Posts by Collection

coding

General R Resources

coding, University of Oxford, 2020

This is a simple collection of resources that I find useful. In the future, this site will feature more extensive discussions about R, stata, GitHub and python coding practices.

Climate Tools and Tricks

coding, University of Oxford, 2020

A collection of packages, code snippets and gists to import, modify, and analyse Climate Data.

R Markdown and LaTeX

coding, University of Oxford, 2021

Some resources on writing Journal articles in RMarkdown

Teaching Econometrics in R

coding, University of Oxford, 2021

A collection of resources that I have used to teach econometrics and statistics.

portfolio

publications

Wirtschaftswachstum und Klimawandel: Chancen und Herausforderungen auf dem Weg zur klimafreundlichen Gesellschaft

Published in Wirtschaftspolitische Blätter, 2017

Die internationale Staatengemeinschaft hat die Dekarbonisierung der Wirtschaft zum Schutz vor unbeherrschbarem Klimawandel beschlossen. Gegenwärtig gibt es auf globaler wie nationaler Ebene eine Vielzahl politischer Maßnahmen zur Erreichung dieses Ziels. Diese müssen jedoch stark ausgebaut und effizient ausgestaltet werden. Der vorliegende Beitrag zeigt auf, dass Klimaschutz grundsätzlich mit Wirtschaftswachstum vereinbar ist, aber ebenso, dass diese Vereinbarkeit sehr anspruchsvoll sein wird und eine kohärente politische Regulierung benötigt: Umfassende CO2-Preise sind eine notwendige Bedingung für ambitionierten Klimaschutz in wachsenden Wirtschaften. Diese sind aber nicht hinreichend; ergänzende Maßnahmen zum existierenden EU-Emissionshandel werden für eine effiziente Dekarbonisierung in Österreich benötigt. Am Beispiel des Verkehrssektors und der Landwirtschaft Österreichs zeigen wir auf, wie eine gut gestaltete Klimapolitik Chancen für Wirtschaft und Gesellschaft eröffnet.

Blog Post

Recommended citation: Mattauch, L., Roesti, M., Schwarz, M. and Siegmeier J. (2017). Wirtschaftswachstumund Klimawandel: Chancen und Herausforderungen auf dem Weg zur klimafreundlichenGesellschaft. Wirtschaftspolitische Blätter. 3/2017. https://www.wko.at/site/WirtschaftspolitischeBlaetter/mattauch-et-al.pdf

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming

Published in Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2018

Empirical evidence suggests that variations in climate affect economic growth across countries over time. However, little is known about the relative impacts of climate change on economic outcomes when global mean surface temperature (GMST) is stabilized at 1.5°C or 2°C warming relative to pre-industrial levels. Here we use a new set of climate simulations under 1.5°C and 2°C warming from the “Half a degree Additional warming, Prognosis and Projected Impacts” (HAPPI) project to assess changes in economic growth using empirical estimates of climate impacts in a global panel dataset. Panel estimation results that are robust to outliers and breaks suggest that within-year variability of monthly temperatures and precipitation has little effect on economic growth beyond global nonlinear temperature effects. While expected temperature changes under a GMST increase of 1.5°C lead to proportionally higher warming in the Northern Hemisphere, the projected impact on economic growth is larger in the Tropics and Southern Hemisphere. Accounting for econometric estimation and climate uncertainty, the projected impacts on economic growth of 1.5°C warming are close to indistinguishable from current climate conditions, while 2°C warming suggests statistically lower economic growth for a large set of countries (median projected annual growth up to 2% lower). Level projections of gross domestic product (GDP) per capita exhibit high uncertainties, with median projected global average GDP per capita approximately 5% lower at the end of the century under 2°C warming relative to 1.5°C. The correlation between climate-induced reductions in per capita GDP growth and national income levels is significant at the p<0.001 level, with lower-income countries experiencing greater losses, which may increase economic inequality between countries and is relevant to discussions of loss and damage under the United Nations Framework Convention on Climate Change.

