Essays in Environmental & Resource Economics by Léopold Temoana
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Essays in Environmental & Resource Economics by L´eopold Temoana Marc Biardeau A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Agricultural and Resource Economics in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Maximilian Auffhammer, Chair Professor Solomon Hsiang, Co-chair Professor Lucas W. Davis Professor Gordon Rausser Summer 2020 1 Abstract Essays in Environmental & Resource Economics by L´eopold Temoana Marc Biardeau Doctor of Philosophy in Agricultural and Resource Economics University of California, Berkeley Professor Maximilian Auffhammer, Chair Professor Solomon Hsiang, Co-chair At its core, environmental & resource economics seeks to identify and correct market failures, i.e. situations in which markets fail to allocate resources in a way that maximizes society's economic welfare. Some of the greatest issues of our time such as water and air pollution, the over-exploitation of natural resources, or climate change all result from market failures. While market failures can take many forms, they are often associated with time-inconsistent preferences, negative externalities, or the difficulty to provide and manage common goods. In this dissertation, I investigate three key issues relative to each of these types of market failure. In the first chapter, coauthored with Solomon Hsiang and S´ebastienAnnan-Phan, we pro- pose that the probability that individuals focus attention on a moment a fixed temporal distance from their present moment is stable. We call Kernel of Attention to Time (KAT) the resulting probability distribution across moments in relative time, which directs human attention across the past, present, and future. We then analyze how populations across the world query Google Search for information related to specific moments in time and provide the first evidence of a coherent KAT for most humans on Earth. We discover consistent structure to the distribution of attention across time, regardless of populations' language or country, with the present strongly dominating all other moments and capturing roughly 25% of time-related attention on average. Attention to the past and future decays rapidly with increasing temporal distance, much faster than exponentially. Despite consistency in the form of the KAT around the world, we find regional patterns in attention to the past, present, and future. Furthermore, it appears that over the last decade, attention to the present has been increasing at the expense of attention to the past. Together, these findings suggest that human populations exhibit strong common patterns 2 of thought with respect to time, but some non-biological factors that vary across space and over time can alter these patterns. While the KAT does not capture time-related economic tradeoffs directly (e.g. foregoing present consumption to increase future consumption), the structure of its future-oriented portion could enable better understanding of the origin of time-based preferences and pro- vide new insights on time-inconsistent behavior. In the second chapter, coauthored with Lucas Davis, Paul Gertler and Catherine Wolfram, we develop new measures of global air conditioning potential using temperature data from more than 14,000 monitoring stations around the world. We combine this information with disaggregated global population estimates to calculate cooling degree days (CDDs) and other measures of air conditioning potential by region, country, and city. Overall, the evidence points to enormous potential growth in air conditioning, particularly in low-income and middle-income countries. India, China, Indonesia, Nigeria, Pakistan, Brazil, Bangladesh, and the Philippines all have greater air conditioning potential than the United States, a country where a staggering 400 terawatt hours of electricity are currently used annually for air conditioning. We find, moreover, that a significant portion of total global air conditioning potential comes from the earth's largest cities. Mumbai, for example, has by itself the air conditioning potential of 25% of the entire United States. Our estimates imply that, were global air conditioning usage to reach U.S. levels, total electricity consumption worldwide for air conditioning could reach 20,000 terawatt hours annually, which roughly corresponds to the current net global electricity consumption. If unmitigated by improvements in air conditioner energy-efficiency or updated power network infrastructures, this rise in overall electricity demand could generate two negative externalities. First, it could lead to black- outs around the globe, especially in low and middle income countries. What is more, most electricity worldwide continues to rely on fossil fuels. Consequently, growing air conditioner adoption could lead to hundreds of millions of tons of increased carbon dioxide emissions, further aggravating climate change. In the third and last chapter, coauthored with David Zilberman, we rely on satellite-based data tracking vessel fishing hours to investigate the extent to which Very Large Marine Protected Areas (VLMPAs), { Marine Protected Areas spanning at least 100,000 km2,{ prohibiting all types of fishing have been successful at deterring fishing effort. These VLM- PAs have been created in an attempt to protect and replenish fish stocks, 34.5% of which have fallen below biologically sustainable levels,1 partly as a result of overfishing. Indeed, most fisheries have traditionally been open access resources, leading individually-acting fish- ers to collectively extract more than the efficient level and threatening the viability of the resource over time, a situation known as the tragedy of the commons.2 3 In spite of their large size which may constitute a challenge for enforcement, we find that VLMPAs have on average been able to deter fishing effort. However, a case-by-case analysis reveals varying levels of success, with the most successful VLMPA managed by the Republic of Kiribati and the worst performing one managed by the United States. To better understand the nature of illegal fishing effort in these VLMPAs, we focus on the characteristics of the vessels infringing the fishing bans in these VLMPAs and find that most of the infractions can be traced back to a few industrialized countries. i Contents Contents i List of Figures ii List of Tables iii Acknowledgements iv 1 The Distribution of Human Attention to Moments in Time1 1.1 Introduction.................................... 1 1.2 Model: The Kernel of Attention to Time (KAT)................ 2 1.3 Estimation: Recovering the KAT using Google Search ............. 6 1.4 Results....................................... 6 1.5 Discussion..................................... 11 2 Population, Warming, and Global Air Conditioning 15 2.1 Introduction.................................... 15 2.2 Methods...................................... 16 2.3 Results....................................... 22 2.4 Discussion..................................... 29 3 Evaluating the Effectiveness of Very Large Marine Protected Areas at Deterring Fishing Effort 30 3.1 Introduction.................................... 30 3.2 Methods...................................... 34 3.3 Results....................................... 38 3.4 Discussion..................................... 42 References 43 A Full derivation of the Kernel of Attention to time 52 A.1 A Probabilistic Model for Attention to Time.................. 52 A.2 Predictions for Internet Search Volume..................... 53 ii A.3 Google Search Data................................ 56 A.4 Empirical estimation of the KAT ........................ 57 B Supplemental Figures and Tables 61 B.1 Figures....................................... 61 B.2 Tables....................................... 73 List of Figures 1.1 Google search volume reflects changes in relative attention over time....... 3 1.2 Attention to time expressed through Google search queries............ 5 1.3 Google search volume for time-related queries and KAT model predictions... 7 1.4 The estimated Kernel of Attention to Time (KAT) ................ 9 1.5 Relative attention to past, present, and future around the world and over time . 11 1.6 The relative attention to the past, present and future for individual countries . 12 2.1 Simulation results................................... 18 2.2 Reporting Frequencies for Monitoring Stations................... 19 2.3 Global Cooling Degree Days............................. 23 2.4 Comparing Our Estimates to Previous Estimates ................. 25 2.5 Does Population-Weighting Matter?......................... 26 2.6 Robustness check................................... 28 3.1 List of all the Very Large Marine Protected Areas (VLMPAs) .......... 32 3.2 Evolution of daily hours of fishing effort in each VLMPA per 1,000 km2. 33 3.3 Displacement of fishing effort ............................ 36 3.4 Quartic polynomial curves of best fit and their associated 95% confidence intervals 39 B.1 Google search as convolution of KAT with daily dummies............. 62 B.2 Predicted search volume using estimated KATs .................. 63 B.3 Estimated KAT with alternative model choices .................. 64 B.4 Robustness checks for the shares of attention to different moments in time . 65 B.5 Estimated KAT using daily, monthly and yearly targets.............. 66 B.6 Country boundaries shapefile ............................ 67 B.7 Global CDD maps with alternative CDD thresholds................ 68 B.8 Expansion of vessel