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The effect of different pricing strategies in the Dutch housing market Ingrid Janssen Roger Bougie Koen Pillen Istanbul, June 27th 2015 ERES 2015.

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Presentation on theme: "The effect of different pricing strategies in the Dutch housing market Ingrid Janssen Roger Bougie Koen Pillen Istanbul, June 27th 2015 ERES 2015."— Presentation transcript:

1 The effect of different pricing strategies in the Dutch housing market Ingrid Janssen Roger Bougie Koen Pillen Istanbul, June 27th 2015 ERES 2015

2 Pricing strategies in the housing sector The common asking price strategy is still widely applied and gives potential buyers the opportunity to negotiate below a listed asking price. 2014: one out of 50 transactions were based on a bottom price strategy

3 Introduction: trends in the Dutch housing sector Average Time on Market (houses sold): 86 days in 2007 to 176 days in 2013 Market is recovering: First quarter of 2015 T o M has decreased to 123 days Source: NVM

4 Introduction: trends in the Dutch housing sector Average selling price existing housing stock

5 Pricing strategies in the housing sector Bottom price strategy (best-offer-over or reserved pricing) Literature on the explanation of differences between listing (or asking) prices and transaction prices in different market conditions. Gan (2013) Australian market. Best-offer-over strategy is applied in a sellers market There is no evidence of the effect of this price strategy in a COLD market.

6 Bottom pricing in a cold market We found that this strategy is applied in two different ways: 1.From start 2.Halfway Switch: if the asking price strategy does not work out

7 Hypothesis The application of the bottom price strategy compared to the asking price strategy, 1.leads to lower transaction prices 2.shortens the Time on Market “Switch” dwellings… 3.are sold for lower average prices 4.have a longer Time on Market

8 Method Hedonic regression modeling Transaction price model Ln VKP i = ß 0 + ß 1 VM i + ß 2 F i + ß 3 L i + ß 3 M i +ε i (1) Time on Market model Ln VKT i = ϕ 0 + ϕ 1 VM i + ϕ 2 F i + ϕ 3 L i + ϕ 3 M i +ε i (2) Where: Ln VKP i =natural logarithm of sales price of dwelling i Ln VKT i =natural logarithm of time on market of dwelling i VM i =price strategy for dwelling i F i =physical characteristics of dwelling i L i =location characteristics of dwelling i M i =market circumstances when dwelling i is for sale

9 Data collection Data-set Time periodJanuary 2009 – June 2014 Total number of transactionsabout 500.000 “Asking price” transactions24.583 (random sample) “Bottom price” transactions5.316 Data source: NVM (covers 75% of all transactions in Dutch housing market)

10 Results transaction price model Dependent variableNatural log transaction price Constant8,785*** [0,036] Independent variables: Pricing strategy (1=asking price) -0,045*** [0,007] Fysical characteristics (F): Market circumstances (M) Sp. M. living space (log)0,789*** [0,008] Transaction period (ref. 2009) Type (ref. Appartment) - 2010 0,016*** [0,005] - Tussenwoning-0,003 [0,005] - 20110,003 [0,005] - Schakelwoning0,096*** [0,012] - 2012-0,060*** [0,005] - Hoekwoning0,008 [0,006] - 2013-0,103*** [0,005] - Helft-van-dubbel0,088*** [0,008] - 2014-0,072*** [0,006] - Vrijstaand0,151*** [0,012] Building periode (ref. before 1945) Location effects (L) Not shown - 1945-1970-0,141*** [0,005] - 1971-1990-0,131*** [0,005] - Na 1990-0,003 [0,006] Sq. M. M2 parcel (ref. 0 to 200) - 200 to 5000,126*** [0,006] - 500 to 1.0000,268*** [0,011] - >= 1.0000,384*** [0,014] Maintenance - Inside (1 = ‘good’)0,121*** [0,006] - Outtside (1 = ‘good’)0,050*** [0,007] Isolution (0 to 5)0,013*** [0,001] Centr. heating system (1=‘yes’)0,073*** [0,007] Number of observations26.232 Adj. R20,744

11 Effects price strategy on transaction price ERES 2015 The application of the bottom price strategy compared to the asking price strategy, leads to a decrease of the transaction price of.. - 4.4%

12 Time on Market model Dependent variableNatural log Time on Market Constant2,501*** [0,119] Independent variables: Pricing strategy (1=asking price)-0,810*** [0,027] Fysical characteristics (F): Market circumstances (M) Sp. M. living space (log)0,325*** [0,026]Transaction period (ref. 2009) Type (ref. Appartment) - 2010 0,091*** [0,023] - Tussenwoning-0,256*** [0,023] - 20110,168*** [0,024] - Schakelwoning-0,091 [0,058] - 20120,294*** [0,024] - Hoekwoning-0,222*** [0,030] - 20130,335*** [0,024] - Helft-van-dubbel-0,055 [0,036] - 20140,229*** [0,030] - Vrijstaand0,284*** [0,043] Building periode (ref. before 1945) Location effects (L)Not shown - 1945-19700,080*** [0,022] - 1971-19900,067*** [0,022] - Na 19900,186*** [0,027] Sq. M. M2 parcel (ref. 0 to 200) - 200 to 500-0,031 [0,028] - 500 to 1.000-0,072 [0,047] - >= 1.000-0,136*** [0,052] Maintenance - Inside (1 = ‘good’)0,239*** [0,029] - Outtside (1 = ‘good’)-0,028 [0,033] Isolution (0 to 5)0,013** [0,006] Cent. heating system (1= ‘yes’)0,062** [0,031] Number of observations26.232 Adj. R20,087

13 ERES 2015 Effects price strategy on Time on Market The application of the bottom price strategy compared to the asking price strategy, leads to a decrease of the Time on Market.. - 55.5%

14 Switch effect Results show that the transaction price of “switch” dwellings is 8% lower than transaction prices of dwellings that have been sold with a bottom price strategy from start. -> Not significant The number of “switch” transactions increased during the observed time period. - > Sellers apply the bottom price strategy more often from start.

15 Regional differences in application best-offer- over strategy % number of bottom price transactions / % total transactions

16 Effect pricing strategy on transaction price: differences for regions ERES 2015 1 In regions where the bottom price strategy was applied incidentally, application of this strategy leads to higher price differences. (-9,5%, after correction: -9,0%).

17 Effect pricing strategy on transaction price: differences for different building periods The more recent the dwelling was built, the smaller the effect of the best- offer-over strategy on the transaction price. It seems that for younger dwellings the best-offer-price is not associated with a lower quality.

18 Conclusions Application of the bottom price strategy in a cold market leads to: –A price decrease (4.4%) –Decrease time on market (55.5%) This disadvantage disappears for: –In regions where the application of the bottom price is more common –Dwellings that are built recently (> 1990) This research helps sellers and brokers to make more grounded decisions when choosing for a particular pricing strategy.

19 ERES 2015


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