Javier Oyakawa Center for Community and Business Research
Institute for Economic Development University of Texas at San
Antonio Paper presented at the 2015 Users Conference, Austin,
Texas, May 20, 2015 Energy Prices and the Eagle Ford Region
Slide 2
ABOUT MYSELF Economics researcher at the Center for Community
and Business Research (CCBR). Studied economics at the PhD degree
level at the University of Texas at Austin and worked on
computational general equilibrium models for analyzing trade and
fiscal policies. In early 2005, together with Dr. Mark Hager and
Robert McKinley, UTSA Associate Vice- President for economic
development, the CCBR began its activities. In early 2011, together
with Dr. Dominique Halaby, I designed, developed, and implemented
the first Eagle Ford Shale economic impact study, and continued to
be the lead investigator in all following studies. Later in that
year, I was the Interim Director of the CCBR, between the months of
May and October while preparing the second report for the Eagle
Ford Shale. I have taught economics courses at several universities
in Texas and Per. In 2000-2001 I was full-time instructor at
Trinity University in San Antonio, and in 2002 I was a full-time
professor at the Catholic University in Per.
Slide 3
I.Introduction. II. Economic Impacts and Official data III.
Hydraulic fracturing and horizontal drilling IV. Comparing costs
conventional and shale gas wells V. Oil, gas prices different
effects in different plays VI. Some Eagle Ford Shale developments
VII. Community issues, the boomtown framework VIII. Community
issues, the resource curse framework IX. Comments on Mexicos energy
reform. Presentation topics:
Slide 4
I.INTRODUCTION
Slide 5
Four shale oil and gas plays in Texas
Slide 6
Slide 7
Slide 8
Slide 9
II. Economic Impacts and Official Data
Slide 10
Official employment data and employment impact studies show
different aspects of the processes and need to be understood in
context.
Slide 11
Source: Texas Workforce Commission, the Quarterly Census on
Employment & Wages (QCEW) data for the fourth quarter of 2009
and 2011.
IV. COMPARING COSTS AND PRODUCTIVITY: VERTICAL AND HORIZONTAL
DRILLING
Slide 25
In the initial years of the combined use of fracking and
horizontal drilling: Cost ratio of horizontal versus vertical wells
is approximately 2 to 1, but varies by well. Production ratio for
horizontal wells versus vertical wells is approximately 3.2 to 1.
Also varies by well. http://www.horizontaldrilling.org/
Slide 26
But over time technology has become more efficient
V.OIL AND GAS PRICES. DIFFERENT EFFECTS ON DIFFERENT PLAYS
Slide 29
Slide 30
Slide 31
Slide 32
Slide 33
Slide 34
Why did this happen?
Slide 35
Eagle Ford Shale produces oil and natural gas liquids in large
quantities. Natural gas producers moved from the Barnett Shale to
the Eagle Ford Shale as the price of dry natural gas declined.
Drilling permits in the Eagle Ford soared while in the Barnett
Shale collapsed.
What is the effect of a decrease in the price of natural gas in
the Eagle Ford after 2008?
Slide 39
The final estimates included the price of oil, the price of
gas, and a dummy variable (D): Parameter Estimates
VariableDFEstimate Standard Error Intercept11.89181.19101.590.1181
lnPoil1 0.83470.26333.170.0025 lnPgas1 -0.6775 0.1644-4.120.0001
DmlnPoil1-0.05480.0273-2.010.0497 THE LOWER THE PRICE OF GAS THE
MORE DRILLING ACTIVITY IN THE EAGLE FORD SHALE Source: Economic
Impact of the Eagle Ford Shale. CCBR study Sept 2014
Slide 40
AGAIN: THE LOWER THE PRICE OF GAS THE MORE DRILLING ACTIVITY IN
THE EAGLE FORD SHALE AFTER 2008. DIFFERENT FROM WHAT HAPPENED IN
THE BARNETT SHALE.
