Tag: Job Growth

Professional, Scientific, and Technical Services – Key to Colorado Recovery

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The Professional, Scientific, and Technical Services (PST) sector is critical to the state. Companies in the sector provide engineering and architecture services, conduct scientific research, and manage computer systems. Of particular note, the sector is composed of companies from the various high-tech clusters (photonics, biosciences, nanotechnology, homeland security, IT, etc.).

PST accounted for about 10.6% of state private sector Real GDP in 2010. Between 1997 and 2010 it expanded at an annualized rate of 4.4% versus 3.4% for the Colorado private sector.

Average annual private sector PST Colorado wages for 2010 (most current year available) were $79,623, compared to $47,916 for the overall state average. In 2010, the Colorado PST sector accounted for 9.1% of total private sector employment. Between 1997 and 2010, the sector added employment at an annualized rate of 2.1% compared to 0.7% for the state.

The Healthcare, Higher Education, Tourism, and Extractive industries are leading the recovery. PST is next. It has added about 9,100 jobs since the low point in 2010.The sector has recovered about 78% of the jobs lost since peaking in 2008. If the positive employment trends continue, that level will be reached later this year.

It’s a long slow road to recovery.

For a more complete update on the recovery of the Colorado economy, go to https://cber.co/.

©Copyright 2011 by CBER.

Warmer Weather – A Source of Job Creation?

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Recently, a local economist hypothesized that the recent strength of the Colorado economy was correlated with a warmer winter. The rationale for this hypothesis was that warmer weather may have benefitted outdoor sports such as golf courses, biking, rollerblading, and so forth. In addition, the economist surmised that retail sales would be stronger because warmer weather was more conducive to shopping and increased construction activity.

On one hand, the warmer weather theory sounded plausible because the weather “seemed” milder this winter, but on the other hand it sounded like it was full of hot air.

Premise 1 – The winter was warmer.
If heating degree days are the defining factor for how cold a winter is, then the period October 2011 through March 2012 was negligibly colder than the prior year. For this six month period, the most recent October, December, and February were colder, the two Novembers were similar, and January and March were warmer this year. (A larger number means it is colder, more heat is needed to heat a building).

October 2010         174 heating degree days
November 2010     645 heating degree days
December 2010     789 heating degree days
January 2011          925 heating degree days
February 2011        863 heating degree days
March 2011             513 heating degree days
Total                      3,909 heating degree days

October 2011          312 heating degree days
November 2011      636 heating degree days
December 2011  1,058 heating degree days
January 2012           763 heating degree days
February 2012         935 heating degree days
March 2012              364 heating degree days
Total                       4,068 heating degree days

Possibly it seemed warmer, because there didn’t seem to be snow on the ground that often. A comparison of snowfall for the metro area shows that there was 2.5 times as much snow this past winter as the prior year.

October 2010         none
November 2010    1.5 inches
December 2010    3.3 inches
January 2011         8.0 inches
February 2011       5.3 inches
March 2011            2.5 inches
Total                      20.6 inches

October 2011         8.5 inches
November 2011    4.5 inches
December 2011 16.5 inches
January 2012        4.9 inches
February 2012    20.2 inches
March 2012         none
Total                     54.6 inches

It is truly a shocker to learn that the past winter was actually colder and wetter than the previous year. The timing of the storms, the lack of wind, or some other factor must have created the perception that it was warmer this past winter.

Even with greater snowfall in the metro area, snowpack is below average and 95% of Colorado is reportedly in drought conditions. Two significant forest fires have occurred and summer hasn’t arrived.

Conclusion: Premise 1 is FALSE.

Premise 2 – The warm weather resulted in increased participation for local sporting activities.
There is no easy way to prove this. HOWEVER, the lack of snow in the ski country, at the right times, was in part responsible for diminished lift ticket sales – a decrease of more than 7%. Ouch that hurts! Not only did the lack of snow hurt ski business it will play havoc with rafting businesses this summer.

Conclusion: #2 Possibly true in the metro areas, FALSE in ski areas.

Premise 3 – Warm weather means stronger retail sales.
This is an interesting concept that is difficult to prove. Cold and snowy weather on key shopping days have reduced retail sales during past Christmas shopping seasons, but there is no evidence that warmer weather has increased trade sales. Retail sales are noticeably higher compared to a year ago, but that is attributed to more people working than last year at this time. And in some cases, sales are higher because retailers have finally been able to raise prices. Sales may be higher in the metro areas, but they are probably below expectations in the ski country because of reduced traffic.

Conclusion: #3 – Possibly true in the metro area, FALSE in ski areas.

