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Statements

Subject Item
n2:RIV%2F62156489%3A43110%2F13%3A00209699%21RIV14-MSM-43110___
rdf:type
skos:Concept n9:Vysledek
dcterms:description
As economic time series or cross sectional data are typically affected by serial correlation and/or heteroskedasticity of unknown form, panel data typically contains some form of heteroskedasticity, serial correlation and/or spatial correlation. Therefore, robust inference in the presence of heteroskedasticity and spatial dependence is an important problem in spatial data analysis. In this paper we study the standard errors based on the HAC of cross-section averages that follows Vogelsang's (2012) fixed-b asymptotic theory, i.e. we continue with Driscoll and Kraay approach (1998). The Monte Carlo simulations are used to investigate the finite sample properties of commonly used estimators both not accounting and accounting for heteroskedasticity and spatiotemporal dependence (OLS, GLS) in comparison to brand new estimator based on Vogelsang's (2012) fixed-b asymptotic theory in the presence of cross-sectional heteroskedasticity and serial and spatial correlation in panel data with fixed effects. Our Monte Carlo experiment shows that the OLS exhibits an important downward bias in all of the cases and almost always has the worst performance when compared to the other estimators. The GLS corrected for HACSC performs well if time dimension is greater than cross-sectional dimension. The best performance can be attributed to the Vogelsang's estimator with fixed-b version of Driscoll-Kraay standard errors. As economic time series or cross sectional data are typically affected by serial correlation and/or heteroskedasticity of unknown form, panel data typically contains some form of heteroskedasticity, serial correlation and/or spatial correlation. Therefore, robust inference in the presence of heteroskedasticity and spatial dependence is an important problem in spatial data analysis. In this paper we study the standard errors based on the HAC of cross-section averages that follows Vogelsang's (2012) fixed-b asymptotic theory, i.e. we continue with Driscoll and Kraay approach (1998). The Monte Carlo simulations are used to investigate the finite sample properties of commonly used estimators both not accounting and accounting for heteroskedasticity and spatiotemporal dependence (OLS, GLS) in comparison to brand new estimator based on Vogelsang's (2012) fixed-b asymptotic theory in the presence of cross-sectional heteroskedasticity and serial and spatial correlation in panel data with fixed effects. Our Monte Carlo experiment shows that the OLS exhibits an important downward bias in all of the cases and almost always has the worst performance when compared to the other estimators. The GLS corrected for HACSC performs well if time dimension is greater than cross-sectional dimension. The best performance can be attributed to the Vogelsang's estimator with fixed-b version of Driscoll-Kraay standard errors.
dcterms:title
Heteroskedasticity, temporal and spatial correlation matter Heteroskedasticity, temporal and spatial correlation matter
skos:prefLabel
Heteroskedasticity, temporal and spatial correlation matter Heteroskedasticity, temporal and spatial correlation matter
skos:notation
RIV/62156489:43110/13:00209699!RIV14-MSM-43110___
n9:predkladatel
n10:orjk%3A43110
n3:aktivita
n18:P
n3:aktivity
P(7E12049)
n3:cisloPeriodika
7
n3:dodaniDat
n11:2014
n3:domaciTvurceVysledku
n8:3445550 n8:4938364
n3:druhVysledku
n15:J
n3:duvernostUdaju
n13:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
77269
n3:idVysledku
RIV/62156489:43110/13:00209699
n3:jazykVysledku
n19:eng
n3:klicovaSlova
HAC estimator; spatial correlation; Monte Carlo simulation; panel data; heteroskedasticity; serial correlation
n3:klicoveSlovo
n7:Monte%20Carlo%20simulation n7:panel%20data n7:serial%20correlation n7:heteroskedasticity n7:spatial%20correlation n7:HAC%20estimator
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[E5C46E32CEAF]
n3:nazevZdroje
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
n3:obor
n4:AH
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n17:7E12049
n3:rokUplatneniVysledku
n11:2013
n3:svazekPeriodika
61
n3:tvurceVysledku
Střelec, Luboš Issever Grochová, Ladislava
s:issn
1211-8516
s:numberOfPages
5
n20:doi
10.11118/actaun201361072151
n14:organizacniJednotka
43110