Invisible Expectations

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June 2, 2024

by Stephen Stofka

This week’s letter continues a topic from last week, our expectations of inflation. The high inflation of the 1970s prompted a lot of debate on this topic, and I will try to cover a portion of those ideas. Hypotheses regarding the formation of expectations influence monetary policy and the manner in which the Fed raises interest rates. Different policy approaches reach across the country into the pocketbooks of many Americans. They can mean the loss of many jobs or few jobs, or the viability of buying a home.

The University of Michigan conducts a monthly survey of consumer sentiment in a rotating sample among 500 participants. Respondents are asked to estimate the rate of inflation for the next twelve months (see here, p. 5). Inflation is a rise in the average price of all goods but in casual conversation, we often use the term loosely to refer to a rise in prices of the goods and services that have the most impact on our lives. Each of our estimates are biased but an average of many estimates should approximate a comprehensive survey of the prices of many goods. This BBC five-minute video explains this phenomenon known as The Wisdom of the Crowd when many people try to estimate the number of jelly beans in a mason jar.

The blue line in the graph below is the headline CPI that tracks a basket of goods and excludes expenses like the employer portion of health care insurance. The Fed pays more attention to the PCEPI, the green line in the graph below. That methodology is based on actual expenditures in various sectors of the economy, including employer paid health insurance. Notice how closely the average estimates of inflation approximate this broad measure of price movement. In the April 2024 survey, expectations averaged 3.2%, a big decrease from over 5% in 2022 but a slight rise from 2.9% in March.

How do we form inflation expectations? There are two hypotheses, and they are distinguished by how errors occur in our expectations. Adaptive expectations was a predominant hypothesis until the 1970s. It holds that we revise our forecasts up when actual inflation is higher than we expected, and down when inflation data indicates that our forecast was too high (Blanchard, 2017). Imagine that we are offered a discount at the doctor’s office if we guess our weight within three pounds. We base our guess on a previous weight reading. If it is too low, we lose our discount so the next time we revise our guess higher. Under this hypothesis, our expectations are very much guided by past experience and our forecast errors are systemic. To tame high inflation, monetary policy must act like a shock that induces a recession and alters the expectations of investors and consumers.

In August 1979, during the Carter administration, Paul Volker assumed the position of Fed chair. In October, the Fed raised interest rates 1.5%, then lowered by a half-percent in November, then raised them again by a half-percent in December. In those three months, sales of new one-family homes (HSN1F) dropped 25%. A few months later, in the spring of 1980, came another interest rate shock of a 3.5% increase over two months and new one-family homes sank by 38%. They did not begin to recover until the spring of 1982. This cattle prod approach to taming expectations was influenced by the adaptive expectations hypothesis.

Statistical tests done in the early to mid-1970s showed that we paid much more attention to ongoing conditions than previously thought. This contradicted the notion that our expectations relied mostly on past experience. Two economists, Robert Lucas and Thomas Sargent presented a rational expectations hypothesis claiming that we form the best inflation forecast we can with the information available to us. Rational does not mean perfect. Errors in our forecasts are random and arise from unseen shocks (Humphrey, 1985). The critique against this hypothesis was that people were too naïve or uninformed to form rational expectations. Information frictions blurred the distinction between rational and non-rational (Angeletos et al, 2021).

 Over the past several decades, the rational expectations hypothesis has guided policymaking at the Fed. If the Fed presents a convincing policy commitment to steer inflation toward a particular target, investors will change their behavior in accordance with their belief in the Fed’s commitment. Economist Roger Farmer (2010) has called them self-fulfilling beliefs and devotes a section of his book to rational expectations. Under this regime, the Fed uses steady, incremental rate increases and consistent policy statements to “corral” expectations like a trained sheepdog persistently badgering a flock of sheep to guide them into a holding area. By guiding expectations, monetary policy can tame high inflation without necessarily producing a recession. This has been dubbed a soft landing.

In the spring of 2022, the Fed under Chairman Jerome Powell raised rates a half percent a month, a steady rate to let everyone know that the Fed was serious. From the spring of 2022, the number of new one-family homes did not fall. That was the rational expectations hypothesis at work. The Federal Reserve as sheepdog. As with any comparison, there are a number of other factors. My point here is that ideas about people’s motivations and behavior make a concrete difference in the lives of ordinary people.

We respond to high inflation with behavior that can exacerbate inflation. Next week I will look at several scenarios that illustrate why the Fed is concerned about managing consumer and investor expectations.

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Photo by Hassaan Here on Unsplash

Keywords: housing, interest rates, monetary policy, adaptive expectations, rational expectations, inflation

Angeletos, G.-M., Huo, Z., & Sastry, K. A. (2021). Imperfect macroeconomic expectations: Evidence and theory. NBER Macroeconomics Annual, 35, 1–86. https://doi.org/10.1086/712313

Blanchard, O. (2017). Macroeconomics (Seventh ed.). Boston, MA: Pearson Education. p. 337. This is an intermediate economics textbook.

Farmer, R. E. A. (2010). How the economy works: Confidence, crashes and self-fulfilling prophecies. Oxford University Press. This book contains succinct descriptions of various economic theories that have influenced policy and is aimed toward the general reader.

Humphrey, Thomas M., The Early History of the Phillips Curve (1985). Economic Review, vol. 71, no. 5, September/October 1985, pp. 17-24, Available at SSRN: https://ssrn.com/abstract=2118883

Cause and Effect

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May 26, 2024

by Stephen Stofka

This week’s letter is about the causes of inflation. Inflation can be easily described as a mismatch between supply and demand but that is a tautology that does not explain how the mismatch occurred. For hundreds of years, scholars and academics have identified various components of inflation’s causal web but identifying a primary cause has inspired enthusiastic debate. In the past century, economists have built sophisticated mathematical models which failed to predict a subsequent episode of inflation or predicted an inflation that did not occur. Economic models predicted that large government support during the financial crisis fifteen years ago would lead to higher inflation. It did not. Some economists were surprised at the extent and strength of the inflationary surge following the pandemic. In hindsight, turning off the world’s economic supply engine for even a short time was likely to have a strong effect on prices.

In The Power of Gold, Peter Bernstein (2000) recounts the causes that sixteenth century scholars gave for the persistent inflation in Europe during the 1500s. Those factors included “the decline of agriculture, ruinous taxation, depopulation, market manipulation, high labor costs, vagrancy, luxury and the machination of businessmen” (p. 191). Five hundred years later, most factors are relevant today in an altered form. With more sophisticated analytical tools, economists have developed a better understanding of these causal influences but that understanding has not led to better inflation forecasting. These factors can be grouped into those that affect supply or demand. Missing from that list was war, a common cause of inflation that distorts both supply and demand.

Prior to the severe cooling of the Little Ice Age in the 1600s, England and northwest Europe experienced a cooler climate that affected harvests. In an economy that relied mostly on agriculture, a poor harvest, or decline in agriculture was a supply constraint that pushed up prices. The demand / supply relationship is a fraction that helps explain a change in price. A lower supply, the denominator in that fraction, equals a higher price. Repeated waves of the plague and other general pandemics led to a depopulation that reduced the work force and pushed up the subsistence wages paid to workers. Employment in the U.K. has still not recovered from pre-pandemic levels, contributing to slightly higher inflation in the U.K. compared to the U.S.

