Master Programme Cultural Economics and Cultural Entrepreneurship




НазваниеMaster Programme Cultural Economics and Cultural Entrepreneurship
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Erasmus University Rotterdam

Faculty of History and Arts

Master Programme Cultural Economics and Cultural Entrepreneurship


Weronika Adamowska

314894


Is art such a good investment?

Investing in fine art

on the international and Polish auction market’




Contemporary art auction at Sotheby’s New York held on 15.05.2007.

(http://www.portfolio.com/images/feeds/blogs/auction-rothkoauction-large.jpg)


Master thesis

written under the supervision of

Dr. Filip Vermeylen


Rotterdam, June 2008

Table of contents

1. Introduction


Art investment has a long history. Although some academics argue that financially-driven art investment began only after the Second World War (e.g. Frey and Pommerehne, 1989a), the idea that holding art might be a source of potential gains is not new. In fact, de la Barre et al. (1994, p.144) quote the 17th century diarist John Evelyn, who noted that ‘even Dutch farmers pay high prices for paintings, which they resell at “very great gains”’.

Analyzing the financial performance of art may seem controversial, especially to those who purchase artworks purely for their aesthetic value. However, it cannot be denied that works of art, like commodities, financial instruments or real estate, can be a source of monetary appreciation, sometimes making higher returns than alternative asset classes. This can be best illustrated by the following example. In November 1987, Vincent van Gogh’s ‘Irises’ was sold for 53.9 million dollars at Sotheby’s New York. 40 years earlier, seller’s mother bought them for only 84,000 dollars, which is less than 0.5 million dollars expressed in today’s money terms. This purchase has thus generated an annual real rate of return of about 12 per cent to the lucky owner (Frey and Pommerehne, 1989b).

The major question is whether this case is representative of the whole art market, or is it just a notable exception. If the answer were to be given based solely on the news publicized by the media, one could conclude that art outperforms other forms of investment. The hype created around the stunning auction records (with Jackson Pollock’s ‘No. 5’ sold recently for 140 million dollars) nourishes the widespread belief that money invested in art might yield extraordinary returns. It is further reinforced by the record-breaking sales at the major auction houses, as well as optimistic signals coming cyclically from the international art market. However, as this view is based solely on the superior performance of one particular market segment, it may not necessarily apply to other parts.

In this thesis, I attempt to verify the robustness of the argument that investing in art may generate extraordinary gains, following on from numerous previous studies that have attempted to test this hypothesis. With the ever growing interest in art as an alternative asset class and recent emergence of numerous enterprises offering art investment services, it may be the right moment to examine the strengths and weaknesses of art as a source of monetary appreciation, as well as point to the potential benefits of purchasing art for investment purposes. Moreover, previous art booms have attracted the attention of many academics, especially those active in the field of cultural economics. Therefore, the abundant literature will allow me to gain a deep insight not only into art investment as such, but also various related aspects.

The art market possesses several characteristic features, which distinguish it from other markets. Artworks are unique, highly heterogeneous, infrequently traded and illiquid goods, whose value is hard to estimate. Moreover, art market inefficiency seems to give rise to many anomalies, which are not annulled by arbitrage.

One of the potential consequences of the anomalous nature of the art market is that it may be possible to reap above-average gains, especially with the use of superior knowledge and expertise. Moreover, it has been suggested (e.g. Campbell and Pullan, 2006) that there might be an inverse relationship between the degree of maturity of the art market and returns on art investment. This would imply that, similarly to the emerging economies, the highest rates of return could be observed on the fairly underdeveloped art markets, such as the Polish auction market. In order to verify the validity of this assumption, I have carried out an empirical research on returns on artworks sold since the beginning of the auction market in Poland. As this issue has received by far little attention, the obtained outcomes will hopefully contribute to the present state of knowledge, as well as fill in the gap in the existing literature.

