 -0.04800352 -0.248889 -0.0126461 -0.11774395 -0.10196952
#> eq8 -0.1293787 -0.09404945 -0.266600 -0.0671837 -0.03681726 -0.11973159
#> eq7 eq8
#> eq1 -0.1000967 -0.1293787
#> eq2 -0.0480035 -0.0940494
#> eq3 -0.2488887 -0.2666005
#> eq4 -0.0126461 -0.0671837
#> eq5 -0.1177440 -0.0368173
#> eq6 -0.1019695 -0.1197316
#> eq7 1.0000000 -0.1621032
#> eq8 -0.1621032 1.0000000
#>
#>
#> 3SLS estimates for 's1' (equation 1)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe638b791c8>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 1.33857e-01 2.36982e-03 56.48376 < 2.22e-16 ***
#> y^1 -6.19142e-02 4.02495e-03 -15.38259 < 2.22e-16 ***
#> y^2 7.20463e-03 4.05126e-03 1.77837 0.07535151 .
#> y^3 -5.43186e-03 4.55482e-03 -1.19255 0.23305207
#> z1 1.27175e-03 8.72457e-05 14.57663 < 2.22e-16 ***
#> z2 -1.13256e-02 1.96514e-03 -5.76325 8.3134e-09 ***
#> z3 1.79211e-02 2.23440e-03 8.02056 1.1102e-15 ***
#> z4 -6.93770e-05 3.84732e-04 -0.18033 0.85689823
#> z5 1.13826e-02 2.68137e-03 4.24505 2.1905e-05 ***
#> ps1 1.58924e-03 2.15320e-02 0.07381 0.94116312
#> ps2 1.99950e-02 1.82143e-02 1.09776 0.27231491
#> ps3 1.20441e-02 1.19471e-02 1.00812 0.31340135
#> ps4 -2.03688e-02 1.31489e-02 -1.54908 0.12136989
#> ps5 6.43066e-02 1.78947e-02 3.59362 0.00032652 ***
#> ps6 2.73614e-03 1.34204e-02 0.20388 0.83844856
#> ps7 -2.61740e-02 1.04903e-02 -2.49508 0.01259712 *
#> ps8 -4.26708e-02 1.70603e-02 -2.50117 0.01238263 *
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.066944 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 21.645434 MSE: 0.004481 Root MSE: 0.066944
#> Multiple R-Squared: 0.309899 Adjusted R-Squared: 0.307613
#>
#>
#> 3SLS estimates for 's2' (equation 2)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe638ab1510>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 1.00742e-01 2.33659e-03 43.11497 < 2.22e-16 ***
#> y^1 3.90206e-02 3.83655e-03 10.17075 < 2.22e-16 ***
#> y^2 -7.94406e-03 3.86189e-03 -2.05704 0.0396892 *
#> y^3 -1.02457e-02 4.34177e-03 -2.35979 0.0182900 *
#> z1 -4.31073e-04 8.31464e-05 -5.18451 2.1767e-07 ***
#> z2 -3.30787e-02 1.87280e-03 -17.66274 < 2.22e-16 ***
#> z3 9.51098e-03 2.13354e-03 4.45784 8.3021e-06 ***
#> z4 -2.28279e-03 4.79194e-04 -4.76380 1.9067e-06 ***
#> z5 -1.33648e-02 2.55850e-03 -5.22367 1.7632e-07 ***
#> ps1 1.99950e-02 1.82143e-02 1.09776 0.2723149
#> ps2 3.76877e-02 2.35288e-02 1.60177 0.1092157
#> ps3 -7.95008e-03 1.31792e-02 -0.60323 0.5463598
#> ps4 3.48307e-02 1.22549e-02 2.84218 0.0044829 **
#> ps5 -6.40912e-02 2.00754e-02 -3.19252 0.0014115 **
#> ps6 -6.06129e-02 1.55082e-02 -3.90844 9.3052e-05 ***
#> ps7 -3.61643e-03 1.07699e-02 -0.33579 0.7370303
#> ps8 2.17469e-02 1.94980e-02 1.11534 0.2647118
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.063799 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 19.659859 MSE: 0.00407 Root MSE: 0.063799
#> Multiple R-Squared: 0.16823 Adjusted R-Squared: 0.165474
#>
#>
#> 3SLS estimates for 's3' (equation 3)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe638a587f0>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 0.341632535 0.003138294 108.85932 < 2.22e-16 ***
#> y^1 -0.141730466 0.006225420 -22.76641 < 2.22e-16 ***
#> y^2 -0.044153992 0.006267277 -7.04516 1.8834e-12 ***
#> y^3 0.057029303 0.007045841 8.09404 4.4409e-16 ***
#> z1 0.000836942 0.000134738 6.21161 5.2978e-10 ***
#> z2 0.011815851 0.003038546 3.88865 0.00010097 ***
#> z3 0.034858317 0.003452690 10.09599 < 2.22e-16 ***
#> z4 0.003609541 0.000378017 9.54863 < 2.22e-16 ***
#> z5 0.013475472 0.004145172 3.25088 0.00115145 **
#> ps1 0.012044145 0.011947089 1.00812 0.31340135
#> ps2 -0.007950078 0.013179200 -0.60323 0.54635982
#> ps3 0.068069679 0.016510980 4.12269 3.7525e-05 ***
#> ps4 -0.012995886 0.008152114 -1.59417 0.11090531
#> ps5 0.023882356 0.013056226 1.82919 0.06737841 .
