Economic Studies 146

Haishan Yu Essays on Environmental and Energy Economics

Haishan Yu

Essays on Environmental and Energy Economics

Department of Economics, Uppsala University

Visiting address: Kyrkogårdsgatan 10, Uppsala, SwedenPostal address: Box 513, SE-751 20 Uppsala, SwedenTelephone: +46 18 471 00 00Telefax: +46 18 471 14 78Internet: http://www.nek.uu.se/_______________________________________________________

ECONOMICS AT UPPSALA UNIVERSITY

The Department of Economics at Uppsala University has a long history. The first chair in Economics in the Nordic countries was instituted at Uppsala University in 1741.

The main focus of research at the department has varied over the years but has typically been oriented towards policy-relevant applied economics, including both theoretical and empirical studies. The currently most active areas of research can be grouped into six categories:

* Labour economics* Public economics* Macroeconomics* Microeconometrics* Environmental economics * Housing and urban economics_______________________________________________________

Additional information about research in progress and published reports is given in our project catalogue. The catalogue can be ordered directly from the Department of Economics.

Dissertation presented at Uppsala University to be publicly examined in Lecture Hall 2,Kyrkogårdsgatan 10, Uppsala, Wednesday, 4 June 2014 at 10:15 for the degree of Doctor ofPhilosophy. The examination will be conducted in English. Faculty examiner: Tomas Sjögren(Umeå School of Business and Economics, Department of Economics).

AbstractYu, H. 2014. Essays on Environmental and Energy Economics. Economic studies 146. 132 pp.Uppsala: Department of Economics. ISBN 978-91-85519-53-8.

Essay I: In January, 2005, the EU launched the first international emissions trading system(EU ETS), aimed at reducing carbon emissions in a cost-effective way by means of a market-based instrument. In this paper, we use the treatment/control, before/after design of the naturalexperiment approach to investigate the treatment effect of the EU ETS on the profitability of asample of Swedish energy firms in 2005 and 2006. We also investigate whether under-cap andover-cap firms respond differently to the EU ETS. The estimation results in general suggest nosignificant impact in 2005 and a negative significant impact in 2006. The sub-sample analysissuggests that profitability of under-cap and over-cap firms were affected differently by the EUETS in 2005, but not in 2006.

Essay II: The paper empirically explores the possible causes behind electricity price jumps inthe Nordic electricity market, Nord Pool. A time-series model (a mixed GARCH-EARJI jumpmodel) capturing the common statistical features of electricity prices is used to identify pricejumps. By the model, a categorical variable is defined distinguishing no, positive and negativejumps. The causes for the jumps are then explored through the use of ordered probit models ina second stage. The empirical results indicate that the structure of the market plays an importantrole in whether shocks in the demand and supply for electricity translate into price jumps.

Essay III: Scientific evidence indicates that human development faces multiple andinteracting regime-switching environmental thresholds such as climate change, oceanacidification and biodiversity loss. And crossing one or more such thresholds would trigger rapidand large changes in our life-support system with widespread consequences. This paper attemptsto study the effects of such thresholds on human well-being in a growth theoretical framework.We derive the accounting prices of pollution stocks such as the concentration of greenhousegases for the risk of triggering catastrophic events, which are needed for conducting a dynamiccost-benefit analysis. We first analyze a simple model with a single threshold and then extendit to a planar system with correlated double thresholds with a joint probability distribution. theresults can be applied for analyzing global climate change and ocean acidification risks, whichare highlighted in a Nature article by Rockström et al. (2009).

