【问题标题】:Stargazer does not recognise tobit even though it is supported即使支持,Stargazer 也无法识别 tobit
【发布时间】:2021-01-11 10:53:05
【问题描述】:

我想让stargazer 打印一个AER::tobit 回归(数据在底部)。

require(AER)
require(stargazer)
s1.tobit <- AER::tobit(taxrate ~ votewon + industry + size + urbanisation + vote,
                  left=12, right=33, data=DF)
stargazer(s1.tobit)

% Error: Unrecognized object type.

根据小插图,这应该没问题:https://cran.r-project.org/web/packages/stargazer/vignettes/stargazer.pdf

谁能帮我看看发生了什么?

数据

DF <- structure(list(country = c("C", "C", "C", "C", "J", "J", "B", 
"B", "F", "F", "E", "E", "D", "D", "F", "F", "I", "I", "J", "J", 
"E", "E", "C", "C", "I", "I", "I", "I", "I", "I", "C", "C", "H", 
"H", "J", "J", "G", "G", "J", "J", "I", "I", "C", "C", "D", "D", 
"A", "A", "G", "G", "E", "E", "J", "J", "G", "G", "I", "I", "I", 
"I", "J", "J", "G", "G", "E", "E", "G", "G", "E", "E", "F", "F", 
"I", "I", "B", "B", "E", "E", "H", "H", "B", "B", "A", "A", "I", 
"I", "I", "I", "F", "F", "E", "E", "I", "I", "J", "J", "D", "D", 
"F", "F"), year = c(2005, 2010, 2010, 2005, 2005, 2010, 2010, 
2005, 2010, 2005, 2005, 2010, 2010, 2005, 2005, 2010, 2005, 2010, 
2005, 2010, 2010, 2005, 2010, 2005, 2005, 2010, 2005, 2010, 2010, 
2005, 2010, 2005, 2005, 2010, 2010, 2005, 2005, 2010, 2005, 2010, 
2005, 2010, 2005, 2010, 2010, 2005, 2005, 2010, 2010, 2005, 2010, 
2005, 2010, 2005, 2010, 2005, 2010, 2005, 2010, 2005, 2010, 2005, 
2010, 2005, 2010, 2005, 2010, 2005, 2005, 2010, 2005, 2010, 2005, 
2010, 2005, 2010, 2005, 2010, 2005, 2010, 2010, 2005, 2005, 2010, 
2005, 2010, 2010, 2005, 2010, 2005, 2010, 2005, 2005, 2010, 2005, 
2010, 2010, 2005, 2010, 2005), sales = c(15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9, 15.48, 12.39, 3.72, 
23.61, 4, 31.87, 25.33, 7.64, -0.26, 2.9), industry = c("D", 
"D", "E", "E", "F", "F", "F", "F", "D", "D", "E", "E", "D", "D", 
"E", "E", "F", "F", "F", "F", "D", "D", "F", "F", "E", "E", "D", 
"D", "D", "D", "E", "E", "F", "F", "D", "D", "E", "E", "E", "E", 
"D", "D", "E", "E", "D", "D", "D", "D", "E", "E", "D", "D", "F", 
"F", "D", "D", "D", "D", "E", "E", "D", "D", "E", "E", "D", "D", 
"D", "D", "D", "D", "F", "F", "F", "F", "E", "E", "D", "D", "E", 
"E", "F", "F", "E", "E", "F", "F", "E", "E", "F", "F", "D", "D", 
"D", "D", "D", "D", "D", "D", "F", "F"), urbanisation = c("B", 
"B", "A", "A", "B", "B", "A", "A", "C", "C", "C", "C", "A", "A", 
"B", "B", "C", "C", "A", "A", "C", "C", "B", "B", "A", "A", "A", 
"A", "A", "A", "A", "A", "A", "A", "C", "C", "B", "B", "B", "B", 
"B", "B", "C", "C", "A", "A", "B", "B", "B", "B", "A", "A", "B", 
"B", "A", "A", "A", "A", "B", "B", "C", "C", "A", "A", "C", "C", 
"A", "A", "B", "B", "A", "A", "B", "B", "B", "B", "B", "B", "C", 
"C", "A", "A", "A", "A", "A", "A", "A", "A", "C", "C", "A", "A", 
"B", "B", "A", "A", "B", "B", "B", "B"), size = c(1, 1, 5, 5, 
5, 5, 1, 1, 1, 1, 5, 5, 5, 5, 2, 2, 2, 2, 5, 5, 1, 1, 1, 1, 5, 
5, 5, 5, 4, 4, 5, 5, 5, 5, 4, 4, 2, 2, 5, 5, 1, 1, 1, 1, 2, 2, 
1, 1, 2, 2, 5, 5, 1, 1, 3, 3, 2, 2, 2, 2, 5, 5, 4, 4, 1, 1, 5, 
5, 2, 2, 5, 5, 2, 2, 2, 2, 4, 4, 3, 3, 4, 4, 3, 3, 3, 3, 3, 3, 
5, 5, 3, 3, 2, 2, 3, 3, 1, 1, 5, 5), base_rate = c(14L, 14L, 
14L, 14L, 19L, 19L, 30L, 30L, 20L, 20L, 29L, 29L, 20L, 20L, 20L, 
20L, 24L, 24L, 19L, 19L, 29L, 29L, 14L, 14L, 24L, 24L, 24L, 24L, 
24L, 24L, 14L, 14L, 17L, 17L, 19L, 19L, 33L, 33L, 19L, 19L, 24L, 
24L, 14L, 14L, 20L, 20L, 23L, 23L, 33L, 33L, 29L, 29L, 19L, 19L, 
33L, 33L, 24L, 24L, 24L, 24L, 19L, 19L, 33L, 33L, 29L, 29L, 33L, 
33L, 29L, 29L, 20L, 20L, 24L, 24L, 30L, 30L, 29L, 29L, 17L, 17L, 
30L, 30L, 23L, 23L, 24L, 24L, 24L, 24L, 20L, 20L, 29L, 29L, 24L, 
24L, 19L, 19L, 20L, 20L, 20L, 20L), taxrate = c(12L, 14L, 14L, 
12L, 21L, 18L, 30L, 30L, 20L, 20L, 29L, 30L, 20L, 20L, 20L, 20L, 
24L, 24L, 21L, 18L, 30L, 29L, 14L, 12L, 24L, 24L, 24L, 24L, 24L, 
24L, 14L, 12L, 18L, 19L, 18L, 21L, 33L, 32L, 21L, 18L, 24L, 24L, 
12L, 14L, 20L, 20L, 22L, 25L, 32L, 33L, 30L, 29L, 18L, 21L, 32L, 
33L, 24L, 24L, 24L, 24L, 18L, 21L, 32L, 33L, 30L, 29L, 32L, 33L, 
29L, 30L, 20L, 20L, 24L, 24L, 30L, 30L, 29L, 30L, 18L, 19L, 30L, 
30L, 22L, 25L, 24L, 24L, 24L, 24L, 20L, 20L, 30L, 29L, 24L, 24L, 
21L, 18L, 20L, 20L, 20L, 20L), vote = c(0, 0, 0, 0, 1, 1, 1, 
0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 
1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 
1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 
1, 0, 1, 1, 1, 1, 0, 1, 1), votewon = c(0, 0, 0, 0, 1, 0, 1, 
0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 
1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 
0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 
1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 
0, 0, 1, 1, 0, 1, 0, 1, 1)), class = "data.frame", row.names = c(NA, 
-100L))

