4 posts from November 2011

And now for something completely different (and positive?) on employment

You have to look long and hard to find positive employment news these days. But there appears to be some good news lurking outside the spotlight of the traditional job market you typically hear about in regular government reports.

Much of the state and national information on employment comes from the Quarterly Census of Wage and Employment (QCEW), a state-administered survey whose information is then passed up the ladder to the federal Bureau of Labor Statistics. The QCEW counts employment in sort of a round-about fashion: Companies with at least one paid employee must register with their home state’s unemployment insurance (UI) system and then regularly report their company’s employment levels, and these reports are the basis of the QCEW.

While the large majority of workers are covered by the UI umbrella, there is nonetheless a hole in the employment doughnut because workers in some occupations or industries are exempt from UI. There are no official government counts of this so-called noncovered worker population, and it’s a hard group to measure.

For starters, states have different exemptions to UI. There are more than 30 UI exemptions in Minnesota alone, for example, including (among others) self-employed workers, some farms, insurance and real estate salespeople who work on commission, most religious personnel and all elected public officials. Some of these categories, like the self-employed, are particularly difficult to measure (and is the focus of the cover article in the January fedgazette.)

Private firms have begun to reverse-calculate these figures through a complicated process that uses employment and income data from the likes of the Bureau of Economic Analysis, which goes to great lengths to identify income-producing jobs. Estimates are then developed for jobs not typically covered by UI.

Economic Modeling Specialists, Inc., for example, is an economics and labor market consulting firm in Moscow, Idaho. It shared its estimates on noncovered workers with the fedgazette, as well as its methodology, “quite a bit (of which) is based on the BEA's much-appreciated work in this area,” said Jared Miller, an EMSI data analyst.

Unlike the population of covered workers, which has taken a big and well-publicized drop during the recession, EMSI’s data show steady, if modest, growth among noncovered workers in every district state, as well as the nation as a whole (see chart).

 Noncovered Chart 1 -- 11-29-11

There are also a couple of important caveats to acknowledge that might well take some of the shine off this seemingly good news. For starters, the noncovered population is a count of jobs, not employed individuals, which means there are multiple plausible interpretations for job trends. From an optimistic standpoint, a growing number of noncovered jobs might mean there are more employed individuals in this gray area of employment. However, a growing number of noncovered jobs might also be indicative of growing part-time jobs and outsourced labor in the form of independent labor contracts. Were this the case, total noncovered workers could well be stagnant or even falling as they take on more of these jobs to make ends meet.

Secondly, noncovered job counts cannot distinguish employment duration; in many cases, someone self-employed for a single month would count the same as a year-long job, whereas QCEW is more precise, reporting monthly job counts as well as quarterly and annual averages.

A deer stuck in your headlights

It’s that time of year again when attention for a significant portion of the population turns to whitetail deer. Most often it’s toward hunting season and dreams of hat racks. But a not-so-small number get an unfortunately close encounter with deer this time of year—with their vehicle.

With high deer populations and significant rural roadway—both a factor in collisions—every Ninth District state ranks in the top 10 in likelihood of hitting a deer over the course of a year, according to estimates from State Farm Mutual Insurance. South Dakota ranks highest in the district at number three (see table below).

Deer crashes -- Table 1 - 11-14-11

Few states closely track the number of vehicle-deer collisions. Wisconsin appears to keep better records than most. The good news is that deer collisions, at least in that state, are trending lower over the past decade in absolute numbers (see Chart 1), and the rate of collisions per vehicle mile has fallen considerably, from about 50 per 100 million miles in 1994 to fewer than 30 in 2010, according to a study by the state’s Department of Transportation. The number of persons killed or injured has also been cut in half, to about 400, over the past decade.

Still, the costs of deer collisions are considerable. In Wisconsin, collisions cost a total of almost $27 million in 2008, according to the Deer-Vehicle Crash Information Clearinghouse at the University of Minnesota. These figures are likely conservative, because the DVCIC included only investigated crashes involving at least $1,000 in property damage (about 15,000 in 2008 for Wisconsin), which are considerably below estimates in that state of both the number of deer killed by vehicles (the blunt force of which is likely to cause considerable damage to a vehicle) as well as insurance estimates of annual deer crashes.

And while you’re out driving, it might pay to know that the majority of deer-vehicle collisions occur during the months of October and November (see Chart 2) when deer are most active during the breeding phase, according to the Wisconsin DOT.

Deer -- chart 1&2 11-14-11

Municipal debt in district bubbling up

During the recession and slow recovery, high consumer and other debt has come under scrutiny for spurring the recession and blockading a quick recovery. Federal and even state government debt has also come under scrutiny. But local debt levels are not widely known, especially on a macro basis.

A debt-spin around the largest cities in the Ninth District shows that municipal debt varies considerably on a per capita basis. Total bonded debt was collected for the five largest cities in each of the four states entirely in the Ninth District, plus three cities combined for Wisconsin and the Upper Peninsula of Michigan (see chart).

West Fargo, N.D., has the largest amount of bond debt at nearly $5,000 per capita. In contrast, Billings, Mont., has just $203 of bond debt per capita. Similarly, average per capita debt among the state’s five largest cities was highest in North Dakota ($2,639) and lowest in Montana ($555), with Minnesota ($2,250) and South Dakota ($1,466) in the middle.

The form and proportion of that debt also differs among cities, but is largely predicted by a city’s home state. Cities typically borrow by issuing either general obligation (GO) or revenue bonds. GO bonds are repaid through general tax revenue, backed by the full faith of the issuer (a city, in this case) that local taxes can and will be increased if necessary. Revenue bonds, on the other hand, are repaid by revenue derived from the project being financed by a bond issue (a public parking ramp, for example).

Cities use these two tools to varying degrees. For example, a high percentage of municipal debt for Minnesota and Wisconsin cities is general obligation debt. Minneapolis has nearly 88 percent of its debt funded through GO bonds. The opposite is true of cities in the Dakotas. Only 7 percent of total debt among North Dakota’s five largest cities is GO debt. South Dakota cities use revenue bonds exclusively because state statutes preclude cities there from issuing a lot of general obligation debt.

Muni debt -- 11-1-11

Community orgs report struggles among low and moderate income

The current state of the economy is a daily topic of discussion on the news and at dinner tables across the country. Of particular importance to Community Development offices within the Federal Reserve System is the economic state of low- to moderate-income (LMI) communities.

Existing government data provide some insight into how these communities are faring. However, many of the factors that play an important role in their economic health, such as job training opportunities, the availability of affordable rental housing or business owners’ ability to access credit, are not measured well through existing data sources.

To provide a more comprehensive read on LMI community conditions in the Ninth District, the Minneapolis Fed’s Community Development department has launched Community Insight, a semi-annual survey of community development and service organizations that serve LMI communities. The survey is designed to capture their perspectives on changes in local employment, housing, consumer finance and business conditions.

According to the survey, most Ninth District LMI communities experienced deteriorated economic conditions in the second quarter of this year compared to 12 months prior. The most pervasive signs of economic stress among LMI communities were increased demand for financial counseling, decreased availability of affordable rental housing and reduced access to credit for business owners (see Charts 1-3 below).

Survey responses also revealed some positive signs, including increased homeownership opportunities for LMI buyers with good credit and an increase in the number of micro-businesses.

The baseline survey conducted during the months of May and June 2011 contains responses from 335 organizations representing more than 180 cities and townships across the Ninth District. For more on the survey and its findings, view the full Community Insight report.

Community Insight charts -- 10-27-11