Essay IV: Lump-sum transfers as a means of tackling climate change are mainly perceived asa theoretical construct to achieve the first best Pareto optimum. The previous literature on lump-sum transfers normally focuses on the two polar cases: the absence of lump-sum transfers andperfect or unconstrained lump-sum transfers, leaving the middle way aside. In this paper, weattempt to explore the unmarked part by developing a model where transfer costs are explicitlytaken into account. We show that whether the Pareto optimum characterized by the equalizationof marginal abatement costs is attainable depends on the formation of transfer costs. Whenthe marginal transfer cost is zero, the separability of equity and efficiency under perfect lump-sum transfers is kept. However, when the marginal transfer cost is positive, the optimum withequalization of marginal abatement costs is neither attainable, nor desirable. We also simulatea policy experiment in China to review the optimal abatement and transfer patterns betweenChina's provinces within a framework of imperfect lump-sum transfers. The highlighted welfaregains is supportive of considering lump-sum transfers as a national climate change policy.

Keywords: Carbon market, Difference-in-differences, Electricity market, Time series model,Carbon emissions, Global warming, Ocean acidification, Threshold effect, Lump-sumtransfers, Equity and efficiency

Haishan Yu, Department of Economics, Box 513, Uppsala University, SE-75120 Uppsala,Sweden.

© Haishan Yu 2014

ISSN 0283-7668ISBN 978-91-85519-53-8urn:nbn:se:uu:diva-222837 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-222837)

List of papers

This thesis is based on the following papers, which are referred to in the textby their Roman numerals.

I The EU ETS and firm profits: an ex-post analysis of Swedish energyfirms

II Why do electricity prices jump? Empirical evidence from the Nordicelectricity market

III Economic growth and social welfare with global regime-switchingenvironmental thresholds

IV Optimal carbon abatement in the presence of lump-sum transfer costs

Reprints were made with permission from the publishers.

Contents

Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Empirical research tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Theoretical research tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Summary of essays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Essay I:The EU ETS and firm profits: an ex-post analysis of Swedish energy firms . . . . . . . . . . 23

Essay II:Why do electricity prices jump? Empirical evidence from the Nordic electricitymarket . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

EssayIII:Economic growth and social welfare with global regime-switching environmentalthresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 482 The model with a single threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

2.1 The basic model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522.2 An explicit example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

3 An extension with interrelated double thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633.1 The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633.2 A simulation experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76A Derivation of the Expected Welfare Loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76B The explicit example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

EssayIV:Optimal carbon abatement in the presence of lump-sum transfer costs . . . . . . . . . . . . . . . . . . 93

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 942 The General Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 973 An Explicit Analysis with Two Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

3.1 The fixed transfer cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

3.2 The iceberg type transfer cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1053.3 The quadratic type transfer cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

4 A Policy Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1125 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120A Corner solutions in the policy experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120B Theoretical support for a linear abatement function . . . . . . . . . . . . . . . . . . . . . . . . . . 121C Figures and tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

Acknowledgement

“The way ahead is long, I shall search high and low.”

— free translation from Li Sao (Author: Qu Yuán).

Time has elapsed quickly, just like a flash. When I look back, I cannot help exclaimingthat I have lived in Sweden longer than in any other place except my hometown. Firstfor the master program and next the Ph.D. program, here is where my academic lifestarts. The long journey of my doctoral studies is now approaching the end. Workingon my Ph.D. has been a wonderful and often overwhelming experience. This thesiswould not have been possible without the guidance and support of the kind peoplearound me, to only some of whom it is possible to give particular mention here.

First and foremost, I would like to express my deepest gratitude to my advisor,Chuan-Zhong Li, whose selfless supply of time and care were sometimes all that keptme going. To Li, thank you for your continuous support of my studies and research, foryour endless patience, motivation, encouragement and positive attitude. I will alwaysremember your patience when I knocked on your door many times in a day, youre-mails that I got in the wee hours, and the message exchange on research throughmobile phones. I will also remember that once you told me that “Sikta mot stjärnorna,så når du trädtopparna” (aim for the stars, and you will reach the treetops). In research,you have been a steady influence throughout my Ph.D. career. In life, you have mademe feel like a friend, which I appreciate with all my heart. I cannot be more gratefulfor the care from you and Aunt Du beyond the supervisor-student tie. Vivid in mymemory are those Christmas Eves at your place, pumping warmth into my heart at atime when I was supposed to be homesick. I feel very fortunate and blessed to haveyou as my advisor.

