The oil and gas extraction industry in Texas gained 2,500 jobs from April 2014 to May 2014. Compared to May 2013, the cumulative number of jobs added in this industry is 9,700, an increase of 9.4%.
Image Source: http://www.eliteexploration.com/texas-oil-gas-companies/
Compared to May of last year, all of the main MSAs (metropolitan statistical areas) in Texas saw an annual increase in the number of job openings and decrease in the searcher-to-job opening ratio.
Overview
In this case, several truck driver plaintiffs filed a FLSA and wage and hour lawsuit against a petroleum transport company that provides crude oil transportation services. Its drivers pick up crude oil from well sites and deliver that oil to refineries, pipelines and storage facilities, etc. The driver’s compensation plan for its drivers included: a) pay per load for transporting the oil; and b) hourly pay for certain other activities.
Pay Per Load. For transporting a load of oil, the company paid the drivers a certain percentage of the price it received from its customer for transporting that load.
The number of job openings in Texas decreased from 361,597 in April 2014 to 342,800 in May 2014. The median number of job searchers per job opening across all MSAs (metropolitan statistical areas) and occupations in Texas was 1.12 in April 2014 and 1.29 in May 2014.
In a recent document and interview, GM has laid out its plan to compensate people injuried or those with familiy members who were killed due to product defects. The full plan can be found here. Some highlights are below.
Types of claims covered by plan:
1. Individual Death Claims
2. Category One Physical Injury Claims: claims involving quadriplegic injury,
paraplegic injury, double amputation, permanent brain damage requiring
continuous home medical assistance, or pervasive burns encompassing a
substantial part of the body.
3. Category Two Physical Injury Claims: claims, other than Category One
Physical Injury Claims, that, within 48 hours of the accident, require either
overnight hospitalization of one or more nights or, in extraordinary
circumstances as determined on a case by case basis by the Administrator,
outpatient medical treatment
METHODOLOGIES FOR CALCULATING COMPENSATION
1. Track A – Presumptive Compensation
The Track A presumed methodology relies upon a combination of the decedent’s
historical earnings and personal details with assumptions of likely future events based
upon multiple sources of publicly available national data including the Bureau of Labor
Statistics and the Internal Revenue Service. Eligible Claimants need not present detailed
computations or analyses
This Track A presumed methodology ensures consistent economic loss calculations for
similarly situated victims (i.e., same age, number of dependents and income level)
2. Track B – Complete Economic Analysis
Track B entails a complete, comprehensive economic loss analysis of the decedent’s past,
present and assumed future income. The Facility will consider the financial history of the
decedent through incorporation of submitted individual income data, including past,
present and future earnings, wage growth, work life expectancy, etc., as well as other
case-specific information and circumstances of the decedent that the claimant believes
the Facility should consider in determining the total value of the claim. I
Non-economic losses will also be determined as follows.
• $1,000,000 for the death of the decedent, and
• $ 300,000 for the surviving spouse, and
• $ 300,000 for each surviving dependent of the decedent.
In addition, life care plans to cover future medicals will also funded for injured individuals needing future care.
In May 2014, VA launched the Accelerating Access to Care Initiative, a nation-wide program to ensure timely access to care. As part of the Initiative, the VHA identified Veterans across the system experiencing long waits. The VA also published a 50 page report on the delays experienced by VA patients. Among the findings, they found:
1. The VA scheduling system resulted in confusion among
scheduling clerks and front-line supervisors.2. Meeting a 14-day wait-time performance target for new appointments was simply
not attainable3. The concept of “desired date” is a scheduling practice unique to VA, and difficult
to reconcile against more accepted practices such as negotiating a specific
appointment date based on provider availability, or using a “return to clinic”
interval requested by providers.4. . Overall, 13 percent of scheduling staff interviewed indicated they received
instruction (from supervisors or others) to enter in the “desired date” field a date
different from the date the Veteran had requested. At least one instance of such
practices was identified in 76 percent of VA facilities. In certain instances this
may be appropriate (e.g., a provider-directed date can, under VA policy, override
a date specified by a patient), but the survey did not distinguish this, nor did it
determine whether this was done through lack of understanding or malintent
unless it was clearly apparent.5. Eight percent of scheduling staff indicated they used alternatives to the Electronic
Wait List (EWL) or Veterans Health Information Systems and Technology
Architecture (VistA) package. At least one of such instance was identified in 70
percent of facilities. As with desired date practices, we did not probe the extent
to which some of these alternatives might have been justified under VA policy.
