HETEROSKEDASTICITY ROBUST SPECIFICATION TESTING IN SPATIAL AUTOREGRESSION Article Swipe
Jung-Yoon Lee
,
Peter C.B. Phillips
,
Francesca Rossi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1017/s0266466624000173
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1017/s0266466624000173
Spatial autoregressive (SAR) and related models offer flexible yet parsimonious ways to model spatial and network interactions. SAR specifications typically rely on a particular parametric functional form and an exogenous choice of the so-called spatial weight matrix with only limited guidance from theory in making these specifications. Also, the choice of a SAR model over other alternatives, such as spatial Durbin (SD) or spatial lagged X (SLX) models, is often arbitrary, raising issues of potential specification error. To address such issues, this paper develops a new specification test within the SAR framework that can detect general forms of misspecification including that of the spatial weight matrix, the functional form and the model itself. The test is robust to the presence of heteroskedasticity of unknown form in the disturbances and the approach relates to the conditional moment test framework of Bierens ([1982, Journal of Econometrics 20, 105–134], [1990, Econometrica 58, 1443–1458]). The Bierens test is shown to be inconsistent in general against spatial alternatives and the new test introduces modifications to achieve test consistency in the spatial setting. A central element is the infinite-dimensional endogeneity induced by spatial linkages. This complexity is addressed by introducing a new component to the omnibus test that captures the effects of potential spatial matrix misspecification. With this modification, the approach leads to a simple pivotal test procedure with standard critical values that is the first test in the literature to have power against misspecifications in the spatial linkages. We derive the asymptotic distribution of the test under the null hypothesis of correct SAR specification and prove consistency. A Monte Carlo study is conducted to study its finite sample performance. An empirical illustration on the performance of the test in modeling tax competition in Finland is included.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1017/s0266466624000173
- https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B344C755A8B2DFC47749A51B3E3C2DE7/S0266466624000173a.pdf/div-class-title-heteroskedasticity-robust-specification-testing-in-spatial-autoregression-div.pdf
- OA Status
- hybrid
- Cited By
- 1
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4398180396
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https://openalex.org/W4398180396Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1017/s0266466624000173Digital Object Identifier
- Title
-
HETEROSKEDASTICITY ROBUST SPECIFICATION TESTING IN SPATIAL AUTOREGRESSIONWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-05-21Full publication date if available
- Authors
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Jung-Yoon Lee, Peter C.B. Phillips, Francesca RossiList of authors in order
- Landing page
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https://doi.org/10.1017/s0266466624000173Publisher landing page
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B344C755A8B2DFC47749A51B3E3C2DE7/S0266466624000173a.pdf/div-class-title-heteroskedasticity-robust-specification-testing-in-spatial-autoregression-div.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B344C755A8B2DFC47749A51B3E3C2DE7/S0266466624000173a.pdf/div-class-title-heteroskedasticity-robust-specification-testing-in-spatial-autoregression-div.pdfDirect OA link when available
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Heteroscedasticity, Mathematics, Econometrics, Autoregressive model, Vector autoregressionTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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58Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I184558857 |
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