#> ps6 -0.024377790 0.009860607 -2.47224 0.01343120 *
#> ps7 -0.009473078 0.010789996 -0.87795 0.37997626
#> ps8 -0.024124565 0.013387121 -1.80207 0.07154175 .
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.10352 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 51.760485 MSE: 0.010716 Root MSE: 0.10352
#> Multiple R-Squared: 0.310185 Adjusted R-Squared: 0.3079
#>
#>
#> 3SLS estimates for 's4' (equation 4)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe6389fe748>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 4.84964e-02 1.50619e-03 32.19806 < 2.22e-16 ***
#> y^1 7.27329e-03 2.44900e-03 2.96991 0.00298074 **
#> y^2 1.08792e-02 2.46514e-03 4.41322 1.0212e-05 ***
#> y^3 -8.20989e-03 2.77139e-03 -2.96237 0.00305468 **
#> z1 -1.62026e-04 5.31058e-05 -3.05099 0.00228241 **
#> z2 1.77838e-02 1.19562e-03 14.87405 < 2.22e-16 ***
#> z3 9.06894e-03 1.36008e-03 6.66796 2.6286e-11 ***
#> z4 5.12632e-04 2.85747e-04 1.79401 0.07281928 .
#> z5 5.72461e-03 1.63275e-03 3.50611 0.00045522 ***
#> ps1 -2.03688e-02 1.31489e-02 -1.54908 0.12136989
#> ps2 3.48307e-02 1.22549e-02 2.84218 0.00448293 **
#> ps3 -1.29959e-02 8.15211e-03 -1.59417 0.11090531
#> ps4 4.33578e-02 1.21347e-02 3.57306 0.00035326 ***
#> ps5 -2.76387e-02 1.38733e-02 -1.99222 0.04635406 *
#> ps6 -9.33810e-03 1.05280e-02 -0.88698 0.37509727
#> ps7 -2.86846e-02 7.62226e-03 -3.76326 0.00016796 ***
#> ps8 3.11561e-02 1.28851e-02 2.41798 0.01561134 *
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.040629 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 7.972878 MSE: 0.001651 Root MSE: 0.040629
#> Multiple R-Squared: 0.110327 Adjusted R-Squared: 0.10738
#>
#>
#> 3SLS estimates for 's5' (equation 5)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe6389a95f0>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 3.28683e-02 1.91029e-03 17.20593 < 2.22e-16 ***
#> y^1 4.47148e-02 2.87743e-03 15.53986 < 2.22e-16 ***
#> y^2 1.60626e-02 2.89648e-03 5.54554 2.9495e-08 ***
#> y^3 -5.28537e-03 3.25613e-03 -1.62321 0.10455363
#> z1 -9.75294e-05 6.23902e-05 -1.56322 0.11800985
#> z2 1.00156e-02 1.40536e-03 7.12672 1.0458e-12 ***
#> z3 7.99729e-03 1.59900e-03 5.00143 5.7156e-07 ***
#> z4 1.83941e-04 6.53334e-04 0.28154 0.77829675
#> z5 1.50144e-03 1.91974e-03 0.78211 0.43415734
#> ps1 6.43066e-02 1.78947e-02 3.59362 0.00032652 ***
#> ps2 -6.40912e-02 2.00754e-02 -3.19252 0.00141152 **
#> ps3 2.38824e-02 1.30562e-02 1.82919 0.06737841 .
