Visualizing History

Housing Prices and Rents Around Epidemics 

From the Archives

Thrift is Basis of Film Fortune (1933)

In 1933, the Indianapololis Times did a fascinating six-part series on businessmen that made fortunes during the Great Depression. As we encounter our own crisis today, this article serves as a timely reminder that disciplined businesswomen and businessmen (as well as investors) can find good opportunities in dark times.

This article focuses on the story of Columbia Pictures. You know, the movie studio / production company that you always see at the beginning of popular movies?

Well this piece describes how the two brothers running Columbia Pictures, Harry & Jack Cohn, were able to take advantage of their disciplined and budgeted approach during the Great Depression as other studios that had spent recklessly went into bankruptcy.

‘During the last two years when many moving picture firms have been going into receivership or otherwise suffering financial pangs, a small  outfit, Columbia Pictures. steadily has been growing and strengthening its position. The result is that its ratio of current assets to liabilities is 3 to 1.’

Read the whole article (it’s short), but the Cohn brothers learned their lesson in being disciplined with spending after their movie ‘Traffic in Souls’ made an enormous profit:

‘But to the Cohns, Harry and Jack… “Traffic in Souls” spoke another message in terms of the balance sheet. It cost $5,700, as Jack Cohn woll knew from having helped produce it, and its gross earnings were $450,000.

“Therefore,” reasoned the brothers Cohn, “it isn’t necessary to shoot the works like a drunken sailor to earn money on a picture.” That idea steadied them through all the years in which they saw film giants waging a battle of bankrolls  around them. One depression fortune has been built in the movies apparently, and it belongs to the Cohns of Columbia Pictures.

As the larger companies have gone into receivership or suffered reorganizations and accumulated headaches. Columbia has enjoyed the best business in its history. It is earning more and has more to spend than ever before. During the bank holiday in March, most of the Hollywood studios also took a holiday; virtually most all of them cut salaries in half.’

This is an incredible story of good business management. The fact that Columbia Pictures remains a dominant player in the industry almost 100 years later is a testament to their approach.

Sunday Reads

After yet another volatile week in markets, this week’s roundup of financial history links takes a deeper dive into investing through crises. As the Columbia Pictures example above demonstrates, good business practices and operations are rewarded in hard times. Similarly, disciplined investors today have the opportunity to take advantage of the downturn and identify good companies with strong business fundamentals (like a Columbia Pictures) trading at cheap valuations.

To best prepare investors for what may lie ahead, this week’s links focuses on some of the key questions facing investors today.

  • How will coronavirus affect the housing market?
  • How the US economy impacts presidential elections (1828 – 2008)
  • What is the relationship between oil prices and equities?
  • How can we track investor sentiment as an indicator of where markets are headed?
  • Who panics during a panic? Institutional investors? Retail investors?
  • What are the roles of banks in a panic?

Without further ado, let’s dive in!

Housing Markets in a Pandemic: Evidence from Historical Outbreaks

Cholera Prevention Man

As we all continue trying to navigate through these uncertain times with volatile markets, I will continue to share any new articles I find that provide historical context on financial markets and pandemics. This week I’ve included a fascinating article on the impact of pandemics on urban housing markets through case studies on 19th century Paris and 16th/17th century Amsterdam.

The results show that during an epidemic, housing prices fall roughly 5.5% a year, and then fall a further 4.1% after the epidemic. However, the positive news is that these declines are short-lived, with both Amsterdam and Paris displaying quick bounce-backs following their respective epidemics. The authors state that ‘real house prices and rents grew in the decades around the epidemic by almost one percent per year – significantly above their historical average.’


As the chart below demonstrates, Amsterdam was no stranger to the plague during the 16th and 17th centuries. The most severe plague in this period killed a staggering 10% of the city’s population, and it’s possible that the real figure is even higher due to under reported data.

As it turns out, the citizens of Amsterdam had a very similar experience to what we’re living through right now in terms of social distancing. The best example is found in the ‘Plague Law of 1558’, which forbid the population from ‘visiting markets, inns, and churches during epidemics, as well as any other place where many people gathered.’ 

Additionally, many industries were shut down by the government in efforts to prevent spreading the disease. The description below sounds exactly like the problems facing hotel chains, restaurants, airlines, and other affected industries today:

‘After the 1617 epidemic, owners of inns complained that they lost most of their income because travelers avoided the city due to the epidemic. In the 1635 epidemic, Amsterdam merchants halted all orders from the textile industry in Leiden because they were afraid of the spread of the plague. In Hoorn, a town nearby Amsterdam, a chronicler wrote in 1656 that all businesses and artisans have shut down by now, and people have not much else to do than to help the sick.”

However, a positive takeaway from the city’s unfortunate battle with an epidemic is that the economic impact was short-lived, and did not stunt Amsterdam’s long-term growth .

