ABOUT DAN HAMBLIN
Since its formation in 1989, Dan Hamblin & Associates, Inc. has engaged in economic consulting, project management, market assessment, business communications, and modeling and simulation.
In 2005 Dan developed Escalator P– a software tool for managing geothermal bilateral
contracts using W. Michael Warwick’s innovative escalator pricing scheme for
attracting buyers and sellers to a resource thought to be more risky than conventional
fossil and nuclear alternatives.
Before forming his own business, Dan was projects manager for Battelle Memorial
Institute, and research scientist and group leader for Oak Ridge National Laboratory
(ORNL). His interest and experience in modeling and simulation focuses on energy,
technology, and policy issues. He has developed industrial process simulation
models for the Electric Power Research Institute (EPRI) and the Gas Research
Institute (GRI), as well as optimizing simulation residential and commercial
sector energy forecasting models for ORNL and the Bonneville Power Administration
(BPA). Dan has led and conducted risk/benefit assessments of the need for electric
power, broadleaf herbicide use, and bt corn. He worked on assignment for the
BPA Division of Power Forecasting; and developed models for the U.S. Department
of Energy, the Northwest Power Planning Council, and Ontario Hydro. For GRI and
its successor, the Gas Technology Institute, Dan led and participated in several
projects related to technologies for electric power generation– including micro-
and mini-turbine distributed generation systems, stationary fuel cell and hybrid
systems, natural gas combined cycle and renewable energy systems. In 2003 and
2005, Dan worked on projects for the U.S. Air Force, funded through the Portland,
Oregon office of Pacific Northwest National Laboratory. In February 2004, he
completed a report, Economic Analysis– Scenarios Depicting Structural Change
in Volatile Markets for Natural Gas Used to Generate Electricity, in which Chapter
VI. Market Making for Geothermal Power looked at flash geothermal as
case study in concert with a project objective to assess renewable energy potential
on U.S. military property.
In 1979 and 1980, Dan enhanced the Stock Market Game software, by figuring out how to detect the value of stock splits from When
Issued and When Declared prices on the ticker tape, and subsequently and automatically adjust game-player portfolios for the split. He also developed a simple program for discerning blocking factors on the Francis Emory Fitch stock price tape, thus solving a problem that had been a mystery and plague to other institutions trying to use the information. His version of the Stock Market Game was purchased by the Security Industries Association.
Dan received his Doctorate
in Applied Economics from the State University of New York at Buffalo,
where he was awarded three University Fellowships to support his
graduate training. He earned Bachelor of Arts degrees in Mathematics
and Economics with Honors from the University of Kansas, where he
was awarded the Domenico Gagliardo Scholarship as the Outstanding
Senior in Economics, the John Ise Scholarship for excellence in Economics,
and elected to Pi Mu Epsilon– the National Honorary Mathematics Society.
Dan was one of 40 junior faculty selected as post-doctoral program
participants, to attend seminars describing recent developments in
applied economics, conducted by business and economics faculty at
the University of Chicago.
Your fortune teller for predicting
the future of deregulated markets
shadowprice.com is the brainchild
of Dan Hamblin, President of Dan Hamblin & Associates,
Inc. (DH&A), an economic consulting firm located in Fort Wayne,
Indiana. The game developed as an idea for using Monte Carlo algorithms
and methods for clients to discover the best way to differentiate
products and services in nascent markets doomed to hit the ground
market power impediments to competition, as did the deregulated electricity
business. shadowprice.com is a game that's fun to
play but hard to win, which you can download
free of charge to give it your best shot.
It's a customer retention tool and management decision game to help
you successfully compete in a volatile marketplace. For a comprehensive
overview of shadowprice.com and its application
to household electricity retailing in a deregulated market, download
a copy of Batting
Average: A Composite Measure of Risk for Assessing Product Differentiation
in a Simulation Model, written by Daniel
M. Hamblin and Brian T. Ratchford for the December 2002 Winter
Simulation Conference of the Institute for Operations Research
and the Management Sciences (INFORMS).
Dan Hamblin has
used economic theory and operations research methods to disclose impacts
of policy and solve business problems for over 30 years. His
doctoral thesis used the Slutsky Equation to predict how President
Carter’s National Energy Act would change demand for luxury cars
and other cars distinguished by size class.
During his career, Dan has
interdisciplinary projects of the fire drill and multi-year variety
– with as many as 25 scientists, engineers, and market analysts
and distributed an award-winning industry newsletter
and hosted, as a turnkey operation, industry workshops at different
impact assessments of a broadleaf herbicide and a transgenic grain
and applied energy forecasting/technology and policy assessment models
for the residential and commercial buildings sectors; for industrial
plants and processes including pulp and paper, glass, Portland cement,
and petroleum refining; for generic and specific blast furnaces with
competing techniques for reducing metallurgical coke consumption; and,
for the U.S. Energy Economy
and published programming algorithms.