#> ps4 -2.76387e-02 1.38733e-02 -1.99222 0.04635406 *
#> ps5 -1.35335e-02 3.82061e-02 -0.35422 0.72317415
#> ps6 2.73453e-02 1.72358e-02 1.58654 0.11262429
#> ps7 -1.29348e-02 9.80867e-03 -1.31872 0.18727197
#> ps8 -1.21020e-02 3.03183e-02 -0.39916 0.68977392
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.047793 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 11.032503 MSE: 0.002284 Root MSE: 0.047793
#> Multiple R-Squared: 0.123788 Adjusted R-Squared: 0.120886
#>
#>
#> 3SLS estimates for 's6' (equation 6)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe638950a90>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 6.80334e-02 1.79089e-03 37.98871 < 2.22e-16 ***
#> y^1 5.36278e-02 2.89953e-03 18.49537 < 2.22e-16 ***
#> y^2 2.08672e-02 2.91840e-03 7.15022 8.8174e-13 ***
#> y^3 -5.14651e-03 3.28118e-03 -1.56850 0.11677353
#> z1 -3.88915e-04 6.28457e-05 -6.18842 6.1380e-10 ***
#> z2 2.64340e-02 1.41533e-03 18.67694 < 2.22e-16 ***
#> z3 1.12155e-02 1.61008e-03 6.96578 3.3182e-12 ***
#> z4 -9.50025e-04 3.64889e-04 -2.60360 0.00922851 **
#> z5 -8.57483e-03 1.93257e-03 -4.43702 9.1466e-06 ***
#> ps1 2.73614e-03 1.34204e-02 0.20388 0.83844856
#> ps2 -6.06129e-02 1.55082e-02 -3.90844 9.3052e-05 ***
#> ps3 -2.43778e-02 9.86061e-03 -2.47224 0.01343120 *
#> ps4 -9.33810e-03 1.05280e-02 -0.88698 0.37509727
#> ps5 2.73453e-02 1.72358e-02 1.58654 0.11262429
#> ps6 6.03096e-02 1.73455e-02 3.47695 0.00050771 ***
#> ps7 3.42362e-02 8.49490e-03 4.03020 5.5835e-05 ***
#> ps8 2.31777e-02 1.72462e-02 1.34393 0.17897735
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.048201 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 11.221504 MSE: 0.002323 Root MSE: 0.048201
#> Multiple R-Squared: 0.268442 Adjusted R-Squared: 0.266019
#>
#>
#> 3SLS estimates for 's7' (equation 7)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe6388f7d60>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 1.70753e-01 2.02047e-03 84.51116 < 2.22e-16 ***
#> y^1 -1.48181e-02 3.48399e-03 -4.25320 2.1123e-05 ***
#> y^2 -2.28009e-02 3.50664e-03 -6.50221 8.0113e-11 ***
#> y^3 -2.47867e-03 3.94290e-03 -0.62864 0.52958738
#> z1 -1.73485e-04 7.54648e-05 -2.29888 0.02151685 *
#> z2 -1.28792e-02 1.70036e-03 -7.57438 3.6859e-14 ***
#> z3 -1.04241e-01 1.93289e-03 -53.92997 < 2.22e-16 ***
#> z4 -7.13305e-04 2.98228e-04 -2.39181 0.01677046 *
#> z5 -8.31338e-03 2.31990e-03 -3.58350 0.00033944 ***
#> ps1 -2.61740e-02 1.04903e-02 -2.49508 0.01259712 *
#> ps2 -3.61643e-03 1.07699e-02 -0.33579 0.73703026
#> ps3 -9.47308e-03 1.07900e-02 -0.87795 0.37997626
#> ps4 -2.86846e-02 7.62226e-03 -3.76326 0.00016796 ***
#> ps5 -1.29348e-02 9.80867e-03 -1.31872 0.18727197
#> ps6 3.42362e-02 8.49490e-03 4.03020 5.5835e-05 ***
#> ps7 4.26305e-02 1.15967e-02 3.67608 0.00023716 ***
#> ps8 -4.02475e-03 1.03864e-02 -0.38750 0.69838808
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.057914 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 16.200205 MSE: 0.003354 Root MSE: 0.057914
#> Multiple R-Squared: 0.455128 Adjusted R-Squared: 0.453323
#>
#>
#> 3SLS estimates for 's8' (equation 8)
#> Model Formula: ~+Constante + y^1 + y^2 + y^3 + z1 + z2 + z3 + z4 + z5 + ps1 +
#> ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8
#> <environment: 0x7fe63889fbd8>
