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COMPSTAT 2010 19 TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STATISTICS Paris France August 22-27 INFLUENCE OF THE CALIBRATION WEIGHTS ON RESULTS OBTAINED FROM CZECH SILC DATA Jitk tka a Bartoov and Vladisla islav v Bna University


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SLIDE 1

COMPSTAT 2010

19TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STATISTICS Paris – France August 22-27

Jitk tka a Bartošová and Vladisla islav v Bína

University of Economics in Prague Faculty of Management CZECH REPUBLIC

bartosov@fm.vse.cz, bina@fm.vse.cz

INFLUENCE OF THE CALIBRATION WEIGHTS ON RESULTS OBTAINED FROM CZECH SILC DATA

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SLIDE 2

OBJECTIVE OF THE CONTRIBUTION

To reveal the connection between values of calibration weights and chosen statistical characteristics

  • f the Czech households.

2

Basic ic statist istica ical charact cter erist istics ics of calibrati tion

  • n weights

hts. Influe uence nce of calibrati tion

  • n weights

ts on the income e distribution ibution in Czech h Republic ic. Influe uence nce of the calibrati tion

  • n weights

ts on the measurem emen ent t of monet etar ary y pover erty ty in the Czech h Republic ic.

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SLIDE 3

CONTENT

National variant of european survey EU EU-SIL ILC C as a continuation of former MICROCEN OCENSUS SUS survey. Const nstruc ruction tion of

  • f calibration

bration weights hts for sample survey in Czech Republic. Dependence ndence of

  • f calibration

bration weights ts on chosen variables. Inf nflue uence nce of

  • f the calibration

bration weights ts to the results

  • f survey.

3

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SLIDE 4

 Table

le 1: Rate e of successfu ssfull lly surveyed ed households holds according ing to the regio ion n of the Czech ch Republic blic

REASONS FOR USE OF CALIBRATION WEIGHTS

4

Source ce: Mikrocensus 2002, EU - SILC 2005 and 2008

Succ Succes essfu fully lly s surv rveyed d flats flats (%)

Region egion 2002 2002 2005 2005 2008 2008 Region egion 2002 2002 2005 2005 2008 2008

Ca Capit ital al Pra Pragu gue 61,9% 51,1% 69,5% Hradec Králové 65,9% 62,9% 81,3% Central Bohemian 67,8% 63,7% 84,4% Pardubice 80,7% 68,1% 85,0% South Bohemian 76,2% 62,9% 87,0% Vysočina 78,7% 73,5% 90,0% Plzeň 77,0% 73,3% 82,3% South Moravian 69,8% 60,0% 83,6% Kar arlov

  • vy Var

ary 81,3% 61,1% 83,6% Olo lomouc uc 77,5% 74,4% 84,0% Ústí nad Labem 84,0% 64,6% 84,1% Zlín 78,6% 67,3% 88,1% Liberec 68,8% 64,0% 83,3% Mor

  • rav

avia ian–Sil Silesia esian 73,8% 73,9% 86,9%

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SLIDE 5

CONSTRUCTION OF CALIBRATION WEIGHTS

number of permanently occupied flats number of inhabitants per flat number of retirees (both working and not working) number of unemployed number of self employed age of the leading person size groups of municipalities

5

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SLIDE 6

BASIC STATISTICAL CHARACTERISTICS OF CALIBRATION WEIGHTS

 Table

ble 2: Basic statistical

tistical charact cteristics eristics of calibration bration weights ts

6

Sour urce ce: EU - SILC 2007

Minimum mum 100.0 Me Mean 417.9 Maxim imum 3475. 5.0 3rd qua quartile ile 493.6 Media ian 369.8 1st qua quartile 294.6

  • St. deviati

tion

  • n

205.5 Weigh ght sum 404334 3341

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SLIDE 7

DISTRIBUTION OF CALIBRATION WEIGHTS IN DEPENDENCE ON INCOMES

7

Source ce: EU – SILC 2005 – 2007

Fig. . 1: : Kernel el density ity estimat imates es of calibration ration weights hts distri tribu buti tion

