The Ability of Dutch Foreclosure Auctions in Maximizing Seller Revenue

Home , Auction theory, Dutch auction, English auction, Revenue equivalence, Vickrey auction

The ability of Dutch foreclosure auctions in maximizing seller revenue

Why Dutch foreclosure auction prices fall short of the market price

Martijn Duijster 0475211

Group 2 Finance, semester 2, 2013-2014

17-7-2014 Bachelor thesis Economics and Business - specialization Finance and Organization Sander Onderstal

Faculty of Economics and Business University of Amsterdam

Index Abstract 3 1. Introduction 3 2. Dutch real estate auctions 4 3. Literature review 6 3.1. Types of auctions 6 3.2. The revenue equivalence results 8 3.3. Violations of the revenue equivalence result assumption 8 3.3.1. Information asymmetry 9 3.3.2. Competition 10 3.3.3. Bidder affiliation and the winner’s curse 11 4. Hypotheses 12 5. Research method 13 6. Results 15 6.1.. Explanation of the results 17 6.1.1. Information asymmetry 17 6.1.2. Competition 18 6.1.3 Solutions to improve competition 18 6.1.4. Transaction costs 19 6.1.5 Conflicts of interest between seller and owner 21 7. Conclusion 22 References 24 Appendices 26

Abstract The revenues in Dutch foreclosure auctions are compared to the market values of the properties. The discount rate is calculated which states the difference between the auction price and the market price. Foreclosure auctions in the Netherlands fail to receive an auction price close to the market price; the average discount rate with auction cost included in the auction price is about 20% and the discount rate when auction costs are excluded is about 27%. Asymmetric information, lack of competition, transaction costs and conflicts of interest may be attributable to this price gap.

1. Introduction

When homeowners fail to pay their mortgages the mortgagee can put the property up for auction in a final effort to reclaim the loan by selling it at a foreclosure auction. For the past years Dutch foreclosure auctions have been the subject of public debate. According to a letter from Ivo Opstelten (2014), the Dutch Minister of Security and Justice, complaints have been made by organizations such as the Dutch homeowners association (Vereniging Eigen Huis, VEH) and the Dutch realtors organization (Nederlandse Vereniging van Makelaars, NVM) that properties on auction do not receive a ‘fair’ price resulting in leaving homeowners with a residual debt after foreclosure. After receiving wide spread media attention, political debates have led to a legislative proposal by the Minister that would alter the current proceedings of foreclosure auctions by making it more transparent through online bidding and transferring risks from buyers to sellers.

The difference between the auction price and the private sale price is commonly referred to as the foreclosure discount (Campbell, Giglio and Pathak, 2009). The goals of this thesis are to determine the discount rates and identifying the causes for these discount rates by analysing the Dutch foreclosure auctions and explain its strengths and weaknesses. The suspicion of the Dutch government and the Dutch competition authority (Nederlandse Mededingingsautoriteit, NMa now known as ACM) (2013) of the auction price being far below market value is tested by calculating the discount rate (the difference between market price and auction price as a percentage of the market price) for 53 auctioned properties. The discount is often attributed to a lack of information about the property and real estate traders forming cartels as concluded by the NMa (2013). The claim that a lack of information would increase the discount rate is tested by comparing the discount rates of properties with the possibility of inspection to those without this possibility.

The remainder of this thesis is organized as follows. In section 2 a description of the Dutch real estate auctions is given that explains the circumstances under which the auction price is realised. Next in section 3 the literature is reviewed in which basic auction theory is explored and the models are analysed leading to the revenue equivalence result and circumstances under which the assumptions of the revenue equivalence are violated are reviewed. The hypotheses for testing the research questions are presented in section 4. In section 5 the research method is outlined and the results of testing the hypotheses are presented in section 6 followed by a discussion of the possible causes for the results. I conclude in section 7 and discuss policies that may improve the system of Dutch foreclosure auctions.

2. Dutch real estate auctions Real estate auctions in The Netherlands are divided amongst 17 regional auction houses, 16 of which employ the same terms and conditions, the AVVE 2006. The First Amsterdam Real Estate Auction slightly differs in its auctions methods used with the main difference being that each auctioned object is supervised by a real estate agent in order to provide information to the buyers. The following section elaborates the various aspects of the Dutch auction process with the goal of understanding its strengths and weaknesses in setting the optimal auction price from the sellers’ point of view.

Each auction is organised and executed by a notary with the help of an auctioneer and a secretary. The notary provides information regarding the auction and the bidders in the auction room have the possibility to ask questions which are mostly related to financial details and the state of the object. In addition to bidding in the auction house, all auction houses provide the possibility of bidding online since June 2014. An audio stream keeps the online bidders informed about the course of the auction and with the press of a button one can be the new owner of a house.

Bidders at a real estate auction do not have the same rights as they would have in a private sale. All bids made are unconditional, irrevocable and without any reservation (AVVE, 2006). Consumer rights are well protected within Dutch law, but it would be impossible to grant these rights in auction, such as the right to cancel the sale within three days or the seller being held accountable for non-mentioned defects as they would both undermine the workings of the auction.

