This paper reviews the extant empirical studies of financial innovation. Adopting broad criteria, the authors found just two dozen studies, over half of which (fourteen) had been conducted since 2000. Since some financial innovations are examined by more than one study, only fourteen distinct phenomena have been covered. Especially striking is the fact that only two studies are directed at the hypotheses advanced in many broad descriptive articles concerning the environmental conditions (e.g., regulation, taxes, unstable macroeconomic conditions, and ripe technologies) spurring financial innovation. The authors offer some tentative conjectures as to why empirical studies of financial innovation are comparatively rare. Among their suggested culprits is an absence of accessible data. The authors urge financial regulators to undertake more surveys of financial innovation and to make the survey data more available to researchers

This paper investigates the effect of (potential) market size on entry of new drugs and pharmaceutical innovation. Focusing on exogenous changes driven by U. S. demographic trends, we find a large effect of potential market size on the entry of nongeneric drugs and new molecular entities. These effects are generally robust to controlling for a variety of supply-side factors and changes in the technology of pharmaceutical research

This paper models components of the return distribution, which are assumed to be directed by a latent news process. The conditional variance of returns is a combination of jumps and smoothly changing components. A heterogeneous Poisson process with a time‐varying conditional intensity parameter governs the likelihood of jumps. Unlike typical jump models with stochastic volatility, previous realizations of both jump and normal innovations can feed back asymmetrically into expected volatility. This model improves forecasts of volatility, particularly after large changes in stock returns. We provide empirical evidence of the impact and feedback effects of jump versus normal return innovations, leverage effects, and the time‐series dynamics of jump clustering

The volatility of U.S. real GDP growth since 1984 has been markedlylowerthanoverthepreviousquartercentury.Weutilizefrequency-domain and VAR methods to distinguish among competing explanations for this reduction: improvements in monetary policy, better business practices, and a fortuitous reduction in exogenous disturbances. We find that reduced innovation variances account for much of the decline in aggregate output volatility, suggesting that good luck is the most likely explanation. Good practices and good policy appear to have played a more important role in explaining the post-1984 decline in the volatility of consumer price inflation

We claim that the stock market encourages business creation, innovation, and growth by allowing the recycling of “informed capital”. Due to incentive and information problems, start-ups face larger costs of going public than mature firms. Sustaining a tight relationship with a monitor (bank, venture capitalist) allows them to finance their operations without going public until profitability prospects are clearer or incentive problems are less severe. However, the earlier young firms go public, the quicker monitors' informed capital is redirected towards new start-ups. Hence, when informed capital is in limited supply, factors that lower the costs for start-ups to go public encourage business creation. Technological spill-overs associated with business creation and thick market externalities in the young firms segment of the stock market provide prima facie cases for encouraging young firms to go public

The literature offers many explanations for why the IPO market cycles from hot to cold. These include theories in which hot markets represent clusters of IPOs in a new industry, and signaling models that predict that hot markets draw in better quality firms. Others suggest hot market IPOs' stock returns reflect their poor quality. We compare IPOs over cycles during 1975–2000 and find that hot and cold IPO markets do not differ so much in the characteristics of the firms that go public as in the quantity of firms that go public. Both hot and cold IPOs are largely concentrated in the same narrow set of industries and they have few distinctions in profits, age, or growth potential. Our results suggest that hot markets are not driven primarily by changes in adverse selection costs, managerial opportunism, or technological innovations, but more likely reflect greater investor optimism