Many statutes now permit bounties for whistleblowers who provide enforcement relevant information to the authorities. The growth in such bounties has been quite rapid in recent years generating substantial scholarly, policy and practical interest. However, much of the scholarship does not address a critical feature of corporate liability in the US – there is considerable uncertainty about both the scope and definition of wrongdoing. This talk examines the effects of this uncertainty on the desirable structure and incidence of bounty regimes. Some key findings are that the greater this uncertainty the harder it will be to gather information about wrongdoing both within a firm and more generally because individuals will likely be reluctant to share information that might be relevant to enforcement. This has numerous effects. First, as gathering and sharing of information becomes more difficult it will become harder to deter and prevent wrongdoing, which in part depends on gathering and sharing information. Second, weaker gathering and sharing of information within the firm will hamper the ability of employees to work together cohesively. This not only worsens firm performance (which has its own costs), but also is likely to increase wrongdoing because poor firm performance is a key predicator of corporate wrongdoing. The analysis thus counsels caution in extending whistleblower bounties to areas where the underlying law is uncertain, provides insights on how one might design a bounty system in light of this uncertainty (e.g., differentiating between internal and external whistleblowers, varying bounties by firm size), and lays out certain steps that might be taken to ameliorate some of the identified effects of uncertainty.
Local government fiscal health is typically assessed using objective financial indicators, but little is understood about how local officials subjectively understand their own fiscal health. We compare self-assessment data from the Michigan Public Policy Survey with financial data on Michigan local governments to explore the extent to which self-assessments align with conventional financial indicators. Qualitative results reveal that local officials emphasize long-term spending pressures (e.g. roads, infrastructure) and external factors, such as uncertainty around property values and state aid (i.e. revenue sharing) payments, when assessing their fiscal health. Quantitative results provide some corroborating evidence, but in general, conventional indicators are not powerful predictors of self-assessments, especially for high-stress governments. We believe that part of the disparity is that financial indicators do a poor job of capturing what local officials say they are most worried about. We suggest that self-assessments may be a useful supplement to conventional measures in capturing “true” fiscal health.
Governments have increasingly relied on exchange rate stabilization policies, specifically intervention operations in currency markets and capital controls, to offset external shocks. The focus on exchange rate stabilization is not limited to countries with pegged exchange rate regimes. Indeed, a number of countries that currently actively intervene in currency markets self-describe as floaters. The U.S. has responded by raising concerns that these policies amount to currency manipulation. Article IV of the IMF Articles of Agreement requires that members “avoid manipulating exchange rates” in order to gain an unfair competitive advantage over other members. Separately (since 1989) the U.S. Treasury must report to Congress biannually regarding whether individual trading partners are manipulating currencies for unfair advantage. This talk will examine both the theoretical underpinning and empirical evidence on currency intervention and manipulation, with the goal of better understanding when exchange rate stabilization is effective from the point of view of domestic policy-makers and when it should be considered manipulative from a global perspective.
The massive dollar amounts associated with student loan debt and the impact on individuals and the financial stability of the overall economy has attracted the attention of journalists, economists, and average Americans. There are, however, several myths associated with these eye-popping numbers, and Susan Dynarski, Professor of public policy, education and economics will discuss a few of these myths in our January Blue Bag Lunch Talk.
For example, in a recent paper for Brookings, "The Trouble with Student Loans? Low Earnings, Not High Debt," Professor Dynarski debunks the popular notion that more student debt leads to higher student loan default rates.
In fact, research shows that default rates are highest among individuals with smaller loan balances. Students borrowing under $5,000 default at a rate of 34 percent, compared to 18 percent for those borrowing more than $100,000.
Among policy proposals advocated by Professor Dynarski to address the student loan crisis is to automatically enroll borrowers who are late on payments in income-based repayment, or adjust loan payments each pay period, similar to the current income-tax withholding system.
This will be a presentation of two large-scale field experiments designed to test the hypothesis that group membership can increase participation and pro-social lending for an online crowdlending community, Kiva. The first experiment uses variations on a simple email manipulation to encourage Kiva members to join a lending team, testing which types of team recommendation emails are most likely to get members to join teams as well as the subsequent impact on lending. We find that emails do increase the likelihood that a lender joins a team, and that joining a team increases lending in a short window following our intervention. The impact on lending is large relative to median lender lifetime loans. We also find that lenders are more likely to join teams recommended based on location similarity rather than team status. Our results suggest team recommendations can be an effective behavioral mechanism to increase pro-social lending. In a second field experiment, we manipulate forum messages to explore the underlying mechanisms for teams to be effective.
The rebirth of Detroit is dependent on a multitude of factors including issues related to urban infrastructure, the revitalization of neighborhoods, and beyond. Critical to this rebirth is investment in the city. For the city administration, this investment means being able to collect sufficient tax revenues to turn on streetlights, police neighborhoods, replace infrastructure, and finance other projects. Unfortunately, one consequence of the challenges faced by the city has been a culture of non-payment of the taxes owed. Over the last three years, the Master of Accounting students at the Ross School of Business have worked closely with the city to help address these non-payment issues. This talk will describe the projects the students have worked on, the benefits to both the city and to the students, and the work that still needs to be done. We will be joined by the city’s Director of Audit and Compliance, Odell Bailey.
Historically, public infrastructure systems such as roads, water utilities, and schools are financed using a combination of tax revenue, government and revenue-backed bonds. This system has repeatedly fallen short due to insufficient tax revenue and political aversion towards funding “social infrastructure”. Especially for schools, the access to quality infrastructure is highly correlated (in the US) to poverty, stemming from property values, credit worthiness and other factors. A recent bill (not passed) required a 1:6 leverage of federal with state and private finance, compared to 1:12 in Europe and 1:30 proposed under the Climate accords. Either infrastructure has not been built or upgraded, or private capital has stepped in the breach. At the Center for Smart Infrastructure Finance, we're asking whether data-driven models can close the gap by taking advantage of the internet of things (IoT): smart sensors that deliver information which can be monetized. This seminar will explore how private financing models that leverage digital data supply chains to attract 'efficient capital' (e.g. insurance, options trades, debt securities, variable interest rate bonds) can be adapted to financing public infrastructure while limiting recourse to the citizens that use it, and leveling the economic disparities of access.
Professor Sanjukta Paul will discuss her draft chapter, part of a larger book project, that the surrounding developments in the law, in economic thought, and in the organization of economic activity. March, 2023.
Jeffery Zhang presents his research, co-authored with Jeremy Kress, which argues that using the term “macroprudential” to describe modern financial regulation is a myth. February, 2023.
Debotri Dhar will explore the insights a mixed-methods study can offer to our gendered understandings of violence, vulnerability and risk, and discuss innovative policy measures. November 2022.
Professor Seyhun and his collaborators investigate racial differences in insider trading behavior by corporate leaders to evaluate whether African-American corporate executives have equal access to networks that generate valuable insider informati
Peter Adriaens explains how Environmental, Social & Governance (ESG) measurement, Corporate Social Responsibility (CSR), and Socially Responsible Investing (SRI) are important in managing growth and climate risks in the capital
Linda Tesar reviews some recent evidence on the impact of COVID-19 on economic activity in the US and abroad and discusses some of the ways that macroeconomists have begun to model the "COVID shock" and its economic effects.
