Adonis Yatchew

Professor of Economics, University of Toronto

Editor-in-Chief,  The Energy Journal


Contact information

Department of Economics 

University of Toronto

150 St. George St., Room 278

Toronto M5S 3G7


Tel: (416) 978-7128 


Outstanding Contributions to the Profession, International Association for Energy Economics, June 2018. For details and previous award winners see

Senior Fellow, US Association for Energy Economics, June 2014. For details and previous award winners see


TEACHING 2020-2021

Graduate Courses


ECO 2401S Econometrics II, Ph.D. (joint with Ismael Mourifié)

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 co-integration, 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 (team taught)

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, feed-in-tariffs, carbon taxes, ‘cap-and-trade’ and incentive regulation.  (This course is cross-listed as a senior undergraduate course, Eco 414S. See below.)


ECO 4051F: Topics in Covid Economics (team taught)

This is a special topics course, team taught by members of the Economics Department. Participating faculty include Victor Aguirregabiria, Christian Gourieroux, Jiaying Gu, Yoram Halevy, Philip Oreopoulos, Aloysius Siow, Clémentine Van Effenterre , Ronald Woltoff and Adonis Yatchew.


Undergraduate Courses


ECO 314F Energy and the Environment

The Covid-19 pandemic has 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, feed-in-tariffs, carbon taxes, ‘cap-and-trade’ and incentive regulation. (This course is cross-listed 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

How Scalability is Transforming Energy Industries  Energy Regulation Quarterly, 2019, 7:2, 35-44.


Discerning Trends in Commodity Prices, A. Yatchew and D. Dimitropoulos, Macroeconomic Dynamics, 2017, Vol.22, Special Issue 3, Dynamics of Oil and Commodity Prices, 683-701, doi:10.1017/S1365100516000511.


Rational vs. ‘Feel-Good’ Carbon Policy – Transferability, Subsidiarity and Separation, A. Yatchew, 2016,  Energy Regulation Quarterly, 4:3, 31-40.


Integration of Renewables into the Ontario Electricity System, B. Rivard and A. Yatchew, 2016, The Energy Journal, vol 37, Special Issue 2, pp. 221-242.


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 Non-Economist, A. Yatchew, 2014 Energy Research and Social Science, 1(1), 74-82.


Support Schemes for Renewable Energy: An Economic Analysis, R. Green and A. Yatchew 2012, Economics of Energy & Environmental Policy, 1, 83-98.


Ontario Feed-in-Tariff Programs, A. Yatchew and A. Baziliauskas 2011, Energy Policy, 39, 3885-3893.


Nonparametric Least Squares Estimation in Derivative Families, Peter Hall and A. Yatchew 2010, Journal of Econometrics, 157, 362-374.


Nonparametric Estimation When Data on Derivatives are Available, Peter Hall and A. Yatchew 2007, Annals of Statistics, 35:1, 300-323.


International Welfare Comparisons and Nonparametric Testing of Multivariate Stochastic Dominance, A. Yatchew and B. McCaig, 2007, Journal of Applied Econometrics, 22:5, 951-969.


Nonparametric State Price Density Estimation Using Constrained Least Squares and the Bootstrap A. Yatchew and W. Haerdle, 2006, Journal of Econometrics, 133:2, 579-599.


Unified Approach to Testing Functional Hypotheses In Semiparametric Contexts, with Peter Hall and A. Yatchew, 2005, Journal of Econometrics, 127, 225-252.


Efficient Estimation of Semi-parametric Equivalence Scales With Evidence From South Africa , A. Yatchew, Y. Sun and C. Deri,  Journal of Economic and Business Statistics, 2003, 21, 247-257, Working Paper Version.


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,  1697-1710.


Incentive Regulation of Distributing Utilities Using Yardstick Competition,  A. Yatchew, 2001, Electricity Journal, 56-60.


Scale Economies in Electricity Distribution: A Semiparametric Analysis, 2000 A. Yatchew, Journal of Applied Econometrics, 15, 187-210.


An Elementary Nonparametric Differencing Test of Equality of Regression Functions, 1999,  A. Yatchew, Economics Letters, 271-8.


Nonparametric Regression Techniques in Economics, 1998, A. Yatchew,  Journal of Economic Literature, 36, 669-721.


An Elementary Estimator of the Partial Linear Model, 1997, Economics Letters, A. Yatchew, 57, 135-43. See also Vol. 59, 1998  403-5. 


Nonparametric Least Squares Estimation and Testing of Economic Models  A. Yatchew and L. Bos 1997, Journal of Quantitative Economics, 13, 81-131. 



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 pre-industrial 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.


Canada Energy Flow 2014

Canada Carbon Flow 2014






Monograph:  Semiparametric Regression for the Applied Econometrician, A. Yatchew (2003),in Themes in Modern Econometrics, ed. P.C.B. Phillips, Cambridge University Press. Download introduction. The book is available from Cambridge University Press web at in North America and elsewhere. The paperback and hardback ISBN numbers are 0-521-01226-0 and 0-521-81283-6 respectively.

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 Cobb-Douglas, 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 S-Plus) 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.