We use machine learning algorithms to construct a novel news-based index of US environmental
and climate policy uncertainty (EnvPU) available on a monthly basis over the 1990-2019 period.
We find that our EnvPU index spikes during the environmental spending disputes of the
1995-1996 government shutdown, in the early 2010s due the failure of the national cap-and-trade
climate bill and during the Trump presidency. We examine how elevated levels of environmental
policy uncertainty relate to investments in the low-carbon economy. In firm-level estimations, we
find that a rise in the EnvPU index is associated with a reduced probability for cleantech startups
to receive venture capital (VC) funding. In financial markets, a rise in our EnvPU index is
associated with higher stock volatility for firms with above-average green revenue shares. At the
macro level, shocks in our index lead to declines in the number of cleantech VC deals and higher
volatility of the main benchmark clean energy exchange-traded fund. Overall, our results are
consistent with the notion that policy uncertainty has adverse effects on investments for the low-
carbon economy.

There is growing interest in using text as data in social science research, particularly in econom-ics. The availability of large amounts of digitized text material such as social media posts, news-papers,firms’annual reports, and patents, combined with new computer techniques, makes itincreasingly possible for researchers to use this type of information. The aim of this article is todiscuss the potential of these techniques for thefield of environmental economics and policy.While text-based methods are diffusing quickly in macroeconomics,finance, industrial organi-zation, and political science, the application of these techniques in environmental economicsresearch is still in the early stages. Wefirst provide a brief overview of text-as-data methodsand programming tools. Then we present examples of empirical applications of these methodsin environmental economics. We conclude with a summary and a discussion of the main chal-lenges and future prospects for these methods.

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Cleantech startups often find it difficult to attract investments because of their long horizon development and commercialization, need for large upfront capital investment, high technological risks, and low exit opportunities provided by incumbent companies. In recent years, there is a growing interest for raising capital via a large number of diversified investors through online crowdfunding platforms. In our research, we explored what opportunities crowdfunding platforms provide for financing cleantech startups.

We use machine learning algorithms to construct a novel news-based index of US environmental and climate policy uncertainty (EnvPU) available on a monthly basis over the 1990-2019 period. We find that the EnvPU index spikes during the environmental spending disputes of the 1995-1996 government shutdown, in the early 2010s due the failure of the national cap-and-trade climate bill and during the Trump presidency. We examine how elevated levels of environmental policy uncertainty relate to investments in the low-carbon economy. In firm-level estimations, we find that a rise in the EnvPU index is associated with a reduced probability for cleantech startups to receive venture capital (VC) funding. In financial markets, a rise in our EnvPU index is associated with higher stock volatility for firms with above-average green revenue shares. At the macro level, shocks in our index lead to declines in the number of cleantech VC deals and higher volatility of the main benchmark clean energy exchange-traded fund. Overall, our results are consistent with the notion that policy uncertainty has adverse effects on investments for the low-carbon economy hindering progress to address the urgency of climate action.

After a boom and bust cycle in the early 2010s, venture capital (VC) investments are, once again, flowing towards green businesses. In this paper, we use Crunchbase data on 150,000 US startups founded between 2000 and 2020 to better understand why VC initially did not prove successful in funding new clean energy technologies. Both lackluster demand and a lower potential for outsized returns make clean energy firms less attractive to VC than startups in ICT or biotech. However, we find no clear evidence that characteristics such as high-capital intensity or long development timeframe are behind the lack of success of VC in clean energy. In addition, our results show that while public sector investments can help attract VC investment, the ultimate success rate of firms receiving public funding remains small. Thus, stimulating demand will have a greater impact on clean energy innovation than investing in startups that will then struggle through the “valley of death”. Rather than investing themselves in startups bound to struggle through the valleys of death, governments wishing to support clean energy startups can first implement demand-side policies that make investing in clean energy more viable

This thesis aims to provide novel analyses and data that improve the understanding of the financing of investments in clean technologies. In particular, this thesis explores the role that private and public actors play in supporting young innovative firms.

Clean technology plays an important role to help minimize harmful impacts on the environment through introduction or optimization of technologies in processes, materials, energy and infrastructures. It is an important cornerstone of the current climate strategy to leverage technologies to mitigate and adapt to climate change. Thus, mass mobilization of finance is essential to support the development of new technologies and accomplish climate goals to stay below 2 degrees of warming, with experts estimating that $12.1 trillion is needed over the next 25 years to stay within the goal (Ceres and Locklin, 2016). As investors seem to express some motivation to invest in cleantech startups and also to crowdfund, this report highlights how to best synergize dynamics between investors and entrepreneurs on crowdfunding.

We introduce a novel index measuring the salience of US environmental policy over the 1981-2019 period on a monthly basis and on various sub-topics. The index captures the evolution of the relative share of news articles discussing environmental and climate regulations over the last four decades. Our analysis finds a meaningful empirical association between more news on environmental policy and growing opportunities for clean investments.

We build a novel news-based index of US environmental policy and examine how it relates to clean investments. Extracting text from ten leading US newspapers over the last four decades, we use text-mining techniques to develop a granular index measuring the salience of US environmental policy (EnvP) over the 1981-2019 period. We develop further a set of additional measures, namely an index of sentiment on environmental policy, as well as various topic-specific indices. We validate our index by showing that it correctly captures trends and peaks in the evolution of US environmental policy and that it has a meaning- ful association with clean investments, in line with environmental regulations supporting growing opportunities for clean markets. In firm-level estimations, we find that the salience of environmental policy in newspapers is associated with a greater probability of cleantech startups receiving venture capital (VC) funding and reduced stock returns for high-emissions firms most exposed to environmental regulations. At the aggregate level, we find in VAR models that a shock in our news-based index of renewable energy policy is associated with an increase in the number of clean energy VC deals and in the assets under management of the main benchmark clean energy exchange-traded fund. Overall, our EnvP index provides a lot of substantial information on environmental policy and can help assist the policy and financial community in understanding how these regulations are perceived by investors — providing many avenues for future research.