Slide 41
VI.SOME EAGLE FORD SHALE DEVELOPMENTS
Slide 42
Employment Change by County County Total EmploymentPercent
Change (Annualized) 20012006201020132001-20062006-20102010-2013
Atascosa9,1939,1699,34613,021-0.050.4811.69
Bee8,4448,4508,7589,9240.010.904.25
DeWitt6,8686,9366,5187,3880.20-1.544.26
Dimmit2,6962,6933,0835,727-0.023.4422.93
Frio4,0194,2064,8596,0870.913.677.80
Gonzales5,8826,5706,4156,7772.24-0.601.85
Karnes4,0113,8563,7164,768-0.79-0.928.66 La
Salle1,2621,6211,8273,2585.133.0421.27 Live
Oak2,8622,9173,0154,4280.380.8313.67
Maverick11,32014,05216,18816,9124.423.601.47
McMullen251203256572-4.165.9730.73
Webb70,55984,50785,40492,8313.670.262.82
Wilson5,3836,2506,4907,0723.030.952.90
Zavala2,7272,8462,9522,5530.860.92-4.73 EFS64,91869,76973,42388,487
1.451.286.42 Texas 9,350,770 9,922,313 10,182,150
11,031,9071.190.652.71
Slide 43
County Population Change by CountyAnnualized Change Percent
20012006201020132001-20062006-20102010-2013
Atascosa39,82843,05944,95847,0931.571.081.56
Bee31,69531,97731,90232,7990.18-0.060.93
DeWitt20,06620,10820,04720,5030.04-0.080.75
Dimmit10,0309,97210,03210,897-0.120.152.80
Frio16,31516,72017,23318,0650.490.761.58
Gonzales18,71419,63319,82820,3120.960.250.81
Karnes15,34014,98514,86515,081-0.47-0.200.48 La
Salle5,9346,5496,8987,3691.991.312.23 Live
Oak12,07111,55911,54611,867-0.86-0.030.92
McMullen819765712764-1.35-1.782.38
Maverick47,59450,95154,47755,9321.371.690.88
Webb200,347229,307251,320262,4952.742.321.46
Wilson33,40839,00743,08345,4183.152.521.77
Zavala11,59611,64211,72712,1560.080.181.20
EFS263,410276,927287,308298,256 1.010.921.25
Texas21,319,62223,359,58025,245,17826,448,1931.841.961.56
Slide 44
County Offenses per 100,000 PopulationPercent Change
(Annualized) 20052008201020132005-20082008-20102010-2013
Atascosa2,0332,3102,5442,4464.344.95-1.30 Bee
*698594606351-5.220.96-16.65
DeWitt2,4041,9451,4862,761-6.82-12.5822.93
Dimmit3,9983,7422,0444,203-2.17-26.0927.16
Frio2,9792,0072,0992,275-12.332.262.72
Gonzales2,8642,4262,6803,353-5.385.117.75
Karnes1,6172,1932,9863,00410.6916.700.19 La
Salle1,5131,7141,0616794.23-21.32-13.84 Live
Oak9898718922,343-4.131.1937.97
McMullen1,0141361,1245,236-48.83187.5767.03
Maverick3,1933,7983,0992,5215.95-9.66-6.65
Webb6,2206,7275,2064,5762.65-12.03-4.21
Wilson1,4001,2001,2601,387-5.012.473.25
Zavala2,7322,9081,6141,7192.10-25.502.13
EFS27,43425,84423,49532,276 2.37-9.4911.16
Texas4882450042193654-2.68-3.17-4.68 * Only included Bee SO
Slide 45
Eagle Ford Capital Expenditures 2013-2015 Expected Capital
expenditures budget for 2015: $16 Billion (Shale Experts estimate)
Capital expenditures for 2014: $25.4 Billion (Shale Experts
estimate) Capital expenditures for 2013: $28 Bill (McKenzie
estimate)
Slide 46
Total impact in three scenarios 2023 in millions Low estimate
Moderate estimate High estimate Economic impacts Output
$37,105$106,394$230,734 Employment, full-time 55,328150,793361,974
Payroll $3,174$9,636$20,806 Gross regional product
$19,561$61,816$139,539 Estimated local government revenues
$1,131$3,742$8,849 Estimated state revenue, incl. severance taxes
$1,131$3,774$8,854 Source: Economic Impact of the Eagle Ford Shale.
CCBR study Sept 2014
Slide 47
Comparisons of population growth rankings The counties that had
faster growth during the 2001- 2006 period also had faster growth
during the 2006- 2010 period. The ranking of counties population
growth during the 2010-2013 period has no resemblance to the
previous two periods.