Buyers must provide identification and a declaration of their financial solvency by their bank or a bank guarantee of 15% of the auction price. Within 6 days a 15% deposit and within 6 weeks the remaining sum must be transferred to the notary. These conditions may vary at the discretion of the notary. A liquidity check ensures the sale will go through, avoiding payment problems from the buyers side.

The seller of the object has the right to award or reject the sale after the auction. Dependent on the auction price the mortgagee or selling party can make the decision whether or not to go through with the sale so that in the event that they find the sale price too low the transaction is cancelled.

The auction method of the Dutch real estate auction is a combination of an English auction with a premium followed by a Dutch auction. The English- or ascending bid auction starts out with the auctioneer asking for an opening bid. After the opening bid others may overbid, increasing the price until there are no more contestants and the hammer sounds closing first part of the auction. The highest bidder registers at the notary and the second part of the auction begins. In the Dutch or descending-bid auction the auctioneer sets off at a high price gradually lowering until someone accepts the price by calling ‘mine’ or alternatively the price drops to the level of the bid of the English auction causing the highest bidder of the first part to have won the auction.

The winner of the English auction receives a premium for having the highest bid in order to stimulate bidders. The premium amounts to 1% of the highest bid in the ascending-bid phase. This premium is paid by the winner of the second part of the auction unless there are no bids or both bids come from the same person causing it to be cancelled.

The organisation of these auctions can be a very costly affair. Typical auction costs vary between €5,000 and €15,000 per object. These consist of the actual costs made for organizing the auction and overdue payments from the former owner. An example of these cost is provided in the appendix and a listing from AVVE 2006 is stated below.

1) Real estate transfer tax 2) The notary fees 3) The bid premium 4) Costs of cadastral investigation and registration changing 5) Costs of cancellation of mortgage registration 6) Costs of advertisement, auctioneers fee and room rental

7) Other cost incurred in preparation and organization of the auction 8) Costs due according to specific object’s terms and condition 9) Costs of evacuation of the object

The Dutch competition authority (NMa, now known as ACM) has fined real estate traders for collusion by making price agreements. In 2011 fourteen traders have been fined a total sum of 6,3 million euros and in 2013 another 65 traders were fined a total sum of 6,4 million euros. It is therefore safe to assume collusion took place in the Dutch real estate auctions with the effect of bringing down the auction prices. The NMa attributes the manipulation of real estate auctions to a limited number of bidders and few outsiders because of the risks involved in execution auctions. Buyers have limited options to inspect the property before the auction and uncertainty over possibility of it being rented out.

3. Literature review

This chapter will review basic auction theory. Section 3.1 sets forth four commonly used auction models together with the Amsterdam auction. Section 3.2 shows that under some conditions these basic models yield the same expected revenue, this outcome is known as the revenue equivalence result. In the following sections various circumstances and their causes violating the assumptions of the revenue equivalence result and its effects on the auction price are reviewed. Information asymmetry is discussed in section 3.3 and the effects of competition in section 3.4. Bidder affiliation and the winner’s curse are reviewed in section 3.5.

3.1. Types of auctions

In auction theory there are four basic types of auctions that are widely used and analysed: the English or ascending-bid auction, the Dutch- or descending-bid auction, the first-price sealed-bid auction and the Vickrey- or second-price sealed-bid auction. These four types will be discussed briefly and their understanding will lead to the revenue equivalence result which states that subject to various conditions these four types will generate the same expected revenue.

An English- or ascending-bid auction starts out at a low price with participants overbidding each other so that the price increases. Bidders drop out until there is only one bidder left who has submitted the highest bid, this winning bid is the price for which the object is purchased.

A Dutch- or descending-bid auction works in the opposite way; starting out on a high price that is gradually lowered until it is accepted by one of the participants. This acceptance will end the auction without the possibility of overbidding.

In a first-price sealed-bid auction, each participant submits their private bid, unknown to the other bidders. The placer of the highest bid will purchase the object at the price of the highest bid.

A Vickrey or sealed-bid second price-auction works in a similar way as the first-price sealed-bid auction with the modification that the placer of the highest bid will pay the second highest bid.

The Dutch- and first-price sealed-bid auction are strategically equivalent. The Dutch auction can be seen as a static game, each bidder chooses a price to call out given that no other participants already called a higher price and the winner acquires the object at the price they themselves have stated. This makes the two games strategically equivalent, the dominant strategy is to bid slightly below the level of the bidders true value in equilibrium in the independent private values model.

The English- and Vickrey auction also show resemblance as the price to be paid is the price determined by the second highest bidder. Considering the private value model, in which bidders know how much they value the object but this is private information, a dominant strategy is to bid to one’s true value which implies to stay in the game until the bidder is indifferent between winning and not winning. The bidder with the second highest private value will drop out and at that price the bidder with the highest private value will win for the price of the second highest bidder. The dominant strategy is to bid to one’s true value, whatever other player do (Vickrey, 1961).