Blog Post, Visualisations, and Data

Press Coverage

Recommended citation: Pretis, F., Schwarz, M., Tang, K., Haustein, K., & Allen, M. R. (2018). Uncertain impacts on economic growth when stabilizing global temperatures at 1.5 C or 2 C warming. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2119), 20160460. https://royalsocietypublishing.org/doi/full/10.1098/rsta.2016.0460

Antworten auf zentrale Fragen zur Einführung von CO2-Preisen. Gestaltungsoptionen und ihre Auswirkungen für den schnellen Übergang in die klimafreundliche Gesellschaft

Published in Diskussionsbeiträge der Scientists for Future, 2019

Derzeit wird in Deutschland daher kontrovers diskutiert, ob und wie CO2-Emissionen einen höheren Preis bekommen können. Dabei werden die Formen einer CO2-Steuer, einer Erweiterung des europäischen Emissionshandels oder Mischformen und Varianten dieser Instrumente erwogen. Mit der nachfolgenden Zusammenstellung einiger in der Öffentlichkeit häufig diskutierter Fragen bereiten wir den Stand der Forschung für Interessierte auf.

Online Version

Recommended citation: Mattauch, L., Creutzig, F., aus dem Moore, N., Franks, M., Funke, F., Jakob, M., Sager, L., Schwarz, M., Voß, A., Beck, M. L., Daub, C. H., Drupp, M., Ekardt, F., Hagedorn, G., Kirchner, M., Kruse, T., Loew, T., Neuhoff, K., Neuweg, I., Peterson, S., Roesti, M., Schneider, G., Schmidt, R., Schwarze, R., Siegmeier, J., Thalmann, P., Wallacher, J. (2019). Antworten auf zentrale Fragen zur Einführung von CO2-Preisen. Gestaltungsoptionen und ihre Auswirkungen für den schnellen Übergang in die klimafreundliche Gesellschaft. (Version 2). Diskussionsbeiträge der scientists for future. https://doi.org/10.5281/zenodo.3644498

The Challenge of Using Epidemiological Case Count Data: The Example of Confirmed COVID-19 Cases and the Weather

Published in Environmental and Resource Economics, 2020

The publicly available data on COVID-19 cases provides an opportunity to better understand this new disease. However, strong attention needs to be paid to the limitations of the data to avoid making inaccurate conclusions. This article, which focuses on the relationship between the weather and COVID-19, raises the concern that the same factors influencing the spread of the disease might also affect the number of tests performed and who gets tested. For example, weather conditions impact the prevalence of respiratory diseases with symptoms similar to COVID-19, and this will likely influence the number of tests performed. This general limitation could severely undermine any similar analysis using existing COVID-19 data or comparable epidemiological data. This could mislead decision-makers on questions of great policy relevance.

Data and Code: Github

Selected Press Coverage:
Press release by the Oxford Martin School

Recommended citation: Cohen, F., Schwarz, M., Li, S., Lu, Y., Jani, A. (2020). The Challenge of Using Epidemiological Case Count Data: The Example of Confirmed COVID-19 Cases and the Weather. Environmental and Resource Economics. https://link.springer.com/article/10.1007/s10640-020-00493-2#Sec43

Climate change and emerging markets after Covid-19

Published in A Report prepared for Pictet Asset Management, 2020

This report, written for Pictet Asset Management, offers a deep and broad analysis of the risks and opportunities emerging economies – and the world more generally – face from climate change in a post-Covid-19 world. The insights of this report are based on the latest economic and climate modelling techniques.

Recommended citation: Cohen, F., Ives, M., Srivastav, S., Schwarz, M., Lu, Y., Mealy, P., Bento Maffei de Souza, P., Jackson, L., Hepburn, C. (2020). Climate change and emerging markets after Covid-19. A Report prepared for Pictet Asset Management. https://am.pictet/en/globalwebsite/global-articles/2020/pictet-asset-management/climate-change-and-emerging-markets-after-covid

Climate change: Answers to common questions.

