


Adonis Yatchew Professor of Economics, University of Toronto EditorinChief Emeritus,
The Energy Journal Vice President for Publications,
International Association for Energy Economics Contact
information
Department of Economics University of Toronto 150 St. George St., Room 278 Toronto M5S 3G7 Tel:
(416) 9787128 AWARDS AND
DISTINCTIONS
Outstanding Contributions to the Profession, International Association
for Energy Economics, June 2018. For details and previous award winners see http://www.iaee.org/en/inside/awardprofession.aspx.
Senior Fellow, US Association for Energy Economics, June 2014. For
details and previous award winners see https://www.usaee.org/awards.aspx.
TEACHING 20232024
As the world lurches into an energy transition,
geopolitics has reclaimed center stage. How does one begin to develop an
understanding of energy issues in a world faced by multiple global
challenges? Among the questions woven into energy courses that I teach are
the following: ·
How has the war in
Ukraine altered the global energy transition? ·
How do longterm
political trends affect energy policy and regulation? ·
How does one think
about the proper role of government in energy markets? ·
What kinds of
incentives are effective in driving innovation? Graduate Courses ECO 2400F Econometrics
I, Ph.D. (joint with Yuanyuan Wan) This
course is devoted to a review of introductory mathematical statistics.
Parameter estimation and hypothesis testing are discussed from both the
Bayesian and classical standpoints. In the second half these techniques are
applied to the standard linear regression model. While this course is
primarily theoretically oriented, empirical implementation is addressed in
computer homework assignments directed toward applied economic problems. ECO 2401S Econometrics II, Ph.D. (joint with Victor
Aguirregabiria) This
course develops the conventional econometric tools of the applied economist.
Subjects include asymptotic and bootstrap inference methods, general least
squares and its applications (e.g. heteroscedasticity, autocorrelation,
multivariate regression, mixed estimation, panel data), models where right
hand side variables are correlated with residuals (e.g. errors in variables,
simultaneity), GMM estimation, basic elements of time series analysis
(stationary models, unit roots and cointegration, spectral analysis) and
nonparametric and semiparametric methods. Time permitting, additional topics
which may be covered include duration data and hazard function models, and limited dependent variable models. ECO 3400S Topics in
Econometrics (team taught) This a special topics course, team taught by
econometricians in the Economics Department. ECO 1960S Energy and
Regulation This
course provides a general treatment of the economics of energy markets and
the use of regulation in addressing environmental and other issues. A central
theme is the search for an appropriate balance between market forces and
regulatory/government intervention. Topics include oil, natural gas, coal and
electricity markets, global warming and other externalities, networks,
feedintariffs, carbon taxes, ‘capandtrade’ and incentive regulation. (This course is crosslisted
as a senior undergraduate course, Eco 414S. See below.) Undergraduate Courses ECO 314F Energy and the Environment The war in
Ukraine has The Covid19 pandemic had sigfis led to
enormous changes in energy markets.
Oil demand plummeted as did oil prices. At one point,
Canadian oil was selling for about the price of a latté. This course surveys
important features of energy markets and related environmental challenges in
a rapidly changing world. One of the central objectives is to provide an
understanding of the key economic tools needed to analyse these markets and
to develop an appreciation for the political and geopolitical centrality of
energy issues. A related objective is the development of a framework for
understanding the public discourse on energy and the environment. Topics
include the hydrocarbon economy (oil, natural gas and coal), electricity
markets, global warming and other externalities, renewable energy and
conservation, carbon pricing, sustainability, the geopolitics of energy, and
the impacts of the current pandemic on energy markets. ECO 414S Energy and Regulation This
course provides a general treatment of the economics of energy markets and
the use of regulation in addressing environmental and other issues. A central
theme is the search for an appropriate balance between market forces and
regulatory/government intervention. Topics include oil, natural gas, coal and
electricity markets, global warming and other externalities, networks,
feedintariffs, carbon taxes, ‘capandtrade’ and incentive regulation.
(This course is crosslisted as graduate course Eco 1960S. See above.) ENV462S Energy and Environment: Economics,
Politics, and Sustainability This
course assembles a handful of ideas that are foundational to appreciating the
complexities of today's energy issues. Drawing on history, economics, politics and geopolitics the course develops a series of
simple narratives which provide a basis for thinking about these challenges.
The course will cover energy markets, energy security and its geopolitical
implications, and the increasing role that sustainability plays in setting
policies. The RESEARCH
Books, Edited Volumes ·
Semiparametric Regression for the Applied Econometrician, A. Yatchew, 2003, Themes in Modern Econometrics, Cambridge
University Press. For details, data and code see below. ·
Chinese Energy Economics, Special Issue of The
Energy Journal, Edited by Ying Fan and Adonis Yatchew, 2016. Selected Papers ·
Carbon Pricing and Alberta’s
EnergyOnly Electricity Market, Derek E. H. Olmstead and Adonis Yatchew, Electricity
Journal, 35:4, May 2022. ·
How Scalability is Transforming
Energy Industries, A. Yatchew, Energy Regulation
Quarterly, 2019, 7:2, 3544. ·
Discerning Trends in Commodity
Prices, A. Yatchew and D. Dimitropoulos, Macroeconomic Dynamics, 2017,
Vol.22, Special Issue 3, Dynamics of Oil and
Commodity Prices, 683701, doi:10.1017/S1365100516000511. ·
Rational vs.