The questionnaire employed did not isolate appropriate uses of external lists.6. Findings indicate that in some cases, pressures were placed on schedulers to
utilize inappropriate practices in order to make waiting times (based on desired
date, and the waiting lists), appear more favorable. Such practices are
sufficiently pervasive to require VA re-examine its entire performance
management system and, in particular, whether current measures and targets for
access are realistic or sufficient.7. Staffing challenges were identified in small CBOCs, especially where there were
small counts of providers or administrative support.
Excerpted from: “Solar company spinoffs lure investors with dividends”, by Reuters
Long shunned by cautious investors, solar companies have hit on a new way, [known as Yield Companies or Yield Cos], to deliver returns to shareholders. that could attract new money to an industry notorious for its stock price volatility.
Yield cos… own and operate solar assets under long-term power-purchase agreements with utilities – a guarantee of stable cash flow.
SunEdison Inc is the first of a wave of companies preparing to bundle up existing solar power plants and then spin them off into separate entities, known as “yield cos”, to raise money to build new plants.
The promise of regular dividend payouts, hitherto unknown in the solar industry, offers an entry point to the sector for retail investors and is expected to generate huge demand when these companies go public, analysts and investors said.
Most of this cash will be paid out as dividends, with the remainder re-invested in new plants, a valuable source of funding for parent companies that will retain a sizeable stake in the new entities.
The only U.S.-listed yield co that currently holds solar assets is power company NRG Energy Inc’s NRG Yield Inc , which made its stock market debut last July [2013].
The stock for NRG increased from about $30 at its offering to over $50 on July 7, 2014.
Dwight Steward wrote:
Cattle prices in Texas will continue to go up. There are several factors that point to a continued increase in prices.
1. The overall number of cattle in Texas has fallen. From 2012 to 2013, the total number of cattle on feed decreased by over 600,000 from 11.9 M to 11.3M which is a 5% reduction. As with anything, the fewer that you have the more that they will cost.
2. The number of breeding cows has decreased even more. From 2012-13, the number of breeding cows decreased 12%, from 4.57M to 4.02M. The smaller number of breeding cows in Texas means that there will be fewer calves born in subsequent years which absent significant imports of cattle into the state, means that there will be smaller herds into the indefinite future for Texas.
3. The Fracking Boom. The fracking boom has made cattle ranching relatively more expensive in certain areas of the state. In some areas, such as South Texas, cattle ranchers have found that it is more profitable to sell or lease their land for oil and/or gas exploration.
See the cattle price data here;
https://docs.google.com/spreadsheets/d/15jia1S9wv7BVUzGngeHoX-Ac6ERhCWTrzqIj2GUR4dA/edit?usp=sharing
A person’s earnings will tend to increase as they age…to a certain point. After that point, which is around age 46 or so depending on the person’s education level and occupation, the person’s earnings will tend to decrease as the age.
The age-earnings profile captures this phenomenon. The age-earnings profile is calculated from data sources like the Current Population Survey from the U.S. BLS
Here is a question that we recently addressed:
Q: Any idea on how to create an age-earnings profile for someone specifically with an MBA? Are there data somewhere that have created such a profile? I can see using the ACS (American Community Survey) to look at people by age who have a master’s degree and are employed in management occupations. Anything more specific?
A: The ACS would be a good start and would allow you to estimate an age-earnings profile more specific to the facts in your case. In our cases we generally estimate the age earnings profiling using a regression model. In our cases, there are generally not enough observations to filter for all the specific facts that we want to account for so a regression approach has been useful for us.
Standard age earnings profile regressions from labor economics models, see for example papers by Mincer et al., Lazear et al, , Welch et al. and many more, regress earnings on experience, experience squared, occupation variables, geographical variables, and education variables.
Schumpter @theeconomist argues that State owned enterprises that own significant portions of many of the major companies in their country have found ways to continue to survive and even grow. Schumpter, referencing a new book “Reinventing State Capitalism” says that even though China and Russia own approximately 60% and 35% of their respective stock market capitalizations, some of the new State Owned Enterprises in some ways resemble private sector firms.