The Market for Picasso Prints: An Hybrid Model Approach

Marilena Locatelli-Biey Department of Economics University of Torino - Italy E-mail: locatell@cisi.unito.it

Roberto Zanola Department of Public Policy and Public Choice - Polis

Palazzo Borsalino - via Cavour, 84 – 15100 Alessandria - Italy E-mail: zanola@sp.unipmn.it

ABSTRACT: Two basic approaches have been used by the literature focusing on the return to holding artistic works: the hedonic price model and the repeat-sales model. This paper provides a procedure for jointly estimating the two models in a way that take advantages of the unique information contained in each. A semiannual price index for Picasso prints is estimated by using a model derived from the basic framework of the hybrid models. The empirical results suggest that the hybrid model provides the most precisely estimated price index by reducing the level of price volatility.

JEL Classification Numbers: C5, Z1. Key Words: Prints, Picasso, Hedonic Prices, Repeat Sales, Rate of Return, Hybrid models.

1 Introduction

The literature on art auctions focusing on the return to holding artis-

tic works uses two basic approaches: the hedonic price model and the

repeat-sales model.1 The hedonic price model attributes an implicit

price to each of the time-invariant and time-varying characteristics of

the item. As dependent variable the logarithm of price is used which

is regressed on those time-variant and time-invariant variables and on

a vector of time dummies-equal to one if the asset is sold in period t

and zero otherwise - that capture the pure effect of price changes over

time. Using the hedonic price model, however, it is difficult to control

for variable selection, functional form, instability of item characteris-

tics over time and sample selection [Knight et al., 1995; Wolverton and

Senteza, 2000].

The repeat sales model, first advanced by M.J.Bailey et al. (1963),

estimates all pairs of consecutive transactions of a single item trans-

acting more than once during the study period. Using ordinary least

squares, this technique estimates an index for price of art items by re-

gressing the change in the log of price of each object on a set of dummy

variables, one dummy for each period in the sample, with the exception

of the first value of the log price index, which is set to zero to normal-

ization. The dummy variables are +1 if the second sale of the asset

1See Ashenfelter and Graddy (2002) for a survey.

2

is in period t, and −1 if the first sale of the asset is in period t; the

dummy variables are zero otherwise. Using the repeat sales model there

is the difficulty to control for a typical market trend during the period

between a sale and resale of a given item, as well as sample selection

bias.

Case and Quigley (1991), focusing on the market for houses, go be-

yond these two approaches, by jointly estimating conventional hedonic

and repeat sales models. This methodology represents an improvement

over the previous techniques since it combines information on repeat

sales with hedonic approach, which allows to capture either the increase

and/or the depreciation of prices within the repeat sales model and

the serial correlation in hedonic data. They apply a generalised least-

squares estimation procedure. In particular, the estimator is a two-step

iterative maximum-likelihood procedure for models with grouped het-

eroschedasticity.

Carter Hill et al. (1997) extend this approach by assuming that even

if it is plausible that in the hedonic model errors are serially correlated,

nevertheless market forces tend to eliminate the systematic error over

time. This hypothesis about the first-order autoregressive properties of

errors in the hedonic model combined with the stochastic properties of

errors in the repeat sales model, allows to define log-likelihood functions

for auctioned items and repeat sales, which are maximised numerically

3

to obtain maximum-likelihood parameter estimates.

Although this last approach appears to be interesting, it is focused

on the market for houses, and until now no applications exist on the

market for arts due to the difficulty to identify time-varying variables

[Chanel et al., 1996]. The purpose of this study is to provide a partial

answer to this difficulty by considering the effect of boom period on

prices as a time-varying variable. To this aim three different models

have been estimated by focusing on the market for Picasso prints: the

hedonic price model; the repeat sales model; and the hybrid model.

The rest of the paper is organised as follows. Section 2 presents the

model which draws from Carter Hill et al. (1997). Section 3 describes

dataset. Results are analysed in Section 4. Section 5 concludes.

4

2 The Model

Define Pit as the logarithm of print value (i.e., selling price) at time t, Xi

as the set of relevant time-invariant characteristics, Bit as the set of rel-

evant time-varying characteristics, Dit as a set of dummy variables with

a value of one if a transaction on print i occurs in year t and zero oth-

erwise, and εit as a well-behaved error term. The hedonic specification

of the price may be expressed as:

Pit = Xiα+Bitβ +Ditδ + εit (1)

where α, β and δ are the shadow prices of the print-i characteristics.

