The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Testing for Cross-Sectional Dependence in Panel-Data Models
Open accessAbstract
This article describes a new Stata routine, xtcsd, to test for the presence of cross-sectional dependence in panels with many cross-sectional units and few time-series observations. The command executes three different testing procedures—namely, Friedman's ( Journal of the American Statistical Association 32: 675–701) (FR) test statistic, the statistic proposed by Frees ( Journal of Econometrics 69: 393–414), and the cross-sectional dependence (CD) test of Pe-saran ( General diagnostic tests for cross-section dependence in panels [University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics, Paper No. 0435]). We illustrate the command with an empirical example.
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Cites
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
The use of ranks to avoid the assumption of normality implicit in the analysis of variance
Friedman, M. (1937) · Journal of the American Statistical Association · doi:10.1080/01621459.1937.10503522 · Cited by 7,005
Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
Driscoll, J. C., & Kraay, A. C. (1998) · Review of Economics and Statistics · doi:10.1162/003465398557825 · Cited by 6,865
Estimating long-run relationships from dynamic heterogeneous panels
Pesaran, M. H., & Smith, R. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01644-f · Cited by 5,479 · cited 1×
“See, for example, Robertson and Symons (2000), Pesaran (2004), Anselin (2001), and Baltagi (2005, sec.”
Research works printed but not linked: 15
- 10.1080/01621459.1981.10477691 · DOI · Paper page
- Anselin L., 2001, A Companion to Theoretical Econometrics, 310
- 10.2307/2297968 · DOI · Paper page
- Baltagi B. H., 2005, Econometric Analysis of Panel Data.
- 10.1007/BF01205444 · DOI · Paper page
- 10.1177/1536867X0100100108 · DOI · Paper page
- 10.1177/1536867X0300300211 · doi:10.1177/1536867x0300300211
- 10.1177/1536867X0400400214 · doi:10.1177/1536867x0400400214
- 10.2307/2297111 · DOI · Paper page
- 10.1016/0304-4076(94)01658-M · DOI · Paper page
- 10.1017/CBO9780511790928 · DOI · Paper page
- Munnell A., 1990, New England Economic Review, 3
- Pesaran M. H., 2004, General diagnostic tests for cross section dependence in panels., 10.2139/ssrn.572504 · DOI · Paper page
- 10.1111/j.1468-0262.2006.00692.x · DOI · Paper page
- 10.1111/1368-423X.00108 · DOI · Paper page
Cited by
Panel Data Econometrics in R : The plm Package
Croissant, Y., & Millo, G. (2008) · Journal of Statistical Software · doi:10.18637/jss.v027.i02 · Cited by 1,243
Shahbaz, M., Nasreen, S., Ahmed, K., & Hammoudeh, S. (2017) · Energy Economics · doi:10.1016/j.eneco.2016.11.008 · Cited by 518
Khan, I., Hou, F., Irfan, M., Zakari, A., & Le, H. P. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111157 · Cited by 363
Dhahri, S., & Omri, A. (2018) · World Development · doi:10.1016/j.worlddev.2018.01.008 · Cited by 361
Zhang, C., Khan, I., Dagar, V., Saeed, A., & Zafar, M. W. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121570 · Cited by 340
Metadata
- Authors
- De Hoyos, R. E., & Sarafidis, V.
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2006-11
- Volume
- 6
- Issue
- 4
- Pages
- 482-496
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W1543166152
- Cited by
- 1,373
- References
- 5
- FWCI
- 23.09
- Type
- journal article
- Language
- en
- Open access
- bronze
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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- De Hoyos, R. E., & Sarafidis, V. (2006). Testing for Cross-Sectional Dependence in Panel-Data Models. The Stata Journal: Promoting communications on statistics and Stata. https://doi.org/10.1177/1536867x0600600403
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