#> Instruments: [1] "~ + z1 + z2 + z3 + z4 + z5 + ps1 + ps2 + ps3 + ps4 + ps5 + ps6 + ps7 + ps8 + inst_y^1 + inst_y^2 + inst_y^3"
#>
#> Estimate Std. Error t value Pr(>|t|)
#> Constante 8.30862e-02 2.24518e-03 37.00645 < 2.22e-16 ***
#> y^1 6.77452e-02 3.79020e-03 17.87379 < 2.22e-16 ***
#> y^2 2.06887e-02 3.81507e-03 5.42288 5.8997e-08 ***
#> y^3 -1.35795e-02 4.28911e-03 -3.16605 0.0015465 **
#> z1 -7.79162e-04 8.21321e-05 -9.48669 < 2.22e-16 ***
#> z2 -2.54823e-02 1.85051e-03 -13.77045 < 2.22e-16 ***
#> z3 1.02558e-02 2.10396e-03 4.87451 1.0951e-06 ***
#> z4 3.40386e-04 5.87519e-04 0.57936 0.5623482
#> z5 -7.86386e-04 2.52459e-03 -0.31149 0.7554293
#> ps1 -4.26708e-02 1.70603e-02 -2.50117 0.0123826 *
#> ps2 2.17469e-02 1.94980e-02 1.11534 0.2647118
#> ps3 -2.41246e-02 1.33871e-02 -1.80207 0.0715418 .
#> ps4 3.11561e-02 1.28851e-02 2.41798 0.0156113 *
#> ps5 -1.21020e-02 3.03183e-02 -0.39916 0.6897739
#> ps6 2.31777e-02 1.72462e-02 1.34393 0.1789773
#> ps7 -4.02475e-03 1.03864e-02 -0.38750 0.6983881
#> ps8 -1.02249e-02 2.98625e-02 -0.34240 0.7320531
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.063009 on 4830 degrees of freedom
#> Number of observations: 4847 Degrees of Freedom: 4830
#> SSR: 19.175769 MSE: 0.00397 Root MSE: 0.063009
#> Multiple R-Squared: 0.192375 Adjusted R-Squared: 0.1897
# fitted values
head(predict(est))
#> s1 s2 s3 s4 s5 s6
#> [1,] 0.3148521 0.007088799 0.2718483 0.10431671 0.04797565 0.12398362
#> [2,] 0.2815752 0.007296639 0.3765217 0.07960349 0.03833235 0.11151020
#> [3,] 0.2159977 0.068854341 0.3748992 0.04737345 0.03658791 0.09920668
#> [4,] 0.2333557 0.069060035 0.3759948 0.04441345 0.02861974 0.09857289
#> [5,] 0.1253354 0.103084623 0.2460621 0.03725748 0.04965151 0.12915065
#> [6,] 0.2247643 0.075434197 0.3746137 0.03903780 0.03360408 0.10165050
#> s7 s8
#> [1,] 0.03439408 0.04200202
#> [2,] 0.04535731 0.01645048
#> [3,] 0.07163017 0.06119997
#> [4,] 0.07645149 0.04879235
#> [5,] 0.18377317 0.09936264
#> [6,] 0.07717741 0.04963816
# Residuals
head(residuals(est))
#> s1 s2 s3 s4 s5 s6
#> 1 0.19184705 -0.007088799 0.09355974 -0.094572495 0.01048964 -0.0764805708
#> 2 -0.02243903 -0.007296639 0.22148493 -0.007344349 -0.03833235 -0.0699819603
#> 3 0.23676673 -0.036203058 -0.08060230 -0.031265482 -0.03658791 -0.0099598331
#> 4 0.02755754 -0.058021400 -0.14117293 -0.014308084 -0.01557408 0.1026313179
#> 5 -0.11269960 0.092265383 0.02687199 0.013538576 -0.02791788 0.0275337059
#> 6 0.00672091 -0.014730029 -0.08201964 -0.007066936 -0.03319938 -0.0008815854
#> s7 s8
#> 1 -0.030740001 -0.0383479352
#> 2 -0.045357306 -0.0006697501
#> 3 0.016745977 -0.0524929638
#> 4 -0.040826807 0.1499030874
#> 5 0.055044122 -0.0708056495
#> 6 0.008617811 0.1219522859
# Covariance Matrix
dim(vcov(est))
#> [1] 136 136
Created on 2022-07-29 by the reprex package (v2.0.1)
Update 05-JUN-2023
Fixed several bugs in the engel() function @Prasanna S; if you reinstall the package, it should now work as expected:
# reinstall the updated package
remotes::install_github("jpmam1/easi", force = TRUE)
#> Downloading GitHub repo jpmam1/easi@HEAD
#>
#> ── R CMD build ─────────────────────────────────────────────────────────────────
#> * checking for file ‘/private/var/folders/gf/3p_ynkts411bs238rtw3y0b40000gn/T/Rtmp5uN9An/remotes5734e908d92/jpmam1-easi-26fc918/DESCRIPTION’ ... OK
#> * preparing ‘easi’:
#> * checking DESCRIPTION meta-information ... OK
