JOHANNES KEPLER UNIVERSITY LINZ Altenberger Str. 69 4040 Linz, Austria www.jku.at, DVR 0093696 REQUIEM FOR DONBAS Three Essays on the Costs of War in Ukraine By Artem Kochnev A Doctoral Thesis submitted at Department of Economics to obtain the academic degree of Doctor of Philosophy in the Doctoral Program “PhD Program in Economics” Supervisor and First Examiner Second Examiner em. Univ-Prof. Dr. Michael Landesmann Dr. habil. rer. soc. oec. Robert Stehrer May 2020 Abstract The thesis investigates short- and long-term effects of war on the economy of Ukraine. Specifically, it discusses the impact of separatists’ control and subsequent adverse trade policies on the real economy, responses of stock market investors to battle events, and the effect of conflict intensity on reform progress and institutional change in Ukraine. The thesis finds that the impact of war on the economy is most pronounced on the real economy of the war-torn regions. Whereas separatists’ control caused a decline in economic activity by at least 38%, the thesis does not find evidence supporting that the impact of conflict intensity on asset prices and institutional change in Ukraine was linear in parameters. The thesis explains the lack of the linear relationship between asset price move- ments and conflict intensity by investors’ inattention caused by information overload during the early stages of the conflict. Regarding the possible relationship between con- flict and institutional change, the thesis argues that it was electoral competition, not the conflict dynamics, that had an impact on the decision-making process of the policymak- ers in Ukraine. i Declaration I hereby declare that the thesis submitted is my own unaided work, that I have not used other than the sources indicated, and that all direct and indirect sources are acknowl- edged as references. This printed thesis is identical to the electronic version submitted. Vienna | May 15, 2020 ii Acknowledgements Although many humans might not realize it, a little research spirit lives in most of us. The proof is simple: type “the secret to a happy relationship” into a search engine and check the results. The sheer number – similar to figures depicted on Zimbabwe dollars at times of hyperinflation – suggests that the research topic has the top priority for humanity. My own contribution would be small as it’s easier for me to think of what doesn’t help a happy relationship. For instance, living with a scientist. Take me, for instance. Sometimes I wonder, how do I still have friends: conceited and vulnerable, egocentric and critical, pedantic and pretentious – I barely make the lives of those close to me any better. Yet there are people who welcome my society no matter how unbearable I might be: the “ESH First Floor gang” and the “Kochnev clan”. I had a great time – and hopefully am still going to have more! – with the ESH gang, exercising all sorts of (legal) human entertainment: be it LAN parties, watching series at 8 in the morning, food-sharing, or playing board games. Ironically, playing "Cards against humanity" late at night with them helped to preserve my human nature when the academic rigor was just about to vaporize the last bits of it. Yet while the ESH gang kept me entertained, my family – the Kochnev clan – took care of pretty much the rest. They gave up ambitions and pleasures to let me go abroad. They gave up their rest to help me solve my problems. They kept cheering me up when I was in doubt and whining. It is a luxury available only to a handful of people and I am glad that I can still enjoy your spirit, advice, and a warm welcome – together with a happy meal – at home. My final word of praise goes to Michael. You showed me that economics means more than a bunch of equations and made me believe I can tell something to the scientific world. I was a stubborn student who rarely followed the advice of the senior colleagues and this is the reason I didn’t go to Harvard, as you once suggested. Yet maybe it was ex- actly the same reason why I made it thus far. Either way, our conversations and exchanges changed my life and I am grateful for that. I don’t know how much you’ve benefited from these talks, but I hope that they were at least as intellectually pleasing for you as they were for me. iii Contents 1 Dying Light: War and Trade of the Separatist-Controlled Areas of Ukraine 5 1.1 Introduction . .5 1.2 Setting . .7 1.2.1 Context of the conflict . .7 1.2.2 State of the separatists’ cconomies . 