PM 465 - Advanced Multivariate Analysis

Institution:

University of Rochester

Subject:

Description:

The first part of this course introduces general estimation frameworks including least squares (specifically, least squares as applied to multivariate models, and nonlinear least squares), maximum likelihood, generalized method of moments, and some corresponding variants (e.g., quasi-likelihood, Monte Carlo methods, and instrumental variables). The second part of the course focuses on the application of the preceding estimation methods to the development and analysis of qualitative and limited dependent variable models (e.g., logit, probit, multinomial/conditional/nested logit, multinomial probit, mixed logit and probit, and censored and truncated data), duration models (e.g. Kaplan-Meier product limit estimator, Cox's proportional hazard model, and full parametric specifications), and multivariate models (e.g., multivariate regression, sample selection models, and simultaneous equation models).

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.rochester.edu

Phone Number:

(888) 822-2256

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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