Skewed Employment Impacts
Issue
The truth concerning some economic impact models is seldom revealed in the media, much less a publication such as The Washington Post. The Post recently printed an article (PDF) on organizations overstating their employment economic impacts. In the case cited, the numbers are made up to persuade gullible lawmakers to reduce regulation to create more jobs.
Employment Impacts
In all fairness to the economists who manufacture numbers, if lawmakers do not take the time to understand the data they use to make policy decisions, who is at fault? In the article some analysts published their model methods, and I applaud that. You may not agree with what they have done, but at least you can evaluate the model accuracy.
Employment impacts include:
- Direct – The actual number the company will supposedly hire.
- Indirect – The number of employees other businesses will hire as a result of direct hiring.
- Induced – The number of employees hired as a result of a rising economic tide in the study area.
Often the numbers are summed and presented as direct impact. In the article, one economist argues that induced jobs are accurate, and they are if you count food service and lawn care workers. But let’s not confuse those jobs with high-paying drilling jobs by providing a total without accompanying employment detail.
Assumption Pitfalls
It is the assumptions, then, that are at the heart of the debate. Two common mythological tweaks that significantly change employment impacts are geography selected (not discussed), and initial direct impact calculations. The article provides an example of a flawed direct assumption:
“The Wood Mackenzie study also makes assumptions about current policy. For example, it assumes that current regulations limit the number of Gulf of Mexico exploratory wells to 20 a year. But the number of exploration wells being drilled now is already well above that. As a result, gulf exploration would have little effect on job creation.”
This results in an estimate that is the equivalent to taking a 10 year old employment number, taking the difference from that time period to present and stating it as the new impact!
Conclusion
Currently firms that sell impact software have been unwilling to set guidelines for appropriate use of their software. A simple one is to require publishing model assumptions. It is true that some information is confidential to organizations. But on the other hand, if one is asking for public support to do something that benefits your organization, is it not reasonable to provided the data behind your model? Kudos to The Washington Post for publishing this piece. It is clear we need more transparency in the impact business.
Hotel Occupancy and Revenue Per Room
The Issue
The Post and Courier recently published and article on the regional hotel occupancy forecast for 2011. We are not exactly sure how they derived these numbers, but they are important enough in this community that we need to shed some light on the impact of these data.
I am not convinced there is going to be a rebound in occupancy levels with national growth recently being reported to be under 2 percent. Having said that, those results are probably statistically insignificant as a result of noise in the data. In addition, we always need to include this caveat in South Carolina hotel research: With any inkling of a hurricane, all bets are off. This is one reason that August, September and October tend to be very volatile months, with occupancy slipping from highs achieved in the first six months of the year.
Demand, Occupancy and Money: The Trifecta of the Hotel Business
To make forecasts in the hotel industry, a researcher needs historical occupancy data. My source is the venerable STR Global. There definitely is seasonality to these data, so I stay with the annual data which are adjusted slightly by STR at the end of each year.
I reviewed two data sets: occupancy and revenue per available room (RevPAR). I chose to compare three geographies; Charleston/West Ashley, the state of South Carolina and the entire nation (PDF). It appears that Charleston has done a better job of managing occupancy than the state as a whole, but has paid the price in a lower RevPAR. Instead, it opted for market share. In a market with declining demand, hotels need to create and execute a strategy to grab market share. However, if hoteliers believe there is going to be a measurable increase in demand, keeping prices high likely would be the winning strategy. As capacities creep to more than 80 percent, they can demand higher room rates. Unfortunately, this is not likely the baseline scenario going into 2011.
Community Economic Impact
A back of the envelope calculation nets the following impacts: On average there about 6,ooo hotel rooms in STR’s study area. A calculation using annual RevPAR, occupancy and days returns a gross annual income of $147 million. A small adjustment of just 1 percent in occupancy increases this number by $2.1 million. In 2005 the average daily rate, sightly different than RevPAR, was $128.61 with occupancies at 70 percent. Those numbers result in $51.5 million positive difference in revenue.
