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At our recent Chapman Update Forecast, we presented the results of research that explained why so many Californians are leaving the state.  

We concluded that the two most significant factors that explain this exodus are California’s high rate of taxation and business regulation. Our findings also showed that California’s high median housing price was not a major factor in explaining the exodus.

Imagine our surprise when we read the state’s controller’s recently issued study, “The Impact of Migration on California Income Tax Revenues.” Its conclusion was the opposite to ours, namely that “real estate prices are the most important factor in California migration decisions.”

The fact that our research findings are so radically different from the controller’s office is worthy of careful examination, particularly as it relates to public policy.  

If California’s recent domestic migration annual outflow of 261,000 people to other states is a result of high taxes and regulation, then that suggests the state needs to give careful scrutiny to reducing taxes and regulation.  

But if, as the controller’s office argues in its recently published study, that high housing prices are the culprit, then policies should be directed at increasing the supply of housing.

In fact, the state is already implementing policies directed at forcing county and local governments to adopt zoning changes designed to increase the supply of housing. The controller’s report presents findings that support those policies.

Our review of the controller’s report, however, suggests that its findings do not stand up to careful scrutiny.

For example, the report presents Figure 1 that purports to show that “…the flow of net migration in and out of California has followed a pattern similar to that of the cost of housing in California relative to that of the country.”

A closer examination of Figure 1, however, points to a lead/lag pattern that does not support that conclusion. For example, net out-migration peaks in 2005 and then drops sharply. The relative price of a home in California, however, continued to increase for two more years. If relative home prices in California explain net out-migration, as the controller’s report argues, then the change in home prices should lead not lag the change in out-migration.

A more fundamental error in the controller’s study is that its finding that high housing prices explain California’s high levels of out-migration is not supported by statistical measures of correlation.  

The correlation coefficient between home prices and net domestic migration for all 50 states indicates that there is no significant relationship between home prices and migration.  

But the correlation coefficients between taxation and migration and between regulation and migration are both highly significant at a 99% level of confidence.  

More intuitively, Figure 2 shows the average net migration from each quintile of 10 states from the lowest median home prices to the highest home prices. The findings in the controller’s study suggest that net migration should be positive when home prices are low and become increasingly negative at higher home prices. No such pattern exists in Figure 2.

But when states are arranged in ranking from lowest to highest in state and local tax, net domestic migration, as shown in Figure 3, steadily moves from positive to negative. The 10 states that ranked lowest in state and local taxes, for example, had positive net migration, on average, of about a half percent in population growth. These states, however, that ranked highest in taxes had negative net migration of -0.34%.

Similarly, when states are arranged in ranking from lowest to highest in regulation, net domestic migration, as shown in Figure 4 clearly moves from positive to negative.

Identifying differences in the methodology and findings between our research and that included in the controller’s report is much more than an argument over statistics.  

Bad research often leads to conclusions that give spurious statistical support to public policy decisions. In the case of the controller’s report, the findings suggest that legislation should be aimed at increasing the supply of homes rather than focusing the attention on the real culprit—high state and local taxes and onerous business regulation.

The state’s bad research is similar to a terribly flawed study by the McKinsey Global Institute that served as the basis for Gov. Gavin Newsom’s goal of building 3.5 million housing units by 2025.  

As has been shown in previous research we’ve published, the assumption in the McKinsey study that California’s population to housing unit ratio should equal the average for the U.S. is ludicrous.

Yet, that terribly flawed assumption was the basis for the study’s recommendations that ultimately led to draconian legislative dictates from Sacramento to local jurisdiction about zoning policies. Now the recent controller’s study, another report based on faulty statistical approaches, serves to buttress the case for Sacramento’s oppressive intrusion into housing markets and local zoning policies.

It’s critically important that legislation be based on sound and accurate statistical information. Research findings shouldn’t be used as cannon fodder that provides cover for a particular policy path.  

Rather, research findings should be carefully designed, studied and debated so that public policy is grounded in sound economic and statistical analysis.

Editor’s Note: By James L. Doti, Ph.D., is president emeritus and professor of economics at Chapman University. Raymond Sfeir, Ph.D., is director of the A. Gary Anderson Center for Economic Research at Chapman.

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