Pollution and Expenditures in a Penalized Vector Spatial Autoregressive Time Series Model with Data-Driven Networks
This paper introduces a Spatial Vector Autoregressive Moving Average (SVARMA) model in which multiple cross-sectional time series are modeled as multivariate, possibly fat-tailed, spatial autoregressive ARMA processes. The estimation requires speci...
| Main Authors: | , , , , , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2019
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/162631551119359071/Pollution-and-Expenditures-in-a-Penalized-Vector-Spatial-Autoregressive-Time-Series-Model-with-Data-Driven-Networks http://hdl.handle.net/10986/31331 |