I also want to thank my co-advisor, Bertil Holmlund. Although we have not writ-ten any paper together, without your support in the first place I would not be able tostart the doctoral studies in Uppsala smoothly. Thank you for believing in me andnever saying no when I needed help. A special acknowledgement goes to my formersupervisors at Örebro University and Dalarna Högskolan, Lars Hultkrantz and NiklasRudholm. Without your excellent guidance and support, the first two essays in thisthesis would not have been such a success. I am also indebted to your generous sup-port in my transferring to Uppsala. Lars, you have been such a good problem-solver.Whenever I encounter a problem, “talk to Lars” always has the magic of putting mymind at ease. Niklas, I will never forget that you took the early train at 5 o’clock in themorning and traveled more than three hours to attend my seminar. I also want to thankyou for introducing me to the excellent scholars Jörgen Hellström and Jens Lundgren,with whom I collaborated in Essay II.

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I want to take this opportunity to send my thanks to Professor Larry Karp at UCBerkeley for kindly inviting me to Berkeley and for taking the time to discuss researchand inviting me to join a project. I would also like to express my thanks to the dis-cussant at my licentiate seminar, Jesper Stage, for your valuable comments that haveimproved the quality of Essay I and Essay II to a great extent. Running into you atthe canteen at the I-house at UC Berkeley was an amazing coincidence. I am alsoindebted to Tommy Lundgren, the discussant at my final seminar. Thank you for read-ing through Essay III and Essay IV carefully and your humorous comment on my typo“chemestry”. Your suggestions have improved the papers in many ways.

My time in Uppsala was made enjoyable in large part due to many colleagues andfriends. Thanks to my fellow classmates with whom I started the program. To Glenn,I just realize that we have shared an office for five years. Wow, longer than any of mystudy periods since elementary school. You have been such a wonderful officemate.The smell of white tea constantly keeps our office in comfort. Also remembered arethose inspiring conversations, guitar lessons, movie nights and the street dance classthat we took together at Gränby. To Jon, thank you for initiating those movie nightsand after works. Although I kept saying we should do this and we should do that, itis you who make these activities actually happen. And thank you for running lunchheadquarters and tolerating my multiple rain checks. To Gabriella and Tove, thankyou for always being nice and ready-to-help. The natural bound as being womenand studying Ph.D. in the same year cohort speaks for itself. To Chris, thank youfor introducing me to the best hamburger at the nation, although the hamburger is nolonger as good as before. To Johan and Daniel, the big office that we shared in the firstyear constituted a relief to my loneliness when moving into a new town. Thanks alsogo to Selva, Rachatar, Karolina and Lovisa for those nice and interesting talks at thelunch-breaks at Gin Dee. The administrative staff at the department deserves specialthanks. Katarina, Ann-Sofie, Nina, and Stina, thank you all for your excellent workthat makes all practical problems solved efficiently. My studies would not have goneas steady and fast without your assistance. Åke, thank you for your patience with mytiresome computer problems. It was good to discover that we have the same favoritelunch spot.

I also want to extend my thanks to my former colleagues at Örebro Universityand Dalarna Högskolan. To Xing and Yeasmin, we have not only shared an officefor a year but also our life as friends forever. To Mattias P, thank you for the talksand jokes during the commuting time between Uppsala and Örebro. They have madethose boring journeys lovely. The Wednesday fika in Örebro has always been a nicemoment and is lodged in my memory. To Elin, Linda, Patrick, Daniela, Anders L andAnders E, thank you for making my time at the department wonderful. Anders E, Iwas very touched when you said “You are our girl”. Yes, the time at Örebro Universityis part of my life. Thanks also go to Aili, Anna K, and Li Dao, we have not only hadthe same experience of studying and teaching in Borlänge, but have also shared many

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girls’ talks! I would like to take this opportunity to thank Tobias and Reza, who mademy teaching in Borlänge go off without a hitch.