High labor costs are the essence of a cost-push theory of inflation. When there is not enough supply of labor, workers are able to command higher wages. In many businesses, labor is an employer’s highest cost. Because employers markup all production costs, that markup increases the rise in prices. If employees get an extra $1 wage and the employer marks it up 50% to cover operating expenses, required taxes, fixed investment and profit, then the price will rise $1.50. The additional wage income will increase demand, resulting in a wage-price spiral that further exacerbates inflation. Any policy that reduces the supply of labor can be included in a cost-push theory of inflation.

Vagrancy, or homelessness, was a new phenomenon in the 16th century as Europe emerged from the feudal system in which workers were bound to the properties they cultivated. Policies that tolerated idleness of any sort reduced the work force and gave workers more bargaining power. Scholars of that century would be puzzled by modern day unemployment insurance which “rewards” workers for idleness. The mathematics of probability and risk that makes any insurance program feasible was barely in its infancy. By the late 17th century, Blaise Pascal and Pierre de Fermat had developed probability analysis, giving pools of underwriters gathered in coffee houses near London’s Royal Exchange the mathematical tools to sell insurance policies on many risky events (Bernstein, 1996, 63, 90).

Ruinous taxation consisted of import taxes and the debasement of hard metal currencies by the sovereign as a substitute for taxation. Import taxes on necessary commodities increased production costs, creating a cost-push effect. To repay debts incurred during war campaigns, rulers debased the currency by mixing base metals with gold or silver. In the 4th century B.C., Dionysius of Syracuse in Sicily had all the coins in his kingdom restamped to double their value so he could pay his debts (Bernstein, 2000, 48). Monetarists claim that an excess supply of money is the root cause of inflation. The economist Milton Friedman, never one to equivocate, stated flatly that inflation was “always and everywhere a monetary phenomenon.” In the Wealth of Nations, Smith (1776; 2009) noted that gold discoveries in the Americas had driven prices higher in England. A higher supply of money of any form will increase demand so this root cause is a subset of demand-pull theories of inflation.

Popular and scholarly opinion often points an accusing finger at the business class, whose conspiratorial machinations are thought to be responsible for rising prices. Historian Barbara Tuchman (1978, 163-165) described the power that merchants had acquired as the Third Estate under feudalism in 14th century France. Because many merchants were free citizens of a town and not subject to the rule of a noble, they enjoyed wealth and privileges like that of nobles, and at the expense of the workers who regarded them with scorn and envy. In Part 1, Chapter 10 of the Wealth of Nations, Smith wrote “People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the public, or in some contrivance to raise prices.” Responding to the global inflation following the Covid-19 pandemic, some op-ed writers and Twitter threads were convinced that collusion by business interests was the primary cause of the inflation.

The reasoning and analysis by thinkers of centuries past did not include the role of expectations in fostering and feeding inflation. Expectations are a key part of some prominent models because supply and demand operate on different time scales. The companies that make up the supply chain must anticipate the level of demand for a product or service before the demand manifests. Each year, the risk of being wrong increases in an economy marked by technological change and rapidly evolving tastes. Inflationary expectations needs a bit more space and will have to wait until next week. Have a good holiday weekend!

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Photo by Elias Kauerhof on Unsplash

Keywords: expectations, money, taxation, unemployment, supply, demand, cost-push, demand-pull

Bernstein, P. L. (1998). Against the Gods, the Remarkable Story of Risk. John Wiley & Sons.

Smith, A. (2009). Wealth of Nations. Classic House Books.

Tuchman, B. W. (1978). A Distant Mirror: The calamitous 14th Century. Alfred A. Knopf.

Price Waves

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May 19, 2024

by Stephen Stofka

This week’s letter is about our perception of inflation and the uncomfortable feelings we experience at higher-than-expected changes in prices. We notice price changes relative to the goods and services we experience and purchase in our daily lives. If the water is rising under our boat, we reason that the water is rising under all boats. We may have a good understanding of local conditions but a less accurate picture of underlying trends in a national economy. Economists understand the term on a macro level, when most people experience rising prices in the bundle of goods they buy. Inflation is a rise in the average of all prices for consumer purchases and often reflects price changes throughout the supply chain. To gather this information, the Bureau of Labor Statistics and the Census Bureau interview households and businesses from around the country each month. The monthly report on inflation may confirm our intuitive sense of changing prices or it may challenge our own appraisal. With all those resources and data, why do economists argue over the causes of inflation? In either case, we experience high inflation as a loss of purchasing power, and that sense of loss is magnified by the particular attention we pay to losses.

The Federal Reserve and most central banks around the world try to keep inflation at about 2% per year. That rate is thought to compensate for measurement error and a rise in the quality of goods. Our tendency to ignore small changes is evident in other areas of our lives. The 410-mile journey west on I-70 through Kansas is almost flat, yet in that span there is gain in elevation of 3258 feet (calculations in notes). Expectations play a key role in the decisions that people and companies make. Central bankers want small changes in the average price to play a negligible role in those decisions. Claude Shannon wrote that if what happens tomorrow is what happened today, then there is no new information. Our attention is piqued by news, or new information, so that we tend to pay attention to deviations from that average. The average becomes our environment. Statisticians recapture this human tendency when they standardize or normalize an average by setting it to 0, called a z-score.

We integrate quality improvements into our expectations so that gradual improvements are little noticed. In 35 years a 2% annual improvement in the quality of a product or service will result in a doubling of its quality. The reliability, safety, efficiency and performance of cars today are vastly superior to the cars in the 1970s. In 2020, the price of a new car was about 50% higher than in 1980, an annual price increase of less than 2%. I will leave the series identifier in the notes.

The quality of cars has increased far more than the increase in price. During that time, control of many systems within a car transitioned from mechanical control to precise electronic control, improving fuel efficiency. The quality of tires improved, reducing the number of flats that forces a driver to the side of the road. Air conditioners perform better and do not need to be recharged every few years because the seals leak. In 1980, the design of a car transferred too much of the impact of a crash to the driver. Today, a car is designed to absorb and distribute those physical forces. Seat belts protect the passengers from being thrown about during an accident, while front and side airbags cushion a violent change in direction. Quality has improved by at least twice the 50% increase in price.

During the high inflation of the 1970s, the real weekly earnings of wage and salary workers (LES1252881600) fell, as shown in the chart below. The term real means inflation-adjusted. In an age when families paid their monthly bills by check or money order, rapidly increasing costs sometimes meant that there was not enough money to pay all the bills. Although the recent surge in inflation has invited comparisons with the 1970s, workers’ earnings have outpaced inflation in this past decade and shown real gains.

If wage gains are rising faster than prices, why do consumer sentiment surveys not reflect this economic reality? Economist Paul Krugman had a short and helpful op-ed on the sentiment gap in recent surveys. Consumer purchasing power has increased since the pandemic, but consumer sentiment has declined by an amount comparable to the Great Recession in 2007-2009 when purchasing power decreased. He shows evidence from other surveys that one’s political party affiliation is strongly correlated with changes in consumer sentiment. People who usually vote Republican are optimistic about the economy when a Republican is President. Democrats express positive feelings when a Democrat is in the White House.

