Optimal climate policy with fat-tailed uncertainty: What the models can tell us. ESRI Working Paper 697 March 2021.

We present a modification of the most commonly used integrated assessment model (IAM) of climate change (DICE-2016), AD-DICE2016, which is designed to address three key aspects of climate economy models: treatment of uncertainty, the use of more appropriate utility functions, and including adaptation policies to climate change. These modifications ensure that two of the key difficulties identified with IAMs, the choice of the risk aversion parameter and the underestimation of damages, are also directly addressed. The use of a bounded (Burr) utility function ensures that the model is able to appropriately assess the effects of parameters whose distributions have “fat tails”. Uncertainty is accommodated via the state-contingent approach enabling us to include more state (seven) and control variables (four) than recursive derivatives of DICE. Our approach to uncertainty ensures that the optimal climate policies account for outcomes in every possible state, unlike the Monte Carlo approach. Our treatment of uncertainty is extensive: eight parameters are allowed to be random, with distributions –many “fat tailed”– identified using current knowledge. Our model suggests that uncertainty regarding damages and climate sensitivity are key drivers of climate policy. We also find that uncertainty leads to increases in both optimal mitigation and adaptation, with adaptation and mitigation reacting differently to uncertainty over different parameters. Finally, our estimates of the social cost of carbon are larger when uncertainty is allowed for and significantly affected by adaptation

Essays in Climatic Extremes, Agriculture and Natural Resources

The first part of this dissertation attempts to add to our understanding of two aspects of the climate change issue, using tools from two different disciplines: Economics and Hydro-Climatology, for the case of India. The two aspects addressed are :( 1) understanding and summarizing changes in the climate system (and systems driven by it, such as the hydrologic system) and (2) translating such an understanding into quantitative assessments of impacts upon different activities. Modifications of conventional approaches in Environmental Economics are used to obtain a quantitative understanding of the type of changes in agricultural productivity induced by probable scenarios of climate change. Using a newly available observational rainfall data set from the Meteorological Department, assessments are carried out of changes in extremes of rainfall. These putative changes are then assessed in relation to certain larger scale climatological phenomena which presumably impact hydrologic extremes, based on hypotheses presented in the literature. The second part of the dissertation addresses the issue of unified, coherent and more realistic analysis of groundwater-based models in the Economics literature

Time-consistent renewable resource management with present bias and regime shifts

We investigate the extraction plan of present-biased decision makers managing a renewable resource stock whose growth is uncertain and which could undergo a rapid and significant change when stock falls below a threshold. We show that the Markov-Nash equilibrium extraction policy is unique, time consistent, and increasing in resource stock. An increase in the threshold leads to increased resource extraction, rather than the precautionary reduction in extraction often observed with exponential discounting. An increase in the degree of present bias also leads to an increase in resource extraction. Our analysis suggests that accounting for and appropriately dealing with resource managers’ present bias may be important to understand resource use sustainability

Unlocking the unsustainable rice-wheat system of Indian Punjab : assessing alternatives to crop-residue burning from a systems perspective

This work was funded by Formas (Project # 2018-01824), and through the generous support of the Erling-Persson Family Foundation to the Global Economic Dynamics and the Biosphere, the Royal Swedish Academy of Sciences, Sweden.Crop residue burning in Indian Punjab emits particulate matter with detrimental impacts on health, climate and that threaten agricultural production. Though legal and technological barriers to residue burning exist – and alternatives considered more profitable to farmers – residue burning continues. We review black carbon (BC) emissions from residue burning in Punjab, analyse social-ecological processes driving residue burning, and rice and wheat value-chains. Our aims are to a) understand system feedbacks driving agricultural practices in Punjab; b) identify systemic effects of alternatives to residue burning and c) identify companies and financial actors investing in agricultural production in Punjab. We find feedbacks locking the system into crop residue burning. The Government of India has greatest financial leverage and risk in the current system. Corporate stakeholders have little financial incentive to enact change, but sufficient stakes in the value chains to influence change. Agricultural policy changes are necessary to reduce harmful impacts of current practices, but insufficient to bringing about sustainability. Transformative changes will require crop diversification, circular business models and green financing. Intermediating financial institutions setting sustainability conditions on loans could leverage these changes. Sustainability requires the systems perspective we provide, to reconnect production with demand and with supporting environmental conditions.Publisher PDFPeer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Residential end-use electricity demand and the implications for real time pricing in Sweden *

Abstract Using a unique and highly detailed data set on energy consumption at the appliance-level for 200 Swedish households, seemingly unrelated regression (SUR)-based end-use specific load curves are estimated. The estimated load curves are then used to explore possible restrictions on load shifting (e.g. the office hours schedule) as well as the cost implications of different load shift patterns. The cost implications of shifting load from &quot;expensive&quot; to &quot;cheap&quot; hours, using the Nord pool spot prices as a proxy for a dynamic price, are computed to be very small; roughly 2-5% reduction in total daily cost from shifting load up to seven hour

