Poverty in America finds that a rising tide does not raise all ships. Although real GDP continues to rise, the US poverty rate has remained relatively constant, signaling a growing discord between poverty and the macro-economy. In spite of this drift, data from CPS (Current Population Survey) indicates that changes in labor market opportunities and family structure effectively forecasts changes in the poverty rate but that immigration and anti-poverty government programs (both previously reasoned to be integral factories) seem to have little effect in the rate.
Although poverty lacks a simple root and most likely a simple corrective measure, painting a picture of trends in poverty is straightforward. The poverty level, defined roughly as $10,000 for an individual and $19,000 for a family of four in today’s dollars, dropped from 22.4% in 1959 to 12.1% in 1969, but has vacillated between 13.8% in the 1980s to 12.5% in 2003 since then. The elderly group has effectively reduced their poverty from 35.8% in 1959 to roughly 10% today, and this change is likely due to the expansion of social security. The modal person living in poverty is a non-Hispanic white living in a married couple family or in a childless family; however, being non-white and coming from a single parent increases the likelihood of poverty by 300% and 600%, respectively. Women are slightly more likely to live below the poverty line (13.9% for women versus 11.7% for men). Also, children and the uneducated are more likely to live in poverty. The one difficulty in portraying poverty is in its definition. Government benefits (food stamps, welfare etc.) which are currently excluded from it should be added to the equation to better reflect wealth, but these changes are irrelevant since past data which uses the same definition is being compared.
The effects of the variables:
With this method, changes in the labor market effectively diagnose trends in poverty. However, the authors believe that its impact, while important, is not as critical as changes in family structure. First, a one percent increase in unemployment historically has increased poverty by between 0.4%-0.7%. Also, a 10% increase in wage inequality (the ratio of wages in the 20th and 50th percentiles) raises poverty by around 2.5%. The researchers believe that a “virtually continuous increase in wage inequality below the median is an important explanation for the upward drift in poverty rates.” Rise of the median wage by 10% drops poverty around 2%. Since growth in wage inequality and stagnation in median income accompanied growth in real GNP for essentially the first time in the 1980s, current economic thought posits that economic growth lost its bite in reducing poverty. This research expands this idea with statistical support.
The researchers conclude that the demographic trend with the greatest impact on poverty is changes in the family structure. They show that erosion of the nuclear family for an economic perspective has raised poverty by 4%, especially among children. One reason why the break-up of the family inflates poverty is that single mothers often do not receive the indicated support from the ex-husbands. The positive impact of more females entering the workforce and providing financial support for their family in the last forty years has been negated by this increase in female headship. Households headed by females are in fact 3 to 4 times more likely to be below the poverty level. Examining only changes in the family structure, the researchers conclude that poverty levels would have risen from 13% in 1967 to 17% in 2003. The benefits of having women enter the workforce have been negated by a rise in female headship for people near the poverty level.
Hoynes, Page, and Stevens effectively disprove the myth that increases in immigration are a core root for poverty. Despite a two-fold increase in immigrants in the past 25 years and the fact that on average these immigrants are less educated and less skilled than natives, their relatively small proportion of the overall population mitigates any strong negative impact on poverty. They calculate that immigrants are more likely to be poor (17.4% versus 12.4%) but that their inclusion in national data only means a few tenths of a percentage point increase in poverty. However, the impact may be understated with a simple comparison of data with and without their presence because their presence may over-saturate the market for low-wage labor which depresses wages and augments unemployment. The researchers also find that changes to anti-poverty programs have little effect on poverty rate. Changes in generosity do not seem to matter.
I thought the authors made a thorough argument considering the complexity of the issue. Poverty clearly has many causes. I liked the manner in which they broke down these causes and dispelled myths like the one about immigrants raising the poverty level. I thought they did a better job diagnosing different parts of poverty than explaining why. Of course no one has figured that out yet. One explanation I can think of for the expanding gap between poverty levels and GDP per person is not that they have actually diverged but sampling has improved. Poorer people are generally less accessible than wealthy people. If sampling improves, more poor people will be measured. Overall, I liked the article.