We all hear about cycles all the time, the real estate cycle, the business cycle, and the housing cycle. There always seems to be someone with a cycle for just about anything with a chart. Long cycles, short cycles, and in some cases imaginary cycles. What exactly is a cycle? A cycle is a pattern in data that occurred or reoccurred over time. We can only see patterns after they have happened. What causes these patterns in real estate? It really depends what we are looking for.
If we look back at the Herengracht Index, we will begin to see "patterns". The closer we look at the chart, the more we will see cyclical patterns. Approximately every four to eight years location values go up and down. Is this a cycle? Not exactly, what we are most likely witnessing is the balancing between supply and demand. Not just in real estate, but in terms of the regional economy. As we will see, it is all about balance.
A region is generally considered a metropolitan statistical area, with our major city at or near the center. The economies can be very different for each region within a country, and is driven by the demand for the regions products and services along with its ability to supply a workforce. Regions are distinguished from a country in that trade, exports, and immigration are largely unregulated - only a country can impose tariffs or protectionist measures. Citizens and companies can easily trade and move between regions. Money and profits can also move easily.
In order to understand how regions behave, researchers had broken them down to three categories, output, labor, and real estate. Output represents the export of local goods and services - shipping product out or receiving fees for services outside our region. Local consumption of goods is recycling the revenue. Funds coming from outside our region are required for economic growth. Labor is our work force. Real estate is the rental rate and supply of housing. The inter-relation of the three variables explains the value of real estate within a specific region.
Outputs, again, are local goods and services that are exported out of the region. As demand abroad for those exports grow, more jobs will be created. The region will grow. Growth from increased exports is known as demand induced growth. With demand-induced growth, incomes, and real estate rents will rise. The amount of change in each of these factors is affected by the restrictions on growth. Restrictions may be local property laws or anti-growth sentiment. Other restrictions may be geological such as a coastlines or mountain ranges.
In regions with unrestricted growth, the increases in incomes and rents will be small. However, there will be a rapid expansion of the regions size. In restricted growth regions, the income and rent increases will be much larger. The growth in the area is driven by workers with higher incomes. Instead of a rapid expansion of the region, the character of the existing real estate will change. More home amenities will be desired. In any region, the increase of incomes and housing costs will reduce the demand for the output. Employers will need to increase prices to cover the higher wages, and related increases in commercial real estate costs/rents. Not all of factors of output, income, and rents will adjust simultaneously. Income will rise faster than rent, and rent cannot rise faster than output prices. If demand for output decreases, the process will go into reverse. Incomes drop, real estate values and rents drop, and prices drop.
Regions can also grow due to a large influx of immigrants - remember Amsterdam had two such large migrations. This is known as supply induced growth and is much different from demand-induced growth. Labor has moved into the region from another, not mainly for work, but due to external events such as war or a weather related disaster. Output prices will go down as the quantity of the output rises, as long as demand remains - more jobs are created. Wages will go down as the new workers compete for employment. The degree of wage losses will exceed the price reduction in outputs. Meanwhile, demand for housing will actually cause real estate values and rents to increase.
With high demand for the regions products and services, the new immigrants will be absorbed into the workforce. The region will experience large increases in worker productivity and employment. Only a slight decline in wages and prices would occur. Real estate prices and rent would still rise due to increased residential and commercial demand.
If demand for our products and services is fixed - it is a much different outcome for the region. Most of the immigrants will not be able to be absorbed into the workforce. Output prices and wages will fall significantly. There may be a slight increase in output due to the lower prices - we create a few more low paying jobs. Real estate values and rents will rise, but modestly when compared to the demand growth scenario. In the end, many of the immigrants will leave the region to find work elsewhere.
A region's outputs are important. When export demands for the outputs are up, more jobs are created and new businesses move into the region or are created. Here is where the national economy plays a strong role. Interest rates, unemployment, regulations, and foreign events can affect export demand. To sum up a very complicated relationship in an over simplistic way - a rising tide raises all ships. If the tide goes down - so do the ships. No region can escape the affects of the national economy.
Over time, regions tend to specialize in certain goods and services - outputs. Due to specialization, they may experience greater growth than competing regions for a longer period. How can they achieve greater growth? Due to the composition of firms and industries in the region called the industrial mix. Regions made up of more growing industries will perform better than regions with an inferior industrial mix. It has been theorized that some of the industry growth and mix may have similar attributes to a product cycle. In a typical product cycle an item is invented, produced, and then standardized. The basic concept of the theory is as follows.
Once a new product is invented, new firms will expand rapidly to supply demand as the market begins to accept the product. Competitors and collaborators will begin to "cluster" near the firm forming a concentration of the industry. The clustering has many beneficial effects, as new products and businesses will spin off existing firms to start new companies and production. New industries will be developed, and the region will experience further rapid growth. As the prior model suggests, incomes and property values will go up. As the products become standard, producers and competitors will look for other areas where they can pay lower wages and overhead costs to increase profits. Outsourcing begins.
