Mah Ebrahimi Pronounced: Mah (rhymes with car) Eh-brah-hee-mee

Publications

• “Trading Opportunities around Morningstar Stock Rating Changes”, The Journal of Investing, Dec 2022
  (with Paul J. Bolster & Emery A. Trahan) (link)
  Show Abstract
  The authors examine Morningstar information changes stemming from changes in their 5-Star stock-rating system. Converse to many studies of other second-hand information effects, Morningstar rating changes lead to abnormal returns (ARs) that persist for 30 days subsequent to the information release. This information may be used to derive alpha-generating trading strategies. Statistically significant positive ARs persist for 30 days postannouncement for upgrades to 4 and 5 stars, while significant negative ARs persist for 30 days postannouncement for upgrades to 2 and 3 stars and for downgrades to 4, 3, 2, or 1 star. Traders can use this information to devise long, short, and long–short trading strategies. Morningstar’s analysis has high credibility, particularly with retail investors. Morningstar changes a stock’s rating when the price of the stock moves further from the intrinsic value estimate derived by Morningstar’s model, suggesting that its analysis of the current stock price relative to intrinsic value and the timing of the rating change provide some relevant information to the market.
  
  

Working Papers

1. DARPA’s Role in Financing Innovation: Do Program Managers Have Private Information?
   (Job Market Paper, with Aldo Musacchio & Debarshi Nandy)
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2. DARPA’s Role in Financing Innovation: A Descriptive Analysis of Funding Allocations and Outcomes
   (with Aldo Musacchio & Debarshi Nandy)
   Show Abstract
   This paper provides the first systematic descriptive analysis of the Defense Advanced Research Projects Agency’s (DARPA) funding allocations and innovation outcomes using newly assembled project–grantee–year data covering 2012–2019. We link FOIA-obtained DARPA disbursements to grantee characteristics, program classifications, program manager (PM) biographies, USPTO patent outcomes, and Department of Defense follow-on contracts. Our analysis addresses four central questions raised in the literature on public R&D: (i) whether different program types (basic, applied, advanced technology development) receive systematically different levels of funding; (ii) whether DARPA’s portfolio is concentrated among a small set of large grantees; (iii) whether lobbying intensity and political cycles shape allocations; and (iv) whether DARPA directs resources toward industries experiencing high growth, and with what outcomes. We further examine heterogeneity by grantee type (private, public, university) and PM background (industry, academia, military). The results highlight DARPA’s dual strategy of seeding entry by private firms while maintaining strong ties with established incumbents, and reveal systematic differences in continuation, concentration, and innovation outputs across grantee and allocator types. Beyond describing DARPA’s funding landscape, our findings establish a foundation for causal analysis of the DARPA's funding mechanisms.
   
   
3. A New Dataset on DARPA’s Role in Financing Innovation
   (with Aldo Musacchio & Debarshi Nandy)
   Show Abstract
   We introduce a new panel dataset of the Defense Advanced Research Projects Agency (DARPA), covering 2012–2019. Built from FOIA-obtained disbursement records, USAspending data, USPTO patent filings, and hand-collected PM biographies, the dataset links DARPA projects to innovation and adoption outcomes at project–grantee–program manager (PM)–year granularity. Our contributions are threefold. First, we connect DARPA awards to project-relevant patents and citations using a NAICS–CPC crosswalk, enabling field-specific measures of technological impact. Second, we compile biographical profiles of DARPA PMs, allowing analysis of how allocator discretion and prior experience shape funding outcomes. Third, we match DARPA-funded projects to follow-on Department of Defense contracts, tracing diffusion from R&D to procurement. By providing DARPA-specific microdata that complement broad resources such as NIH grant–publication datasets and the Government Patent Register, this dataset offers a foundation for studying informational asymmetries, favoritism, and efficiency in public R&D allocation.
   
   
4. Does Having Student Debt Hurt Households’ Ability to Withstand Recessions?
   (with Karthik Krishnan & Pinshu Wang)
   Show Abstract
   We assess the relationship between the level of educational debt and ability of households to withstand the negative impact of recessions that happen around the time they graduate from college. Households with higher student debt where household head experiences a recession shortly after graduation from college have lower family income and spend a shorter amount of time being employed in full time jobs. These effects are the strongest during the early part of one’s career, but weaken (in aggregate) after that. Our study indicates that policymakers and academics trying to understand the impact of recessions on economic outcomes may have to consider the impact of student loans.