Political alliances are easily exploited via social media, whose use has skyrocketed since the Great Recession began at the end of 2007. Negative news and negative views proliferate on social media because we have a tendency to pay more attention to bad news. In the newspaper business, the rule was “If it bleeds, it leads.” Taking advantage of this human tendency, anonymous accounts on social media post total fabrications in order to get views. Higher views earn more revenue from ad placement, turning bad news into good news for the poster. News that gives the reader a sense of uplift or empowerment can be treated as “Pollyannish.” What other factors might account for the discrepancy between sentiment and reality? One aspect might be a rising standard of living.

Just as the quality of cars has increased, so has our standard of living in general. Families today are used to a higher standard with more conveniences than was typical fifty years ago. More conveniences equals more bills. These include monthly cell phone costs, TV and cable subscriptions, and higher electrical costs to run all the new appliances, computers and entertainment devices we have today. Some homeowners may experience fees for trash pickup or parking fees that were not typical in decades past.

Higher prices feel like a loss to us, and we pay attention to losses more than we do the wage gains. Economists Daniel Kahneman and Amos Tversky (1977) invented behavioral economics when they presented compelling evidence that our decisions are not always rational, that we weigh gains and losses on different scales. This challenged the conventional view that people’s choices were fundamentally rational, that bad decisions or poor choices were due to errors in judgment or a lack of information. Kahneman and Tversky asserted that irrational decisions were systematic rather than random error. Our tendency to measure gains and losses with different yardsticks can help explain why we become accustomed to improvements in our lives so that they escape our attention. Losses challenge our survival more than wins so we give losses our greater attention.

We survive by reacting promptly to threats. Children are taught to curb this natural impulse, to use their words, not their fists when responding to the behavior of other young children. We do not hit the butcher in the grocery store because the price of a steak has gone up 20%, but we might feel a bit of anger or resentment toward some nameless cause of the higher price. Even though inflation is part of our economic environment, it is not like the weather, we reason. Human decisions cause inflation so someone is responsible. However, the cause is more likely to be a composite of human behavior, of natural biases in how we process and react to information. That would make each episode of high inflation a unique blend of circumstance and policy decisions unlikely to be repeated in the future.

Economists, ever on a quest to find the Holy Grail, to understand the underlying process of high inflation, cannot admit the singularity of each episode. Next week, I will explore some of the factors that contribute to episodes of high inflation. Until then, watch Monty Python and the Holy Grail.

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Photo by Tadeu Jnr on Unsplash

Keywords: monetary policy, Prospect Theory, inflation

Bernstein, P. L. (1998). Against the Gods. John Wiley & Sons. In Chapter 16, Bernstein explores the ideas in Prospect Theory proposed by Kahneman and Tversky.

Kahneman, D., & Tversky, A. (1977). Prospect Theory. an Analysis of Decision Making under Risk. https://doi.org/10.21236/ada045771.

The index on new car prices is https://fred.stlouisfed.org/series/CUUR0000SETA01 The series identifier for the used car price index is CUSR0000SETA02.

Journey through Kansas: Kansas City on the eastern border is 909′ in elevation. Burlington, CO, at the western border of Kansas is 4167′, a rise of 3258′, or 0.617 miles. Dividing Hays, KS on the west side of Kansas is 2018′, a rise of 1000 feet. The state is 410 miles wide so the 1000′ gain in elevation is only .05% per mile. The 3000 gain in elevation is .15% per mile, a grade that feels flat to us.

Our Perception of Risk

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May 12, 2024

by Stephen Stofka

This week’s letter is about our perception of investment risk, and the subjective and objective aspects of risk evaluation. Our journey will take us several hundred years in the past and several decades into the future. The triennial survey of consumer finances indicated that less than half of people nearing retirement have $100,000 in liquid financial assets like savings accounts, stocks and bonds. Half of all working households have no savings, leaving them vulnerable to specific circumstances or a general economic shock. In our 20s, retirement looks remote with many years of work ahead of us. As we near retirement, we look in the other direction, to the past, and wish we had saved more. We confront the reality that we feel today’s needs more urgently than tomorrow’s possibilities. A $100 saving has a $100 impact on our current consumption but is only a faint light compared to the many thousands of dollars we will need in the future. We may not understand the underlying mechanism of saving.

We rely on what is visible to our senses to develop a flow of causality. We press on our car’s gas pedal and go faster, convinced that our action is adding more fuel to the engine. What the pedal controls is not fuel, but the air flow leading into the combustion chambers of the engine. The increased flow of fuel occurs in response to the change in air pressure. Prior to the 1980s cars used carburetors and mechanically employed this process called the Bernoulli principle, the idea that faster moving air induces a lower air pressure, a vacuum effect that sucks fuel toward the engine. Today’s fuel injection systems use air flow sensors that direct a computer to adjust the fuel flow. So, what does this have to do with risk?

Bernoulli’s principle is named after Daniel Bernoulli, the son of a noted Swiss mathematician and the nephew of Jacob Bernoulli, a 17th century mathematician who developed foundational concepts in probability like the Law of Large Numbers. Jacob maintained that people perceived risk in two ways. The first was an objective measure, an estimate of the probability of some event. The second was a subjective measure that depended on each person’s wealth, an inverse relationship. The first is visible, like the pressing of a gas pedal. The second is less visible, like the change in air pressure. Imagine that two people agree to flip a fair coin for a $100 bet. Person A has $1000 in her pocket; person B has $200. The loss or gain of $100 represents only 10% of A’s wealth, but 50% of B’s wealth. Even though the chance of winning or losing is the same for each person, they perceive the outcome differently. Peter Bernstein (1998) presents an engaging narrative of Jacob’s ideas in his book Against the Gods. His trilogy of books on the history of investing, risk and gold will inform and entertain interested lay readers.

Jacob may have identified one subjective element in each person’s evaluation of risk, but a person’s stock of wealth is not the only basis for a subjective estimate of risk. There are retired folks with accumulated savings of a million dollars who keep their money in savings accounts or CDs because they perceive the stock and bond markets as risky. A $10,000 loss in the stock market is only 1% of a million-dollar wealth yet some people perceive that loss in absolute dollars, magnifying the effect of a $10,000 loss. They regard the stock and bond markets as different versions of a casino. That same person might give $10,000 to a grandchild for college or to help buy a car, reasoning that there is an exchange of something that a person values for the $10,000. A person has no sense of receiving anything when their stock portfolio shows a $10,000 decrease. The stock market should have to pay an investor for using her investment, not the other way around. Such perceptions are confirmed during crises when the stock market loses 50% of its value.

Is an investment in the stock market like putting a quarter in a slot machine? Another perspective: an investor is like an investment company selling insurance to the stock market. A century of data shows that the probability of a loss in the stock market in any specific year is about 25%, according to an article in Forbes. In 70 years, the SP500 has doubled every seven years on average. An insurance company relies on Jacob Bernoulli’s Law of Large Numbers and diversification to manage risk. An investor, like any insurance company, will experience losses in some years. In last week’s letter (see note below) I wrote about surplus as a key dynamic factor in market transactions. In most years, an investor with a surplus of funds can “sell” those funds to the market and reap a gain.