Let us take a quick look at an example of product cycle growth and clustering. Imagine we are back during 1950 in Palo Alto, California. The area is known as "The Valley of the Hearts' Delight". Here they grow trees to harvest prunes and apricots. After the Second World War, Stanford University had amassed a large debt due to its many expansion efforts. Looking for a solution, they conceived of an industrial park on a ranch left to them by Leland Stanford. The staff at Stanford felt they could develop the land to help solve some of the financial woes of the university. Not able to sell the land due to terms in the bequest by Leland, they would lease the land for 99-year contracts. Most importantly, only high technology companies that could benefit the university would be allowed in the development.
The Stanford Industrial Park was established, with the first facility opened in 1953. High tech companies of the day, like Hewitt Packard, soon began leasing land and building facilities. The high-tech industrial park was very successful - it was a cluster of high-tech firms. Within the next two decades, this cluster would change the world.
In 1968, a company called Intel was formed in Santa Clara nearby. In 1971 they created the first microprocessor, and the area was coined "Silicon Valley" by a local trade paper reporter. Intel then produced the first microcomputer in 1972 - then things really get moving. The microchip industry would be launched, followed by the personal computer, microprocessors, and internet industries. Not to mention the venture capital firms. New industries and companies were born with several spin-offs. As the technologies matured, other firms in various regions and countries would compete. Eventually, some of the earlier technologies and products would move overseas to low cost manufacturers.
Many believe that housing prices also experience cycles. Researchers though, seem to have concluded that the housing price movements are a combination of external "shocks" and buyers/sellers expectations of housing value movement. The price movement is a markets continual attempt to come to a point of equilibrium. Supply and demand want to be equal.
To illustrate, think of a metropolitan region as a pond where a large rock is thrown in the middle. Our rock could be a positive event, such as a surge in demand for our cities products and services. Imagine the water's surface as housing prices; there we see small ripples due to wind - pricing fluctuations from the local supply and demand. Once the rock hits the water, there is a huge splash - our external shock. Initially a large wave imitates outward. Since there was only so much energy, the wave will eventually decrease in magnitude, however; the surface of the pond is now rippling up and down as the water surface tries to come to back to equilibrium. Equilibrium though can never be reached, because the world will keep chucking rocks at us.
Although dramatically oversimplified, housing prices behave similar to our pond's surface. After a positive economic shock, there is a run up (or drop if negative) in housing prices as demand suddenly increased. To meet the new demand and capitalize on the higher prices, new homes will be built to add to the housing supply. Due to a variety of reasons, developers will supply more homes than there is demand for - prices drop. At some point, the prices reach a level where buyers will begin purchasing new homes again - prices rise, and so on.
In general, housing demand is driven by the number of households, which is a group of people living in the same dwelling. Changes in the number of households or the composition of the households indicate a change in demand. The more households that come into a region - the more dwellings required.
Demographics keep us abreast of how a regions housing market is composed. Homeowners take a basic path. First, rent a dwelling, and then eventually purchase the first home (starter home). Next, they trade-up to a larger home, and finally buy a retirement home. Along the path, the homeowner is getting older. The demographics will show the various numbers of the population that are potentially on different parts of the "path". Understanding the composition of the population and the changes within age groups can help identify changes in demand. As people age, they generally see an increase in their income. With a growing income, they are more likely to own a home, the larger the income the larger the home. Purchasing of houses of increasing value continues until people hit their mid-sixties, then retirement considerations come into play - and home values decrease. For our purposes, the demographics would show if the composition and changes in the population growth was from households and demographics with higher incomes, which could be a positive sign of home values increasing. A growth spurt from low-income households would have limited housing value increase potential.
Affordability is the throttle that governs price movement. Since most buyers finance a large portion of their home purchase, the mortgage market has a large influence on how much values can rise. Terms of the mortgage, such as interest rates and amortization schedule, will limit the amount of money buyers can borrow. If incomes are not rising, home prices cannot increase as much since fewer buyers will qualify for loans. When the economy is strong, mortgage lenders may be less risk adverse and allow higher borrowing limits anticipating rising incomes. In a down economy, the lenders would tighten their lending policies - lower borrowing limits regardless of income. Affordability directly affects the level of housing demand.
Average sales time is a good indicator of future housing prices. The average sales time during a "normal" economy is around two to three months. A longer the sales time could indicate problems in the local or regional economy - housing prices would be expected to drop the longer a home is on the market. Shorter sales periods may indicate new demand coming into the market - we would expect prices to increase.
Although there are several other variables that could be considered, by looking at demographics, affordability, and average sales time we can get a good sense of potential market direction. To try to predict the levels of housing prices we would need to build an econometric model, which is beyond the scope this book. How does this tie back into the ripples on the pond? Our variables explain the direction of price, but do not address the volatility of the price movement. Again we will go back to the regions attempt to balance supply and demand.
Let us tie it all together. Recall that the main growth in property values comes from outside the region for our exports of goods and services - the rock thrown into the pond. The demand for exports fluctuates with the national economy. Higher demand will spur growth that will bring in new workers who will compete for local housing. Demographic data will be able to help to break down the growth into potential demand in each housing category. Regional prices adjust quickly to demand, so prices will go up the most in the housing categories with the most demand. As prices rise, builders, and developers will be enticed to develop new housing supply. At the same time, owners and realtors are seeing prices rise, and anticipate similar or slightly better pricing for their homes. Everything is going up, at least on paper.
