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.

We examine the effect of in-state and out-of-state renewable energy policies on wind energy patenting. Using a semiparametric fixed-effects Tobit model, we regress patent counts on a series of policy variables within a state and a spatially weighted average for each of these policies implemented in other states. We develop a lower bound for the marginal effects and find important differences across policy types. For renewable portfolio standards, overall demand matters. Policies in other states increase innovation, but own-state policies do not. In contrast, for financial incentives such as tax incentives and subsidy policies, own-state policies induce innovation.

As countries reform their patent laws to be in compliance with the Trade Related Intellectual Property Rights Agreement, an important question is how increased patent protection will affect drug prices in low-income countries. Using pharmaceutical trade data from 1996 to 2005, we examine the role of China and India as suppliers of medicines to other middle- and low-income countries and evaluate the competitive effect of medicine imports from these countries on the price of medicines from high- income countries. We find that imports of antibiotics and unspecified medicaments from India and China significantly depress the average price of these commodities imported from high-income trading partners, suggesting that India and China are not only important sources of inexpensive medicines but also have an indirect effect by lowering prices through competition. As India is the leading supplier of medicines in Sub-Saharan Africa, this region will likely be affected most adversely.

In this paper, we improve upon Coe and Helpman’s model of international R&D spillovers, using seemingly unrelated regression (SUR) to include interdependence among national economies and allow for variations in coefficients across countries. We find that the impact of knowledge spillovers on national productivity is context dependent: positive in some cases while negative in others. From our interpretation, the results suggest that both beneficial and competitive effects from foreign knowledge spillovers are important. We view the most important contribution of our work as simply providing evidence of this variation, and suggesting directions for future research to explain this phenomenon.