Beyond the Unit Root Question
Uncertainty and Inference
Datos Bibliográficos
| ID | 6231502 |
|---|---|
| Autores | Christopher M Webb (0000-0001-6840-9476, University of Kansas), Clayton Webb, Suzanna Linn (0000-0001-7758-4137, Penn State University), Matthew J Lebo (0000-0003-0334-2703, University of Western Ontario) |
| Año | 2020 |
| Volumen | 64 |
| Número | 2 |
| Páginas | 275-292 |
| Fecha de publicación | 2020-04-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | American Journal of Political Science (JOURNAL) |
| Identificadores de la revista | ISSN: 0092-5853 • E-ISSN: 1540-5907 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ajps.12506 |
| OpenAlex | W3005811290 |
| Idioma | EN |
| Citas recibidas | 23 |
| Referencias citadas | 54 |
A fundamental challenge facing applied time‐series analysts is how to draw inferences about long‐run relationships (LRR) when we are uncertain whether the data contain unit roots. Unit root tests are notoriously unreliable and often leave analysts uncertain, but popular extant methods hinge on correct classification. Webb, Linn, and Lebo (WLL; 2019) develop a framework for inference based on critical value bounds for hypothesis tests on the long‐run multiplier (LRM) that eschews unit root tests and incorporates the uncertainty inherent in identifying the dynamic properties of the data into inferences about LRRs. We show how the WLL bounds procedure can be applied to any fully specified regression model to solve this fundamental challenge, extend the results of WLL by presenting a general set of critical value bounds to be used in applied work, and demonstrate the empirical relevance of the LRM bounds procedure in two applications
Data mining · Econometrics · Extant taxon · Inference · Machine learning · Relevance (law · Reliability engineering · Root (linguistics · Root cause · Set (abstract data type · Unit root · Value (mathematics · Artificial Intelligence · Complex Systems and Time Series Analysis · Computer Science · Engineering · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
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| Obras citantes distintas | 23 |
|---|---|
| Citas por año | 3,83 |
| Intervalo de citas | 2020 - 2026 (7) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 22 |