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Output R Data Panel Shellen Model 1

Aug 12th, 2021
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  1. Restarting R session...
  2.  
  3. > Panel <- read.csv("C:/Users/betau/OneDrive/Documents/Data Shellen Persamaan 1.csv")
  4. > View(data)
  5. > Panel <- read.csv("C:/Users/betau/OneDrive/Documents/Data Shellen Persamaan 1.csv")
  6. > View(data)
  7. > View(Panel)
  8. > str(Panel)
  9. 'data.frame':   140 obs. of  23 variables:
  10.  $ ï..Kabupaten.Kota                   : chr  "Merauke" "Merauke" "Merauke" "Merauke" ...
  11.  $ Tahun                               : int  2014 2015 2016 2017 2018 2014 2015 2016 2017 2018 ...
  12.  $ kab.kota                            : int  1 1 1 1 1 2 2 2 2 2 ...
  13.  $ tahun                               : int  1 2 3 4 5 1 2 3 4 5 ...
  14.  $ lnPAD                               : num  4.94 4.98 5.11 5.08 4.94 4.14 4.31 4.25 4.33 4.33 ...
  15.  $ lnDAU                               : num  7.06 7.1 7.12 7.14 7.11 6.41 6.46 6.57 6.59 6.57 ...
  16.  $ lnDAK                               : num  5.27 5.68 5.17 5.23 5.72 4.82 5.34 5.56 5.11 5.43 ...
  17.  $ lnDOK                               : num  4.63 4.63 4.63 4.63 4.63 4.96 4.76 4.76 4.76 4.76 ...
  18.  $ lnBM                                : num  6.27 6.49 5.74 6.08 6.14 5.68 6.16 5.92 5.87 5.65 ...
  19.  $ lnPDRB                              : num  8.88 8.94 9.02 9.09 9.17 8.2 8.26 8.3 8.36 8.42 ...
  20.  $ PAD..dlm.miliar.                    : num  139 146 166 161 140 ...
  21.  $ DAU..dlm.miliar.                    : num  1161 1216 1233 1257 1220 ...
  22.  $ DAK..dlm.miliar.                    : num  194 292 177 186 306 ...
  23.  $ Dana.Otsus..dlm.miliar.             : num  103 103 103 103 103 ...
  24.  $ Belanja.Modal..dlm.miliar.          : num  529 658 312 439 462 ...
  25.  $ PDRB.atas.harga.konstan..dlm.miliar.: num  7169 7662 8249 8865 9584 ...
  26.  $ PAD                                 : num  1.39e+11 1.46e+11 1.66e+11 1.61e+11 1.40e+11 ...
  27.  $ DAU                                 : num  1.16e+12 1.22e+12 1.23e+12 1.26e+12 1.22e+12 ...
  28.  $ DAK                                 : num  1.94e+11 2.92e+11 1.77e+11 1.86e+11 3.06e+11 ...
  29.  $ Dana.Otsus                          : num  1.03e+11 1.03e+11 1.03e+11 1.03e+11 1.03e+11 ...
  30.  $ Belanja.Modal                       : num  5.29e+11 6.58e+11 3.12e+11 4.39e+11 4.62e+11 ...
  31.  $ PDRB.atas.harga.konstan..dlm.juta.  : num  7169283 7662491 8249368 8864810 9583662 ...
  32.  $ kemiskinan.t.1                      : num  11.1 11.1 10.8 10.5 10.3 ...