Slide 48
County Population Rank of Percent Change
2001-20062006-20102010-2013 Atascosa676.5 Bee101311 DeWitt121415
Dimmit13111 Frio985 Gonzales8914 Karnes141516 La Salle363 Live
Oak1512 McMullen16 2 Maverick7413 Webb228 Wilson114 Zavala1110
EFS559 Texas436.5
Slide 49
Population Rankings Spearman Correlation Coefficients
N=16Prob>|r| under H0: Rho=0 2001-20062006-20102010-2013
2001-20061.00000.92650.2355
By the late 1970s, a so-called boomtown model or social
disruption model emerged as a prominent framework among researchers
to describe the rapid growth that overwhelms local governments and
permanently alters social relationships. The body of evidence
tended to find a mix of positive and negative economic impacts to
local residents, contrasted with highly negative social impacts.
Jeffrey Jacquet Energy Boomtowns & Natural Gas: Implications
for Marcellus Shale local governments & rural communities The
Northeast Regional Center for Rural Development The Pennsylvania
State University. Rural Development Paper No. 43, January 2009
Need to be careful when forecasting impacts to avoid inflating
numbers creating confusion. The CCBR prepares estimates under three
scenarios, based on three different price projections from the EIA.
The low estimates scenario assumes prices in the mid $60s for most
of the decade ahead. Just in November last year, six months ago,
some forecasts were extremely optimistic about production growth in
the Eagle Ford this year.
Slide 57
Employment data and employment impacts. The case of McMullen
county with official population in 2012: 726 people
Slide 58
Source: Texas Workforce Commission, the Quarterly Census on
Employment & Wages (QCEW) data for the fourth quarter of 2009
and 2011. Author elaboration
Slide 59
Source: Oyakawa et al. (2012). Workforce Analysis for the Eagle
Ford Shale
Slide 60
How many new jobs are really created?
Slide 61
Source: Jacquet et al. (2011).
http://www.greenchoices.cornell.edu/downloads/development/shale/Workforce_Development_Challenges.pdf
Slide 62
Need for community and regional planning
Slide 63
Source: Jacquet, J The Boomtown Impact model from oil & gas
drilling
http://www.visionwestnd.com/documents/TheBoomtownImpactModelfromOilandGasDrilling.pdf
Slide 64
Projections: population, employment before the Eagle Ford
Developments
The NEDAM model North Dakota Economic-Demographic Assessment
Model (NEDAM) by Leistritz et al. (1982) developed an extensive
analysis and designed a model to ascertain the impacts of major
industrial and resource- based projects. Their model divides
employment into four broad types: major project-related
construction, project-related permanent, project-related temporary,
and non-project employment which they termed baseline.
Slide 70
For population projections, they used a cohort-survival
demographic model, and for employment forecasts they used
information on direct employment from the project itself and on
indirect and induced impacts from input-output multipliers applied
to the projects direct impacts
Slide 71
VIII. COMMUNITY ISSUES, THE RESOURCE CURSE FRAMEWORK
Slide 72
Some studies found that energy industries only impacted
Personal Income growth but had no impact on employment and even had
negative impact on population growth. These results are very
different from the traditional boomtown model. But they try to
emphasize the problems with the natural resource dependence or
resource curse
Slide 73
CONTROVERSY ON THE IMPACTS OF NATURAL RESOURCES Several studies
indicate that: there is an inverse relationship between the rate of
economic growth and natural resource dependence at the
international level. (Sachs and Warner 1995, 1999, 2001) Other
papers show that: the natural resource curse is present at an even
more disaggregated county level, as highlighted by a brief case
study of Maine and Wyoming (James and Adland, 2010) On the
contrary, other studies show that: for counties in the U.S., an
increase in natural gas production has not been a natural resource
curse for local economies. (Jason Brown, 2014)
Slide 74
With respect to negative crowding out effects of natural
resource curse Jeremy G. Weber 2014 found no evidence of the curse.
Combined, these statistics imply that natural gas extraction was
associated with higher average educational attainment among the
local adult population, with high school graduates replacing high
school non-graduates.
Slide 75
In 2012, I developed a research using input-output tables and
occupational matrices with similar results to Jeremy Weber
Slide 76
IX. MEXICOS ENERGY REFORM
Slide 77
PowerPoint presentation by Cacheaux, Cavazos & Newton
Mexicos Energy Reform Feb 25, 2015, San Antonio, TX
Slide 78
Slide 79
THANK YOU! Javier Oyakawa The University of Texas at San
Antonio | Institute for Economic Development 501 W Csar E. Chvez
Blvd | San Antonio, TX 78207 210-458-2036 | [email protected][email protected]