Free Markets, Free People

Dale Franks

Dale Franks’ QandO posts

Observations: The QandO Podcast for 13 Mar 11

In this podcast, Bruce, Michael, and Dale discuss the Japanese earthquake and the implications for US nuclear policy, and Pres Obaba’s leadership style.

The direct link to the podcast can be found here.

Observations

As a reminder, if you are an iTunes user, don’t forget to subscribe to the QandO podcast, Observations, through iTunes. For those of you who don’t have iTunes, you can subscribe at Podcast Alley. And, of course, for you newsreader subscriber types, our podcast RSS Feed is here. For podcasts from 2005 to 2010, they can be accessed through the RSS Archive Feed.

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My book, Slackernomics, should be available for Kindle tomorrow

I’m happy to announce that sometime tomorrow my book, Slackernomics, will be available on Kindle at the Amazon store for the low, low price of $3. For those who don’t know, Slackernomics is a book on basic economics for people who think economics is boring. Instead of a bunch of charts and math, I present economics in a more enjoyable way.  For instance, here is a portion of my discussion on the role of prices:

Another feature of the price system is that it forces producers to put resources to their most valued uses. This is important because, quite often, consumers demand different goods that use many of the same components.

Let’s take petroleum, for example. People don’t just need gasoline; they need plastics to make computer keyboards and ugly furniture for college students. Businesses need chemicals for industrial production and dyes. Textile companies need artificial fabrics that don’t fade or discolor. Perverts need Vaseline.

So, in bidding for each of those items, their producers are also bidding for the petroleum required to make them. When more people buy Vaseline, Johnson & Johnson has to bid away some of that petroleum from refineries or textile mills. In turn, this increased demand in petroleum causes the price of oil to rise for everyone who uses it.

In order to keep buying oil, everyone now has to pay the price that Johnson & Johnson is willing to pay. As this raises consumer prices for these items, consumers are likely to buy less of them. For example, a consumer, noticing the increase in the cost of Vaseline, decides to spend Saturday night alone.

So, the price that Johnson & Johnson is willing to pay for oil becomes an added cost for all of the other businesses that use oil. If they want to bid away some of that oil, they have to be willing to pay the higher price. But since higher prices tend to mean lower sales, other producers will only bid away as much oil as they think they can use, now that sales are dropping.

The end result is that Johnson & Johnson ends up with a relatively larger portion of oil. In other words, the resource of oil has flowed to the highest valued product, an important…uh…medical lubricant.

Eventually, because there is an increasing supply of Vaseline, demand is affected. At some point, consumers are unwilling to buy it, because there’s enough of it on the shelves. And, of course, with all this petroleum bidding going on, the price has been increasing. So, some consumers may notice that the price of Vaseline has now increased relative to, say KY Jelly, and they may decide to purchase that instead.

Of course, either way, Johnson & Johnson wins.

So, if you’d like to get a better understanding of how economics work, and maybe get a few good laughs on the way, you can get it tomorrow for about 1/6 the price of the physical book.

I’ll provide the direct link to Amazon to purchase it when it becomes available tomorrow.

Observations: The QandO Podcast for 06 Mar 11

In this podcast, Bruce, Michael, and Dale discuss the situation in Libya, and this week’s employment numbers.

The direct link to the podcast can be found here.

Observations

As a reminder, if you are an iTunes user, don’t forget to subscribe to the QandO podcast, Observations, through iTunes. For those of you who don’t have iTunes, you can subscribe at Podcast Alley. And, of course, for you newsreader subscriber types, our podcast RSS Feed is here. For podcasts from 2005 to 2010, they can be accessed through the RSS Archive Feed.

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February Employment Situation

Once again, the headline unemployment number for February, which droped from 9.0% to 8.9%, hides much weakness in employment, despite the 193k new payroll jobs. Indeed, the BLS’ own U-3 unemployment rate, which is calculated in a similar fashion to mine, increased from 9.8% to 10.4%.

For my methodology, the numbers look like this:

Civilian noninstitutional population: 238,851,000
Historical participation rate: 66.2%
Proper labor force size: 157,641,660
Actually employed: 138,093,000
Actual unemployment rate: 12.4%

At the end of the day, we need another 8 million new jobs to bring us back to full employment.

Observations: The QandO Podcast for 27 Feb 11

In this podcast, Bruce, Michael, and Dale discuss the demonstrations by public employee unions in Wisconsin, and the state of the economy.

The direct link to the podcast can be found here.

