Displaying 20 results from an estimated 1000 matches similar to: "Problems with obtaining t-tests of regression"
2007 Feb 20
0
Problems with obtaining t-tests of regression coefficients applying consistent standard errors after run 2SLS estimation. Clearer !!!!!
First I have to say I am sorry because I have not been so clear in my
previous e-mails. I will try to explain clearer what it is my problem.
I have the following model:
lnP=Sc+Ag+Ag2+Var+R+D
In this model the variable Sc is endogenous and the rest are all objective
exogenous variables. I verified that Sc is endogenous through a standard
Hausman test. To determine this I defined before a new
2007 Feb 19
1
Urgent: How to obtain the Consistent Standard Errors after apply 2SLS through tsls() from sem or systemfit("2SLS") without this error message !!!!!!!!!!!!!
Hi,
I am trying to obtain the heteroskedasticity consitent standard errors
(HCSE) after apply 2SLS. I obtain 2SLS through tsls from package sem or
systemfit:
#### tsls ####
library (sem)
Reg2SLS <-tsls(LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D)
summary (Reg2SLS)
#### systemfit ####
library (systemfit)
RS <- LnP~Sc+Ag+Ag2+Var+R+D
Inst <- ~I2+Ag+Ag2+Var+R+D
labels
2011 Jan 16
1
Hausman Test
Hi,
can anybody tell me how the Hausman test for endogenty works?
I have a simulated model with three correlated predictors (X1-X3). I also
have an instrument W for X1
Now I want to test for endogeneity of X1 (i.e., when I omit X2 and X3 from
the equation).
My current approach:
library(systemfit)
fit2sls <- systemfit(Y~X1,data=data,method="2SLS",inst=~W)
fitOLS <-
2005 May 25
3
Problem with systemfit 0.7-3 and transformed variables
The 'systemfit' function in systemfit 0.7-3 CRAN package seems to have a
problem with formulas that contain transformed (eg. log) variables. If I
have my data in a data frame, apparently systemfit doesn't "pass" the
information of where the variables should be taken to the transforming function.
I'm not entirely sure if this is a bug or just a limitation, I was just
2011 Nov 23
0
Error using coeftest() with a heteroskedasticity-consistent estimation of the covar.
Hey
I am trying to run /coeftest()/ using a heteroskedasticity-consistent
estimation of the covariance matrix and i get this error:
# packages
>library(lmtest)
>library(sandwich)
#test
> coeftest(*GSm_inc.pool*, vcov = vcovHC(*GSm_inc.pool*, method="arellano",
> type="HC3"))
/Fehler in 1 - diaghat : nicht-numerisches Argument f?r bin?ren Operator/
something like:
2009 Oct 28
1
New variables "remember" how they were created?
Hello all,
I hope this question is appropriate for this ML.
Basically, I am wondering if when you create a new variable, if the
variable holds some information about how it was created.
Let me explain, I have the following code to replicate an example in a
textbook (Greene's Econometric Analysis), using the systemfit package.
dta <-
2011 Jul 25
1
predict() and heteroskedasticity-robust standard errors
Hello there,
I have a linear regression model for which I estimated
heteroskedasticity-robust (Huber-White) standard errors using the
coeftest function
in the lmtest-package.
Now I would like to inspect the predicted values of the dependent
variable for particular groups and include a confidence interval for
this prediction.
My question: is it possible to estimate confidence intervals for the
2007 Dec 18
0
New version of systemfit (not backward compatible)
Dear R users,
the systemfit package contains functions for fitting systems of simultaneous
equations by various estimation methods (e.g. OLS, SUR, 2SLS, 3SLS).
Currently version 0.8 of systemfit is available on CRAN. However, shortly we
will upload version 1.0, which is NOT BACKWARD COMPATIBLE. The changes that
broke backward compatibility were necessary to make systemfit() more similar
to
2007 Dec 18
0
New version of systemfit (not backward compatible)
Dear R users,
the systemfit package contains functions for fitting systems of simultaneous
equations by various estimation methods (e.g. OLS, SUR, 2SLS, 3SLS).
Currently version 0.8 of systemfit is available on CRAN. However, shortly we
will upload version 1.0, which is NOT BACKWARD COMPATIBLE. The changes that
broke backward compatibility were necessary to make systemfit() more similar
to
2011 Jan 17
2
How to still processing despite bug errors?
Hi, everybody.
