What Causes Residential Real Estate to Appreciate?
Before reading on, please take a moment to answer the above question by selecting the best answer from the choices below:
A. High household income
B. High population
C. Rising household income
D. Rising population
We all know that real estate prices are higher in urban than in rural areas, and highest of all in the affluent residential enclaves of our largest cities. But, how did these high prices get to where they are? In other words, what are the essential factors that cause real estate prices to rise?
Thinking about human settlement patterns, urbanization and industrialization throughout the course of civilization, my initial guess was that rising household income (choice C) and rising population (choice D) would be the most important drivers of residential real estate prices. I figured that, not income levels and populations themselves but instead changes in these variables would be most highly correlated to rising real estate prices. After all, classical equilibrium economics tells us that, not supply and demand themselves but changes in supply and demand are what drive changes in prices.
To explore this issue, I use data from the U.S. Census Bureau (www.census.gov) for median household income and population and from the Office of Federal Housing Enterprise Oversight (www.ofheo.gov) for changes in median housing prices. Interested in long-term price behavior, I go as far back as the OFHEO data allow (to 1980), capturing changes over the past 25 years. To achieve a large enough but still manageable sample size, I focus on the 50 states plus the District of Columbia, giving 51 distinct geographical entities in total.
Below I summarize the data, showing extremes, averages and correlations:
(To help display correlations, I provide in parentheses beside each data point the corresponding annual percentage change in median housing prices for the period 1980-2005)
Median Household Income in 1984 (A)
Highest:
1. Alaska: $32.3k (3.4%)
2. Connecticut: $30.0k (5.9%)
3. Maryland: $29.7k (5.9%)
4. Hawaii: $28.9k (5.9%)
5. New Jersey: $27.8k (6.5%)
Lowest:
47. Alabama: $17.3k (3.7%)
48. West Virginia: $16.8k (3.1%)
49. Tennessee: $16.8k (4.0%)
50. Arkansas: $15.7k (3.4%)
51. Mississippi: $15.4k (3.2%)
Average: $22.4k (5.1%)
Population in 1980 (B)
Highest:
1. California: 23.7 mil. (6.9%)
2. New York: 17.6 mil. (7.2%)
3. Texas: 14.2 mil. (2.7%)
4. Pennsylvania: 11.9 mil. (5.1%)
5. Illinois: 11.4 mil. (4.9%)
Lowest:
47. District of Columbia: 0.6 mil. (6.8%)
48. Delaware: 0.6 mil. (5.9%)
49. Vermont: 0.5 mil. (5.6%)
50. Wyoming: 0.5 mil. (3.1%)
51. Alaska: 0.4 mil. (3.4%)
Average: 4.4 mil. (5.1%)
Annual Percentage Increase in Median Household Income from 1984 to 2003 (C)
Highest:
1. Tennessee: 4.3% (4.0%)
2. Wisconsin: 4.3% (4.5%)
3. District of Columbia: 4.3% (6.8%)
4. Minnesota: 4.1% (5.1%)
5. Alabama: 4.1% (3.7%)
Lowest:
47. Montana: 3.0% (4.5%)
48. Texas: 2.9% (2.7%)
49. New Mexico: 2.8% (3.9%)
50. Oklahoma: 2.8% (2.4%)
51. Alaska: 2.5% (3.4%)
Average: 3.5% (5.1%)
Annual Percentage Increase in Population from 1980 to 2002 (D)
Highest:
1. Nevada: 4.6% (5.1%)
2. Arizona: 3.2% (4.5%)
3. Florida: 2.5% (5.3%)
4. Alaska: 2.2% (3.4%)
5. Utah: 2.1% (4.2%)
Lowest:
47. Pennsylvania: 0.2% (5.1%)
48. Iowo: 0.0% (3.4%)
49. North Dakota: -0.1% (3.1%)
50. West Virginia: -0.4% (3.1%)
51. District of Columbia: -0.5% (6.8%)
Average: 1.1% (5.1%)
Annual Percentage Increase in Median Housing Price from 1980 to 2005
Highest:
1. Massachusetts: 8.0%
2. New York: 7.2%
3. Rhode Island: 7.0%
4. California: 6.9%
5. District of Columbia: 6.8%
Lowest:
47. Wyoming: 3.1%
48. North Dakota: 3.1%
49. Louisiana: 2.9%
50. Texas: 2.7%
51. Oklahoma: 2.4%
Average: 5.1%
Correlations Between Increase in Median Housing Price and:
A. Initial Median Household Income: Correl. = 0.45
B. Initial Population: Correl. = 0.08
C. Increase in Median Household Income: Correl. = 0.15
D. Increase in Population: Correl. = 0.07