Goeree and Offerman (2004) introduce and describe the Amsterdam auction as a model of the auctions used by real estate auctions in the Netherlands. Goeree and Offerman describe the auction as a two-stage premium auction: “In the first stage the price level rises until all but two bidders have dropped out. The level at which the last bidder exits is called the bottom price, which acts as a reserve price for the second stage. In this stage both finalists make sealed bids, the highest bidder wins the object, and both bidders receive a premium proportional to the difference between the lowest sealed bid and the bottom price. In the fist-price Amsterdam auction the winner pays her own bid, while she pays the other finalist’s sealed bid in the second-price Amsterdam auction”. This hybrid type auction with

a premium is revenue equivalent to the standard auctions, given the symmetric private values model assumptions. Goeree and Offerman conclude that Amsterdam auctions stimulate weak bidders to compete aggressively without having the implementation difficulties of Myerson’s (1981) optimal auction. They also name the Amsterdam as a prime example of practical mechanism design and the introduction of a premium as being a robust and costless way to enhance revenues in an otherwise uncompetitive asymmetric setting. Hu, Offerman and Onderstal (2011) show that the Amsterdam auction triggers less collusion than the English and first-price sealed-bid auctions.

3.2. The revenue equivalence result

The two similarities described above lead to the same dominant strategy for all four basic auction types which is bidding slightly below one’s true value. As a consequence the various types of auctions all generate the same expected revenue in the private value model and therefore the seller should be indifferent between the various auction types. This leads to the revenue equivalence result by Vickrey (1961). Myerson (1981) and Riley and Samuelson (1981) both showed that Vickrey’s results about the same expected revenue hold true more generally. The general revenue equivalence result is defined as follows: Consider an auction mechanism, in which n risk-neutral bidders each has a privately known value drawn independently from a common distribution. Then any such mechanism, in which (1) the object always goes to the bidder with the highest value or bid and (2) any bidder with lowest possible value expects zero utility, yields the same expected revenue.

The auction types described above are all revenue equivalent in the symmetric independent private values model. This model assumes symmetric, risk-neutral bidders who hold independent private information about the object and act independently of each other.

3.3. Violations of the revenue equivalence result assumptions

The assumptions of the revenue equivalence result are not always satisfied. In the following sections causes of these violations are examined. In section 3.3.1. asymmetric information is explored which implies that bidders do not all have the same information available which will be of influence to the height of their bid. A lack of competition will cause the auction to be no longer perfectly competitive which translates into lower auction prices as reviewed in section 3.3.2.. Finally in section 3.3.3. the influences of affiliation and the winner’s curse are examined.

3.3.1. Information asymmetry

Bidders do not all have the same information about a property and their valuations may differ. The components that make up bidder’s information here are private information (knowledge on the object that is not publicly available) and common values (a general appraisal value of the object). The situation with slight asymmetry and common values brings us to the almost common values model (Klemperer, 1999). In this model, if one bidder has a small advantage through superior information, for instance a slightly higher private value in a close to pure common values setting, he will bid a little more aggressively. This makes private information very valuable (Klemperer, 1999).

Bidders face uncertainty about the state and value of the property, referred to as real value risk by Eklöf and Lunander (2003). Because of the lack of consumer protection in real estate auctions the seller cannot be held responsible for any damages whatsoever. The bidder will seek compensation for the risk he is exposed to. This translates into a lower auction price and could be solved by offering reliable information on the state of the house. Milgrom and Weber (1982) prove that the seller always benefits from providing information about the object.

Differences in market conditions can affect the auction price. Mayer (1995) predicts that the auction discount will be higher in a bust market than in a boom market. In a bust market more houses will be available in the regular private sales market and competition and expected sale time increases. This will cause the buyers to anticipate the lower expected revenues and adjust their bids accordingly. A study of Ong, Lusht and Mak (2005) verifies this outcome in a study on real estate auctions. When looked at specific market conditions for different types of houses Mayer (1995) concludes that homogeneous houses (like apartments or terraced houses) have a smaller auction discount than heterogeneous houses (such a unique villa or a farmhouse). This is because homogeneous houses are easier to sell as they appeal to a wide audience which decreases the holding time for real estate traders.

Another argument on why the auction price may be lower than the market price is Akerlof’s lemons problem (1970) as an illustration of problems associated with information asymmetry and self-selection. The information asymmetry is caused by the seller having more information on the object than the buyer. In the market for used cars buyers cannot distinguish between good cars and bad cars, also called lemons in America. The buyer is willing to pay the average price of a good and a bad car. This causes the seller of the good

car not to sell as the price offered is lower than the price of his good car. The lemon sellers stay in the market because the price offered is higher than the value of the lemon. This puts the seller of the good car at a disadvantage as he can only expect an average price for a good car with a high value. If the buyer anticipates this he will only be offering the price of a lemon, expecting that there are only lemons for sale. The same principle holds for real estate auctions in which there is limited information or quality uncertainty. In the case of real estate auctions the owner of a good house will opt to sell their house in the open market, where the good quality is signalled to the buyers or alternatively they make sure the buyers at the auction have the possibility to inspect the house beforehand to inform them on the high quality. The bad quality house owners will be hoping for an average price and not signal the bad quality. The effect of this that houses with limited information provided will be perceived as bad houses and therefore will be offered only low bids.

