U.S. Economy

All 4 of the largest MSAs (metropolitan statistical areas) in California experienced an increase in job openings for the month of April.

Los Angeles-Long Beach-Anaheim

The Los Angeles-Long Beach-Anaheim MSA experienced an increase of 26,029 job openings in April 2015, an 18.79% change from March 2015.

Month	Total Openings	Percent Monthly Change	Percent Yearly Change
May-14	129,540	-5.69	27.01
Jun-14	129,782	0.19	27.01
Jul-14	137,333	5.82	27.01
Aug-14	136,939	-0.29	27.01
Sep-14	112,657	-17.73	27.01
Oct-14	121,598	7.94	27.01
Nov-14	108,123	-11.08	27.01
Dec-14	104,302	-3.53	27.01
Jan-15	140,013	34.24	27.01
Feb-15	137,967	-1.46	27.01
Mar-15	138,496	0.38	27.01
Apr-15	164,525	18.79	27.01

San Francisco-Oakland-Fremont

The San Francisco-Oakland-Fremont MSA experienced an increase of 13,276 job openings in April 2015, an 18.65% change from March 2015.

Month	Total Openings	Percent Monthly Change	Percent Yearly Change
May-14	65,783	-5.55	28.41
Jun-14	66,213	0.65	28.41
Jul-14	69,790	5.4	28.41
Aug-14	69,209	-0.83	28.41
Sep-14	58,567	-15.38	28.41
Oct-14	63,065	7.68	28.41
Nov-14	56,940	-9.71	28.41
Dec-14	54,986	-3.43	28.41
Jan-15	72,089	31.11	28.41
Feb-15	70,884	-1.67	28.41
Mar-15	71,196	0.44	28.41
Apr-15	84,472	18.65	28.41

Riverside-San Bernardino-Ontario

The Riverside-San Bernardino-Ontario MSA experienced an increase of 9,550 job openings in April 2015, an 18.21% change from March 2015.

Month	Total Openings	Percent Monthly Change	Percent Yearly Change
May-14	48,935	-5.13	26.71
Jun-14	49,141	0.42	26.71
Jul-14	52,360	6.55	26.71
Aug-14	51,924	-0.83	26.71
Sep-14	40,018	-22.93	26.71
Oct-14	42,870	7.13	26.71
Nov-14	38,138	-11.04	26.71
Dec-14	37,377	-2	26.71
Jan-15	52,811	41.29	26.71
Feb-15	52,141	-1.27	26.71
Mar-15	52,454	0.6	26.71
Apr-15	62,004	18.21	26.71

San Diego-Carlsbad-San Marcos

The San Diego-Carlsbad-San Marcos MSA experienced an increase of 8,967 job openings in April 2015, an 18.38% change from March 2015.

Month	Total Openings	Percent Monthly Change	Percent Yearly Change
May-14	46,354	-5.38	24.58
Jun-14	46,681	0.71	24.58
Jul-14	49,258	5.52	24.58
Aug-14	49,007	-0.51	24.58
Sep-14	41,343	-15.64	24.58
Oct-14	44,408	7.41	24.58
Nov-14	39,956	-10.02	24.58
Dec-14	38,937	-2.55	24.58
Jan-15	49,272	26.54	24.58
Feb-15	48,492	-1.58	24.58
Mar-15	48,782	0.6	24.58
Apr-15	57,749	18.38	24.58

Source: BLS

Waiters and Waitresses experienced the largest increase of new openings of all occupations in the US for the month of March with 4,538 new job openings.

March 2015

Occupation	Total Openings	New Openings
Waiters and Waitresses	62,102	4,538

Source: BLS

There a number of different types of economic damages that arise in business interruption cases. One type of damage is the lost profits associated with the business interruption. Another type has to do with the loss of asset and/or property values. Out-of-pocket expenses associated with the incident that caused the business interruption is another common loss in business litigation.

The example below involves business interruption litigation involving a midsize cattle operation. The impacted cattle operation is is based on an 1000 acre ranch in Central Texas. The cattle company earned its revenue from the sell of registered cows and calves, commercial steers, hay and other agricultural products related to cattle production.
The company’s the ranch operation was damaged by a welding fire that was sparked in the main section of the property. The fire caused a number of buildings to be damaged. Several livestock areas suffered damage that resulted in the death of livestock and the damage and destruction of machinery and equipment.
The company had business interruption insurance. The company’s insurance policy worked off a formula that reimbursed the company for a set period of lost profits, out-of-pocket expenses, and expenses to get the business back to where it was prior to the incident.

After the fire the ranch management filed a claim with the insurance company. The insurance company did their analysis and reimbursed them for their losses according to the policy. The ranch owners did not agree with the amount that was paid by the insurance company. The ranch owners calculated that they were both out of pocket a lot more than the insurance company calculated and their lost profits were higher. The ranch also calculated that it would take a longer period of time for them to be able to get back up to speed.
Ultimately after several year months of dealing with insurance company the ranch owners suit the insurance company and other parties including the company that started the fire. In this case the ranch alleges that several types of economic loss associated with the business interruption have occurred.

