The 50 American States in Space and Time
Applying Conditionally Autoregressive Models
Bibliographic Data
| ID | 6445310 |
|---|---|
| Authors | Joshua Lee Monogan Jackson (0000-0003-1943-7168, University of Georgia), James E Monogan (0000-0002-1968-6052, University of Georgia, corresponding author) |
| Year | 2018 |
| Volume | 8 |
| Issue | 3 |
| Pages | 543-557 |
| Publication date | 2018-12-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Science Research and Methods (JOURNAL) |
| Journal identifiers | ISSN: 2049-8470 • E-ISSN: 2049-8489 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/psrm.2018.55 |
| OpenAlex | W2904955377 |
| Language | EN |
| References cited | 19 |
Spatial conditionally autoregressive (CAR) models in a hierarchical Bayesian framework can be informative for understanding state politics, or any similar population of border-defined observations. This article explains how a hierarchical CAR model is specified and estimated and then uses Monte Carlo analyses to show when the CAR model offers efficiency gains. We apply this model to data structures common to state politics: A cross-sectional example replicates Erikson, Wright and McIver’s (1993) Statehouse Democracy model and a multilevel panel model example replicates Margalit’s (2013) study of social welfare policy preferences. The CAR model fits better in each case and some inferences differ from models that ignore geographic correlation
Autoregressive model · Bayesian inference · Bayesian probability · Econometrics · Multilevel model · Population · Sociology · State space · Statistics · Wright · Computer Science · Demography · Electoral Systems and Political Participation · Mathematics · Social Policy and Reform Studies · Spatial and Panel Data Analysis
Spatial Regression Models
Theories of the Policy Process
Bayesian image restoration, with two applications in spatial statistics
Inference from Iterative Simulation Using Multiple Sequences
Whose Variance Is It Anyway? Interpreting Empirical Models with State-Level Data
Spatial Econometric Models of Cross-Sectional Interdependence in Political Science Panel and Time-Series-Cross-Section Data
The politics of immigrant policy in the 50 US states, 2005-2011
Bayesian Spatial Survival Models for Political Event Processes
Regression in Space and Time
Explaining Social Policy Preferences
Innovation in the States
State Lottery Adoptions as Policy Innovations
| Citation velocity | historical |
|---|---|
| Highly cited | No |