In this section the importance of available information in optimal auctions is stressed. There can be a big difference in the supply of information of auctioned houses if compared to private sales. This leads to insecurity on the state of the house en will therefore lower the auction price. Later on this theory will be tested by comparing the discount rates of auction houses with and without the possibility of viewing by the potential buyers so that the impact of incomplete information on auction prices is shown.

3.3.2. Competition

A competitive auction encourages bidders to bid close to their true valuations. It is therefore in the interest of the selling party to encourage competition. Milgrom and Weber (1982) show that if buyers bid under competition, the price will be higher than if negotiated in a select group. Because a lack of competition will cause auction prices to fall below the prices of private sales the aim of this section is to find out if there is a lack of competition in Dutch real estate auction.

Intuitively, a high number of bidders would increase the chance of a high auction price just like a small number of bidders would prohibit an auction from being competitive. Ong, Lusht and Mak (2005) find that a higher number of bidders increases the likelihood of a sale which they combine with findings of Ching and Fu (2003) which show a positive relation between bidder turnout and the price of auctioned land. Cautiously concluding that a higher number of bidders leads to a higher auction price. Mayer (1998) also mentions this relationship without providing evidence and Bulow and Klemperer (1996) state that an

auction with N+1 bidders yields a higher price than negotiations with N bidders, N being the number of participants.

The number of participants in an auction is influenced by entry barriers. These may take on the form of actual costs or costs in the form of investment of time and effort. Entry barriers are obstacles that make it difficult to enter a given market. In the Dutch real estate auctions some of these obstacles would be access to capital, knowledge on the workings of the auction and housing market and a tolerance for the risks involved. These kinds of barriers reduce the number of bidders and therefore influence the auction price in a negative way.

The revenue equivalence result requires bidders to be independent of each other. Independence of bidders is important in auctions because it stimulates competition amongst bidders which in turn generates higher auction prices. In an optimal auction the bidders are therefore always independent. If bidders collude to alter the price in their favour the revenue equivalence result no longer holds as the bidders are no longer independent. Collusion is a non-competitive agreement between rivals that attempts to disrupt the market equilibrium by collaborating with each other, altering the price in their favour.

3.3.3. Bidder affiliation and the winner’s curse

The concept that bidders may be affiliated is introduced by Milgrom and Weber (1982), they show the existence of a positive correlation in bidder’s valuations. Bidder’s signals are affiliated when a high value signal makes other high valuations more likely. Affiliation violates the assumptions made for the revenue equivalence result. With affiliation, common-value elements and more than two symmetric, risk-neutral bidders, the first-price sealed-bid auction earns on average less revenue than the second-price sealed-bid auction which earns less than the English auction.

In an almost common values auction, the value assigned to the object is roughly the same for all bidders, but the true- or market value is unknown at the time of the bid and all participants value the object independently. The winning bid will be higher than the average bid, which should be an accurate estimate of the market value. Hence, the winner is likely to overpay because he overestimated the value. To overcome this phenomenon, bidders can apply bid shading; the practice of setting a bid below their estimation of the value of the object. It is used as a compensation for the winner’s curse. In first-price auctions, the winner pays the amount of his own bid. If this is equal to the estimated value of the object,

the winner gains nothing from winning the auction and therefore will bid below his valuation of the object (Klemperer, 1999).

Milgrom and Weber (1982) prove that the seller always benefits from providing information about the object. An explanation of this may be that bidders are uncertain of their valuations and can gain useful information by observing the bidding behaviour of his competitors over the course of the English auction. This extra information weakens the winner’s curse and will therefore induce more aggressive bidding which leads to a higher price.

In the review of the literature it becomes apparent that if some conditions hold the various auction types are all revenue equivalent. However, information asymmetry, issues with competition and affiliation violate the revenue equivalence result and cause auction prices to be lower than the revenue maximizing level.

4. Hypotheses

The description of auction theory in the previous section suggests that under some conditions seller revenue should be maximised. However, it is uncertain if these conditions hold for the Dutch real estate auctions. Information asymmetry and collusion violate the assumptions for the revenue equivalence result. The legislative proposal by Minister of Security and Justice Ivo Opstelten (2013) with the aim of increasing seller revenue at Dutch foreclosure auctions, rulings by the Dutch competition authority NMa (2013), and a paper by Brounen (2012) suggest that prices at foreclosure auctions are below the market prices. To examine the suspicion that the auction prices fall short of the market prices because of information asymmetry and collusion, an examination of the auction prices versus the market prices will be conducted. The following hypothesis captures this suspicion and is based on the expectation that the Dutch real estate auctions do not satisfy the conditions for the revenue equivalence result.

Hypothesis 1: The average auction price is lower than the average market price.

Previous research like Brounen (2012) focusses predominantly on the auction price on its own and states the auction costs as an additional factor lowering the auction price. From a buyer’s perspective there is no economical distinction in the separation of the full price payable at auction into the auction price and the auction costs. Therefore hypothesis 2 takes into account the auction costs in comparing auction prices and market prices.

