3.1 Behavioral Explanation

price bubble collapsed. Temin and Voth (2004) argue that some investors, in special Hoare’s Bank, were aware of the existence of the bubble and they could proft from it. In other words, the bank rode the bubble until it knew that were no more fools willing to enter into the market. Other investors did not fare that well and lost a lot of money in the South Sea Bubble. One famous investor was Isaac Newton, who purchased shares of the South Sea Company close to the top and lost 20.000 pounds (see, Kindleberger and Aliber 2005). To have a sense of the magnitude of the South Sea bubble, Temin and Voth (2004) document that the (log) decline in the stock of the South Sea Company was 2.12. They compared this fall with the decline in the stock price of Cisco during the Dot-Com Bubble. Cisco is a poster child of the DotCom Bubble episode and it experienced a (log) fall in the stock price of 1.49. Note that this decline represents only about the 70% of the collapse in the stock price of the South Sea Company. To summarize, the South Sea Bubble started with a fnancial innovation that attracted new and inexperienced investors into the market and ended up when enough investors understood that the profts of the company were based on a Ponzi scheme.

Our review of famous asset price bubbles concludes with the DotCom Bubble. In this case, the bubble was attached to technological companies. It is not clear when it started (the general consensus is around 1996) but we are certain of when it burst (March 2000). We can use the Nasdaq index to quantify the size of the bubble. The (log) decline in the index between the peak (March 2000) and the bottom (September 2001) was 1.11.2 Kindleberger and Aliber (2005) explain how, during this episode, technological frms had seemingly unlimited funding from venture capitalists before the companies went public (i.e., before their initial public offering, IPO). Since, in most cases, after the end of the frst trading date, the price of the stock was higher than the IPO, venture capitalists were happy to borrow to lend money to the start-up Dot-Com frms. This funding activity would be positive for the overall economy if only productive frms received these funds. However, it can be negative if frms receive funds only because they are labeled as technological and promise big returns in the future. An illustrative example of this second type of frm is the (short) history of Pets.com.

2 Data on the Nasdaq index is obtained from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/NASDAQCOM.

This company was a website that sold pet supplies. It was founded in August 1998, one of the most exuberant times of the Dot-Com Bubble. The IPO was $11 and it reached $14 relatively fast. It seemed another successful Dot-Com story. The company even featured in the Super Bowl commercials or Macy’s Thanksgiving Day Parade. However, once it became evident that it could not be a proftable frm (shipping costs were very high), it had to close in November 2000.3 This example helps us to illustrate the origin of the Dot-Com Bubble. The Dot-Com Bubble started because investors were convinced that a new technology (information technology, which also represented a reduction in communication costs) was disrupting the market and creating a “new era” (Shiller 2003) in which everything would be done through internet. As more people were convinced that this was indeed a new era and participated in the stock market, it further increased stock prices and “validated” their views. Once the Fed started to raise interest rates, venture capitalists became more selective and the number of IPOs declined. In addition, investors realized that some stocks were overvalued and started selling them, which burst the bubble. Finally, we also want to emphasize that not all frms founded thanks, in part, to the Dot-Com Bubble had the same fnale as Pets.com. Some of these frms are dominating today’s market like Amazon (founded in 1994) or Google (founded in 1998). That is, optimists could argue that thanks to the Dot-Com Bubble some productivity-enhancing frms were created, which spurred the economic growth of the economy. The pessimistic view would be that the asset price bubble also helped to fund useless companies and some households lost a large part of their savings in the stock market.

To conclude, note that all these boom-bust episodes can be summarized by the title of the infuential book of Kindleberger and Aliber (2005), “Manias, Panics and Crashes”. These episodes start when, given some technological (or fnancial) change, investors start investing in a particular asset. Then, other investors enter into the market convinced that the price of the asset is going to keep growing in the future (mania). The following step is that there is an event that makes some investors change their opinion on the possibility of reselling the asset to a higher price (panic). This event acts as a wake-up call and enough investors

3 For more information on the boom-bust of Pets.com, read the article in the New York Times (Nov 8th, 2000) https://www.nytimes.com/2000/11/08/business/technologypetscom-sock-puppet-s-home-will-close.html.

become convinced that prices are overvalued. At this moment, they sell their assets and prices collapse (crash).