Observations

As a reminder, if you are an iTunes user, don’t forget to subscribe to the QandO podcast, Observations, through iTunes. For those of you who don’t have iTunes, you can subscribe at Podcast Alley. And, of course, for you newsreader subscriber types, our podcast RSS Feed is here. For podcasts from 2005 to 2010, they can be accessed through the RSS Archive Feed.

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Observations: The QandO Podcast for 20 Feb 11

In this podcast, Bruce, Michael, and Dale discuss the demonstrations by public employee unions in Wisconsin, and the wave of protests across the Mideast.

The direct link to the podcast can be found here.

Observations

As a reminder, if you are an iTunes user, don’t forget to subscribe to the QandO podcast, Observations, through iTunes. For those of you who don’t have iTunes, you can subscribe at Podcast Alley. And, of course, for you newsreader subscriber types, our podcast RSS Feed is here. For podcasts from 2005 to 2010, they can be accessed through the RSS Archive Feed.

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Observations: The QandO Podcast for 13 Feb 11

In this podcast, Bruce, Michael, and Dale discuss the situation in Egypt, and CPAC.

The direct link to the podcast can be found here.

Observations

As a reminder, if you are an iTunes user, don’t forget to subscribe to the QandO podcast, Observations, through iTunes. For those of you who don’t have iTunes, you can subscribe at Podcast Alley. And, of course, for you newsreader subscriber types, our podcast RSS Feed is here. For podcasts from 2005 to 2010, they can be accessed through the RSS Archive Feed.

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Unemployment Calculations (Updated)

I‘ve gotten some questions about how I do the unemployment calculation every month, and the wide variance between my rate and the official rate. It’s quite simple, although there are some caveats to the data, which I’ll cover in a methodology discussion below.

First of all, the data is all available from the Bureau of Labor Statistics, here. This is the retrieval page for the historical “A” tables of the employment report.  You only need to retrieve historical data, in the following series: Civilian noninstitutional population, Participation rate, and Employed.

You have a choice, by the way, of choosing seasonally adjusted data or not. Seasonal adjustments smooth the numbers a bit from month to month, but not enough to be a major concern. There are pros and cons to the seasonal adjustments, but I’m happy either way. I use non-seasonally adjusted, so there’s more month-to-month variation, but it smooths out over longer time horizons anyway.

The BLS actually creates the employment/unemployment series from two different statistical surveys. One is the Household Survey, which asks households who is employed, who’s looking for work, and who has dropped out of the labor force. This is the series used to calculate the unemployment rate. The second series is the Establishment survey, which asks businesses how much hiring and firing they’ve done. This gives us the number of non-farm payroll jobs that have been created. It generally leaves out the self-employed, agricultural jobs, households, etc., so it doesn’t tell you much about unemployment. It mainly tells you about the rate of job creation. So, to calculate unemployment, we really only need to look at the Household survey’s historical data.

The first step is to calculate the historical labor force participation rate. This is complicated, conceptually, although not technically.  All you have to do, technically, is download the participation data in excel, and run an average between two dates.  Conceptually, you have to try and figure out what good dates are.  There are…issues with this.

You don’t want to go back too far in time, because you are trying to capture the current labor force’s participation, not the participation of your dad’s generation. Labor force participation rates change over time, so the numbers need to be relatively current. I really didn’t want to project the numbers back into the 90s, for example, when the participation rate was solidly above 67%.

You also want the time frame to reflect at least one full economic cycle, so you can capture all the variation between an expansion and recession.  But, you don’t want to choose an end date in the current economic cycle, because that skews the data up or down depending on where you are in the current economic cycle.

The dates I chose are January 2000 to Dec 2009.  That takes data from right after the peak of the 90’s expansion, to right before the steep decline in labor force participation in the current recession. That’s where I get the 66.2% historical labor force participation rate. I could now include 2010 in that rate, which would introduce a slight downwards bias to the historical rate, but not much, yielding a participation rate of 66.1%. If I drop the rates from 2000, and go with a 10-year moving average (2001-2010), it drops to 66%. But, of course, that means that we’re including the current decline in participation, which hides, to an extent, how steep the decline actually is.

Now, there is a big question mark that is really impossible to address at the current time, which is whether or not the current decline in labor force participation is skewed by the Baby Boomer retirements which have begun as the first-year cohort of the Baby Boom hits 65 this year. The logical supposition is that such a large bolus of population retiring and passing out of the system will cause the participation rate to decline. How big of a decline?  I dunno.  We’ll really only know the answer to that question at the next peak of economic expansion, when the participation rate hits a new cycle high. I think it’s already started, though, and, indeed, started in the early 2000s, when the participation rate dropped a full percentage over several months, and then stayed in the 66% range, vice the 67% range of the 1990s. I think–though I can’t be sure–that we’re seeing a fair amount of early retirements among Baby Boomers who are affluent enough to do so.

