我正在尝试使用pgmm
plm
包中的R
函数。Error in t(y) %*% x : non-conformable arguments
。回归运行,我可以调用结果,但是,要求摘要会出现以下错误:
library(WDI) # Load package
COUNTRIES <- c("AGO","BEN","BWA","BFA","BDI") # Specify countries
INDICATORS <- c("NY.GDP.PCAP.KN", "SP.DYN.TFRT.IN", "SP.DYN.CBRT.IN", "SP.POP.TOTL") # Specify indicators
LONG <- WDI(country=COUNTRIES, indicator=INDICATORS, start=2005, end=2009, extra=FALSE) # Load data
PANEL <- pdata.frame(LONG, c("iso2","year")) # Transform to PANEL dataframe
PANEL$year <- as.numeric(as.character(PANEL$year)) # Encode year
EQ <- pgmm( log(fertility) ~ log(gdp) + lag(log(fertility), 2) | lag(log(fertility), 2), data=PANEL, effect="twoways", model="twosteps", gmm.inst=~log(fertility) ) # Run regression
我使用WDI软件包从世界银行导入数据:
EQ
如下调用结果。
summary(EQ)
但摘要(如下)给出了上面提到的错误信息。
{{1}}
答案 0 :(得分:3)
我认为错误的发生是因为summary.pgmm
尝试对您的数据进行二阶Arelland-Bond序列相关性测试,但您的数据只有两点(2008年和2009年),因此失败。
要解决此问题,您可以修补该功能,以便检查数据集中是否只有两个点,并且仅当您有两个以上的点时才运行测试。我在下面提供了补丁功能:
summary.pgmm.patched <- function (object, robust = FALSE, time.dummies = FALSE, ...)
{
model <- plm:::describe(object, "model")
effect <- plm:::describe(object, "effect")
transformation <- plm:::describe(object, "transformation")
if (robust) {
vv <- vcovHC(object)
}
else {
vv <- vcov(object)
}
if (model == "onestep")
K <- length(object$coefficients)
else K <- length(object$coefficients[[2]])
Kt <- length(object$args$namest)
if (!time.dummies && effect == "twoways")
rowsel <- -c((K - Kt + 1):K)
else rowsel <- 1:K
std.err <- sqrt(diag(vv))
b <- coef(object)
z <- b/std.err
p <- 2 * pnorm(abs(z), lower.tail = FALSE)
CoefTable <- cbind(b, std.err, z, p)
colnames(CoefTable) <- c("Estimate", "Std. Error", "z-value",
"Pr(>|z|)")
object$CoefTable <- CoefTable[rowsel, , drop = FALSE]
object$sargan <- sargan(object)
object$m1 <- plm:::mtest(object, 1, vv)
# The problem line:
# object$m2 <- mtest(object, 2, vv)
if (length(object$residuals[[1]] ) > 2) object$m2 <- plm:::mtest(object, 2, vv)
object$wald.coef <- plm:::wald(object, "param", vv)
if (plm:::describe(object, "effect") == "twoways")
object$wald.td <- plm:::wald(object, "time", vv)
class(object) <- "summary.pgmm"
object
}
您可能想写信给plm
包的作者并向他展示这篇文章。作者将能够编写一个不那么“hacky”的补丁。
使用您自己的(略微修改过的)示例数据,以下是使用该函数的方法:
library(WDI) # Load package
library(plm)
COUNTRIES <- c("AGO","BEN","BWA","BFA","BDI") # Specify countries
INDICATORS <- c("NY.GDP.PCAP.KN", "SP.DYN.TFRT.IN", "SP.DYN.CBRT.IN", "SP.POP.TOTL") # Specify indicators
LONG <- WDI(country=COUNTRIES, indicator=INDICATORS, start=2005, end=2009, extra=FALSE) # Load data
PANEL <- pdata.frame(LONG, c("iso2c","year")) # Transform to PANEL dataframe
PANEL$year <- as.numeric(as.character(PANEL$year)) # Encode year
names(PANEL) [c(4,5)] = c('gdp','fertility')
EQ <- pgmm( log(fertility) ~ log(gdp) + lag(log(fertility), 2) | lag(log(fertility), 2), data=PANEL, effect="twoways", model="twosteps", gmm.inst=~log(fertility) ) # Run regression
summary.pgmm.patched(EQ)