I am working processing EEG data from 1000 pacients. I have a specific
syntax to perform the Spectral Analysis and a loop to analyse all subjects.
each subject data are in separate folders (P1, P2 P3...)
My question is: in some cases, some errors can appear in one subject. I want
to know if is possible to jump to the next subject and perform the same
syntax , exibiting an error
2009 May 29
1
Error messages/systemfit package
Hello !
I’m trying to estimate a system of equation (demand and supply) using the systemfit package. My program is:
library(systemfit)
demand <- tsyud ~ tsyud1 + tsucp + tspo + tssn
supply <- tscn ~ tsyn + tsqn + tsksn + tsucp
system <- list(demand=eqdemand, learning = eqsupply)
labels <- list(demand="eqdemand", learning="eqsupply")
inst <- ~ tsupp1 + tsupp2
2009 Dec 08
1
Serial Correlation in panel data regression
Dear R users,
I have a question here
library(AER)
library(plm)
library(sandwich)
## take the following data
data("Gasoline", package="plm")
Gasoline$f.year=as.factor(Gasoline$year)
Now I run the following regression
rhs <- "-1 + f.year + lincomep+lrpmg+lcarpcap"
m1<- lm(as.formula(paste("lgaspcar ~", rhs)), data=Gasoline)
###Now I want to find the
2009 Mar 10
1
HAC corrected standard errors
Hi,
I have a simple linear regression for which I want to obtain HAC corrected
standard errors, since I have significant serial/auto correlation in my
residuals, and also potential heteroskedasticity.
Would anyone be able to direct me to the function that implements this in R?
It's a basic question and I'm sure I'm missing something obvious here. I
looked up this post:
2006 Mar 21
0
New version of 'systemfit'
Dear R users,
The authors of the systemfit package have released a new version of this
package with substantial enhancements.
The systemfit package contains functions for fitting simultaneous systems of
linear equations using Ordinary Least Squares (OLS), Weighted Least Squares
(WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS),
Weighted Two-Stage Least Squares
2006 Mar 21
0
New version of 'systemfit'
Dear R users,
The authors of the systemfit package have released a new version of this
package with substantial enhancements.
The systemfit package contains functions for fitting simultaneous systems of
linear equations using Ordinary Least Squares (OLS), Weighted Least Squares
(WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS),
Weighted Two-Stage Least Squares
2007 May 08
0
help with memory problem in SystemFit
Hi - I encounter two problems with SystemFit. I have a matrix of 20 variables (380000 observations each). I am trying to fit using "2SLS" in Systemfit because I want to be able to simulate new observations with the resulting model. The first problem I found is that it ran out of memory given that I have 2GB of RAM. How can I circumvent this? Can I do some mixing or bootstrapping with
2007 May 08
0
Help with systemfit
Hi - I encounter two problems with
SystemFit. I have a matrix of 20 variables (380000 observations each).
I am trying to fit using "2SLS" in Systemfit because I want to be able
to simulate new observations with the resulting model. The first
problem I found is that it ran out of memory given that I have 2GB of
RAM. How can I circumvent this? Can I do some mixing or bootstrapping
with
2005 Feb 18
0
single equation IV estimation in R using systemfit
Hello,
I see on the systemfit manual that you can estimate one-equation IV - I have
a variable, and need to test if it's endogeneous, but do not need to
estimate a system.
Does anyone have any examples of this? Do you just run OLS with the
endogenous variable, and then run a Hausmann to test endogeneity of OLS
resid. vs. IV resid?
Thanks in advance,
DM
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2010 Dec 27
0
Heteroskedasticity and autocorrelation of residuals
Hello everyone,
I'm working on a current linear model Y = a0 + a1* X1 + ... + a7*X7 +
residuals. And I know that this model presents both heteroskedasticity
(tried Breusch-Pagan test and White test) and residuals autocorrelation
(using Durbin Watson test). Ultimately, this model being meant to be used
for predictions, I would like to be able to remove this heteroskedasticity
and residuals
2013 Jun 23
1
2SLS / TSLS / SEM non-linear
Dear all, I try to conduct a SEM / two stage least squares regression with
the following equations:
First: X ~ IV1 + IV2 * Y
Second: Y ~ a + b X
therein, IV1 and IV2 are the two instruments I would like to use. the
structure I would like to maintain as the model is derived from economic
theory. My problem here is that I have trouble solving the equations to get
the reduced form so I can run