explaining residential ethnic segregation in the netherlands using price hedonics cheng boon ong
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Explaining Residential Ethnic Segregation in the Netherlands using Price Hedonics
Cheng Boon OngHSA-ECS Workshop 15 April 2010
Presentation Outline
1. Context2. Price Hedonic Method3. Data and specification4. 1st stage semiparametric5. 3rd stage: heterogeneous preference
for neighbourhood ethnic composition
Native Non-western Western Total
Homeownership 59.20 22.65 42.79 54.53
Social rental 30.59 66.32 42.89 34.84
Private rental 8.25 9.02 12.40 8.67
Median indoor floor space (m2) 127.39 86.37 109.94 122.23
Average net rent (€/month) 368.97 329.87 386.33 364.80
Average WOZ dwelling price (€ ‘000) 211.91 149.32 193.36 204.70
Big City (Randstad) 11.51 42.84 21.69 15.26
Other municipalities 88.49 57.16 78.31 84.74
Why homeowners and segregation?
• Non-price mechanism drives social rented sector (e.g. waiting list)
• Increase in homeowner sector at the expense of social rented sector (mortage tax relief, privatisation of housing associations, …)
• This line of research is relatively unexplored for the Netherlands
Price Hedonic Method
• Real estate valuation, transaction data• Microeconomic consumer choice theory
(utility, budget constraint, …)• Housing as a bundle of separable attributes
with unique subutility components and implicit prices for each attribute (Lancaster 1966, Rosen 1974)
• Bajari and Kahn (2005): heterogeneous preferences
Bajari and Kahn (2005) three-stage
• 1st stage: estimate implicit prices for each housing attribute (semiparametric GAM)
• 2nd stage: recover household preference parameter with 1st stage coefficients and observed housing attributes
• 3rd stage: estimate joint distribution of preferences and household characteristics
Utility of household i consuming dwelling j with housing attributes, k:uij = u(xj, ξj, c)
= βi,kln(xj) + βi,kxj + βi,jln(ξj) + c
Household preference for attribute k, βi,k = xj*,k(∂p(xj*, ξj*)/∂xj,k)
…as a function of household characteristics, zβi,k = fk(zi) + εi,k
Dutch Housing Survey (WoON 2006)
• Nationally representative sample• > 60,000 respondents• Household characteristics, housing and
neighbourhood conditions, mobility• Linked to administrative (postcode)
neighbourhood data
1st semiparametric model
Log(Pricej) = β0,j + β1,j*YEAR1945-1959 + β2,j*YEAR1960-1969
+ β3,j*YEAR1970-1979 + β4,j*YEAR1980-1989 + β5,j*YEAR1990-1999
+ β6,j*YEARafter2000 + β7,j*s(log(ROOMS))
+ β8,j*s(log(INDOORSIZE)) + β9, j*s(log(OUTDOORSIZE))
+ β10, j*ONEFLOOR + β11, j*GARDEN + β12, j*BALCONY
+ β13, j*CARPARK + β14, j*CENTRALHEAT
+ β15, j*DETACHED + β16, j*SEMIDETACH + β17, j*APARTMENT
+ β18, j*DISTANCETOWN15minwalk + β19, j* DISTANCETOWNwithintown
+ β20, j*DISTANCETOWNsurrounding + β21, j*DISTANCETOWNcountryside
+ β22, j*s(log(MEANINCOME)) + β23, j*s(log(NONWESTERN))
+ β24, j*s(log(URBANITY)) + β25, j*BIGCITY
Log WOZ (indexed) df Lin. Coef. Std. Error z Gain P>Gain1945-1959 1 -0.0466 0.00656 -7.104 . .1960-1969 1 -0.0576 0.00591 -9.754 . .1970-1979 1 -0.0044 0.00538 -0.821 . .1980-1989 1 0.03925 0.00564 6.956 . .1990-2000 1 0.16509 0.00552 29.913 . .after 2000 1 0.18298 0.00687 26.624 . .log rooms 4.004 0.25669 0.00698 36.785 41.17 0log indoor size 3.999 0.12526 0.00393 31.9 74.139 0log outdoor size 3.989 0.07108 0.00164 43.231 447.33 0detached house 1 0.26742 0.00589 45.404 . .semidetached 1 0.04712 0.00442 10.663 . .apartment 1 -0.0894 0.00792 -11.28 . .single floor 1 0.04874 0.00452 10.774 . .garden 1 -0.0005 0.00662 -0.07 . .balcony 1 0.07807 0.00392 19.94 . .carpark 1 0.13955 0.00395 35.371 . .central heating 1 0.06257 0.00544 11.502 . .distance2 1 -0.0249 0.00503 -4.955 . .distance3 1 -0.0321 0.00603 -5.324 . .distance4 1 -0.0099 0.00567 -1.738 . .distance5 1 -0.0191 0.00776 -2.459 . .log mean WOZ 4.006 0.27245 0.00559 48.765 515.069 0proportion non-western 10.003 -0.0037 0.00026 -14.128 106.121 0log urbanity 3.995 -0.1309 0.0049 -26.736 105.062 0big city 1 0.0633 0.00792 7.99 . .
