Pardee RAND Graduate School Course Catalog

Kenneth Kuhn teaches a course

Diane Baldwin

Kenneth Kuhn teaches a course

Course selection is subject to change. Some elective courses are not offered every year, and seminar topics may vary from year to year.

Core Courses

Cost Benefit and Cost Effectiveness Analysis (Keeler/Pacula, .5 unit)
This course introduces two related analytic tools used to structure policy problems and evaluate options: cost benefit and cost effectiveness analysis. These tools apply economic methods to facilitate a more efficient allocation of resources in situations where markets are not working well. Cost Benefit analysis is used in fine tuning public investments and regulations. It consists of techniques for converting all the estimated inputs and outcomes into current dollar equivalents. Cost-effectiveness can be used whenever all outcomes can be expressed in a single non-financial metric, but has been most commonly used in health care, where decision makers may value all people's health equally and are reluctant to assign a dollar value to health.

Decision Analysis (Keeler, .5 unit)
This mini-course introduces two commonly used analytic tools that can be used to structure policy problems and evaluate options: difference equations, decision analysis. By the end of the course, students should be able to set up problems, apply the tools if appropriate, interpret the results, and understand the limitations of these methods.

Empirical Analysis I: Probability and Statistics (Kuhn, 1 unit)
This course introduces students to the technical and practical statistical knowledge necessary for providing informed and careful policy analysis. The topics include descriptive statistics, principles of probability, discrete and continuous random variables, elementary sampling, and tests of hypotheses associated with the univariate normal distribution. The computer program Stata is taught and used throughout.

Empirical Analysis II: Regression Analysis (Han, 1 unit)
This course examines the theoretical underpinnings and the practical application of multivariate regression models, with an emphasis on Ordinary Least Squares. The course uses extensive analytic derivations, practical examples, and presentations by RAND researchers. A significant portion of the course is devoted to understanding the uses and limitations of regression techniques in policy analysis.

Empirical Analysis III: Econometrics (Martorell, 1 unit)
Often in policy analysis, the crucial analytic question concerns the causal effect of a policy, program, or procedure. This course provides an in-depth consideration of the problem of estimating causal effects and the three leading approaches to doing so in applied work: random assignment, fixed effects, and instrumental variables. To do so, the course develops linear asymptotic theory, which is applied to analyzing causal models and then to analyzing data that is not independent and identically distributed (non-i.i.d.). Non-i.i.d. models considered include heteroscedasticity, panel and clustered data, and time series. The course is taught through a combination of written problem sets, data analyses, and close reading of recent, exemplary papers.

Microeconomics I (Powell, 1 unit)
Economic models provide a tool for anticipating the consequences of policy decisions and evaluating their effectiveness. These models are used in the analysis of traditional economic issues like compensation policy and minimum wages as well as the analysis of health care, education, law, and other areas. This course provides a background in microeconomic theory that is used in policy analysis. The main topics are consumer theory, theory of the firm, and partial equilibrium analysis.

Microeconomics II (Maestas/Gutierrez, 1 unit)
This course explores the concepts of market equilibrium and market failure. It begins by developing the techniques necessary for understanding equilibrium in a complex economy with many simultaneously operating markets, and the methods economists use to evaluate policy in this context. Specific topics will include public goods, externalities, the economics of property rights and legal institutions, and the fundamental welfare theorems. The second half of the course will be devoted to understanding the economics of information, and the way in which information flows govern economic equilibrium. Specifically, we will explore situations of asymmetric information, adverse selection, moral hazard, uncertainty, and insurance.

Operations Research I (Alkire/Bennett, 1 unit)
This course teaches prescriptive and descriptive modeling techniques that can be used to structure policy problems and evaluate options. It focuses on some commonly used analytic tools and software for optimization and simulation. Additionally, we will discuss two specific types of problems: Markov processes and Queuing Systems. More broadly, the course is also an introduction to problem formulation. By the end of the course, students should be able to structure policy problems, formulate mathematical models that address them, use the tools to solve simple problems, interpret the results, and understand the limitations of these methods.

Policy Analysis I: Perspectives on Public Policy Analysis (Ryan/Wasserman, 1 unit)
The purpose of the course is to introduce PRGS students to the profession of public policy analysis and to provide them with an overview of the tools of the trade. This includes describing the general framework, methods, ethics, and professional standards used by policy analysts, as well as techniques for communicating with clients. In short, the course is designed to help students develop a professional identity.