  33. > class(Panel)
  34. [1] "data.frame"
  35. > summary(Panel)
  36.  ï..Kabupaten.Kota      Tahun         kab.kota         tahun  
  37.  Length:140         Min.   :2014   Min.   : 1.00   Min.   :1  
  38.  Class :character   1st Qu.:2015   1st Qu.: 7.75   1st Qu.:2  
  39.  Mode  :character   Median :2016   Median :14.50   Median :3  
  40.                     Mean   :2016   Mean   :14.50   Mean   :3  
  41.                     3rd Qu.:2017   3rd Qu.:21.25   3rd Qu.:4  
  42.                     Max.   :2018   Max.   :28.00   Max.   :5  
  43.      lnPAD           lnDAU          lnDAK           lnDOK      
  44.  Min.   :0.240   Min.   :6.01   Min.   :3.950   Min.   :4.460  
  45.  1st Qu.:2.453   1st Qu.:6.34   1st Qu.:4.710   1st Qu.:4.610  
  46.  Median :2.980   Median :6.46   Median :5.010   Median :4.660  
  47.  Mean   :3.173   Mean   :6.48   Mean   :4.978   Mean   :4.684  
  48.  3rd Qu.:3.830   3rd Qu.:6.61   3rd Qu.:5.247   3rd Qu.:4.750  
  49.  Max.   :5.840   Max.   :7.14   Max.   :5.750   Max.   :5.140  
  50.       lnBM           lnPDRB       PAD..dlm.miliar. DAU..dlm.miliar.
  51.  Min.   :3.820   Min.   : 6.310   Min.   :  1.27   Min.   : 405.6  
  52.  1st Qu.:5.390   1st Qu.: 6.680   1st Qu.: 11.59   1st Qu.: 566.8  
  53.  Median :5.675   Median : 7.200   Median : 19.74   Median : 639.9  
  54.  Mean   :5.648   Mean   : 7.550   Mean   : 45.69   Mean   : 668.4  
  55.  3rd Qu.:5.940   3rd Qu.: 8.065   3rd Qu.: 46.03   3rd Qu.: 740.4  
  56.  Max.   :6.710   Max.   :11.220   Max.   :342.13   Max.   :1257.4  
  57.  DAK..dlm.miliar. Dana.Otsus..dlm.miliar. Belanja.Modal..dlm.miliar.
  58.  Min.   : 52.06   Min.   : 86.51          Min.   : 45.53            
  59.  1st Qu.:111.12   1st Qu.:100.60          1st Qu.:219.49            
  60.  Median :150.24   Median :105.69          Median :290.91            
  61.  Mean   :156.38   Mean   :108.79          Mean   :307.53            
  62.  3rd Qu.:190.31   3rd Qu.:115.50          3rd Qu.:378.55            
  63.  Max.   :315.37   Max.   :171.14          Max.   :818.74            
  64.  PDRB.atas.harga.konstan..dlm.miliar.      PAD          
  65.  Min.   :  550.8                      Min.   :1.266e+09  
  66.  1st Qu.:  797.5                      1st Qu.:1.159e+10  
  67.  Median : 1340.4                      Median :1.974e+10  
  68.  Mean   : 4977.9                      Mean   :4.569e+10  
  69.  3rd Qu.: 3172.5                      3rd Qu.:4.603e+10  
  70.  Max.   :74249.7                      Max.   :3.421e+11  
  71.       DAU                 DAK              Dana.Otsus      
  72.  Min.   :4.056e+11   Min.   :5.206e+10   Min.   :8.651e+10  
  73.  1st Qu.:5.668e+11   1st Qu.:1.111e+11   1st Qu.:1.006e+11  
  74.  Median :6.399e+11   Median :1.502e+11   Median :1.057e+11  
  75.  Mean   :6.684e+11   Mean   :1.564e+11   Mean   :1.088e+11  
  76.  3rd Qu.:7.404e+11   3rd Qu.:1.903e+11   3rd Qu.:1.155e+11  
  77.  Max.   :1.257e+12   Max.   :3.154e+11   Max.   :1.711e+11  
  78.  Belanja.Modal       PDRB.atas.harga.konstan..dlm.juta. kemiskinan.t.1
  79.  Min.   :4.553e+10   Min.   :  550805                   Min.   :10.35  
  80.  1st Qu.:2.195e+11   1st Qu.:  797495                   1st Qu.:23.48  
  81.  Median :2.909e+11   Median : 1340423                   Median :30.57  
  82.  Mean   :3.075e+11   Mean   : 4977946                   Mean   :29.24  
  83.  3rd Qu.:3.786e+11   3rd Qu.: 3172476                   3rd Qu.:37.59  
  84.  Max.   :8.187e+11   Max.   :74249680                   Max.   :45.74  
  85. > library(plm)
  86. > model = lnPDRB ~ lnPAD + lnDAU + lnDAK + lnDOK + lnBM
  87. > pls1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="pooling")
  88. > summary(pls1)
  89. Pooling Model
  90.  
