A Critique of Beggs and Graddy’s RAND Journal of Economics paper

A Critique of Beggs and Graddy’sRAND Journal of Economics paper Artie Zillante UNC Charlotte Prepared for: ECON 6901, Spring 2014

Objectives of this talk • Provide an overview of Beggs and Graddy (1997) • Provide a critique of Beggs and Graddy (1997) • Discuss how the paper has been (or can be) extended • Discuss how your interests can lead to a potential topic • Throughout I will discuss dos and don’ts of presenting

Beggs and Graddy question(s) How does final bid relative to auctioneer’s estimate change over the course of an auction? What can explain this behavior? (Always tell the audience what question(s) you are answering very early in the talk)

Findings • Over the auction, final bids decline relative to auctioneer estimate • Result can occur even if bidders are risk neutral • Ordering heterogeneous items by value maximizes revenue for the seller (“policy prescription”) (Always give findings early in the talk when people are paying attention)

A Note about Slide Design • These slides are not very busy • They do not have a lot of extraneous pieces that take up much space – just the circle in the lower right hand corner and a little along the right edge • There is a little color on the slides but not an overabundance • The slide title is at the top – some layouts have the title at the bottom, which goes against how most, if not all, written material is read

Art Auctions • Contemporary Art • Christie’s King Street location • 1980-1994 • Impressionist and Modern Art • Use Ashenfelter and Richardson data • London and New York auctions at Christie’s and Sotheby’s • 1980-1990

Beggs and Graddy Data Do NOT copy a table from your paper and use it as a slide Unclear from table what these mean

Beggs and Graddy Data • Provide many summary statistics – good because people do not know their data • Provide a detailed description of how they obtained the data – good • Their tables are oftentimes spread across multiple pages – bad because this makes it difficult for the reader to keep track of things (Hint: Make life easy for the reader)

Theoretical Model • Build a theoretical model to motivate their findings (I am not going to go through the details) • While we will not ask you to build your own theoretical model, you can use an existing one as a basis for your research question • It will help tie your theory and empirical courses together • If there are competing theoretical models your findings can hopefully lend support to one of the explanations

Theoretical Model – Critique • Fairly general model that leaves out a lot • They mention multiple omissions: • Valuations are perfectly correlated • Buyers only want one item • Cash constraints are omitted (If you are going to use a theoretical model for guidance, make sure it is applicable.)

Back to the Data • Dependent variable(s): • ln(bid price) • ln(presale estimate) • ln(bid/presale) • Independent variables: • Order (I’m still not quite clear on this) • Painting characteristics (length, width, date, signed, etc.) • Presale estimate (in some models) and high/low spread • VAT • Dummy variables

Data Critique • Dependent variables – these are fine • More information in the table would be helpful to know it is ln(variable) • Concerned about nonlinear effects of order but the log-linear specification alleviates some concern • Note: Be careful when including counts or discrete time periods as independent variables • Independent variables • Seems like they have incorporated all the information they have, though again the form of the variable is unclear at times (I don’t think they have information on bidders, just the paintings) • I wonder if there is a general time trend in prices (1980 vs. 1994)

Econometric Models • They use an OLS model • Dependent variable is about as continuous as a variable will get • Dependent variable does not seem to be censored in any way • The paper was published in 1997, so probably written in 1994-1995 – many of today’s techniques were not readily available back then • Their lack of available techniques could create an opportunity for you

Important point on model selection You will have to determine which econometric models to use when conducting your research. This is why you have taken (and/or are taking) courses in econometrics!!!

Results (I am not a big fan of these “transition” slides – my own belief that it is just an extra click with no real information.)

Again, do not copy and paste a slide from the paper! 6 decimal places!!! Also, standard errors are good but asterisks for stat. sig. would help

Results Critique • Tables • Lacking too much information for me (meaning it is difficult to understand the tables without reading the text) • Extended across multiple pages which makes them more difficult to read • Text • They do a good job in the text of explaining what they have done (though some of this could also be in a table caption) • They do a good job in interpreting their results (meaning they discuss the meaning of regression coefficients)

Robustness Checks • Numerous methods of performing robustness checks • Different econometric models • Different specifications of the same econometric model • Different slices of data • They focus on different specifications and different data slices • Regressions with/without covariates • Regressions with all auctions and only sold auctions • Regressions with changes

Extensions • More rigorous theoretical models • Chakraborty, Gupta, and Harbaugh (2006) • Lambson and Thurston (2006) • van den Berg, van Ours, Pradhan (2001) • Aalsmeer flower auctions • Critique the use of a regression of transaction price on rank number • Maximum rank number may vary by lots • Price observations in the sequential auction are likely not indepedent

Important points • Make sure that the reader knows what tests you are conducting • Do not hide from your results • Your job is to take the best data you can find and use the best methods to analyze the data • If a coefficient estimate is not statistically different than zero, what impact does that variable really have in your model? • Do not oversell your results – as a friend of mine said when we saw a conference presentation “That guy oversold and underdelivered” – don’t do that

Look to your own interests for topics • Think about how the markets in which you are interested work • Think about differences in industries in which you are interested

A Critique of Beggs and Graddy’s RAND Journal of Economics paper