  • n
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SLIDE 8

DEPENDENCE OF CALIBRATION WEIGHTS ON INCOME OF HOUSEHOLDS

8

Source ce: EU - SILC 2007

  • Fig. 2:

: Dependence

nce of calibrat ratio ion n wei weights ts on income of households

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SLIDE 9

DEPENDENCE OF CALIBRATION WEIGHTS ON NET OF INCOME

9

  • Fig. 3: Calibration weights of the households with different

number of members

Source: ce: EU - SILC 2007

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SLIDE 10

DEPENDENCE OF CALIBRATION WEIGHTS ON THE HOUSEHOLD SIZE

 Fig.

. 3: Ca Calibrat

ratio ion n wei weights hts of the households with different rent number of members

10

Source ce: EU - SILC 2007

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SLIDE 11

DEPENDENCE OF THE CALIBRATION WEIGHTS ON THE SOCIAL GROUP AND MUNICIPALITY

1 1 Low

  • wer

er employees ees 2 2 Self employed ed 3 3 Highe her r employees ees 4 4 Retired ired with EA members 5 5 Retired ired without

  • ut

EA EA members 6 6 Unem employed ed 7 7 Other ers 8 8 All ll househ ehold

  • lds

11

Table le 3: Samp mple le sizes s and means ns of calibra rati tion

  • n weight

ghts of differen erent t social l group ups

Sour urce: ce: EU - SILC 2007

So Social g ial gro roup of

  • f t

the he head head of

  • f h

hou

  • usehold

ehold

1 2 3 4 5 5 6

7 8

sa samp mple le size size

2385 2385 802 2297 418 3423 3423 258 258 110 9675 9675

mean mean of

  • f w

weig eights hts

420.4 630.1 433.6 429.2 332.3 731.1 380.4 417.9

Table le 4: Samp mple le sizes s and means ns of calibra rati tion

  • n weight

ghts of differen erent t mun unici cipali paliti ties es

Type e of

  • f munic

icip ipalit ality

cap apital tow ital town cou

  • unty

ty s seat eat urban rban villag villages es villag villages

sa samp mple le size size

864 864 1423 3952 3952 3436 3436

mean mean of

  • f w

weig eights hts

617 617.3 .3 446 446.4 .4 395.6 38 381.7

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SLIDE 12

DEPENDENCE OF THE CALIBRATION WEIGHTS ON THE SOCIAL GROUP

 Fig.

. 4: : Calib

ibration ation wei weights ts of the households lds from different rent social groups ps

12

Source: ce: EU - SILC 2007

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SLIDE 13

DEPENDENCE OF THE CALIBRATION WEIGHTS ON THE TYPE OF MUNICIPALITY

 Fig.

. 5: Calib

ibration ation wei weights ts of the households lds from different rent types

  • f municipal

icipalities ities

13

Source: ce: EU - SILC 2007

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SLIDE 14

INFLUENCE OF CALIBRATION WEIGHTS ON THE ESTIMATES OF INCOME CHARACTERISTICS

 Table

le 4: Income

  • me charact

cteris eristics tics of the househ useholds

  • lds from

m different erent social group ups

 Table

le 5: Income

  • me charact

cteris eristics tics of the househ useholds

  • lds from

m different erent mun unicip ipaliti alities es

14

Source: ce: EU - SILC 2007

Differe Difference betw e betwee een weig eighted an hted and u d unweig eighted hted characteris haracteristic tics

So Social g ial gro roup of

  • f t

the he head head of

  • f h

hou

  • usehold

ehold

1 2 3 4 5 5 6 7 8 mea ean (C (CZK ZK)

10628 17486 17486 10878 14424 14424 2374 3243 1181 1181 22131 22131

med median n (CZK) (CZK)

