SLX模型 - 使用splm软件包和矿渣函数的R数据中面板的空间计量经济学

我需要单独使用空间滞后X（SLX），结合空间自回归模型（SAR）或空间误差模型来估计空间计量经济模型（SEM）。当它们结合后，它们被称为空间Durbin模型（SDM）或空间Durbin误差模型（SDEM），遵循Elhorst（2015）的论文“The SLX Model”的Vega 。SLX模型 - 使用splm软件包和矿渣函数的R数据中面板的空间计量经济学

我打算使用splm包估计R中的所有空间面板模型，这也需要spdep函数。在这个意义上，我创建邻居列表由形状键入文件张大且k = 4：

> W <- nb2listw(contnbk4, glist = NULL, style = "W") 

attributes(W) 
$names 
[1] "style"  "neighbours" "weights" 

$class 
[1] "listw" "nb" 

$region.id 
[1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19" "20" 
[21] "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" 
[41] "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60" 
[61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" "73" "74" "75" "76" "77" "78" "79" "80" 
[81] "81" "82" "83" "84" "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96" "97" "98" "99" "100" 
[101] "101" "102" "103" "104" "105" "106" "107" "108" "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120" 
[121] "121" "122" "123" "124" "125" "126" "127" "128" "129" "130" "131" "132" "133" "134" "135" "136" "137" "138" "139" "140" 
[141] "141" "142" "143" "144" "145" "146" "147" "148" "149" "150" "151" "152" "153" "154" "155" "156" "157" "158" "159" "160" 
[161] "161" "162" "163" "164" "165" "166" "167" "168" "169" "170" "171" "172" "173" "174" "175" "176" "177" "178" "179" "180" 
[181] "181" "182" "183" "184" "185" "186" "187" "188" "189" "190" "191" "192" "193" "194" "195" "196" "197" "198" "199" "200" 
[201] "201" "202" "203" "204" "205" "206" "207" "208" "209" "210" "211" "212" "213" "214" "215" "216" "217" "218" "219" "220" 
[221] "221" "222" "223" "224" "225" "226" "227" "228" "229" "230" "231" "232" "233" "234" "235" "236" "237" "238" "239" "240" 
[241] "241" "242" "243" "244" "245" "246" "247" "248" "249" "250" "251" "252" "253" "254" "255" "256" "257" "258" "259" "260" 
[261] "261" "262" "263" "264" "265" "266" "267" "268" "269" "270" "271" "272" "273" "274" "275" "276" 

    $call 
    nb2listw(neighbours = contnbk7, glist = NULL, style = "W")

下一步，我创建一个：

> TCAL <- readOGR(dsn = ".", "Municipios_csv") 
> coords <- coordinates(TCAL) 

> contnbQueen <- poly2nb(TCAL, queen = TRUE) 
> enter code herecontnbk4 <- knn2nb(knearneigh(coords, k = 4, RANN = FALSE))

然后我在权重矩阵转换此邻居列表公式面板SAR和SEM模型，它运作良好，产生估算值：

> fmPanel <- Area ~ Dist + Land + CredAg 
> vegSAR <- spml(fmPanel, data = veg, index = c("Mun","Year"), listw = W, model = "within", effect = "twoways", spatial.error = "none", lag = TRUE) 
> vegSEM <- spml(fmPanel, data = veg, index = c("Mun","Year"), listw = W, model = "within", effect = "twoways", spatial.error = "b", lag = FALSE)

然后，我试图通过创建协变量X的空间滞后估计SLX，SDM和SDEM机型：

> vegX <- pdata.frame(veg, index = c("Mun","Year")); class(vegX) 

    [1] "pdata.frame" "data.frame"

然后我创建的pSeries值：

> DistX <- vegX$Dist; class(DistX) 
    [1] "pseries" "numeric" 
> LandX <- vegX$Land; class(LandX) 
    [1] "pseries" "numeric" 
> CredAgX <- vegX$CredAg; class(CredAgX) 
    [1] "pseries" "numeric"

但是当我申请发生的错误渣功能：

DistX <- slag(agSPX$Dist, listw = W) 

    Error in lag.listw(listw, xt) : object lengths differ

我的面板数据，有5年，276个区。所以，对象特点是：

> length(DistX) 
[1] 1380 

> length(W) 
[1] 3 

> length(W$weights) 
[1] 276

所以，我在想，如果我能在一个矩阵变换矩阵W $权重如usaww作为例子渣功能，我可以申请功能mat2listw和然后在X上使用炉渣。

有人能告诉我我错在哪？

来源

2017-09-01 dfamaral

也许它不是最好的解决办法，但我计算SLX，这些SDM和SDEM模型步骤：

1）通过加载形文件：

TCAL <- readOGR(dsn = ".", "Municipios_csv_BIO") 
coords <- coordinates(TCAL)

2）创建加权矩阵W通过：

contnbQueen <- poly2nb(TCAL, queen = TRUE) 
contnbk4  <- knn2nb(knearneigh(coords, k = 4, RANN = FALSE))

3）选择哪些矩阵申请：

W <- nb2listw(contnbk4, glist = NULL, style = "W")

4）在PDATA转换data.frame。帧：

vegSPX <- pdata.frame(vegPainel, index = c("ID","Ano"))

5）创建特定pdata.frame空间矢量，例如：

vegIDDX <- vegSPX$IDD 
vegSoilX <- vegSPX$Soil 
vegQAIX <- vegSPX$QAI

6）指定用于这些模型的公式：

fmSPvegX <- Area ~ IDD + Soil + QAI + slag(vegIDDX, listw = W) + slag(vegSoilX, listw = W) + slag(vegQAIX, listw = W)

7）在原始数据上应用plm和splm函数（data.tabl e数据帧对象）：

vegSLX<-plm(fmSPvegX,data=vegPainel,listw=W,index=c("ID","Ano"),model="within",effect="twoways",spatial.error="none",lag=F) 
vegSARX<-spml(fmSPvegX,data=vegPainel,listw=W,index=c("ID","Ano"),model="within",effect="twoways",spatial.error="none",lag=T) 
vegSEMX<-spml(fmSPvegX,data=vegPainel,listw=W,index=c("ID","Ano"),model="within",effect="twoways",spatial.error="b",lag=F)

我希望它可以帮助。

来源

2017-12-29 13:36:51 dfamaral

SLX模型 - 使用splm软件包和矿渣函数的R数据中面板的空间计量经济学

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