Published in A Report prepared for Pictet Asset Management, 2020

This report, written for Pictet Asset Management, seeks to dispel many of the lingering myths about climate change and sheds new light on the scale of the likely damage if decision makers fail to meet carbon emission targets. Uncertainty about climate science and economics poses challenges for business and finance. Reasonable and intelligent people frequently ask us for a reference document to set out what is known and not known about climate change, including research that is sometimes contrary to prevailing societal beliefs, if only to avoid debates about areas that are settled and instead to direct attention to the areas where further research is valuable. We have structured this report into nine areas of doubt commonly expressed about climate science and economics, each of which is broken down into points of contention. We also highlight key facts and estimates in which scholars have high levels of confidence. Each section begins with a common challenge about climate science and economics, expressed as a quotation.

Recommended citation: Hepburn, C. and Schwarz, M. (2020). Climate change: Answers to common questions. A Report prepared for Pictet Asset Management. https://www.group.pictet/media-relations/media-releases/climate-change-9-contentions-testing-truthfulness

Testing for Coefficient Distortion due to Outliers with an Application to the Economic Impacts of Climate Change

Published in Working Paper, 2021

Outlying observations can bias regression estimates, requiring the use of robust estimators. Comparing robust estimates to those obtained using OLS is a common robustness check, however, such comparisons have been mostly informal due to the lack of available tests. Here we introduce a formal test for coefficient distortion due to outliers in regression models. Our proposed test is based on the difference between OLS and robust estimates obtained using a class of Huber-skip M-type estimators (such as Impulse Indicator Saturation or Robustified Least Squares). Establishing asymptotics of the corresponding Huber-skip M-estimators using an empirical process CLT recently developed by Berenguer-Rico et al. (2019), we show that our distortion test has an asymptotic chi-squared distribution, and is valid for cross-sectional as well as panel and time series models. To improve finite sample performance and to alleviate concerns on distributional assumptions, we further introduce and explore three bootstrap testing schemes. We apply our outlier distortion test to estimates of the macro-economic impacts of climate change allowing for adaptation. We find that OLS estimates are significantly different to those obtained using a robust estimator and provide evidence of income-driven adaptation. Projecting the resulting damage curve to the end of the century shows that outlier-robust estimates dampen projected GDP losses and reduce the estimated marginal impacts of additional warming under adaptation.

Recommended citation: Jiao, Xiyu and Pretis, Felix and Schwarz, Moritz, Testing for Coefficient Distortion due to Outliers with an Application to the Economic Impacts of Climate Change (August 31, 2021). Available at SSRN: https://ssrn.com/abstract=3915040 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3915040

Discovering What Mattered: Answering Reverse Causal Questions by Detecting Unknown Treatment Assignment and Timing as Breaks in Panel Models

Published in Working Paper, 2022

Much of empirical research focuses on forward causal questions (‘Does X cause Y?’) while answering reverse causal questions (‘What causes Y?’) can provide invaluable insights but is difficult to implement in practice. Here we operationalise the modelling of reverse causal questions through the detection of unknown treatment assignment and timing as structural breaks in fixed effects panel models. We show that conventional treatment evaluation of known interventions in a two-way fixed effects panel (often interpreted as difference-in-differences) is equivalent to allowing for heterogeneous structural breaks in the treated units’ fixed effects. Using machine learning, we can thus detect previously unknown heterogeneous treatment effects as structural breaks in individual fixed effects corresponding to unit-specific treatment which can be subsequently attributed to potential causes. We demonstrate the feasibility of our approach by detecting the impact of ETA terrorism on Spanish regional GDP per capita without prior knowledge of its occurrence. Our proposed method to detect breaks in panel models can be readily implemented using our open-source R-package ‘gets’ with the ‘getspanel’ update or using the (adaptive) LASSO.

Recommended citation: Pretis, Felix and Schwarz, Moritz, Discovering What Mattered: Answering Reverse Causal Questions by Detecting Unknown Treatment Assignment and Timing as Breaks in Panel Models (January 31, 2022). Available at SSRN: https://ssrn.com/abstract=4022745 or http://dx.doi.org/10.2139/ssrn.4022745 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4022745

An Empirical Climate Damage Function Accounting for Climate Extremes and Adaptation