Hypothesis 2: The average full price paid at auction (auction price plus auction costs) is lower than the average market price.

One of the reasons that the auction price might be lower than market price may be a lack of information. Usually there is little to no information provided about the auctioned property. This influences the auction price in a negative way. Just like Akerlof’s lemons problem (1970) the bidder is unable to estimate the quality of the property and will therefore offer a lower price. To test this presumption, the discount rate including auction costs from properties with and without the possibility of inspection are compared. The possibility of inspection is a good measure for the lack of information because inspection can reveal the state of the property to a great extent. Hypothesis 3 is therefore defined as follows.

Hypothesis 3: Properties with the possibility of inspection have a lower auction discount including costs than properties without the possibility of inspection.

5. Research method

In order to test the hypotheses the sales comparison approach (Isakson, 2002) is used with multiple listing data. The concept is calculating the market value by means of comparing transactions of nearly identical houses. This method is used by members of the Dutch realtors association, the NVM. The auction prices and costs are obtained from the auction site veilingbiljet.nl and the comparisons from the land register. The difference between the market price and the auction price expressed as a percentage of the market price called the discount rate. In this thesis two versions of the discount rate are estimated: One excluding the auction costs in the auction price and the other including the transaction cost in the auction price which I call the full auction price. These two rates will determine if the relevant hypotheses will be rejected or not.

The third hypothesis states that property with information provision will have a lower discount rate than without information provision. In order to test this the average discount rate of auctions with the possibility of inspecting the property and the discount rate of those without are compared.

The Sales comparison approach, also known as the market data approach or grid adjustment technique, is widely regarded by most appraisers as the approach that produces the most reliable estimate of the market value, especially when there are many recently sold comparable objects (Isakson, 2002). Diaz (1990) argues that experts examine less data than

students and Spence and Thorson (1998) add that the estimated values produced by students are less accurate than those derived by experts. In this research, the selection of comparisons will therefore focus on quality rather than quantity. Mayer (1998) warns against potential biases from hedonic modelling (estimating house prices using a regression with variables like floor space, location, number of rooms, etcetera) because properties at auction are not randomly chosen. Though the sales comparison approach suffers the same drawback, the error is smaller as the comparison is made from more closely related observations.

In the gathering of data 53 houses being auctioned were randomly selected from 244 properties being auctioned from April to June 2014. In selecting houses for comparison the following criteria were set up to guarantee an unbiased selection. Upon availability the number of comparisons per auctioned object may vary but this will not bias the discount rate up or down. An important lesson from Diaz (1990) is that more is not better, a fewer number of accurate indicative values is better than a large number as the best suited indicators are selected first and adding more results in less comparable indicators. In selecting comparisons the same exact model of houses was used where available and fortunately in the Netherlands one housing design is often used multiple times in the same or adjacent streets and apartments may be even more homogenous. The state of the auctioned house could in most cases be determined as most foreclosure sales take place within a few years after acquisition. In cases this could not be determined the state was assumed to be the equal to the state found most in the comparisons as the states of the comparisons were nearly always equal and therefore highly related to the neighbouring houses. The transactions were at most ten years ago but always the most recent transactions were selected that met the other criteria resulting that most were realized within the last three years. In the event that not enough houses with the same floor space could be selected the price was adjusted in ratio of the floor space. This is the adjustment factor used as mentioned in the sales comparison approach by Isakson (2002). In this study the maximal deviation in floor space is limited to 25% and only used when there were no better suiting comparisons available. To conclude all variables except floor space are merely used to select indicative value comparisons. To adjust the value at the time of sale for the time the auction sales took place in 2014, a price index per province plus the four largest cities from the bureau of statistics in the Netherlands (Centraal Bureau voor Statistiek, CBS) was modified to create a discount factor as to calculate the present value of the indicative values.

The average value of the indicative values of the comparison object gives the estimated market value of the auctioned property at the time of auction. The estimated market value is not corrected for transaction cost like taxes as these also apply to auctioned properties. These cost are not part of the auction costs as described later on. The two discount rates used in testing the hypotheses are calculated as follows.

Auction price discount rate = (market price - auction price)/market price x 100%

Full auction price paid discount rate = (market price - (auction price + auction costs))/market price x 100%

The third hypothesis is answered by comparing both discount rates from properties with the possibility of viewing and the discount rates of those without the possibilities of viewing. The discount rate with auction costs included in the auction price is used for this purpose as buyers take these costs into account in setting their bid.