10 1.3 Data sources and processing . 12 1.4 Descriptive statistics . 14 1.5 Estimations . 17 1.5.1 Estimated model . 17 1.5.2 Difference-in-difference estimates of the separatists’ control . 18 1.5.3 Impact of the nationalization and trade ban . 22 1.6 Discussion . 26 1.6.1 Withdrawal of banking and public services . 29 1.6.2 Quality of public governance . 31 1.6.3 Perceived security . 31 1.7 Conclusion . 33 2 Smoke on the Market: Inattentive Investors and the War in Ukraine 35 2.1 Introduction . 35 2.2 Theory and previous contributions . 37 2.3 Context . 38 2.4 Data sources and descriptive statistics . 41 2.5 Results . 45 2.6 Discussion . 56 2.7 Conclusion . 61 3 Marching to Good Laws: The Impact of War, Politics, and International Credit on Reforms in Ukraine 63 3.1 Introduction . 63 3.2 Theory and previous contributions . 65 3.2.1 Previous contributions . 65 3.2.2 A stylized model . 68 3.3 Context . 73 iv CONTENTS 3.4 Data . 75 3.4.1 iMoRe . 76 3.4.2 UAF casualties . 78 3.4.3 IMF tone . 78 3.4.4 Popularity measures . 78 3.4.5 Real wages . 79 3.4.6 Stationarity . 80 3.5 Estimations . 80 3.5.1 Models and methods . 80 3.5.2 Results . 84 3.5.3 Robustness checks . 87 3.5.4 Discussion . 93 3.6 Conclusion . 93 Appendices 109 A Supplementary materials for Chapter 1 110 A.1 Timeline: List of the Major Events Related to the Protests and War in East Ukraine . 110 A.2 Figures . 114 A.3 Tables . 119 B Supplementary materials for Chapter 2 130 B.1 Figures . 131 B.2 Tables . 134 C Supplementary materials for Chapter 3 144 C.1 Mathematical Appendix . 144 C.1.1 Proof of Proposition 1 . 144 C.2 Datasets . 148 C.2.1 Tone of the IMF communication . 148 C.2.2 Final classification . 156 C.2.3 Measures of electoral competition . 156 C.3 Tables . 159 v List of Figures 1.1 Change of the separatist-controlled areas . .8 1.2 Luminosity of the Donetsk surroundings in January of 2014 - 2017 years . 15 1.3 Change of the mean log luminosity in the Donetsk region by quarter and controlling party . 16 1.4 Change of the mean log luminosity in the Luhansk region by quarter and controlling party . 16 1.5 Urban areas within 3.5 km radius away from the headquarters of each na- tionalized firm . 24 1.6 Change of the mean log luminosity in the separatist-controlled region of Donetsk by quarter . 25 1.7 Change of internally displaced persons and battle events in the Donetsk and Luhansk regions . 32 2.1 Google search interest for selected requests in Ukraine. 40 2.2 Dynamics of the total PFTS index and battle intensity in Ukraine. 44 2.3 Dynamics of PFTS-weighted stock prices for Donbas companies and battle intensity in Ukraine. 44 2.4 Estimated probabilities of being in Regime 1 for Donbas sample and Google search interest for ‘ATO’. 57 2.5 Estimated probabilities of being in Regime 1. Donbas sample. Initial prob- abilities are fixed and symmetric. 58 2.6 Estimated probabilities of being in Regime 1. Non-Donbas sample. Initial probabilities are fixed and symmetric. 58 2.7 Advancement of government and separatist troops reported by media. 59 2.8 Territorial control of separatists on June 18th . 60 2.9 Territorial control of separatists on July 17th . 60 3.1 Graph of the game . 70 3.2 Fatalities of the Ukrainian Armed Forces: 2014 – 2019 . 75 3.3 VAR: orthogonal impulse-response functions. 86 3.4 VAR: orthogonal impulse-response functions. Adjusted sample . 90 3.5 VAR: orthogonal impulse-response functions. Variables in first-differences. 91 vi LIST OF FIGURES 3.6 Correlation between the popularity of the ruling party and the iMoRe in- dex. First differences. 92 A.1 Nighttime luminosity of Ukraine in January 2013 . 114 A.2 Change of the mean log luminosity in the Crimea and Kherson regions by quarter and control. 115 A.3 Cells within 20 - 40 km away from the contact line . 116 A.4 Change of the mean log luminosity in the Donetsk region by quarter and controlling party, 20-40 km away from the contact line . 117 A.5 Change of the mean log luminosity in the Luhansk region by quarter and controlling party, 20-40 km away from the contact line . 117 A.6 Change of the mean log luminosity in the separatist-controlled region of Donetsk by quarter excluding the cells within the districts crossed by the contact line . 118 A.7 Change of the mean log luminosity in the separatist-controlled.