However, since the only time-varying characteristic of the dataset is

represented by a boom period from 1987 to 1991,2 Bit may be defined

as a dummy variable with a value of one for the boom-period and zero

otherwise.

Since there are a number of observations within the dataset that are

observed to sell more than one, the repeat sales method can be used.

Define Pit+s as the logarithm of the print value at time t+ s. The price

difference between two sales of the same print may be expressed as:

Pit+s − Pit = ∆Piτ = Aiτβ + Tiτδ + νiτ (2)

2A potential time-varying characteristic is print depreciation, which is not regis-

tered in the dataset. However, due to the short period covered by the dataset, we

can assume that time does not cause any demage to the prints.

5

where: Aiτ = Bit+s −Bit, νiτ = εit+s − εit, and

Tiτ =

1

−10

if τ = t+ s

if τ = t

otherwise

(3)

Econometric problems preclude estimation of the parameter β in

equation (2). In fact, the effect of non-boom period cannot be distin-

guished econometrically without using additional data to provide an in-

dependent estimate of the parameter β [Bailey, 1963; Palmquist, 1979,

1980]. Hence, following Case and Quigley (1991), and Carter et al.

(1997), we impose cross equation equality constraints on β and δ in

order to obtain smaller standard deviations observations. The matrix

form for the system of the two equations is equal to:

Pit

∆Piτ

= X B D

0 A T

α

β

δ

+ ε

ν

(4)

6

3 Data

The empirical analysis utilises data collected during the period 1988-

1995 from the 1995 edition of the Mayer International Auction Records

on CD-Rom. The publication contains records of prints sold at the

world’s major auctions, providing information on a number of variables

(artist’s name, nationality, title of the work, year of production, mate-

rials, date and city of sales, prices, pre-sale estimate (when available),

dimensions, whether or not it is signed, and a number of further infor-

mation). Prices are gross of the buyers and sellers’ transaction fees paid

to auction houses and are recorded in four different currencies. No in-

formation is provided on the provenence of the prints and exhibitions of

the prints. As noted by Pesando and Shum (1996), due to the homoge-

neous quality and condition of the impressions we only focus on Picasso

prints, which also closely resemble price movements in the market for

modern prints as a whole.

The explanatory variables included in the study are:

• Dimension: the variable defines the surface of the print, dim.

• Number of prints: the variable defines the total number of copiesproduced of the same print, n_print.

• Signature: a dummy variable is introduced to take into account ifprints are signed, with sign =1 if prints are signed, and sign = 0

7

otherwise.

• Colour: a dummy variable is introduced to take into account ifprints are colored, with color = 1 if prints have more than one

color, and color = 0 otherwise.

• Salerooms: Sotheby’s and Christie’s are known to be the leading

auction houses in this kind of transaction while the most impor-

tant art auction markets are New York and London. In order

to avoid overlaps between auction houses and cities of sale, we

add some interaction dummies between salerooms and cities, as

follows: sothny, for Sotheby’s New York; sothlon, for Sotheby’s

London; chriny, for Christie’s New York; chrilon, for Christie’s

London; francall, for print sold in France; germany, for prints

sold in Germany; otherus, for prints sold in US but not in New

York; othereu, for prints sold in the European countries not men-

tioned before; world, all other salerooms and cities of sales; swiss,

for prints sold in Switzerland (excluded variable).

• Media: a set of dummy variables, reflecting the technique adopted,is used: etching, etching; litho, litho (excluded variable); drypoint,

dry point; aquatint, aquatint or eau-forte; linocut, linocut; and

maeother, all other media.

• Boom: a dummy variable is introduced to take into account if

8

prints are sold in the boom years or not, with dboom = 1 if prints

are sold between 1988 and 1990, and dboom = 0 otherwise.

• Period : a set of dummy variables, Dt, with t = 1988, ......, 1995,

are introduced for each semester between 1988:I and 1995:II (with

1995:II excluded).

Table 1 summarises the main findings of the sample.