‘The frequent plague outbreaks do not seem to have prevented Amsterdam’s growth over the longer term. Between the late 16th century and the late 1660s, the period of the most severe epidemics, Amsterdam rose to prominence and established itself as the merchant capital of the world. Its population rose from about 30,000 in the 1580s to over 200,000 in the 1660s, and in their landmark work on the Dutch economy, De Vries and Van der Woude classified this period as the first round of modern economic growth.” So while plague outbreaks vaged the city over the shorter-term, migration towards Amsterdam stayed very high, resulting in significant population growth over time.


The first outbreak of cholera in Paris occurred in March 1832, and killed more than 11,500 people in the first month alone. Eventually, the outbreak killed roughly 2.5% of the city’s population. In 1849, cholera returned and claimed the lives of another 1.5% of Paris’ population. In some areas of the city with higher population density, cholera killed up to 6% of the neighborhood’s community. The exhibit below shows the death rate per 1000 inhabitants by sections of Paris:

If there was a silver lining, however, it was that the worst hit areas of Paris (which were essentially slums) were cleared away and rebuilt to higher sanitary standards following the first cholera outbreak in 1832.

‘When Count de Rambuteau came to power in Paris in 1833, he proclaimed that his mission was to provide “air, water and shadow” to all citizens in Paris, and started clearing unhealthy housing in the worst-affected central areas of the city, as well as introducing public urinals to improve sanitation…

The epidemic in 1849 confirmed the validity of Rambuteau’s approach: mortality levels were still much higher in the working-class areas in the cities on the left bank but had gone down in the historical city center, where much of the slum housing had been cleared . This confirmation paved the way for massive renovations: the Hausmann renovations that took place in the late 1850s and 1860s destroyed a large part of the unhealthy medieval Paris and gave Paris the image it still has today.’

As far as the outbreaks’ impact on housing prices, for the 1832 outbreak:

‘Between 1832 and 1836, high-mortality areas fall significantly in prices relative to low-mortality areas, with a relative price drop of 7.3%. Reassuringly, this drop is more significant in areas profoundly affected by cholera in 1832 compared to 1849. Until the mid-1840s, house prices between high and low mortality areas remain at relatively stable levels, except for a slight but insignificant jump in 1840.’


US Crude Oil and Stock Market Prices: 1859 to 2013

To say that oil markets have been volatile over the last month would be the understatement of the year. As of April 3rd, oil prices are down roughly 50% year-to-date. With news of a potential OPEC production cut being worked on at the end of last week, prices rallied. After everything that’s gone on in this area of markets in 2020, however, this is a good opportunity to review the long-term relationship between oil prices and equities.

‘This paper examines the relationship between US crude oil and stock market prices… [using] a monthly data set from 1859 to 2013. Our sample period begins at the time usually identified as the modern era of the petroleum industry, which links to the drilling of the first oil well in the US at Titusville, Pennsylvania in 1858. The early part of the 20th century saw the major international oil companies capturing control of the pricing of crude oil, This control continued until OPEC established its dominance with the nationalization of domestic oil industries in OPEC countries. That effect control by OPEC saw its initial success in the first oil price shock of 1973. Since then, OPEC’s power waxed and waned over time.’

‘We find that the natural logarithms of SP500 stock market index and the WTI crude oil price series exhibit non-stationary behavior. Moreover, these two series prove co-integrated, leading to our estimation of the MS-VEC model. We find that the high-volatility regime more frequently exists prior to the Great Depression and after the 1973 oil price shock caused by the OPECs. The low-volatility regime occurs more frequently during the period of time from the end of the Great Depression to the first OPEC oil price shock, where the oil markets fell largely under the control of the major international oil companies.’

Also, how’s this for a fun fact? The footnote on page 15 notes that ‘the first oil well drilled goes back to the middle of the 4th Century in China, using bamboo to drill and to form pipelines.’

The Effect of the U.S. Economy on Presidential Elections: 1828-2008

With a recently strong economy now in an increasingly fragile state, what are the implications for the presidential election in November? This paper analyzes almost 200 years of data to study the relationship between elections and the U.S. economy:

‘The influence of the economy on presidential elections has been well documented. However, citing the substantial growth of the federal government and the enactment of legislation such as the Employment Act of 1946, the majority of the literature focuses on the effect of the economy only on modern presidents. While some scholars study the influence of the economy on presidents starting in 1913 or even the late nineteenth century, few, if any, scholars study the effect of the economy on earlier presidents. This paper examines the extent to which the U.S. economy affected presidential election from the early 19th century to the present day. Arguing that the federal government’s role in the national economy changed dramatically during the middle of the twentieth century, we present evidence that price stability was positively associated with incumbent party electoral success from 1828 to 1948 and that income growth was directly related to incumbent party electoral success in the subsequent years. While the nature of the economic effects on presidential elections have varied over time, economic conditions have clearly played a role in national elections since the early years of the American republic.