Policy Analysis II: Case Studies (Ryan, .5 unit)
This five-week, case-study course is designed to expose students to the many complexities of policy analysis. Examples will be drawn from across the policy-analysis spectrum and will cover issues related to: (1) formative evaluations where analysts have to define and scope policy problems, assess intervention options, and design implementation strategies; (2) process evaluations where analysts have to assess and improve on existing program implementations or policies; and (3) summative evaluations where analysts have to assess the impact of a program and advise on whether it should be continued or scaled-up. Each week, materials on a specific case and will be provided and students will be expected to discuss the case in class.

Policy Analysis III: Organizational Culture of Government Institutions (Marquis, 1 unit)
Why do government institutions behave the way they do? This course will provide students with an understanding of the context and reality of public policy making and implementation from the perspective of government agencies and other institutions. Through the discussions and reading, students will learn the influences and incentives on the behavior of government institutions, how they differ in their behavior and perspective; the elements of organizational theory applicable to public organizations and those that are not; the possibility for leadership in public policy making and implementation; and the reality of implementation. The focus will be largely on federal institutions, however, all of the material will be relevant to the state and local level.

Social and Behavioral Science I: Social Science Perspectives (Bird/Meredith/Ryan/Nelson, 1 unit)
The purpose of this course is to expose first year students to some of the key theoretical and analytic frameworks used in sociology, political science, psychology, and anthropology. The course focuses on how such frameworks can be used in policy analysis to generate important insights into potential policy options, implementation strategies, and, ultimately, recommendations for policy change.

Social and Behavioral Sciences II: Methods of Social Science (Berry, 1 unit)
The second course in the social and behavioral sciences sequence is designed to enable students: to learn how to translate policy issues into research questions and make use of alternative social science methods, including structured and qualitative, to answer them; to become more informed users and critics of policy research, to develop the capacity to write a comprehensive research proposal, and to prepare to work on RAND projects for OJT.

Understanding Macroeconomic Policy I (Neu, .5 unit)
Course is being developed.

Optional Preparatory Course

Mathematics for Policy Analysis (Ringel, 1 unit)
This course is a primer in the fundamental principles of mathematics used in Microeconomics, Statistics, Econometrics, Analytic Methods, and other PRGS courses. It is intended for entering PRGS students who do not have strong backgrounds in mathematics and quantitative methods. The Mathematica software package is used to help students understand and interpret the mathematical concepts taught in the course. This course covers: functions, particularly exponential and logarithmic functions, techniques of proof, single variable calculus, linear algebra (vectors, matrices, linear systems), multivariate calculus (integral and differential), sequences and series, optimization.

Anticipated Elective Courses

(Note: elective offerings are subject to change)

Advanced Econometrics I: Applied Non-Linear Modeling and Multi-Level Analysis (Sturm, 1 unit)
This course is a continuation of and complementary to Empirical Analysis III: Econometrics. This second year course extends the analysis to asymptotic theory for non-linear models, non-linear econometric models (e.g., NLLS, non-linear GMM, and ML), and considers structural approaches to estimation. In addition, it includes considerable empirical work. Specific models considered include the linear probability model, probit, logit, poisson regression, tobit, index function models, sample selection models, hazard models (discrete time and continuous time); and their generalizations to panel data, systems of equations, and the estimation and simulation of the parameters of stochastic processes commonly encountered in the analysis of dynamic systems in policy analysis.

(Economic Analysis and Quantitative Methods concentrations)
Pre-requisite: Empirical Analysis III

Advanced Econometrics II: Topics in Advanced Econometrics (Angrisani, 1 unit)
This ten-week course is complementary to Empirical Analysis III: Econometrics. While that course focuses on identification strategies in linear models, this course considers non-linear models as well as extensions of linear and non-linear models to panel data. The course first provides students with a basic understanding of the econometric theory behind non-linear models defined implicitly as solutions to an optimization problem. This allows students to get a better understanding of the relationship between the various estimation methods used in the course and their relative merits for different applications. Using that theory, the course considers some commonly applied non-linear models: binary, ordered and multinomial choice, censored and truncated outcomes, and duration models. The course also considers generalizations of these models for panel data and advanced methods for treatment evaluation. Emphasis is put on the policy relevance of such applications. Evaluation is based on biweekly problem sets and a take-home final exam.

