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IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006
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IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

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Page 1: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

IMPUTED RENT IN HOUSEHOLD BUDGET

SURVEY

Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006

Page 2: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Content

Definition of the imputed rent

Methods

Results

Conclusion and proposals

Page 3: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Imputed rent

The imputed rent refers to the value that shall be imputed for all households that do not report paying full rent, either because they are owner-occupiers or they live in accommodation rented at a lower price than the market price, or because the accommodation is provided rent free.

Page 4: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Methods

• Self – assessment method

• Homogeneity groups method

• Heckman method

• Log-linear method

Page 5: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Self assessment method

Self – assessment method is based on the owner-occupiers answers about potential rent for their dwellings. This method is subjective method, and can not show real situation in the rental market.

Page 6: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Homogeneity groups method

The dwelling are disjointed in quantity groups so that the rental value of dwelling within each group is a homogenous as possible. Data on actual rents paid within each group are obtained. The average rent paid in the group to which dwelling belongs is imputed to the owner-occupier.

Page 7: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Heckman method 1The sample selection model consists of two equations The first equation indicates if target variable is observed, i.e. if there is a response or a nonresponse:

kkkr z*

here zk is a value of a vector of auxiliary variables, is a vector of parameters, k is the error term, a random component.We only observe whether it exceeds a certain threshold, say 0, because that results in the response or nonresponse:

kz

.0,0

,0,1*

*

k

k

krif

rifr

Page 8: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Heckman method 2The second equation assumes a linear relationship between the target variable y and a vector of auxiliary variables ),...,( 1 Jxxx

kkk uy x*

here is a random component, is a vector of parameters that have to be estimated using the sample data. is also a latent variable. The study variable y is defined by:

ku *ky

.0,

,1,*

k

kk

krif

rifyy

.

Page 9: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Log-linear regressionLets us introduce a variable l with the values:

Then the log-linear model can be defined as:

Nkyl kk ,...,1,ln

kkkl x

here – is vector of coefficients, – are values of known auxiliary variables, – are random errors.

kx

k

Page 10: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Population and sample design

 Nr. Strata Population Sample

1 Vilnius 1997 206

2 Kaunas 1854 191

3 Klaipėda 764 79

4 Šiauliai 625 64

5 Panevėžys 628 65

6 Other cities 6262 645

7 Rural areas 7000 750

  Total 19130 2000

Stratified random sample is used. Replication number is 1000.

Page 11: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Auxiliary variablesLocation of dwelling (strata)Type of dwellingNumber of roomsWaterHot waterElectricityHeatingGasKitchenKabel TVGarageSeweragePhone

Page 12: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 1Empirical average of estimates of mean rent using different imputation methods by strata (5 per cent of tenants)

50

150

250

350

450

1 2 3 4 5 6 7

Strata

Litas True rent Heckman Homogeneity Log-linear Self assess

Page 13: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 2Empirical average of estimates of mean rent using different imputation methods by number of rooms (5 per cent of tenants)

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8+

Number of rooms

LitasTrue rent Heckman Homogeneity Log-linear Self assess

Page 14: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 3Empirical average of estimates of mean rent using different imputation methods by strata (10 per cent of tenants)

0

100

200

300

400

500

1 2 3 4 5 6 7

Strata

Litas True rent Heckman Homogeneity Log-linear Self assess

Page 15: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 4 Empirical average of estimates of mean rent using different imputation methods by number of rooms (10 per cent of tenants)

0

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8+

Number of rooms

Litas

True rent Heckman Homogeneity Log-linear Self assess

Page 16: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 5Empirical average of estimates of mean rent using different imputation methods by strata (30 per cent of tenants)

50

150

250

350

450

1 2 3 4 5 6 7

Strata

LitasTrue rent Heckman Homogeneity Log-linear Self assess

Page 17: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 6Empirical average of estimates of mean rent using different imputation methods by number of rooms (30 per cent of tenants)

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8+

Number of rooms

Lit

as

True rent Heckman Homogeneity Log-linear Self assess

Page 18: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

Results 7Empirical average of estimates of coefficient of variation of rent using different imputation methods

Coefficient of variation, %

0,0

0,5

1,0

1,5

2,0

2,5

3,0

True coef f icientof variation

Heckman Homogeneity Log-linear Self assess

%

Page 19: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

ConclusionThe imputed rest estimated by Self-assessment method is better to use when we have 5 per cent of tenants.

The imputed rent estimated by Homogeneity groups method has a smaller bias than estimated by Heckman or Log-linear methods.

Proposals

Test these methods on EU-SILC data.

Test influence of new auxiliary variables on the estimation of rent.

Page 20: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

ReferenceJeroen Smits, (2003) Estimating the Heckman two-step procedure to control for selection bias with SPSS. http://home.planet.nl/~smits.jeroen/selbias/Heckman-SPSS.doc .

WEN Hai-zhen, JIA Sheng-hua. GUO Xiao-yu, (2004) Hedonic price analysis of urban housing: An empirical research on Hangzhou, China, Journal of Zhejiang University SCIENCE, 6A(8), p. 907-914.EU–SILC DOC TFMC-12/06. Third Meeting of the EU-SOLC task force on methodological issues. Imputed rent.. Eurostat-Luxembourg, April 2006, EU-SILC DOC TFMC-12/06.

DOC HBS/161/2006/EN, DOC EU-SILC/162/06/EN. Meeting of the working group on living conditions (HBS, EU-SILC and IPSE). HBS and EU-SILC Imputed rent.. Eurostat-Luxembourg, May 2006.

Bethlehem J., Cobben F., Schouten B., May 2006, Nonreponse in Household Surveys. Version 1, Statistics Netherlands, Methods and Informatics Department, p. 141-142.

Bradley C. Martin, Rahuk Ganguly, SAS program for Heckman 2-stage estimation. University of Georgia, College of Pharmacy, Athens, GA 30602, http://www.rx.uga.edu/main/home/cas/faculty/heckman.pdf Eurostat Phare MultiCountry Programme, Organise by ICON-Institute GmbH/Germany of behalf of Eurostat. Report on the Methodological Study: “Possible data sourses and methods to calculate the target variable “imputed rent” for Lithuania”. Action code: 1138-ILC-SerCon-Lithuania-1

Page 21: IMPUTED RENT IN HOUSEHOLD BUDGET SURVEY Inga Masiulaitytė, August 24-28, Ventspils, Latvia 2006.

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