Federal Reserve Economic Data

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Native Americans in the U.S.

A look at county-level Native American population data

FRED has added a great deal of county-level data recently, including population estimates, which include various race and ethnicity categories. These new data are especially well-suited for viewing on a map. So, of course, we look to GeoFRED: The map above shows non-Hispanic Native Americans. Note that the color scheme relates to the total number of Native Americans in each county, not in proportion to the county’s overall population.

Clearly, large numbers of Native Americans live in the West, especially the Southwest, and in Oklahoma—for obvious historical reasons that involve displacement of Native peoples. There are also quite a few counties where hardly any Native Americans live: For example, there are none in the Kansas counties of Comanche and Cheyenne. On the other side of the range, the Arizona counties of Navajo and Apache are in the top five most-populated. Unfortunately, we have no data for Oglala Lakota County in South Dakota.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

Globalization affects India, too

A look at trade openness and the labor income share in India

A previous post discussed the recent decrease in the labor share and increase in the capital share in GDP for many nations. Reasons for this decline in payments to labor include capital-augmenting technology growth, globalization, and changing skill composition of the labor force. In this post, we focus solely on India’s story.

In the 1990s, India began to implement a series of economic reforms that, among other things, helped open up the economy to trade and foreign investment. These policy changes reduced import tariffs and regulations, with the aim of making the economy more market-oriented. As a result, the labor share of India’s income decreased significantly.

The graph above shows that India’s trade openness, measured as the ratio of the sum of India’s exports and imports to India’s GDP, increased by nearly 124% between 1980 and 2017. (In comparison, U.S. trade openness increased by only 19% over the same period.) India’s labor share of income fell by 30%, with a 24% fall from 1990 to 2017.

So, how are trade openness and labor shares related? Trade openness often goes hand-in-hand with reforms that allow greater international mobility of capital but not labor. If higher wages would lead capital to relocate abroad, domestic labor’s bargaining power and wage increases may be limited. Also, domestic firms may face greater foreign competition and respond accordingly. If they increase the use of labor-saving technologies, that can dampen domestic wages.

Is this bad news for India’s workers? Not necessarily. All the graph shows is that trade openness and the labor share in India have been negatively correlated. This analysis doesn’t suggest labor is worse off. A declining labor share simply means that labor income growth is slower than GDP growth; it does not mean that labor income has declined. Finally, the graph doesn’t capture the effects of the tax and transfer policies of the Indian government. If trade openness increases GDP growth, it also increases tax revenues at given tax rates; this can be good for labor if they benefit more from the government’s tax and expenditure policies.

How this graph was created: Search for the series “Goods, Value of Exports for India” (FRED series ID VALEXPINM052N) and change the frequency to “Annual” with the aggregation method as “Sum.” Use the “Customize data” search bar to search for and add “Good, Value of Imports for India” (VALIMPINM052N) and “Gross Domestic Product for India, current U.S. Dollars” (MKTGDPINA646NWDB). In the formula bar, enter (a+b)/c. Then add a second line to the graph: “Share of Labor Compensation in GDP at Current National Prices for India” (LABSHPINA156NRUG). Finally, change the start date of the graph to 1980-01-01. 

Suggested by Subhayu Bandyopadhyay and Asha Bharadwaj.

View on FRED, series used in this post: LABSHPINA156NRUG, MKTGDPINA646NWDB, VALEXPINM052N, VALIMPINM052N

A New Year’s resolution: More homemade food

Food prices for dining out vs. staying home

Here at the FRED Blog we’re continuously looking for self-improvement opportunities, and our New Year’s resolution is to focus on home-cooked foods. Food at home is often fresher and healthier, but it’s also less expensive: The graph above shows that the cost of food away from home has been increasing much faster than the average of all foods. We’ll try to pepper the FRED Blog with healthier and tastier posts all through the year.

How this graph was created: Search for “CPI food,” check the two series, and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CPIFABSL, CUSR0000SEFV


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