Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call
Year of publication: |
2024
|
---|---|
Authors: | Pesaran, M. Hashem ; Song, Hayun |
Publisher: |
Munich : CESifo GmbH |
Subject: | voter turnout | popular and electoral college votes | simultaneity and recursive identification | high dimensional forecasting models | Lasso | OCMT |
Series: | CESifo Working Paper ; 11415 |
---|---|
Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 1906675775 [GVK] RePec:ces:ceswps:_11415 [RePEc] |
Classification: | C53 - Forecasting and Other Model Applications ; c55 ; D72 - Economic Models of Political Processes: Rent-Seeking, Elections, Legistures, and Voting Behavior |
Source: |
-
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Forecasting 2024 US presidential election by states using county level data : too close to call
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