  91. Call:
  92. plm(formula = model, data = Panel, model = "pooling", index = c("ï..Kabupaten.Kota",
  93.     "Tahun"))
  94.  
  95. Balanced Panel: n = 28, T = 5, N = 140
  96.  
  97. Residuals:
  98.      Min.   1st Qu.    Median   3rd Qu.      Max.
  99. -2.024444 -0.324724  0.034791  0.342125  1.472272
  100.  
  101. Coefficients:
  102.              Estimate Std. Error t-value  Pr(>|t|)    
  103. (Intercept) 16.673475   2.621483  6.3603  2.94e-09 ***
  104. lnPAD        0.856225   0.055384 15.4597 < 2.2e-16 ***
  105. lnDAU       -0.268246   0.286485 -0.9363 0.3507863    
  106. lnDAK       -0.074029   0.154251 -0.4799 0.6320623    
  107. lnDOK       -1.882617   0.533979 -3.5256 0.0005788 ***
  108. lnBM        -0.162223   0.146989 -1.1036 0.2717286    
  109. ---
  110. Signif. codes:  0***0.001**0.01*0.05 ‘.’ 0.1 ‘ ’ 1
  111.  
  112. Total Sum of Squares:    175.81
  113. Residual Sum of Squares: 52.973
  114. R-Squared:      0.69869
  115. Adj. R-Squared: 0.68745
  116. F-statistic: 62.1447 on 5 and 134 DF, p-value: < 2.22e-16
  117. > fem1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="within")
  118. > summary(fem1)
  119. Oneway (individual) effect Within Model
  120.  
  121. Call:
  122. plm(formula = model, data = Panel, model = "within", index = c("ï..Kabupaten.Kota",
  123.     "Tahun"))
  124.  
  125. Balanced Panel: n = 28, T = 5, N = 140
  126.  
  127. Residuals:
  128.       Min.    1st Qu.     Median    3rd Qu.       Max.
  129. -0.1769784 -0.0341254 -0.0021206  0.0317282  0.1678521
  130.  
  131. Coefficients:
  132.         Estimate Std. Error t-value  Pr(>|t|)    
  133. lnPAD -0.0040548  0.0129684 -0.3127  0.755144    
  134. lnDAU  1.1263201  0.1230779  9.1513 4.243e-15 ***
  135. lnDAK  0.0480050  0.0211373  2.2711  0.025143 *  
  136. lnDOK  0.0612013  0.0967789  0.6324  0.528486    
  137. lnBM  -0.0802444  0.0220876 -3.6330  0.000432 ***
  138. ---
  139. Signif. codes:  0***0.001**0.01*0.05 ‘.’ 0.1 ‘ ’ 1
  140.  
  141. Total Sum of Squares:    1.0632
  142. Residual Sum of Squares: 0.38151
  143. R-Squared:      0.64116
  144. Adj. R-Squared: 0.53384
  145. F-statistic: 38.2362 on 5 and 107 DF, p-value: < 2.22e-16
  146. > rem1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="random")
  147. > summary(rem1)
  148. Oneway (individual) effect Random Effect Model
  149.    (Swamy-Arora's transformation)
  150.  
  151. Call:
  152. plm(formula = model, data = Panel, model = "random", index = c("ï..Kabupaten.Kota",
  153.    "Tahun"))
  154.  
  155. Balanced Panel: n = 28, T = 5, N = 140
  156.  