8727 14198 14198 8658 14237 14237 10128 9260 -1288 1288 20582 20582

standard dev eviatio iation n (CZK) (CZK)

5294 19872 19872 3135 9512 9512

  • 143

143 2289 -4574 21380 21380

Differe Difference betw e betwee een weig eighted an hted and u d unweig eighted hted characteris haracteristic tics

Type e of

  • f munic

icip ipalit ality

cap apital tow ital town cou

  • unty

ty s seat eat urban rban villag villages es villag villages

mea ean (C (CZK ZK)

17387 17387 20973 20973 18278 21102 21102

med median n (CZK) (CZK)

26499 26499 21500 21500 16152 16152 18862

standard dev eviatio iation n (CZK) (CZK)

13035 9799 9799 23437 23437 20544 20544

1 1 – low

  • wer

r employ

  • yees,

2 2 – se self em employed, , 3 – higher r employ

  • yees,

, 4 – ret retired red wit with ec econom nomical cally act active ve members rs, 5 5 – ret retired red wit without

  • ut ec

econo

  • nomical

cally a act ctive m ve members rs, , 6 6 – un unemploy

  • yed,

, 7 – ot

  • thers

rs, 8 – al all house

  • useholds
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SLIDE 15

DIFFERENCE BETWEEN WEIGHTED AND UNWEIGHTED CHARACTERISTICS

15

  • 5000

5000 10000 15000 20000 25000

Difference of means (CZK) Difference of medians (CZK) Difference of standard deviations (CZK)

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SLIDE 16

DEFINITIONS OF THE CONSUMING UNIT

H – total income per household SJ SJ – equivale alent nt scale

  • f OECD

D EJ EJ – equivalent alent scale

  • f EU

R – income per representative

16

  • ch

ch – num umbe ber r of childre ren n betw etwee een n 0 and 13 13

  • op
  • p – num

umber ber of ot

  • ther

her childre ren n and membe mbers s (except ept „he head“ of househ usehold

  • ld)
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SLIDE 17

THRESHOLD OF MONETARY POVERTY FOR DIFFERENT TYPES OF CONSUMING UNITS

 Table 6: Influence

luence of calibra rati tion

  • n weight

ghts s on the thresh shold

  • ld of mone

neta tary y pover erty ty for differe erent nt types es of consuming ming un units

Sour urce ce: Mikrocensus 2002, EU-SILC 2005 – 2007

Ye Year ar

Type of the e of the cons

  • nsum

uming ing un unit it

Threshold hreshold of m

  • f monet
  • netary p

pov

  • verty (CZ

(CZK)

weighted eighted esti timat ate un unweighted eighted esti timat ate Dif ifferen erence betwe tween weighted eighted and and un unweighted eighted

2002 2002 household

116909 114554 2355

representative

52000 53522

  • 1522

2005 2005 household

132549 123246 9303

repr epres esentativ entative

58200 58230

  • 30

30

def

  • ef. E

. EU

78786 78786 76500 76500 2286 2286

def

  • ef. OE

. OECD

68223 68223 67199 67199 1024 1024

2006 2006 hou

  • useh

ehold

  • ld

139743 128088 11655 11655

representative

60912 60384 528

def

  • ef. E

. EU

83052 83052 79568 79568 3484 3484

def

  • ef. OE

. OECD

72000 72000 69926 69926 2074 2074

2007 2007 hou

  • useh

ehold

  • ld

152069 139718 12351 12351

representative

65850 65246 604

def

  • ef. E

. EU

89611 89611 86129 86129 3482 3482

def

  • ef. OE

. OECD

89611 89611 86129 86129 3482 3482

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SLIDE 18

THRESHOLD OF MONETARY POVERTY FOR DIFFERENT TYPES OF CONSUMING UNITS

18

20000 40000 60000 80000 100000 120000 140000 160000 household representative household representative

