To download the Stata code and some ancillary files
for the paper “Household Expenditures, Wages, Rents”
click here (.zip
file).
Notes:
|
Users will need to register with IPUMS (for free) to download 1980, 1990, and 2000 DCH data. The IPUMS data are available here: http://usa.ipums.org/usa/ In our data work, we use the 1% sample for 1980, 1990 and 2000 (rectangular). The variables we downloaded for this project are listed at the end of this document. Once the IPUMS data are downloaded and converted from ASCII to Stata data sets, users will need to run the Stata code ipums_to_fips.do. This converts the IPUMS MSA codes to more standard FIPS code. The files will then need to be saved as Stata files with the following names: 1980census_ind, 1990census_ind, 2000census_ind. After that, users will need to run davisom1.do and davisom2.do to replicate the results of Tables 1, 2 and the first two columns of Table 3. For each IPUMS census year (1980, 1990, 2000)
davisom2.do produces one
files. Using the year 2000 as an
example, the file produced is 2000.expratio.csv. The three variables in this file are For each IPUMS census year (1980, 1990, 2000) davisom1.do produces two files. Using the year 2000 as an example, the files produced are 2000_avg_renter_inc.csv and 2000_results_rent.csv. The variables produced by 2000_avg_renter_inc.csv are The variables produced by 2000_results_rent.csv are */ *********************************************** */ report correlation of inverse of ratio and my_income */ (should be 1.0) */ *********************************************** quietly gen inv_ratio = 1/ratio if ratio!=. quietly gen linv_ratio = log(inv_ratio) if inv_ratio!=.
*/ *********************************************** */ determine deviation from average */ *********************************************** quietly egen temp = mean(linv_ratio) if linv_ratio!=. quietly gen deviation = linv_ratio-temp if linv_ratio!=.
*/ *********************************************** */ age of highest income earner */ *********************************************** gen high_income = 1 quietly gsort include_wage serial -incwage quietly by include_wage serial: replace high_income = sum(high_income) quietly replace high_income = . if include_wage!=1
*/ *********************************************** */ regress deviation on agebin of primary respondent */ *********************************************** reg deviation imyage* if deviation!=. & high_income==1, noconstant Finally, to replicate the results of Table 4: This is more involved – users will need to pay for year-2000 ACCRA data. If users organize the ACCRA data (stored in a file called accra.2000.csv) in columns as: QUARTER, YEAR, STATE_CODE, CBSA_CODE, CITY_CODE, STATE_NAME, METRO_MICRO_NAME, URBAN_AREA_NAME, COMPOSITE_INDEX, GROCERY_ITEMS, HOUSING, UTILITIES, TRANSPORTATION, HEALTH_CARE, MISC_GOODS_SERVICES. Then users can run the Stata file accra.do, which uses the file fips.csv and then exports the file accra_cons_prices.2000.csv. This file includes the variables fips: The same fips code used by davisom1.do and davisom2.do |
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Extract Request Summary The variable EDUCREC was removed
from your extract because it is no longer available. Samples
Extract
File Type rectangular Variables
and Case Selection
If
you would like to make changes to your extract request...
If
your extract request is complete... Please provide a description of
this extract
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||