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Curriculum Vitae

Gaurab Aryal

Placement Director: Neil Wallace
    (814) 863-3805
    neilw@psu.edu


 Graduate Secretary &
Placement Assistant:
Lynn Sebulsky
    (814)865-1458
    lms50@psu.edu

Contact Information:
Gaurab Aryal
  Office: (814) 865-6148
  Cell: (814) 321-1902
E-mail: gxa914@psu.edu
Website: http://sites.google.com/site/gaurabaryal
Curriculum Vitae

CITIZENSHIP:

 
  • Nepal (F-1)

EDUCATION:

 

 

 
  • Ph.D. Economics, The Pennsylvania State University (expected completion July 2010)
  • M.S. in Quantitative Economics, Indian Statistical Institute, New Delhi, India June 2004
  • B.A (Honors) Economics, University of Delhi, Shri Ram College of Commerce, June 2002.

PH.D. THESIS:

 

 

  • “Essays in Structural Estimation of Multidimensional Screening Models"
    Thesis Advisors:  Isabelle Perrigne and Quang Vuong

FIELDS:

 

 
  • Primary: Industrial Organization, Applied Microeconometrics
  • Secondary: Microeconomic Theory, Game Theory.

PAPERS:

 

 

 
  • Working Papers:
    1. “Identification of Insurance Models with Multidimensional Screening,” with Isabelle Perrigne and Quang Vuong. (Job Market Paper 1)
    2. "Competition and Nonlinear Pricing in Yellow Pages,” with Yao Huang. (Job Market Paper 2)
    3. “An Insurance Model with Bi-Dimensional Screening,” with Isabelle Perrigne.
    4. “Nonidentification of Insurance Models with Probability of Accidents,” with Isabelle Perrigne and Quang Vuong.
  • Work in Progress:
    1. “An Empirical Analysis of Multidimensional Screening in Automobile Insurance,” with Isabelle Perrigne and Quang Vuong.
    2. “Car Choice and Insurance Coverage,” with Isabelle Perrigne.
    3. “Stackelberg Common Agency Game.”
    4. "Identification of Multiproduct Nonlinear Pricing.”

GRANTS & FELLOWSHIPS:

 
  • Research Support (Summer 2007), Dept. of Economics, Penn State
  • Research Fellow under Professor Isabelle Perrigne and Professor Quang Vuong
  • Graduate Fellowship, Indian Statistical Institute, N-Delhi, India

TEACHING EXPERIENCE:

 
  • Instructor: Principles of Microeconomics (Undergraduate): Summer 2005 and 2006.
  • Instructor: Statistical Foundation of Econometrics (Undergraduate): Summer 2008.
  • Teaching Assistant and Recitation Leader: Intermediate
  • Microeconomics Analysis. (Fall 2004-Fall 2007).

RESEARCH EXPERIENCE:

 
  • Research Assistant for Professors Isabelle Perrigne and Quang Vuong since Fall 2007.

PRESENTATIONS & OTHER PROFESSIONAL ACTIVITIES:

 

 
  • Stanford University, SITE (conference): Summer 2009.
  • Pennsylvania State University. October 2009. 

REFERENCES:

 

 
  • Prof. Isabelle Perrigne, 511 Kern Graduate Building, University Park, PA 16802. Tel: +1-814-863-2157; E-mail: perrigne@psu.edu
  • Prof. Quang Vuong, 613 Kern Graduate Building, University Park, PA 16802. Tel: +1-814-863-2158; E-mail: qvuong@psu.edu
  • Prof. Mark Roberts, 513 Kern Graduate Building, University Park, PA 16802. Tel: +1-814-863-1535; E-mail: mroberts@psu.edu
  • Prof. Vijay Krishna, 516 Kern Graduate Building, University Park, PA 16802. Tel: +1-814-863-8543; E-mail: vkrishna@psu.edu

THESIS ABSTRACT

Essay 1. “Identification of Insurance Models with Multidimensional Screening” (with I. Perrigne and Q. Vuong)

 

We study the identification of insurance models with multidimensional screening, where insurees are characterized by risk and risk aversion. The model is solved using the concept of certainty equivalence under constant absolute risk aversion and an unspecified joint distribution of risk and risk aversion. The paper then analyzes how data availability constrains identification under four data scenarios ranging from the ideal situation (continuum of contracts and no truncated damage distribution) to the most realistic one (finite contracts with a truncated damage distribution). The observed number of accidents for each insuree plays a key role in identification. Despite bunching in multidimensional screening, we show that the joint distribution of risk and risk aversion is identified. With finite contracts and a truncated damage distribution, the latter is identified up to the probability of damage being above the deductible. We also derive the restrictions imposed by the model on observables and propose several identification strategies for the damage probability at the deductible.


Essay 2. “Competition and Nonlinear Pricing in Yellow Pages” (with Yao Huang)

 

This paper proposes a structural framework to analyze the pricing strategies of two yellow page-advertising publishers. The data collected from the Yellow Page Association and the phone books suggest that the utility publisher is a leader in the market. Therefore, we consider a Stackelberg duopoly model of nonlinear pricing in which firms buying advertising are characterized by a bi-dimensional vector of tastes for the two directories. The model and the econometric specification incorporate the features observed in the data such as the quadratic price schedules and a basic free advertisement offered to all firms by both publishers. Empirical results show substantial heterogeneity among firms’ willingness to pay. The estimated model is used to assess the  welfare loss due to (i) asymmetric information, (ii) a merger between the two publishers and (iii) withdrawal of the non-utility publisher from the market.

 

Essay 3. “Insurance Model with Bi-Dimensional Screening” (with I. Perrigne)

 

This paper extends the Stiglitz (1977) model to incorporate heterogeneous preferences of insurees and random damage in the event of an accident. The insurees’ heterogeneity in both risk and risk preferences leads to a multidimensional screening problem. We show that the certainty equivalence without insurance coverage can be used by the insurer to optimally screen insurees. The certainty equivalence reduces the dimension of screening and leads to some pooling of insurees as implied by the results in the multidimensional screening literature. We show that the optimal coverage preserves the certainty equivalence ranking and that the deductible should be independent of damage despite its randomness. 

 

Essay 4. “Nonidentification of Insurance Model with Probability of Accidents” (with I. Perrigne and Q. Vuong)

 

 This paper studies the nonparametric identification of multidimensional insurance models where insurees are heterogeneous in both risk and risk aversion. Following the theoretical literature, the risk is measured as the probability of accident. When the data contain only information on whether an insuree has been involved in some accident we show that the joint distribution of risk and risk aversion is not identified.