6. Results

Table 1 Descriptive statistics Lowest Highest Average observation observation Estimated market price € 141,102.38 € 73,440.44 € 227,398.86 Auction costs € 8,418.92 € 4,600.00 € 13,928.00 Auction discount, costs included € 27,230.62 -€ 11,676.01 € 90,183.92 Auction price, costs included € 113,871.75 € 49,125.00 € 204,200.00 Discount rate, costs included 20,13% -7,99% 54,93% Auction discount, costs excluded € 35,649.55 -€ 4,876.01 € 97,183.92 Auction price, costs excluded € 105,452.83 € 41,000.00 € 198,000.00 Discount rate, costs excluded 26,79% -3,34% 59,19%

Table 1 reports various descriptive statistics from the analysis of the 53 randomly selected foreclosure auctions that took place from April to June 2014. The average auction costs are €8418.92, which amount to 7,4% of the average total auction price paid (including costs). From a buyer’s perspective the most interesting number of table 1 is the discount rate calculated with the inclusion of auction costs, which is 20.1%. This implies that on average, the full auction price is 20,1% lower than the market price. In this thesis this difference is referred to as the auction discount, but the lowest observation: -8,0% suggests that in this case the auction price is above the estimated market price, making it a premium rather than

a discount. From a seller’s perspective (the mortgagee, usually a bank) the most interesting number from table 1 is 26,8%, which is the discount rate without auction costs. This means that if a bank were to sell a house at auction, the revenue from the auction would be 26,8% lower than the estimated market value. A bank can use this percentage to estimate whether it should put a property up for auction or find alternative ways to collect the outstanding mortgage loan. If the mortgage is lower than (100%-26,8%=) 73,2% of the market price, also known as the loan-to value ratio, the bank will on average not make a loss selling the property at auction (given symmetrical distribution of the discount rate).

To find the appropriate statistical test for H1: The average auction price (without costs) is lower than the average market price, the distributions and if necessary the variances are tested. To test if the observation are normally distributed, the Shapiro-Wilk test for normality is used. The estimated market prices have a p-value of 0.169, making it not significant that they are not normally distributed. The auction prices without costs have a p- value of 0.02, making the probability that it is not normally distributed significant. Because the auction prices are not normally distributed the F-test for comparing variances is no longer valid. Because the auction prices are not normally distributed, instead of the one- sided paired t-test, the one-sided sign test is used with x=51, the number of observations where the auction price excluding costs is lower than the estimated market price and n=53, the total number of observations. The sign test has a p-value smaller than 0.0001, rejecting the null hypotheses that the market price and the auction price without costs are equal in favour of H1: The average auction price (without costs) is lower than the average market price. As described in table 1, the average discount rate with auction costs excluded is 26,8% lower than the average estimated market price.

Just like the auction price with costs excluded, the auction price with costs included is also not normally distributed according to the Shapiro-Wilk test with a p-value of 0.024. To test H2: The average full price paid at auction (auction price plus auction costs) is lower than the average market price, the sign test is used with x=52, the number of observations where the auction price including costs is lower than the estimated market price. The p-value of the sign test is smaller than 0.0001, rejecting the null hypothesis that the average full price paid in auction is equal to the market price in favour of H2: The average full price paid at auction (auction price plus auction costs) is lower than the average market price. In table 1 it can be seen that the average difference between the auction prices including costs and the estimated market prices, called the discount rate with auction costs included is 20,1%.

The third hypothesis is tested by comparing the discount rate including costs from properties with the possibility of inspection to those without this possibility. The discount rate including costs is used as the buyers set the auction price and only care about the sum of auction price and auction costs and not the auction price alone. Both groups of observations are not normally distributed with Shapiro-Wilk test p-values of 0.875 and 0.113 respectively. To see if the discount rate with inspection is lower than the discount rate without, the Mann-Whitney test is used to overcome the non-normality. The p-value is 0.0719 therefore not rejecting the null hypothesis at a 5% significance level. The null hypothesis that properties with and without the possibility have the same discount rate is therefore not rejected in favour of H3: Properties with the possibility of inspection have a lower auction discount than properties without the possibility of inspection. The average discount rate with costs included for properties with the possibility of inspection is 12,1% and for those without is 21,4%, though it is not statistically significant that properties with inspection have a lower discount rate than those without.

6.1. Explanation of the results

The results have shown that both types of discount rates are significantly different from zero. The following step is to provide explanations why auction prices fall short of market prices. In the description of auction theory in section 3.3. theoretical circumstances are outlined that cause a violation of the revenue equivalence result. In this section violations of the revenue equivalence result are discussed from a more practical viewpoint and additional factors influencing the auction price are investigated. The arguments are categorised into four different categories; information asymmetry, competition, transaction costs and agency problems between seller and owner.

6.1.1. Information asymmetry

In foreclosure auctions it is fairly common that the buyer has limited information on the objects up for auction. In most cases it is difficult to get a reliable estimate of the state and value of the house, as the possibility of inspection is rarely offered. Means of gathering information by bidders can differ widely, from peeking through the window, gathering market information from Funda; a joint Dutch realtor website or the land registry office. Because the limited availability and costs of gathering information, different people will assign different values to the object, though these will be roughly based on the common

market value of the property. The problem of information asymmetry is described in section 3.3.1. and quality uncertainty is illustrated by Akerlof’s lemons problem (1970).

6.1.2. Competition

A key element in price mechanisms is competition and a lack thereof may have a severe influence on auction prices. The main issues of competition are discussed in section 3.3.2.. Correlation, affiliation and collusion are causing the bidders to gain market power making the auction no longer perfectly competitive. A limited group of bidders and budget constraints decrease competition. These lacking elements of competition cause the auction prices to fall below the level of private sales.

