Single Family Housing Starts Vs. Unemployment Rate

One of the key metrics for the health in the housing market are the "privately owned housing starts". "Housing starts" are an economic indicator that reflect the number of privately owned new houses (technically housing units) on which construction has been started in a given period. Usually, a decline in the "housing starts" leads to the start of a recession. 

The "housing starts" are a leading indicator for the unemployment rate. Both metrics are inversely correlated. When the "housing starts" drop, the unemployment rate will rise with a lag of about 1 to 2 years.

Because of the fact that the "housing starts" are a leading indicator, this is a very important metric to predict the unemployment rate. As a consequence, the "housing starts" are also a predictor of real GDP, capacity utilization, the stock market index and the consumer price index (CPI).

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The True Jobs Numbers

Just a reminder to those who thought the jobs numbers on Friday were positive.

See the blue line (and just recently also the grey line).

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Unemployment Vs. Real GDP

The inverted Unemployment Rate is correlated to Real GDP and is also known as Okun's Law named after Arthur Melvin Okun.

Zero Hedge featured Okun's Law in this article.

Red curve: inverted yoy% change in unemployment rate

Blue curve: yoy% change in real GDP

Never in history has the unemployment rate been so artificially low (red graph artificially high) as today. The red curve has never been higher than the blue curve, which implies that the unemployment rate is much higher than officially reported.

We already know what the cause is: a lot of discouraged and part-time workers.

Moreover, the chart suggests that Real GDP (blue chart) is a leading indicator for the unemployment rate (inverted red chart).

As a final note, notice that we are talking about real GDP, which is inflation adjusted. This means that inflation negatively impacts real GDP and therefore inflation will in turn create higher unemployment rates at a constant GDP rate.

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Average Hourly Earnings do not confirm Unemployment

As Zero Hedge reports here, the average hourly earnings were going down. That is not consistent with a lower unemployment rate.

Coincidentally, I have a chart on this correlation right here.

And it looks like this:

As you can see, how can the unemployment rate fall (yellow chart) if the average earnings go down (blue chart).

Reason: part time workers and people leaving the labor force.

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Wage Inflation Vs. Unemployment Rate

This page is created to monitor the Average Hourly Earnings of Production Vs. Unemployment Rate.

When unemployment declines (yellow chart), wages inflate (blue chart).

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Capacity Utilization Rate Vs. Unemployment

This page is created to monitor the Unemployment Rate Vs. Capacity Utilization Rate.

Historically, when the capacity utilization rate goes up (blue chart goes down), the unemployment rate goes down (red chart).

We also know that a high capacity utilization rate points towards inflation. Inflation points towards a higher CPI and a higher CPI means higher average hourly wages. Higher wages point to lower unemployment. And the circle is round.

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Correlation: Initial Unemployment Claims Vs. S&P

Another way to value the stock market is to look at the initial unemployment claims. You take the inverted chart of this metric and you will see that this is highly correlated with the S&P index.

Chart 1: Initial Unemployment Claims (Inverted) Vs S&P Index

So whenever you hear that the initial unemployment claims went up, you sell the S&P index.

Oh, and what do you know, weekly initial unemployment claims just went up:
http://www.marketwatch.com/story/us-weekly-jobless-claims-edge-up-to-352000-2013-04-18?link=MW_latest_news

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Correlation: Wage Inflation Vs. Unemployment Rate Vs. Consumer Price Index

There is an inverse relationship between the unemployment rate and the wage inflation. Whenever people get unemployed, it means the economy isn't doing well. Employers won't be able to raise wages of the people during these difficult times, so you will get a low wage inflation trend (blue line). In these periods, the unemployment rate tends to go up (yellow line).

Chart 1: Wage Inflation Vs. Unemployment Rate

The same can be said the other way round. When the unemployment rate declines, people will demand a higher salary as skilled workers get scarcer. At this stage the wages will inflate.

It is also so that wages correlate highly with the consumer price index (CPI). So if the unemployment rate declines, you can expect a higher CPI as you can see on Chart 2.

So if you don't believe the CPI the government is reporting, you just look at the average hourly earnings. The average hourly earnings were positive in March. So I expect the CPI to increase too.

