This grant provides partial support for a study by the National Research Council (NRC) of the National Academy of Sciences on proposed reforms to the “Common Rule” – a set of rules governing the use of human subjects in research funded by 17 federal agencies. Untouched for two decades, the Common Rule is unarguably in need of revision to reflect changes in the way modern research is conducted in the U.S. Yet ill-advised changes to the Rule could significantly hinder the conduct of harmless research, particularly in the behavioral and social sciences. A proposed rule change by the Department of Health and Human Services, for instance, would extend the privacy guidelines in the Health Insurance Portability and Accountability Act (HIPAA) to research in all fields, even though the guidelines therein were specifically formulated to protect personal health information. If adopted, such an extension could require academic scientists of all kinds to obtain new permissions from human subjects, including survey respondents, before reusing their data for any purpose other than the one originally stated—even if those data have already been anonymized.The NRC will convene a blue ribbon committee of scientific and policy experts, study the likely impacts of proposed and hypothetical changes to the Common Rule, and issue a high-profile report on their findings, and hold a workshop with relevant stakeholders.

Traditionally, macroeconomics and finance have been surprisingly separate subjects.  Yet if the Great Recession taught us anything, it is that macroeconomic models should not ignore the financial sector.  We now know that financial considerations such as risk, regulation, leverage, liquidity, and default can affect the “real economy.”  Funds from this grant support the work of a team led by Robert Engle at New York University to build, test, and refine macro-economic models that incorporate these financial factors.  Engle’s team will pay particular attention to modeling how undercapitalization relative to regulatory requirements affects macroeconomic dynamics.

Financial contracts range from stocks, options, and futures to loans, annuities, and swaps.  Each has its own rules governing who pays whom under what circumstances.  Understanding the obligations imposed by these real world contracts under various hypothetical future scenarios is essential to evaluating the risks posed by the financial system to the global macroeconomy.  What will happen if oil prices drop precipitously?  What will happen if Chinese growth slows far faster than expected?  What happens if there is another recession in the Eurozone? Project ACTUS (Algorithmic Contract Types Unified Standards), based at the Stevens Institute of Technology, seeks to answer these questions by simplifying the analysis of financial transactions.  In theory, every financial agreement can be modeled algorithmically in terms of just 30 basic paradigms called “contract types.”  Each contract type’s algorithm accepts as inputs both the parameters of the original agreement as well as information about the subsequent state of the world.  It then outputs the payments dictated by the contract to and from its counterparties.  In other words, the algorithm calculates “state dependent cash flows.”  Banks and consultants already have their own proprietary systems that accomplish this, of course, but ACTUS is developing a system that would be comprehensive, standardized, open source, and compatible across organizations.  It would allow the calculation of state dependent cash flows not just within a company, but across entire industries and economies, with potential applications in everything from risk management to regulatory reporting.  A 2012 planning grant from the Sloan Foundation supported ACTUS in the development and testing of the first six contract types.  Funds from this grant will expand the project, allowing the development and testing of six additional types, enough to cover most routine bank transactions.