Code
library(tidyverse)
knitr::opts_chunk$set(echo = TRUE)Final Project 1
finalpart1
desriptive statistics
probability
Research Question
How much does state policy intervention impact future social and economic value preferences in residents?
While political values often explicitly inform social and economic policy actions taken by governments, policy actions themselves can also affect the development of the values of both program recipients and the greater public. Low-income recipients are assumed to benefit from, and therefore favor, state intervention and redistributive policies while upper income groups are assumed to be against but this is not always true, especially at the program level (Bueno et al.). Authors like Holland note that “the poor only have an economic interest in supporting social expenditures in contexts where they expect policies to redistribute resources or risks in their favor”.
This study seeks to better understand the relationship between policy action and value formation at the sub-national level by looking at the effect of US state policy interventions on residents’ subsequent policy preferences. By looking at how differences in US states’ social and economic policy intervention from 1936 to 2000 we can see how these factors may shape the subsequent policy values of residents. The dataset “Correlates of State Policy” includes variables which also allow us to better understand the role of differences in policy design and implementation by controlling for variables that may moderate impact, such as the length of policy implementation (Soss) and differences in economic interest (Ansell).
Sources:
Ansell, Ben. 2014. “The Political Economy of Ownership.” American Political Science Review 108(02):383{402.
Boehmke, Frederick J., and Paul Skinner. 2012. “State Policy Innovativeness Revisited.” State Politics and Policy Quarterly, 12(3):303-29.
Bueno, Natalia and Nunes, Felipe and Zucco, Cesar, Making the bourgeoisie? Values, voice, and state-provided homeownership (January 7, 2022). SSRN.
Caughey, Devin, and Christopher Warshaw. 2015. “The Dynamics of State Policy Liberalism, 1936–2014.” American Journal of Political Science, September. doi: 10.1111/ajps.12219.
Holland, Alisha C. 2018. “Diminished Expectations: Redistributive preferences in truncated welfare states.” World Politics 70(4):555{594
Jacoby, William G., and Saundra K. Schneider. 2008. “A New Measure of Policy Spending Priorities in the American States.”
Jordan, Marty P. and Matt Grossmann. 2016. The Correlates of State Policy Project v.1.10. East Lansing, MI: Institute for Public Policy and Social Research (IPPSR).
Rigby, Elizabeth and Gerald C. Wright. 2013. “Political Parties and Representation of the Poor in the American States.” American Journal of Political Science 57(3): 552-565.
Soss, Joe. 1999. “Lessons of Welfare: Policy Design, Political Learning, and Political Action.” The American Political Science Review 93(2):363{380.
Hypothesis
Increased state intervention increases US state residents’ preference for future interventions in social and economic policy.
This study proposes to build on Bueno et al.’s exploration of the effects of state-provided home ownership on political values and policy preferences by exploring that relationship at the level of US states. Additionally, instead of focusing on a single social program, we will examine the cumulative effects of multiple policy interventions across 65 years in 50 US states. This will provide insights into the effect of public policy on value differences at the sub-national level and on different subgroups including program non-participants. We will be able to see how this relationship may vary according to state and population characteristics despite differences in policy design and implementation.