Chart 2: Average Hourly Earnings Vs. CPI

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ADP Report Vs. Unemployment Rate

Today we also found the ADP jobs numbers for the month of January 2013 and it came out to 192000 jobs. This is pretty good, but if you look at the trendline on Chart 1 we are still going down.

Job growth isn't keeping up with the rise in population, we need to have at least a payroll number above 200000 to reduce the unemployment rate.

The declining unemployment rate (blue dots) is not to be trusted because if it were real, the red bars would be going up, not down.

Chart 1: ADP numbers Vs. Unemployment

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Correlation: Food Stamp Participation Rate: The Real Way to Measure Unemployment

I want to make sure that people comprehend the manipulation in the unemployment numbers.

If we look at the unemployment rate in the U.S., it seems that everything is improving. U3 unemployment has dropped from 10% to 8% in the last two years. U6 unemployment came from 17% to 14% in 2 years.

But all is not well if we look at another metric which is the percentage of people on food stamps. I think this metric is giving a much better view on the state of the U.S. jobs market (Chart 1). Chart 1 tells us that the declining U6 unemployment rate is BS as a record number of people are still making use of food stamps.

Chart 1: Percent of Population on Food Stamps

If we compare the unemployment rate (Chart 2) against the percentage of the population on food stamps (Chart 3), we can see that there is a correlation here. In 1970 for example, the U3 unemployment rate was 5% with a food stamp percentage of 2%. Then we peaked in 1982 with a U3 unemployment rate of 10% and a food stamp percentage of 10%. The unemployment then dropped to 4% in 2000 with the food stamp percentage dropping to 6%. And since then the food stamp percentage has hit a record of 15% today.

If the correlation is correct, we should now have a much higher unemployment rate than 8%. More like 14%. And more importantly, the real unemployment rate is not declining. The reason for this is that the percentage of people on food stamps is still at record highs of 15% for the population (and 19.3% for the non-institutional population) (Chart 3).

Chart 2: U3 and U6 Unemployment

Chart 3: Percentage of Population on Food Stamps

So there you go, another correlation, one that accounts for underemployment by discouraged and part-time workers. We are in times of wage stagnation and will have difficult times up ahead.


Data on the Food Stamp Participation Rate can be found on the SNAP website.

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Correlation: Capacity Utilization Vs. Unemployment Rate

It's fascinating how many correlations there exist in the economic world. Today I found this one: Capacity Utilization Vs. Unemployment are inversely correlated. And the best part is: the capacity utilization rate is a leading indicator for unemployment, meaning the trend in the capacity utilization rate can predict the trend in the unemployment rate.

For the U.S. the chart looks like this:

Chart 1: U.S. Unemployment Vs. Capacity Utilization

For the country I live in, Belgium, the correlation works too (one chart goes up, other chart goes down):

Chart 2: Capacity Utilization Belgium

Chart 3: Unemployment Rate Belgium

For Canada it works too:

Chart 4: Capacity Utilization Canada

Chart 5: Unemployment Rate Canada

It even works for the Euro Area:

Chart 6: Capacity Utilization Euro Area

Chart 7: Unemployment Rate Euro Area

And Japan:

Chart 8: Capacity Utilization Japan

Chart 9: Unemployment Rate Japan

Do you know what this means? If we just look at the capacity utilization (which is a leading indicator), we can predict the unemployment rate. And if we can predict the unemployment rate, we can predict the retail sales, GDP growth, current account deficit/surplus, currency ratio, etc... I could never believe capacity utilization rate could be so important and significant.

Cherish this correlation!

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Unemployment: Getting Worse in Europe

Today, the unemployment number for Italy was released at 11.1% in October 2012. The number is very big, but the slope at which the unemployment is increasing in Italy is even more concerning. See Chart 1.

It is not getting better in Europe, only worse. Also France and the Netherlands are doing worse and worse.

Our country Belgium is actually doing very well as is Germany.

Chart 1: PIGS Unemployment

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More and More Discouraged Workers

This following graph should be concerning. We have government statistics (grey and red chart) and we have the real SGS Shadowstats statistics (blue chart). The key statistic to look at is that of the discouraged worker.

Let's go over the definitions first. A discouraged worker is a person of legal employment age who is not actively seeking employment or who does not find employment after long-term unemployment. This is usually because an individual has given up looking or has had no success in finding a job, hence the term "discouraged".