  • def. EU
  • def. OECD

household representative

  • def. EU
  • def. OECD

household representative

  • def. EU
  • def. OECD

2002 2005 2006 2007

weighted unweighted

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SLIDE 19

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Lower employees

19

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SLIDE 20

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD Income per consuming unit (EU) Self-employed

20

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SLIDE 21

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Higher employees

21

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SLIDE 22

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Retired with EA members

22

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SLIDE 23

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Retired without EA members

23

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SLIDE 24

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Unemployed

24

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SLIDE 25

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) Other households

25

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SLIDE 26

INFLUENCE OF CALIBRATION WEIGHTS ON THE INCOME DISTRIBUTION AND POVERTY THRESHOLD

Income per consuming unit (EU) All households

26

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SLIDE 27

RATE OF HOUSEHOLDS UNDER THE THRESHOLD FOR DIFFERENT TYPES OF CONSUMING UNITS

 Table 7: Influen

ence ce of calibra rati tion

  • n weight

ghts s on the rate of househ useholds

  • lds

un under der the thres esho hold ld of mone netar tary y pover erty ty

Sour urce: ce: Mikrocensus 2002, EU-SILC 2005 – 2007

Ye Year ar

Type of the e of the cons

  • nsum

uming ing un unit it

  • Freq. u
  • eq. under

der risk isk-of

  • f-pov
  • ver

erty th thresh eshold

  • ld

Pear earson son in in. . test test

weighted es eighted esti timat ate un unweighted e eighted esti timat ate

statistics istics χ2 p-value lue

ab absol

  • lut

ute rel elat ative ab absol

  • lut

ute rel elat ative

2002 2002

household 1833 22.99 % 1782 22.35 % 0.894304 0.344314 representative 672 8.43 % 757 9.49 % 5.423770 0.019864

2005 2005

household 1095 25.17 % 1012 23.26 % 4.210827 0.040167 representative 439 10.09 % 439 10.09 % 0.001267 0.971608 def.

  • ef. EU

331 331 7.61 % 291 291 6.69 % 2.633580 0.104626 def.

  • ef. OECD

CD 176 176 4.05 % 167 167 3.84 % 0.194245 0.6594065

2006 2006

household 1878 25.10 % 1691 22.60 % 12.729007 0.000360 representative 753 10.06 % 733 9.80 % 0.269714 0.603523 def.

  • ef. EU

570 570 7.62 % 469 469 6.27 % 10.342669 0.001300 def.

  • ef. OECD

CD 297 297 3.97 % 253 253 3.38 % 3.490078 0.061738

2007 2007

household 2409 24.90 % 2193 22.67 % 13.178869 0.000283 representative 858 8.87 % 832 8.60 % 0.4052132 0.524409 def.

  • ef. EU

697 697 7.20 % 566 566 5.85 % 14.315212 0.000155 def.

  • ef. OECD

CD 363 363 3.75 % 324 324 3.35 % 2.179265 0.139881

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SLIDE 28

RATE OF HOUSEHOLDS UNDER THE THRESHOLD FOR DIFFERENT TYPES OF CONSUMING UNITS

28

0% 5% 10% 15% 20% 25% 30% household representative household representative

  • def. EU
  • def. OECD

household representative

  • def. EU
  • def. OECD

household representative

  • def. EU
  • def. OECD

2002 2005 2006 2007

weighted (%) unweighted (%)

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SLIDE 29

CONCLUSIONS

Sam Sample le su survey Mi Mikr krocensu

  • census and

and Czec Czech EU EU-SILC sur survey pr provid vides es an an inf nfor

  • rmat

mation

  • n

ab about

  • ut

incom ncomes es and and

  • th

ther so social cial and and dem emog

  • grap

raphi hic charact characteri eristi tics cs of

  • f Czec

Czech ho house useho holds

  • lds. Th

The data ata files les cont

  • ntain cali

alibrat bration

  • n

wei eigh ghts th that at can can signi significan cantl tly influence fluence the the resul esults of

