An essay on 'combined' time series processes
Bibliographic Data
| ID | 4170085 |
|---|---|
| Authors | Christopher Wlezien (0000-0002-0719-697X, University of Houston, corresponding author) |
| Year | 2000 |
| Volume | 19 |
| Issue | 1 |
| Pages | 77-93 |
| Publication date | 2000-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Electoral Studies (JOURNAL) |
| Journal identifiers | ISSN: 0261-3794 • E-ISSN: 1873-6890 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/s0261-3794(99)00037-2 |
| OpenAlex | W2085358982 |
| Language | EN |
| Citations received | 17 |
| References cited | 26 |
Algorithm · Component (thermodynamics · Econometrics · Machine learning · Order of integration (calculus · Physics · Process (computing · Series (stratigraphy · Sociology · Stationary process · Statistical physics · Suspect · Time series · Computer Science · Electoral Systems and Political Participation · Mathematics · Monetary Policy and Economic Impact · Applied Mathematics
Political Choice in Britain
Long Memory Methods and Structural Breaks in Public Opinion Time Series
The economy, crime and time
Presidential Election Polls in 2000
The state house prices make
Opinion–Policy Dynamics
The Timeline of Presidential Election Campaigns
Polls and the Vote in Britain
Detecting true relationships in time series data with different orders of integration
Mass Media and Electoral Preferences During the 2016 US Presidential Race
Valence as Macro-Competence
Campaign Effects in Theory and Practice
Public Ideology and Political Dynamics in the United States
Persistence and aggregations of survey data over time
On filtering longitudinal public opinion data
Campaign trial heats as electoral information
Modelling memory and volatility
Ideology and discontent
Long-run economic relationships
Long memory relationships and the aggregation of dynamic models
An Introduction to Long‐memory Time Series Models and Fractional Differencing
Distribution of the Estimators for Autoregressive Time Series With a Unit Root
Distribution of the Estimators for Autoregressive Time Series with a Unit Root
Public Opinion in America
What Moves Macropartisanship? A Response to Green, Palmquist, and Schickler
Mass Political Attitudes and the Survey Response
Peasants or Bankers? The American Electorate and the U.S. Economy
Comparing Dynamic Specifications
An Essay on Cointegration and Error Correction Models
Error Correction, Attitude Persistence, and Executive Rewards and Punishments
The Methodology of Cointegration
The Public as Thermostat
Investigating Political Dynamics Using Fractional Integration Methods
Near-Integrated Data and the Analysis of Political Relationships
Dynamics of Representation
The SRC Panel Data and Mass Political Attitudes
Persistence and aggregations of survey data over time
You must remember this
The Dynamics of Aggregate Partisanship
What Moves Policy Sentiment
| Unique citing works | 17 |
|---|---|
| Citations per year | 0,65 |
| Citation span | 2000 - 2024 (25) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 17 |