  157. Effects:
  158.                   var  std.dev share
  159. idiosyncratic 0.003565 0.059712 0.012
  160. individual    0.290374 0.538863 0.988
  161. theta: 0.9505
  162.  
  163. Residuals:
  164.      Min.    1st Qu.     Median    3rd Qu.       Max.
  165. -0.1374105 -0.0549282 -0.0048105  0.0426738  0.3465637
  166.  
  167. Coefficients:
  168.             Estimate Std. Error z-value Pr(>|z|)    
  169. (Intercept)  0.421187   1.228833  0.3428 0.731784    
  170. lnPAD        0.010017   0.016584  0.6040 0.545821    
  171. lnDAU        1.115347   0.153500  7.2661  3.7e-13 ***
  172. lnDAK        0.044897   0.026927  1.6674 0.095443 .  
  173. lnDOK        0.023345   0.124012  0.1882 0.850683    
  174. lnBM        -0.082010   0.028283 -2.8997 0.003736 **
  175. ---
  176. Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  177.  
  178. Total Sum of Squares:    1.4912
  179. Residual Sum of Squares: 0.79352
  180. R-Squared:      0.46788
  181. Adj. R-Squared: 0.44803
  182. Chisq: 117.824 on 5 DF, p-value: < 2.22e-16
  183. > # Uji Haussman, jika signifikan maka fem lebih baik
  184. > phtest(fem1, rem1)
  185.  
  186.     Hausman Test
  187.  
  188. data:  model
  189. chisq = 2.0743, df = 5, p-value = 0.8388
  190. alternative hypothesis: one model is inconsistent
  191.  
  192. > plmtest(pls1, type="bp")
  193.  
  194.     Lagrange Multiplier Test - (Breusch-Pagan) for balanced panels
  195.  
  196. data:  model
  197. chisq = 94.5, df = 1, p-value < 2.2e-16
  198. alternative hypothesis: significant effects
  199.  
  200. > # ujia Heterokedastistas
  201. > library(lmtest)
  202. Loading required package: zoo
  203.  
  204. Attaching package: ‘zoo’
  205.  
  206. The following objects are masked from ‘package:base’:
  207.  
  208.    as.Date, as.Date.numeric
  209.  
  210. > install.packages(zoo)
  211. Error in install.packages : 'match' requires vector arguments
  212. > install.packages('zoo')
  213. Error in install.packages : Updating loaded packages
  214.  
  215. Restarting R session...
  216.  
  217. > install.packages("zoo")
  218. WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:
  219.  
  220. https://cran.rstudio.com/bin/windows/Rtools/
  221. Installing package into ‘C:/Users/betau/Documents/R/win-library/4.1’
  222. (as ‘lib’ is unspecified)
  223. trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.1/zoo_1.8-9.zip'
  224. Content type 'application/zip' length 1038767 bytes (1014 KB)
  225. downloaded 1014 KB
  226.  
  227. package ‘zoo’ successfully unpacked and MD5 sums checked
  228.  
  229. The downloaded binary packages are in
  230.     C:\Users\betau\AppData\Local\Temp\RtmpsDcFiY\downloaded_packages
  231. > # ujia Heterokedastistas
  232. > library(lmtest)
  233. Loading required package: zoo
  234.  
  235. Attaching package: ‘zoo’
  236.  
  237. The following objects are masked from ‘package:base’:
  238.  
  239.    as.Date, as.Date.numeric
  240.  
