Federal Reserve Economic Data

If the map above looks familiar, either you’re experiencing déjà vu or you read our post last year about regional price parities (RPPs), which measure cost of living in metropolitan areas. Cost of living is generally persistent over time, which is why our updated map of the 2016 RPPs looks eerily similar to last year’s map. (The data are released on a two-year lag, by the way.) A reminder: The national average cost of living is set equal to 100. So, an RPP above 100 means an area is more expensive than the national average and an RPP below 100 means it’s less expensive than the national average. Of the 349 metro areas in the data, 94 fall within 5 percent of the national average.

As we showed last year, high cost of living remains concentrated in the Northeast and on the West Coast. As of 2016, San Jose, CA, takes the title of most-expensive metro area, with a cost of living 27 percent above the national average. The Midwest and South are still the least-costly places to live. In the cheapest metro area, Morristown, TN, the cost of living is more than 20 percent below the national average.

And why are some metro areas more expensive than others? Housing. The single largest consumer expenditure category is housing, and that drives most differences in cost of living (source). The map below shows the RPPs for rents, which range from nearly 50 percent below the national average to over 200 percent above. Because households spend about 20 percent of income on housing, high rent prices beget high cost of living overall. It’s no coincidence that San Jose also has the highest rent RPP.

In contrast, the goods RPPs on the next map show much less regional variation. Unlike housing, goods are more easily tradeable, so arbitrage tends to suppress regional price differences. For example, if a laptop in San Jose costs more than the same laptop in Morristown, a consumer in San Jose may just buy the cheap laptop online from Morristown and have it shipped. To compete with its rivals in Morristown, retailers in San Jose would have to cut prices. Consequently, goods prices are much more uniform nationwide: All metro areas fall within 15 percent of the national average.

The regional variation in goods prices that does exist likely results from goods that are more difficult to buy online, like fresh foods. For these items, businesses in areas with higher rent costs may charge higher prices to consumers to compensate, while businesses in areas with lower rent costs may charge lower prices. That said, some economists have found that most variation in food prices may be due to measurement error (source).

How these maps were created:The original post referenced interactive maps from our now discontinued GeoFRED site. The revised post provides replacement maps 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 Charles Gascon and Andrew Spewak.

Populations can replace themselves by having children (fertility) and through immigration. Here, we focus on fertility. A general rule is that women must have an average of 2.1 children to maintain the population, with the extra 0.1 owing to the fact that some children will not reach the age of procreation.

This GeoFRED map of the world shows how each country stands with respect to replacing itself. The color white indicates the country is below its replacement rate, light blue indicates pretty much the minimum replacement rate, and the darkening greens move up the fertility scale from there.

It’s not news that many Western industrialized nations have low fertility, which they compensate for with immigration. Poorer countries, as expected, have higher fertility. But there are a few cases that aren’t so well known. For example, some South American countries have low fertility, as does Thailand. Iran is a low-fertility country in between two high-fertility countries, Iraq and Afghanistan. These latter two countries tend to have net emigration, which is not surprising given the waves of conflict there, and thus their populations don’t increase as fast as their fertility would otherwise indicate. And then there’s Eastern Europe: very low fertility and net emigration, leading to substantial population loss.

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.