


Adonis Yatchew Professor of Economics, University of Toronto EditorinChief, The Energy Journal Contact
information
Department of Economics University of Toronto 150 St. George St., Room 278 Toronto M5S 3G7 Tel:
(416) 9787128 Recent 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.
Current Teaching
Graduate
Courses Eco 2400F
Econometrics I, Ph.D. (joint with Christian Gourieroux) 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 2403S
Topics in Econometrics, Ph.D. This a special topics course, team taught by econometricians in
the Economics Department. ECO 3502S
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 This course surveys important features of energy markets and
related environmental challenges. One of the central objectives is to provide
an understanding of the key economic tools needed to analyse
these markets. 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,
conservation, carbon taxes and 'capandtrade'. 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
3502S. See above.) ENV462S Energy
and Environment: Economics, Politics, and Sustainability This is an interdisciplinary course that examines key ideas in
economics, politics and security that are essential to understanding energy
and environmental issues. The course will cover energy markets, energy
security, and the increasing role that sustainability plays in setting
policies. 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
1.
Discerning Trends in Commodity Prices, A.
Yatchew and D. Dimitropoulos, Macroeconomic Dynamics, Vol.22, Special
Issue 3, Dynamics of Oil and Commodity Prices, 683701,
doi:10.1017/S1365100516000511. 2.
Rational
vs. ‘FeelGood’ Carbon Policy – Transferability, Subsidiarity and Separation,
A. Yatchew, 2016, Energy Regulation Quarterly, 4:3, 3140. 3.
Integration of Renewables into the Ontario
Electricity System, B. Rivard and A. Yatchew, 2016, The Energy Journal, vol 37, Special Issue 2, pp. 221242. 4.
Is Productivity Growth in Electricity
Distribution Negative? An Empirical Analysis Using Ontario Data, 2015, D. Dimitropoulos
and A. Yatchew, May 2015, forthcoming, The
Energy Journal. 5.
Economics
of Energy: Big Ideas for the
NonEconomist, A. Yatchew, (2014) Energy
Research and Social Science, 1(1), 7482. 6. Support
Schemes for Renewable Energy: An Economic Analysis, R. Green and A. Yatchew
(2012), Economics of Energy &
Environmental Policy, 1, 8398. 7.
Ontario FeedinTariff Programs, A. Yatchew and
A. Baziliauskas (2011), Energy Policy, 39, 38853893. 8.
Nonparametric Least Squares Estimation in
Derivative Families, Peter Hall and A. Yatchew (2010), Journal of Econometrics, 157, 362374. 9.
Nonparametric
Estimation When Data on Derivatives are Available, Peter Hall and A.
Yatchew (2007), Annals of Statistics,
35:1, 300323. 10.
International Welfare Comparisons and
Nonparametric Testing of Multivariate Stochastic Dominance, A. Yatchew and B.
McCaig (2007), Journal
of Applied Econometrics, 22:5,
951969. 11.
Nonparametric State Price Density Estimation
Using Constrained Least Squares and the Bootstrap A. Yatchew and W. Haerdle (2006), Journal of Econometrics, 133:2,
579599. 12.
Unified Approach to Testing Functional
Hypotheses In Semiparametric Contexts, with Peter
Hall and A. Yatchew, (2005), Journal of Econometrics, 127, 225252. 13.
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, Working
Paper Version. 14.
Hydro One
Transmission and Distribution: Should They Remain Combined Or Be
Separated , with Stephen C. Littlechild and A. Yatchew (2002). 15.
Household Gasoline Demand in Canada, A. Yatchew
and J.A. No, (2001) Econometrica, 69, 16971710. 16.
Incentive Regulation of Distributing Utilities
Using Yardstick Competition, A. Yatchew, (2001), Electricity
Journal, 5660. 17.
Scale Economies in Electricity Distribution: A
Semiparametric Analysis, (2000) A. Yatchew, Journal of Applied
Econometrics, 15, 187210. 18.
Differencing
Methods in Nonparametric Regression : Simple Techniques for the Applied
Econometrician, A. Yatchew (1999). 19.
An Elementary Nonparametric Differencing Test of
Equality of Regression Functions, (1999), A.
Yatchew, Economics Letters, 2718. 20.
Nonparametric Regression Techniques in Economics,
(1998), A. Yatchew,
Journal of Economic Literature, 36, 669721. 21.
An Elementary Estimator of the Partial Linear
Model, (1997), Economics Letters, A. Yatchew, 57, 13543.
See also Vol. 59, 1998 4035. 22.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