Premise 4 – Warm weather means increased construction activity.
For the six month period October to March there were 114,500 construction workers this year versus 113,300 last year. Last June, the Construction sector finally bottomed out from the 2007 recession and has been slowly adding jobs since. The big boost of construction jobs in January is more likely a result of improved economic conditions than warmer weather.

Conclusion:#4 – Inconclusive.

One of the fun things about economics is dissecting “grassy knoll” or “warmer weather” theories to see if they are true, partially true, or false. In this case, it is highly improbable that the “warmer” weather was a source of net job creation. The gains in revenue at Denver golf courses, bike shops, and shopping malls were offset by losses on the ski slopes and sales in mountain t-shirt shops, hotels, and restaurants. The warmer weather will also result in a dismal rafting season and increased costs for fighting forest fires.

For a more complete update on the recovery of the Colorado economy, go to https://cber.co/.

©Copyright 2011 by CBER.

Leisure and Hospitality Leads the Recovery

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The Leisure and Hospitality (L&H) Sector has played a critical role in the recovery of the national and state economies. It is important because of the number of jobs added and because it is part of the economy in every county in the state.

Nationally, seasonally adjusted employment peaked in December 2008 at 13,560,000 workers. The number of workers declined with the Great Recession and in March 2012 employment surpassed that previous peak, reaching 13,587,000. It took 50 months for the sector to go from peak-to-trough-to-peak.

There was a similar pattern for Colorado. L&H employment peaked in May 2009 at 276,000. L&H Employment declined with the recession and in January 2012 it surpassed the prior peak at 277,800. It took 44 months for the state sector to recover.

While 50 and 44 months is a long time, it is possible that the overall state economy may take close to six years before it reaches the 2006 peak.

Nationally, the time from peak to trough was 24 months, or two years. During this time 637,000 jobs were lost. The recovery period was slightly longer, 26 months.

At the state level, the time from peak-to-trough was 20 months. About 16,000 jobs were lost during this period. The recovery period was 24 months.

It is depressing to consider some of these number; however, it is even more unsettling to think that these numbers describe one of the state’s stronger sectors.

For additional information on the overall state economy go to the cber.co website.

©Copyright 2011 by CBER.

Colorado’s Recovery is Broad Based and Includes Primary Jobs

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Within the past month, there have been several reports citing how Colorado has one of the faster growing economies in the country. This is good news, but it must be remembered that for several years local economists were saying, “Thank God for Nevada, if it weren’t for them Colorado would have the worst economy in the country.” Part of the reason for the comparatively “strong growth” is about 150,000 jobs were lost in the Great Recession and our current tepid growth looks great compared to job losses.

Case in point…  Job losses in Colorado’s Construction sector have been so severe that employment is at mid-1990s levels. The Manufacturing sector declined for 12 years. It is just now beginning to add jobs again. Despite the build out in the Retail Trade sector, employment has been volatile over the past decade. Today it is similar to the late 1990s and retail Trade jobs are up 4,600.

With increased population in the state growth is inevitable in these sectors.

The real story is that the Colorado recovery is broad-based and it is includes primary jobs (jobs that create wealth).

The recovery has been led by the Tourism and Health Care sectors. They are sectors that add jobs in all areas of the state. There are very few primary jobs in either sector. They account for 19,000 of the 47,300 jobs added when comparing Q1 2012 to Q1 2011.

The Manufacturing and Professional Scientific sectors have added a combined total of 7,700 jobs. Many of these are primary jobs.

Colorado has added 3,900 jobs in the Employment Services sector – The addition of temporary jobs is considered a harbinger that the economy is improving.

Only two sectors recorded significant job losses during this period. Combined, the Information and Local Government, excluding schools, sectors declined by 5,700 jobs.

For additional information go to https://cber.co.

©Copyright 2011 by CBER.

U.S. Employment Tapers Off – Another False Start?

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After three months of solid job growth, BLS released what seems to be a bad April Fool’s Day joke in the form of the March jobs report. After adding jobs at an average monthly rate of 246,000 for December 2011 – February 2012, total nonfarm payroll employment rose by only 120,000 in March.

In light of projections by analysts that job gains would exceed 200,000, this report begs the question, “Are we seeing another false start in job growth, as we did in the first half of 2010 and 2011, or was the March report just another bump in the seemingly endless road to full recovery?”

On Monday (April 9), the DJIA lost 130 points, or 1%. Is that a real answer to the question or just a partial answer?

On a positive note, jobs were added in the Leisure and Hospitality (39,000); Private Education and Health Care (37,000); Manufacturing (37,000); Professional and Business Services (31,000), and Financial Services (15,000) sectors.

