similar to: Newey West HAC-errors for panels

Hello: My dataset set contains several thousand rows of data, with each row containing information for a house. The variables include the sale price of the house, the quarter and year of sale, the attributes of the house, and the attributes of the neighborhood and the city in which the house is located. The data is for a 10-year period. No house is repeated in the dataset. In summary, the dataset

Hi, Does anyone read Verbeek's "A Guide to Modern Econometrics"? In its Section 4.11, how does the last two equations' HAC calculate? I've tried several groups of parameters in sandwich::NeweyWest, but I still cannot get the same result. I've tried lag=2 and lag=3, as long as prewhite=FALSE and prewhite=TRUE yet, but... Sincerely Hsiao-nan Cheung

Dear R-users, has anybody combined the glm function with the Newey-West estimator of variance, similar as in Stata 7.0? I'd like to estimate corrected standard errors within a logistic regression model, taking into account the auto-correlated binary observations within individuals. I use R1.5.1 on Mac OS X (10.2). Thanks, Christof

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

Hi, I want to calculate the t- and p-values for a linear model using the Newey West estimator. I tried this Code and it usually worked just fine: > oberlm <- lm(DYH ~ BIP + Infl + EOil, data=HU_H) > coeftest(oberlm, NeweyWest(oberlm, lag=2)) t test of coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.1509950 0.0743832 2.0300 0.179486 BIP

Is anyone aware of a procedure to apply Newey-West corrections for autocorrelation to a SUR regression model? The SANDWICH package seems to be applicable only to LM or GLM models. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric at auburn.edu

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

Hi All, I am using R 2.11.0 on a Ubuntu machine. I estimated a model using "tsls" from the package "sem". Is there a way to get Newey West standard errors for the parameter estimates? When estimating the model by OLS, I used "NeweyWest" from the package "sandwich" to get HAC standard errors. But, I am not able to use the same method with the results of the

# Using Moving/Rolling Windows, here we do an OLS Regression with corrections for #Heteroscedasticity and Autocorrelations (HAC) using Newey West Method. This code is a #extension of Ajay Shah?s code for moving windows simple OLS regression. # The easiest way to adjust for Autocorrelations and Heteroscedasticity in the OLS residuals is to #use the coeftest function that is included in the

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:

Hello, I would like to estimate a VAR model with HAC corrected standard errors. I tried to do this by using the sandwich package, for example: > library(vars) > data(Canada) > myvar = VAR(Canada, p = 2, type = "const") > coeftest(myvar, vcov = vcovHAC) Error in umat - res : non-conformable arrays Which suggests that this function is not compatible with the VAR command.

Dear all, I am working on a large dataset and need to use biglm() to perform OLS regressions. I have detected significant ARCH effects which I try to account for using the Newey-West correction. So far, I have worked with NeweyWest() in the sandwich package. NeweyWest() however seems to be unable to handle an object of class "biglm". Looking into the code, I figured out that

I want to calculate Newey West robust standard error using NeweyWest. Comparing the results to what I get in STATA, in order to get the same results in I need to specify "prewhite=0". Can someone explain what this prewhite command means? Thanks [[alternative HTML version deleted]]

Dear R-users, I would like to compute a robust covariance matrix of two series of realizations of random variables: ###Begin Example### data <- cbind(rnorm(100), rnorm(100)) model <- lm(data ~ 1) vcov(model) library(sandwich) NeweyWest(model) #produces an error ###End Example### NeweyWest() produces an error but sandwich(), vcovHAC(), kernHAC, weave(),... do not produce any errors. It

Hi, I think he's talking about how much a statistical estimator is influenced by extreme datapoints, e.g. https://en.m.wikipedia.org/wiki/Robust_statistics#Breakdown_point Olivier -- Olivier Crouzet Assistant Professor @LLING UMR6310 - Universit? de Nantes / CNRS Guest Scientist @UMCG - University Medical Center Groningen / RijksUniversiteit Groningen > Le 19 avr. 2018 ? 11:00,

On 15/04/2018 17:26, Marc Girondot via R-help wrote: > Le 15/04/2018 ? 17:56, alireza daneshvar a ?crit?: >> break-down point > > Can you explain more what you plan to do and give an example of what you > have tried to do until now to do a "break down point" in R. Perhaps a > "break down point" is common in your field, but I have no idea about > what

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both

Hi there, is it possible in r to use the Initial partition established by using the HAC partition with the kmean clustering? E.g. perform the HCA, write the cluster affiliation in a seperate column > DF$hclus.label <- assignCluster(model.matrix(~-1 + A15 + B12 + C70 + E14 + + H61 + N56 + P48 + T69 + W32 + Y43, DF), DF, cutree(HClust.1, k = 3) -> use this as initial partition in the

Dear everyone: I am doing a research on several stock markets. And I need to construct an Bartlett HAC covariance matrix estimator for Sigma(Cov(Y0,Yj)), j is from 0 to T. Can you tell me how to do it. Your Sincerely! Nigel Gregory 01/09/11 [[alternative HTML version deleted]]

Hi, how to estimate a the following model in R: y(t)=beta0+beta1*x1(t)+beta2*x2(t)+...+beta5*x5(t)+beta6*y(t-1)+beta7*y(t-2)+beta8*y(t-3) 1) using "lm" : dates &lt;- as.Date(data.df[,1]) selection&lt;-which(dates&gt;=as.Date("1986-1-1") &amp; dates&lt;=as.Date("2007-12-31")) dep &lt;- ts(data.df[selection,c("dep")]) indep.ret1