Descriptive Statistics
This dataset is from the Correlates of State Policy Project by the Institute for Public Policy and Social Research at Michigan State University. The full dataset, which contains 928 variables and covers data from 1900 to 2016, draws from multiple sources including government agencies and peer-reviewed articles listed in the Sources section. Due to limited data coverage across all years however, this study will focus on the period from 1935 to 2000. We will examining the following 25 variables (listed with description and years available):
Independent-
Year 1935 - 2000
State 1935 - 2000
Econdev - Did State adopt Strategic Planning for Economic Development? 1981 – 1992
Pldvpag - Did State adopt Planning/Development Agency? 1935 – 1978
Urbrenen - Did State adopt Urban Renewal ? 1941 – 1952
Pollib_median - State Policy Liberalism Score – Median 1936 – 2014
Policypriorityscore - State Policy Priority Score - collective goods (e.g., education and highways) v particularized benefits (e.g., health care and welfare) 1982-2005
Poptotal - Population Total 1900 – 2008
Popfemale - Female Population 1994 – 2010
Nonwhite - Proportion of the population that is nonwhite 1974 - 2011
Soc_capital_ma - Hawes et al. Weighted Moving Average Measure of Social Capital 1984 - 2011
Evangelical_pop - Evangelical Population 1975 - 2013
Newimmig - New Immigrant Green Card Holders 1988 – 2011
Popdensity - Population Density 1975 – 1999
Gsp_q - Gross State Product Combined in Millions of 2016 Dollars 1963 – 2010
Gini_coef - Gini Coefficient 1917 - 2013
Hsdiploma - High School Diploma 1975 – 2006
Educspend - State Education Spending 1975 – 2001
Nofelons - Number of Felons Ineligible to Vote 1980 – 2010
Co2emissions - Total CO2 emissions from fossil-fuels (metric tons) 1960 – 2001
Ideo - State Ideology Score 1976 – 2011
Dependent-
Vst_ec - Mean Economic Liberalism- All Voters 2000
Vst_soc - Mean Social Liberalism- All Voters 2000
Vavgec_low - Mean Economic Liberalism Score for Low Income Voting Citizens 2000
Vavgsoc_low - Mean Social Liberalism Score for Low Income Voting Citizens 2000
Reading in dataset
Code
library(readr)
library(readxl)
statedata <- read.csv("_data/correlatesofstatepolicyprojectv1_10.csv")Specifying variables
Code
statedata1 = subset(statedata, select = c(policypriorityscore, econdev, pldvpag, urbrenen, year, state, poptotal, popfemale, nonwhite, soc_capital_ma, evangelical_pop, newimmig, popdensity, gsp_q, gini_coef, hsdiploma, educspend, nofelons, co2emissions, ideo, pollib_median,vst_ec, vst_soc, vavgec_low, vavgsoc_low))Specifying date range
Code
sd <- subset(statedata1, year>1934 & year<2001, na.rm = TRUE ) Descriptive statistics
Code
str(sd)'data.frame': 3366 obs. of 25 variables:
$ policypriorityscore: num NA NA NA NA NA NA NA NA NA NA ...
$ econdev : int 0 0 0 0 0 0 0 0 0 0 ...
$ pldvpag : int 0 0 0 0 0 0 0 0 0 0 ...
$ urbrenen : int 0 0 0 0 0 0 0 0 0 0 ...
$ year : int 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 ...
$ state : chr "Alaska" "Alaska" "Alaska" "Alaska" ...
$ poptotal : int NA NA NA NA NA NA NA NA NA NA ...
$ popfemale : int NA NA NA NA NA NA NA NA NA NA ...
$ nonwhite : num NA NA NA NA NA NA NA NA NA NA ...
$ soc_capital_ma : num NA NA NA NA NA NA NA NA NA NA ...
$ evangelical_pop : num NA NA NA NA NA NA NA NA NA NA ...
$ newimmig : int NA NA NA NA NA NA NA NA NA NA ...
$ popdensity : num NA NA NA NA NA NA NA NA NA NA ...
$ gsp_q : int NA NA NA NA NA NA NA NA NA NA ...
$ gini_coef : num NA NA NA NA NA NA NA NA NA NA ...
$ hsdiploma : num NA NA NA NA NA NA NA NA NA NA ...
$ educspend : int NA NA NA NA NA NA NA NA NA NA ...
$ nofelons : int NA NA NA NA NA NA NA NA NA NA ...
$ co2emissions : int NA NA NA NA NA NA NA NA NA NA ...
$ ideo : num NA NA NA NA NA NA NA NA NA NA ...
$ pollib_median : num NA NA NA NA NA NA NA NA NA NA ...
$ vst_ec : num NA NA NA NA NA NA NA NA NA NA ...
$ vst_soc : num NA NA NA NA NA NA NA NA NA NA ...
$ vavgec_low : num NA NA NA NA NA NA NA NA NA NA ...