This thesis is organized as follows. First, I review the literature on art investment and present the major findings, especially with regard to artworks’ financial performance relative to other asset classes. Next, the process of art price formation and main determinants of art prices are discussed. This part is intended as an introduction to the analysis of return factors. In the following chapter, I shed some light on different art investment-related issues, such as the relationship between the art and other markets, and the prospects for portfolio diversification. I also discuss how to assess the monetary performance of art, analyze different avenues for allocating funds into artworks and point to the potential benefits of using art as an alternative investment vehicle. The next part concentrates on the major factors determining returns on art, especially art market-specific anomalies. In chapter 6, I describe the Polish art market and center my focus particularly on the auction market. This part serves as an introduction to the empirical study on the returns on artworks auctioned in Poland between 1990 and 2004, which is presented in the following chapter. First, I introduce the hypothesis, which will guide me through the empirical part of my thesis. Next, the study, its main findings and limitations are discussed. This chapter is followed by a conclusion summarizing the major points of my thesis. In addition, I include two appendices, in which I analyze the findings of particular papers devoted to art investment and returns on art. I also attach a CD-ROM, which contains repeat-sales data that forms the basis for the empirical study.

In this thesis, the focus is on the auction market. This choice is dictated by the fact that auction results are the only publicly available information regarding art prices. Therefore, studying returns on art is necessarily limited to those works that were purchased and resold with the intermediation of the auction house. Moreover, since art is a broad concept encompassing different categories, I narrow my analysis only to the fine art segment, i.e. paintings, drawings and prints.


2. Literature review


2.1. Introduction


Over the last 30 years, a great scope of literature has been devoted to the analysis of art investment and various related aspects. The ever growing interest in this field has been driven by the widespread belief, cyclically nourished by the media, that art can be a source of extraordinary gains. Especially the art boom in the end of the 1980s and stunning prices fetched at consecutive auctions have drawn the attention of economists, particularly those active in the field of cultural economics. As a consequence, researchers started to systematically investigate transactions on the art market.

As observed by Frey and Eichenberger (1995a), there are three main goals pursued by the authors interested in art investment, namely:

  • to study the art market in a similar manner to any other market and thus enable comparisons between returns yielded by art and alternative forms of investment

  • to apply the newest tools and techniques from the field of finance and econometrics to the art market

  • to investigate the specific and unique features of the art market

This chapter is organized as follows. The subsequent section focuses on the empirical findings of major studies on art investment, as well as some related issues. In the third part, I point to the main shortcomings and limitations of the literature devoted to art as an alternative asset class.


2.2. Empirical findings


In order to assess whether art outperforms other alternative forms of investment, two major factors need to be considered, namely the rate of return and degree of risk involved. Only then is it possible to compare various forms of investment and draw conclusions on relative financial performance of artworks. This is indeed what most researchers do in their studies. With few exceptions, where art investment is evaluated solely on the basis of the rate of return and where no benchmarks from the financial markets are used (e.g. Buelens and Ginsburgh, 1993; de la Barre et al., 1994), authors usually construct an art price index and estimate whether artworks could be considered a good investment, as compared to other assets (usually financial assets, such as bonds and equities, but sometimes also gold or real estate).

In this section, I summarize the general findings of the major studies. Since the literature is abundant and encompasses various types of collectibles, only those papers that research the market for fine art, in particular paintings, drawings and prints, are presented1. I narrow my focus to the issues I consider both most important and relevant to art investment. However, it should be noted that, even though subjective, my choice is guided by the opinions of researchers active in the field. For a detailed analysis of the findings of particular studies see appendix A.

In contrast to the widespread belief, nourished by the media, especially in times of booming art prices, academic studies seem to provide little support to the fact that art might be a superior investment. In fact, a rather consistent picture emerges from the literature – on the whole, art does not outperform other asset classes, at least in the long run. Despite huge differences in the periods and markets studied, as well as measurement methods applied, most papers report similar findings, namely that the rates of return seem to be pretty modest, as compared to alternative forms of investment, and the risk involved is high2. However, there are some exceptions to the general pattern that need to be mentioned.