The data reveal that, moreso than changes in income and population (C and D, low correlations), it is median household income itself (A, correl. of 0.45) that appears to be the most significant driver of housing prices. This is an unexpected result, indicating that the mechanism underlying appreciation of residential real estate prices over at least the past 25 years has NOT been the traditional model of people flocking from countryside to city for work, receiving higher pay and concurrently bidding up real estate values in the cities through increased demand and limited supply. Based on percentage increase in median household income, Tennessee and Wisconsin rank #1 and #2; yet, when ranked by real estate appreciation, they fall to #35 and #26, respectively. Similarly, population has risen most dramatically in Nevada and Arizona; however, in terms of real estate price appreciation, these states rank #19 and #25, respectively.
Another way to view the data is to see how the top 15 states by housing price appreciation compare with their corresponding rankings across our four factors:
Ranking by Housing Price Appreciation vs. Ranking by Factors: A, B, C, D
1. Massachusetts: 6, 12, 36, 37
2. New York: 25, 3, 27, 43
3. Rhode Island: 26, 41, 14, 35
4. California: 12, 2, 23, 9
5. District of Columbia: 38, 48, 3, 51
6. New Jersey: 5, 10, 19, 26
7. Maine: 35, 39, 41, 32
8. New Hampshire: 8, 43, 6, 14
9. Connecticut: 2, 26, 39, 39
10. Delaware: 9, 49, 34, 16
11. Hawaii: 4, 40, 43, 20
12. Maryland: 3, 19, 46, 19
13: Vermont: 23, 50, 31, 24
14. Virginia: 7, 15, 15, 15
15. Washington: 13, 21, 33, 10
Average Rankings: 14 (A), 28 (B), 27 (C), 26 (D)
Among our four factors, only initial median household income (A) carries a significantly high average ranking, being in the teens instead of the mid-twenties--hence, exhibiting a much higher correlation to price appreciation than the other factors do.
How, then, do we explain our result that housing prices have appreciated most significantly in states where median household income started off 25 years ago being higher than average? I offer the following plausible explanation:
1. Maturing Society: During the past 25 years, we have seen a maturing of American society, with established cities and neighborhoods receiving more attention than newer communities. Driving influences include the aging of the babyboomer generation and their lifestyle preferences (social "herding"), growth of the service sector and office-related work (favoring in-city workplaces), etc.
2. Wealth Concentration: The result is increased demand for real estate in already established areas where incomes are already high and cultural amenities are more developed. Existing income drives real estate prices higher, producing additional wealth for existing property owners and further concentrating wealth in these areas.
3. Attraction to the Coast: Among the top 15 states showing the greatest real estate price appreciation, all are located in the Northeast or Mid-Atlantic (between Maine and Virginia) or on the West Coast (including Hawaii), and only Vermont has no coastline exposure on the Atlantic or Pacific Ocean. Geography (ocean, beaches), climate (milder temperatures) and business and trade patterns (with Europe and Asia) all contribute to the attraction of people and businesses to coastal states and cities.
Based on this trend of coastal property price appreciation, I would venture to guess that, for better or worse, over the next 25 years we will see further polarization of American society into older, more established "haves" residing in affluent communities on the Atlantic and Pacific Coasts and contributing to a further rise in real estate prices in the coastal states, versus a larger group of "have nots" living in more inland areas with a lower wealth base and experiencing less property price appreciation.
In essence, real estate price appreciation trends are an example of how wealth (high household income--choice A) tends to beget more wealth (manifested, in this case, by rising real estate prices). Surprisingly, the absolute level of income and wealth (as opposed to changes in income levels) appears to have the most significant impact on real estate appreciation.
