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[Lauro Pericles]

Ourrecent staff research finds that new technology risks widening the gap between rich and poor countries by shifting more investment to advanced economies where automation is already established. This could in turn have negative consequences for jobs in developing countries by threatening to replace rather than complement their growing labor force, which has traditionally provided an advantage to less developed economies. To prevent this growing divergence, policymakers in developing economies will need to take actions to raise productivity and improve skills among workers.

Share-in-production: Advanced economies have higher wages because total factor productivity is higher. These higher wages induce firms in advanced economies to use robots more intensively to begin with, especially when robots easily substitute for workers. Then, when robot productivity rises, the advanced economy will benefit more in the long run. This divergence grows larger, the more robots substitute for workers.

Terms-of-trade: A developing economy will likely specialize in sectors that rely more on unskilled labor, which it has more of compared to an advanced economy. Assuming robots replace unskilled labor but complement skilled workers, a permanent decline in the terms of trade in the developing region may emerge after the robot revolution. This is because robots will disproportionately displace unskilled workers, reducing their relative wages and lowering the price of the good that uses unskilled labor more intensively. The drop in relative price of its main output, in turn, acts as a further negative shock, reducing the incentive to invest and potentially leading to a fall not just in relative but in absolute GDP.

Our results critically depend on whether robots indeed substitute for workers. While it may be too early to predict the extent of this substitution in the future, we find suggestive evidence that this is the case. In particular, we find that higher wages coincide with significantly higher use of robots, consistent with the idea that firms substitute away from workers and towards robots in response to higher labor costs.

Improvements in the productivity of robots drive divergence between advanced and developing countries if robots substitute easily for workers. In addition, those improvements will tend to increase incomes but also increase income inequality, at least during the transition and possibly in the long run for some groups of workers, in both advanced and developing economies.

Our findings also underscore the importance of human capital accumulation to prevent divergence and point to potentially different growth dynamics among developing economies with different skill levels. The landscape is likely going to be much more challenging for developing countries which have hoped for high dividends from a much-anticipated demographic transition. The growing youth population in developing countries was hailed by policymakers as possibly a big chance to benefit from a transition of jobs from China as a result of its graduating middle-income status. Our findings show that robots may steal these jobs. Policymakers should act to mitigate those risks. Especially in the face of these new technologically-driven pressures, a drastic shift to rapidly improve productivity gains and invest in education and skills development will capitalize on the much-anticipated demographic transition.

IMFBlog is a forum for the views of the International Monetary Fund (IMF) staff and officials on pressing economic and policy issues of the day.The IMF, based in Washington D.C., is an organization of 190 countries, working to foster global monetary cooperation and financial stability around the world.The views expressed are those of the author(s) and do not necessarily represent the views of the IMF and its Executive Board. Read More

But according to research from the nonpartisan Public Policy Institute of California, income inequality in the Bay Area has worsened only marginally, at least when compared to other parts of the state. In 2007, Bay Area households at the top 10 percent of incomes made about 10.6 times what Bay Area households at the bottom 10 percent of incomes brought home. By 2014, they made about 11.6 times as much.

So much for the growth in the gap; what about the size of the gap itself? Income inequality within California may not look like what you would expect. Regions such as Orange County and the Bay Area, despite their notable concentrations of wealth, are some of the more equal in the state. By far the most unequal California region is the Central Valley, where high-income households make 14 times as much as poor households.

There are other important lessons to draw from how income inequality varies throughout the state, and how the pattern has changed since the Great Recession. Part of the reason why regions such as the Bay Area and Orange County stack up favorably is because recent changes in income inequality have more to do with the deteriorating incomes of the poor than the growing fortunes of the rich.

Those California regions with the biggest chasm between rich and poor typically have some of the poorest populations in the state. In the Central Valley for example, households in the bottom 10 percent of the income distribution made less than $10,000 per year (adjusted for a family of four). Their equivalents in the Bay Area made more than double that.

Focusing on very rich households will yield different results than focusing on even slightly less rich households. Research from the Brookings Institute that compares higher-income households (those at the top 5 percent) to those at the bottom 20 percent makes the Bay Area appear much more unequal, with the greater San Francisco metro area the third most unequal region in the country.

Matt Levin was the data and housing dude for CalMatters. His work entails distilling complex policy topics into easily digestible charts and graphs, finding and writing original stories from data, yelling...More by Matt Levin

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Poverty in the U.S. is often associated with deprivation, in areas including housing, employment, and education. Now a study co-authored by two MIT researchers has shown, in unprecedented geographic detail, another stark reality: Poor people live shorter lives, too.

More precisely, the study shows that in the U.S., the richest 1 percent of men lives 14.6 years longer on average than the poorest 1 percent of men, while among women in those wealth percentiles, the difference is 10.1 years on average.

This eye-opening gap is also growing rapidly: Over roughly the last 15 years, life expectancy increased by 2.34 years for men and 2.91 years for women who are among the top 5 percent of income earners in America, but by just 0.32 and 0.04 years for men and women in the bottom 5 percent of the income tables.

In addition to reporting the size and growth of the income gap, the study finds that the average lifespan varies considerably by region in the U.S. (by as much as 4.5 years), but that the sources of that regional variation are subtle, and, like the aggregate national gap, subject to further investigation.

The researchers looked at 1.4 billion anonymized income tax filings from the federal government, and combined that with mortality data from the years 2001 through 2014 from the Social Security Administration. This represents the most complete geographic and demographic landscape of mortality in America.

A new puzzle emerging from the study, the authors note, is that differences in lifespan exist along the entire continuum of wealth in the U.S.; it is not as if, say, the top 10 percent of earners cluster around identical average lifespans.

And then there are the new geographic patterns in the findings. For instance: Eight of the 10 states with the lowest life expectancies for people in the bottom income quartile form a contiguous belt, curving around from Michigan through Ohio, Indiana, Kentucky, Tennessee, Arkansas, Oklahoma, and Kansas.

The researchers say that more analysis on the sources of local variation in lifespans could be among the most fruitful research areas stemming from the current paper. The research team is releasing all the data from the study today as well.

Among the municipalities where low-income people have experienced the greatest increases in lifespan from 2001-2014, for example, are Toms River, New Jersey; Birmingham, Alabama; and Richmond, Virginia. Cities with the largest drops in lifespan among the poor are Tampa and Pensacola, Florida; and Knoxville, Tennessee.

Places with the overall longest lifespans for the poor include New York City, with a chart-topping 81.8 years on average, as well as a passel of cities in California. The bottom of that list includes Gary, Indiana (77.4 years on average); Las Vegas; and Oklahoma City.

The research was supported by a grant from the U.S. Social Security Administration to the National Bureau of Economic Research; the National Institutes of Health; the Social Sciences and Humanities Research Council of Canada; the Smith Richardson Foundation; and the Laura and John Arnold Foundation.

Fifty years of research has revealed the sad truth that the children of lower-income, less-educated parents typically enter school with poorer language skills than their more privileged counterparts. By some measures, 5-year-old children of lower socioeconomic status score more than two years behind on standardized language development tests by the time they enter school.

Stanford researchers have now found that these socioeconomic status (SES) differences begin to emerge much earlier in life: By 18 months of age, toddlers from disadvantaged families are already several months behind more advantaged children in language proficiency.

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