The first one to have taken a more optimistic approach towards art investment is Goetzmann (1993). Contrary to previous studies, he claims that art can appreciate at a high rate, even in the long run. He also shows that, similarly to other financial markets, over time the art market both flourishes and declines in a cyclical manner. However, despite those favorable results, Goetzmann still recognizes the shortcomings of art investment and high volatility of art prices, and thus considers artworks a potential source of gains only to the nearly risk-averse investors.

The next significantly different finding emerges from the paper of Buelens and Ginsburgh (1993), who show that allocating financial funds into certain sub-markets (i.e. artistic movements, schools, artists, etc.), or during particular periods could result in extraordinary gains. This view seems to be supported by the stunning art records reported by the media. Nevertheless, the question remains whether such opportunities could be forecast in advance or, as claimed by Baumol (1986), as a result of changes in tastes and fashions, random behavior of art prices excludes their predictability.

The latter point of view appears to have generated particular disagreement among researchers. Some (e.g. Frey and Pommerehne, 1988, 1989a; Buelens and Ginsburgh, 1993; de la Barre et al., 1994; Ginsburgh and Schwed, 1992) postulate that it is indeed possible to predict movements of art prices, at least to a certain extent. Buelens and Ginsburgh (1993) attribute this to a wide time span between the occurrence and actual effect of a shift in tastes. Frey and Pommerehne (1988, 1989a) do not preclude that with the right expert knowledge it may be possible to predict the direction, in which art prices will evolve. This is similar to Landes’ (2000) conclusion – he claims that the extraordinary returns on the Ganz collection (earned irrespective of the time period, artist, or type of the artwork) could not have been solely a result of luck, but required superior skills and expertise. Finally, Ginsburgh and Schwed (1992), and de la Barre et al. (1994) compare econometric estimates with price patterns forecast by art experts and conclude that their appraisals could compete with those made by professionals, which would support the argument that there is little randomness to art price trends. Finally, Holub et al. (1993, p.52) suggest that Baumol’s (1986) finding on random behavior of art prices is based on an erroneous interpretation of statistical results and ‘confusion of transactions and transactors’. On the other hand, some authors (e.g. Pesando and Shum, 2008) acknowledge the fact that prices fluctuate in a random manner.

Another important question that arises, especially with regard to Buelens and Ginsburgh’s (1993) work, is whether the long-run underperformance of art precludes the possibility to reap high gains within a short time horizon. The evidence is somehow mixed. Nevertheless, various studies (e.g. Baumol, 1986; Frey and Pommerehne, 1989a) seem to support the hypothesis that extraordinary gains (but also losses) may be made during short periods, particularly in times of booming art prices. Moreover, the outcomes of various papers inspired by Buelens and Ginsburgh’s (1993) findings seem to confirm the fact that returns on art investment are highly dependent on the school, artistic movement, subject matter, as well as period studied.

Furthermore, there is also disagreement on the so called ‘masterpiece effect’, i.e. whether the most expensive artworks yield abnormal returns. Whereas some researchers either fail to identify, or find weak or mixed evidence for the existence of this phenomenon, others try to estimate its direction and extent (for more details see chapter 5 Return factors, section 5.2.4.2.‘Masterpiece effect’). Thus far, no general agreement on this issue has been reached.

In addition, while most authors observe high volatility of art prices (comparable, or often exceeding that of stocks), there are some studies that question, or even contradict this finding. For example, Buelens and Ginsburgh (1993) suggest that higher returns do not necessarily imply higher risk. Pesando and Shum (2008) reexamine Pesando’s (1993) results and come to a somehow different conclusion, namely that modern prints might be, in fact, far less risky than stocks (although still more volatile than Treasury bills). Finally, Mei and Moses (2002a) suggest that the degree of volatility of art price indices may equally depend on the sample size.

