Department of Economics
University of Toronto
150 St. George St., Room 278
Toronto M5S 3G7
Editor-in-Chief, The Energy Journal
ENV282F Big Ideas in Energy 1 – Technology and Society
ENV282 takes an historical perspective on the development of energy technologies, and how energy has influenced the development of human societies. The course analyses historical energy transitions and explores their relevance to current energy and environmental issues facing humankind. It is team taught by Ben Akrigg (Classics), Adonis Yatchew (Economics) and Stephen Morris (Physics).
ENV382S Big Ideas in Energy 2 – Economics, Politics and Security.
In ENV382, students will be introduced to the central ideas in economics, politics and security that are essential to understanding today’s complex energy and environmental decisions. Security issues will cover regional and geopolitical aspects. The course is team taught by Ben Akrigg (Classics), Adonis Yatchew (Economics) and Stephen Morris (Physics).
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 'cap-and-trade'.
ECO 414S/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.
Eco 2401S Econometrics II, Ph.D.
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, Ph.D.
This a special topics course, team taught by econometricians in the Economics Department.
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.
§ 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.
§ Discerning Trends in Commodity Prices, 2015, D. Dimitropoulos and A. Yatchew, forthcoming, Macroconomic Dynamics.
§ 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.
§ 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.
§ Differencing Methods in Nonparametric Regression : Simple Techniques for the Applied Econometrician, A. Yatchew (1999)
§ 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.
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.