varying the economies of scale in housing: impact on ... · spm thresholds for 2a+2c: 2015 50.5...

Varying the Economies of Scale in Housing:

Impact on Supplemental Poverty Measure

Statistics

Thesia I. Garner, Bureau of Labor StatisticsTrudi Renwick, U.S. Census Bureau

Seventh Meeting of the Society for the Study of Economic InequalityThe Graduate Center, City University of New York

New York City, NYJuly 17-19, 2017

Disclaimer

This presentation reports the results of researchand analysis undertaken by researchers within theBureau of the Census (Census) and Bureau ofLabor Statistics (BLS).

Any views expressed are those of the authors andnot necessarily those of the Census or BLS.

Results are preliminary and not to be quotedwithout authors’ permission.

2

First, thresholds to be based only on food, clothing, shelter, utilities (FCSU), and multiplier for other basic goods and services like for personal care and nonwork related transportation

Second, since NAS Panel report was issued in 1995, became clear that significant number of low-income families own a home without a mortgage and therefore have quite low shelter expense requirements (see ITWG document, March 2010)

Not taking this into account may overstate their poverty rates

Suggests the need to adjust SPM thresholds for housing status, distinguishing renters, owners with a mortgage, and owners without a mortgage.

There would be THREE thresholds, NOT a single threshold for all.

3 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Why Three Thresholds?

35%

10%

9%

11%

12%

15%

22%

29%

39%

60%

27%

17%

22%

29%

36%

38%

32%

30%

25%

22%

38%

73%

69%

60%

52%

47%

46%

42%

35%

19%

Allconsumer

units

Lessthan

$5,000

$5,000to

$9,999

$10,000to

$14,999

$15,000to

$19,999

$20,000to

$29,999

$30,000to

$39,999

$40,000to

$49,999

$50,000to

$69,999

$70,000and

more

Percent Distribution of Consumer Units by Before Tax Income and Housing Type: 2015

With mortgage

Without mortgage

Renter

Source: Bureau of Labor Statistics, Prepublication Table 1202. Income before taxes: Annual means, standard errors, coefficients of

variation, and quarterly percents reporting, Consumer Expenditure Interview Survey, 2015.

Motivation Supplemental Poverty Measure (SPM) assumes that all SPM resource units

within each housing type (renter, owner with a mortgage, owner without a mortgage) devote the same share of their threshold to housing costs. This is important because … Geographical adjustments applied to only the housing share of threshold

Value of housing assistance benefits capped at no greater than housing share of the threshold

Concerns about underestimation of the value of housing benefits led to an investigation of this assumption… Should the housing share vary by household size?

Should economies of scale in housing differ from those of other commodities in SPM thresholds?

Bishop (2010) critique regarding holding economies of scale parameter constant and concern with implications for housing

5

Prior Research by Renwick and Mitchell

on Alternative Housing Shares

34.7

17.6

50.5

21.6

31.8

13.6

29.926.0

0

10

20

30

40

50

60

Poverty ratefor units with

housingassistance

Percent withzero subsidies

Percentcapped

Aggregateamount of

housingsubsidies

SPM New Housing Shares

Source: Renwick and Mitchell, 2015, using 2013 CPS ASEC.

Changed housing shares to 70 percent for one person units; 60 percent for two person units

Increased effect of housing subsidies on SPM rates.

6

Housing Status Thresholds and Adjustments


FCSU expenditures for CUs with 2 children convert to FCSU for reference unit 2 adults with 2 children based on means within 30th to 36th

percentile range of FCSU for reference CUs

Thresholds produced for each housing tenure group, j

Owners with mortgages, Owners without mortgages. Renters

For reference 2A+2C, shelter+utility shares of thresholds produced, αj

Apply 3-parameter equivalence scale to derive Tj,s

Finally geographically adjust housing part of threshold for cost of living, geo-adjusted thresholdj = p(αjTj,s )+ (1- αj )Tj,s

Research Experimental Supplemental Poverty

Measure (SPM) Thresholds for Two Adults and

Two Children, 2015

Threshold amount Housing Share

SPM Owners with mortgages

$25,930 0.505

SPM Owners without mortgages

$21,806 0.411

SPM Renters $25,583 0.498

http://www.bls.gov/pir/spm/spm_chart1_2015data.htm

Housing Shares of

SPM Thresholds for 2A+2C: 2015

50.5

41.1

49.8

0

10

20

30

40

50

60

Homeownerswith a Mortgage

Homeownerswithout aMortgage

Renters

Source: Bureau of Labor Statistics, Division of Price and Index Number Research, September 2016.

