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我正在尝试使用 systemfit 包来估计计量经济学模型。我继续得到error: Error in eval(predvars, data, env) : object 'gdp_gro' not found. 事情gdp_gro肯定在我的数据集中。

我试图用谷歌搜索这个错误，但我无法找出解决方案。基于 Stackoverflow 和其他地方的其他问题，我认为问题在于 R 处理公式环境的方式。我将不胜感激有关为什么我的代码不起作用以及如何修复它的一些指导。非常感谢。

我附上了一个代表和部分数据集（下）：

library(systemfit)
#> Loading required package: Matrix
#> 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
#> 
#> Please cite the 'systemfit' package as:
#> Arne Henningsen and Jeff D. Hamann (2007). systemfit: A Package for Estimating Systems of Simultaneous Equations in R. Journal of Statistical Software 23(4), 1-40. http://www.jstatsoft.org/v23/i04/.
#> 
#> If you have questions, suggestions, or comments regarding the 'systemfit' package, please use a forum or 'tracker' at systemfit's R-Forge site:
#> https://r-forge.r-project.org/projects/systemfit/

#Prepare a new list
DF = list()

#Splitting the data in list elements by years
for (i in seq(from = 1, by =1, to =length(unique(as.numeric(df$year))))){

  DF[[i]] <- df[df$year == unique(as.numeric(df$year))[i],]

}
#> Error: object of type 'closure' is not subsettable

Equation = list()
Inststruments = list()

#### SPECIFCIATION OF EQUATIONS
for (i in seq(from = 1, by =1, to =length(unique(as.numeric(df$year))))){

  #Automatically pick up the instruments
  instruments <- select_vars(colnames(as.data.frame(DF[i])), ends_with("_I", ignore.case = FALSE))

  #Variables picked out automatically
  variables <- colnames(as.data.frame(DF[i]))[!colnames(as.data.frame(DF[i])) %in% c(instruments, "gdp_gro")]

  #Automatizing the equation specification 
  Equation[[i]] <- with(DF[i] , as.formula(paste("gdp_gro ~ ", paste(variables, collapse="+"))) )

  Inststruments[[i]] <- with(DF[i] , as.formula(paste("~ ", paste(instruments, collapse="+"))) )

}
#> Error: object of type 'closure' is not subsettable

#Finally run the key regressions
reg <- systemfit(Equation, method = "3SLS", inst = Inststruments, methodResidCov = "noDfCor" )
#> Error in formula[[i]]: subscript out of bounds

