An Empirical Model of the Medical Match

This paper develops a framework for estimating preferences in a many-to-one matching market using only observed matches. I use pairwise stability and a vertical preference restriction on one side to identify preferences on both sides of the market. Counterfactual simulations are used to analyze the antitrust allegation that the centralized medical residency match is responsible for salary depression. Due to residents' willingness to pay for desirable programs and capacity constraints, salaries in any competitive equilibrium would remain, on average, at least $23,000 below the marginal product of labor. Therefore, the match is not the likely cause of low salaries.National Bureau of Economic Research (Nonprofit Fellowship)Gardner and Florence Call Cowles Foundatio

Toxic exposure in America: estimating fetal and infant health outcomes

We examine the effect of toxic exposure on U.S. infant and fetal mortality rates between 1989 and 2002 from toxic pollution released by facilities reporting to the Toxic Release Inventory (TRI). Unlike previous studies, we control for toxic pollution from mobile sources and from non-TRI reporting facilities. We find significant adverse effects of TRI exposure on infant mortality. There is evidence that health effects vary across media: air and water having a larger impact than land pollution. And, within air, we find that releases of carcinogens are particularly problematic for infant health outcomes. We estimate that the average county-level decreases in TRI concentrations between 1988 and 2002 saved in excess of 13,800 infant lives.Newborn infants - Mortality ; Public welfare

Essays in Empirical Matching

This thesis combines three essays on empirical applications and methods in two-sided matching markets. The first essay uses existing methods to estimate preferences for schools using rank order lists from New York City's new high school assignment system launched in Fall 2003 to study the consequences of coordinating school admissions in a mechanism based on the student-proposing deferred acceptance algorithm. The second essay develops techniques for estimating preferences in two-sided matching markets with non-transferable utility using only data on final matches. It uses these techniques to estimate preferences in the market for family medicine residents. These estimates are then used to analyze two economic questions. First, it investigates whether centralization in the market for medical residents is primarily responsible for low salaries paid to medical residents. Second, it analyzes the effects of government interventions intended to encourage training of medical residents in rural areas. The final essay studies estimation and non-parametric identfication of preferences in two-sided matching markets with non-transferable utility. It studies the special case in which preferences of each side of the market is vertical and data from a pairwise stable match, in a single large market is observed.Economic

Winning in Digital Economy

Even in best of the times, big companies find it difficult to sustain in the market with the same line of products. There is always a threat from the competitors and the new entrants of the market, engaged in creating new businesses and products. With the coming of digital age & fierce competition, breathing space of company is reduced to minimum. Managers of old industrial companies are sending SOS calls and looking forward for new business models. The need of the time is to listen to the survival calls for the ‘clicks-and-bricks’ business model that blends the traditional off-line assets with digital initiatives. The Internet is encouraging a shift from industrial age “brick and mortar” strategic thinking to a greater emphasis on the use of alliances

Identification and Estimation in Two-Sided Matching Markets

We study estimation and non-parametric identification of preferences in two-sided matching markets using data from a single market with many agents. We consider a model in which preferences of each side of the market are vertical, utility is non-transferable and the observed matches are pairwise stable. We show that preferences are not identified with data on one-to-one matches but are non-parametrically identified when data from many-to-one matches are observed. The additional empirical content in many-to-one matches is illustrated by comparing two simulated objective functions, one that does and the other that does not use information available in many-to-one matching. We also prove consistency of a method of moments estimator for a parametric model under a data generating process in which the size of the matching market increases, but data only on one market is observed. Since matches in a single market are interdependent, our proof of consistency cannot rely on observations of independent matches. Finally, we present Monte Carlo studies of a simulation based estimator

Moral Rights: International Framework and Indian Approach

In the wake of increasing globalization and technical advancements in the digital field, the dissemination of creative work has become easier than ever. However, this development has come with its own set of challenges, particularly for Intellectual Property Law, as most of online transfer of information is unregulated. Digitalization has lead to the imminent need for standardized and stringent protection of an author‟s work. While this protection is mainly conceived as commercial right of the author on his work, there is another fundamental element to it, which is equally important and cannot be neglected, i.e., moral rights. These rights include right of attribution and integrity and are so inextricably related, that they stay with the author, even after transfer of economic rights on the work. In order to ensure effective globalized protection, there is a requirement for minimum standards of protection in all domestic laws, as was provided in the TRIPS agreement. This paper analyzes the Moral Rights regime as envisaged by the TRIPS agreement, and the monoist and dualist approaches that have been adopted by different countries. It also analyzes the evolution of moral rights in India

Cognitive system to achieve human-level accuracy in automated assignment of helpdesk email tickets

Ticket assignment/dispatch is a crucial part of service delivery business with lot of scope for automation and optimization. In this paper, we present an end-to-end automated helpdesk email ticket assignment system, which is also offered as a service. The objective of the system is to determine the nature of the problem mentioned in an incoming email ticket and then automatically dispatch it to an appropriate resolver group (or team) for resolution. The proposed system uses an ensemble classifier augmented with a configurable rule engine. While design of classifier that is accurate is one of the main challenges, we also need to address the need of designing a system that is robust and adaptive to changing business needs. We discuss some of the main design challenges associated with email ticket assignment automation and how we solve them. The design decisions for our system are driven by high accuracy, coverage, business continuity, scalability and optimal usage of computational resources. Our system has been deployed in production of three major service providers and currently assigning over 40,000 emails per month, on an average, with an accuracy close to 90% and covering at least 90% of email tickets. This translates to achieving human-level accuracy and results in a net saving of about 23000 man-hours of effort per annum