Housing shares for the reference SPM unit (2 adults+2 children) used and impact two aspects of the SPM calculation:

Geographic adjustment on only the housing share of the threshold

Value of housing assistance capped using the housing portion of threshold minus renter payment (e.g., $12,663)

9

Restated: Concern with Holding Housing Shares Constant


Housing is expected to exhibit greater economies of scale than food and clothing, so seems reasonable to examine using smaller or larger portions of thresholds for account for economies of scale differences

Portion of SPM thresholds subject to geographic adjustment would be larger for smaller families, thereby increasing thresholds for those living in areas with housing costs greater than national median and decreasing for those in lower housing costs areas

Because value of housing subsidy capped, increase value of housing subsidies for some smaller families that could reduce their poverty rates

Options to Deal with Greater

Economies of Scale in HousingOPTION 1

Apply 3-parameter equivalence scale for other household sizes and types But now, housing share varies also by consumer unit size

Tg,β,j,s= pg(βj,sTj,s)+ (1- βj,s )Tj,s

New Βj,s from survey data

OPTION 2 Apply housing equivalence scale to housing part of 2A+2C threshold Apply F+C equivalence scale to F+C part of 2A+2C threshold For example, for 1-person thresholds, with N=4:

Estimate new scales parameters, h and f, using survey data

11 — U.S. BUREAU OF

LABOR STATISTICS • bls.gov

𝑇𝑔, 𝑗, 1 = pg

(α𝑗𝑇𝑗,2+2)

𝑁ℎ + ((𝟏−𝛼𝒋)𝑇𝑗,2+2)

𝑁𝑓

Alternative Estimates of Housing

Shares

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 2 3 4 5 6 7+

Household Size

Figure 1. Total Population Housing Expenditures as a Percent of Income

Gross Rent as aPercentage ofHousehold Income

Selected MonthlyOwners Costs as aPercentage ofHousehold Income -Mortgage

Selected MonthlyOwners Costs as aPercentage ofHousehold Income -No Mortgage

Source: 2014 American Community Survey Five Year Data.For more information, see census.gov/acs.

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 2 3 4 5 6 7+

Household Size

Figure 2. Housing Expenditures as a Percent of Income - Households with Income Less than 200

percent of Official Poverty




Source: 2014 American Community Survey Five Year Data. For more information, see census.gov/acs.

12

Comparing ACS to CE Estimates

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 2 3 4 5 6 7+

Household Size

Figure 2. Housing Expenditures as a Percent of Income - Households with Income Less than 200

percent of Official Poverty




Source: 2014 American Community Survey Five Year Data. For more information, see census.gov/acs.

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 2 3 4 5 6 7+

Consumer Unit Size

Figure 3. Housing Expenditures as a Percent of the Sum of Food, Clothing, Shelter, Utilities

(FCSU), and Other Basic Needs (20%) Expenditures

Renters

Owners withMortgage

Ownerswithout aMortgage

Source: Quarterly Consumer Expenditure Survey, all consumer units participating In 2008Q2-2013Q1

13

Regression-Based Equivalence Scales

Basic model:

𝑙𝑛𝐸𝑥𝑝 = 𝛽0 + 𝛽1𝑙𝑛𝑌 − 𝛽2𝑙𝑛𝑁 +⋯+ 𝜀

Rearranging predicted values yields an expression for log income share devoted to, for example, housing.

𝑙𝑛𝑆𝐻𝐴𝑅𝐸 = 𝛽0 + 𝛽1 − 1 𝑙𝑛 𝑌 − 𝛽2𝑙𝑛𝑁 +⋯

All else constant, a consumer unit with 𝑌𝑁 will be equally well-off as a single person with 𝑌1if:

𝛽0 + 𝛽1 − 1 𝑙𝑛 𝑌1 +⋯ = 𝛽0 + 𝛽1 − 1 𝑙𝑛 𝑌𝑁 − 𝛽2𝑙𝑛𝑁 +⋯

Cancelling and rearranging terms yields the single-parameter approximation:

𝑌𝑁

𝑌1= 𝑁

𝛽2𝛽1−1

• Run separately for housing and for food+clothing• 5 years of CE Interview data, expenditures in constant dollars• Control variables: urban/rural, region (NE,S,MW,W), time (2008, 2009, 2010, 2011, 2012)

Consumer Unit Size Equivalence Scale Parameters

0.569

0.316

0.589

0.118

0.571

0.120

0.665

0.286

0.582

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

1.000

3-P

aram

eter

Sca

le

Ho

usi

ng

Foo

d+C

loth

ing

Ho

usi

ng

Foo

d+C

loth

ing

Ho

usi

ng

Foo

d+C

loth

ing

Ho

usi

ng

Foo

d+C

loth

ing

All Housing Types Together Owners with Mortgages Owners withoutMortgages

Renters

Source: Bureau of Labor Statistics, Garner’s analysis of internal CE Interview data from 2008Q2 through 2013Q1, four quarters of data for each

consumer unit. Three parameter scale based on 1 person=1adult, 2 people=1 adult+1 child, 3 people=2 adults+1 child, 4 people=2 adults+2 children, 5

people=2 adults+3 children, and 6 people=3 adults+3 children.