[TABLE 1]

9

4 Results

In this section the results of three different models are compared:

• the hedonic price model, which involves the estimate of the implicitprices for each characteristic included in the equation by making

it possible to control for any non-temporal determinants of price

variations;

• the repeat sales model, which estimates a price index for arts byregressing the change in the log of price of each prints on a set

of dummy variables, one dummy for each period in the sample

(with the exception of the first value) which is set equal to +1 at

the time of second sale, -1 at the time of the initial sale, and 0

otherwise;

• the hybrid model, which jointly estimates the hedonic regressionequation and the repeat sales regression with cross-equation equal-

ity constraints on the common parameters.

Table 2 displays the coefficient estimates and standard errors obtained.

[TABLE 2]

The hedonic regression results are reported in columns (1) and (2).

Standard errors and variance-covariance matrices of the coefficients have

10

been computed by using theWhite (1980) heteroskedasticity-robust pro-

cedure due to heteroskedasticity. The coefficients associated with each

kind of independent variable can be used to rank prints according to

the price of a ‘normalised’ print, that is, the price of a print when all

the other variables are assumed to be at a standard level. The values of

coefficients are those expected. An F-test run for each group of dummy

variables shows that coefficients are significantly different from zero at

5 per cent probability level.3

Columns (3) and (4) show the results of the repeat sales method.

We compare the prices of identical prints that were sold twice or more

during the analysed period of time.4 For simplicity, we assume that all

sales occur at the end of each period. These estimates are substantially

different from the previous ones due to the impossibility to distinguish

econometrically the effect of non-boom period without using additional

data to provide an independent estimate of the parameter β in eq. (2).

To this aim, columns (5) and (6) display the set of coefficients from

joint estimation of the two equations. Due to the existence of con-

temporaneous correlation between equation errors,5 the hybrid model is

3Results are available on request by the authors.4The potential effect of outliners on the final results cannot be isolated due to

the few number of repeat sales.5The value of the χ2(1) = 0.460 (Breusch and Pagan, 1980) suggests to refuse

the null hypothesis of no contemporaneous correlation.

11

estimated using the seemingly unrelated regression methodology. The

hybrid model yields a smaller estimated standard deviation of the dis-

turbance term than the corresponding hedonic price model. In fact, the

hybrid model is estimated more precisely than the hedonic price model

since data on repeat sales are not ignored [Case and Szymanoski, 1995].

The set of dummy variables introduced for each semester between

1988 and 1995 is used to build a semiannual price index for Picasso

prints.6 The estimated values of the price index are presented in Table

3 and depicted in Figures 1.

[TABLE 3]

[FIGURE 1]

Although the period under scrutiny is characterized by price fluctu-

ations, the trend of price indexes shows the existence of a boom period

until 1990.7 Figure 1 suggests that the hybrid model provides the most

precisely estimated price index of the approaches considered. In fact,

the evidence based on this sample suggests that the hybrid model re-

duces the level of price volatility by capturing either the increase and/or

the depreciation of prices within the repeat sales model and the serial

correlation in hedonic data.

6The use of semiannual data are due to the characteristics of the international

auction market which concentrates sales in May/June and November/December of

each year [Pesando and Shum, 1999].7The trend corresponds to the least squares fitted through points.

12

5 Conclusions

This paper provides a procedure for combining the hedonic and repeat

sales approaches by analysing the performance of an investment in Pi-

casso prints during the period of time 1988-1995. In particular, we

jointly estimate the two models in a way that take advantages of the

unique information contained in each as developed by Carter Hill et al.

(1997). Although this last approach appears to be interesting, up to

now no applications exist on the market for arts due to the difficulty to

identify time-varying variables.

By considering the effect of boom period on prices as a time-varying

variable, this study represents a partial answer to this difficulty. The

empirical results suggest that the hybrid model provides the most pre-

cisely estimated price index of the approaches considered by reducing

the level of price volatility.

Given the limited sample used in this paper, it is difficult to de-

velop confident conclusions about the overall market for the visual arts.

However, the evidence presented here does help to clarify some issues

concerning the relative precision of different approaches to estimating

price indexes.

Acknowledgments

13

The authors are grateful to the participants of the12th International

Conference on Cultural Economics, Rotterdam, June 2002, for useful

comments to an early version of this paper. Usual disclaimers apply.