Many of the jobs in the Manufacturing and PBS sectors are primary jobs, i.e. they bring outside wealth to the community and they create more support jobs than other sectors. It is good news when jobs are added in the Tourism sector because the industry touches most regions. Increased tourism jobs are an indicator that people have greater disposable income – and they are spending it.

Increased jobs in the Financial sector may be a sign that the woes of the industry may be behind us – with an emphasis on “may”. And then there is the Private Education and Health Care sector. Depending on our perspective this sector may be viewed as a perpetual job creation machine or nothing more than a bureaucracy builder.

The losers were Retail Trade (33,800) and Construction (7,500) sectors.

So is the latest report an April Fool’s Day joke? Employment growth is likely to continue, but not likely at the rate of 2250,000 jobs a month that is needed to significantly lower the unemployment rate.

 

©Copyright 2011 by CBER.

BLS reports 33,000 Colorado jobs added in 2011

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The Bureau of Labor Statistics recently released its benchmark revisions for 2011 that show Colorado added 33,000 jobs in 2011. The updated total is nearly double the projected job growth of the monthly data presented throughout the year.

After peaking in 2008, approximately 150,000 jobs were shed in 2009 and 2010. Employment declines were so severe that total employment dropped below the 2001 peak. Finally, in 2011, Colorado employment again surpassed the high point in 2001.

If Colorado employment increases by about 1.7% in 2012 and 1.9% – 2.2% for the 2 years after that, it will reach the 2008 peak in 2014. In other words, it will take six years to return to the 2008 peak.
By comparison, it took 4½ years for employment to return to the 2001 peak after jobs losses associated with the 2001 recession. (Some economists are saying the full recovery will return to peak just in time for the next cyclical downturn).

Here’s to quicker recoveries from future recessions.
©Copyright 2011 by CBER.

Where are all the Startups? – Are they Really a Job Creation Machine?

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Suppose your investment advisor called you and said, “Have I got a deal for you? I will sell you 12,027 shares of a fund at $6.10 per share. The total cost to you is only $72,918. Sound good?”

Your advisor continues, “This is a killer fund. In 17 years, the price per share will rise from $6.10 to $18.30. And, in full disclosure I am required to tell you the fund will buy back a few shares along the way.  Sound good?

You reply, “Sounds great, but could you tell me more about the number of shares that will be bought back along the way?”

The advisor nervously answers, “Well, you see…the price per share increases from $6.10 to $18.10. Sound good?” Very quickly the advisor continues, “And the fund will only buy back 9,348 shares. You will still have about 22%-23% of your original shares. Sound good? Can you sign right here?”

You say, “Let me get out my calculator. That means the value of the fund is only $48,987 after 17 years. Sound good?”

The manner in which jobs are created by startups has a similar rate of return. (For purposes of this discussion, startups will be defined as companies less than one-year old that have employees. The Bureau of Labor Statistics (BLS) has tracked the performance of these companies since 1994.)

From the BLS data it is possible to look at the number of firms, average firm size, total employment, and survival rates for the firms formed in 1994. The BLS data shows:

Number of Firms
• In 1994 there were 12,027 firms.
• In 2011 there were 2,679 firms.
Average Firm Size
• In 1994 the average firm size was 6.1 employees.
• In 2011 the average firm size was 18.3 employees.
Total Employment
• In 1994 the firms had 72,918 employees.
• In 2011 the firms had 48,987 employees.
Survival Rate
• In 1994 the survival rate was 100%.
• In 2011 the survival rate was 22.3%.

Do the numbers look familiar? If not, revisit the opening paragraphs.

Startups are critical to future of our country for a variety of reasons; however, they may not be job creation machine that we have been led to believe. They add jobs in year one, but that base declines in year 2 and erodes further over time. Sound good?

With the decline in the number of startups and survival rates, this is a particularly frightening model for economic growth in the state!

For additional information on startups and job creation go to https://cber.co/ or the report “Where Are All the Startups?”

 

©Copyright 2011 by CBER.

Occupy the Labor Market – Shields Foretells Growth in Northern Colorado

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In January, Dr. Martin Shields, CSU economics professor, produced his business and economic forecast for the Northern Colorado Business Review. In short, Shields pointed out that the U.S. will see a lackluster recovery that will be driven by national and international events (debt, war, oil prices, political crises, etc.)

At the national level, Shields emphasized three points:
• “Tepid and sustained” Real GDP growth.
• The decline in unemployment will be slow as the median number of weeks that workers are unemployed remains high, based on the slow rate at which jobs are being created.
• Core inflation has returned to pre-recession levels.

The Northern Colorado economy will continue to be a mixed bag, although it has been a leader in the recovery. It is expected to continue in that role. Nevertheless, unemployment will be high by historical standards. Locals have struggled with the decline in real household income, a challenge that is likely to continue in the months ahead.

