Federal Reserve Economic Data

A nation’s employment-to-population ratio can provide an indicator of the health of its labor markets—specifically, how much of the workforce participates in the formal economy. The map shows worldwide employment-to-population ratios in 2016, where lighter-colored countries have higher employment ratios. The data reflect the proportion of the working age population in various countries employed during the reference period. However, the World Bank advises that nations vary in their definitions of working age, whether they include armed services personnel and the institutionalized in their counts, and how women view their employment status based on cultural norms. The United Nations reports that, globally, women’s involvement in the labor force is only 50%, whereas men’s is 77%; yet, women work longer hours when unpaid work is accounted for—which it is not in employment-to-population ratio data. Given all of these complexities, comparisons of employment ratios between nations have their limitations.

Overall, the nations with the highest ratios of employed individuals to the overall population tend to be smaller, such as those in Southeast Asia and Central Africa, with many reporting ratios over 70%. Nations surrounding the Mediterranean Sea have some of the lowest employment ratios, most below or near 40%. While purely economic factors may explain some of the discrepancies, a look at other employment-related indicators may shed some light on the factors at play.

Indeed, nations with high employment ratios also have some of the highest female labor force participation rates (as a percentage of the total female population), according to the World Bank. For example, in Uganda, where the employment-to-population ratio stood at 83.05% in 2016, the third highest worldwide, the female labor force participation rate was 82.33%, the 5th highest worldwide. The reverse also appears to be true: Many nations with low ratios, especially in North Africa and the Middle East, have far lower labor force participation rates for females than the rest of the world.

Comparisons of the GeoFRED and World Bank maps illuminate a clear correlation, which can be analyzed using a linear regression. For all nations with 2016 data on both the employment ratio and the female labor force participation rate, the correlation coefficient between the two variables is 0.82, meaning if one is high in a country, the other is very likely to be high as well. While the relationship may seem obvious, it has important implications for developing economies seeking to increase their overall employment ratio.

How these maps were 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 Maria Hyrc.

A well-known fact in the ordinary business of life is that the value of money doesn’t stay the same: The amount of goods and services you can buy with $100 today is far less than what you could buy 30 years ago. A somewhat similar comparison can be made about the purchasing power of $100 in different places. The amount of goods and services you can buy in a developed country, such as the United States, is far less than what you can buy in a developing country, such as India. Here, we analyze this latter phenomenon but within the United States.

Regional price parities (RPPs) measure the differences in the price levels of goods and services across states and metropolitan areas for a given year. RPPs are expressed as a percentage of the overall national price level for each year, so RPPs higher than 100 represent state prices higher than the national average and vice versa. The map shows the price parities in 2015 for each U.S. state. In general, price levels are lower in the middle section of the country and get higher on the east and west coasts.

In 2015, Hawaii’s RPP (118.8) was higher than that of any state. The other locations with the highest RPPs were District of Columbia (117.0), New York (115.3), California (113.4), and New Jersey (113.4). Kentucky (88.6), South Dakota (88.2), Arkansas (87.4), Alabama (86.8), and Mississippi (86.2) had the lowest RPPs among the states. States with RPPs closest to the national average price level were Vermont (101.6), Delaware (100.4), Illinois (99.7), Florida (99.5), and Oregon (99.2).

RPPs are important because they help inform the purchasing power behind a person’s income in different areas of the country. For example, an income of $47,520 in Hawaii has the equivalent purchasing power of an income of $36,480 in Mississippi because both of these incomes divided by the state’s RPP equal $40,000.

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 Maximiliano Dvorkin and Hannah Shell.