I also want to thank all other friends who put up with me through the whole Ph.D.process and helped me with personal challeges. Li Jie, being close friends with youhas been a wonderful part of my life. If you had not put the application form for themaster program on my desk, I would not have ended up on the Ph.D. track. To Shelleyand George, thank you for introducing me to Swedish culture and life. Time withyou always makes me feel at home. To Mr Liu Yang, you were the first to inspireme to do a Ph.D. when I was your teaching assistant in mathematics. Beyond that Iam also indebted to your fatherly care, which will be kept as a treasure in my life.To Luo Hao, my dear friend in statistics, you set a good example for me in balancingthe Ph.D. and personal pursuits. I will always remember the echo of the yellow lightsfrom our offices. To Zhao Xin and Liu Xijia, I have lost count of how many times thatI scrounged food at your place. Thank you for opening the door of gourmet delightsto me. To Su Xi, thank you for being good company in the last couple of years. ToWenjing, you have been a wonderful roomie! To Miaomiao, thank you for being openwith both sophisticated talks and hilarious jokes. Many Thanks also go to Li Ying, WeiJianxin, Wang Yanwu, Zhou Xingwu, Hu Xiao and Che-Yuan, for the many times get-togethers and being the back-up in my life in Uppsala. To Tsen-Che Chu, thank youfor the half-way language exchange and fikas at Café Linnea.

Last, but surely not least, I would like to thank my family. No words can expressmy gratitude for your unconditional love and support. Thanks to my father, who hasbeen a wonderful advisor in life. I am grateful to you for encouraging me to makethe trip to Sweden and to start the journey of the Ph.D., which is now coming to anend. Thanks to my mother who gives me the love and care that has no equivalent inthe world. Your letters from my high school and undergraduate periods have been agreat consolation during the tough times in the Ph.D. pursuit. My younger brother,Chong-shan, deserves special thanks. Thank you for taking care of our parents whenI am away from home, for putting up with my phone calls when I burst into tears.And finally, to Huang Wei, my soul-mate and life partner. Nobody in the world couldunderstand me better than you. Thank you for your faith in me and my intellect,even when I did not have faith in myself. Although it took a long time for us toupgrade friendship to partnership, I knew you were the one from the first day of ourrelationship! Your support, encouragement, patience during the final stages of thisPh.D. are so appreciated. Holding your hand, I have faith to live life to its fullest.

Uppsala, April 2014Haishan

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Introduction

The science of economics, noted in J.A. Schumpeter (1954a, 1954b), took itsshape towards the end of the eighteenth century, with Adam Smith’s Wealthof Nations in 1776 being the peak success of the epoch. With respect to thehistory of the economics profession, environmental economics is remarkablyyoung as a subdiscipline of economics. It can claim at most a 50-year her-itage dating from the foundation of Resource for the Future in 1952, andmore likely, a 40-year heritage, dating from the seminal works of the 1960s bythe likes of Boulding, Krutilla, Kneese, Dales, and Weisbrod (Pearce, 2002).Like all other subdisciplines of economics, environmental economics bor-rowed ideas and methods heavily from its precursors. As expressed by Baumoland Oates (1988), “when the “environmental revolution” arrived in the 1960s,economists were ready and waiting.” Environmental economics, standing onthe shoulders of giants and empowered by the increasing awareness of theimportance of the environment, has then entered the dynamic stage of rapidgrowth. Environmental issues involve trade-offs, primarily in how we use en-ergy. Many important environmental problems like climate change are closelyrelated to the production, conversion and consumption of energy. Since the1973 oil crisis, energy related issues have been widely present in the economicliterature. Energy economics studies energy resources and energy commodi-ties. It includes forces motivating firms and consumers to supply, convert,transport, and use the energy resource; market and regulatory structures; dis-tributional and environmental consequences; and economically efficient use(Sickles, 2008). Issues related to energy and the environment are inextrica-bly involved with multiple disciplines where, among others, economics is animportant one.