In 2005, Dan developed Escalator P for managing 7x24
wholesale electricity, bilateral contracts for geothermal power. It uses a
market-based pricing mechanism conceived by Mike Warwick, and a clustering algorithm Dan developed in 1980 – to predict the
ratio of future stock splits for the Stock Market Game. Escalator P is a
tool brokers can use to buy and sell geothermal at market-based wholesale
prices. It determines a mutually advantageous green tag distribution and
timing to reduce seller dry hole exploration and development risk and buyer
risk from adverse selection and moral hazard. The clustering algorithm
minimizes CFD settlement payments for this highly volatile wholesale price
Escalator P manages or brokers the demand for geothermal
electricity as a base load resource while it augments the return to supply
through green tags. Without green tags, the competition for new base load
power generation between combined cycle gas turbine and geothermal depends
critically on the natural gas price and the O & M expenditure for geothermal.
For a low-heat-rate gas turbine, and overnight and O & M cost data
describing the Roosevelt Hot Springs Blundell geothermal plant in Utah, a
nomograph discloses preferred regions for geothermal and CCGT, and a
trading range between the two:
(click on table for larger size image)
The nomograph competition for new base load generation is
described in a paper
Dan presented in September 2006 at the annual meeting of the Geothermal
Resources Council. The paper tells how to use Mike Warwick's innovative
pricing scheme and green tags to make money for geothermal supplier,
utility, and power broker. You may also want to connect the dots
between geothermal, natural gas combined cycle, and coal-fired generation
by contrasting utility profitability from a coal and nuclear (low) base
load power cost regime versus a natural gas-fired and nuclear (high) base
load power cost regime.
Dan presented results
of and conclusions from the
base-load-power- cost-regime competition in a poster session at the INFORMS
Winter Simulation Conference held in December 2006 in Monterey, California.
His most stark conclusion was that, under current
environmental regulation enforcement practice, California's accelerated
Renewable Portfolio Standard will export pollution to states that generate
and export electricity from coal.
In October 2007, Dan
presented a paper written
by Lance McKinzie and him to the First European Geothermal Review, sponsored
by BESTEC GmbH in
A sequel to
Dan’s September 2006 paper presented at the Geothermal Resources
Council annual meeting, the new paper described a Latin Hypercube Sample
diagnosis of Escalator P’s vulnerability to insurance hazards. These
could (1) induce geothermal power producers or vendors to default on
contract obligations before a contract matures, or (2) accommodate fraud
by brokers who have better information about present and future wholesale
electricity price than other contract stakeholders. Dan and Lance show how
a simple expert system and a password-protected web site accessible to
stakeholders and independent audit can eliminate the first hazard and
expose evidence of brokerage fraud – in the real-time context of
Escalator P’s contract management. In 2007, the U.S. Supreme Court (reversed itself and) sided with the
EPA in ruling that changes in power plants that may contribute to air
pollution, calculated on an annual basis, can be done only by permit.
Further, a 2007 American Electric Power settlement agreed to pay at least
$4.7 billion to reduce the utility’s chemical emissions by two-thirds
over the next decade. The reversal and settlement, which occurred after Dan
and Lance’s paper was completed, apply to electricity generated from
coal, and should make geothermal more attractive, and Escalator P’s
use for real-time contract management more attractive as well.
In 2009, Dan presented another paper written with
Lance to the 10th International Association for Energy Economics European
Conference in Vienna, Austria. They extended the Latin Hypercube Sample
diagnosis to a formal statistical analysis of Escalator P's vulnerability
to insurance hazards in a turbulent electricity price environment.
In October 2010, Dan presented a paper to the 29th USAEE/IAEE North American Conference in Calgary, Alberta. Using a completely revamped edition of shadowprice.com Autopilot, he examined the welfare impacts of single-provider price discrimination that includes Energy Star technologies on offer from Nash coalition partners. Tables and charts included in the paper were developed on a spreadsheet from shadowprice.com Autopilot input parameters and results.
In October 2015, Dan presented a paper to the 33rd USAEE/IAEE North American Conference in Pittsburgh, Pennsylvania. It was labeled Part 2 of the Calgary 2010 paper, adding 5 additional Energy Star technologies for Nash coalition partner inclusion in the assessment of welfare impacts of single-provider price discrimination. Dan took a second look at the Calgary 2010 scenarios in light of the expanded choices, then looked at welfare impacts if households were willing to pay 3 additional cents/kWh for 21.7% of wholesale kWh from renewable suppliers, or else 5 additional cents/kWh for a third of wholesale kWh from renewable suppliers.
Part 2 added a so-called Floor Space Module to shadowprice.com Autopilot, capable of predicting household response to income elasticities of demand, in light of the difference between housing as an inelastic necessity or an elastic luxury good. This difference sheds light on the paper’s prediction of welfare impacts from suburban migration versus movement back into city centers enlivened by improvements in cultural amenities.
Dan can be reached at email@example.com.