$ vavgsoc_low : num NA NA NA NA NA NA NA NA NA NA ...Code
glimpse(sd)Rows: 3,366
Columns: 25
$ policypriorityscore <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ econdev <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
$ pldvpag <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
$ urbrenen <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
$ year <int> 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 19…
$ state <chr> "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", …
$ poptotal <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ popfemale <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ nonwhite <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ soc_capital_ma <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ evangelical_pop <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ newimmig <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ popdensity <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ gsp_q <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ gini_coef <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ hsdiploma <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ educspend <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ nofelons <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ co2emissions <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ ideo <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ pollib_median <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ vst_ec <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ vst_soc <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ vavgec_low <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ vavgsoc_low <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…Code
summary(sd) policypriorityscore econdev pldvpag urbrenen
Min. :-0.2296 Min. :0.00000 Min. :0.0000 Min. :0.0000
1st Qu.:-0.0372 1st Qu.:0.00000 1st Qu.:1.0000 1st Qu.:0.0000
Median : 0.0144 Median :0.00000 Median :1.0000 Median :1.0000
Mean : 0.0093 Mean :0.09364 Mean :0.7703 Mean :0.5327
3rd Qu.: 0.0638 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:1.0000
Max. : 0.1987 Max. :1.00000 Max. :1.0000 Max. :1.0000
NA's :2416 NA's :66 NA's :66 NA's :66
year state poptotal popfemale
Min. :1935 Length:3366 Min. : 100000 Min. : 236763
1st Qu.:1951 Class :character 1st Qu.: 960954 1st Qu.: 645293
Median :1968 Mode :character Median : 2600000 Median : 1900000
Mean :1968 Mean : 3892303 Mean : 2692111
3rd Qu.:1984 3rd Qu.: 4700000 3rd Qu.: 3100000
Max. :2000 Max. :34000000 Max. :17000000
NA's :30 NA's :3009
nonwhite soc_capital_ma evangelical_pop newimmig
Min. :0.0048 Min. :-2.9133 Min. : 1.10 Min. : 159
1st Qu.:0.0785 1st Qu.:-0.4193 1st Qu.: 9.60 1st Qu.: 1518
Median :0.1360 Median : 0.2357 Median :14.10 Median : 3973
Mean :0.1752 Mean : 0.3108 Mean :18.83 Mean : 18447
3rd Qu.:0.2586 3rd Qu.: 1.0615 3rd Qu.:26.00 3rd Qu.: 11424
Max. :0.7130 Max. : 3.0868 Max. :74.00 Max. :732735
NA's :2016 NA's :2550 NA's :2066 NA's :2703
popdensity gsp_q gini_coef hsdiploma
Min. : 0.6496 Min. : 993 Min. :0.3215 Min. : 0.00
1st Qu.: 31.2611 1st Qu.: 12325 1st Qu.:0.4324 1st Qu.:73.90
Median : 85.3188 Median : 31568 Median :0.4667 Median :76.80
Mean : 163.7982 Mean : 74118 Mean :0.4766 Mean :75.94
3rd Qu.: 165.7868 3rd Qu.: 83769 3rd Qu.:0.5147 3rd Qu.:80.80
Max. :1082.7000 Max. :1300000 Max. :0.7172 Max. :91.80
NA's :2116 NA's :1428 NA's :48 NA's :2054
educspend nofelons co2emissions ideo
Min. : 0.0 Min. : 0 Min. : 4.00 Min. :-0.5806
1st Qu.: 816.2 1st Qu.: 4668 1st Qu.: 24.00 1st Qu.:-0.2157
Median : 1809.5 Median : 15733 Median : 60.00 Median :-0.1392
Mean : 3421.9 Mean : 34844 Mean : 88.28 Mean :-0.1364
3rd Qu.: 4058.0 3rd Qu.: 41280 3rd Qu.:107.50 3rd Qu.:-0.0625
Max. :35482.0 Max. :499362 Max. :669.00 Max. : 0.4545
NA's :2054 NA's :2805 NA's :1275 NA's :2129
pollib_median vst_ec vst_soc vavgec_low
Min. :-2.32065 Min. :-0.367 Min. :-0.379 Min. :-0.387
1st Qu.:-0.66509 1st Qu.:-0.171 1st Qu.:-0.163 1st Qu.: 0.021
Median :-0.07600 Median :-0.094 Median :-0.001 Median : 0.108
Mean :-0.01096 Mean :-0.094 Mean :-0.024 Mean : 0.079
3rd Qu.: 0.68865 3rd Qu.:-0.047 3rd Qu.: 0.106 3rd Qu.: 0.174
Max. : 2.57199 Max. : 0.147 Max. : 0.357 Max. : 0.290
NA's :114 NA's :3319 NA's :3319 NA's :3319
vavgsoc_low
Min. :-0.466
1st Qu.:-0.200
Median :-0.093
Mean :-0.073
3rd Qu.: 0.052
Max. : 0.377
NA's :3319