部分数据（使用 dput 生成）：

  structure(list(country_code = c("AUS", "AUS", "AUS", "AUS", "AUT", 
"AUT", "AUT", "AUT", "BEL", "BEL", "BEL", "BEL", "BGR", "BGR", 
"BGR", "BGR"), year = c(1995L, 2000L, 2005L, 2010L, 1995L, 2000L, 
2005L, 2010L, 1995L, 2000L, 2005L, 2010L, 1995L, 2000L, 2005L, 
2010L), tot_lif = c(0.0128486367909746, 0.0126208212768577, 0.0123698898778096, 
0.0122406329302881, 0.0130432016288096, 0.0127997002997003, 0.0126053003750845, 
0.0124099521762818, 0.0130139312547017, 0.0128663779576979, 0.0126613550738064, 
0.0124714828897338, 0.0140739189685534, 0.0139541215710299, 0.013781512605042, 
0.0136031851360319), cap_aset = c(NA, 6.9, 6.9, 5.43, NA, 5.2, 
4.8, 7.49276, NA, 2.8, 2.7, 4.96531, NA, 15.3, 7.4, 10.4677), 
    cb_assets = c(3.06318, 2.46202, 2.20076, 3.33956, 0.399895, 
    0.536933, 0.551538, 0.815212, 0.972776, 0.466959, 0.248117, 
    0.823367, 7.90828, 8.51751, 3.15831, 0.095416), tot_fert = c(1.822, 
    1.756, 1.807, 1.928, 1.42, 1.36, 1.41, 1.44, 1.56, 1.67, 
    1.76, 1.86, 1.23, 1.26, 1.37, 1.57), nat_res = c(2.09714172369929, 
    3.51179102271941, 7.72238072354596, 8.01628506180971, 0.11853075155191, 
    0.150961988690622, 0.206953989580903, 0.216777594515187, 
    0.0223053533152314, 0.0203362079028292, 0.0177518400351335, 
    0.019336002220052, 1.47167055527445, 1.33790542432826, 2.31972541945117, 
    2.08046786610067), trad_term = c(NA, 100, 131.0849232, 178.9001645, 
    NA, 100, 95.91930131, 92.25883781, NA, 100, 98.77006835, 
    96.59919868, NA, 100, 84.20837461, 125.8550667), gov_cons = c(0.1471103005, 
    0.1474746565, 0.151790273666667, NA, 0.149812934333333, 0.154511682833333, 
    0.1511594605, NA, 0.171062330333333, 0.180379932166667, 0.174480045833333, 
    NA, 0.289015879333333, 0.323738674333333, 0.276189208166667, 
    NA), gdp_gro = c(3.8293687531652, 3.94318908229896, 3.19031634041626, 
    2.05294200395332, 2.66798366552709, 3.37572197324998, 2.24406681223554, 
    1.83709459152502, 2.3847572377606, 3.63365201492995, 2.09427270847185, 
    2.74421327182894, 2.86018944148833, 4.94055377635733, 7.12351107638302, 
    1.32408780093829), gross_inv = c(0.266632934333333, 0.260118643666667, 
    0.300801128, 0.264703502, 0.335587352333333, 0.260061338333333, 
    0.270549208, 0.287363499333333, 0.2805128, 0.246921166666667, 
    0.308350493333333, 0.324811398666667, 0.0818940103333333, 
    0.136577869666667, 0.236514484, 0.19643417), gdp_cap_1 = c(0.00192864730372135, 
    0.00222430451645368, 0.00250264618548625, 0.00273814839048662, 
    0.0027345490098763, 0.0032819778735874, 0.00334421790851598, 
    0.0037646138629738, NA, 0.00344158786452203, 0.00350312141684792, 
    0.00395886153650055, 0.000862928006781417, 0.000734707837639529, 
    0.000935582564325206, 0.0013229694175178), gdp_cap_2 = c(0.00191622588648934, 
    0.00221469960943122, 0.00254717484680898, 0.00285420952389829, 
    0.00252904621475959, 0.00305993171114882, 0.00329798344078102, 
    0.00354070266940731, NA, 0.00289716367632824, 0.00329402073984151, 
    0.00365521257262544, 0.000834744862348611, 0.000765775240349386, 
    0.000991473707456532, 0.0012880711598984), econ_open = c(1.11564470333333, 
    1.07036188216667, 1.31764187416667, NA, 1.19112350533333, 
    1.13605700933333, 1.37068624266667, NA, 1.14728215333333, 
    1.1020498675, 1.34182663783333, NA, 1.01287280516667, 0.982563148, 
    1.2535847325, NA), demo_2 = c(0.0156360833333333, NA, NA, 
    0.0272981816666667, 0.0162439233333333, 0.016152265, 0.0163356866666667, 
    0.0192567566666667, 0.0179158466666667, 0.02126817, 0.023894505, 
    0.0293736833333333, NA, 0.05795811, 0.0639238566666667, 0.052836915
