Institutions have a decisive impact on the prevalence and nature of entrepreneurship. To date, the impact of institutions on (productive) entrepreneurship and the effects of entrepreneurship on economic growth have largely been investigated in isolation. In this paper, we bring together institutions, entrepreneurship, and economic growth using a parsimonious growth model in a 3SLS specification. In our first stage, we regress multiple measures of entrepreneurial activity on institutional proxies that are known to correlate with more productive forms of entrepreneurial activity. Using the fitted values of this first-stage regression as our proxy for productive entrepreneurship, we can then estimate a panel growth regression following Islam (1995) in a second stage. The third stage then optimizes the estimation of the two equations simultaneously. Our results show that productive entrepreneurship contributes to economic growth. In our set of proxies for institutional quality, financial stability, small government, and perceived start-up skills are the most important predictors of such productive entrepreneurship.

Economic losses from natural disasters have been increasing in recent decades. This has been attributed mainly to population and economic growth in disaster-prone areas. Future natural disaster losses are expected to increase due to a continued increase in economic exposure and climate change. This highlights the importance of designing policies that can mitigate the impacts of these disasters on the economy and society. A rapidly expanding literature has estimated the direct (e.g., property damage) and indirect (e.g., gross domestic product growth, trade) economic impacts of natural disasters. This article reviews this emerging literature. We synthesize the main theoretical, computational, and empirical methods used, summarize key findings on the economic impacts of natural disasters, and discuss factors that have been found to mitigate disaster impacts. We conclude by identifying lessons for policymakers and outlining an agenda for future research in this field.

Inhalation has been employed as a method for delivering medications for more than two thousand years, and the benefits of delivering medication directly to the affected site - the lungs - have been understood for more than two hundred years. At the beginning of the Industrial Revolution, physicians were inventing therapies and experimenting with ideas for devices: it was a time of great creativity. However, by the end of the period the scientist and the regulated pharmaceutical industry had emerged and the role of the physician had been constrained. Few of the devices invented then remain in use today, but many of the principles used are still embodied in modern devices. This review traces the developments produced by the early pioneers who applied their creative thoughts to inhalation therapy, and examines how inhaled drug delivery has progressed. The devices pictured are from www.inhalatorium.com, an online museum of inhalation technologies.

In this paper, we propose a method by which the entrepreneurial ecosystem, if present, reveals itself in the data. We first follow the literature and define the entrepreneurial ecosystem as a multidimensional set of interacting factors that moderate the effect of entrepreneurial activity on economic growth. The quality of such an ecosystem, by its multidimensionality, is impossible to measure directly. But so defined, we argue that variation in entrepreneurial ecosystem quality should result in variation in the estimated marginal effect of entrepreneurial activity on economic growth. Testing for such variation is possible using a combination of a multilevel growth regression and latent class analysis. We motivate and validate our approach in simulated data before illustrating its applicability in a data set covering 107 European NUTS1-2 regions across 16 EU member states. For this dataset, we cannot reject the hypothesis of a homogeneous contribution of entrepreneurship to regional growth. That is, in this dataset, we find