Federal Reserve Economic Data

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Newspapers are still more important than cheese

Relative importance weights of the components of industrial production: Part 1

Many sectors of the economy, with their specific products and processes, contribute to the nation’s overall industrial production. The Board of Governors of the Federal Reserve System provides data on these components in their G.17 Industrial Production and Capacity Utilization release. As they state, these values are “estimates of the industries’ relative contributions to overall growth.” The graph above covers four specific components on the smaller end of the scale: newspaper publishing, cheese, tobacco, and fruit and vegetable processing. (FRED offers 322 series in this category.) Again, to be clear, these data measure the raw volume of goods that contribute to industrial production—not to health, wealth, or quality of life.

Over the past 45 years, the contributions of these components have changed—drastically, in some cases. From the late 1970s through the late 1980s, for example, newspaper publishing enjoyed prominence at the top of this list. But its contribution to this index has never been lower than it is today. Tobacco’s contribution surged to the top in the early 1990s and again in the early 2000s and is now neck and neck with fruits and vegetables. Cheese continues its quiet but rock-steady course at the bottom of this list.

How this graph was created: Search for “Relative Importance Weights”: As noted above, you’ll find 322 series to choose from. Check the measures you want and click “Add to Graph.”

Suggested by George Fortier.

View on FRED, series used in this post: RIWG3114S, RIWG3122S, RIWG51111S, RIWN311513S

Don’t be surprised: Employment data get revised

BLS revisions to metro area employment data can be substantial but predictable

The Bureau of Labor Statistics (BLS) released the latest state and local employment data on March 13, 2017. The BLS initially estimated that St. Louis added 38,300 jobs in 2016, but the revised data show that St. Louis actually added 17,100 jobs. This isn’t the first time large revisions have occurred in St. Louis: Last year, BLS revisions to St. Louis employment added 6,800 jobs. Each March, these revisions account for data through the third quarter of the previous year. They can have a significant impact on the story of job growth in the region, so it’s important to be cautious about these preliminary estimates.

The top graph shows year-over-year growth in total nonfarm employment in the St. Louis MSA before and after the revision. Before the revision, St. Louis was estimated to have added 38,300 jobs and grown at 2.8% in 2016. St. Louis has not seen growth that strong since the 1990s. However, the BLS revised those numbers down to around 17,100 jobs added and growth of only 1.3%. While these revised numbers still show moderate growth, it is below the national rate of 1.6% and represents a significant decline from 2015’s 27,800 jobs added and 2.1% growth. Overall, the MSA has 16,600 fewer jobs than previously thought.

Data revisions occur because counting new jobs is a difficult process that relies on samples and advanced statistical techniques. As more information becomes available, data are revised. The BLS uses the monthly Current Employment Statistics (CES) survey to estimate local employment for nonagricultural industries, but the best source of local employment statistics comes from their Quarterly Census of Employment and Wages (QCEW). The QCEW includes data derived from establishments’ reports to the various unemployment insurance programs that are released with about a 6-month lag. Every March, the BLS reconciles the CES estimates with the data from the QCEW, which can result in significant revisions, as we’ve seen repeatedly here in St. Louis.

This year’s revisions underscore the importance of a cautious approach, despite the temptation to take unrevised data at face value: The BLS often revises employment data significantly, and the average absolute revision to 2016 metro area employment growth this year was 1.1 percentage points. The good news is that the revisions are generally predictable. The QCEW data had been growing at a much slower pace than the CES for much of the year for both nonfarm and leisure and hospitality employment. In addition, employment in St. Louis tends to follow the national cycle, so any large deviations in growth from the national rate should be corroborated with other sources of information. It can also be worthwhile to look at other sources such as the Fed’s Beige Book, to gain an understanding of the labor market beyond the latest BLS estimates. While the unrevised estimates were reporting strong growth in St. Louis, the Beige Book reported only modest or moderate growth for the region.

The BLS revised employment numbers in many of the MSAs in the Eighth District. In Memphis, the unrevised data reported employment gains of 2,700 and growth of 0.4% in 2016, but the revision brought those numbers up to 7,900 and 1.2%. In Louisville, jobs for 2016 increased from 4,400 to 5,400 and growth increased from 1.7% to 2.7%. In Little Rock, numbers were revised down only slightly, beginning in July 2015, with minimal effects on jobs added and growth in 2016.

How these graphs were created: The St. Louis Fed maintains records of all data revisions in its ALFRED® database, which allows you to retrieve vintage versions of data that were available on specific dates in history. On the “All Employees: Total Nonfarm in St. Louis, MO-IL (MSA)” page on FRED, click on “ALFRED Vintage Series” in the “Related Content” section underneath the chart to retrieve the two most recent releases, which currently include the revision. Under the “Edit Graph” button, click on “Format” and change the graph type from bar to line. Click on “Edit Lines” and select “Percent Change from Year Ago” for the units and copy to all. The three other graphs are built in a similar fashion.

Suggested by Charles Gascon and Paul Morris.

View on FRED, series used in this post: LOINA, LRSNA, MPHNA, STLNA

Regional income

In our previous blog post, we reported that inflation was higher in the New York City area than in the Cleveland area. Today, we look at their local incomes to see if the same conditions apply. The top graph shows personal income per capita for these areas. It’s not possible to get a perfect geographic match, but we use Cuyahoga County to represent the Cleveland consolidated metropolitan statistical area and a broader area around New York City (but without the western Connecticut towns used in the previous post). Without forgetting these mismatches, we see that overall income growth seems to be similar in both areas, except for the bubble in NYC just before the previous recession. So it doesn’t look like New Yorkers are compensated for their more-quickly-increasing living expenses.

The bottom graph reveals a similar exercise but with median household income, which is collected by county. Again, we use Cuyahoga County as a proxy for the Cleveland MSA. We use New York County to represent the NYC area.* The picture looks quite different, with Manhattan residents showing impressive income gains recently that probably aren’t matched in the wider New York metropolitan area.

*Admittedly, this is a restrictive choice; but piecing together data from the many surrounding counties is beyond the scope of this post. Readers are always encouraged to browse through FRED’s data aisles to find the best data to meet their needs.

How these graphs were created: Search for “personal income per capita Cleveland” and Cuyahoga County should be near the top. From the “Edit Graph” button, add a line searching for “personal income per capita New York.” For both lines, change units to “100 for selected date” using 1984-01-01 to match the data of the previous blog post. For the second graph, search for “median income Cleveland” then add the second line by searching for “median income New York county.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: MHINY36061A052NCEN, MHIOH39035A052NCEN, NEWY636PCPI, PCPI39035


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