Induced innovation and international environmental agreements: evidence from the ozone regime

This paper revisits one of the rare success stories in global environmental cooperation: the Montreal Protocol and the phase-out of ozone-depleting substances. I show that the protocol increased science and innovation on alternatives to ozone-depleting substances and argue that agreements can indeed be useful to solving global public goods problems. This contrasts with game-theoretical predictions that agreements occur only when costs to the players are low, and with the often-heard narrative that substitutes were readily available. I reconcile theory and empirics by discussing the role of induced innovation in models of environmental agreements

Induced innovation and international environmental agreements: evidence from the Ozone regime

Global environmental problems are some of the most pressing issues that humanity is facing. There are few examples of success at resolving them; the fight to protect the ozone layer is one of them. This paper provides evidence that the Montreal Protocol’s restrictions on chlorofluorocarbons ( CFCs) triggered a substantial increase in research and innovation on alternatives to ozone-depleting molecules. I compare CFC substitute molecules to molecules that have similar uses but are unrelated to ozone depletion. After the signing of the agreement, patents on CFC substitutes increased by 400% and scientific articles by 500% compared to the control group. These findings suggest that agreements can indeed trigger the development of technological solutions, thereby improving the benefit-cost equation of environmental protectio

Essays on the Economics of Technological Change and the Environment

Technological change bears the promise of addressing environmental problems without reneging on economic development. However, taping its full potential requires an understanding of its drivers and barriers. The three chapters of this dissertation are a modest attempt at casting light on some of the factors that can foster technological change towards more environmental-friendly technologies. In Chapter One, I provide the first quantitative evidence that the Montreal Protocol, and its following amendments to protect the ozone layer, triggered a large increase in research and innovation on alternatives to ozone-depleting molecules. To do this, I use the full text of patents and scientific articles and implement a difference-in-differences strategy and a synthetic control method. To compare molecules’ chemical and industrial characteristics, I construct descriptive variables by applying machine learning techniques to the documents’ text. In Chapter Two, I investigate barriers to adopting solar lanterns in the context of rural Indian households. I design and implement a randomized controlled trial on people’s willingness to pay for such lanterns, and find that, despite the relative simplicity of the product, information barriers to adopting solar lanterns remain high. Chapter Three theoretically investigates firm-level barriers to green technological change. I outline a mechanism that explains why coordination at the industry level might be necessary. I argue that radical innovations (such as electric cars) require complementary innovations in interdependent components, and show that, when technological change requires investment by both suppliers and producers, coordination within an industry is needed and can be difficult to obtain

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry’s transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry’s markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms

Induced innovation, inventors and the energy transition

We study how individual inventors respond to incentives to work on 'clean' electricity technologies. Using natural gas price variation, we estimate output and entry elasticities of inventors and measure the medium-term impacts of a price increase mirroring the social cost of carbon. We find that the induced clean innovation response primarily comes from existing clean inventors. New inventors are less responsive on the margin than their average contribution to clean energy patenting would indicate. Our findings suggest a role for policy to increase the supply of clean inventors to help mitigate climate change

Directed technological change and general purpose technologies: can AI accelerate clean energy innovation?

Transitioning away from dirty and towards clean technologies is critical to reduce carbon emissions, but the race between clean and dirty technologies is taking place against the backdrop of improvements in general-purpose technologies (GPT) such as information and communication technologies (ICT) and artificial intelligence (AI). We show how, in theory, a GPT can affect the direction of technological change and, in particular, the competition between clean and dirty technologies. Second, we use patent data to show that clean technologies absorb more spillovers from AI and ICT than dirty technologies and that energy patenting firms with higher AI knowledge stocks are more likely to absorb AI spillovers for their energy inventions. We conclude that ICT and AI have the potential to accelerate clean energy innovation

Directed technological change and general purpose technologies: can AI accelerate clean energy innovation?