Price agreements are of great concern for the auction prices, according to the rulings of the Dutch competition authority price agreements have been made illustrated here in two possible scenarios. In the first scenario the bidders agree who gets to buy the object for a certain price. Afterwards the buyer pays other members of the price agreement a certain amount as a reward for not bidding above the agreed upon price therefore keeping the price down. The second scenario is closely related, here the bidders agree on a price for which one bidder buys the object and afterwards a second, private auction is held amongst the members of the agreement to decide who buys the object. The buyer of the private auction then pays the other members a fee for participating in the agreement. These scenarios may obviously not always work, as they have no control over outside bidders who may offer a higher price at the auction. In order for the agreements to work it is therefore necessary that a significant part of the bidders cooperate. This is easier in smaller auctions with less bidders. As a way of expanding the power of the cartel outsiders were persuaded to join the agreement.

6.1.3. Solutions to improve competition

The Dutch competition authority has fined real estate traders for collusion by making price agreements as described in section 2. They attribute the manipulation of real estate auctions to a limited number of bidders and few outsiders because of the risks involved in execution auctions. Buyers have limited options to inspect the property before the auction and uncertainty over possibility of it being rented out.

The NMa calls upon notaries to organise larger auctions attracting more bidders which makes it harder for cartels to be formed. It also recommends the use of online bidding to

make it easier to participate in an auction and to restrict contact between bidders. A new legislative proposal designed to lower the barriers of entry by making the auctions more accessible for potential buyers is welcomed by the NMa as it expects to increase the auction prices with possibly a lower residual debt for the homeowners.

This legislative proposal was approved by the Dutch senate in June 2014, making it most likely that it becomes a law in the near future. It addresses current issues in an effort to make the auctions more accessible to private individuals. The elements of the proposal and their intended effect will be briefly discussed below.

-The possibility of bidding online must be offered. This has already been introduced and since June 2014 all auctions provide this service. The best solution would be a hybrid version where predominantly traders would bid in the auction room and private individuals who might prefer the online platform. -The announcement of the auction no longer needs to take place in regional newspapers but instead at well known, accessible auction websites. -The costs of the auction will be borne by the selling party to increase transparency. -The transfer risk will be reduced by making the selling party responsible for the state of the property until it the ownership is transferred in the land registry. This will incentivise mortgagees to take precautionary measures to limit damage done by occupants. -A potential rental stipulation must be issued before the auction takes place to provide certainty about the occupancy by tenants. -The eviction procedures will be simplified, the eviction term will be reduced from twelve to three months and people without a rental agreement like squatters can also be evicted.

All these measures are designed to simplify the process and reducing risk for the bidders in an attempt to increase the number of bidders and make the auctions more accessible to private individuals. The increased competition and transparency should result in higher auction proceeds and reduce the residual debt for the homeowners.

6.1.4. Transaction costs

As mentioned in the description of the Dutch real estate auctions, auction costs are of a significant influence on the auction price. The costs borne by the bidder are typically around €5,000 to €15,000. In the sample of 53 properties on auction, the average auction costs are

€8,419. An overview of the types of costs involved can be found in the description of the Dutch real estate auctions and an example of these in the appendix.

In an economic sense the bidders on a property should not be concerned about the height of these costs on its own as they are inescapable when buying a house at an auction. They should only care about the sum of the auction price and the auction costs. This is because the auction price is altered by the full amount of these costs. Said differently the auction price and the auction costs are components of the full price paid in auction. This implies the bidder should subtract the auction costs from the full price he is willing to offer for the property to come to his auction bid. In researching the difference between the market price and the auction price it is important to make a distinction between the full price paid and the auction price. The full price can be seen as the economic cost of acquiring a property at an auction and the auction price as the revenue of the seller.

Unfortunately this distinction is not always made very clear in the literature and may lead to bias or misinterpretation of research findings. If the research object is to find the difference in the economic cost of acquiring a house at auction and the cost of acquiring a house in the private market the full price paid should be used. If the aim of the research is to find the loss of value inflicted by selling a house at auction the auction price should be used. As an example of this misinterpretation the presumably most quoted research on this subject in the media (both popular and professional literature) will probably be Dirk Brounen’s Executieveilingen: voorkomen of verbeteren? (Execution auctions: prevent or improve?) (2012) which mentions a price difference of 34%. A well informed reader will notice this price difference is the difference between the auction price and the market price, but media may bring forth this difference as being the difference between the full price paid at auction and the market price (Opstelten, 2014).

In 2012 a discussion arose about the notary fees in foreclosure auctions. Two organizations, a Dutch homeowners association (VEH), and a Dutch realtor organization (NVM), expressed concerns about the notary fees being too high in real estate auctions. In Eigen Huis Magazine (June 2012), a monthly publication of the VEH, Sander van der Ploeg explains the issue as follows: In a normal transaction the buyer is free in the choice of a notary. In foreclosure auctions this is impossible and the buyer is stuck to the notary handling the auction. Because since 1999 notaries are free to decide their own fee this creates a monopoly position increasing the notary costs and with that the transaction costs.