2015 SPM Thresholds: Varying Equivalence Scales

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

Three-Parameter Scale

Owner With Mortgage

Owner Without Mortgage

Renter

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

1 2 3 4 5 6

Single Parameter for All CUs

Owner With Mortgage


Renter

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

1 2 3 4 5 6

Single Parameter for Housing Type Separately

Owner With Mortgage


Renter

Source: Bureau of Labor Statistics, Garner’s analysis of internal CE Interview data from 2008Q2 through 2013Q1, four quarters of

data for each consumer unit.

Housing Share of SPM Thresholds by

Methodology before Geo Adjustment

17

1 2 3 4 5 6

SPM 49.8% 49.8% 49.8% 49.8% 49.8% 49.8%

ACS 59.3% 52.8% 52.8% 49.8% 47.3% 45.8%

CE 53.3% 51.8% 50.3% 49.8% 48.3% 47.8%

SP for All Units 59.2% 54.5% 51.8% 49.8% 48.3% 47.0%

SP by Housing Type 59.9% 54.9% 51.9% 49.8% 48.1% 46.8%

45.0%

50.0%

55.0%

60.0%

Current SPM

CE Shares

Single parameter by housing type

Single parameter -- all units

ACS Shares

Source: Authors’ calculations based on ACS 2014 5 year data, shares and alternative equivalence scales derived by Garner from CE data.

Monthly Average Housing Expenditures Implicit in SPM

Thresholds for Washington DC Metro Area Renters:

1 Person vs 6 People

$2,235

$2,056

$2,168

$1,946$1,922

Six person

18

$793

$944$841

$1,104 $1,152

One Person

SPM

ACS Shares

CE Shares

Garner1

Garner2

Overall SPM Poverty Rates:2015

14.32 14.2 14.26 14.56 15.14

0

5

10

15

20

25

30

35

Overall Poverty Rates

Current Methodology

Shares based on ACS data

Shares based on CE data

Single parameter for allhousing units

Single parameter byhousing type

19

Source: 2015 Current Population Survey Annual Social and Economic Supplement.

Poverty Rates by Consumer Unit

Size: 2015

20

0

5

10

15

20

25

30

35

1 person 2 person 4 person 6 person 7+ person

SPM

ACS Shares

CE Shares

Garner1

Garner2


Poverty Rates by Consumer Unit

Age: 2015

21

0

5

10

15

20

25

30

35

Under 18 18 to 64 65+

SPM

ACS Shares

CE Shares

Garner1

Garner2


Poverty Rates by Place of

Residence:2015

22

0

5

10

15

20

25

30

35

Principal City Suburbs Outside metro

SPM

ACS Shares

CE Shares

Garner1

Garner2


Consumer Units with Housing

Subsidy: 2015

0

5

10

15

20

25

30

35

40

45

50

SPM Rate for Unitswith Housing

Assistance

Percent with $0Subsidy

CurrentMethodology

Shares based on ACSdata

Shares based on CEdata

Single parameter forall housing units

Single parameter byhousing type

23

0

5

10

15

20

25

30

35

40

45

50

Percent with cappedsubsidy

Aggregate Amount ofSubsidies(billions)


Marginal Impact of Housing Subsidies on

Poverty Rates: 2015

0.79

0.85 0.830.79

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Impact of Housing Subsides for AllUnits

Current Methodology

Shares based on ACSdata

Shares based on CEdata

Single parameter forall housin units

Single parameters byhousing type

21.1

22.621.9

21.0 20.9

0.0

5.0

10.0

15.0

20.0

25.0

Impact of Housing Assistance on SPMRate for Units with Assistance

24


Negative impact Negative impact

Conclusions and Future Research

Impact on poverty rates Little overall Adjustments through equivalence scales impact rates

Consumer unit size—higher for smaller sizes and lower for larger Elderly rates higher

Impact on housing subsidies and result Adjustments based on equivalence scales

Reduce percentage with $0 subsidy Reduce percentage with capped subsidy

Little marginal impact of housing subsidies on poverty rates

Future Develop a methodology to validate the existing and/or proposed

equivalence scales, consider adults and children Making adjustments for differences in prices for FCSU at local level

and interarea before producing reference unit thresholds

25

Contact Information

Thesia I. GarnerSupervisory Research Economist Divisionof Price and Index Number Research/

Office of Prices and Living Conditions

Bureau of Labor Statistics

http://stats.bls.gov/pir/spmhome.htm

202-691-6576

[email protected]

Trudi J.RenwickAssistant Division Chief

Economic Characteristics

Social, Economic and Housing Statistics Division

U.S. Census Bureau

census.gov

301-763-5133

[email protected]

26

http://stats.bls.gov/pir/spmhome.htm

mailto:[email protected]

census.gov

mailto:[email protected]

varying the economies of scale in housing: impact on ... · spm thresholds for 2a+2c: 2015 50.5...

Documents