Fall 2015 - 60170 - PA397 - Introduction to Empirical Methods for Policy Analysis

Quantitative methods provide the means to integrate empirical evidence into all phases of the public policy process. These methods are used in describing policy problems, analyzing policies and their impacts, and framing management decision-making. This course will develop an understanding of basic quantitative tools, their applications in public policy and management, and strategies to interpret and communicate empirical evidence to multiple audiences. The methods discussed include modeling, optimization, sensitivity analysis, probability theory, statistical inference, estimation, and prediction. These methods will be applied to constrained decision-making (including linear programming), probabilistic dimensions of policy choice (including the application of Bayesian techniques), statistical modeling of policy problems, and statistical forecasting. The course is taught in a problem-solving applications mode, with frequent computer applications, rather than a theoretical and mathematical approach. The limitations of quantitative methods are also addressed.

As the first course in the MPAff’s quantitative methods sequence, the emphasis is on broad exposure to techniques and developing skills through applications in homework assignments. It is highly recommended that this course be taken in the fall semester of the first year. The background prerequisites are college level algebra (including interpretation of graphs), matrix algebra, basic differential calculus, probability theory, and simple descriptive statistics.

Student progress will be evaluated on three types of work: (1) 5 problem sets (40% of the final grade) are designed to demonstrate competency over fundamentals and to provide practice in the application of quantitative methods to problems of public policy; (2) two exams, mid-term and final (each accounting for 25%); and (3) class participation (10%).