(Economic Analysis and Quantitative Methods)
Pre-requisite: Empirical Analysis III or permission from the professors

Advanced Statistics for Policy Analysis (Moore, 1 unit)
This course will discuss the modeling and analysis of temporal and spatial data to inform policy issues. We will use software, namely the R system, which enables the exploration of such data. Employment data over time is a frequently encountered example of a temporal data set. Geographic data is an example of a spatial data set where the location of data points and their proximity to others is studied. Our examination of time series analysis will consider frequency-domain, relating to the number repeating events occurring per unit time, and time-domain, relating to events occurring at specific points in time, methods. For the analysis of spatial series we will use clustering, the assignment of objects to groups, and spatial or geometric methods. When the student completes this course he or she will be able to identify time and spatial series and their components as well possess the ability to undertake analysis of these data to support policy decisions.
(Quantitative Methods)

Pre-requisite: Empirical Methods 1, II, and knowledge of R system

Applications of Risk Analysis to Public Policy (Willis, .5 unit)
The methods of risk analysis provide tools and processes for helping policy makers decide what problems to address, how to address them and in which order to do so. They have been applied across diverse topics that are reflected in RAND research including public health, infrastructure design, acquisition management, and homeland security. The course introduces concepts of risk analysis and tools that can be used in all stages of risk management. Topics covered will include frameworks for risk management policy, probabilistic risk assessment for engineered systems, acquisition risk management, natural disaster risk assessment, human health risk assessment, risk analysis for strategic planning, terrorism risk analysis, and risk communication. In each case, the course will introduce tools and methods using policy relevant case studies as examples and highlighting inherent assumptions and limitations of each.

(Quantitative Methods and Social and Behavioral Science concentrations)

Applied Psychometrics (Miles, .5 unit)
This course aims to introduce students to the application of psychometric analysis, from a research perspective. Psychometrics involves measurements of people's beliefs, moods, attitudes, aptitudes, and abilities; measuring these constructs in people requires a set of tools that allow us to make links between the thing we are actually assessing (i.e. the answers to questions given by individuals) and the thing we are actually interested in (the psychological state of the individuals who have completed the measures). It is this distinction that makes psychological measurement both challenging and interesting. We cannot make decisions about policy to improve outcomes if we cannot measure those outcomes.

We will focus on the application of psychometric theory, not on the mathematical proof of that theory. Students should have an understanding of basic statistics, probability, correlation, and linear and logistic regression. The course will cover the development and testing of a psychometric instrument, developed by the student.

(Quantitative Methods and Social and Behavioral Science)

Behavioral Economics (TBD, 1 unit)
Decision-making is a very active area of research both in economics and psychology. There is ample evidence that individuals and groups do not conform to the predictions of classical rational models of behavior. Some of the anomalies that psychologists have discovered include framing effects, priming, non-standard discounting in time preferences, nonstandard probability weighting in risk preferences, and biases in multi-attribute choice evaluation. The field of behavioral economics focuses on two fronts. First, produce utility models that account for the most robust anomalies (e.g., cumulative prospect theory, hyperbolic discounting, mental accounting models, self-control models). Second, design experiments, or use field data, to test these utility models. Utility models allow economists to explore the “market implications” of consumer anomalies. Experimental data allows them to improve the descriptive accuracy of the models.

In this Behavioral Economics course, we will explore the most robust anomalies in the behavior of individuals and consumers. These include loss aversion, over-weighting of small probabilities, decreasing impatience, magnitude effects in discounting, salience effects, sunk cost effects, flat-rate bias, endowment effect, and inconsistent attribute weighting, among others. For each, we will review the evidence from experiments, discuss possible models that explain this behavior, and discuss the experimental evidence from testing these models.

(Economic Analysis and Social and Behavioral Science concentrations)

Big Data Applications (Davis/Winkelman, 1 unit)
This course will present a survey of Big Data tools and applications and will show how both techies and non-techies can easily use these technologies to facilitate analysis for complex policy challenges. The course will begin with an overview of major Big Data techniques as well as a review of existing projects and publications that demonstrate the potential impact that these techniques can have on policy research. The course will then introduce students to new open source and commercial tools for data analysis that mine the web, social media, and other ‘big’ data sets for policy relevant insights. After this initial exploration of tools, students will nominate other similar tools or techniques of interest for further exploration by the rest of the class.