  • f real

realized zed an analyses

  • alyses. It

appears that the role of calibration changes with number of household members, grows with the growing incomes, etc. The paper focuses on the strength of influence of the calibration weight on the risk of monetary poverty in the Czech Republic. We

We had had sh shown wn that hat the the bias bias of

  • f

results results occurred

  • ccurred in

in all all cases cases (u (usuall ually highe higher valu alues) es) and and in in more

  • re th

than an hal half

  • f
  • f cases

cases thi his cha hange nge was as statisti tatisticall ally signi significan cant (o (on the he 5% le level el). Thus hus, the he un unwei eight ghted ed resu esult lts ar are sli light htly dist storted ed; on

  • nly

ly in in hal half of

  • f cases

cases the the bias bias is is stati atisti tical cally ly signi nifi ficant cant.

In order to create a complex insight on the problem of biasing the results of measuring the relative poverty by calibration weights, our analyses were based

  • n the study of different definitions of consuming unit which handles the

monetary poverty from different perspectives. We

We sh shown wn th that the the choi choice ce of

  • f

scale ale can can suppres press or

  • r emp

mphasize hasize the the influen luence ce of

  • f calibrat

bration

  • n weigh

ghts. An An impor

  • rta

tant nt out

  • utcome

come is is the he inf nflu luence ence of

  • f consu
  • nsuming

ming un unit defi efini nition on

  • n the

the ri risk sk of

  • f poverty

ty of

  • f Czec

Czech ho househ usehol

  • lds. And

And th there refor

  • re the

the suitab suitable le definition tion of

  • f

consuming nsuming unit plays ys the the key role in in identi ntifyi ying ng of

  • f relat

ative pover erty ty in in soci

  • ciety

ty.

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SLIDE 30

REFERENCES

BARTOŠOV OVÁ, , J. (2009): ): Analysis ysis and Modell llin ing of Financ ncial ial Power of Czech Households eholds. Aplimat, Journal of Appl. Math. 2(3), STU Bratislava, 31-36. BARTOŠOV OVÁ, , J. and BÍNA, , V. (2009): ): Modell lling ng of income

  • me distribution

ribution of Czech househ useholds

  • lds in years 1996 - 2005
  • 2005. Acta Oeconomica Pragensia 17(4), Oeconomica,

Prague, 3-18. BARTOŠOV OVÁ, , J. and BÍNA, , V. (2009): ): Financi ncial al Power of the Czech Househol eholds

  • ds. In:

EURISBIS09: Book of Abstracts. TILAPIA, Cagliari, 201-202. BÍNA, , V. (2009): ): The role of calibrat ration

  • n weights

s in SILC data. In: Finanční potenciál domácností '09 (Proceedings of workshop of GAČR 402/09/0515). University of Economics in Prague, CDROM. NICODEM DEMO, O, C., LONGFOR ORD, D, N.,T. (2009): ): A sensitivity vity analysi ysis s of poverty y defini nitions

  • ns

used d with EU-SILC. In: Finanční potenciál domácností '09 (Proceedings of workshop of GACR 402/09/0515). Univ. of Economics in Prague, CDROM. STANKOVIČOVÁ, I., BARTOŠOVÁ, J. (2009): Príspevok k analýze subjektívnej chudob

  • by

y v SR a ČR. Forum Statisticum Slovacum 5(3), SŠDS, Bratislava, CDROM.

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SLIDE 31

ACKNOWLEDGEMENT

The paper was supported by Czech ch Science ence Foundation ndation: Project GAČR 402/09/0515 „Anal nalysis ysis and Modelling elling of Financi ancial al Power er

  • f Czech

ch and Slovak ak Ho Household seholds“

Thank you for your attention and wish a nice day!

Happy to answer your questions in writing at: bartoso sov@fm. fm.vs vse.cz e.cz

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