A. High household income
B. High population
C. Rising household income
D. Rising population
We all know that real estate prices are higher in urban than in rural areas, and highest of all in the affluent residential enclaves of our largest cities. But, how did these high prices get to where they are? In other words, what are the essential factors that cause real estate prices to rise?
Thinking about human settlement patterns, urbanization and industrialization throughout the course of civilization, my initial guess was that rising household income (choice C) and rising population (choice D) would be the most important drivers of residential real estate prices. I figured that, not income levels and populations themselves but instead changes in these variables would be most highly correlated to rising real estate prices. After all, classical equilibrium economics tells us that, not supply and demand themselves but changes in supply and demand are what drive changes in prices.
To explore this issue, I use data from the U.S. Census Bureau (www.census.gov) for median household income and population and from the Office of Federal Housing Enterprise Oversight (www.ofheo.gov) for changes in median housing prices. Interested in long-term price behavior, I go as far back as the OFHEO data allow (to 1980), capturing changes over the past 25 years. To achieve a large enough but still manageable sample size, I focus on the 50 states plus the District of Columbia, giving 51 distinct geographical entities in total.
Below I summarize the data, showing extremes, averages and correlations:
(To help display correlations, I provide in parentheses beside each data point the corresponding annual percentage change in median housing prices for the period 1980-2005)
Median Household Income in 1984 (A)
Highest:
1. Alaska: $32.3k (3.4%)
2. Connecticut: $30.0k (5.9%)
3. Maryland: $29.7k (5.9%)
4. Hawaii: $28.9k (5.9%)
5. New Jersey: $27.8k (6.5%)
Lowest:
47. Alabama: $17.3k (3.7%)
48. West Virginia: $16.8k (3.1%)
49. Tennessee: $16.8k (4.0%)
50. Arkansas: $15.7k (3.4%)
51. Mississippi: $15.4k (3.2%)
Average: $22.4k (5.1%)
Population in 1980 (B)
Highest:
1. California: 23.7 mil. (6.9%)
2. New York: 17.6 mil. (7.2%)
3. Texas: 14.2 mil. (2.7%)
4. Pennsylvania: 11.9 mil. (5.1%)
5. Illinois: 11.4 mil. (4.9%)
Lowest:
47. District of Columbia: 0.6 mil. (6.8%)
48. Delaware: 0.6 mil. (5.9%)
49. Vermont: 0.5 mil. (5.6%)
50. Wyoming: 0.5 mil. (3.1%)
51. Alaska: 0.4 mil. (3.4%)
Average: 4.4 mil. (5.1%)
Annual Percentage Increase in Median Household Income from 1984 to 2003 (C)
Highest:
1. Tennessee: 4.3% (4.0%)
2. Wisconsin: 4.3% (4.5%)
3. District of Columbia: 4.3% (6.8%)
4. Minnesota: 4.1% (5.1%)
5. Alabama: 4.1% (3.7%)
Lowest:
47. Montana: 3.0% (4.5%)
48. Texas: 2.9% (2.7%)
49. New Mexico: 2.8% (3.9%)
50. Oklahoma: 2.8% (2.4%)
51. Alaska: 2.5% (3.4%)
Average: 3.5% (5.1%)
Annual Percentage Increase in Population from 1980 to 2002 (D)
Highest:
1. Nevada: 4.6% (5.1%)
2. Arizona: 3.2% (4.5%)
3. Florida: 2.5% (5.3%)
4. Alaska: 2.2% (3.4%)
5. Utah: 2.1% (4.2%)
Lowest:
47. Pennsylvania: 0.2% (5.1%)
48. Iowo: 0.0% (3.4%)
49. North Dakota: -0.1% (3.1%)
50. West Virginia: -0.4% (3.1%)
51. District of Columbia: -0.5% (6.8%)
Average: 1.1% (5.1%)
Annual Percentage Increase in Median Housing Price from 1980 to 2005
Highest:
1. Massachusetts: 8.0%
2. New York: 7.2%
3. Rhode Island: 7.0%
4. California: 6.9%
5. District of Columbia: 6.8%
Lowest:
47. Wyoming: 3.1%
48. North Dakota: 3.1%
49. Louisiana: 2.9%
50. Texas: 2.7%
51. Oklahoma: 2.4%
Average: 5.1%
Correlations Between Increase in Median Housing Price and:
A. Initial Median Household Income: Correl. = 0.45
B. Initial Population: Correl. = 0.08
C. Increase in Median Household Income: Correl. = 0.15
D. Increase in Population: Correl. = 0.07
The data reveal that, moreso than changes in income and population (C and D, low correlations), it is median household income itself (A, correl. of 0.45) that appears to be the most significant driver of housing prices. This is an unexpected result, indicating that the mechanism underlying appreciation of residential real estate prices over at least the past 25 years has NOT been the traditional model of people flocking from countryside to city for work, receiving higher pay and concurrently bidding up real estate values in the cities through increased demand and limited supply. Based on percentage increase in median household income, Tennessee and Wisconsin rank #1 and #2; yet, when ranked by real estate appreciation, they fall to #35 and #26, respectively. Similarly, population has risen most dramatically in Nevada and Arizona; however, in terms of real estate price appreciation, these states rank #19 and #25, respectively.
