The Performance of Contemporary Art As an Investment Good Conceptual Art in the United Kingdom Between 2000 and 2014
Total Page:16
File Type:pdf, Size:1020Kb
The performance of contemporary art as an investment good Conceptual Art in the United Kingdom between 2000 and 2014 The physical impossibility of death in the mind of someone living, by Damien Hirst, 1991 Thesis Cultural Economics and Entrepreneurship Meike Kaasenbrood, 332650 January 2015 Supervisor: Prof. Dr. Marilena Vecco Co-reader: Prof. Dr. Filip Vermeylen Contents Index of Tables and Figures .................................................................................................................... 3 Acknowledgement .................................................................................................................................. 4 Abstract ................................................................................................................................................... 5 Chapter 1 - Introduction ......................................................................................................................... 6 Part I - Theory and Context 9 Chapter 2 - Literature review ................................................................................................................ 9 2.1 Performance of art investment 9 2.1.1 Contemporary art 14 2.2 Psychic return 15 2.3 Problems with data 16 2.3.1 Selection bias 16 2.3.2 Bought-in bias 16 2.3.3 Transaction costs 17 2.3.4 Survivalship bias 18 2.3.5 Backfill bias 18 2.4 Art indices 19 2.4.1 Average Price Index 20 2.4.2 Advanced Indices 20 2.4.3 Repeated Sales Regression 22 2.4.4 Hedonic Pricing Method 23 2.4.5 Hedonic Pricing versus Repeated Sales Regression 25 2.4.6 Heckit model 26 2.5 Relationship between the art market and the stock market 31 2.6 Recent events 34 2.7 Motivation 35 Part II - Research 36 Chapter 3 – Aims, Objectives and Hypotheses formulation 36 Chapter 4 - Methodology .................................................................................................................... 38 4.1 Heckit model 38 4.2 Relationship art market and stock market 40 4.2.1 Ordinary Least Square regression 40 4.2.2 Granger-causality test 40 4.2.3 Vector Autoregressive model 40 4.3 Other researches 41 Chapter 5 - Data collection.................................................................................................................. 42 5.1 Explantory variables 42 5.1.1 Selection equation variables 43 5.1.2 Price equation variables 44 1 5.1.1 Hedonic variables: the painter 45 5.1.2 Hedonic variables: the painting 47 5.1.3 Hedonic variables: the sale 49 5.1.1 Other variables 50 5.1.1 Variables not included 50 5.2 Collecting the data 51 5.3 Data Handling 52 5.3.1 Medium attribution 53 Chapter 6 – Results ............................................................................................................................. 56 6.1 Descriptive statistics 56 6.2 Results of statistical analyses 62 6.2.1 Artist-specific dummies 62 6.2.2 Estimation of the model 65 6.2.2.1 Artist-specific hedonic variables 65 6.2.2.2 Artwork-specific hedonic variables 69 6.2.2.3 Sale-specific hedonic variables 74 6.2.2.4 Preliminary conclusions on Heckit estimates 76 6.2.3 Quarterly index 78 6.2.4 Art returns 80 6.2.5 Relationship art market and stock market 83 6.2.6 Heckit versus Hedonic Pricing Method 89 Chapter 7 - Discussion ......................................................................................................................... 92 7.1 Hedonic outcomes 92 7.1.1 Selection equation 92 7.1.2 Price equation 95 7.1.3 Selection equation versus price equation 97 7.2 Art index 98 7.3 Relationship art market and stock market 99 7.4 Heckit versus Hedonic Pricing Method 100 7.5 Limitations 101 7.5 Further Research 102 Chapter 8 - Conclusion ...................................................................................................................... 103 Bibliography ........................................................................................................................................ 105 Appendix A .......................................................................................................................................... 110 Appendix B .......................................................................................................................................... 