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The Regional Economist | October 2006

Income Inequality: Time for Predatory Lending Laws?

Income inequality, the gap between the rich and the poor, seems to indicate a higher probability of a predatory lending law being adopted. States that recently adopted predatory lending laws had higher than average levels of income inequality over the past 10 years than their nonadopting counterparts.

Predatory lending—an illegal activity by lenders or brokers leading to a further decrease of well-being of relatively poor individuals—could generate greater inequality between individuals in the U.S. economy. Predatory lending laws, the laws aimed at reducing fraudulent lending activity, may do the most good in reducing inequality in states where inequality is larger.

Between 1999 and last year, 24 states plus the District of Columbia adopted laws to combat predatory lending. The law in each state is designed to restrict origination of specific types of loans—mostly mortgages—and/or to require lenders to disclose details about those loans to state regulators.

Predatory lending, even though it lacks an exact definition, is most often associated with lending to relatively poor borrowers, to those who are uneducated about the lending process and to those whose credit scores are low. Borrowers with incomes and/or credit scores below a certain threshold are usually not able to obtain credit unless they pay higher prices for their loans. Such loans are called subprime or high-cost loans. Not all high-cost loans are predatory, though.

Lending is considered predatory, or fraudulent, when lenders or brokers:

  • take advantage of borrowers by charging very high fees that are not justified by a risk factor;
  • issue loans knowing they can never be repaid or would almost certainly lead to home losses and complete bankruptcy; or
  • change the terms of a loan at closing, thus knowingly misleading borrowers.1

The relatively weak are both the easiest prey for predatory lenders and those most likely to suffer the greatest economic losses. If predatory lending—which tends to hurt poor people disproportionately more than those who are better off—is populated in an economy, then inequality may increase.

Income Inequality

Income inequality in the United States is greater than in any other developed country. Moreover, it has been increasing during the past 25 years.2 Whatever the actual level of an individual’s income, a person might be discouraged and unhappy if he or she is relatively poorer than many other people in society. Therefore, rising income inequality might be considered harmful to society not only because it represents a disparity between people, but also, as some research shows, because it can cause slower economic growth, an increase in crime, worse overall well-being, poor educational outcomes and even higher death rates, the same way a higher level of poverty (absolute, not relative) would.3

Besides predatory lending, there are a number of possible factors that can be responsible for inequality in a society. Differences in education and abilities create wage differentials leading to income differences; race, gender and cultural differences can give rise to discrimination in the labor market. Also, income inequality can rise if wealth circulates only among those who have the means to invest and to increase already existing wealth.

Several country-wide economic factors may affect inequality as well. For example, some research studies show that faster economic growth and greater economic development in an economy would benefit the rich and the poor equally. Because the “boats” of both would rise the same, however, the level of inequality would remain the same.4

Other studies show that countries with better-developed financial intermediaries experience faster declines in both inequality and poverty.5 However, financial development that offers greater credit availability to previously left-out borrowers (those with lower credit scores and incomes) can also open the door for more fraudulent lending. The number and variety of loan products available on the market these days are reaching enormously large magnitudes. A single financial institution can offer more than 600 different types of mortgage loans, which can confuse borrowers regarding what product to choose and allow unscrupulous lenders to take advantage of not just the poor but all who don’t know enough to protect themselves. Such “development,” once again, can increase income inequality.

If predatory lending leads to higher income inequality in an economy, then laws that restrict predatory activity would seem to be most needed in those states where inequality is relatively large. The analysis conducted for this article shows that predatory lending laws were indeed adopted in states where they might do the most good in reducing inequality.

Income Inequality in States with Predatory Lending Laws

To examine a possible link between income inequality and predatory lending in the United States, an individual-level income inequality measure, a Gini index, is calculated separately for each state and year for the past 10 years.