As mentioned earlier, due to the nature of development the new supply tends to lag behind demand. Once prices hit an appropriate level, developers will begin building new units and subdivisions - they get overly optimistic. When demand suddenly falls, the new supply is still being put onto the market as construction is being completed. The net effect is the market becomes oversupplied with homes for sale. Average sales time on the market will begin to increase. Developers will cut prices to get rid of the left over inventory of homes - if possible. With comparable sales prices dropping, sellers will eventually need to lower their prices or stay put. Here is where it gets interesting. Prices will drop to a point where buyers will begin purchasing again. Investors begin to jump in with the buyers figuring home prices are undervalued - remember - prices tend to rise or fall to meet demand. Home prices will rise to new level, which may be much lower than the earlier highs, and may require adjustment to meet demand. As we can see, the "cycle" is really just supply continually trying to balance with demand. Pricing seems to be more of an outcome than a cause.
To forecast housing prices one must consider effects of the national economy, local economy, households, income growth, and housing supply. We need an econometric model. Running a trend line on housing prices will not work. Only models that take into account all the factors of supply and demand have a chance of correctly anticipating price movements. Although building a model seems daunting, with a bit of research most find that it is worth the effort. The math is basic, and most models can be done in a spreadsheet. The hardest part of the exercise is getting all of the data.
Luckily, today many websites and associations are continually trying to forecast housing price levels. If we cannot put our own model together, we can look to compare other econometric models. Keep in mind that we must seriously consider the source of the model and whether the results are biased. Always check more than one model, and see what assumptions are being made.
Speculation is taking on higher risks to gain short-term profits. Most investments in residential real estate such as house flipping and "fixer uppers" are speculative. This is not to say that these investments are bad - they are just high risk. Understanding speculative behavior can help us to take advantage of housing price movements, especially when speculation moves into frenzy - bubbles form.
Speculation is an emotional response to positive economic shocks, and can be a prime mover of home prices. Initially home prices will rise based on the new demand created by the positive economic shock. Speculators following price trends will now have expectations that home prices will continue to rise. To reinforce their expectations many will attempt to predict future pricing trends based on past market "cycles". Once the media begins exaggerating the positive housing market, we move from a few speculators to a feeding frenzy. Everyone wants to make a quick buck. We see it on television, read about it, and hear about it at cocktail parties. The frenzy may be localized in one region. In time, it will eventually spread like a virus to contaminate other regions. Home prices will be driven up by short-term speculative forces - not rational supply and demand. So begins a bubble.
To keep the bubble growing requires the help of lending institutions. Less stringent lending practices are the equivalent to adding fuel to the fire. To keep lending and making fees, the lenders allow greater leverage for buyers to compensate for the rapidly rising home values. Excessive credit is provided. Furthermore, inflated real estate values are used as collateral for loans. This sets up a mechanism for raising home and property values. Lenders provide excess credit to buy properties with inflated prices. If prices increase further, the buyers will use the inflated price as collateral for financing to invest in another over valued property. Our initial economic shock may have started the bubble, but loose lending practices are what inflate it to its maximum limit.
Eventually, the fundamentals of supply and demand will assert themselves. Sales of homes will begin to decrease. Prices will flatten out - then fall dramatically. Buyers find they cannot sell their investment property and loose them to the banks. The lenders end up with overvalued properties that they end up selling below mortgage costs. Many lenders may go out of business. The regional and national economies will be negatively affected.
Bubbles tend to happen in assets where values are difficult to assess. This makes them common in the property markets were investors fall prey to poor pricing ability and forecasts. Nearly every country with a free property market has experienced a housing bubble at various points in history. Like it or not, bubbles will be around as long as people feel they can make a profit. For synthetic real estate, bubbles can be highly profitable, as we will cover later. What we need to focus on is where prices will move the most.
Much like normal housing values, bubbles will tend to grow largest in areas with restricted zoning practices or physical constraints in size - think Manhattan. New supply will be difficult to bring to the market. Land to build new buildings is expensive, no thanks to our speculative behavior; and difficult governmental procedures will slow how fast the new supply can be brought to market. Therefore, existing prices will rise rapidly. At least until a glut of supply hits the market. In regions with low barriers to growth, even a bubble has a limited affect on housing prices. Supply quickly steps in to compete with existing properties so prices do not rise as much.
What are the warning signs that a bubble is occurring? Unfortunately, we will not have a definitive sign. However, we can look out for a few things. In the media, there will be a lot of positive home real estate chatter, and a lot more get rich quick gurus will have infomercials. People outside of real estate will start chatting about getting into real estate. A large number of new development announcements. If we monitor home prices, we might see home values begin to increase faster than incomes can afford. Other warning signs would be a contraction of housing sales average days on the market and months of inventory - smaller than two to three months may indicate a buying frenzy.
As the bubble begins to burst, the months of inventory will continue to grow due to new developments completing construction and coming to market. The supply will overshoot demand.