The research has been financially supported by CNR program on cul-

tural goods.

14

References

[1] Ashenfelter, O., Graddy, K. (2002), Art Auctions: A Survey of

Empirical Studies, NBER Working Paper N.8997.

[2] Bayley, M.J., Muth, R.F., Nourse H.O. (1963), A Regression

Method for Real Estate Price Index Construction, Journal of the

American Statistical Association, 58,933-942.

[3] Calhoun, C. (1996), OFHEO House Prive Indexes: HPI - Tech-

nical Description, Office of Federal Housing Enterprise Oversight,

Washington, mimeo.

[4] Candela, G., Scorcu, A.E. (2001), In Search of Stylized Facts on

Art Market Prices: Evidence from the Secondary Market for Prints

and Drawings in Italy, Journal of Cultural Economics 25, 219-231.

[5] Carter Hill, R., Knight, J.R., Sirmans, C.F. (1997), Estimating

Capital Asset Price Indexes, The Review of Economics and Statis-

tics, 79, 226-233.

[6] Case, B., Quigley, J.M. (1991), The Dynamic of Real Estate Prices,

The Review of Economic and Statistics, 72, 50-58.

[7] Case, B., Szymanoski, E. J. (1995), Precision in House Price In-

dices: Findings of a Comparative Study of House Price Index Meth-

ods, Journal of Housing Research, 6, 483-496.

15

[8] Case, K.E., Shiller, R.J. (1987), Prices of Single Family Homes

Since 1970: New Indeces for Four Cities, New England Economic

Review, 45-56.

[9] Chanel, O., Gérard-Varet, L.A., Ginsburgh, V. (1996), The Rele-

vance of Hedonic Price Indeces, Journal of Cultural Economics, 20,

1-24.

[10] Englund, P, Quigley, J.M., Redfearn, C.L. (1997), Improved price

indexes for real estate: measuring the course of Swedish housing

prices, University of California, mimeo.

[11] Goetzmann, W., N., Spiegel, M. (1995), Non temporal Components

of Residential Real Estate Appreciation, The Review of Economic

and Statistics, 77, 199-206.

[12] Knight, J., Dombrow, J., Sirmans, C. (1995), A Varying Parame-

ters Approach to Constructing Housing Price Indexes, Real Estate

Economics, 23, 187-205.

[13] Palmquist, R.B. (1979), Hedonic Price and Depreciation Indexes for

Residential Housing: A Comment, Journal of Urban Economics, 6,

267-271.

16

[14] Palmquist, R.B. (1980), Alternative Techniques for Developing

Real Estate Price Indices”, The Review of Economics and Statis-

tics, 62, 442-458.

[15] Pesando, J.E., Shum, P.M. (1996), Price Anomalies at Auction:

Evidence from the Market for Modern Prints, in Ginsburgh, V.A.,

Menger, P.M. (eds.), Economics of the Arts, 113-134, Elsevier Sci-

ence, Amsterdam.

[16] Pesando, J.E., Shum, P.M. (1999), The Returns to Picasso’s Prints

and to Traditional Financial Assets, 1977 to 1996, Joural of Cultural

Economics, 23, 183-192.

[17] Wolverton, M.L., Senteza, J. (2000), Hedonic Estimates of Regional

Constant Quality House Prices, Journal of Real Estate Research,

19(3), 235-253.

[18] White H. (1980), A heteroskedasticity-consistent covariance matrix

estimator and a direct test for heretoskedasticity, Econometrica, 48,

817-838.

17

Table 1. Descriptive Statistics

Variable Mean Std. Dev. Min. Max.