3rd stage: OLS
MWTPi,nonwestern = β0,i + β1,iFamilyKid + β2,iHouseholdSize + β3,iNativeDutchHead + β4,iWesternHead + β5,iNonWesternPartner
+ β6,iLowIncome + β7,i1to1.5ModalIncome+ β8,i1.5to2ModalIncome + β9,i2ModalhighIncome+ β10,ilog(Age)+ β11,iTertiaryEducated
Calculate Marginal Willingness to Pay
MWTPnonwestern10-35%increase,i = βi,k*(10) - βi,k*(35)
MWTPnonwestern0-3%increase,i = βi,k*(3) - βi,k*(0)
MWTP 10% to 35% non-western Coef. Std. Err. t P>t [95% Conf. Interval]
Family with kids 0.0745 0.7296 0.1000 0.9190 -1.3556 1.5045
# household members -1.4839 0.3020 -4.9100 0.0000 -2.0759 -0.8920
Western minority -19.1146 1.3957 -13.7000 0.0000 -21.8504 -16.3789
Native Dutch -21.8883 1.2169 -17.9900 0.0000 -24.2734 -19.5031
< Social minimum -1.6483 1.4538 -1.1300 0.2570 -4.4979 1.2012
1-1.5 Model income -0.4339 0.8502 -0.5100 0.6100 -2.1003 1.2326
1.5-2 Modal income -1.3046 0.8411 -1.5500 0.1210 -2.9532 0.3440
> 2 Modal income -2.1119 0.8179 -2.5800 0.0100 -3.7150 -0.5087
Log age of household head -7.3057 0.7661 -9.5400 0.0000 -8.8072 -5.8042
Tertiary education -0.2726 0.4382 -0.6200 0.5340 -1.1315 0.5863
Non-western partner 24.5194 1.2483 19.6400 0.0000 22.0728 26.9661
constant 60.5632 3.4702 17.4500 0.0000 53.7613 67.3651
Adj R-squared 0.0817
MWTP 0% to 3% non-western Coef. Std. Err. t P>t [95% Conf. Interval]
Family with kids -0.0089 0.0876 -0.1000 0.9190 -0.1805 0.1627
# household members 0.1781 0.0362 4.9100 0.0000 0.1070 0.2491
Western minority 2.2938 0.1675 13.7000 0.0000 1.9655 2.6220
Native Dutch 2.6266 0.1460 17.9900 0.0000 2.3404 2.9128
< Social minimum 0.1978 0.1745 1.1300 0.2570 -0.1441 0.5398
1-1.5 Model income 0.0521 0.1020 0.5100 0.6100 -0.1479 0.2520
1.5-2 Modal income 0.1566 0.1009 1.5500 0.1210 -0.0413 0.3544
> 2 Modal income 0.2534 0.0981 2.5800 0.0100 0.0610 0.4458
Log age of household head 0.8767 0.0919 9.5400 0.0000 0.6965 1.0569
Tertiary education 0.0327 0.0526 0.6200 0.5340 -0.0704 0.1358
Non-western partner -2.9423 0.1498 -19.6400 0.0000 -3.2359 -2.6487
constant -7.2676 0.4164 -17.4500 0.0000 -8.0838 -6.4514
Adj R-squared 0.0817
Some preliminary conclusions
• Nonlinear relationship between proportion of non-western households in neighbourhood and dwelling price
• Different demand across ethnicity of household for non-western neighbours – some positive “taste” for non-western neighbours up to a certain level and then the “distaste” sets in
Thank you for your attention!
Comments/suggestions welcome: cheng.ong@maastrichtuniversity.nl
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