Like risk, values in the stock market are based on both objective and subjective components. Sales, profits, dividends and efficiency help anchor a stock’s price movements as objective measures of value. Price responds to changes in these variables. Objective measures also include the variation in a company’s stock as a precise measure of uncertainty. There are various less precise but objective measures of economic and financial risk. Subjective measures include an investor’s need for liquidity, the ability to turn an investment into cash without impacting the price. An investor’s wealth can act as a cushion against fear of loss, a subjective measure discussed earlier.

Index funds have grown in popularity because they take advantage of Jacob Bernoulli’s Law of Large Numbers. By owning partial shares in many companies, an investor reduces the risk exposure to the variation in the fortunes of one company. The SEC might open an investigation into the ABC company, or the company loses an important overseas market, or the company reveals that the profit margins on some of its popular products are decreasing. To an index fund investor, a 10% decrease in that company’s stock price may be barely noticeable. The investor still has a risk of a change in general conditions, like a pandemic, but has dramatically reduced the risk of local conditions specific to one company.

Investors in Bitcoin do not act as an insurance fund for Bitcoin companies who mine Bitcoin. The miners have the surplus and are the sellers of Bitcoin. In the secondary market, the sellers of access to the digital currency market are the two dozen or so ETFs that allow investors to buy interest in a fund that owns bitcoin. Price movement is like a tailless kite flying in a breeze, responding mostly to price forecasts, a characteristic of some derivatives markets. The only objective measure of value and risk is the number of Bitcoin in circulation and the reward for mining new Bitcoin. Bitcoin’s price movement has a high volatility greater than 50% because there is little economic activity that anchors the variation in Bitcoin’s price. Despite the high volatility, an asset manager at an ETF fund makes the case for investing a few percent of a portfolio in a bitcoin ETF. As in our earlier example, the loss or gain depends on the current state of one’s savings.

Understanding the two aspects of risk perception, the objective and subjective, can help us manage our personal risk profile. Through research or the advice of a financial consultant we can understand the objective measures of portfolio risk but there are subjective elements unique to our personal history and disposition. The fear of having to be in a long-term care facility may influence our yearning for safety, regardless of our current health. A parent or relative may have had a similar experience and our primary concern is the protection of our portfolio value. We may feel fragile after the loss of our entire savings in a business venture. We can only become comfortable with our apprehensions by becoming familiar with them.

Next week I will look at our perceptions of other significant factors in our lives, particularly inflation.

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Photo by 𝓴𝓘𝓡𝓚 𝕝𝔸𝕀 on Unsplash

Keywords: stocks, bonds, risk, investment

Bernstein, P. L. (1998). Against the Gods: the Remarkable Story of Risk. John Wiley & Sons.

In last week’s letter I wrote about surplus as a key dynamic factor in market transactions. A seller of a good or service has a surplus which it values less than the buyer. However, the seller’s cost, including opportunity cost, is more than the cost to the buyer. These two ratios of benefit and cost find an equilibrium in the market that depends on the type of good or service and general conditions.

https://etfdb.com/themes/bitcoin-etfs/

https://www.vaneck.com/us/en/blogs/digital-assets/the-investment-case-for-bitcoin/

The Role of Surplus

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May 5, 2024

by Stephen Stofka

This week’s letter begins a series of subjects related to income and consumption. I will start with income, how we get the money to buy the goods and services we consume. A first-year course in microeconomics conveniently and simplistically divides the world into consumers and producers. In their textbook titled Microeconomics, Krugman and Wells (2018) explore the subject of labor as a factor of production in Chapter 19 at the end of the book. Since most of us work for forty to fifty years, the subject could be introduced to students in one of the early chapters. John Maynard Keynes, schooled in neoclassical analysis as a student of Alfred Marshall, criticized this framework because it ignored many of the flows in an economy. In a modern economy, we implement our choices with an exchange of money. Where did the money come from?

An entrepreneurial attitude to work is this: we either work for money or money works for us. If we work for money, money is our boss. If money works for us, we have a responsibility to direct it and manage it well. In that framework, money is a factor of production, the capital we use to realize goals for ourselves and our family. I was first introduced to this notion of money working for me when I was a child, and my folks opened up a savings account for me. I was amazed that my birthday money did chores just like a real person and got an allowance called interest. As the money got bigger, it worked harder and got a bigger allowance. What an amazing system!

Adam Smith, the first economist, analyzed the exchange of goods and money as a system. In the Wealth of Nations, Smith (1776; 2009) emphasized that the key to a developing economy was the subdivision of tasks to become more productive. Higher productivity created a surplus of a good or service so that the producer was willing to trade with someone else who wanted that good or service. In Chapters 2, 3, and 4 of Part 1 he repeats the point that this imbalance of supply and demand provides the energy to an economic system. In an often-cited example, Smith recounted the efficient production of a pin factory where each worker is assigned just one step in the production of a pin. An economy grows as the division of labor becomes more complex.

In Part 5 of the book, Smith predicted that the increasing division of labor would lead to greater prosperity but unevenly distributed. “For one very rich man there must be at least five hundred poor,” he wrote. Such inequality could lead to violent anarchy because the “avarice and ambitions in the rich” clashed with the “hatred of labour and the love of present ease and enjoyment” by the poor. A sovereign government had a responsibility to keep order and protect people from each other. Secondly, it should provide public works and institutions that distributed the benefits of a growing economy to more people. A road or port does not provide enough benefit to any one person or group to justify its expense, but such public projects raise the productivity and standard of living for many. Smith saw this improved public welfare and private security as key features that distinguished England from less-developed economies. To Smith, government was an intermediary between parties just as money was an intermediary of exchange.

A cost-benefit analysis of an exchange of surplus reveals some interesting ratios. A seller with a surplus of a good values the benefit from the good less than the buyer does. On the other hand, the cost to the seller includes the opportunity cost of not producing something which would earn a higher price from a buyer. The commitment of capital or time to producing a good or service requires a choice between alternative uses of that capital or time (see notes for measurement of opportunity costs). Presumably, the ratio of benefits equals the ratio of costs. If not, there is less motivation for exchange between seller and buyer. A less developed economy like Brazil generates less surplus so there is less inducement to make economic trades and money circulates at less than a third of the speed that it does in the U.S. (Notes).

The concept of surplus helps us distinguish different types of exchange. When two people trade services, they trade their labor, which has no surplus as such. To barter their labor, buyer and seller must match the type of good or service to be exchanged. To each party, the benefit must equal the cost, a hindrance to exchange. In an economy promoting the production of surplus, the benefit and cost are unequal to each party, but the ratios of benefits and costs are equal. Matching is easier and there are more trades.

Can we apply this analysis to the exchange of securities? The seller of a security like Apple’s stock does not have a surplus because she produces Apple stock for sale. She is motivated to sell because she thinks it might go down in price, and the benefit she receives from the sale is greater than the cost if she held onto the stock. The buyer thinks the security might go up in price, so his benefit is also greater than the cost. The key to this transaction is the broker who produces trades for sale, the matching of security transactions. The benefits to the buyer and seller of the stock are greater than the benefit to the broker. The broker’s cost, including the opportunity cost, is greater than either the buyer or seller of the security because the broker could always make more in commission by facilitating a different type of trade.

A year ago, I spent a few months studying the dynamics of a developing country in Africa. Because there was a lack of surplus in some parts of the economy, I came to appreciate the key role that surplus plays in our lives. In the coming weeks, I will try to understand various aspects of our working lives through these ratios of seller and buyer costs and benefits and how those ratios are influenced by surplus.

