World War II to 2011: Changes and Challenges in the Global Economy

This paper discusses six major changes and challenges that have emerged since World War II that will shape the global economy for the indefinite future. These are the changing economic role of women, the emergence of the global economic and financial system, the re-emergence of state-supported enterprises, the impact of the Internet, the global diffusion of opportunity and innovation, and globalization as an opportunity and a threat. How these challenges are addressed will have important consequences for business and for public policy. In addition to the prepared remarks, this paper also has a summary of the question-and-answer session that followed Dr. Hormats’ address.     

A general equilibrium analysis of conjunctive ground and surface water use with an application to Morocco

Groundwater resources (GW) account for nearly 30% of the world's sustainable water supplies. Yet, this resource, which is fraught with externalities, has largely been left unregulated. The economic literature on GW is predominantly of a partial equilibrium type. We analyze GW regulation in a general equilibrium setting, focusing on the stabilization value of GW under natural (drought) and economic (rural–urban water transfer) shocks. A general equilibrium approach allows evaluating direct and indirect effects of GW regulation on agriculture and nonagriculture sectors and extends the scope for water policy. The analysis is applied to Morocco by extending an existing computable general equilibrium (CGE) model to include ground and surface water (SW) resources. We study effects of (i) an increase in GW extraction cost (e.g., as a result of prolonged extraction beyond natural recharge that lowers the aquifer's water table), (ii) a transfer of SW from rural (irrigation) to urban (domestic) use, and (iii) a reduction of water availability due to severe drought. We estimate the value of GW and assess the direct (partial equilibrium) and indirect (general equilibrium) impacts. We find that GW plays a critical role in mitigating the negative effects of these types of shocks.     

A model of boundedly rational “neuro” agents

We consider a model in which each agent in a population chooses one of two options. Each agent does not know what the available options are and can choose an option only after observing another agent who has already chosen that option. In addition, the agents’ preferences over the two options are correlated. An agent can either imitate an observed agent or wait until he meets two agents who made different choices, in which case he can compare their choices and choose accordingly. A novel feature of the model is that agents observe not only the choices made by others, but also some information about the process that led them to those choices. We study two cases: In the first, an agent notes whether the observed agent imitated others or whether he actually compared the available alternatives. In the second, an agent notes whether the observed agent’s decision was hasty or not. It is shown that in equilibrium the probability of making a mistake is higher in the second case and that the existence of these nonstandard “neuro” observations systematically biases the equilibrium distribution of choices.     

Ronald Seavoy. Origins and Growth of the Global Economy: From the Fifteenth Century Onward. Westport, Conn.: Praeger, 2003. 275 pp. ISBN 0-275-97912-1, $70.95.

Few scholars are confident enough to believe that they can describethe history of the "origins and growth of the global economy"in 275 pages. But Ronald Seavoy, an emeritus professor of historyat Bowling Green State University, uses that history to illuminatetwo themes: to show that the global economy is built on thefoundation of European commercial imperialism and "to show thatthe global economy as it is currently evolving is capable ofproducing     

Markov decision processes under model uncertainty

We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting. By providing a dynamic programming principle, we obtain a local-to-global paradigm, namely solving a local, that is, a one time-step robust optimization problem leads to an optimizer of the global (i.e., infinite time-steps) robust stochastic optimal control problem, as well as to a corresponding worst-case measure. Moreover, we apply this framework to portfolio optimization involving data of the . We present two different types of ambiguity sets; one is fully data-driven given by a Wasserstein-ball around the empirical measure, the second one is described by a parametric set of multivariate normal distributions, where the corresponding uncertainty sets of the parameters are estimated from the data. It turns out that in scenarios where the market is volatile or bearish, the optimal portfolio strategies from the corresponding robust optimization problem outperforms the ones without model uncertainty, showcasing the importance of taking model uncertainty into account.     

Stochastic vs. deterministic frontier distance output function: Evidence from Brazilian higher education institutions

Journal of Productivity Analysis - Using data from the Brazilian Higher Education Census and other public institutions, this study aims to obtain and compare efficiency scores from stochastic...     

Ambiguity and risk factors in bank stocks

The determinants of banks' cost of equity are not well understood. We depart from prior work assuming rational expectations and instead explore the impact of Knightian uncertainty or ambiguity on bank stocks. We test a large set of asset pricing models and find that investors' lack of confidence in both the drift and correlation structure driving bank stock returns affects banks' cost of capital. We also investigate the economic relation among ambiguity, market liquidity, and banks' capital shortfall, which reveals the transmission channels through which ambiguity may increase the probability of a systemic crisis. Our findings have implications for macroprudential policy.