Therefore, from a community standpoint, it is important to consider the effect policy has on these numbers. As we can see, small changes in the customers perception of Charleston and/or the state of the economy can and do have significant impact occupancy and room rates, which ultimately affect the community as a whole.
Deep Water Horizon Rig Employment
Off-Shore Moratorium
The economic impact of shutting down a deep water drilling rig is no doubt massively expensive. But employment impact is different. As a benchmark, the employment on the BP rig was 126 persons. It is reported that wages average about 100k per year for those workers. However, I could not find that person anywhere, except in the management ranks according to National OES data! Furthermore, most if not all support workers, according to the BLS, make less than 1/2 that unsubstantiated amount.
Interestingly, as soon as we get into a multiplier discussion, the numbers start off ridiculously high and go up from there. But a multiplier over two is not reasonable or supported in any research and especially not in this case. One primary reason is the service nature of the JOBS we are talking about, NOT the industry multipliers.
Rig Count
Of all the rigs out there, only 4% are off shore! (Baker Hughes) Therefore few if any support persons are going to be affected by a stoppage of drilling; as a result of 94 percent of their support services not being located off-shore. A potential economic impact is close to 400 million a year, which includes a multiplier. More likely however, those wages are moved to another location, or just paid, the result being no impact. The reason is most companies can not afford to idle (loose) those skilled workers.
Simple calculation: (number of rigs, 33 * employment, 126/rig * wages, 100k)
Economic-Ecologic Commodity Flow Impact
Detailed Example of Economic-Ecologic Commodity Flows
The ‘TEAM’ model has done the heavy lifting calculating coefficients for a ecologic commodity flows. The classification was first created by Johnson and Bennett (1981). They used the ecologic terms commodities for inputs and sinks for discharges or outputs. Miller and Blair (2009)
The ecologic matrix is defined using matrix algebra. In example (econ_ecol) (pdf), matrices A, R and Q are created from the table of commodity flows. Matrices R* and Q* are calculated using the following formula:
R* =R(I – A)ˉ¹ Reflect the amount of ecologic inputs required directly and indirectly to deliver a dollar’s worth of industry output. In the example, 0.455 represents 0.455 units of water required to deliver a dollar’s worth of agricultural products!
Q* =Q(I – A)ˉ¹ Reflect the amount of ecologic output associated directly and indirectly with a dollar of industry output. In the example, 0.358 means that associated with one dollar’s worth of manufacturing goods to final demand is production of 0.358 units of hydrocarbon pollutants!
Industry may shy from these formula. The opportunity for industry however is to review manufacturing processes using these data to uncover opportunities to reduce waste or identify material/process substitutions (cost savings). For those interested in economic-ecologic impact, this opens, for the first time through the TEAM model, the capability for applied analysis in both industry and transportation development projects.
Benefits of Clean Energy
EPA has just released a resource for states and other interested parties for assessing the benefits of clean energy. This document is a absolute necessity for any organization which analyzes energy development, production, transmission and the associated effects these systems have on economies, public health and policy.
Assessing the Multiply Benefits of Clean Energy(pdf)
Travel (Tourism) Impact in South Carolina
South Carolina Parks and Recreation and Tourism, completed their 2008 economic impact of travel in South Carolina. The project was completed by the U.S. Travel Association. This report is based on well established current third part data, including Smith Travel Research (STR Global), BEA and BLS data sets.
Appendix A of the report details the method used to calculate impacts. U.S. Travel Association uses their proprietary Travel Economic Impact Model (TEIM) program which calculates impacts based on a number of inputs. What is intersting about these data is their method of estimating impacts based on travel generated business receipts, employment, and payroll for 16 travel sectors. The data combined then generate a total impact and dollars/job created.
One criticism of these findings is travel is viewed from a single dimension, i.e. dollars flowing into the state. In reality, travel includes dollars both coming into the state and leaving the state. This calculation would provide a true estimate of travel impact and thus travel related employment within a specific geography.
