| Policy_Opinion {bqror} | R Documentation |
Data contains public opinion on the proposal to raise federal income taxes for couples (individuals) earning more than $250,000 ($200,000) per year and a host of other covariates. The data is taken from the 2010-2012 American National Election Studies (ANES) on the Evaluation of Government and Society Study I (EGSS 1)
Description
Data contains public opinion on the proposal to raise federal income taxes for couples (individuals) earning more than $250,000 ($200,000) per year and a host of other covariates. The data is taken from the 2010-2012 American National Election Studies (ANES) on the Evaluation of Government and Society Study I (EGSS 1)
Usage
data(Policy_Opinion)
Details
The data consists of 1,164 observations taken from the 2010-2012 American National Election Studies (ANES) on the Evaluations of Government and Society Study 1 (EGSS 1). The objective is to analyze public opinion on the proposal to raise federal income taxes for couples (individuals) earning more than $250,000 ($200,000) per year. The responses were recorded as oppose, neither favor nor oppose, or favor the tax increase, and forms the dependent variable in the study. The independent variables include indicator variables (or dummy) for employment, income above $75,000, bachelor's and post-bachelor's degree, computer ownership, cellphone ownership, and white race.
Value
Returns data with components
Intercept: |
Column of ones. |
EmpCat: |
Indicator for employment status. |
IncomeCat: |
Indicator for household income > $75,000. |
Bachelors: |
Individual's highest degree is Bachelors. |
Post.Bachelors: |
Indicator for highest degree is Masters, Professional or Doctorate. |
Computers: |
Indicator for computer ownership by individual or household. |
CellPhone: |
Indicator for cellphone ownership by individual or household. |
White: |
Indicator for White race. |
y: |
Public opinion on the proposal to raise federal income taxes. The three categories are: oppose, neither favor nor oppose, or favor the tax increase. |
References
Rahman, M. A. (2016). '"Bayesian Quantile Regression for Ordinal Models."' Bayesian Analysis, 11(1): 1-24. DOI: 10.1214/15-BA939