Current Research

Safiya Castel


Safiya Castel - Management and Organizations

When Helping Others Hurts You: Differences in the Evaluation of Prosocial Job Seekers Based on Group Membership

Abstract Summary: While generosity is typically rewarded, I propose that members of low status groups are penalized for acts of service that benefit other members of their ingroup. Low status group members who help members of their ingroup are likely perceived as highly identified with their ingroup. As highly identified low status group members are discriminated against because they are thought to hold beliefs that reject the legitimacy of the status hierarchy, low status group members who display generosity towards their ingroup may face hiring discrimination. Members of high status groups, on the other hand, are not likely to be penalized for their generosity, regardless of who is being helped. I will propose 4 studies to test this phenomenon and corresponding mechanisms.

Alex Fabisiak



 Alex Fabisiak - Finance

 Financing Growing Tuition Costs: The Role of Income Contingent Loans

Abstract Summary: This paper derives the optimal education investment decisions in a model where students must finance their tuition.  I intend to show that the flexible repayment option provided by Income Contingent Loans acts as insurance for students who have poor labor market outcomes.  However, they may also weaken incentives for high ability students to invest in education, or even hamper their ability to borrow sufficient capital.

Chady Gemayel

Chady Gemayel - Finance

When Agency Costs are Worth Paying - Comparing Inside and Outside CEOs

Abstract Summary: I develop a relevant labor pool instrument to identify the net difference between CEOs that were hired internally (Inside CEOs), and CEOs with no prior interaction with the hiring firm (Outside CEOs). Outside CEOs are less prone to agency issues than Inside CEOs, but may be less familiar with the firm. I isolate CEO-driven agency issues by instrumenting CEO type by the number of geographically local firms, weighting each by its similarity in firm characteristics. Given a larger relevant labor pool, a firm is more likely to employ an Outside CEO. Using this instrument in 2SLS regressions, I find that Inside CEOs outperform Outside CEOs across a number of firm-level performance metrics, including Tobin's Q, asset growth, and sales growth.

Hossein Jahandideh

Hossein Jahandideh - Decisions, Operations and Technology Management

Resource Allocation in Production Systems and Services under Uncertainty with Learning

Abstract Summary: We study the problem of allocating resources to minimize costs or to maximize revenue in food-production industries and in services. We consider three different types of industries which face model uncertainty and require learning considerations. The first problem arises in distilleries and refineries, where a catalyst is used in a reactor to refine raw material. Catalyst performance decays as it is consumed. The productivity of a catalyst is not known a priori and is learned through production observations. We must decide when to replace the costly catalyst to minimize the total inventory costs and catalyst replacement costs. We develop a heuristic to solve this problem and a lower bound to evaluate the quality of the heuristic. We test our methods with real data from a leading food processing company and show our methods outperform current practice. The second problem is on production of products for which the value increases with age. Such products include whiskey and wine. We analyze the decision of a firm that is considering introducing an older aged product to the market. The older age product has uncertain demand and competes with the younger age product both in production capacity and in the market demand. The goal is to maximize the expected discounted revenue extracted from a fixed yearly production capacity, while considering uncertainty in demand, product substitution, and the learning process.  We solve a simple version of the problem in closed form. We use the observations from the closed form solution, in addition to some theoretical properties to derive heuristics for more complex settings. The third problem is in cloud computing services. Customers require different classes of service. The service provider has a limited capacity per unit time and must allocate this capacity to arriving customers to maximize its revenue. There is uncertainty regarding completion times of each class of service, which requires learning over time.