  241. > bptest(rem1)
  242. Error in x$terms %||% attr(x, "terms") %||% stop("no terms component nor attribute") :
  243.  no terms component nor attribute
  244. > # ujia Heterokedastistas
  245. > library(lmtest)
  246. > bptest(rem1)
  247. Error in x$terms %||% attr(x, "terms") %||% stop("no terms component nor attribute") :
  248.  no terms component nor attribute
  249. > # uji korelasi
  250. > pbgtest(rem1)
  251. Error in pbgtest(rem1) : could not find function "pbgtest"
  252. > # penanganan dengan robust covarian
  253. > coeftest(rem1, vcovHC(rem1, "arellano"))
  254. Error in vcovHC(rem1, "arellano") : could not find function "vcovHC"
  255. >
  256. > fem1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="within")
  257. Error in plm(model, data = Panel, index = c("ï..Kabupaten.Kota", "Tahun"),  :
  258.  could not find function "plm"
  259. > summary(fem1)
  260.             Length Class       Mode  
  261. coefficients   5    -none-      numeric
  262. vcov          25    -none-      numeric
  263. residuals    140    pseries     numeric
  264. df.residual    1    -none-      numeric
  265. formula        3    Formula     call  
  266. model          6    pdata.frame list  
  267. assign         6    -none-      numeric
  268. args           6    -none-      list  
  269. aliased        5    -none-      logical
  270. call           5    -none-      call  
  271.  
  272. Restarting R session...
  273.  
  274. > Panel <- read.csv("C:/Users/betau/OneDrive/Documents/Data Shellen Persamaan 1.csv")
  275. > View(Panel)
  276. > str(Panel)
  277. 'data.frame':   140 obs. of  23 variables:
  278. $ ï..Kabupaten.Kota                   : chr  "Merauke" "Merauke" "Merauke" "Merauke" ...
  279. $ Tahun                               : int  2014 2015 2016 2017 2018 2014 2015 2016 2017 2018 ...
  280. $ kab.kota                            : int  1 1 1 1 1 2 2 2 2 2 ...
  281. $ tahun                               : int  1 2 3 4 5 1 2 3 4 5 ...
  282. $ lnPAD                               : num  4.94 4.98 5.11 5.08 4.94 4.14 4.31 4.25 4.33 4.33 ...
  283. $ lnDAU                               : num  7.06 7.1 7.12 7.14 7.11 6.41 6.46 6.57 6.59 6.57 ...
  284. $ lnDAK                               : num  5.27 5.68 5.17 5.23 5.72 4.82 5.34 5.56 5.11 5.43 ...
  285. $ lnDOK                               : num  4.63 4.63 4.63 4.63 4.63 4.96 4.76 4.76 4.76 4.76 ...
  286. $ lnBM                                : num  6.27 6.49 5.74 6.08 6.14 5.68 6.16 5.92 5.87 5.65 ...
  287. $ lnPDRB                              : num  8.88 8.94 9.02 9.09 9.17 8.2 8.26 8.3 8.36 8.42 ...
  288. $ PAD..dlm.miliar.                    : num  139 146 166 161 140 ...
  289. $ DAU..dlm.miliar.                    : num  1161 1216 1233 1257 1220 ...
  290. $ DAK..dlm.miliar.                    : num  194 292 177 186 306 ...
  291. $ Dana.Otsus..dlm.miliar.             : num  103 103 103 103 103 ...
  292. $ Belanja.Modal..dlm.miliar.          : num  529 658 312 439 462 ...
  293. $ PDRB.atas.harga.konstan..dlm.miliar.: num  7169 7662 8249 8865 9584 ...
  294. $ PAD                                 : num  1.39e+11 1.46e+11 1.66e+11 1.61e+11 1.40e+11 ...
  295. $ DAU                                 : num  1.16e+12 1.22e+12 1.23e+12 1.26e+12 1.22e+12 ...
  296. $ DAK                                 : num  1.94e+11 2.92e+11 1.77e+11 1.86e+11 3.06e+11 ...
  297. $ Dana.Otsus                          : num  1.03e+11 1.03e+11 1.03e+11 1.03e+11 1.03e+11 ...
  298. $ Belanja.Modal                       : num  5.29e+11 6.58e+11 3.12e+11 4.39e+11 4.62e+11 ...
  299. $ PDRB.atas.harga.konstan..dlm.juta.  : num  7169283 7662491 8249368 8864810 9583662 ...
  300. $ kemiskinan.t.1                      : num  11.1 11.1 10.8 10.5 10.3 ...