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Photo by Adam Jang on Unsplash

Keywords: securities, stock, cost, benefit

Krugman, P. R., & Wells, R. (2018). Microeconomics (Fifth). Macmillan education.

Smith, A. (2009). Wealth of Nations. Classic House Books.

Brazil Money Velocity: In the third quarter of 2023, M1 velocity for Brazil was .35, meaning that money circulates a rate that is a third of GDP output. The same velocity in the U.S. was 1.5, more than four times the rate. Brazil M1 measure is MANMM101BRM189S. Final demand, a measure similar to GDP, is  BRAPFCEQDSMEI. There was not a current measure of M2, a broader measure of money often used in the U.S. The series for M1 velocity is M1V.

Physics Imbalance: Coincidentally, an imbalance in electron fields causes atoms to bind together in an exchange of electrical charge. Khan Academy has a short explanation with graphics.

Opportunity cost: this is a fundamental concept in economics, yet economists disagree on how it should be measured. In 2012, Potter & Sanders justified four different answers economics graduate students gave to the calculation of opportunity cost found in an introductory economics textbook.

Potter, J., & Sanders, S. (2012). Do economists recognize an opportunity cost when they see one? A dismal performance or an arbitrary concept? Southern Economic Journal, 79(2), 248–256. https://doi.org/10.4284/0038-4038-2011.218

Targets of Taxation

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April 28, 2024

by Stephen Stofka

The subjects of this week’s letter are home prices, household income and property taxes. The policy of using property tax revenue to fund public education has provoked controversy since the 19th century. Like other social species we are watchful of threats like freeloading to our group’s cohesion, however we determine “our” group. Newcomers to an area are often regarded with suspicion as being freeloaders who get from the group before they have contributed to the common welfare. This suspicion often underlies the heated debates that erupt at local council meetings. I will begin with property valuations, the basis of property taxation.

As a young man I was taught not to buy a home that was priced more than four times my income. In 2022, families paid more than six times the median household income, as shown in the chart below. Despite the high prices, mortgage debt service is a tame 10% of the household disposable personal income. Almost 40% of homeowners have a fully paid mortgage, according to Axios. Many homeowners hold mortgages at the historically low rates of the last decade. If higher mortgage rates persist for several years, we may see greater delinquency rates as recent buyers cope with payments that stretch their budget.

Graph shows an increasing ratio of home prices to median household income since 2000.

The Center for Microeconomic Data at the NY Federal Reserve has tracked household finances for more than twenty years. The highest percent of total household debt continues to be mortgage debt at 68% to 70%. Mortgage debt has grown at an annual rate of 3.9%, slightly more than the 3.7% annual increase in owner equivalent rent that I discussed last week. A low 3% of mortgages are more than 30 days delinquent, down from 11% to 12% during the 2008-2009 financial crisis. Only 40,000 people are in foreclosure, less than half the number in 2019. The numbers today are the lowest on record except for the pandemic years of 2020 and 2021 when many foreclosures were halted.

As I discussed last week, property prices reflect the anticipated cash flows from the house during a 30-year mortgage, a process called capitalization. The home buyer replaces the seller in the stream of cash flows from the house. Because property taxes are based on the appraisal values, the taxing authority implicitly bases property taxes on cash flows that a homeowner has not received yet. Each state sets an assessment rate that is a percent of the appraised value of the home. Each taxing authority within the state then charges a dollar amount – the mill value – per thousand of that assessed value. A home with an appraised value of $500,000 and an assessment rate of 8% would have an assessed valuation of $40,000. If the mill levy were $100 per $1000 of assessed value, then the homeowner’s property tax bill would be $4000. The effective property tax rate would be $4000 divided by $500,000, or 0.8%. Investopedia has a longer explanation for interested readers.

Each state taxes property at different rates. Colorado charges ½% of the appraised property value, one of the lowest in the nation. California averages ¾%. Texas averages a whopping 1.74% of home property values but has no income tax. Families earning the median household income and owning a house valued at the median house price in Texas and Colorado pay the same combined property and income tax of $5883 and $5669, respectively. Colorado has a cheaper tax burden despite having an income tax and far higher median house values. The same family living in California would pay $8256, largely because their property tax bill would be about the same as in Texas because the home values are more than double those in Texas. I will leave data sources in the notes.

Many districts give seniors a discount on their property taxes, effectively throwing a higher burden on working homeowners. Some argue that these exemptions should be means tested, effectively lessening or eliminating the discount for seniors with higher incomes. A wave of seniors may move to an inter-urban area that features lower home prices yet is within an hour of vital medical services like a hospital. The higher demand drives up home prices for others who have lived in the area for decades. Secondly, seniors consume more medical services and public accommodations. That requires more public spending, which is shared by the entire community and leads to resentments and contentious public meetings at the local town hall.

The majority of property taxes are used to fund public schools, and it is the largest line item on an individual homeowner’s property tax statement. This system of funding raises principled objections from childless couples and those who privately school their children, but are expected to share the burden of funding public schools. Homeowners have often resented having to fund the schooling of recently arrived immigrants. In the 19th century a wave of immigrants from Catholic Ireland, then Catholic Italy prompted many states with Protestant majorities to pass laws that excluded public funding for schools run by Catholics. Since the 16th century, the two main branches of Christianity had fought bloody civil wars in Europe and Britain. Those who colonized America brought those antagonisms with them.

During the 1970s, the number of encounters at the southern border increased almost ten times, according to the CBP. High inflation and migration of Amerians to western states caused a surge in property valuations and higher property taxes. In 1978, a taxpayer revolt in California led to the passage of Proposition 13 limiting property tax increases. In some school districts, undocumented parents had to pay a fee to enroll their children in public school.

In a 1982 case Plyler v. Doe, a slim 5-4 majority on the Supreme Court ruled that undocumented immigrant children did not have to pay a fee to go to school. The court reasoned that the equal protection clause of the 14th Amendment extended protection to “persons,” not “citizens.” Therefore, a state could not provide public benefits to one child in a school district and not another child because their parents were undocumented. The court interpreted “protection” to include public benefits, a construction that the Connecticut Constitution made explicit in 1818 with the phrase “exclusive public emoluments or privileges from the community.” The conservative majority on the Supreme Court overruled an interpretation of the due process clause in the 14th Amendment that justified the 1972 Roe v. Wade decision. This court might revisit this interpretation of the equal protection clause of the 14th Amendment as well.

Districts with lower property valuations struggle to raise adequate taxes to meet minimum educational standards. They may have to tax homeowners at a higher rate than a neighboring district, raising legal questions about uniformity and proportionality. The disparity in valuation was the subject of the 1997 Claremont decision by the New Hampshire Supreme Court. At the time, local districts provided 75% to 89% of funding for elementary and secondary education. The state’s general fund provided only 8% of school needs. The decision forced the state to distribute tax revenues among districts to meet adequate education standards for all children in the state. A 2017 analysis found that states now provide almost half of public education funding, relying on income tax revenue to smooth disparities in income among districts within each state.

