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Part 1: Document Description
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Citation |
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Title: |
"Replication Data for" Parameterizing Spatial Weight Matrices in Spatial Econometric Models |
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Identification Number: |
doi:10.7910/DVN/V9L9XC |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-08-05 |
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Version: |
1 |
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Bibliographic Citation: |
Elhorst, J.Paul, 2024, ""Replication Data for" Parameterizing Spatial Weight Matrices in Spatial Econometric Models", https://doi.org/10.7910/DVN/V9L9XC, Harvard Dataverse, V1 |
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Citation |
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Title: |
"Replication Data for" Parameterizing Spatial Weight Matrices in Spatial Econometric Models |
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Identification Number: |
doi:10.7910/DVN/V9L9XC |
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Authoring Entity: |
Elhorst, J.Paul (University of Groningen) |
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Producer: |
<i>Political Analysis</i> |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Elhorst, J.Paul |
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Depositor: |
Elhorst, J.Paul |
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Date of Deposit: |
2024-02-26 |
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Holdings Information: |
https://doi.org/10.7910/DVN/V9L9XC |
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Study Scope |
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Keywords: |
Social Sciences, Military Expenditures |
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Abstract: |
Abstract: Spatial econometric models allow for interactions among cross-sectional units through spatial weight matrices. This paper parameterizes each spatial weight matrix in the widely used spatial Durbin model with a different instead of one common distance decay parameter, using negative exponential and inverse distance matrices. We propose a joint estimation approach of the decay and response parameters and we investigate its performance in a Monte Carlo simulation experiment. We also present the results of an empirical application on military expenditures. Indirect effects in particular appear to be sensitive to different parameterizations. |
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Methodology and Processing |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Forthcoming, Political Analysis |
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Bibliographic Citation: |
Forthcoming, Political Analysis |
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Label: |
PAsubmissionR.zip |
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Text: |
Consult the README file for explanation and instructions |
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Notes: |
application/zip |