The ranch first alleges incurred out-of-pocket us expenses associated with the cleanup of the damage and destruction of its property and assets. In this case these expenses include removing machinery replacing machinery and disposing of livestock. In addition the company has also incurred a loss associated with the amount that will be required to get the company back to where it was before the fire. In this instance, these expenses include fixing and replacing the machinery fixing and replacing buildings and purchasing new livestock. In addition to the out-of-pocket expenses associated with the remediation of the damage and the purchase of new equipment and livestock, the business operation has also alleges lost profits during in the time period in which they were the remediation occurred. In this instance the company lost out on calf sales, hay, and other agricultural products that were damaged or destroyed from the fire. The ranch operation also was not able to conduct its auction of its crop because of the fire.

The health care and social assistance industry gained 7,000 jobs from February 2015 to March 2015. Compared to March 2014, the cumulative number of jobs added in this industry is 49,900, an annual increase of 3.8%.

Source:http://www.tracer2.com/admin/uploadedPublications/2133_TLMR-March_15.pdf

Image source: http://blogs.wsj.com/health/2012/01/06/health-care-sector-adds-jobs-as-overall-employment-picture-looks-healthier/

The U.S. rig count was 932 in April 2015, down from 1,048 in March 2015; Texas rig count was 393 in April 2015, down from 462 in March 2015; The Eagle Ford Shale rig count was 115 in April 2015, down from 137 in March 2015.

 

Source:Baker Hughes

The U.S. rig count was 932 in April 2015, down from 1,048 in March 2015; Texas rig count was 393 in April 2015, down from 462 in March 2015; The Eagle Ford Shale rig count was 115 in April 2015, down from 137 in March 2015.

 

Source:Baker Hughes

That’s a question that comes up a lot in wage and hour land employment lawsuits.  Typically the question is how many employees do I need to  look at to have a statistically significant sample?

In some instances it’s not feasible to collect data or get all the records for
all the employees of a particular company. Sometimes the data is kept
in such a way that it takes a lot of effort to get that information.  In
other instances it is a matter of the limitations of imposed by the court.

In any event, that’s a question that comes up a number times in wage and hour lawsuits particularly ones involving class or collective actions. So what’s the answer?

Generally, the size of the sample needs to be sufficiently large so that it is representative of
the entire employee population. That number could be relatively small say 40 employees or relatively large say to 200 employees depending on the number of employees at the company and the characteristics of the employee universe that is being analyzed.

For example if there are no meaningful distinctions between the employees in the universe, that is
it is generally accepted that all the employees are pretty much all
similarly situated, then a sheer simple random sample could be
appropriate.

That is, you could simply draw names from a hat, essentially. A simple random sample typically requires the smallest number of employees.

If there are distinctions between employees that need to be accounted for, then
either a larger sample or some type of stratified sampling could be appropriate.
Even if there are distinctions between employees, if the sample is sufficiently large then distinctions between the employees in the data could take care of themselves.

For instance, assume that you have a population of 10,000 employees and they are
divided into four different groups  that need to be looked at differently.

One way to do a sample in this setting is to sample over each of the different groups of employees separately. The main purpose of the individual samples is to make sure that you have the appropriate number of employees in each of the different groups. That is, to make sure that the number of employees in the different samples are sufficiently representative of the distribution of the different groups of employees in the overall population.

Another way to do this is to simply just take a large enough sample so that the distinctions take care of themselves.  If the sample is sufficiently large then the distribution of the different groups of employees in the sample should on be representative of the employee population as a whole.

So in this example, if there is a sufficiently large sample it could be okay to use a simple random sample and you would get to the same point as a more advanced stratified type of approach.

The key however is to make sure that the sample is sufficiently large that of course depends on the overall population and the number of groups of employees being studied.

Update of our Mexican work life paper on the way!

We’re pleased to let you know that we have released our most current database: MMP150.  The MMP150 database consists of 150 communities, which includes the original 143 communities plus 7 new additional communities: 4 from the state of Jalisco and 3 from the state of Puebla.  MMP150 – PERS file provides individual level data for 157,879 persons;  the MMP150 – MIG file provides detailed information about 8,052 heads of households with migration experience to the U.S; and the MMP150 – HOUSE file provides information about 24,989 households.   The COMMUN file now provides homicide rates at the municipio level from 1990 to 2013.

 MMP150 databases are available in SAS, Stata, SPSS, and also on CSV. To access these datasets, please visit the OPR’s archive webpage.  We will be updating both the NATLYEAR and NATLHIST files over the summer.

http://mmp.opr.princeton.edu/databases/dataoverview-en.aspx

 

Median rent rose in San Antonio, Laredo, and Corpus Christi from January 2015 to February 2015.

Median house prices for all three MSAs (metropolitan statistical areas) rose from January 2015 to February 2015.

 

Image source: http://www.asemooni.com/news/economic-news/the-president-agreed-with-the-increase-in-housing

The health care and social assistance industry gained 3,000 jobs from January 2015 to February 2015. Compared to February 2014, the cumulative number of jobs added in this industry is 43,500, an annual increase of 3.3%.

Source:http://www.tracer2.com/admin/uploadedPublications/2133_TLMR-March_15.pdf

Image source: http://blogs.wsj.com/health/2012/01/06/health-care-sector-adds-jobs-as-overall-employment-picture-looks-healthier/