Another way to view the data is to see how the top 15 states by housing price appreciation compare with their corresponding rankings across our four factors:
Ranking by Housing Price Appreciation vs. Ranking by Factors: A, B, C, D
1. Massachusetts: 6, 12, 36, 37
2. New York: 25, 3, 27, 43
3. Rhode Island: 26, 41, 14, 35
4. California: 12, 2, 23, 9
5. District of Columbia: 38, 48, 3, 51
6. New Jersey: 5, 10, 19, 26
7. Maine: 35, 39, 41, 32
8. New Hampshire: 8, 43, 6, 14
9. Connecticut: 2, 26, 39, 39
10. Delaware: 9, 49, 34, 16
11. Hawaii: 4, 40, 43, 20
12. Maryland: 3, 19, 46, 19
13: Vermont: 23, 50, 31, 24
14. Virginia: 7, 15, 15, 15
15. Washington: 13, 21, 33, 10
Average Rankings: 14 (A), 28 (B), 27 (C), 26 (D)
Among our four factors, only initial median household income (A) carries a significantly high average ranking, being in the teens instead of the mid-twenties--hence, exhibiting a much higher correlation to price appreciation than the other factors do.
How, then, do we explain our result that housing prices have appreciated most significantly in states where median household income started off 25 years ago being higher than average? I offer the following plausible explanation:
1. Maturing Society: During the past 25 years, we have seen a maturing of American society, with established cities and neighborhoods receiving more attention than newer communities. Driving influences include the aging of the babyboomer generation and their lifestyle preferences (social "herding"), growth of the service sector and office-related work (favoring in-city workplaces), etc.
2. Wealth Concentration: The result is increased demand for real estate in already established areas where incomes are already high and cultural amenities are more developed. Existing income drives real estate prices higher, producing additional wealth for existing property owners and further concentrating wealth in these areas.
3. Attraction to the Coast: Among the top 15 states showing the greatest real estate price appreciation, all are located in the Northeast or Mid-Atlantic (between Maine and Virginia) or on the West Coast (including Hawaii), and only Vermont has no coastline exposure on the Atlantic or Pacific Ocean. Geography (ocean, beaches), climate (milder temperatures) and business and trade patterns (with Europe and Asia) all contribute to the attraction of people and businesses to coastal states and cities.
Based on this trend of coastal property price appreciation, I would venture to guess that, for better or worse, over the next 25 years we will see further polarization of American society into older, more established "haves" residing in affluent communities on the Atlantic and Pacific Coasts and contributing to a further rise in real estate prices in the coastal states, versus a larger group of "have nots" living in more inland areas with a lower wealth base and experiencing less property price appreciation.
In essence, real estate price appreciation trends are an example of how wealth (high household income--choice A) tends to beget more wealth (manifested, in this case, by rising real estate prices). Surprisingly, the absolute level of income and wealth (as opposed to changes in income levels) appears to have the most significant impact on real estate appreciation.
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