This thesis consists of four self-contained essays on environmental and en-ergy economics. They can be divided into two general lines according to theresearch tools applied: the first two essays are empirical studies employingeconometric models to evaluate the relevant policies from the microfounda-tion, while the last two essays turn to theoretical models and take welfareeconomics as the starting point to pay close attention to climate change. Theintroduction is structured as follows: Section 1 gives a brief account of the

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most commonly used empirical tools in environmental and energy economics.Section 2 concerns the most commonly used theoretical tools. A summary ofthe essays is outlined in Section 3. Our discussion on research tools is drawnfrom Batabyal and Nijkamp (2011). As noted in their book, no study can rea-sonably be expected to cover every conceivable research tool. Our primaryobjective here is to systematically organize the thesis and provide an angel onunderstanding environmental and energy economics which have a wide cov-erage of diversified issues.

1 Empirical research toolsIn what follows, we will briefly introduce four commonly used empirical toolsin environmental and energy economics: (i) contingent valuation, (ii) regres-sion analysis, (iii) experimental methods, and (iv) simulation methods. It isnoted that these tools are not independent. In fact, some tools are inextricablyinterwoven in application.

Contingent valuation is a common tool in environmental economics. Sincefew environmental goods can find their way in the marketplace, ingeniousmethods are called on to uncover the value estimates for environmental goodsbefore moving further to a cost-benefit analysis. In a broad sense, non-marketvaluation methods in environmental economics can be divided into two majorcategories, “revealed preference” and “ stated preference”. The revealed pref-erence methods are based on the assumption that, although there is no directmarket for the environmental goods considered, it is possible to find a tie be-tween people’s behavior and the environment goods in question. The hedonicmethod and the travel cost method are two common methods with “revealedpreference”.1 The stated preference methods, in contrast, elicit individual val-uations through surveys, and have come to be known as “contingent valuation”(CV), as the “valuation” estimates are obtained based on the information pro-vided by the respondents, “contingent” on the survey questions (Carson andHanemann, 2005). This approach is inherently flexible and elicits far moreinformation than the stated willingness to pay or revealed preference methods.

1The hedonic price method is used to estimate the economic value for environmental goods thatdirectly affect market prices. It is most commonly applied to variations in land and housingprices that reflect the value of environmental attributes. Another commonly used revealed pref-erence method is the travel cost method, or recreation demand modeling, based on the premisethat the time and travel cost expenses that people spend to visit a site represent the “price” ofaccess to the site.

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For this reason, stated reference techniques have secured a major place in thevaluation armory of the environmental economists (Pearce, 2002).

Regression analysis is the most commonly used statistical method in bothnatural and social science. There is a vast array of issues that researchers haveattempted to address using regression analysis. Thanks to the availability ofmore and better data, along with advances in the understanding of theoret-ical econometrics, the application of a regression analysis has been promi-nent in some subfields of economics (e.g., labor and development economics).Environmental and energy economics are flush with opportunities to applythe regression analysis too. In particular, quasi-experimental approaches havegained popularity in environmental economics to overcome the shortcomingsof data availability. Greenstone and Gayer (2009) list three common quasi-experimental approaches applied in environmental economics, which are: (i)Difference in differences (DD) and fixed effects (Essay I falls into this cate-gory); (ii) Instrument variables (IV); and (iii) Regression discontinuity. Re-gression analysis in energy economics is prominent with time series modelsas data on energy markets are mostly time series data. Essay II is an exampleof combining a mixed GARCH-EARJI time series model and ordered probitmodels to study the integration of the Nordic electricity market.

Experimental methods have seen a growing popularity in environmentaland energy economics. Evidently, environmental problems are particularlysuitable for experimental research. Sturm and Weimann (2006) identify threeconnecting factors for the experimental method and environmental economics.First, social dilemmas are at the core of environmental problems. Experimentsare able to test behaviorial hypotheses in such social dilemma situations, e.g.,experiments on decision making relevant to common pool resources. Second,the field of applied experimental work can be characterized as test-bedding ofinstitutional arrangements for the solution to environmental problems, e.g., ex-perimental markets for tradable emissions permits. Third, experimental meth-ods can be applied to the individual evaluation of environmental resources,e.g., experiments can be an excellent tool to test the validity of applied valu-ation methods to deal with open problems such as large differences regularlyobserved between the values of willingness to pay and the willingness to ac-cept. There is a wide range of environmental and energy related problems thatcan be investigated using the methods of experimental economics, as shownin Cherry et al. (2008).

