Charles Holt Teaching:  

The UVA Economics Department has a culture of excellent teaching at all levels; and each person has their own style, although most of us are motivated by the inspirational examples set by Ken Elzinga and Lee Coppock.  My own teaching is closely associated with my research in experimental economics.  My classes are participatory, based on classroom simulations with subsequent lab reports (Econ 2820) or student presentations based on experiments that they design and run with the students in the class (Econ 4820).  Class experiments can sometimes morph into research experiments, and I am very proud of the many academic papers that I coauthor with UVA students and lab research assistants.  One of these papers, coauthored with an engineering student (Ricky Sahu) and a former doctoral student (Angela Smith), was recently awarded the Southern Economic Journal Georgescu-Roegen best paper (runner up) award. 

I also promote my style of teaching more broadly in the profession.  Since 1996, I have published one classroom teaching experiment paper per year (27 total in a special section of my CV).  This year’s paper is “Cost Curve Confusion,” coauthored with Erica Sprott, 2021 Econ DMP,  is forthcoming in the Journal of Economic Education. along with 2 other papers by UVA colleagues (Lee Coppock and Robert Brunner).  These papers were presented in a special session on “Teaching the Crisis” that Lee Coppock and I organized at the 2023 ASSA Meeting in New Orleans, where I also received the inaugural American Economic Association Distinguished Economic Education Award. 

I write all of the textbooks that I use, and I do all of the programming for the free web-based Veconlab software that is used at UVA and in many classes around the world (about 15,000 student logins each month).  The writing sample that follows shows the preface, table of contents for a new book manuscript (coauthored with Erica Sprott) that is currently under review.  I love our non-definition of a price bubble at the end of the “What Economists Don’t Do” subsection of the chapter on price bubbles that follows:  

To conclude, there is no need to define a price bubble, since bubbles are like tidal waves, you’ll recognize one when you see it, but you probably won’t see it coming!

Experimenting with Economics: 

A Behavioral Appetizer

Charles A. Holt, University of Virginia, and Erica R. Sprott, Harvard University

 This book is intended to provide an experience-based introduction to economics, with a behavioral focus and an active-learning component based on classroom exercises.  It may be used as a textbook in a stand-alone course, as a quick economics review for professional school students (MBA, Law, or Public Policy), or as an outline to be supplemented by more diverse readings and applications. 

The presentation is organized around a number of basic principles that underlie an economic way of thinking.  These insights are so important that they should be reinforced by a process that allows students to discover the main ideas for themselves after participating in a classroom simulation or online “experiment.”  The goal is go beyond documenting behavioral anomalies and help students navigate and anticipate them in a manner that promotes a deeper understanding and better decision making.

Each chapter has an associated lab report that provides fill-in-the-blank structure for responses and the construction of figures.  The lab reports are available in a format that permits easy copying and distribution during class, so that students can work together after the experiment is finished. The motivation is that students do not have to read a lot to learn a lot. 

The first three chapters introduce economic thinking and analysis from a behavioral perspective: notions of trust, gains from trade, and marginal analysis.  Chapters 4-6 cover basic economic concepts and the price system.  Chapters 7-10 are focused on market failures due to monopoly, public goods, externalities, and rent seeking.  Chapters 11-13 introduce notions of risk and mechanism design in strategic games and auctions.  The final chapters cover behavioral issues that arise in a macroeconomic setting: bank runs, financial markets, and the role of money.

Each chapter is organized around a classroom simulation or experiment. Although the earnings will not typically be paid in cash, students will have the chance to get an insider’s feel for how markets and other economic games are played out in a setting that permits interpersonal earnings comparisons.   The experiments provide data for the lab report that will be used to develop a hands-on understanding of simple (but important) economic insights. 

Chapters begin with some warm-up exercises that introduce the context of the experiment, along with relevant parts of the instructions that will be encountered later.  The instructor will set up the experiment and provide the link to access instructions and decision pages online, either during or after class.  Some instructors may prefer non-computerized versions, especially for highly interactive exercises like market trading, and the experiments in many chapters can be done either way.   The subsequent lab report helps students discover the main points and make the transition to understanding economic concepts that are explained in more detail in standard textbooks.  The “What Economists Do” sections discuss policy applications of the main points. A summary section provides some examples and a big-picture perspective. Finally, there is an end-of-chapter quiz.  The goal is to help students understand fundamental economic concepts through an enjoyable interactive experience!

Instructions for Software Use (for Instructors)

All classroom experiments are freely available online through the University of Virginia’s Veconlab site (https://veconlab.econ.virginia.edu/). Instructors who are first-time users of Veconlab software should first select “Login as Administrator" and then “Get Started” and “Register” to obtain a username profile for future use.