Residential End-use Electricity Demand : Implications for Real Time Pricing in Sweden

Using a unique and highly detailed data set on energy consumption at the appliance-level for 200 Swedish households, seemingly unrelated regression (SUR)based end-use specific load curves are estimated. The estimated load curves are then used to explore possible restrictions on load shifting (e.g. the office hours schedule) as well as the cost implications of different load shift patterns. The cost implications of shifting load from "expensive" to "cheap" hours, using the Nord pool spot prices as a proxy for a dynamic price, are computed to be very small; roughly 2-4% reduction in total daily cost from shifting load up to five hours ahead, indicating small incentives for households (and retailers) to adopt dynamic pricing of electricity.Originally published in manucript form with the title: Residential End-use electricity demand and the implications for real time pricing in Sweden.</p

Space-time structure of extreme precipitation in Europe over the last century: a climate perspective

Historical observations show a significant change of globe temperature distribution as a consequence of global warming. In the midlatitude , and specifically in Europe, annual and seasonal changes of the midlatitude climate driving variables as EPG ( equator pole gradient) and OLC ( ocean land contrast ) were recorded, show significant trends, as shown in fig.1 and 2 . As a consequence of these changes a spatio-temporal trends in extreme precipitation in Europe is expected. We analyze over a century of continuous rainfall data available from the ECA&D archive for spatio-temporal trends in extreme precipitation. The data base includes 515 stations with records longer than 100 years. For each station, we identify daily rainfall events in the winter 6 months (Oct-Mar) that exceed the 99th percentile of daily rainfall. An annual time series of the frequency of such events is created, as well as an annual time series of the average daily rainfall in these events. Space and time analyses of the variation of the frequency and intensity time series are then pursued using multivariate time and frequency domain (multi-taper method) methods. The key trends and organized spectral modes identified can be related to potential anthropogenic change and to well established climate indices (e.g., NAO, EAWR and SL). The simultaneous analysis of monotonic trends over the secular period and quasi -oscillatory phenomena is informative as to the attribution of changes in extreme precipitation over the region

Space-time structure of extreme precipitation in Europe over the last century

We investigate the space-time structure of extreme precipitation in Europe over the last century, using daily rainfall data from the European Climate Assessment & Dataset (ECA&D) archive. The database includes 267 stations with records longer than 100 years. In the winter season (October to March), for each station, two classes of daily rainfall amount values are selected that, respectively, exceed the 90th and 95th percentile of daily rainfall amount over all the 100 years. For each class, and at each location, an annual time series of the frequency of exceedance and of the total precipitation, defined respectively as the number of days the rainfall threshold (90th and 95th percentiles) is exceeded and total precipitation on days when the percentile is exceeded, are developed. Space-time structure of the frequency and total precipitation time series at the different locations are then pursued using multivariate time and frequency domain methods. The identified key trends and organized spectral modes are linked to well-known climate indices, as North Atlantic Oscillation (NAO) and El Nino Southern Oscillation (ENSO). The spectra of the leading principal component of frequency of exceedance and of total precipitation have a peak with a 5-year period that is significant at the 5% level. These are also significantly correlated with ENSO series with this period. The spectrum of total rainfall is significant at the 10% level with a period of ∼8years. This appears to be significantly correlated to the NAO index at this period. Thus, a decomposition of both secular trends and quasi-periodic behaviour in extreme daily rainfall is provided. © 2014 Royal Meteorological Society

SPACE-TIME STRUCTURE OF EXTREME PRECIPITATION IN EUROPE OVER THE LAST CENTURY: A CLIMATE PERSPECTIVE

We analyze over a century of continuous rainfall data available from the ECA&D archive for spatio-temporal trends in extreme precipitation. The database includes 267 stations with records longer than 100 years. For each station, we identify daily rainfall events in the winter 6 months (Oct-Mar) that exceed the 90th and 95th percentile of daily rainfall. An annual time series of the frequency of such events is created, as well as an annual time series of the total precipitation above the threshold in these events. Space and time analyses of the variation of the frequency and intensity time series are then pursued using both multivariate time and frequency domain methods and principal component analysis (PCA). The key trends and organized spectral modes identified are related to potential anthropogenic change and to well established climate indices (e.g., NAO, EAWR and SL). The analysis shows that there is compelling evidence for statistically significant trends for increasing frequency and intensity of exceedance of daily rainfall extremes in the Oct-Mar season over North and Western Europe, where the highest station density is located. From a Principal Component Analysis and from a MTM-SVD analysis, these trends are seen to be spatially coherent. Furthermore, the influence of NAO and ENSO is seen through the significance of the frequency spectra of the associated climate indices and the leading PC of each series analyzed. The ENSO connection is prominent at a frequency of ∼ 0.2 cycles/year, and for NAO at a frequency of ∼ 0.15 cycles/year