People do not like paying taxes but grudgingly accept them. People elect local officials to decide on spending priorities yet some homeowners object to the way their taxes are spent. On my property tax bill are eleven items which include funding for schools, the city’s bonds, police, fire, libraries and flood control. Homeowners might prefer a questionnaire of thirty categories of spending which allowed them to allocate their tax dollars by percentage when they paid their property tax each year. In my district, a half-percent goes to affordable housing, three percent to social services. Some might prefer 5% or more. A homeowner paying online could elect to answer the questionnaire online. Would homeowners respond? Next week I will begin an exploration of various aspects of consumption, the chief component of our economy.

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Photo by Museums Victoria on Unsplash

Keywords: housing, home prices, mortgage, property tax

Property taxes by zip code and state can be found at Smart Asset
Median home prices by state are at Bank Rate
Median Sales Price of Homes Sold in the U.S. is FRED Series MSPUS at https://fred.stlouisfed.org/ Median Household Income in the U.S. is series MEHOINUSA646N. The ratio of mortgage payments to disposable personal income can be found here. The home price to property tax ratio can be found here

Home Sweet Housing Service Flow

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April 21, 2024

by Stephen Stofka

This week’s letter is about the cash flows we receive from a house and whether we can use those cash flows to help us determine an appropriate price range for a house. While we might not think of a house as a business, the owner is a landlord. Like any business, a house has similar metrics: an initial investment, loans, cash flows, continuing expenses and investment, “sweat equity,” capitalization and profits.

A house offers similar features to a coupon bond with one important difference – the mortgage. When we buy a coupon bond, we pay for the bond outright. The bond pays a series of payments called coupons over the life of the bond, then pays back the principal amount at the end of the bond’s term. What is the coupon we receive from a house? The housing service which is valued at what we could expect to rent the house for. Each year we discount that coupon by the opportunity cost of what that money could earn. As a benchmark rate, I will use the 40-year average rate of 5.5% that a 30-year Treasury bond (FRED Series DGS30) has paid.

As I noted last week, average owner equivalent rent has grown 3.7% each year for the past thirty years. Urban areas drive the growth of housing rents, and the highest growth occurs in the most competitive cities that offer employment and urban amenities. For several decades the city average of owner equivalent rents has been 8 – 15% higher than the median household income in the country as a whole (FRED graph). Incomes are much lower in rural areas and so are the rents and the taxes. Some rural areas offer a picturesque natural setting and recreational opportunities, but the lackluster job market does not attract young families.

Consider a house that might rent for $2000 a month, or $24000 a year. In thirty years, that annual rent will be $68,833, the result of a 3.7% increase in housing rents each year. Using the 30-year Treasury yield of 5.5%, today’s net present value of those rising cash flows from the house is $537,673. I will leave the calculation in the notes along with the address of an online calculator so you can do this yourself. These are long-term averages that can vary by decade. In 2014 the fair market rent for a 2-BR apartment in the Denver metro area rose 20%, according to HUD. Rental prices can respond quickly and dramatically to population migration and underinvestment in multi-family housing.

An investment in a house is partially funded with a mortgage whose principal and interest payments remain stable for the term of the mortgage. Although interest rates are above recent averages, they are about half of what a borrower might pay on a car loan or a margin loan from a broker. Interest on car loans can vary from 6% to 25%, according to Bankrate.com. Vanguard would charge 11% to 14% on a margin loan to buy stock. These are shorter term loans yet charge higher interest rates. Implicit guarantees of mortgages by the federal government give a homeowner the same interest rate on long-term debt as Apple, the second most valuable company in the world. In 2014, Apple paid a rate of 4.45% on its 30-year bonds. The average 30-year mortgage rate (MORTGAGE30US) at that time was 4.36%.

While government support introduces distortions to the housing market, residential investment and strong population growth do not fit a free-market model because land in a dense urban area is not a commodity like farm or ranch lands. Before the Federal Housing Administration was created in 1934, creditors often required a down payment of up to 40% even from those with good income and credit, according to a history published by the Richmond Fed. In the late 19th century, twelve percent of mortgages were underwritten by building and loan associations of the mortgage holders themselves. During stressful economic times, these associations would go bankrupt, leaving homeowners with deficient claims to their property. In all developed countries today, national government policies support home ownership.

Let us say a homeowner buys a home for almost $600,000 as in the example above. After thirty years, the owner will have received the net present value of the purchase price and will have a home that will be worth $2 million (calculation in the notes). However, this does not represent a windfall for the owner. A replacement home will also contain its cash flows for the past thirty years so that similar homes in that area will sell at a similar price. What the owner discovers is that their home’s value is priced like a share in a community resource. They can capture the capital gain in their home while they are alive by buying a home in a different community with a lower-priced resource pool, a strategy often employed by retired folks.

So, future cash flows are capitalized into the price of a house. The homeowner’s profit comes from any spread between the growth in house prices and the growth in market rentals over three decades of ownership. For some people, the true profit is the piece of mind that comes from ownership in a house that is mortgage free. Economic factors and changing tastes can slow the growth of home prices in an area. Crime may have increased; the quality of schools may have declined. Homeowners in these areas can feel trapped because they can not leverage the smaller equity in their home to buy a home in a more expensive area.

While the principal and interest on a mortgage remain stable during the term of the mortgage, taxes, repairs and insurance do not. Next week I will look at property taxes, the annual dues we pay to the county where our property is located.

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Photo by Kara Eads on Unsplash

This online calculator allows you to specify the number of cash flows but you need to input each cash flow.

Excel requires less work so you can calculate 30 years of cash flows based on a 3.7% increase in housing rents and an opportunity cost of 5.5% each year. Microsoft has an example of using NPV. In case you do not use Excel often for this kind of work, here are some instructions. In an empty spreadsheet:
In cell A1 enter 1.037. That is the annual growth of housing rents at 3.7%.
In cell B1, enter .055, the interest rate you could earn investing the purchase price of the house in a Treasury bond.
In cell A2, enter 24000, an estimate of the current rental value of the home.
In cell A3, enter the formula “=A2*A$1” without the quotes.
With the caret, grab the right lower corner of cell A3 and drag it down to include cell A31. This will copy the formula to the cells A4:A31.
In cell C1, enter “=NPV(B1, A2:A31)” without the quotes. That is the Net present value.
You can change the starting annual rent in cell A2, vary the discount rate in cell B1, or the growth of housing costs in cell A1. You can select and copy cells A1:C31, then go to cell E31 and paste in the cells. Now you have a side-by-side comparison.

Calculation of future home price: The Case-Shiller national home price index (CSUSHPINSA) has risen an average of 4.25% for the past 35 years.

Landlord and Tenant

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April 14, 2024

by Stephen Stofka

This week I will continue my look at housing, focusing on the dual role of homeowners. There are several advantages to owning a home, one of which is a type of self-imposed rent control. Our mortgage payments are fixed for the term of the mortgage, so we do not have to worry about a 10% rent increase from our landlord. We are the landlord, and we are our favorite tenant. While the mortgage payments remain stable, the maintenance costs for the home do not. The house may need a new furnace, hot water heater, updated plumbing or a new sewer line, major expenses that remind us that we are the owners of an investment property.

