Assignment Instructions:

Go to IPUMS USA, and create an account if you don’t already have one.

!. Perform an extract of the 2019 5 Year ACS data.

  1. Select the PUMA variable from the Houshold Geographic variables.

  2. Select the MIGRATE1 variable from the Person>Migration variables.

  3. Select cases that only include the state of California.

  4. Using these data, create estimates for Californian PUMAs of the % of the population that lived in the same house last year.

  5. Produce a map of these estimates, and publish the map to Rpubs and submit the link to the site.

#downloading geo data for CA pumas
options(tigris_class = "sf")
pumas = pumas(state = "CA",
              year = "2019",
              cb = T)

Geographic Data for Public Use Microdata Areas (PUMAs) in California

This short report presents estimates for California PUMAs of the percentage of the population that remained in the same house in 2018 based on 2019 American Community Survey 5-year estimates.

plot(pumas["GEOID10"],
     main="Public Use Mircrodata Areas in California")

mapview::mapview(pumas, zcol="GEOID10")
data$pwt = data$perwt
data$hwt = data$hhwt

#recode outcome variable
data$migrate = as.numeric(data$migrate1) %>% 
Recode(data$migrate1, recodes = "1='same house';
                      2='moved within state';
                      3='moved between states';
                      4='moved abroad';
                      else=NA")
## Warning in if (as.factor) {: the condition has length > 1 and only the first
## element will be used
#generate survey design object
des = svydesign(ids = ~cluster,
                strata = ~strata,
                weights = ~pwt,
                data = data)



#perform survey estimation for pumas
puma_est_migrate = svyby(formula = ~migrate,
                        by = ~puma,
                        design = des,
                        FUN = svymean,
                        na.rm = T)
head(puma_est_migrate)

Map Estimates of Idleness Rates by PUMA

According to the map, residents living within PUMAs in SW California and coastal West PUMAs reported a higher percentage of living in the same home in 2018 compared to other California residents.

#join to geography
pumas$puma = as.numeric(pumas$PUMACE10)
geo_ca = left_join(pumas, puma_est_migrate, by=c("puma"="puma"))
head(geo_ca)
tmap_mode("view")
## tmap mode set to interactive viewing
map = geo_ca %>% 
  tm_shape()+
  tm_polygons("migratesame house",
              style = "kmeans",
              n = 7,
              legend.hist = T)+
  tm_layout(legend.outside = T,
            title = "Percentage of California Residents Who Remained in the Same House in 2018, California PUMAs \n 2014-2019")