The Gini index is one of the most widely used measures of income inequality. The Gini index would be zero in an economy in which everyone has the same income; the index would be 100 percent in an economy where one person has all the income and everybody else has zero income. The average income inequality across the U.S. states was about 50 percent in the year 2000.6

In the figure, the solid line shows that average inequality has been increasing over the past decade, with a peak during the recession in the early part of the 2000s.7 Comparing income inequality for the group of 24 states plus the District of Columbia that adopted predatory lending laws with the group of 26 states that did not, an interesting finding emerges: The states that adopted predatory lending laws experienced a higher degree of income inequality over the past 10 years, while the states that did not adopt predatory lending laws averaged lower income inequality over the past decade.

One conclusion that could be drawn from this finding is that the states which adopted predatory lending laws needed to do so to decrease the level of income inequality more than the states that did not adopt these laws.

Because states adopted these laws in different years, it is hard to tell whether higher inequality is associated with the higher need and probability of passing predatory lending laws. That relationship can be examined using a statistical model that estimates the probability of an event occurring, taking into account data from the past. Based on the estimated results, it appears that higher income inequality is associated with a higher probability of a predatory lending law being adopted.8

The model estimates that at the average value of income inequality and at the average values of all control factors over the past 10 years, the probability of a predatory lending law being adopted in each state is 47 percent. Also, holding other factors constant, in a given state, a 10 percent increase in inequality in a current period is associated with an 8 percent greater chance of having a predatory lending law adopted during the next period.

It is too early to formally test for any actual real effects that predatory lending laws have on states’ economies and, in particular, whether these laws are really fighting income inequality. Future studies are needed to address this issue. In addition, more studies are needed to test whether there are factors that influence both predatory lending (and the probability a predatory lending law will be adopted) and income inequality at the same time.

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Endnotes

  1. See www.hud.gov for more examples of predatory lending activities. [back to text]
  2. The U.S. Census Bureau publishes different historical income inequality measures at www.census.gov/hhes/income/histinc/ie6.html. [back to text]
  3. See Kennedy et al. (1996) and Kaplan et al. (1996). [back to text]
  4. For a list of references, see www.economist.com/inequality. [back to text]
  5. See Beck et al. (2004). [back to text]
  6. Author’s calculations based on the data from the Current Population Survey. [back to text]
  7. This finding is consistent with the results of a growing body of economic research that shows there is a negative relationship between inequality and economic growth, i.e., inequality almost always rises in recessions. See Alesina and Rodrik (1994), Aghion et al. (1999) and Adams (2003), among others. [back to text]
  8. The model also takes into account several control factors: long-lasting differences that may exist between the states, such as size or geographical location, time trend, prevalence of individuals with lower income and prevalence of minorities in each state. [back to text]

References

Adams, Richard H. Jr. “Economic Growth, Inequality, and Poverty: Findings from a New Data Set.” The World Bank, Policy Research Working Paper 2972, 2003.

Aghion, Philippe; Caroli, Eve; Garcia-Penalosa, Cecilia. “Inequality and Economic Growth: The Perspective of the New Growth Theories.” Journal of Economic Literature, 1999, Vol. 37, No. 4. pp. 1615-60.

Alesina, Alberto; and Rodrik, Dani. “Distributive Politics and Economic Growth.” Quarterly Journal of Economics, 1994, Vol. 109, No 2, pp. 465-90.

Beck, Thorsten; Demirguc-Kunt, Asli; and Levine, Ross. “Finance, Inequality and Poverty: Cross-Country Evidence,” NBER Working Paper No. 10979, Issue December 2004.

Ho, Giang; and Pennington-Cross, Anthony. “States Fight Predatory Lending in Different Ways,” Federal Reserve Bank of St. Louis The Regional Economist, January 2006, pp. 12-13.

Kaplan, George, A.; Pamuk, Elsie R.; Lynch, John W.; Cohen, Richard D.; and Balfour, Jennifer L. “Inequality in Income and Mortality in the United States: Analysis of Mortality and Potential Pathways,” British Medical Journal, April 1996, Vol. 312, pp. 999-1003.

Kennedy, Bruce P.; Kawachi, Ichiro; and Prothrow-Stith, Deborah. “Income Distribution and Mortality: Cross Sectional Ecological Study of the Robin Hood Index in the United States,” British Medical Journal, April 1996, Vol. 312, pp. 1004-07.

The Economist, June 15, 2006.

 

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