Interestingly, the evolving role of the Federal Reserve suggests that there may have been a shift in exactly what evidence supported a ‘strong economy’, and how this helped/hurt the incumbent during elections:

Though the Federal Reserve System was established in 1913, it did not enjoy its current level of policymaking independence until the Accord with the Treasury Department in 1951 . Prior to the Accord, the Federal Reserve helped to keep interest rates low in order to support government bond prices as was desired by the Treasury Department. However, after the war, inflation began to increase and the Federal Reserve‘s purchase of Treasury issues to maintain government bond prices led to more inflation… In other words, the operation of the Federal Reserve was no longer fully tied with the goals of the Treasury. Thus, until 1952, the executive branch had significantly more control over monetary policy—and the value of the currency—than it did following the Accord.

Therefore, there seem to be two separate periods worth studying: Pre-1952 and Post-1952.

‘The concomitant transformation of the position of the federal government in the national economy and the increase in the independence of the Federal Reserve suggests the following hypotheses related to the role of economic circumstances in presidential elections:

    1. Prior to 1952, price stability was positively associated with the share of the vote received by the incumbent president (or his fellow partisan).
    2. From 1952 to the present, income growth was positively associated with the share of the vote received by the incumbent president (or his fellow partisan).’

The findings in this paper largely support these two hypotheses.

Patterns of Panic: Financial Crisis Language in Historical Newspapers

Messengers from brokerage houses crowd around a newspaper in New York City on October 24, 1929

Headlines during bear markets today have a tendency to give off ‘Armageddon’ vibes (think CNBC’s “Markets in Turmoil”). The newspapers are also a great source for understanding investor’s sentiment in a particular period. Performing text and sentiment analysis on over 35 MILLION (!) newspaper titles, this article compares the content of news articles with other major economic indicators and measures of financial instability.

‘This paper presents a new indicator on financial stress from 1889 to 2016 based on the reporting in five major US newspapers. This indicator provides detailed and high-frequency coverage of more than a century of financial history based on a previously untapped corpus of 35 million newspaper titles. I validate the indicator using 23,000 manually coded articles. The indicator displays plausible comovement with key economic variables and other measures of financial instability. Periods of negative financial sentiment predict recessions, rising unemployment, foreshadow lower stock market performance and rising corporate bond spreads.’

It is interesting to see the trends in certain keywords over time, particularly around notable events like market crashes and panics:

Also, similar to how we would say that a sign of the market ‘top’ is when bars start showing CNBC instead of sports games, it’s interesting to see the coverage of financial markets in national newspapers change over time in relation to market movements.

In the best chart of the whole article, the author also shares the long-term data for his ‘Financial Stress Indicator’, exhibiting both the exuberant periods where markets are overly calm, and the skyrocketing levels of ‘stress’ are markets are snapped back to reality:

Who Panics During Panics? 19th Century Evidence

Over the course of this market downturn, some commentators have pointed out that retail investors have actually been buying equities instead of selling, primarily through low-cost index funds. This goes against the narrative that the dumb retail investors always sell out at the bottom and buy at the top. This begs the question, what does the long-term evidence show?

‘Using records of the bank accounts of individual depositors, this paper provides a detailed micro-economic analysis of two nineteenth century banking panics. The panics of 1854 and 1857 were not characterized by an immediate mass panic of depositors and had important time dimensions. We examine depositor behavior using a hazard model. Contagion was the key factor in 1854 but it was not strong enough to create more than a local panic. In contrast, the panic of 1857 began with runs by businessmen and banking sophisticates followed by less informed depositors. Uninformed contagion may have been present, but the evidence suggests that this panic was driven by informational shocks in the face of asymmetric information about the true condition of bank portfolios.’

Using the accounts of customers at banks at the time, the paper specifically calls out what categories of people ‘panicked’ during the panics of 1854 and 1857:

The paper concludes that:

‘Banking panics were not characterized by an immediate mass panic of depositors, and account closings were a modest fraction of all accounts. Although depositor behavior clearly changed quite rapidly, there were time dimensions to the panics. Account closings rise quickly, with distinct jumps in the number per day, often apparently influenced by news. The heterogeneous behavior of depositors allows us to see that there were elements of contagion and responses to dramatic news events. However, while contagion seems to have been present, it does not appear to be strong enough to drive the panic onwards in 1854, the one panic most likely to have been driven by pure uninformed contagion. The panic of 1857 appears more likely to have been led by business leaders and banking sophisticates followed by less informed depositors. Uninformed contagion may be present, but the evidence suggests that the run on the banks was driven by informational shocks in the face of asymmetric information about the true condition of bank portfolios.’

Banking Crises Without Panics

‘We examine historical banking crises through the lens of bank equity declines, which cover a broad sample of episodes of banking distress both with and without banking panics. To do this, we construct a new dataset on bank equity returns and narrative information on banking panics for 46 countries over the period 1870-2016. We find that even in the absence of panics, large bank equity declines are associated with substantial credit contractions and output gaps. While panics can be an important amplification mechanism, our results indicate that panics are not necessary for banking crises to have severe economic consequences. Furthermore, panics tend to be preceded by large bank equity declines, suggesting that panics are the result, rather than the cause, of earlier bank losses. We also use bank equity returns to uncover a number of forgotten historical banking crises and to create a banking crisis chronology that distinguishes between bank equity losses and panics.’