Calculating impact measures for spatial panel models and trouble specifying SDEM model using spml
Dear Roger, Thank you for your quick response. I have uploaded the spatial weights matrix and sample dataset I'm working with here: https://drive.google.com/drive/folders/1NjCODKEix-_nA5CfiIos6uiKAUbGp_BZ?usp=sharing Reading the data in and transforming them into a pdataframe and listw, respectively: spatialweight <- read.csv("spatialweight.csv", header = T) row.names(spatialweight) <- spatialweight$X spatialweight <- spatialweight[, -1] spatialweight.mat <- as.matrix(spatialweight) mylistw <- mat2listw(spatialweight.mat, style = "M") mydata <- read.csv("sampledata.csv", header = T) mydata <- pdata.frame(mydata, index = c("Country", "Year")) I first ran a non-spatial model to determine the best specification for fixed effects: nonspatial.pooledOLS <- plm(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI, data = mydata, model = "pooling") nonspatial.individualFE <- plm(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI, data = mydata, model = "within", effect = "individual") nonspatial.timeFE <- plm(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI, data = mydata, model = "within", effect = "time") nonspatial.twowayFE <- plm(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI, data = mydata, model = "within", effect = "twoways") I would like to compare these models based on log likelihood and AIC, but the plm() function does not appear to provide a log likelihood or AIC. I have read through the JSS plm article and it states that models made with the plm() function are "estimated using the lm function to the transformed data". I'm aware that we can use logLik() and AIC() for a model estimated with the lm() function. However it doesn't seem to work with the plm() function. For example, I did logLik(nonspatial.twowayFE) and AIC(nonspatial.twowayFE) but the error message for both is: Error in UseMethod("logLik") : no applicable method for 'logLik' applied to an object of class "c('plm', 'panelmodel')" Please let me know if I'm calling the wrong function(s) and/or if you're aware of a way to compare these models based on log likelihood and/or AIC. For the spatial models, here is my code: spatial.SDEM <- spml(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI + slag(lnGDP, listw = mylistw) + slag(lnGDP2, listw = mylistw) + slag(lnEI, listw = mylistw), data = mydata, listw = mylistw, model = "within", effect = "twoways", lag = F, spatial.error = "b") spatial.SEM <- spml(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI, data = mydata, listw = mylistw, model = "within", effect = "individual", lag = F, spatial.error = "b") spatial.SLX <- plm(lnY ~ lnGDP + lnGDP2 + U + RE + IS + lnEI + slag(lnGDP, listw = mylistw) + slag(lnGDP2, listw = mylistw) + slag(lnEI, listw = mylistw), data = mydata, model = "within", effect = "individual") As in my original post, the SLX and SEM models ran OK but the error when I try to run the SDEM model is: Error in UseMethod("slag") : no applicable method for 'slag' applied to an object of class "c('double', 'numeric')" The variables that I use the slag() function on are all numeric, so I don't know what's wrong. I seem to be able to use slag() with plm() but not with spml(), but I don't know why this is so. I need to compare the models to see if SDEM can be reduced to one of its nested form. As was the case of the non-spatial models, I can't get the log likelihood for models created with the plm() function, so any suggestions are welcome. I've already read through the JSS articles for splm and plm as well as both documentations and there's no information on this (except that models built with the plm() function are estimated using the lm function to the transformed data). Thanks for clarifying the impact measures for SDEM and SLX. Just to check - when you say linear combination for standard errors do you mean e.g. beta1*se + theta1*se = totalse (where beta1 is the coefficient of the direct impact and theta1 is the coefficient of the indirect impact)? Thank you for your help! Best wishes, Sarah
From: Roger Bivand <Roger.Bivand at nhh.no>
Sent: Wednesday, July 24, 2019 9:50:13 PM
To: Letisha Sarah Fong Rui Zhen <geolsfrz at nus.edu.sg>
Cc: r-sig-geo at r-project.org <r-sig-geo at r-project.org>
Subject: Re: [R-sig-Geo] Calculating impact measures for spatial panel models and trouble specifying SDEM model using spml
Sent: Wednesday, July 24, 2019 9:50:13 PM
To: Letisha Sarah Fong Rui Zhen <geolsfrz at nus.edu.sg>
Cc: r-sig-geo at r-project.org <r-sig-geo at r-project.org>
Subject: Re: [R-sig-Geo] Calculating impact measures for spatial panel models and trouble specifying SDEM model using spml
On Wed, 24 Jul 2019, Letisha Sarah Fong Rui Zhen wrote:
> Dear all,
Please do not post HTML-formated messages.