Whereas there might be no consensus with regard to the actual magnitude of returns on art investment, most researchers seem to agree on one issue, namely the existence of psychic returns (consumption benefits) derived from the pleasure of viewing or possessing an artwork. According to many authors, this additional gain compensates the owner for the underperformance of art relative to alternative forms of investment. Nevertheless, its existence and extent still remain more of a hypothetical issue (for more details see chapter 5 Return factors, section 5.2.10.Psychic versus financial returns).

Finally, many studies analyze the potential benefits of adding art to a diversified portfolio, and correlation between returns on art and other assets (e.g. equities, real estate, or gold), composition of an optimal art portfolio, as well as market inefficiency, anomalies and resulting potential opportunities for arbitrage. All those issues will be discussed in detail in the following chapters.

In the light of the above mentioned findings, one final question should be asked, namely why is it still commonly believed that art is a superior investment that offers extraordinary gains? As Frey and Pommerehne (1989a) argue, it might be partly due to the representation bias of our memory, which tends to be selective and puts an inadequately high weight on the few publicized auction records, but neglects other, less stunning sales. It might also result from the fact that investors tend to underestimate the effects of inflation and thus consider only nominal rates of return. But the most obvious explanation are the intensive publicity efforts made by the auction houses and media hype sparked by ‘superstar’ sales. While the most spectacular transactions form just a small fraction of the total market turnover, studies on art investment analyze sales that occur at different auction houses, at various points in time (Holub et al., 1993).

In general, although art might underperform alternative forms of investment in the long run, one should be cautious about drawing any final conclusions on its (inferior) financial performance. The first caveat is that there were times, artists, artistic schools, etc. that offered extraordinary gains to the potential investor. Two periods in particular, namely the 1950s and 1960s, as well the end of the 1980s have seen returns on art investment which rivaled those yielded by financial assets. And even though risks involved might be relatively high, as argued by many authors, returns on art investment, especially within shorter time periods, could be still large enough to compensate the high volatility of art prices. On the other hand, some researchers observe low (or even negative) correlation between returns on art and other assets, which would suggest that art could play an important role in portfolio diversification (for more details see chapter 4 Art investment, section 4.4.Portfolio diversification). Moreover, it is still open to debate whether there is a certain degree of predictability to art price behavior. If this is true, with the right skills, expertise or insider knowledge, it could be possible to make substantial gains by allocating funds into art. In fact, Chanel et al. (1996, p.19) suggest that the idea of the predictable nature of prices cannot be rejected, for ‘most statistical tests do not show that returns cannot be forecasted but only that these are not “very” forecastable’.


2.3. Limitations and shortcomings


Thus far, a consistent approach towards measuring returns on art investment has not been developed. Since previous studies concentrate on different sub-markets and time periods, their major shortcoming is that, in many cases, it is not really possible to compare or generalize the obtained results. Furthermore, as the non-transparent nature of the art market allows one to analyze only the auction market, where the data is publicly available, it is hard to estimate whether the biased figures should be adjusted downwards or rather upwards. In the following sections, I discuss some further serious limitations, which, to some extent, undermine the reliability of the empirical findings.


2.3.1. Auction data


The first major shortcoming common to most studies3 is their reliance on auction data. This is a source of a significant bias, since auction transactions account only for around 25 per cent of all the sales performed on the art market (Sagot-Duvauroux, 2003). But whether this inflates or depresses the obtained rates of return is hard to estimate.

Moreover, analysis based on auction data may result in further biases. First of all, not every hammer price is necessarily a sale price, since the artwork might be ‘bought in’4. This clearly inflates the prices and therewith rates of return5. On the other hand, a complete omission of ‘bought-in’ works in the data set could also lead to a bias, e.g. if the item is sold in a private transaction once the auction is finished. Second, relying on auction data implies the so called ‘survivorship bias’, which is a consequence of the complete disappearance of some artworks from the market, usually due to unfavorable changes in tastes or fashions – only those works that do not fall out of fashion (or are not bought by or donated to a museum) and remain in demand reappear on the market (Goetzmann, 1996).

