Will Poor Countries Catch Up?

"Relative Income Traps." Maria A. Arias and Yi Wen, Federal Reserve Bank of St. Louis Review, vol. 98, no. 1, First Quarter 2016.

Absolute poverty has declined dramatically around the world over the past quarter-century. For some observers, this trend validates neoclassical convergence theory, which posits that capital flows and technology spillover to low- and middle-income nations will cause their income levels to catch up to those of developed nations. In absolute terms, it is true that many developing economies have been consistently experiencing income growth. Thus, it would seem they are escaping low- and middle-income levels and converging to American living standards.

Or are they? Most of the literature has focused on absolute notions of convergence, but a recent paper by two St. Louis Fed economists redefines this concept in relative terms. They find that most developing countries have not seen their income levels, as measured by real per capita GDP, increase as a percentage of U.S. levels. The researchers conclude that, excluding the Asian Tigers, the probability of developing countries remaining behind the United States is close to 100 percent in the long run.

The researchers believe prevailing explanations, which emphasize the importance of institutions and barriers to technology diffusion, inadequately account for this apparent contradiction to convergence theory. Instead, they argue that developing countries should follow the Asian Tigers’ example by enacting policies that increase domestic market size in order to support industry.

"Changes in Labor Participation and Household Income." Robert Hall and Nicolas Petrosky-Nadeau, Federal Reserve Bank of San Francisco Economic Letter No. 2016-02, Feb. 1, 2016.

A notable economic trend so far this century has been the decline in the U.S. labor force participation rate (LFPR) for all individuals over age 16, which had an unusually steep drop from 67.2 percent to 62.4 percent between 2004 and 2013. Economists propose various explanations such as an aging population and a changing welfare system.

In a recent San Francisco Economic Letter, economists Robert Hall and Nicolas Petrosky-Nadeau propose an additional factor — "the changing relationship between household income and the decision to participate in the labor force." Using data from the Census Bureau's Survey of Income and Program Participation (SIPP), they develop a probability model to analyze changes over time in the likelihood that an individual with certain demographic characteristics will participate in the labor market.

As might be expected, their model shows a much lower LFPR for low-income households than for high-income ones. Surprisingly, however, the researchers find that the recent drop in the LFPR among prime working-age individuals (aged 25 to 54) has been led by higher-income households; households in the poorest income quartile "added 0.7 percentage point to the total participation rate between 2004 and 2013," whereas households in the highest and second-highest income quartiles subtracted 1.6 and 2.1 percentage points, respectively. Likewise, high-income households have led the drastic 9.6 percentage point drop in the LFPR among workers aged 16 to 24.

Also, SIPP data seem to contradict arguments that an aging population largely explains this decline. Workers 55 and older saw a 3.1 percentage point increase in their LFPR between 2004 and 2013.

"The Limited Macroeconomic Effects of Unemployment Benefit Extensions." Gabriel Chodorow-Reich and Loukas Karabarbounis, Federal Reserve Bank of Minneapolis Working Paper No. 733, April 2016.

In 2008, Congress authorized emergency unemployment compensation in response to high unemployment rates. Combined with state-level extended benefits, the measure caused the duration of unemployment insurance (UI) benefits to increase from 26 weeks to an unprecedented 99 weeks in some states. Many opponents of these extensions predicted that they would delay economic recovery by effectively subsidizing unemployment; others argued that such benefits would help the unemployed maintain their previous consumption levels, thus accelerating economic recovery by increasing total consumer spending.

A recent working paper by two researchers from the Minneapolis Fed attempts to determine the macroeconomic effects of these UI extensions. Most states normally offer 26 weeks of UI as regular benefits and provide extended benefits based on state unemployment rates. Because unemployment rates are measured in real time for these purposes, they are prone to measurement errors. The researchers exploit these measurement errors to isolate the effects of benefit extensions.

Overall, they find results "inconsistent with either large negative or positive effects of benefit extensions on macroeconomic aggregates including unemployment," concluding that UI extensions "increased the unemployment rate by at most 0.3 percentage point" during the Great Recession. These conclusions are consistent with previous literature. (See "Expanding Unemployment Insurance," Econ Focus, Second Quarter 2014.)