Transitioning away from dirty and towards clean technologies is critical to reduce carbon emissions, but the race between clean and dirty technologies is taking place against the backdrop of improvements in general-purpose technologies (GPT) such as information and communication technologies (ICT) and artificial intelligence (AI). We show how, in theory, a GPT can affect the direction of technological change and, in particular, the competition between clean and dirty technologies. Second, we use patent data to show that clean technologies absorb more spillovers from AI and ICT than dirty technologies and that energy patenting firms with higher AI knowledge stocks are more likely to absorb AI spillovers for their energy inventions. We conclude that ICT and AI have the potential to accelerate clean energy innovation

Assessing reliability of electricity grid services from space: the case of Uttar Pradesh, India

While most households around the world have access to electricity, the number of hours per day when the grid supplies them with adequate voltage can be low. Improving the reliability of electricity is crucial to make progress on energy poverty but measuring and monitoring it is difficult, especially in lower-income countries where official data is sparse. We develop a transparent method using only easily accessible data to track the reliability of electricity. We train a decision tree model to predict the number of hours with normal electricity in Uttar Pradesh, India, using monthly nighttime luminosity, village characteristics, and voltage data from monitors installed in households. The approach successfully predicts reliability across time and space, and we document that, in Uttar Pradesh, the average number of hours per day with normal electricity has increased by 0.6 h between 2014 and 2019. The predicted number of hours with normal/reliable electricity supply for 2019 remains as low as 8.1 h

Traditional Chinese medicines in the treatment of hepatocellular cancers: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Liver cancer is a common malignancy with a high mortality rate. Given the poor prognosis associated with this cancer, many patients seek additional therapies that may improve quality of life or survival. Several Traditional Chinese Medicines (TCM) have been evaluated in clinical trials, but little is known about them outside of China.</p> <p>Methods</p> <p>We searched independently and in duplicate 8 electronic databases, including 2 Chinese language databases, until February 2009. We included any randomized clinical trials (RCT) evaluating a TCM oral preparation for the treatment of hepatocellular cancers. We abstracted data on survival, tumor response, and performance scores. We conducted a random-effects meta-analysis and applied a meta-regression analysis.</p> <p>Results</p> <p>We included 45 RCTs (n = 3,236). All studies employed an active control group. In general, the reporting of methodological issues was poor. We analyzed data from 37 trials reporting on complete response effects score (Relative Risk [RR] of 1.26 (95 CI, 1.04–1.52, P = 0.01, I²= 0%, P = 0.99). Products containing ginseng, astragalus and mylabris had a larger treatment effect (OR 1.34, 95% CI, 1.04–1.71, P = 0.01) than the pooled broad estimate, also the case for astragalus-based treatments (OR 1.35, 95% CI, 1.001–1.80. P = 0.048). We examined survival rates and pooled 15 studies reporting on 6 month outcomes (RR 1.10, 95% CI, 1.04–1.15, P = < 0.0001, I²= 0%, P = 0.60). This effect was consistent at other prospective dates, including 12 months (22 trials, RR 1.26, 95% CI, 1.17–1.36, P = < 0.0001, I²= 7%, P = 0.36), 24 months (15 trials, 1.72, 95% CI, 1.40–2.03, P = < 0.0001, I²= 0%, P = 0.75); and, at 36 months (8 trials, RR 2.40, 95% CI, 1.65–3.49, P = < 0.0001, I²= 0%, P = 0.62).</p> <p>Limitations</p> <p>All included trials were conducted in China where emerging evidence suggests many RCTs are not, in fact, randomized. Publication bias may exist, favouring positive reports.</p> <p>Conclusion</p> <p>Our meta-analysis displays compelling evidence of effectiveness for hepatocellular cancers that should be evaluated in high-quality and transparent clinical trials.</p

Satellite data for the social sciences: measuring rural electrification with night-time lights

Remote-sensing data has the potential to revolutionize social science. One of the most prominent examples of this is the Nighttime Lights data set, which provides digital measures of night-time luminosity from 1992 to 2013. This study evaluates the Nighttime Lights data against detailed rural electrification data from the 2011 Census of India. The results suggest that many night-time luminosity measures derived from satellite data are surprisingly accurate for measuring rural electrification, even at the village level and using simple statistical tools. We also demonstrate that this accuracy can be substantially improved by using of better GIS maps, basic geoprocessing tools, and particular aggregations of night-time luminosity. Night-time luminosity performs worse in measuring financial inclusion or proxies of poverty, however, and detects rural electrification less accurately when the supply of power is intermittent. These results offer guidelines for when and how remote-sensing data can be used when administrative data is absent or unreliable