Other serious limitations result from the specific nature of the auction market. Many auction houses, especially the most renowned ones, such as Sotheby’s and Christie’s, accept only top-quality artworks or those that could potentially enjoy high demand. This contributes to the sample selection bias and, since many studies are limited to the transactions performed at the major auction houses, might result in an overestimation of the rates of return. It should be noted, however, that the sample selection bias is not only inherent to auction data in general. Many studies select the underlying samples based on subjective criteria, e.g. they choose only artists living in a particular city, born at a certain point in time or having high reputation6. As a consequence, the obtained results may not be representative for the whole art market.

Furthermore, following Guerzoni (1995), Frey and Eichenberger (1995a) suggest that auction prices should be perceived as wholesale, rather than retail prices, for they refer mostly to dealers and not private collectors7. If private buyers pay higher and obtain lower prices, relative to dealers, there might be also differences in the rates of return, which would depend both on buyer’s and seller’s identity.

In conclusion, it should be, however, noted that auction data is the only publicly available source of information on transactions performed on the art market, since the access to prices charged by art dealers and galleries is usually restricted. Moreover, as many art dealers purchase works at auctions, it is possible that auction results serve as guideposts for art prices on the secondary and primary market (Candela and Scorcu, 2001).


2.3.2. Reitlinger data


In his three-volume compendium ‘The Economics of Taste’ Reitlinger (1961, 1963, 1970)8 records auction data on some 5,900 sales that occurred between 1760 and 1960. In the introduction to the first volume, the author says (1961, p.241): ‘Painters have […] been included either because they have been fashionable at one time or another or because they have generally been recognized as classical.’ This statement alone shows the first major limitation of Reitlinger data as a source of information on the auction transactions, namely the great extent of subjectivity in the choice of the recorded transactions9. Not only did Reitlinger collect information on the works by arbitrarily chosen ‘most popular’ artists, but he also narrowed the sample to the high- and low-end works (Guerzoni, 1995). Finally, there is a significant overrepresentation of late 18th Century paintings, relative to other artistic schools, as admitted by the author himself (1961, p.241).

Another quote from Retlinger (ibid., p.242): ‘Unless otherwise stated, the items refer to London sales. Until 1920 or thereabouts this means with few exceptions sales at Christie’s.’ further supports the sample selection bias. In fact, transactions performed with the intermediation of Christie’s account for over 75 per cent of the recorded data (Guerzoni, 1995). Finally, Candela and Scorcu (1997) argue that Reitlinger data does not include small-sized paintings, which is another source of bias.

Holub et al. (1993) compare Reitlinger (1961, 1963, 1970) with other data sets, and detect substantial inconsistencies and contradictions. Guerzoni (1995) mentions an additional serious limitation of Reitlinger data – it does not contain information on the parties involved in the transaction. As a consequence, it is hard to verify whether no transactions between the subsequent sales occurred10. Furthermore, Candela and Scorcu (1997) claim that transactions recorded by the author encompass not only auction sales, but also other deals (this, however, could be seen as both the advantage and limitation of this database).

A further shortcoming of Reitlinger data set that seriously affects the outcomes obtained with the use of repeat-sales regression (for more details see chapter 4 Art investment, section 4.2.1.Repeat-sales regression) is the small number of transactions recorded for the earlier periods. Moreover, some limitations of Reitlinger data have also serious implications for those studies that apply hedonic regression (for more details see chapter 4 Art investment, section 4.2.2.Hedonic regression). Since it contains a very limited number of information (e.g. it does not record detailed characteristics of paintings), relying on Reitlinger data may result in inaccurate estimates11. However, this shortcoming is also inherent to many other sources of auction data.

The limitations of Reitlinger database can be clearly seen when comparing the studies of Baumol (1986), and Buelens and Ginsburgh (1993). Even though the authors use the same data set and apply the same methodology, they arrive at a different number of observations (640 and 723 transaction pairs, respectively), which has implications for the obtained results. Buelens and Ginsburgh attribute this discrepancy to the subjective treatment of inconsistent information on sales recorded by Reitlinger.