This discouraged worker includes two categories: short-term discouraged (less than 1 year) and long-term discouraged (more than 1 year). The government statistics only show the short-term discouraged workers (U6). Why do you ask? Political considerations, to improve the statistics and this is especially true after year 2009 as we will see below.

Since 1994 Shadowstats has included long-term discouraged workers. Long-term discouraged workers are those people that are out of a job more than 1 year and I don't see a reason why they aren't counted in the statistics.

Official unemployment rate (U3) is 7.8% right now. Unemployment rate including short-term discouraged workers (U6) is 15%. The real unemployment though (SGS), is 23% (Chart 1). This SGS unemployment counts in the long-term discouraged workers upon the U6 number.

Chart 1: SGS Unemployment Rate

Now, what concerns me a lot is that the blue chart has been doing something weird after year 2009. Previously, the blue chart always followed the U3 and U6 unemployment numbers. But since 2009 (after the economic crisis), the blue chart kept going up, while the other red and grey charts are going down. This is a serious deviation. It means that the class of long-term discouraged workers has been massively increasing. It also means that the short-term discouraged workers just can't find a job. That's why they are being added to the long-term discouraged worker category. This only started to happen after 2009. This is also the class of unemployed people that are most unlikely to find a new job due to the length of the unemployed period. The real unemployment rate is now almost on par with the unemployment rate of the Great Depression (25%).

You can be sure of this, the economy isn't doing as well as it seems.

More info here:
http://video.foxbusiness.com/v/1748956928001/the-real-unemployment-numbers/

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Non-Farm Payroll number Vs. Unemployment Rate

Non-Farm Payroll numbers came out at 113000 in September and the unemployment rate fell to 7.8%. Gold initially dropped as everyone thought that the decline in the unemployment rate was positive, but actually it is not. Peter Schiff mentions why in his update here.

As I mentioned before here, the non-farm payroll numbers are more important than the unemployment numbers. Especially when government is underreporting on the unemployment numbers as discouraged workers and part-time workers aren't counted in the unemployment numbers.

To get a higher employment in the U.S. industry we need to have at least 200000 for the non-farm payroll number, which we didn't get at all. We only got 113000, which is only half of the goal we need to achieve.

So the reality is: the unemployment rate went up, even though the government statistics say differently. The reason being that the population is growing faster than people are getting jobs.

Chart 1: Non-farm payroll

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Non-Farm Payrolls and Unemployment: Another Correlation

I came across an interesting Zerohedge article about the odds of QE3. In that article they point out that QE3 odds are based on unemployment rate and non-farm payroll numbers, which will be released in about two weeks.

Table 1: Zerohedge's odds table for QE3

Actually, I think this table is redundant because a rise in payrolls (Chart 1) always accompanies a decline in unemployment rate. We will need the chart of the working-age population (Chart 2) to perform the analysis.

I will tell you the details, in this article.

Chart 1: Non-farm payrolls

Chart 2: Working-age Population in the U.S.

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How Likely is QE3? 70% likely.

Ben Bernanke has been saving his ammo in the past months. Each time the fed meeting was held, markets were hoping for QE3, but they didn't receive any. This is evidence by the U.S. federal reserve balance sheet on Chart 1.

Chart 1: U.S. Federal Reserve Balance Sheet

Today, we have passed several months and we already see that the economy is starting to deteriorate. Not only in Europe and the emerging markets, but especially in the United States. In this article I will focus on the key macroeconomic data in the U.S.

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The Effect of Government on the Economy of a Country

I believe government is an important institution to keep order in a society of a country. It should focus mainly on the country's defense and should obey the constitution of the country. By no means it should involve with the economy of a country as the government is always less efficient as free market capitalism. Governments should be as small as possible, in order to let the private economy flourish. Today, governments are standing in the way of free market capitalism through taxation, regulations and counterproductive measures. What governments don't know are the unintended consequences they cause. I'm sure that governments are the root cause of all the problems in Europe and soon in the United States.

In this article I want to give an overview of several countries and their government involvement. The best measure to rate government involvement would be the amount of spending as a percentage of the country's GDP. We will discuss the effects of a big government on the country's economy and give advice to investors on how to act on this knowledge. We will see that there is a direct correlation between government size and unemployment/debt/tax rate.

To read the article go to: The size of governments and the effect on their economies.

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