  301. > class(Panel)
  302. [1] "data.frame"
  303. > summary(Panel)
  304. ï..Kabupaten.Kota      Tahun         kab.kota         tahun       lnPAD           lnDAU          lnDAK      
  305. Length:140         Min.   :2014   Min.   : 1.00   Min.   :1   Min.   :0.240   Min.   :6.01   Min.   :3.950  
  306. Class :character   1st Qu.:2015   1st Qu.: 7.75   1st Qu.:2   1st Qu.:2.453   1st Qu.:6.34   1st Qu.:4.710  
  307. Mode  :character   Median :2016   Median :14.50   Median :3   Median :2.980   Median :6.46   Median :5.010  
  308.                    Mean   :2016   Mean   :14.50   Mean   :3   Mean   :3.173   Mean   :6.48   Mean   :4.978  
  309.                    3rd Qu.:2017   3rd Qu.:21.25   3rd Qu.:4   3rd Qu.:3.830   3rd Qu.:6.61   3rd Qu.:5.247  
  310.                    Max.   :2018   Max.   :28.00   Max.   :5   Max.   :5.840   Max.   :7.14   Max.   :5.750  
  311.     lnDOK            lnBM           lnPDRB       PAD..dlm.miliar. DAU..dlm.miliar. DAK..dlm.miliar.
  312. Min.   :4.460   Min.   :3.820   Min.   : 6.310   Min.   :  1.27   Min.   : 405.6   Min.   : 52.06  
  313. 1st Qu.:4.610   1st Qu.:5.390   1st Qu.: 6.680   1st Qu.: 11.59   1st Qu.: 566.8   1st Qu.:111.12  
  314. Median :4.660   Median :5.675   Median : 7.200   Median : 19.74   Median : 639.9   Median :150.24  
  315. Mean   :4.684   Mean   :5.648   Mean   : 7.550   Mean   : 45.69   Mean   : 668.4   Mean   :156.38  
  316. 3rd Qu.:4.750   3rd Qu.:5.940   3rd Qu.: 8.065   3rd Qu.: 46.03   3rd Qu.: 740.4   3rd Qu.:190.31  
  317. Max.   :5.140   Max.   :6.710   Max.   :11.220   Max.   :342.13   Max.   :1257.4   Max.   :315.37  
  318. Dana.Otsus..dlm.miliar. Belanja.Modal..dlm.miliar. PDRB.atas.harga.konstan..dlm.miliar.      PAD          
  319. Min.   : 86.51          Min.   : 45.53             Min.   :  550.8                      Min.   :1.266e+09  
  320. 1st Qu.:100.60          1st Qu.:219.49             1st Qu.:  797.5                      1st Qu.:1.159e+10  
  321. Median :105.69          Median :290.91             Median : 1340.4                      Median :1.974e+10  
  322. Mean   :108.79          Mean   :307.53             Mean   : 4977.9                      Mean   :4.569e+10  
  323. 3rd Qu.:115.50          3rd Qu.:378.55             3rd Qu.: 3172.5                      3rd Qu.:4.603e+10  