Price 21072.36 52478.52 200.00 1052630,00dim 1843.61 1627.52 0 31520.31n_print 89.50 102.90 0 1000,00sig 0.8379 0.37 0 1colour 0.2071 0.41 0 2sothny 0.2775 0.45 0 1sothlon 0.1651 0.37 0 1chriny 0.1278 0.33 0 1chrilon 0.1160 0,32 0 1francall 0.0751 0,26 0 1germany 0.0686 0,25 0 1otherus 0.0414 0,20 0 1othereu 0.0296 0,17 0 1world 0.0231 0,15 0 1swiss 0.0633 0,24 0 1etching 0.3834 0,49 0 1drypoint 0.0923 0,29 0 1aquatint 0.0675 0,25 0 1linocut 0.1734 0,38 0 1maeother 0.0178 0,13 0 1litho 0.2639 0,44 0 1dboom 0.4320 0,50 0 1D88:I 0.0568 0,23 0 1D88:II 0.0751 0,26 0 1D89:I 0.0899 0,29 0 1D89:II 0.0580 0,23 0 1D90:I 0.1148 0,32 0 1D90:II 0.0373 0,19 0 1D91:I 0.0450 0,21 0 1D91:II 0.0201 0,14 0 1D92:I 0.0538 0,23 0 1D92:II 0.0438 0,20 0 1D93:I 0.0746 0,26 0 1D93:II 0.0402 0,20 0 1

A. Single Sales (N = 1690)

APPENDICE

D94:I 0.0669 0,25 0 1D94:II 0.0769 0,27 0 1D95:I 0.1083 0,31 0 1D95:II 0.0385 0,19 0 1

Pricet 50523,46 67043,88 1600 378790Price(t+s) 45347,36 64910,00 2660 340000D88:I -0,10 0,30 -1 0D88:II -0,08 0,43 -1 1D89:I -0,12 0,39 -1 1D89:II -0,02 0,42 -1 1D90:I 0,01 0,53 -1 1D90:II 0,01 0,38 -1 1D91:I 0,04 0,49 -1 1D91:II 0,04 0,29 -1 1D92:I 0,12 0,39 -1 1D92:II 0,03 0,23 -1 1D93:I -0,07 0,29 -1 1D93:II -0,04 0,21 -1 0D94:I 0,02 0,15 0 1D94:II 0,00 0,21 -1 1D95:I 0,05 0,31 -1 1D95:II 0,09 0,28 0 1dboom 0,30 0,46 0 1

B.Repeat Sales (N R = 182 = 91 Pairs)

Table 2. Estimates of the different models

Variables Est. Std. Err. Est. Std. Err. Est. Std. Err.(1) (2) (3) (4) (5) (6)

constant 3,2897 0,28 3,8828 0,1252

dim 0,0002 0,00 0,0004 0,0000

n_print 0,0008 0,00 0,0010 0,0004

sig 0,8266 0,11 1,4336 0,0999

colour 0,3138 0,13 0,5708 0,1385

sothny 1,3572 0,19 2,4979 0,1343

sothlon 0,9795 0,20 2,2173 0,1487

chriny 1,0994 0,19 2,3752 0,1569

chrilon 1,3363 0,21 2,6321 0,1607

francall 0,7269 0,23 1,7417 0,1785

germany 1,3498 0,22 2,1521 0,1820

otherus 0,4325 0,20 1,6293 0,2174

othereu 1,4150 0,27 2,4688 0,2439

world 1,3749 0,28 2,7142 0,2687

etching 0,4923 0,18 1,0892 0,1061

drypoint 0,9346 0,20 1,6963 0,1507

aquatint 0,6609 0,18 1,1690 0,1627

linocut 0,6291 0,14 0,5861 0,1501

maeother 1,0474 0,37 1,7549 0,2894

dboom -1,7286 0,15 -0,3152 0,0340

D88:I 4,6653 0,27 -0,0149 0,0123 0,2869 0,0459

D88:II 4,9860 0,29 -0,0173 0,0105 0,3115 0,0430

D89:I 4,8681 0,29 -0,0060 0,0098 0,3238 0,0407

D89:II 5,1638 0,30 0,0476 .0117335 0,3866 0,0444

D90:I 5,0977 0,29 0,0215 .0085302 0,3555 0,0386

D90:II 4,8089 0,30 0,0424 .0143681 0,3410 0,0471

D91:I 3,5967 0,31 0,0271 .0128843 0,1286 0,0348

D91:II 3,0372 0,35 0,0169 .0195767 0,0415 0,0511

D92:I 3,3463 0,31 -0,0488 0,0122 0,0358 0,0322

D92:II 2,8661 0,31 -0,0182 0,0143 -0,0297 0,0371

D93:I 3,1441 0,29 -0,0081 0,0109 0,0354 0,0284

D93:II 3,1490 0,28 -0,0094 0,0148 0,0240 0,0386

D94:I 2,7130 0,29 0,0018 .0117666 -0,0054 0,0307

D94:II 3,2754 0,29 0,0018 .0108874 0,0466 0,0285

D95:I 2,8374 0,28 -0,0126 0,0091 -0,0123 0,0238

F(34,1721) = 748.74 F(15,1741) = 4.08 chi2 = 2056.75R-squared = 0.6532 R-squared = 0.034 "R-squared" = 0.496

