| Title |
A multi-regional generalized RAS updating technique |
| Authors |
Temursho, Umed , Oosterhaven, Jan , CARDENETE FLORES, MANUEL ALEJANDRO |
| External publication |
No |
| Means |
Spat. Econ. Anal. |
| Scope |
Article |
| Nature |
Científica |
| JCR Quartile |
2 |
| SJR Quartile |
1 |
| JCR Impact |
2.31700 |
| SJR Impact |
0.68600 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095768534&doi=10.1080%2f17421772.2020.1825782&partnerID=40&md5=6c352e607004ef264cef077aaca91248 |
| Publication date |
01/01/2021 |
| ISI |
000584191900001 |
| Scopus Id |
2-s2.0-85095768534 |
| DOI |
10.1080/17421772.2020.1825782 |
| Abstract |
We present an extension of the generalized RAS (GRAS) technique to a multi-regional (MR) or multi-national setting. The framework is applicable to updating/regionalizing/balancing any partitioned matrix that needs to conform to new row sums, column sums and additional non-overlapping aggregation constraints. The technique, which we refer to as MR-GRAS, also handles non-exhaustive constraints, in which case the missing values are endogenously generated in the updating process. We derive the closed-form solution of MR-GRAS, propose a simple iterative algorithm for its computation, and discuss the main analytical properties of the method as well as the normalization and interpretation of MR-GRAS multipliers. From a wide range of possible MR-GRAS applications, several updating frameworks of national and interregional supply and use tables are examined. |
| Keywords |
RAS; multiregional GRAS; partitioned matrix updating; non-survey regionalization methods |
| Universidad Loyola members |
|
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