  324. Max.   :171.14          Max.   :818.74             Max.   :74249.7                      Max.   :3.421e+11  
  325.      DAU                 DAK              Dana.Otsus        Belanja.Modal       PDRB.atas.harga.konstan..dlm.juta.
  326. Min.   :4.056e+11   Min.   :5.206e+10   Min.   :8.651e+10   Min.   :4.553e+10   Min.   :  550805                  
  327. 1st Qu.:5.668e+11   1st Qu.:1.111e+11   1st Qu.:1.006e+11   1st Qu.:2.195e+11   1st Qu.:  797495                  
  328. Median :6.399e+11   Median :1.502e+11   Median :1.057e+11   Median :2.909e+11   Median : 1340423                  
  329. Mean   :6.684e+11   Mean   :1.564e+11   Mean   :1.088e+11   Mean   :3.075e+11   Mean   : 4977946                  
  330. 3rd Qu.:7.404e+11   3rd Qu.:1.903e+11   3rd Qu.:1.155e+11   3rd Qu.:3.786e+11   3rd Qu.: 3172476                  
  331. Max.   :1.257e+12   Max.   :3.154e+11   Max.   :1.711e+11   Max.   :8.187e+11   Max.   :74249680                  
  332. kemiskinan.t.1
  333. Min.   :10.35  
  334. 1st Qu.:23.48  
  335. Median :30.57  
  336. Mean   :29.24  
  337. 3rd Qu.:37.59  
  338. Max.   :45.74  
  339. > library(plm)
  340. > model = lnPDRB ~ lnPAD + lnDAU + lnDAK + lnDOK + lnBM
  341. > pls1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="pooling")
  342. > summary(pls1)
  343. Pooling Model
  344.  
  345. Call:
  346. plm(formula = model, data = Panel, model = "pooling", index = c("ï..Kabupaten.Kota",
  347.    "Tahun"))
  348.  
  349. Balanced Panel: n = 28, T = 5, N = 140
  350.  
  351. Residuals:
  352.     Min.   1st Qu.    Median   3rd Qu.      Max.
  353. -2.024444 -0.324724  0.034791  0.342125  1.472272
  354.  
  355. Coefficients:
  356.             Estimate Std. Error t-value  Pr(>|t|)    
  357. (Intercept) 16.673475   2.621483  6.3603  2.94e-09 ***
  358. lnPAD        0.856225   0.055384 15.4597 < 2.2e-16 ***
  359. lnDAU       -0.268246   0.286485 -0.9363 0.3507863    
  360. lnDAK       -0.074029   0.154251 -0.4799 0.6320623    
  361. lnDOK       -1.882617   0.533979 -3.5256 0.0005788 ***
  362. lnBM        -0.162223   0.146989 -1.1036 0.2717286    
  363. ---
  364. Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  365.  
  366. Total Sum of Squares:    175.81
  367. Residual Sum of Squares: 52.973
  368. R-Squared:      0.69869
  369. Adj. R-Squared: 0.68745
  370. F-statistic: 62.1447 on 5 and 134 DF, p-value: < 2.22e-16
  371. > fem1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="within")
  372. > summary(fem1)
  373. Oneway (individual) effect Within Model
  374.  
  375. Call:
  376. plm(formula = model, data = Panel, model = "within", index = c("ï..Kabupaten.Kota",
  377.    "Tahun"))
  378.  
  379. Balanced Panel: n = 28, T = 5, N = 140
  380.  
  381. Residuals:
  382.      Min.    1st Qu.     Median    3rd Qu.       Max.
  383. -0.1769784 -0.0341254 -0.0021206  0.0317282  0.1678521
  384.  
  385. Coefficients:
  386.        Estimate Std. Error t-value  Pr(>|t|)    
  387. lnPAD -0.0040548  0.0129684 -0.3127  0.755144    
  388. lnDAU  1.1263201  0.1230779  9.1513 4.243e-15 ***
  389. lnDAK  0.0480050  0.0211373  2.2711  0.025143 *  
  390. lnDOK  0.0612013  0.0967789  0.6324  0.528486    
  391. lnBM  -0.0802444  0.0220876 -3.6330  0.000432 ***
  392. ---
  393. Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  394.  
  395. Total Sum of Squares:    1.0632
  396. Residual Sum of Squares: 0.38151
  397. R-Squared:      0.64116
  398. Adj. R-Squared: 0.53384
  399. F-statistic: 38.2362 on 5 and 107 DF, p-value: < 2.22e-16
  400. > rem1 = plm(model, data=Panel, index=c("ï..Kabupaten.Kota","Tahun"), model="random")
  401. > summary(rem1)
  402. Oneway (individual) effect Random Effect Model
  403.   (Swamy-Arora's transformation)
  404.  