Another complaint of these organizations was charging high costs for the auction room being rented and not spreading these out over the number of auctioned properties but each charging them the full amount. As seen in the specification of costs used as an illustration and included in the appendix, the rental costs of the auction room are quoted to be €1.258,40. When multiplied by the number of auctions that day, fourteen, this would amount to €17.617,60 while a price of a few hundred euro would probably be a better estimation of the actual costs of renting an auction room.

The transaction costs at real estate auctions are high when compared to a private sale. They are a factor to be reckoned with in evaluating the system of real estate auctions in the Netherlands. The legislative proposal will change the party they are charged to and this might bring them down as the mortgagees may let notaries compete for the job.

6.1.5. Conflicts of interest between seller and owner

The seller always benefits from providing information on the property (Milgrom and Weber, 1982). The seller should have influence on providing relevant information on the state of the property. However, this important condition for raising the auction price is rarely met. The cause of this can be that the seller in this case is not the owner. The seller is the mortgagee (typically a bank) and the owner the homeowner. At first glance it would appear as if they have an alignment of interests: Getting the highest possible auction price. In practice this may not always be true. The mortgagee wants the sum of the outstanding mortgage back, but the outstanding mortgage could be lower than the full value of the house. The mortgagee’s incentive is recovering the outstanding mortgage but does not concern the value that may be realized on top of this amount.

This conflict of interest becomes even larger when the homeowner has got national mortgage guarantee (Nationale Hypotheek Garantie, NHG). NHG can be seen as an insurance against the financial risk of foreclosure. The aim is to provide financial security for the mortgagee in case of foreclosure so that it can provide a lower mortgage rate by covering the loss the mortgagee makes at foreclosure. In this case the mortgagee has no financial risk and therefore no incentive to make any effort increasing the auction price.

Another conflict of interest arises when the property is occupied by tenants. The homeowner may well be willing to provide information but lacks this possibility because he cannot enter the property because of tenants. The tenants have no incentive to cooperate because a successful auction may force them to leave the house.

This section demonstrates that the interests of the involved parties are not always aligned. The mortgagee has an incentive to recuperate the amount due and has no interest in generating value for another party. With NHG the mortgagee has not incentive whatsoever to spend resources in increasing the auction revenue when the price difference between the outstanding debt and the auction revenue is disbursed by the NHG.

7. Conclusion

The results suggest the auction price in Dutch foreclosure auctions is on average around 27% lower than the market value when auction costs are not included and about 20% if auctions costs are included. The main reasons for this are asymmetric information, lack of competition, transaction costs and conflicts of interest. When the problem of incomplete information is resolved by the possibility of inspecting the property the average discount rate including costs falls from about 21% for properties without the possibility of inspection to around 13% for properties with the possibility of inspection. However, this result is not significant at a 5% significance level.

The new legislative proposal approved by the Dutch parliament will show changes in the proceedings of the auctions. The possibility of online bidding has already been introduced at the time of writing so its influence is not measured in this thesis as auction data before this introduction is not available and may contain severe noise from other factors besides the introduction of online bidding. Even though this influence is not tested it can be argued that it decreases the chance of collusion as restricted contact between bidders can reduce the chance of collusion. A second measure from the new legislation is that the transfer risk is moved from the buyer to the seller as the latter is responsible for the state of the property. How this will be implemented is unclear and there will probably be some issues in the compliance of this measure as it the state of the house cannot be measured objectively. The simplification of eviction procedures and certainty about rental stipulations will further decrease the risks borne by buyers. A third measure that realtors would assist in providing information about the object could lead to more information about the property. In the first Amsterdam real estate auction (EAOGV) this situation is already applied leading to lower discount rates. However, the EAOGV is very competitive because of other elements such as a housing shortage in Amsterdam and an abundance of traders so it is hard to filter out the influence of realtors. These changes will affect the factors described influencing the auction price and it will be interesting to see future research on the effects of these measures.

The minister of Security and Justice Ivo Opstelten (2014) has stated that he has no intention of altering the auction method of using a combination of an English auction with a premium followed by a Dutch auction because the problems associated with real estate auctions do not concern the auction methods itself. This view is supported by the auction theory that states the Amsterdam auction as a combination of an English and a Dutch auction to be revenue maximizing in this setting.

Apart from the flaws of Dutch foreclosure auctions for which the new legislative proposal tries to offer solutions there is one issue unresolved. The ability of private individuals to finance the purchase of auctioned property with a mortgage. The process of applying for a mortgage takes too long and holds too much risk to be used as a financing instrument for individuals buying a house at auction. The 15% down payment has to be made in six days and the full amount is due within six weeks. In practice the means the buyer has to have the money up front to pay for the property. Since it is in the best interest of mortgagees to increase the auction price a possible solution is for them to provide financing for individuals buying a house at auction. There will undoubtedly be issues with this this financing method but researching its feasibility will be interesting opportunity to see if the financing issue of real estate auctions can be resolved.

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Appendices

Appendix 1

Example auction costs overview