In October and November of 2020, a record 29.4% of users on redfin.com were seeking to move to another metro, the highest reading since Redfin began tracking the metric in 2017. During the same time period, the Puget Sound region (along with many other regions around the country) experienced housing prices that climbed to record highs, supply levels at all time lows and houses that sold at over the asking price. In some cities, 68.9% or more of all homes sold over the asking price. Certainly, the pandemic was a major driver of this – but how many of these trends were already in place, and where is everybody moving to?
This article examines the migration patterns in the US before the pandemic and how, if at all, the pandemic had affected these patterns. First, we examined the migration patterns before the pandemic using the 2019 Census data as a proxy. Then, we identified four possible factors that drove the migration patterns in the top 10 states with the highest net gain or loss. The four factors we identified were:
- Home Values
- Migration Survey
- Business Tax Climate
- Tech Labor Pool Size
We then compared this data with a study by MyMove which looked at the USPS change of address data during the months of February and July of 2020. As a final data point for consideration, we compared the migration data during the pandemic to the total number of cases by state.
| Highest Net Gain | Highest Net Loss | ||
|---|---|---|---|
| Florida | 144,310 | New York | -184,902 |
| Texas | 106,646 | California | -173,347 |
| Arizona | 79,664 | Illinois | -117,552 |
| North Carolina | 59,869 | New Jersey | -80,224 |
| South Carolina | 46,781 | Maryland | -41,533 |
| Colorado | 42,184 | Massachusettes | -34,025 |
| Tennessee | 40,207 | Louisiana | -28,247 |
| Washington | 32,198 | Michigan | -20,357 |
| Georgia | 30,976 | Hawaii | -18,709 |
| Nevada | 27,593 | Alaska | -16,103 |
Before the pandemic, the states with the highest net inflows of population were Florida, Texas, and Arizona. The states with the highest net outflows were New York, California, and Illinois. We’ll first consider real estate as a potential driver of the migration patterns, as real estate is one of the largest expenses that most households incur.
Home Values
For our comparison, we used the Zillow Home Value Index, which is seasonally adjusted and only includes the middle price tier of homes. The table below shows the home value ranking for the top 10 states we identified above, with 1 being the least expensive and 51 being the most expensive (including the District of Columbia).
| Highest Net Gain | Zillow Home Value Index | Highest Net Loss | Zillow Home Value Index |
|---|---|---|---|
| Florida | 27 | New York | 42 |
| Texas | 24 | California | 49 |
| Arizona | 33 | Illinois | 22 |
| North Carolina | 21 | New Jersey | 43 |
| South Carolina | 17 | Maryland | 41 |
| Colorado | 46 | Massachusettes | 48 |
| Tennessee | 15 | Louisiana | 12 |
| Washington | 47 | Michigan | 13 |
| Georgia | 20 | Hawaii | 51 |
| Nevada | 39 | Alaska | 37 |
| Average | 28.9 | 35.8 |
Of the top 10 states that people are moving to, 8 have home value indexes in the 64th percentile or below. For the states that people are moving away from 7 of them are in the 80th percentile or above. In aggregate, the two data sets appear to be only 14 percentile points different. However, we can see that 3 of the most expensive states in the US (excluding D.C.) are in the highest net loss column. While the trend appears to favor lower cost states (Washington and Colorado being the exception), Louisiana, Michigan, and Illinois appear to have some other driver other than real estate.
Migration Survey
As the previous table shows, real estate is only one of the factors that influence migration patterns. Next, we examined a 2019 study from United Van Lines showing the results of a survey that asked why movers were relocating. The possible options provided were: retirement, health, family, lifestyle, and job.