  405. Call:
  406. plm(formula = model, data = Panel, model = "random", index = c("ï..Kabupaten.Kota",
  407.     "Tahun"))
  408.  
  409. Balanced Panel: n = 28, T = 5, N = 140
  410.  
  411. Effects:
  412.                    var  std.dev share
  413. idiosyncratic 0.003565 0.059712 0.012
  414. individual    0.290374 0.538863 0.988
  415. theta: 0.9505
  416.  
  417. Residuals:
  418.       Min.    1st Qu.     Median    3rd Qu.       Max.
  419. -0.1374105 -0.0549282 -0.0048105  0.0426738  0.3465637
  420.  
  421. Coefficients:
  422.              Estimate Std. Error z-value Pr(>|z|)    
  423. (Intercept)  0.421187   1.228833  0.3428 0.731784    
  424. lnPAD        0.010017   0.016584  0.6040 0.545821    
  425. lnDAU        1.115347   0.153500  7.2661  3.7e-13 ***
  426. lnDAK        0.044897   0.026927  1.6674 0.095443 .  
  427. lnDOK        0.023345   0.124012  0.1882 0.850683    
  428. lnBM        -0.082010   0.028283 -2.8997 0.003736 **
  429. ---
  430. Signif. codes:  0***0.001**0.01*0.05 ‘.’ 0.1 ‘ ’ 1
  431.  
  432. Total Sum of Squares:    1.4912
  433. Residual Sum of Squares: 0.79352
  434. R-Squared:      0.46788
  435. Adj. R-Squared: 0.44803
  436. Chisq: 117.824 on 5 DF, p-value: < 2.22e-16
  437. > # Uji Haussman, jika signifikan maka fem lebih baik
  438. > phtest(fem1, rem1)
  439.  
  440.     Hausman Test
  441.  
  442. data:  model
  443. chisq = 2.0743, df = 5, p-value = 0.8388
  444. alternative hypothesis: one model is inconsistent
  445.  
  446. > plmtest(pls1, type="bp")
  447.  
  448.     Lagrange Multiplier Test - (Breusch-Pagan) for balanced panels
  449.  
  450. data:  model
  451. chisq = 94.5, df = 1, p-value < 2.2e-16
  452. alternative hypothesis: significant effects
  453.  
  454. > # ujia Heterokedastistas
  455. > library(lmtest)
  456. Loading required package: zoo
  457.  
  458. Attaching package: ‘zoo’
  459.  
  460. The following objects are masked from ‘package:base’:
  461.  
  462.     as.Date, as.Date.numeric
  463.  
  464. > bptest(rem1)
  465.  
  466.     studentized Breusch-Pagan test
  467.  
  468. data:  rem1
  469. BP = 14.6, df = 5, p-value = 0.01222
  470.  
  471. > # uji korelasi
  472. > pbgtest(rem1)
  473.  
  474.     Breusch-Godfrey/Wooldridge test for serial correlation in panel models
  475.  
  476. data:  model
  477. chisq = 53.299, df = 5, p-value = 2.92e-10
  478. alternative hypothesis: serial correlation in idiosyncratic errors
  479.  
  480. > # penanganan dengan robust covarian
  481. > coeftest(rem1, vcovHC(rem1, "arellano"))
  482.  
  483. t test of coefficients:
  484.  
  485.              Estimate Std. Error t value Pr(>|t|)    
  486. (Intercept)  0.421187   0.970915  0.4338  0.66513    
  487. lnPAD        0.010017   0.014922  0.6713  0.50318    
  488. lnDAU        1.115347   0.111722  9.9832  < 2e-16 ***
  489. lnDAK        0.044897   0.027370  1.6404  0.10328    
  490. lnDOK        0.023345   0.100759  0.2317  0.81713    
  491. lnBM        -0.082010   0.037523 -2.1856  0.03058 *  
  492. ---
  493. Signif. codes:  0***0.001**0.01*0.05 ‘.’ 0.1 ‘ ’ 1
  494.  
  495. >
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