In this dual role, a  homeowner takes money out of her right tenant’s pocket each month and puts it in her left landlord’s pocket. As landlord, a homeowner does not report that income nor does she report the mortgage payments and expenses necessary to maintain the property. The Census Bureau estimates that homeowners with a mortgage spend $1900 a month. Those without a mortgage spend about $600.

The federal government calls the difference between this implied income and expenses a net imputed rental income and estimated (pdf link) that the tax exclusion saved homeowners $135 billion in 2023 (p. 22).

What is the average yearly tax saving for a homeowner? The Census Bureau estimated that there are 143 million households with an owner-occupancy rate of almost 65%. That results in 93 million owner-occupied homes, making the tax exclusion worth almost $1500 yearly to a homeowner that is not available to a renter. The tax exclusion is worth much more than average to those with higher incomes and more expensive homes.

When we sell the home, we hope to realize a capital gain from the home in addition to the cash flows we received while we were living in the home. After Congress changed the law in 1997, most homeowners do not have to pay tax on the capital gains from their home, an exclusion estimated at $45 billion in 2023. Real estate property is treated differently than other assets under the tax code, an implicit recognition that property ownership has a value to the community where the property is situated. A house attached to the land by a foundation is immoveable and taxed differently than a moveable asset like a car. In fact, a mobile home is taxed similarly to cars while the land the mobile home sits on is taxed like real estate (Investopedia bulletin).

Some assets provide a series of cash flows while we own them; some do not. In the case of a house, an owner’s implied cash flows start as soon as we take possession of the house. The house provides us with a housing service while we live in it. In the Consumer Price Index (CPI) published each month, the Bureau of Labor Statistics (BLS)  includes a calculation of what it calls owner equivalent rent, OER. This is an estimate of what a homeowner would rent out their home to a stranger. The estimate is based on rental prices for similar units in the area, but the calculation uses survey data that is slightly out of date. Some analysts do not think this implied income should be 25% of the CPI calculation, and the Eurozone countries do not include it in their CPI estimates. Below is a chart comparing the EU method, what is called the Harmonized CPI (FRED Series HICP), and the headline CPI (CPIAUCSL) produced by the BLS each month.

Notice the divergence between the two series starting in 2014. During the financial crisis, homebuilders started  the fewest number of multi-family units per capita in modern history. This laid the foundation for the next crisis, and the pandemic sparked a remote work trend that disrupted the customary supply and demand for housing. In the chart below I have charted the number of multifamily units per capita and highlighted the fallout from the S&L Crisis and the financial crisis.

We can see that the rent of a primary residence and the estimate of OER track each other pretty closely. In the following graph I compare the survey of actual rents to the OER estimate and index it to the beginning of 2014 to illustrate the trends more closely. In 2014, rents (redline) began to grow faster than OER, indicating the pricing power migrating to landlords several years after the financial crisis. In the decade that followed, housing costs grew 50%, an annual growth rate of 4%, higher than the 75-year average of 3.6% or the 30-year average of 3.7% (see notes). Most of the above average growth has been in the three-year recovery from the pandemic.

The cost of housing rises faster than the overall price level and faster than incomes. Homeownership limits the actual impact of rising housing costs on an owner’s budget. A homeowner plays the dual role of landlord and tenant and receives favorable tax treatment of imputed income and capital gains. Given these long-term averages, can a buyer calculate the price they would be willing to pay for a home from its future cash flows? I will look at that next week.

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Photo by krakenimages on Unsplash

Hui Shan (2011) has written a brief history of the tax treatment of housing capital gains and measured the effect of the 1997 tax law on home sales in the Boston area.

Owner’s Equivalent Rent of primary residence in U.S. City Average is FRED Series CUSR0000SEHC01. Rent of primary residence in U.S. City Average is CUUR0000SEHA.

Annual growth rates: Average annual growth rates are calculated over a rolling 10-year period.

A Home Is a Magic Wallet

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April 7, 2024

by Stephen Stofka

In this week’s letter I will explore the various roles that housing plays in our lives. Last week I showed the divergence of household formation and housing supply during the financial crisis. Home builders responded to the downturn in household formation by building fewer homes. Because the recovery after the crisis was slow, the demand for housing did not pick up until 2014. It is then that a mismatch between housing demand and supply started to appear in the national and some local home price indices. This week I will examine the demographics of homebuyers and sellers in recent history and the secret life of every homeowner as a landlord. A home is a magic wallet where money flows come and go.

Data from the National Association of Realtors (NAR) indicates that the median age of home sellers has increased from 46 to 60 since 2009. I will leave NAR data sources in the notes. In the four decades between 1981 and 2019, the median age of home buyers rose by twenty years, from 36 in 1981 to 55 in 2019. The median age of first-time buyers, however, increased by only four years, from 29 to 33. In 1981, the difference in age and accumulated wealth between first-time buyers and all buyers was only seven years. Now that difference has grown to 22 years. First-timers typically buy a home that is 80% of the median selling price of all homes.

In the past four decades, there has been a divergence in wealth between older and younger households. The real wealth of younger households has declined by a third since 1983 while households headed by someone over 65 have enjoyed a near doubling of their real wealth in thirty years. Accompanying that imbalance in growth has been a shift in capital devoted to housing.

The Federal Reserve regularly updates their estimates of the changes in household net wealth. The link is an interactive tool that allows a user to modify the time period of the data portal. The chart below shows the most recent decade of changes in wealth. The lighter green bars are the changes in real estate wealth for households and non-profits and show the large gains in real estate valuations during the pandemic. The blue bars represent equity valuations and demonstrate the volatility of the stock market in response to any crisis, large or small.

The Fed’s data includes various types of debt as a percent of GDP. Twenty years ago, household mortgages were 11-12% of GDP. Today they are 19% of GDP, a huge shift in financial commitment to our homes and neighborhoods. A city average of owner equivalent rent (FRED Series CUSR0000SEHC) averaged an annual gain of 2% during Obama’s eight- year term, 2.8% during Trump’s term, and 6% during the first three years of Biden’s term. Biden has little influence on trends in housing costs, but the art of politics is to use correlation as a weapon against your opponent. People feel the change in trajectory as a burden on their households.

The Bureau of Labor Statistics calculates owner equivalent rent by treating a homeowner as both a landlord and renter. Property taxes, mortgage payments, interest, maintenance and improvements to a home are treated as investments just as though the owner were a landlord. The BLS uses housing surveys to determine the change in rental amounts for different types of units. A sample of homeowners are asked how much they would rent out their home but this guess is used only to establish a proportion of income dedicated to rent, not the actual changes in the rental amounts for that area, as the BLS explains in this FAQ sheet.

Let us suppose that a homeowner has a home that is fully paid for. If the house might rent for $2000 a month and monthly expenses are $500 a month, that would represent $1500 per month in implied net operating income for that homeowner, an annual return of $18,000. A cap rate is the amount of net operating income divided by the property’s net asset value. If similar homes are selling for $450,000 in that area, the homeowner is making 4% on their house’s asset value, slightly less than a 10-year Treasury bond (FRED Series DGS10, for example).

Long-term assets compete with each other for yield, relative to their risk. A property is a riskier investment than a Treasury bond, so investors expect to earn a higher yield from a property. Before the pandemic, 10-year bonds were yielding between 2-3%. Landlords could charge lower rents and still earn more than Treasury bonds. As yields rose for Treasury bonds, property investors must charge higher rents to earn a yield appropriate to the risk or sell the property and invest the money elsewhere.

