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
cent25:                 25th percentile of ratio of rental expenditures to wage and salary income (Table 2)
cent25:                 median of ratio of rental expenditures to wage and salary income (Table 1)
cent75:                 75th percentile of ratio of rental expenditures to wage and salary income (Table 2)

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
fips_dch:             The name of the MSA
mypop:                Population (millions)
med_ratio:         ignore
avg_inc_rent:    ignore
avg_inc_rent2:  ignore
avg_inc_rent3: Median wage and salary income of renter households (Table 1)

The variables produced by 2000_results_rent.csv are
fips_dch:             The name of the MSA
numobs_lw1:    Number of observations in log wage regression
rsquare_lw1:     R-squared of log wage regression
wage:                    Household wage holding human capital constant (used in Table 3)
lwage:                   Natural log of the wage variable
avg_lwage:         ignore
numobs_r1:       Number of observations in rent regression
rsquare_r1:        R-squared of rent regression
plrent1:                                Log rent holding housing characteristics constant (used in Table 3 and Table 1 for real rent growth rates)
avg_plrent:         ignore

Note that davisom1.do also has the code to compute the data used in Figure 1.  The regression coefficients from the last line should be stored for each of the three years 1980, 1990, 2000:

  */ ***********************************************

  */ 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
price1:                  ignore
price2:                  The local consumption price level (used in Table 4 calculations)

 

 

 

 

IPUMS Extraction System

logout

Extract Request Summary

The variable EDUCREC was removed from your extract because it is no longer available.

Samples

2000 1% sample

Regular

Extract File Type

rectangular

Variables and Case Selection

Type

Variable

Label

Case Selection

H

YEAR

Census year

--

H

DATANUM

Data set number

--

H

SERIAL

Household serial number

--

H

NUMPREC

Number of person records following

--

H

SUBSAMP

Subsample number

--

H

HHWT

Household weight

--

H

STATEFIP

State (FIPS code)

--

H

METAREA (general)

Metropolitan area [general version]

--

H

METAREAD (detailed)

Metropolitan area [detailed version]

--

H

GQ

Group quarters status

--

H

FARM

Farm status

--

H

OWNERSHP (general)

Ownership of dwelling [general version]

--

H

OWNERSHPD (detailed)

Ownership of dwelling [detailed version]

--

H

RENTGRS

Monthly gross rent

--

H

HHINCOME

Total household income

--

H

VALUEH

House value

--

H

VACANCY

Vacancy status

--

H

ROOMS

Number of rooms

--

H

BUILTYR

Age of structure

--

H

UNITSSTR

Units in structure

--

H

BEDROOMS

Number of bedrooms

--

H

NFAMS

Number of families in household

--

P

PERNUM

Person number in sample unit

--

P

PERWT

Person weight

--

P

FAMSIZE

Number of own family members in household

--

P

NCHILD

Number of own children in the household

--

P

FAMUNIT

Family unit membership

--

P

RELATE (general)

Relationship to household head [general version]

--

P

RELATED (detailed)

Relationship to household head [detailed version]

--

P

AGE

Age

--

P

SEX

Sex

--

P

MARST

Marital status

--

P

RACE (general)

Race [general version]

--

P

RACED (detailed)

Race [detailed version]

--

P

BPL (general)

Birthplace [general version]

--

P

BPLD (detailed)

Birthplace [detailed version]

--

P

CITIZEN

Citizenship status

--

P

SPEAKENG

Speaks English

--

P

HISPAN (general)

Hispanic origin [general version]

--

P

HISPAND (detailed)

Hispanic origin [detailed version]

--

P

RACESING (general)

Race: Single race identification [general version]

--

P

RACESINGD (detailed)

Race: Single race identification [detailed version]

--

P

EMPSTAT (general)

Employment status [general version]

--

P

EMPSTATD (detailed)

Employment status [detailed version]

--

P

LABFORCE

Labor force status

--

P

OCC1990

Occupation, 1990 basis

--

P

IND1990

Industry, 1990 basis

--

P

WKSWORK1

Weeks worked last year

--

P

WKSWORK2

Weeks worked last year, intervalled

--

P

UHRSWORK

Usual hours worked per week

--

P

INCTOT

Total personal income

--

P

INCWAGE

Wage and salary income

--

P

INCSS

Social Security income

--

P

INCWELFR

Welfare (public assistance) income

--

P

INCINVST

Interest, dividend, and rental income

--

P

INCOTHER

Other income

--

P

POVERTY

Poverty status

--

P

MIGRATE5 (general)

Migration status, 5 years [general version]

--

P

MIGRATE5D (detailed)

Migration status, 5 years [detailed version]

--

P

MIGPLAC5

State or country of residence 5 years ago

--

P

MIGMET5

Metropolitan area of residence 5 years ago

--

P

MIGTYPE5

Metropolitan status 5 years ago

--

P

MOVEDIN

When occupant moved into residence

--

P

PWSTATE2

Place of work: state, 1980 to 2005

--

P

PWMETRO

Place of work: metropolitan area

--

P

PWCITY

Place of work: city

--

P

PWTYPE

Place of work: metropolitan status

--

P

PWTYPE00

Place of work: metropolitan status, 2000

--

P

PWPUMAS

Super-PUMA of work

--

P

TRANWORK

Means of transportation to work

--

P

CARPOOL

Carpooling

--

P

RIDERS

Vehicle occupancy

--

P

TRANTIME

Travel time to work

--

P

DEPARTS

Time of departure for work

--

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