Adjustment costs are a central bottleneck of the real-world economic transition essential for achieving the sizeable reduction of greenhouse gas (GHG) emissions set out by policy makers. Could these costs derail the transition process to green growth, and if so, how should policy makers take this into account? I study this issue using the model of directed technical change in Acemoglu, Aghion, Bursztyn, and Hemous (2012), AABH, augmented by a friction on the choice of scientists developing better technologies. My results show that such frictions, even minor, materially affect the outcome. In particular, the risk of reaching an environmental disaster is higher than in the baseline AABH model. Fortunately, policy can address the problem. Specifically, a higher carbon tax ensures a disaster-free transition. In this case, the re-allocation of research activity to the clean sector happens over a longer but more realistic time horizon, namely around 15 instead of 5 years. An important policy implication is that optimal policies do not act over a substantially longer time horizon but must be more aggressive today in order to be effective. In turn, this implies that what may appear as a policy failure in the short-run — a slow transition albeit aggressive policy — actually reflects the efficient policy response to existing frictions in the economy. Furthermore, the risk of getting environmental policy wrong is highly asymmetric and ‘robust policy’ implies erring on the side of stringency.

Massive amounts of investments in clean technologies (e.g., solar energy, electric vehicles) are needed in order to limit global temperature rise below 2°C. Experts estimate that the world needs to invest $12.1 trillion globally over the next 25 years. To put this figure in perspective, it would require increasing the current level of investment by $210bn per year, a bit less than Portugal’s GDP. Yet, the current funding of clean technologies is hindered by an unattractive risk/return profile compared to other types of technologies. It takes high amounts of both capital and time to prove the commercial viability of a cleantech startup (Nanda et al., 2015). To tackle this issue, it is crucial to develop a better understanding of novel financing tools available to startups. One of these new financing tools, which we study in our recent research, is venture competitions.

Venture competitions usually reward winners with a certification of their startup’s quality and a cash prize. We model and estimate the impact of these rewards on startup performances using original data on about 1000 startups that have participated in a highly-regarded venture competition. We find that winning in the competition improves startups’ performances on average. However, it does not affect all technology types equally. Startups in sectors where quality can be more objectively assessed enjoy a long-term benefit from the certification’s effect. By contrast, startups with low running costs and whose quality is harder to evaluate only benefit temporarily from having received a cash prize, with no long-term effect. We also show that the competition’s certification provides valuable information to both entrepreneurs and outside investors. This information accelerates the termination of low-quality startups and improves external funding opportunities for high-quality startups. Our results highlight sector-specific heterogeneity in startups early-stage support needs, which bears implications for the design of entrepreneurial programs.

Substantial private investment is required if public policy objectives aim to increase the market share of Electric Vehicles (EVs) and prevent locking-in emissions-intensive development pathways. To maximize the effectiveness of future policies and successfully attract private capital, policy makers need to gain a better understanding of how investors behave, and of how policy design can drive investments decisions. This paper leverages an adaptive conjoint analysis (ACA) method to investigate the policy preferences of 41 European investors affiliated with different investment institutions. Findings reveal that investors’ characteristics as institution type and size of assets under management affect investors’ preferences over different e-mobility policy attributes. Furthermore, this study shows that behavioral factors, namely investors’ a-priori beliefs on the impacts of climate change and the COVID-19 crisis, play a role in determining investors’ policy preferences. By providing an analysis of investors’ behavior, this research can support policymakers to design more effective policy instruments to attract investments in electric mobility during and after the COVID-19 crisis.

With 25% of worldwide emissions due to road transport, the deployment of electric vehicles (EVs), full battery electric vehicles and plug-in hybrid electric vehicles – presents many promises to mitigate climate change. Despite its rapid growth, the market share of EVs vehicle remains low in Europe. Norway leads the EV market with 10% of total vehicle stock, followed by Iceland (3.3%), the Netherlands (1.9%) and Sweden (1.6%) (IEA, 2019). This Policy Brief presents the results of a survey among European cleantech investors examining which policy instruments and design can best mobilize private investments to advance e-mobility technologies.

Mobilizing private investments for the renewable energy transition requires credible policy support over the long-term. This Policy Brief discusses how Romania’s abrupt policy changes and inconsistent policy signals over the last decade have deterred private investments in the renewable energy sector. The example of Romania provides key policy lessons for other countries engaged in the energy transition.

Despite their potential for urgently needed emission reduction, electric vehicles account for a small fraction of the European vehicle fleet. Large scale deployment of electric vehicles requires considerable investments. While public policies are crucial for leveraging such financing, when ill-designed, they risk being ineffective or might even crowd-out investments. This study sheds light on investors’ policy preferences in the e-mobility sector. Based on behavioural finance literature, I propose that various a priori beliefs and investors’ country-contexts affect their evaluation of e-mobility policies. The policy preferences of European investors are examined through an adaptive conjoint analysis. The results indicate that policy preferences are dependent on investors’ belief in government intervention and the effectiveness of e-mobility technology. Furthermore, the existence of a domestic car manufacturing sector and the size of electric vehicle fleets affect investors’ policy evaluations. These behavioural aspects should, therefore, be incorporated into future policymaking processes.

Mobilizing private investments for the renewable energy transition requires credible policy support over the long-term. This Policy Brief discusses how Romania’s abrupt policy changes and inconsistent policy signals over the last decade have deterred private investments in the renewable energy sector. The example of Romania provides key policy lessons for other countries engaged in the energy transition.