Using the top 10 list of states with the highest net gain/loss from the Census, the table below shows the number one reason why people moved to the state for the states with the highest net gain. Conversely, for states with the highest net loss, the table shows the top reason why people left the state.
| Highest Net Gain | Reason for Arrival | Percentage | Highest Net Loss | Reason for Departure | Percentage |
|---|---|---|---|---|---|
| Florida | Retirement | 40.52% | New York | Job | 37.20% |
| Texas | Job | 56.75% | California | Job | 39.02% |
| Arizona | Retirement | 36.48% | Illinois | Job | 40.66% |
| North Carolina | Job | 44.76% | New Jersey | Job | 34.76% |
| South Carolina | Retirement | 39.55% | Maryland | Job | 46.15% |
| Colorado | Job | 43.01% | Massachusettes | Job | 43.10% |
| Tennessee | Job | 54.27% | Louisiana | Job | 70.68% |
| Washington | Job | 49.27% | Michigan | Job | 46.54% |
| Georgia | Job | 62.02% | Hawaii | Job | N/A |
| Nevada | Retirement | 36.97% | Alaska | Job | N/A |
The study shows that the number one reason why people moved to Florida, Arizona, South Carolina, and Nevada was for retirement. For all other states with the highest net gain, the primary reason for the move was for work. The states with the highest net loss all showed that the number one reason for leaving was for work.
Business Tax Climate
One the biggest motivating factors in relocating is the prospect of increased wealth and thus a better quality of life. As such, changing the amount of taxes an individual owes can have a significant impact on their wealth. Next, we looked at the state business tax climate index from the Tax Foundation, which showed how well states structure their tax systems. The table below shows the business tax climate rank by state, with 1 being the most favorable tax climate and 50 being the least favorable.
| Highest Net Gain | State Business Tax Climate Index | Highest Net Loss | State Business Tax Climate Index |
|---|---|---|---|
| Florida | 4 | New York | 49 |
| Texas | 13 | California | 48 |
| Arizona | 20 | Illinois | 35 |
| North Carolina | 15 | New Jersey | 50 |
| South Carolina | 30 | Maryland | 43 |
| Colorado | 17 | Massachusettes | 36 |
| Tennessee | 18 | Louisiana | 41 |
| Washington | 19 | Michigan | 12 |
| Georgia | 32 | Hawaii | 37 |
| Nevada | 7 | Alaska | 3 |
| Average | 17.5 | Average | 35.4 |
The states with the highest net gain averaged in the 33rd percentile and the states with the highest net loss averaged in the 69th percentile (the lower percentile being more favorable). This shows the average index of the states with the highest net gain approximately twice as favorable as that of states with the highest net loss. New York, California, and New Jersey, (the states with the 3 most unfavorable tax climates) topped the list of states with the highest net loss.
On average, people appear to be migrating towards more favorable tax climates. While the data shows that people are migrating away from states with the most unfavorable tax climates, the reverse is not true about the states with the most favorable tax climates.
Tech Labor Pool Size
In a 2019 report, CBRE analyzed metropolitan areas across the US, and ranked them according to the size of their tech labor pool based on data from the US Bureau of Labor Statistics. The table below shows the ranking of each state, with 1 being the highest rank (largest tech labor pool) and 50 being the smallest. As the metropolitan areas represent the most densely populated areas of each state, we extrapolated the CBRE data as a proxy to represent each state.
| Highest Net Gain | Tech Ranking | Highest Net Loss | Tech Ranking |
|---|---|---|---|
| Florida | 4 | New York | 3 |
| Texas | 2 | California | 1 |
| Arizona | 18 | Illinois | 6 |
| North Carolina | 12 | New Jersey | 13 |
| South Carolina | 28 | Maryland | 14 |
| Colorado | 15 | Massachusettes | 11 |
| Tennessee | 22 | Louisiana | 37 |
| Washington | 7 | Michigan | 16 |
| Georgia | 10 | Hawaii | 46 |
| Nevada | 36 | Alaska | 51 |
| Average | 15.4 | Average | 19.8 |
The top 4 states according to tech labor pool occupy the highest ranks of both the states with the highest net gain and net loss. Could this is be a sign that the tech demographic is driving the some of the most active states with migration? For our analysis, we would require more detailed resolution on the employment classification of the movers. It is worth noting that as we go down the list in both columns the relationship to tech appears to be less important.
Comparison – During the Pandemic
Next, we look at the MyMove study using the USPS change of address data during the peak months of the pandemic and compare it to the migration patterns prior to the pandemic.
The table below shows Florida, New York, and California topping the list of states with the highest net outflow and Michigan, North Carolina, and Texas as the states with the highest net gain.