## convert variables to factors beforehand
DF[c(1, 2, 4, 5, 6, 9, 10)] <- lapply(DF[c(1, 2, 4, 5, 6, 9, 10)], factor)

【问题讨论】:

    标签: r stargazer


    【解决方案1】:

    使用stargazer v5.2.2 和AER v1.2-9 仅当您将AER:: 放在tobit 前面时它才有效,这很奇怪。也许你应该写一份错误报告,尽管我强烈建议使用texreg 而不是stargazer

    require(AER)
    require(stargazer)
    m1.tobit <- AER::tobit(taxrate ~ votewon + industry + size + urbanisation + vote,
                           left=12, right=33, data=DF)
    > stargazer(m1.tobit)
    
    % Error: Unrecognized object type.
    
    m2.tobit <- tobit(taxrate ~ votewon + industry + size + urbanisation + vote,
                      left=12, right=33, data=DF)
    > stargazer(m2.tobit)
    
    % Table created by stargazer v.5.2.2 by Marek Hlavac, Harvard University. E-mail: hlavac at fas.harvard.edu
    % Date and time: Sat, Jan 16, 2021 - 20:13:07
    \begin{table}[!htbp] \centering 
      \caption{} 
      \label{} 
    \begin{tabular}{@{\extracolsep{5pt}}lc} 
    \\[-1.8ex]\hline 
    \hline \\[-1.8ex] 
     & \multicolumn{1}{c}{\textit{Dependent variable:}} \\ 
    \cline{2-2} 
    \\[-1.8ex] & taxrate \\ 
    \hline \\[-1.8ex] 
     votewon & $-$1.593 \\ 
      & (1.558) \\ 
      & \\ 
     industryE & $-$0.787 \\ 
      & (1.446) \\ 
      & \\ 
     industryF & $-$2.861$^{*}$ \\ 
      & (1.515) \\ 
      & \\ 
     size & $-$0.552 \\ 
      & (0.447) \\ 
      & \\ 
     urbanisationB & $-$1.703 \\ 
      & (1.525) \\ 
      & \\ 
     urbanisationC & $-$3.097$^{*}$ \\ 
      & (1.689) \\ 
      & \\ 
     vote & 4.176$^{***}$ \\ 
      & (1.615) \\ 
      & \\ 
     Constant & 25.257$^{***}$ \\ 
      & (1.934) \\ 
      & \\ 
    \hline \\[-1.8ex] 
    Observations & 100 \\ 
    Log Likelihood & $-$299.532 \\ 
    Wald Test & 13.061$^{*}$ (df = 7) \\ 
    \hline 
    \hline \\[-1.8ex] 
    \textit{Note:}  & \multicolumn{1}{r}{$^{*}$p$<$0.1; $^{**}$p$<$0.05; $^{***}$p$<$0.01} \\ 
    \end{tabular} 
    \end{table} 
    

    【讨论】:

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