The Veconlab programs for this book can be accessed through the “Experimenting with Economics” menu on the main page.  This menu provides a suggested sequence of topics (1-16) that match the chapter numbers of this book. After selecting the desired program, the instructor can login using their user profile. For the simplest setup, choose the default settings for each program, and adjust maximum number of participants to fit class size.  Specific setup hints are provided in the shaded Notes for Instructor entry in the Notes section at the end of each chapter.  After setup is complete, the session name will be displayed at the top of the instructor’s screen, which is provided to the students.  Then students can join as participants by selecting “Login as Participant” from the Veconlab (https://veconlab.econ.virginia.edu/) home screen and entering the announced session name. Students begin by entering their names and an optional password before proceeding with the instructions, which are configured automatically to match the setup specified by the instructor.

 Chapter (15): Asset Markets and Present Value

Introduction and Motivation (Omitted), Experiment Instructions (Omitted), Lab Report  (Omitted)                                   

Summary of Evidence from Asset Market Experiments and Field Data

In laboratory experiments, optimistic traders can drive prices up more easily if they have the necessary cash to make high bids.  Consistent with this intuition, the presence of “excess cash” has been identified as a factor that tends to stimulate price bubbles.  Conversely, if the interest rate is low or if dividends are not paid until after the final period, then the lower cash holdings will tend to dampen speculation.  Cash holdings in naturally occurring markets can be reduced by exogenous factors.  Much of the stock market runup in the later Covid years could have been driven by the cash rescue payments that most people in the US received.  Similarly, loose credit with minimal down-payment requirements were common in the boom years prior to the 2008 crash in housing prices.  Economists have also documented the effects of testosterone (in males) and sleep deprivation, both of which tend to enhance laboratory bubble activity.       

Just as excess cash is a reliable driver of price bubbles in laboratory experiments, these speculative tendencies can be depressed by using subjects with prior experience in laboratory market bubbles and crashes.   But even prior experience is not effective at restraining prices if some aspect of the asset structure has changed, which is the “this time is different” argument to be discussed in the next section.

What Economists Don’t Do

Economists can provide general warnings about speculation during price surges, but what they do NOT do well is to tell people what they really want to know: when should I sell, or will the market turn abound by late summer?  If you are an economics major, you have probably already encountered these kinds of questions at cocktail parties with relatives and friends of your parents. 

It’s hard to answer questions about timing.  In all likelihood, very few people in your class this semester anticipated that rising stock prices in the class simulation would be reversed so quickly.  Similarly, investors did not seem to anticipate the sharp stock declines that followed the price surges of “tech” stocks in the late 1990s. Prior to the “dot com” bust, a Stanford economist who was participating in a National Science Foundation panel discussion boasted: “I teach a course on the economics of the internet, it’s so popular it that it would fill up even if I named it the econometrics of the internet.  I tell my students, these tech stocks are over-priced; where is the barrier to entry, where is the patented idea?”  He was right, of course, and the dot-com prices crashed soon after, but timing issues were not so clear at the time.  Another economist at that same panel meeting chimed in, saying “yes, I sold all of my stocks.”  On further questioning, it was revealed that he sold his stocks in the early 1990s, so he missed one of the largest price runups in history! 

Only a few years later in 2007, Eugene Fama (a subsequent Nobel Prize winner)  quipped: “The word ‘bubble’ drives me nuts.”  He also suggested that the high valuations of technology stocks during the “internet bubble” could have been justified by 1.4 firms of the same size as Microsoft.  As for housing, he made the argument that a home purchase is the most important decision that people make, so they are very careful about considering prices of comparable houses.  That sounds OK, but what if everything is over-priced, including the “comps”?  

When one of the authors asked an experimental economist at that time whether assets were overpriced, the answer “no, this time is different… because everything is international.”  Although it sounded reasonable, this argument turned out to be seriously flawed, since international connections caused the 2008 crisis to spread around the world.   Economic historians who study business cycles know better, as indicated by the title of a 2011 book by two economic historians: This Time is Different: Eight Centuries of Financial Folly (see end of chapter notes).

Figure showing Shiller Housing Prices by City (omitted)

Vernon Smith, another Nobel Prize winning economist, did correctly guess the timing of the housing bubble crash.  In 2007, his colleagues at George Mason were asked “How does Vernon like his $900,000 Arlington penthouse apartment?” The answer was that he had sold it, thinking that prices were too high. Later during a post-crisis NPR interview, he was quoted as saying “I believe in that great American value of home rentership!” 

The takeaway from laboratory experiments done by Vernon Smith and others is that easy credit and “excess cash” can create price bubbles, especially when there is an influx of new investors or home buyers.  But history does not reveal how to spot a causal factor that might trigger a downturn; such factors often arise from new technologies or market connections like crypto currencies, mortgage-backed securities, or even the 1907 San Francisco earthquake that stressed insurance providers and New York banks.

To conclude, there is no need to define a price bubble, since bubbles are like tidal waves,

you’ll recognize one when you see it, but you probably won’t see it coming!