On the whole, due to the above mentioned limitations, it is possible that the estimates based on Reitlinger data are biased and most probably upwards (Guerzoni, 1995).


2.3.3. Transaction and other costs


Since transaction costs (i.e. seller’s commission and buyer’s premium) vary across auction houses and countries, as well as time periods, and change both with the artwork’s estimated value and seller’s identity12, most researchers13 do not take them into account in their calculations. Moreover, some substantial additional costs, such as insurance, maintenance, restoration and cleaning costs, borne by the owner should be taken into consideration, especially since they are usually grater than those encountered on financial markets. Also the inability to correctly identify their extent for the earlier periods forces researchers to leave them out of their calculations. On the whole, this biases the resulting rates of return upwards and depresses the risk. However, it should be noted that some researchers (e.g. Frey and Pommerehne, 1989a) argue that costs are of importance only within short holding periods, since they can be spread over time in the long run.


2.3.4. Taxes


Due to substantial discrepancies in tax laws during various periods, as well as a lack of their harmonization across countries, researchers do not take taxes (e.g. VAT, sales and property tax, death duties) into account. In addition, there are differences in potential tax benefits14, as well as regulations considering resale right (‘droite de suite’)15 associated with purchases and sales of artworks. Furthermore, seller’s and buyer’s identity is usually kept secret, which makes it unclear which country’s tax rates should apply to the transaction. Finally, it is hard to estimate the real effective tax burden and/or benefit associated with buying or selling an artifact (Frey and Eichenberger, 1995a). It is, among others, because tax regulations may differ from the day-to-day practice (Frey, 1997). As a consequence, the obtained rates of return are probably overestimated.

2.3.5. Measurement method


Since most researchers generally adopt two approaches towards measuring the returns on art investment – hedonic and repeat-sales regression, I will narrow my focus only to the limitations of those two methods (for more details on those and other methods see chapter 4 Art investment, section 4.2.Art price indices).

The nature of repeat-sales regression is a source of a significant bias, namely sample selection bias, since only works sold at least twice are included in the sample. By focusing on artifacts subject to repeat sales, the sample is drastically narrowed16. Therefore, only transactions involving artworks for which demand is high enough for at least two sales to occur (e.g. those that did not fall out of fashion and/or are of superior quality) are registered by the repeat-sales index (so called ‘survivorship bias’). According to Goetzmann (1993), this implies that repeat-sales method does not account precisely for the stylistic risk resulting from shifts in demand due to changing tastes and fashions. The author also argues that an artwork will not be put up for sale by its owner unless its (expected) market price has increased, which means a further exclusion of certain artworks from the sample. Furthermore, repeat-sales regression does not control for the external factors or changes in quality that might occur between two sales and affect the price of an artwork. Holub et al. (1993) suggest that, by reducing the number of observations, returns on particular segments calculated with the use of repeat-sales regression cannot be generalized to the whole art market.

The already mentioned limitation of hedonic approach is the dependence on the available information. If an insufficient number of variables is used, hedonic regression may fail to capture the ‘true’ quality of a painting, which might, in turn, result in biased estimates of returns.

In their work, Chanel et al. (1996) compare the rates of return calculated for different periods with the use of repeat-sales, hedonic and geometric repeat-sales (double-sales) approach. The discrepancies between the obtained estimates show that the choice of the measurement method can have a decisive impact on the results. It seems that until researches develop a superior, standardized method of measurement, the evidence on most issues concerning art investment will be mixed and many questions will probably remain unanswered.

Finally, a general criticism addressed at both measurement methods is that they fail to account for the external factors that may influence the demand and supply side (e.g. changes in tax regulations). As a result, price movements may be misinterpreted and attributed to wrong factors. Moreover, as pointed out by Frey (1997), in their empirical analyses, most authors rely on quantitative methods, whilst neglecting more qualitative approaches (e.g. structured or semi-structured interviews with art market participants and practitioners), which could provide them with better insights into the workings of the art market.