‘FeelGood’ Carbon Policy – Transferability, Subsidiarity and Separation,
A. Yatchew, 2016, Energy
Regulation Quarterly, 4:3, 3140. ·
Integration of Renewables into
the Ontario Electricity System, B. Rivard and A. Yatchew, 2016, The Energy
Journal, vol 37, Special Issue 2, pp. 221242. ·
Is Productivity Growth in
Electricity Distribution Negative? An Empirical Analysis Using Ontario Data,
D. Dimitropoulos and A. Yatchew, 2017, The Energy
Journal. ·
Economics of
Energy: Big Ideas for the
NonEconomist, A. Yatchew, 2014 Energy Research and Social
Science, 1(1), 7482. ·
Support Schemes for Renewable
Energy: An Economic Analysis, R. Green and A. Yatchew 2012, Economics of
Energy & Environmental Policy, 1, 8398. ·
Ontario FeedinTariff Programs,
A. Yatchew and A. Baziliauskas 2011, Energy Policy, 39, 38853893. ·
Nonparametric Least Squares
Estimation in Derivative Families, Peter Hall and A. Yatchew 2010, Journal of
Econometrics, 157, 362374. ·
Nonparametric
Estimation When Data on Derivatives are Available, Peter Hall and A. Yatchew 2007, Annals
of Statistics, 35:1, 300323. ·
International Welfare
Comparisons and Nonparametric Testing of Multivariate Stochastic Dominance,
A. Yatchew and B. McCaig, 2007, Journal of Applied Econometrics, 22:5,
951969. ·
Nonparametric State Price
Density Estimation Using Constrained Least Squares and the Bootstrap A.
Yatchew and W. Haerdle, 2006, Journal of
Econometrics, 133:2, 579599. ·
Unified Approach to Testing
Functional Hypotheses In Semiparametric Contexts,
with Peter Hall and A. Yatchew, 2005, Journal of Econometrics, 127, 225252. ·
Efficient Estimation of
Semiparametric Equivalence Scales With Evidence From South Africa , A. Yatchew, Y. Sun and C. Deri, Journal of Economic and Business
Statistics, 2003, 21, 247257. ·
Hydro One
Transmission and Distribution: Should They Remain Combined Or Be
Separated , with Stephen C. Littlechild and A. Yatchew 2002. ·
Household Gasoline Demand in
Canada, A. Yatchew and J.A. No, 2001, Econometrica,
69, 16971710. ·
Incentive Regulation of
Distributing Utilities Using Yardstick Competition, A. Yatchew, 2001, Electricity
Journal, 5660. ·
Scale Economies in Electricity
Distribution: A Semiparametric Analysis, 2000 A. Yatchew, Journal of Applied
Econometrics, 15, 187210. ·
An Elementary Nonparametric
Differencing Test of Equality of Regression Functions, 1999,
A. Yatchew, Economics Letters, 2718. ·
Nonparametric Regression
Techniques in Economics, 1998, A. Yatchew, Journal of Economic Literature, 36,
669721. ·
An Elementary Estimator of the
Partial Linear Model, 1997, Economics Letters, A. Yatchew, 57,
13543. See also Vol. 59, 1998 4035. ·
Nonparametric
Least Squares Estimation and Testing of Economic Models A.
Yatchew and L. Bos 1997, Journal of Quantitative Economics, 13, 81131. Energy and Carbon
Flow Diagrams
An especially useful visual representation of
the supply of, and demand for energy is depicted in Energy Flow diagrams,
(also known as Sankey Diagrams). ‘Pipe’ diameters are intended to be roughly
proportional to energy flows. The boxes on the left margin depict supplies of
energy from various sources such as hydrocarbons (natural gas, coal,
petroleum), renewables (hydraulic, wind, solar, geothermal and biomass) and
nuclear. Next, consider the demand side which is divided into residential,
commercial, industrial and transportation uses (pink boxes). The energy in
each sector either produces ‘energy services’ or is lost in the form of
‘rejected energy’ (gray boxes). The
least efficient sector is transportation where almost 80% of the energy is
‘rejected’. The most efficient is the
industrial sector where only 20% is ‘rejected’. Overall, it might appear that humans are
very inefficient, ‘wasting’ well over half of the energy we produce, but this
is primarily a reflection of the state of technology and the Second Law of
Thermodynamics which we will discuss below. In fact, we have already come a
long way. Fires used to heat and cook
in the preindustrial era ‘wasted’ 95% or more of the energy embodied in the
wood they burned. Carbon Flow diagrams depict carbon dioxide emissions
resulting from the various types of energy sources. 
There has been an explosion in nonparametric regression techniques in
statistics and econometrics, yet the use of these tools by applied economists
has been much more limited. The motivation and purpose of this book is to
provide an accessible collection of techniques for analyzing nonparametric and
semiparametric models. We focus on nonparametric regression, partial
linear and index models which collectively capture the dominant share in the
applied semiparametric literature.
One of the themes is the idea of
differencing which permits the removal of nonparametric effects from the data
in order to estimate parametric effects. The estimated parametric effects
are in turn removed from the original data and the nonparametric effects are
analyzed. The differencing device allows one to draw not only on the
reservoir of parametric human capital, but also to make use of existing
software.
A variety of testing procedures are
covered including simple goodness of fit tests and residual regression
tests. These procedures can be used to test hypotheses such as parametric
and semiparametric specification, significance, monotonicity and additive
separability. Other topics include endogeneity of parametric and
nonparametric effects, as well as heteroskedasticity and autocorrelation in the
residuals. Bootstrap procedures are provided.
Worked examples include estimation of
Engel curves and equivalence scales, household gasoline consumption, scale
economies, semiparametric CobbDouglas, translog and
CES cost functions, hedonic housing prices, option prices and state price
density estimation. The book should be of interest to a broad range
of economists including those working in industrial organization, labor,
development, urban, energy and financial economics.
Programs (most of which are in SPlus) and data for
all exercises and examples in the book are available below. The data sets and programs are offered in
conjunction with the title and are for private use only. Reposting, republishing or other usage or
circulation is not permitted without the express written consent of the author.
Programs
·
Data