114 2 Index of Tables and Figures Table Name Page 1 Performance of art indices 12 2 Attributes Hedonic Pricing method and the Repeated Sales Regression 21 3 Researches using the two-step Heckit model 29 4 Art market research using the Heckit model 30 5 Researches on the relationship the stock market and the art market 31 6 Additional variables of the selection equation of the Heckit model 43 7 Variables used for the two-step Heckit model 44 8 Difference Artvalue and Artprice 52 9 Medium attribution 54 10 Descriptive statistics regarding the sales 58 11 Mean and standard deviation of the price for each artist 59 12 Hedonic values of artist dummies 63 13 Hedonic variables included in analyses 66 14 Heckit estimates for the comprehensive model 71 15 Estimated coefficients of Quarter dummies 78 16 Coefficients of the Quarter dummies and nominal return 79 17 Mean and standard deviation financial indices and the CAI 82 18 Correlations between indices 85 19 Estimates of the Ordinary Least Square regressions 86 20 Granger-causality tests 86 21 VAR models 87 Figure Name Page 1 The distribution of the sales over the months 56 2 The distribution of observations in categories 57 3 The distribution of the sales over the different auction houses 57 4 Nominal Conceptual Art Index (CAI) with trimmed outliers 81 5 Real Conceptual Art Index, trimmed for outliers 81 6 Conceptual Art Index, FTSE 100, UK government bonds and UK 90-day T-Bills 83 7 The CAI using Hedonic Pricing method and the CAI using the Heckit model 90 3 Acknowledgement This thesis is the final stage in finishing my studies at the Erasmus University Rotterdam. In September 2009 I started the study trajectory at the Rotterdam School of Management. The choice for International Business Administration was a strategic one. It gave me the chance to postpone big life choices that I was not yet ready to make. The general character of the bachelor however quickly became a reason to look beyond academics and into practical areas to find out where my passions lie. This led me to Museum Boijmans Van Beuningen where I gained insight into the cultural sector and all its pressing issues. And so the seed was planted. I wish to thank my thesis supervisor, Marilena Vecco. She was a valuable addition to my thinking process. She guided me towards an interesting research topic and provided exciting sources to enrich my thesis. Without her help, I would have been working until April. Besides Marilena, another essential factor in the research process was Giacomo Di Benedetto. Thanks to Giacomo I was able to obtain data efficiently and interpret it correctly. Especially the combination of Marilena and Giacomo was much appreciated help. Furthermore I wish to thank my parents, who always challenged me in all my choices. They are also the ones who introduced me to the wide variety of academic fields that I could be active in, which made my life much more difficult, but eventually gave me more insight. I wish to thank my sisters. They helped me with every difficult step, both study related and social, that I took to get where I am now and who I know will be there with every next step that I take. Also I would like to thank the two recent additions to the family. They too were invaluable in this process and were always good for comic relief. Lastly I would like to thank my friends. They went through the same process that I went through during every stage of my student life. Therefore they were the constant reflection of my actions. They so were able to guide me to where I am now. 4 Abstract The art market has been the subject of academic research for decades. Research topics vary from art returns to the drivers of art prices to the relationship between the art market and the stock market. The limited accessibility of art sales data and the heterogeneity of artworks make it difficult to come to a conclusion on any of these issues. Scholars therefore come up with a variety of methods to overcome the data problems. One of these methods is an advanced application of the Hedonic Pricing method, called the Heckit model. This model decreases the selection bias that occurs in art market research by including non-sales in the sample. This thesis uses the Heckit model to obtain the Conceptual Art Index (CAI). The CAI is used to research the relationship between the Conceptual Art market and the stock market in the UK from January 2000 until October 2014. Prior researches have shown that there is a lagged relationship between the art market and financial markets. This thesis does not provide results that proof the existence of this relationship. The results show that there is no significant short-term relationship between the Conceptual Art market and the UK stock market. There is evidence indicating a long-term relationship, but the evidence is weak. Besides that, comparison of the CAI with an index obtained with a traditional Hedonic Pricing model shows that there is no significant selection bias occurring due to non-random selection. This latter result indicates that the Heckit model is not superior to the traditional Hedonic Pricing method. This thesis provides input for further research on the added value of the Heckit model as well as on the relationship between the art market and financial markets.