The growth of simulation based methods over the last two decades, togetherwith the accompany improvements in computational power, has ushered in a

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new era of applied research in economics in general and environmental andresource economics in particular (Scarpa and Alberini, 2005). Many areas andresearch questions in environmental economics naturally lend themselves tothe application of simulation methods. For instance, simulation methods havebeen used to estimate discrete-choice models and the related welfare measuresfor non-market goods (Train and Weeks, 2005).

2 Theoretical research toolsThis section outlines four commonly used theoretical tools in environmentaland energy economics: (i) static analysis; (ii) dynamic analysis; (iii) stochasticanalysis; and (iv) game theory.

Static analysis used to be the core of traditional economic theory and stillplays an important role in modern economic analysis. Kuznets (1930) pointsout that in the early stage of the marginal utility approach, one confined to theproposition that economic theory is to devote itself exclusively to statics forthe time being. Static analysis in environmental economics is primarily em-bodied in static optimization in welfare economics to characterize an optimalallocation of resources. Essay IV is one example to study the Pareto optimalallocation in a constrained lump-sum transfer system in the context of climatechange. Although most environmental and energy related issues are dynamicin nature, the importance of static analysis for deepening the understanding ofthe allocation mechanism cannot be overstated. It also sets up a constructionwhich can be reinterpreted to accommodate both time and uncertainty.

Environmental and energy related questions are fundamentally dynamic innature. For instance, the accumulation of pollutant, the extraction of naturalresources, and the development of cleaner technology all involve time. A dy-namic analysis in environmental economics at an early stage was formulatedin the resource management problem that started with Hotelling (1931) whoconsidered exhaustible resources and characterized optimal extraction poli-cies, using the calculus of variations to verify the argument. The developmentof optimal control theory and dynamic programming provides the opportunityto expand the coverage of environmentally related issues that can be studiedwith dynamic analysis. Essay III starts with a climate-economy model in a dy-namic setting and relies on the optimal control method to arrive at a solutionfor the dynamics of the economy before the uncertainty has been incorporated.

Risk and uncertainty are fundamental notions in the field of environmen-tal and energy economics. Pindyck (2007) emphasizes that the real world is

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one of considerable uncertainty - over the physical and ecological impact ofpollution, over the economic costs and benefits of reducing it, and over the dis-count rates that should be used to compute present values. He also points outthat the implications of uncertainty are complicated by the fact that most en-vironmental problems involve highly nonlinear damage functions, importantirreversibleness, and long time horizon. Essay III makes an attempt at incor-porating global environmental threshold uncertainty, i.e., uncertain thresholdsin global warming and ocean acidification, into the growth model by assumingan irreversible flip in the economic system caused by crossing the threshold. Ithas been examined how the threshold effect would be translated into economicgrowth and social welfare.

Game theory is a tool to model and analyze situations involving interactionsand, possibly, cooperations. Many environmental problems are inextricablyinvolved with interactive decision making and hence, are suitable for applyinggame theory models. Both static and dynamic games have been successfullyemployed to shed some light on many resource and environmental issues in-volving strategic interactions among a number of players. Benchekroun andLong (2014) discuss some relevant games, for example interactions betweenplayers with opposing objectives in the context of pollution emissions andabatement games and the related question of the design of international envi-ronmental agreements.

