Measurement Models for Time Series Analysis
Estimating Dynamic Linear Errors-in-Variables Models
Bibliographic Data
| ID | 7971047 |
|---|---|
| Authors | Gregory E Mcavoy (corresponding author) |
| Year | 1998 |
| Volume | 7 |
| Pages | 165-186 |
| Publication date | 1998-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Analysis (JOURNAL) |
| Journal identifiers | ISSN: 1047-1987 • E-ISSN: 1476-4989 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1093/pan/7.1.165 |
| OpenAlex | W2328299108 |
| Language | EN |
| Citations received | 2 |
| References cited | 20 |
This article uses state space modeling and Kalman filtering to estimate a dynamic linear errors-in-variables model with random measurement error in both the dependent and independent variables. I begin with a general description of the dynamic errors-in-variables model, translate it into state space form, and show how it can be estimated via the Kalman filter. I report the results of a simulation in which the amount of random measurement error is varied, to demonstrate the importance of estimating measurement error models and the superiority that Kalman filtering has over regression. I use the model in a substantive example to examine the effects of public opinion regarding nuclear power on the enforcement decisions of the Nuclear Regulatory Commission. I then estimate a dynamic linear errors-in-variables model using multiple indicators for the latent variables and compare simulations of this model to the single indicator model. Finally, I provide substantive examples which examine the effect of people's economic expectations on their approval of the president and their approval of government more generally
Algorithm · Econometrics · Errors-in-Variables Models · Kalman filter · Latent variable · Linear model · Linear regression · Observational error · Regression analysis · Series (stratigraphy · State space · State variable · State-space representation · Statistics · Variables · Computer Science · Electoral Systems and Political Participation · Mathematics · Monetary Policy and Economic Impact · Risk Perception and Management
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| Unique citing works | 2 |
|---|---|
| Citations per year | 0,29 |
| Citation span | 2019 - 2024 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |