We investigate the information content of stock correlation based network measures for systemic risk rankings, such as SIFIRank (based on Google’s PageRank). Using European banking data, we show that SIFIRank is empirically equivalent to a ranking based on average pairwise stock correlations as developed in this paper. The correlation based network measures complement currently available alternative systemic risk ranking methods based on book or market values. A further analytical investigation shows that the value-added appears to be mainly attributable to pairwise cross-sectional heterogeneity rather than to more subtle network relations and feedback loops.

We provide general conditions under which principal-agent problems admit mechanisms that are optimal for the principal. Our result covers as special cases those in which the agent has no private information – i.e., pure moral hazard – as well as those in which the agent’s only action is a participation decision – i.e., pure adverse selection. We allow multi-dimensional actions and signals, as well as both …nancial and non-financial rewards. Beyond measurability, we require no a priori restrictions on the space of mechanisms. Consequently, our optimal mechanisms are optimal among all measurable mechanisms. A key to obtaining our result is to permit randomized mechanisms. We also provide conditions under which randomization is unnecessary.

Prior research argues that the process of intermediation is opaque and produces uncertainty about the riskiness of banks, which may adversely affect the efficiency of bank stock prices. Using the Hou and Moskowitz (2005) measure of price delay, which captures the inefficiency of stock prices, we test for, and find evidence supporting the idea that opacity is positively associated with price delay. Bank stocks have markedly higher delay than similar non-bank stocks. This higher level of delay is driven, in part, by market-based measures of informational opacity as well as the asset composition of the bank's balance sheet. Combined, our findings suggest that bank opacity reduces the efficiency of financial markets.

Income shifting from high-tax to low-tax jurisdictions is considered a primary method of reducing worldwide tax burdens of multinational firms. Current losses also affect income shifting incentives. We extend prior approaches by explicitly considering unprofitable affiliates and test whether the association between losses and tax incentives for unprofitable affiliates deviates from the negative association observed in profitable affiliates. Results suggest that multinational firms alter the distribution of reported profits to take advantage of losses. Our point estimate for profitable affiliates implies that an increase of one standard deviation in the tax incentive, C, of an affiliate with an average return on assets of 13.3 is associated with a lower return on assets of 0.5 percentage points. The same change in tax incentive of an unprofitable affiliate is associated with an increase in its return on assets of approximately 0.7 percentage points, holding assets, labor, productivity, and other factors constant. We further document a larger responsiveness to tax incentives between profitable and unprofitable affiliates in high-tax jurisdictions, consistent with predictions.

We investigate how urban railroad and highway configurations have influenced urban form in Chinese cities since 1990. Each radial highway displaces 4% of central city population to surrounding regions, and ring roads displace about an additional 20%, with stronger effects in the richer coastal and central regions. Each radial railroad reduces central city industrial GDP by about 20%, with ring roads displacing an additional 50%. We provide evidence that radial highways decentralize service sector activity, radial railroads decentralize industrial activity, and ring roads decentralize both. Historical transportation infrastructure provides identifying variation in more recent measures of infrastructure.

Abduction is the process of generating and choosing models, hypotheses and data analyzed in response to surprising findings. All good empirical economists abduct. Explanations usually evolve as studies evolve. The abductive approach challenges economists to step outside the framework of received notions about the "identification problem" that rigidly separates the act of model and hypothesis creation from the act of inference from data. It asks the analyst to engage models and data in an iterative dynamic process, using multiple models and sources of data in a back and forth where both models and data are augmented as learning evolves.