Published in Working Paper, 2022

Quantifying the economic impacts of climate change is crucial to inform mitigation and adaptation policy but faces challenges surrounding impacts of climate extremes and uncertainty around the range of plausible adaptation pathways. We overcome these by using machine learning and econometric model selection to construct an empirically-derived climate damage function allowing for impacts of a range of climate extremes under adaptation independent of any specific emission scenario. We use a novel baseline of forecasts of future economic development until the end of the century and – in absence of adaptation – project a decline in median country-level GDP per capita of up to 66% for warming beyond 4.5°C relative to no climate change. Projected marginal impacts under no adaptation suggest an approximate 12% decline in median country-level GDP per capita for each additional °C warming. We further show that the damage curve is not invariant to adaptation and provide empirical evidence of historical adaptation over time and incomes at a macro-economic level. Instability over time lowered the level of projected median GDP per capita impacts by approximately 20 percentage points relative to no-adaptation. Income-driven adaptation could reduce the marginal impacts of an additional degree of warming by a half to around 6% of GDP per capita per additional °C. Nevertheless, projected damages remain high and unequal even in the presence of adaptation reiterating the urgent case for stringent mitigation policy.

Recommended citation: Schwarz, Moritz and Pretis, Felix, An Empirical Climate Damage Function Accounting for Climate Extremes and Adaptation (February 1, 2022). Available at SSRN: https://ssrn.com/abstract=4022690 or http://dx.doi.org/10.2139/ssrn.4022690 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4022690

Decarbonization in state-owned power companies: Lessons from a comparative analysis

Published in Journal of Cleaner Production, 2022

A rapid decarbonization of the electricity system is urgently required for the Paris Agreement objectives to stand a reasonable chance of being met. While state-owned power companies (SPCs) are the dominant firm type in the global electricity sector, representing nearly two thirds of global electric power generation capacity, most climate policy literature focuses on private sector companies when analyzing decarbonization interventions. SPCs’ distinct corporate governance structures, objectives, relationships with government, and sources of finance, however, can be markedly different from those of private companies. Here, we develop a framework for analyzing the extent to which common and divergent features of SPCs, and the markets in which they operate, affect their relationship to government interventions on decarbonization. We also consider the implications of these relationships for the effective implementation of sector-wide decarbonization strategies. We then apply this framework using a comparative case study analysis of six major SPCs, and highlight how differences in their agency, motivation, capacity, and market exposure may result in different potential responsiveness to government regulatory, policy and market interventions on decarbonization. We generalize these findings by developing four SPC archetypes and illustrate how they might respond differently to government interventions targeting decarbonization. Our analysis posits that SPCs can, under the guidance of governments pursuing ambitious climate policy, be more effective vehicles for decarbonization relative to private sector companies, particularly when they operate with a high degree of operational independence, are insulated from competitive pressures, and have the financial and technical capacity to invest in the decarbonization of their asset base. Similarly, market-wide policy interventions, such as carbon pricing mechanisms, could in practice be less effective interventions with respect to SPCs than their private counterparts when the SPC is ill-equipped to translate these incentives into decarbonization action because it is mandated to pursue supplementary objectives other than profit maximization alone. Ultimately, governments will need to step up their climate action to achieve carbon neutrality. SPCs can, and where they are major market players, must be key actors in driving decarbonization when the appropriate interventions are utilized and therefore deserve significantly more attention in the climate policy debate.

Recommended citation: Philippe Benoit, Alex Clark, Moritz Schwarz, and Arjuna Dibley. (2022). Decarbonization in state-owned power companies: Lessons from a comparative analysis, Journal of Cleaner Production, Volume 355, 2022, 131796,ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2022.131796. https://doi.org/10.1016/j.jclepro.2022.131796

Whose jobs face transition risk in Alberta? Understanding sectoral employment precarity in an oil-rich Canadian province