2.3.6. Identification of paintings


With the ever growing availability of information and easy Internet access, this limitation seems to lose on importance. However, when applying repeat-sales method, it should be borne in mind that identifying a pair of transactions involving the exactly same artwork is crucial to obtaining a reliable outcome. Unless an artifact is identified by the catalogue raisonné number or provenance, one cannot be sure to have found repeat sales of the exactly same work without verifying it visually. Therefore, whenever any doubt related to a particular artwork occurs17, the researcher should make sure it is correctly identified or exclude it from the sample. This is of particular importance when relying on Reitlinger data set, since it includes no descriptions of artifacts. The best way to avoid misattribution is to check the relevant photographs and information on e.g. provenance in the auction catalogues, and to consult the auction house.


2.3.7. Alternative asset classes


One of the crucial problems when determining the relative financial performance of art is to choose the rate of return on alternative assets. The most commonly used benchmarks are financial assets, such as government bonds and stocks, predominantly the U.S. and British, less commonly other assets, such as gold or real estate. The first question that arises is whether financial assets are the most appropriate for making such comparisons, especially for the earlier periods. One could argue that due to some similar characteristics, returns on real estate could be a more suitable benchmark (Frey and Eichenberger, 1995a). Moreover, the authors’ subjective choice of the rates of return on alternative forms of investment used as reference points is somehow questionable, since they usually focus on two major financial markets (i.e. the U.S. and U.K.). It could be equally argued that foreign buyers and sellers may be more interested in the rates of return yielded by various instruments in their home countries. Moreover, for the periods under study, the used benchmarks are often aggregate figures and sometimes even rough estimates18. Finally, those numbers may be biased downwards, since they usually do not account for reinvestment of capital gains or dividends. On the other hand, they are not adjusted for commission and brokerage fees, or taxes, which has a reverse effect (Landes, 2000).


2.3.8. Comparability of results


Due to various time periods and samples studied, as well as different measurement methods applied, the obtained results should be interpreted and compared with great caution. In particular, the choice of the (base) period has a great impact on the outcomes. As some examples (e.g. Pesando, 1993 and Pesando and Shum, 1999) show, even extending the period by a few years might result in a substantially different estimate, especially in times of booming or rapidly declining prices. Another shortcoming is that there is inconsistency across studies as to whether the reported figures are given in nominal or real terms. In addition, the authors have varying approaches towards the use of inflation rate when deflating the returns on art investment19. The same applies to the choice of currency20.


2.3.9. Psychic returns21


Although most studies account for the existence of psychic returns (consumption benefits), very few go beyond that, and only Stein (1977) names a concrete figure. As noted by Frey and Eichenberger (1995a), many authors calculate the extent of psychic returns as a difference between the rate of return on art and alternative forms of investment, which, considering all the above mentioned limitations, is probably a very rough estimate. Moreover, it still remains to be answered whether the inferior rates of return yielded by artworks can be attributed to the existence of consumption benefits. It could be equally argued that investors, and pure speculators in particular, do not derive viewing pleasure from the purchased works. Moreover, this argument would also imply that if financial returns on art investment exceeded those on other assets, artworks would not generate any psychic benefits to their owners. On the other hand, the method suggested by Stein (1977) (i.e. measuring consumption benefits based on CAPM, with average rental fees for art objects used as a reference point) could be also questioned, due to the thinness of the art rental market (Frey and Eichenberger, 1995a)22. Another related limitation is that the studies rarely account for the behavioral, as well as institutional aspects, and often do not recognize that buyer’s and seller’s identity and/or type may be of importance when measuring the rate of return.


In conclusion, although all those limitations undermine the reliability and accuracy of the results concerning art investment, thus far no better approach has been developed. Holub et al. (1993) suggest that the shortcomings of previous research on the returns on art investment cannot be overcome, which precludes the possibility to draw any final conclusions on this matter. However, even though the results may be biased, it could be equally argued that a number, even an erroneous one, is better than no number, but only if interpreted with caution.

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