Shields also emphasized the following:
• Northern Colorado lost 5,900 jobs over the past 3 years.
• On a positive note, the region added 1,900 jobs in the past year.
• Since 2008 the number of unemployed workers in the region has increased by 6,700.
• Larimer and Weld County have performed differently during the Great Recession.
o Larimer’s labor market has been stronger
o Median household income in Larimer has declined.
o Weld County household income has remained flat.
• FFHA data shows that housing prices are stagnant.
• While it is encouraging that there is an uptick in housing starts, it must be noted that the increase is small and it is from a very low base.

Looking ahead, Shields foretells continued growth in 2012.
• The unemployment rate might approach 5.0% in Larimer County.
• In Weld County, unemployment might fall below 8.0%.
• Between 2,700 and 3,300 workers might be added to local payrolls.
The Government, Information, and Financial Activities sectors will struggle, while the energy, food manufacturing, health care, and professional business services sectors will continue to grow.

Shields heavily emphasized the term “might” in each of his projections. In closing he stated that the real challenge will be to add jobs that pay good wages.

 

©Copyright 2011 by CBER.

Where are all the Startups? – Survival Rates on Downward Path

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The U.S. and Colorado have experienced volatile economic conditions for about 20 years. There was strong growth during the go-go 1990s, follow by two major recessions during the Lost Decade. Startups play an important role in any economy, but until recently there has been little data to understand their performance. This brief analysis uses BLS data and assumes that startups are less than one-year in age and have employees.

The following are the most frequent questions asked about survival rates for startups.
• Are the rates different based on the number of years the firms have been in existence?
• Are the rates different based on when the firm was started?
• How have the rates changed over time?
The answers are explained and can be observed below.

The first question is the easiest to answer – survival rates are lower for longer periods of time.
• The range for two-year rates was 60.9% to 68.9%.
• The range for five year rates was 43.7% to 50.7%.
• The range for eight-year rates was 33.4% to 39.7%.

A partial answer can be given to the second question. Data is available for different time frames (16 years for two-year rates, 13 years for five-year rates, and 10 years for eight-year rates). For the 10-year period that is common to all three rates, the lowest rates occurred in 2001.

The 2-year survival rate was 61.6% in 2001 and 60.9% in 2008. Based on the current trends, the lowest 5-year and 8 -year rates are likely to occur in 2008. This coincides with the low points in the business cycle.

The answer to the final question is simple – survival rates have declined over time.
• The 2-year rates began declining in 1999, posted a slight increase in 2002, declined in 2006 and rebounded in 2009.
• The 5-year rates showed a steady decline beginning in 1995. There was an uptick in 2002 and 2003, but the downward trend reappeared in 2004.
• The 8-year rates showed a downward trend beginning in 1995. There was slight upward movement in 2002 and 2003.
As mentioned above, these changes have coincided with the business cycle; however, over time they are trending downward.

Are there policy decisions that could reverse this downward path? Is this downward trend a function of the quality of teaching in colleges and universities? Are the multitude of higher education entrepreneurial centers that have been started over the past two decade having a positive impact? Is this trend a function of poor service from government programs such as the Small Business Development Centers or the Small Business Administration? Have the banks failed to properly fund the startups? Or would the survival rate have been worse if the university and federal government programs weren’t in place? Or is this downward trend simply a function of ten-years of annualized Real GDP growth of 1.6%.

Startups are an important part of the economy. When data becomes available for 2010 and beyond (several years from now), hopefully it will be possible to look back and see that the downward trend has reversed.

For additional information on startups and job creation go to https://cber.co/ or the report “Where Are All the Startups?”

 

©Copyright 2011 by CBER.

The Mismatch of Skills between Company Needs and the Unemployed

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It is an understatement to say that there is a mismatch of skills between the unemployed and the needs of the companies looking for workers.

There are 2.1 million unemployed workers in occupations with unemployment rates below the natural rate (4.5% to 5.0%). Many of these occupations require a college degree. These occupations account for 31% of total U.S. workers.

There are 4.3 million unemployed workers in occupations with unemployment rates between the natural rate (4.5% to 5.0%) and below the U.S. average. These occupations account for 38% of total U.S. workers.

There are 6.0 million unemployed workers in occupations with unemployment rates above the U.S. average. These occupations account for 31% of total U.S. workers.


The bottom line is there are 10 million workers competing for replacement jobs in their occupations. As well, they are part of the pool who are competing for the handful of jobs in industries where they are not qualified.

It is clear why the unemployment rate has taken so long to return to the “natural rate” and it is easy to prepare the chart that illustrates the challenge.

What is the remedy?

 

©Copyright 2011 by CBER.