>
> I???m working with panel data of 9 countries and 18 years and I???m
> running fixed effects SDEM, SLX and SEM with the splm package.
>
> I have three questions:
>
> 1. I can???t seem to get the SDEM model to run. My code for each of the
> 3 models is:
>
> model.SDEM <- spml(ln(Y) ~ ln(GDP) + (ln(GDP))^2 + EI + RE +
> slag(ln(GDP), listw = my.listw) + slag((ln(GDP))^2, listw = my.listw),
> data = my.data, listw = my.listw, model = ???within???, effect =
> ???individual???, lag = F, spatial.error = ???b???)
>
> model.SLX <- plm(ln(Y) ~ ln(GDP) + (ln(GDP))^2 + EI + RE + slag(ln(GDP),
> listw = my.listw) + slag((ln(GDP))^2, listw = my.listw), data = my.data,
> model = ???within???, effect = ???individual???)
>
> model.SEM <- spml(ln(Y) ~ ln(GDP) + (ln(GDP))^2 + EI + RE, data =
> my.data, listw = my.listw, model = ???within???, effect =
> ???individual???, lag = F, spatial.error = ???b???)
>
> I am able to run both SLX and SEM models without problem, but when I try
> to run the SDEM model, the error message is:
>
> Error in UseMethod("slag") :
> no applicable method for 'slag' applied to an object of class
> "c('double', 'numeric')"
>
> I don???t understand what is wrong here, as I have no problems with the
> slag() function in the SLX model. My data is a pdataframe and each
> variable is a numeric pseries.
My guess would be that you should protect your square with I() in general,
but have no idea - this is not a reproducible example.
>
>
> 2. How can I calculate impact measures (direct, indirect and total) for
> spatial panel models?
>
> The impacts() function in spdep doesn???t work anymore and the impacts()
> function from the spatialreg package seems to work only for
> cross-sectional data and not panel data.
>
> For example, I ran:
>
> spatialreg::impacts(model.SLX)
>
> And the error message is:
>
> Error in UseMethod("impacts", obj) :
> no applicable method for 'impacts' applied to an object of class
> "c('plm', 'panelmodel')"
>
> I have tried methods(impacts) but none of the functions seem to work for
> my SLX model created with the splm package.
But your SLX model is created with the plm package, isn't it? The only use
of splm is for the manual lags with slag()?
>
> I also looked at some previous examples in the splm documentation and
> more specifically the spml() function and the example provided
> (specifically the impact measures) doesn???t work anymore:
>
> data(Produc, package = "plm")
> data(usaww)
> fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
> ## random effects panel with spatial lag
> respatlag <- spml(fm, data = Produc, listw = mat2listw(usaww),
> model="random", spatial.error="none", lag=TRUE)
> summary(respatlag) ## calculate impact measures impac1 <-
> impacts(respatlag, listw = mat2listw(usaww, style = "W"), time = 17)
> summary(impac1, zstats=TRUE, short=TRUE)
>
The implemented impacts methods in splm apply to the case where the lagged
response is included. For SDEM and SLX, you can get the impacts by
addition for the total impactss, and by linear combination for their
standard errors. This is not implemented in a method. Further, slag() does
not give any impacts method any information on which variables have been
lagged - in your illustration above EI and RE are not lagged.
> The error message when I run the impacts() function is:
>
> Error in UseMethod("impacts", obj) :
> no applicable method for 'impacts' applied to an object of class "splm"
>
> My question is therefore, how do I go about calculating direct, indirect
> and total impact measures for spatial panel data?
>
>
> 3. How can I test if the SDEM model can be simplified to the SLX model
> (since I estimate the SDEM by maximum likelihood (spml function) and
> the SLX by ordinary linear regression (plm function))? From my
> understanding the plm() function does not compute a loglikelihood or
> AIC so I probably can???t do a likelihood ratio test to choose
> between models (I haven???t tried this out because I???m stuck at
> running the SDEM model).
Do you know definitely that plm does not provide a log likelihood? I
realise that it isn't OLS unless pooled. Have you reviewed the JSS plm and
splm articles?
Roger
>
> Any help or advice would be greatly appreciated. Thank you.
>
> Best wishes,
> Sarah
>
>
>
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--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: Roger.Bivand at nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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