When we own an asset that provides an income, it is as though the asset owes us. When a home declines in value, we feel a sense of loss. When the housing market turned down in 2007-2008, homeowners expected to get a similar price as the house their neighbor sold in 2006. They used that sale price to determine what their house owed them. In order to get the listing, a real estate agent would agree to list the home for that higher amount, but the property would get few offers. After a period of time, the seller would cancel the listing and wait for the “market to turn around.”

Earlier I noted the dramatic rise in mortgage debt as a percent of GDP. At one-fifth of the economy, that debt represents capital that is not being put to its most efficient use because most homeowners do not regularly evaluate the yield on their homes as professional investors. A higher percent of capital devoted to housing will help sustain higher housing costs and pressure household budgets. I worry that an inefficient use of capital will contribute to a pattern of lower economic growth in the future, stifling income growth. The combination of these two pressures will make it difficult for younger households to thrive. The generational gap will widen, adding more social and political discord to our national conversation.

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Photo by Towfiqu barbhuiya on Unsplash

Keywords: mortgage, housing, owner equivalent rent

Notes on median age of sellers: 2009 data is from the NAR and cited in a WSJ article (paywall). Current data is from the NAR FAQs sheet. Jessica Lautz, an economist with NAR, reported the four-decade trend in home buyers. Median home prices of first-time buyers is from a 2017 analysis by the NAR. The comparison of older and younger households comes from a 2016 NAR analysis.

Notes on Federal Reserve data:  The change in mortgage debt as a percent of GDP is in the zip file component z1-nonfin-debt.xls, in the column marked “Noncorporate Mortgages; Percent of GDP.”

A Home Is More Than a Home

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March 31, 2024

by Stephen Stofka

This week’s letter is about housing, the single largest investment many people make. The deed to a home conveys a certain type of ownership of physical property, but the price reflects a share of the surrounding community, its economy, infrastructure, educational and cultural institutions. We purchase a chunk of a neighborhood when we buy a home.

These are network effects that influence demand for housing in an area. They are improvements paid for by tax dollars or business investment that are capitalized into the price of a home. Take two identical homes, put them in different neighborhoods and they will sell for different amounts. When elements of this network change, it affects the price of a home. Examples of negative changes include the closing of businesses or an industry, a decline in the quality of schools, the presence of graffiti or increased truck traffic. Positive changes might include improved parks and green zones, better schools and alternative transportation like bike lanes and convenient public transportation.

Zoning is a critical tool of a city’s strategic vision. Zoning controls the population density of an area, the available parking and the disturbance from commercial activities. Many cities have some kind of long-term plan for that vision. Los Angeles calls it a General Plan. In Denver it is called Blueprint Denver (pdf). Homes built in the post-war period in the middle of the twentieth century were often smaller. They feature a variety of building styles whose distinctive character and lower prices invite gentrification. As properties are improved, their higher appraisal values bring in more property tax revenue from that city district and the process of building an improved neighborhood network begins.

A representative for that district can argue for more spending on public amenities to enhance the neighborhood. This further lifts property values and increases tax revenues. Developers get parcels rezoned so that they can convert a single-family property into a two-family unit. This may involve “scraping” the old structure down to its foundation, then expanding the footprint of the structure to accommodate two families. As this gentrification continues, there is increased demand for rezoning an area to allow the building of accessory dwelling units, or ADUs, on a property with a single-family home. Here is a brief account of a rezoning effort in Denver in 2022.

In the past decade, the 20-city Case-Shiller Home Price Index (FRED Series SPCS20RSA) has almost doubled. The New York Fed has assembled a map with video showing the annual change in the index for the past twenty years. Readers can click on their county and see the most recent annual price change. Millennials in their late twenties and thirties feel as though some cruel prankster has removed the chair just as they started to sit down. Analysts attribute the meteoric rise in prices to lack of housing built during and after the financial crisis fifteen years ago.

Each generation faces a set of crises that stifle their ambitions. In the 1970s, just as the first Boomers were entering their late twenties, mass migration from the eastern U.S. to the western states and high inflation doubled home prices in some areas within just a few years. The decade is a comparison tool as in “How bad is it? Well, it’s not as bad as the ’70s.” The 1980s began with high interest rates, the worst recession since the Great Depression and high unemployment. Boomers had to buy houses with mortgage rates over 10%. Following that recovery was another housing scandal and the savings and loan crisis that restricted any home price growth. A homeowner who bought a home in 1980 might have seen no price appreciation by 1990. Gen-Xers who bought a home during the 2000s had a similar experience, leaving some families underwater or with little equity for a decade. Equity growth from homeownership helps support new business start-ups.

Despite the insufficient supply of affordable housing, there are more homes than households. In the graph below are the number of homes (orange line) and households (blue line) as a percent of the population. The difference is only a few percent and contains some estimate error, but represents many more homes than the number of households.

Graph showing homes and households as a percent of the population.

Household formation, the blue line in the graph above, is a key feature of the housing market. In 1960, 3.4 people lived in each household, according to the Census Bureau (see notes). By 1990, that number had steadily declined to 2.6 persons and is slightly under that today. The supply of homes naturally takes longer to adjust to changes in household formation. That mismatch in demand and supply is reflected in home prices.

During the financial crisis household formation declined as unemployment rose. Home prices fell in response to that change in demand for housing and a come down from the “sugar high” of easy credit and sloppy underwriting. The percent change in the Home Price Index, the red line in the graph below, fell below zero, indicating a decline in home prices, an event many homeowners had never experienced. The fall in home values crippled the finances of local governments who depended on a steady growth in the property taxes based on rising home values.

Graph containing two lines: 1) the percent difference between homes and households as a percent of the population, 2) the home price index. There is a large gap where the two series diverge during the financial crisis.

The thirty-year average of  the annual growth in home prices (FRED Series USSTHPI) is 4.5% and includes all refinancing. We can see in the chart above that the growth in home prices (red line) is near that long-term mark. However, rising wages and low unemployment have encouraged more household formation, the rising blue line in the first chart. Those trends could continue to keep the growth in home prices above their long-term average. Millennials with mortgages at 6-7% are anxiously waiting for lower interest rates, a chance to refinance their mortgages and reduce their monthly payments. Strong economic growth and rising incomes will continue to put upward pressure on consumer prices, slowing any decisions by the Fed to lower interest rates. These trends are self-reinforcing so that they take a decade or more to correct naturally. Too often, the correction comes via a shock of some sort that affects asset prices and incomes. Millennials have endured 9-11, the financial crisis and the pandemic. “Go ahead, slap me one more time,” this generation can say with some sarcasm. The challenge for those in each generation is to try harder and endure.

Next week I will look at the cash flows that a property owner receives from their home investment.

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Photo by Scott Webb on Unsplash

Keyword: interest rates, mortgages, mortgage rates, housing, households

Notes on series used in the graphs. The total housing inventory is FRED Series ETOTALUSQ176N divided by Total Population Series POPTHM. Total Households is TTLHHM156N divided by the same population series. These are survey estimates so some of the difference between the two series can be attributed to a normally distributed error. The all-transactions Home Price Index is FRED Series USSTHPI. The FRED website is at https://fred.stlouisfed.org/