Mahyar Kargar

Mahyar Kargar - Finance

Personal Website

Financial Intermediary Leverage over the Business Cycle

Abstract Summary: Recent cross-sectional tests of intermediary asset pricing models find conflicting cyclical properties of intermediary leverage and opposite signs for the estimated price of risk for intermediary capital shocks. To reconcile these empirical findings, I propose a continuous-time heterogeneous-agent model with two intermediary sectors: banks and broker-dealers. The model can reproduce the cyclical patterns observed on the balance sheets of different financial intermediaries. Dealers face a risk-based capital constraint which leads to pro-cyclical equilibrium leverage, while the market-clearing condition for the risky asset results in counter-cyclical bank leverage. The model implies a positive price of risk for both bank capital and dealer leverage shocks. Consistent with evidence on financial sector's balance sheet adjustments during the 2008 crisis, broker-dealers reduce their risky asset holdings in crisis states, while banks are willing to absorb these assets due to the increase in risk premiums.

Zhipeng Li

Zhipeng Li - Finance

Organization Capital and Credit Risk

Abstract Summary: My research contributes to the empirical determinants of credit spread fluctuations. One central finding is that labor market conditions have a huge impact on credit risk. Variations in the aggregate organizational capital/total asset ratio help to capture a large proportion of unexplained individual credit spread changes. This is because if a significant part of the cash flow is generated from organizational capital, then whenever key talents who own partial claims to the organizational capital threat to leave for better compensation, the cash flow available to investors suffers a hit. Therefore, labor market conditions may affect the outside option value of key talents, volatilities of the asset value, default probabilities and then credit spreads.

Jonathan Lim

Jonathan Lim - Marketing

The Influence of Magnitude Matching on Causal Selection in Causal Chains

Abstract Summary: How do people reason through causal chains (e.g., A -> B -> C), selecting the appropriate cause (A or B) out of a series of causes? This is a question with implications for consumers, who often need to reason through the explanations given to them by companies for issues such as accidents, recalls, and other negative events. Many scholars in the past have been interested in this question of causal selection, but no definitive answer has emerged as to how far back in a causal chain people go to select the appropriate cause. The proposed research seeks to add to the body of work on causal selection in causal chains by suggesting that magnitude matching is an important factor in people's selection processes. Specifically, people will go back in the chain until they find a cause whose magnitude matches the magnitude of the effect. A set of studies is proposed to test this magnitude matching principle, and future directions are discussed.

Shekhar Mittal

Shekhar Mittal - Global Economics and Management

Personal Website

I am interested in poverty and development issues in emerging economies. Specifically, I want to understand how the incentives of various stakeholders such as politicians, bureaucrats, and citizens vary. I also want to analyze the impact of this variation towards achieving intended developmental outcomes. Currently, I am involved in two  projects.

One of them (along with Prof. Aprajit Mahajan) is focused on examining large-scale tax data from the government of Delhi.

       1.    It has been argued that a key advantage of value-added tax is the emphasis it lays on creation of paper trails through tax returns. However, there is little evidence on how such a system actually plays out in a developing economy with low compliance. We use a specific policy reform in a quasi-experimental framework to understand how and to what extent paper trails improve tax collections and through what mechanisms.

       2.    Tax officials from India (and other countries) argue that firms within a VAT system collude to create fictitious paper trails. This has led to emergence of "bogus" firms who issue fake receipts to genuine firms enabling them to evade taxes. A key challenge in improving tax compliance then is to identify such bogus firms. The plan is to use machine learning algorithms on network data to develop a predictive algorithm for "bogus" firms (based on a training data set with identified fraudulent firms) that will then be more likely to be audited by the tax authority.  

In another project (along with Prof. Aprajit Mahajan and Stefano Fiorin), I focus on a devolutionary scheme introduced by the Government of Delhi to create local decision making bodies called Mohalla Sabhas (MSs). These MSs will have considerable allocative as well as oversight powers over neighborhood spending. In principle, citizens can propose local public good projects, vote to allocate funds for implementation and authorize funding to contractors for work on selected projects. We are running experiments to test, first, if the MSs will be truly representative and will local public spending be aligned with local preferences, or will discrepancies still be present (for example, due to low participation by disadvantaged groups and/or capture by local elites)? Second, how can the state increase participation of citizens in MS, particularly participation by disadvantaged groups?