    ), male_edu_1 = c(5.81, 5.82, 5.84, 5.87, 4.09, 3.86, 3.86, 
    3.87, 5.53, 5.59, 5.63, 5.59, 5.38, 5.43, 5.9, 6.3), male_edu_2 = c(4.78, 
    4.76, 4.81, 4.61, 5.48, 5.77, 6.08, 6.28, 3.79, 3.96, 4.31, 
    4.38, 2.87, 3.11, 3.72, 4.31), male_edu_3 = c(0.88, 0.78, 
    0.93, 1.12, 0.35, 0.48, 0.64, 0.71, 0.8, 0.88, 0.95, 1.05, 
    0.53, 0.58, 0.61, 0.71), male_edu_4 = c(11.48, 11.35, 11.58, 
    11.6, 9.92, 10.11, 10.58, 10.86, 10.12, 10.43, 10.88, 11.02, 
    8.79, 9.13, 10.23, 11.32), tot_lif_I = c(0.0128682464785598, 
    0.0127095722174518, 0.012465515344814, 0.0122834370967119, 
    0.0131404621173837, 0.0128830665052315, 0.012685638515979, 
    0.0124510515974525, 0.0130783197148458, 0.0129052789260619, 
    0.0127617321099324, 0.0125262669490894, 0.0140154543995514, 
    0.0140966755510497, 0.0138573536026272, 0.0136964325672041
    ), tot_fert_I = c(1.822, 1.756, 1.807, 1.928, 1.42, 1.36, 
    1.41, 1.44, 1.56, 1.67, 1.76, 1.86, 1.23, 1.26, 1.37, 1.57
    ), gov_cons_I = c(0.147556354666667, 0.147787615333333, 0.14822341, 
    0.154233063333333, 0.143237327333333, 0.154914428666667, 
    0.150818939, 0.160776774333333, 0.167895371666667, 0.174698651, 
    0.174371118333333, 0.185355464666667, 0.318261792333333, 
    0.319208641666667, 0.313319266, 0.274927805), gross_inv_I = c(0.271324028333333, 
    0.263693382333333, 0.298435052333333, 0.269873092666667, 
    0.342670599333333, 0.287529100666667, 0.262940883333333, 
    0.273333341, 0.290991584333333, 0.259098499666667, 0.269275173666667, 
    0.313822090666667, 0.0746616733333333, 0.12165235, 0.171543354666667, 
    0.245303109333333), gdp_cap_1_I = c(0.00192864730372135, 
    0.00222430451645368, 0.00250264618548625, 0.00273814839048662, 
    0.0027345490098763, 0.0032819778735874, 0.00334421790851598, 
    0.0037646138629738, NA, 0.00344158786452203, 0.00350312141684792, 
    0.00395886153650055, 0.000862928006781417, 0.000734707837639529, 
    0.000935582564325206, 0.0013229694175178), gdp_cap_2_I = c(0.00191622588648934, 
    0.00221469960943122, 0.00254717484680898, 0.00285420952389829, 
    0.00252904621475959, 0.00305993171114882, 0.00329798344078102, 
    0.00354070266940731, NA, 0.00289716367632824, 0.00329402073984151, 
    0.00365521257262544, 0.000834744862348611, 0.000765775240349386, 
    0.000991473707456532, 0.0012880711598984), econ_open_I = c(1.08680443966667, 
    1.05545339966667, 1.146271606, 1.401552578, 1.17984314766667, 
    1.122572442, 1.21375773333333, 1.43774867033333, 1.14471817, 
    1.08343706533333, 1.18125647333333, 1.41352349533333, 1.00123712466667, 
    0.956378658666667, 1.057932824, 1.33654979833333), demo_2_I = c(0.0174405, 
    0.0141582, NA, 0.02649142, 0.01485111, 0.01894116, 0.01685453, 
    0.01725761, 0.01650168, 0.01752877, 0.02481076, 0.02306411, 
    0.0366033, 0.0530792, 0.06323963, 0.05811036)), row.names = c(NA, 
16L), class = "data.frame")
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2 回答 2

1

您需要向 systemfit 提供 data 参数，并在列表的各个项目上运行该函数。

reg <- systemfit::systemfit(Equation[[1]], method = "3SLS", inst = Inststruments[[1]], 
methodResidCov = "noDfCor", data = DF[[1]])
> Error in intI(i, n = x@Dim[1], dn[[1]], give.dn = FALSE) : 
   index larger than maximal 0

这解决了您的第一个问题，但随后又给了您另一个问题:)

于 2018-09-17T08:21:59.290 回答
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我联系了软件包开发人员，由于他的努力，我的问题在 systemfit 1.1-23 中得到了解决。此版本在 CRAN 上尚不可用，但可以从 R-Forge 获得：http ://r-forge.r-project.org/R/?group_id=242或使用以下命令：

install.packages("systemfit",repos="http://R-Forge.R-project.org")
于 2018-11-25T12:50:25.843 回答