In terms of magnitude, the top 3 states with the highest net loss averaged 146,922, and the top 3 states with the highest net gain averaged 37,994, which is 3.9 times less. The evidence suggests that people were leaving highly concentrated areas, but not necessarily moving to other highly concentrated areas.
| Highest Net Gain | Highest Net Loss | ||
|---|---|---|---|
| Michigan | 45,408 | Florida | -235,765 |
| North Carolina | 37,971 | New York | -117,251 |
| Texas | 30,603 | California | -87,750 |
| New Jersey | 25,738 | Arizona | -41,923 |
| Minnesota | 25,315 | District of Columbia | -15,638 |
The table below compares the states with the highest net gain/loss before and during the peak of the pandemic. States that continued the trend of gain before and during would be in the upper left corner of the table and states that continued the trend of net loss before and during would be in the lower right corner.
| Highest Net Gain During | Highest Net Loss During | |
|---|---|---|
| Highest Net Gain Before | Texas, North Carolina | Florida, Arizona |
| Highest Net Loss Before | New Jersey | New York, California |
Texas and North Carolina maintained their position as top destinations before and during the pandemic, while New York and California continued their trend as top originations.
Florida and Arizona flipped from being the states with highest net inflows, to being in the column with the highest net outflows. When we look back at the United Van Lines study, Florida and Arizona were both destinations where the top reason for moving was retirement. Conversely, Texas and North Carolina (top destinations before and during) were both driven by employment.
New Jersey was the only state in our list which went from being a state in the highest net loss column to a state the highest net gain. On the basis of retirement as an explanation, while the number one reason for leaving New Jersey was employment at 34.76%, retirement was a close second at 33.18%. As the case with Florida and Arizona it is possible that those who moved for retirement prior to the pandemic returned home.
Lastly, we will look at the states with the highest net gain/loss during the pandemic and the total number of cases by each state. For this, we used a recent study from Trepp which showed the total number of cases by state based on data from John Hopkins.
| Highest Net Gain | Rank (Number of Cases) | Highest Net Loss | Rank (Number of Cases) |
|---|---|---|---|
| Michigan | 38 | Florida | 49 |
| North Carolina | 42 | New York | 48 |
| Texas | 50 | California | 51 |
| New Jersey | 40 | Arizona | 41 |
| Minnesota | 36 | District of Columbia | 4 |
The results show that while the states with the highest number of cases also had the highest net outflows, the top destination states appear to have some other driver than a low number of cases.
Florida, New York, and California topped the list for highest net loss and were also the states with the highest number of cases. The exception being Texas, which had the third highest net gain, but also the second highest number of cases of any state in the US.
Conclusion
At the beginning of the article, the initial questions we posed were: did the pandemic just accelerate trends that were already existing, or did it change the behavior in migration patterns? It appears that the answer is both.
In all data sets the trend of moving out of high cost, densely populated areas where factors contribution to high cost of living including housing, taxes, and strong employment consistently showed signs of net loss before and during the pandemic. Additionally, most of the moves appeared to be conditioned on some type of employment. As tech was a major driver of job growth, we saw large movements both in and out of areas which had high concentrations of tech workers. Trends that the pandemic did reverse were situations where the moves were not employment related, such as retirement.
In answer to the question of where are people going, one paradigm that the pandemic did accelerate was the shift towards remote work. As such, employees at tech oriented companies who had already had this infrastructure in place were likely among the first to be able to relocate to more affordable areas. The data shows that there was evidence of this migration behavior prior to the pandemic and in that regard, the pandemic likely accelerated this behavior.
With the large discrepancy between housing prices in highly concentrated primary markets and more sparsely populated secondary and tertiary markets, the increase in quality of life that relocating affords is a proposition that many people were and are still seriously considering. A quote from Redfin that commented on movers relocating from the Bay Area to the Sacramento area presents a compelling anecdote regarding the motivations behind recent migration patterns:
“With so many large tech companies allowing employees to work from home for the foreseeable future, homeowners in San Francisco are selling their two-bedroom, two-bathroom condo and buying a 5,000-square-foot home with five bedrooms and five bathrooms on an acre of land here for the same price. It’s simply a no-brainer.”
While there are many reasons that determine why people would choose to live in a specific area, the reality has become that for some employees, work no longer has to be one of those reasons. As long as companies continue to support the work from home model, it is likely that we will see these migration patterns continue.