Hedonic Model Repeat Sales Model Hybrid Model

Table 3. Prices Indexes

Period Hedonic Price Model

Repeat Sales Model

Hybrid Model

D88:I 100,00 100,00 100,00D88:II 137,80 99,76 102,49D89:I 122,48 100,88 103,76D89:II 164,61 106,42 110,49D90:I 154,08 103,66 107,11D90:II 115,43 105,89 105,56D91:I 193,46 104,20 116,99D91:II 110,56 103,16 107,22D92:I 150,61 96,65 106,62D92:II 93,18 99,71 99,86D93:I 123,04 100,69 106,58D93:II 123,64 100,55 105,36D94:I 79,95 101,66 102,31D94:II 140,30 101,68 107,77D95:I 90,54 100,22 101,60

Note: semi-annual period: D88:I=1, D88:II=2, ..., D95:I=15

Figure 1. Price Indexes

50

75

100

125

150

175

200

225

250

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Semi-annual Period

Hedonic Price ModelRepeat Sales ModelHybrid ModelTrend

23

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1999 n. 3* Mario Poma, Benefici economici e ambientali dei diritti di inquinamento: il caso della riduzione dell’acido cromico dai reflui industriali.

1999 n. 2* Guido Ortona, Una politica di emergenza contro la disoccupazione semplice, efficace equasi efficiente.

1998 n. 1* Fabio Privileggi, Carla Marchese and Alberto Cassone, Risk Attitudes and the Shift of Liability from the Principal to the Agent

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Department of Public Policy and Public Choice “Polis” The Department develops and encourages research in fields such as:

• theory of individual and collective choice; • economic approaches to political systems; • theory of public policy; • public policy analysis (with reference to environment, health care, work, family, culture,

etc.); • experiments in economics and the social sciences; • quantitative methods applied to economics and the social sciences; • game theory; • studies on social attitudes and preferences; • political philosophy and political theory; • history of political thought.

The Department has regular members and off-site collaborators from other private or public organizations.

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Instructions to Authors

Please ensure that the final version of your manuscript conforms to the requirements listed below:

The manuscript should be typewritten single-faced and double-spaced with wide margins.

Include an abstract of no more than 100 words. Classify your article according to the Journal of Economic Literature classification system. Keep footnotes to a minimum and number them consecutively throughout the manuscript with superscript Arabic numerals. Acknowledgements and information on grants received can be given in a first footnote (indicated by an asterisk, not included in the consecutive numbering). Ensure that references to publications appearing in the text are given as follows: COASE (1992a; 1992b, ch. 4) has also criticized this bias.... and “...the market has an even more shadowy role than the firm” (COASE 1988, 7). List the complete references alphabetically as follows:

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Periodicals: KLEIN, B. (1980), “Transaction Cost Determinants of ‘Unfair’ Contractual Arrangements,” American Economic Review, 70(2), 356-362. KLEIN, B., R. G. CRAWFORD and A. A. ALCHIAN (1978), “Vertical Integration, Appropriable Rents, and the Competitive Contracting Process,” Journal of Law and Economics, 21(2), 297-326. Monographs: NELSON, R. R. and S. G. WINTER (1982), An Evolutionary Theory of Economic Change, 2nd ed., Harvard University Press: Cambridge, MA. Contributions to collective works: STIGLITZ, J. E. (1989), “Imperfect Information in the Product Market,” pp. 769-847, in R. SCHMALENSEE and R. D. WILLIG (eds.), Handbook of Industrial Organization, Vol. I, North Holland: Amsterdam-London-New York-Tokyo. Working papers: WILLIAMSON, O. E. (1993), “Redistribution and Efficiency: The Remediableness Standard,”

Working paper, Center for the Study of Law and Society, University of California, Berkeley.