Published in Climate Policy, 2022

Labour markets of oil-exporting regions will be impacted by a global transition to low-carbon energy as oil demand reduces to meet the aims of the Paris Agreement. Together with direct job losses in the oil and gas industry, indirect employment effects on other sectors should also be considered to ensure a just transition. We explore these direct and indirect employment impacts that could result from the low-carbon transition by analysing the effect of oil price fluctuations on the labour market of Alberta, a Canadian province economically reliant on oil sands extraction. We employ a mixed methods approach, contextualizing our quantitative analysis with first-hand experiences of career transitions using interviews with oil sands workers. We estimate a vector autoregression for province-wide insights and explore sector-specific dynamics using time series regressions. We find that the price discount on Canadian oil sands, which is determined by local factors like crude oil quality and pipeline capacity, does not significantly affect employment, while the global oil price does. This finding puts in doubt claims of long-term employment benefits from new pipelines. We find that at a provincial scale, oil price fluctuations lead to employment levels also fluctuating. Our analysis at the sectoral level shows that these job fluctuations extend beyond oil and gas to other sectors, such as construction and some service sectors. These findings suggest that the province’s current economic dependence on oil creates job precarity because employment in various sectors is sensitive to a volatile oil market. Furthermore, due to this sectoral sensitivity to oil price changes, workers in these sectors may be especially at risk in a low-carbon transition and warrant special attention in the development of provincial and national just transition policies. Transitional assistance can support workers directly, while economic diversification in Alberta can reduce reliance on international oil markets and thereby ensure stable opportunities in existing and new sectors.

Recommended citation: Antonina Scheer, Moritz Schwarz, Debbie Hopkins & Ben Caldecott (2022) Whose jobs face transition risk in Alberta? Understanding sectoral employment precarity in an oil-rich Canadian province, Climate Policy, 22:8, 1016-1032, DOI: 10.1080/14693062.2022.2086843 https://www.tandfonline.com/doi/full/10.1080/14693062.2022.2086843

Attributing agnostically detected large reductions in road CO2 emissions to policy mixes

Published in Nature Energy, 2022

Policymakers combine many different policy tools to achieve emission reductions. However, there remains substantial uncertainty around which mixes of policies are effective. This uncertainty stems from the predominant focus of ex post policy evaluation on isolating effects of single, known policies. Here we introduce an approach to identify effective policy interventions in the EU road transport sector by detecting treatment effects as structural breaks in CO2 emissions that can potentially occur in any country at any point in time from any number of a priori unknown policies. This search for ‘causes of effects’ within a statistical framework allows us to draw systematic inference on the effectiveness of policy mixes. We detect ten successful policy interventions that reduced emissions between 8% and 26%. The most successful policy mixes combine carbon or fuel taxes with green vehicle incentives and highlight that emissions reductions on a magnitude that matches the EU zero emission targets are possible.

Recommended citation: Koch, N., Naumann, L., Pretis, F., Ritter, N., Schwarz, M. Attributing agnostically detected large reductions in road CO2 emissions to policy mixes. Nat Energy 7, 844–853 (2022). https://doi.org/10.1038/s41560-022-01095-6 https://www.nature.com/articles/s41560-022-01095-6

Large weather and conflict effects on internal displacement in Somalia with little evidence of feedback onto conflict

Published in Global Environmental Change, 2023

Extreme weather and conflict may drive forced displacement. However, their individual contribution to displacement is not fully understood due to challenges around isolating individual channels of causality. Here, we use novel disaggregated data on internal displacement in all of Somalia’s subregions from 2016 to 2018 broken down by reported reason of displacement and combine it with weather and conflict data. This allows us to isolate the effects of extreme weather and conflict on forced displacement, as well as the effects of displacement on conflict itself. We find large non-linear effects of weather on displacement where an increase in temperature anomalies from 1°C to 2°C (to approx. 1.5 standard deviations, SD) leads to a tenfold increase in displaced people, and a reduction in precipitation from 50 mm to 0 mm (approx. 1.5SD) leads to around a fourfold increase in displacement. We find significant effects of conflict events on displacement (which are masked when the data is aggregated) with a 1.5 standard deviation increase in conflict events increasing displacement 50-fold. We further show that displacement itself has little detectable effect on the occurrence of conflict events.

Recommended citation: Thalheimer, L. , Schwarz, M., & Pretis, F. (2023). Large weather and conflict effects on internal displacement in Somalia with little evidence of feedback onto conflict. Global Environmental Change, Volume 79, 2023, 102641, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2023.102641. https://www.sciencedirect.com/science/article/pii/S0959378023000079

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