3 Summary of essaysThis section outlines the summary of essays in the thesis.

Essay I: The EU ETS and firm profits: an ex-post analysis of Swedishenergy firmsIn January, 2005, the EU launched the first international emissions tradingsystem (EU ETS), aimed at reducing carbon emissions in a cost-effectiveway by means of a market-based instrument. In this paper, we use the treat-ment/control, before/after design of the natural experiment approach to inves-tigate the treatment effect of the EU ETS on the profitability of a sample ofSwedish energy firms in 2005 and 2006. We also investigate whether under-cap and over-cap firms respond differently to the EU ETS. The estimationresults in general suggest no significant impact in 2005 and a negative sig-nificant impact in 2006. The sub-sample analysis suggests that profitability

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of under-cap and over-cap firms were affected differently by the EU ETS in2005, but not in 2006.

Essay II: Why do electricity prices jump? Empirical evidence fromthe Nordic electricity marketThe paper empirically explores the possible causes behind electricity pricejumps in the Nordic electricity market, Nord Pool. A time-series model (amixed GARCH-EARJI jump model) capturing the common statistical featuresof electricity prices is used to identify price jumps. By the model, a categoricalvariable is defined distinguishing no, positive and negative jumps. The causesfor the jumps are then explored through the use of ordered probit models ina second stage. The empirical results indicate that the structure of the mar-ket plays an important role in whether shocks in the demand and supply forelectricity translate into price jumps.

Essay III: Economic growth and social welfare with global regime-switching environmental thresholdsScientific evidence indicates that human development faces multiple and in-teracting regime-switching environmental thresholds such as climate change,ocean acidification and biodiversity loss. And crossing one or more suchthresholds would trigger rapid and large changes in our life-support systemwith widespread consequences. This paper attempts to study the effects ofsuch thresholds on human well-being in a growth theoretical framework. Wederive the accounting prices of pollution stocks such as the concentrationof greenhouse gases for the risk of triggering catastrophic events, which areneeded for conducting a dynamic cost-benefit analysis. We first analyze a sim-ple model with a single threshold and then extend it to a planar system withcorrelated double thresholds with a joint probability distribution. the resultscan be applied for analyzing global climate change and ocean acidificationrisks, which are highlighted in a Nature article by Rockström et al. (2009).

Essay IV: Optimal carbon abatement in the presence of lump-sumtransfer costsLump-sum transfers as a means of tackling climate change are mainly per-ceived as a theoretical construct to achieve the first best Pareto optimum. Theprevious literature on lump-sum transfers normally focuses on the two polar

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cases: the absence of lump-sum transfers and perfect or unconstrained lump-sum transfers, leaving the middle way aside. In this paper, we attempt toexplore the unmarked part by developing a model where transfer costs are ex-plicitly taken into account. We show that whether the Pareto optimum charac-terized by the equalization of marginal abatement costs is attainable dependson the formation of transfer costs. When the marginal transfer cost is zero,the separability of equity and efficiency under perfect lump-sum transfers iskept. However, when the marginal transfer cost is positive, the optimum withequalization of marginal abatement costs is neither attainable, nor desirable.We also simulate a policy experiment in China to review the optimal abate-ment and transfer patterns between China’s provinces within a framework ofimperfect lump-sum transfers. The highlighted welfare gains is supportive ofconsidering lump-sum transfers as a national climate change policy.

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Hotelling, H., 1931. The economics of exaustible resources. Journal of PoliticalEconomy 39 (2), 137–175.

Kuznets, S., 1930. Static and dynamic economics. The American Economic Review,426–441.

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Pindyck, R. S., 2007. Uncertainty in environmental economics. Review ofenvironmental economics and policy 1 (1), 45–65.

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Schumpeter, J. A., 1954b. History of economic analysis. New York: OxfordUniversity Press.

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Sturm, B., Weimann, J., 2006. Experiments in environmental economics and someclose relatives. Journal of Economic Surveys 20 (3), 419–457.

Train, K., Weeks, M., 2005. Discrete choice models in preference space andwillingness-to-pay space. In: Scarpa, R., Alberini, A. (Eds.), Applications ofsimulation methods in environmental and resource economics. Springer, pp.1–16.

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Essay I: The EU ETS and firm profits: anex-post analysis of Swedish energy firms

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