#> * checking for LF line-endings in source and make files and shell scripts
#> * checking for empty or unneeded directories
#> * building ‘easi_0.2.tar.gz’
library(easi)
easi::hixdemo()
#>
#> *** Please wait during the creation of final instruments... ***
#> iteration = 1
#> crit_test = 0.0132835
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Creation of final instruments successfully completed... ***
#>
#> *** Please wait during the estimation... ***
#> iteration = 1
#> crit_test = 0.000129
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Estimation successfully completed ***
#>
#> systemfit results
#> method:
#>
#> Coefficients:
#> NULL
shares_HIX=hixdata[,2:10]
log.price_HIX=hixdata[,11:19]
var.soc_HIX=hixdata[,21:25]
log.exp_HIX=hixdata[,20]
est <- easi(shares=shares_HIX,log.price=log.price_HIX,
var.soc=var.soc_HIX,log.exp=log.exp_HIX)
#>
#> *** Please wait during the creation of final instruments... ***
#> iteration = 1
#> crit_test = 0.0132835
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Creation of final instruments successfully completed... ***
#>
#> *** Please wait during the estimation... ***
#> iteration = 1
#> crit_test = 0.000129
#> iteration = 2
#> crit_test = 0.0001305
#> iteration = 3
#> crit_test = 2e-06
#> iteration = 4
#> crit_test = 0
#>
#> *** Estimation successfully completed ***
engel(object = est, file = "graph_engels_curves", sd = FALSE)
Created on 2023-06-05 with reprex v2.0.2
- How to add axis text in ggplot2 including both a symbol and linebreak that is centered correctly
- Merging a Data Frame to each element in a List?
- Can you center a plot using R patchwork
- Checking if an r package is currently attached
- How to create an empty named specified column and position this column into a particular numbered position within the data frame in R
- R - calculate value by each seperate instance of a variable in a data frame
- Randomly Split a Graph into Mini Graphs
- svyby - how to call in different variables for by formula in a function?
- Fading Colors in a Graph
- Retain overlapping ellipses if the center is not overlapped
- When should .default be used over TRUE in dplyr::case_when
- Format ggplotly tick labels when class is POSIXct and update axis when zooming
- Mixing dplyr syntax and SQL in duckdb (dbplyr)
- Databricks: configure R to use custom CRAN mirror by default
- Recoding Multiple Likert-scale Columns at Once
- How to make an OpenMP parallel code to run serially by default?
- Draw ellipses around a point and select an ellipse if they overlap
- execute all R chunks at once from an Rmd document
- How to scrape hierarchical web data into tabular format using rvest?
- How to find R_HOME with VBA Environ
- Subtract the previous number when another row is not NA in R
- Calculating mean of multiple matrices
- Overlaying a line plot over a stacked bar plot with dual y axis
- Scale Quarto PDF table output to fit page
- Passing values from indexed vector into manually-entered labels in ggplot
- Tail recursion on R Statistical Environment
- Specify ellipsis arguments as one object
- Splitting R string based on multiple criteria (data does not have a simple delineation like spaces or comma to separate by)
- Error in tbl_continuous() in gtsummary when using themes
- aggregate sf spatial dataframe values