The upshot of all this is that the selection of dates for calculating the historical average participation rate is very subjective. My calculation is, therefore, arbitrary, although, I think, logically reasoned out. It has a long enough time-line to be a reliable average across an economic cycle. It is not so far in the past that it skews the data. It is not so recent that current declines–or advances–skew the data. But it is arbitrary, and I’m sure others could come up with other ones. And, of course, when we hit another economic peak, the whole thing will have to be recalculated again to catch all those Baby Boomer early retirements.

In any event, once you’ve got the historical labor force participation rate, then all you need to do is multiply that by the civilian adult non-institutional population to derive the size of what should be the current labor force.

You then divide that into the size of the “Employed” population to come up with the unemployment rate.

The equation for all this would be:

1. Population x Participation Rate = Labor Force,

2.- (Labor Force/Employed) + 1 = Unemployment Rate

So, using this last month’s unemployment figures:

238704 * .662 = 158022

-(139323/158022 ) + 1 = 11.8%

And that’s how it’s done…assuming you correctly set up your Excel spreadsheet. As I was writing the formulas above, I noticed that the Excel spreadsheet had the division backwards, and was inflating the unemployment rate. I’ve corrected the post below on the Jan Unemployment Situation.

UPDATE:

While I learned about figuring the average, all it does is pique further interest in determining the number of individuals who are underemployed or have simply given up and have dropped off the statistical graph.

How would you address those two questions and solve for both?

I wouldn’t.

First, we already have a measure on unemployment that covers under-employment/part-time work, called the U-6, which already part of every monthly release. The BLS already does that work about as well as can be expected, so there’s no reason for me to reproduce it. As for those who’ve just dropped out of the labor force, we already see that on a monthly basis via the participation rate, and the labor force size that the BLS reports.

What we don’t know is why people are dropping out of the labor force. The “A” tables keep tabs on the number of discouraged workers, but we don’t have any read on who just decided to retire, or whose spouse got sick and needs them home to care for them, or who just thought taking up mainlining China White would be a good way to pass the time, or whatever.

Ultimately, if they’re out of the labor force, they’re no longer of concern to the statisticians at the BLS. What it really boils down to is how you define the “labor force” and that’s a pretty subjective measure, no matter how you cut it. The BLS has decided that if you’re not employed or actively looking for work, you’re not in the labor force. I’m sure there’s any number of people who would be in the current  labor force under different circumstances, or who’ve been in it in the past, and who will be in it in the future.  But I don’t know how you’d inquire into those myriad of reasons people aren’t in the labor force this month, and come up with a way to quantify that.

January 2011 Unemployment Situation (Updated)

Today’s unemployment situation data is…wierd.  Most noticeable is that the Civilian Non-Institutional Population declined by 185k people, from 238,889k to 238,704k.  Did a lot of people die last month? (Update: Ah. It was an annual population adjustment by the BLS. Carry on.) At the same time, we continue the trend of large increases in the population that dropped out of the labor force, with 319k dropping out last month. Since January, 2010, 2,039k people have left the labor force. On the plus side, 117k more people say they are employed this month than last month.

Still, that 9% unemployment rate is an artifact of 504k people disappearing from the population, not the creation of new jobs, something the anemic 36k new payroll jobs number makes clear. Also, the adjusted U6 unemployment rate surged From 16.6% to 17.3%. In fact, U-3, U-4, U-5, and U-6 all rose sharply.  U-3 (Total unemployed, as a percent of the civilian labor force) rose from 9.1% in December to 9.8% last month. So, we got that goin’ for us.

Getting to the numbers, for a more accurate view of unemployment:

Civilian non-institutional adult population: 238,704
Historical labor force participation rate:
66.2%
Proper labor force size:
158,022
Actually Employed:
139,323
Unemployment Rate:
11.8%

UPDATE: Well, this is embarrassing.  I’ve made a calculation error in the Excel spreadsheet, which provided an incorrect unemployment rate, above.  I reversed the division between the labor force and the number of employed persons.  I noticed that while writing the post above, on how I calculate the number.  I’ve corrected the Excel spreadsheet, to prevent the error from recurring in the future.