2.3 Housing BuBBle indicAtor

Let us now focus on housing bubbles. As we discussed earlier, it is very diffcult to create a real-time bubble indicator. Nonetheless, we can compute a historical “world housing bubble indicator”, based on Jordà, Schularick and Taylor (2015). This exercise will allow us to have a historical perspective of the evolution of housing bubble episodes in the world in the last 40 years. This is the relevant period to spot housing bubbles, as shown in Knoll et al. (2017). They construct a house price index for 14 countries between 1870 and 2012 and document that real house prices were constant until the early 1960s, when this stability was broken and house prices started to rise and diverge across countries.

The procedure to construct this simple housing bubble indicator is the following. First, we compute a trend on house prices for each country. Second, we fnd the deviation of house prices from the trend. Third, we assign a housing bubble indicator for each country and quarter. The housing bubble indicator is one if in that country and quarter (i) the deviation of house prices from the trend were large and (ii) house prices fell in the near future.4 The main advantage of this indicator is that it picks the peak of the housing bubble. One shortcoming of this bubble indicator is that since the second condition requires that prices fall, it will not identify bubbles during the mania period.

As an example of how the bubble indicator works, Fig. 2.1 reports the specifc case of the United States. The red line represents the evolution of nominal house prices between 1980 and 2015. The most striking feature of the trend in house price is the boom-bust episode in the mid2000s. The index was 166 in March 2003 and it climbed up to 243 in March 2006 (an increase of 46%). At this point, house prices suddenly collapsed. Three years later, the index had fallen by 29% and it kept falling until June 2011, when it reached the same value as in March 2003. There is a general consensus that this boom-bust episode represents a

4 To be precise, frst we run, HPit = time + βi + uit, where βi is a country fxed effect and HPit is the quarterly house price index. Then, we predict HPit using the coeffcients of this panel regression. The bubble indicator is one if (i) the deviation is higher than ½*sd(HPit) and (ii) house prices are lower three quarters later.

1

.8

(Bubble Indicator) .6

.4

.2 250

200

150

100 (House Price Index: 1995=100)

0

1980 1985 1990 1995 2000 2005 2010 2015 50

Fig. 2.1 The housing bubble in the United States. Notes Bubble indicator is one if (i) the deviation of house prices from the trend is higher than ½*standard deviation and (ii) nominal house prices are lower three quarters later. House price indices from BIS Residential Property Price database (http://www.bis.org/ statistics/pp.htm)

housing bubble. Note that the bubble indicator is one between March 2006 and June 2007. Therefore, the housing bubble indicator correctly identifed this period as a bubble.

To have an overview of the historical importance of housing bubbles, we repeat the same exercise for the 23 countries with available data from the BIS residential price database.5 Figure 2.2 reports the evolution of the fraction of countries in the sample with a housing bubble between 1980 and 2015. We want to remark two features of this fgure. First, housing bubble episodes are not rare events. In 52% of the quarters

5 The list of countries covered in the BIS residential property price is the following. Australia, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland, Italy, Japan, Korea, Malaysia, Netherlands, New Zealand, Norway, South Africa, Spain, Sweden, Switzerland, Thailand, UK and the USA.

30

(% countries) 20

10

0

1980 1985 1990 1995 2000 2005 2010 2015

Fig. 2.2 World housing bubble indicator. Notes Bars indicate the percentage of countries in the sample with the housing bubble indicator equal to one. The bubble indicator is one if (i) the deviation of house prices from the trend is higher than ½*standard deviation and (ii) nominal house prices are lower three quarters later. House prices indices from BIS Residential Property Price database (http://www.bis.org/statistics/pp.htm)

between 1980 and 2015, the bubble indicator was one for at least one country in the sample. Second, the evolution of the world bubble indicator post-2000 seems different. Indeed, the housing bubble episodes in the 2000s had a multi-country component that was not present before. For instance, the peak of the world bubble indicator pre-2000 was June 1991–September 1992. It involved three countries, Switzerland, Japan and Korea. In contrast, the largest peak in the sample occurred between March 2008 and June 2008. In this case, the bubble indicator was one for seven countries: Denmark, France, Ireland, Netherlands, South Africa, Spain and UK. The housing bubble in the United States had collapsed two years before. Finally, it cannot be seen in the fgure but the size of the bubble (computed as the deviation of the house price index