In the second phase of the course, each student will identify an existing dataset (or one they could feasibly collect during the semester) and formulate a set of policy relevant questions that might be answered via exploration of the data with the previously identified tools. All ‘project’ ideas will be presented to the class, and students will be given the opportunity either to work individually, or to self organize into teams in order to execute projects. Project work might include direct use of any tools explored by the class, innovative combinations of those tools, or the creation of new tools by the students.

A third and final phase of the course will require project teams to devise strategies to effectively communicate the methods used and their results, for example, through dynamic and/or interactive visualizations. The course will culminate with a showcase in which teams will brief their projects to the broader PRGS and RAND community. We expect the showcase to serve as an opportunity for students to lead RAND researchers in the discovery of how Big Data techniques can positively supplement other policy research methods.

(Quantitative Methods concentration)

Dissertation Writing Workshop for Non-native English Speakers (Murphy, 0 unit)
This workshop is for graduate students who are non-native speakers of English and who are beginning to work on dissertations or to write for publication. The course will cover conventions of advanced academic writing and will address problems such as syntax, style, cohesion, register, and vocabulary more common to written than to spoken English. Students will work within the guidelines of the style manuals of their respective fields. Instruction will be individualized and will focus on the demonstrated needs of the students.
 

Economic Development (Kumar/Nataraj et al., 1 unit)
This course introduces basic challenges in economic development, with half of the course dedicated to microeconomic perspectives and half the course dedicated to macroeconomic perspectives.

(Economic Analysis and Social Science concentrations)

Effective Writing Techniques for Policy Analysts (Leuschner, 0 unit)
This workshop is designed to help students write and communicate effectively about public policy analysis. The course will cover such topics as identifying key policy messages, structuring a document for maximum effect, and developing a communication approach to address the needs of multiple audiences. Students will get hands-on practice in writing project descriptions, introductions, report/dissertation chapters, conclusions, and summaries. Students will work on one or more documents of their choice and will receive individualized feedback to help strengthen their writing skills.
 

Entrepreneurship (Gates, .5 units)
Entrepreneurship public policy seminar: What can governments do to support entrepreneurship? What things to governments do that impede entrepreneurship? This policy seminar will review the key policy issues related to entrepreneurship and the analytical methods used to assess the effects of public policy on entrepreneurship.

(Economic Analysis and Social Science concentrations)
(Policy Analysis course for cohort years 2011 and beyond)

Ethics and Public Policy (Wachs, .5 unit)
The meaning of ethics and morals. How do ethics impact public policy. Professional codes of ethics and their enforcement. What is conflict of interest and what should one do when confronting a possible conflict? What is corruption? What is an analyst's responsibility regarding corruption and impropriety? Ethics in the context of societies that differ dramatically — how does one practice in a country or culture where corruption is rampant? Whistle blowing as a complex phenomenon. How aspirational principles can be incorporated in policy analysis without violating ethical codes. Case studies of ethical dimensions of forecasting for public policy. Case studies of "earmarking" by Congress; Case studies of American contractors working abroad and the expectations of local governments regarding bribery.

(Economic Analysis, Quantitative Methods, and Social Science concentrations)
(Policy Analysis course for cohort years 2011 and beyond)

Finance and Accounting (Keating, .5 unit)
This course introduces essential topics in accounting and finance, including the objectives of financial accounting, the role of accounting information in making business decisions and in assessing corporate performance, corporate finance, and investments. Intended for students who will be conducting private sector analysis, such as business regulation and civil justice.

(Economic Analysis, Quantitative Methods, and Social Science concentrations)

Food Policy (Ringel, .5 unit)
The course deals with how governments—particularly that of the United States—design and implement policies and programs to foster social goals such as ensuring a sufficient, safe, affordable, and sustainable food supply. It examines why and how governments do or do not decide to set policies; reviews how stakeholders in the food system become involved in and influence policy development; identifies the social, cultural, economic, and political factors that influence stakeholder and government positions on policy issues; and describes the ways in which these factors promote or act as barriers to policies aimed at promoting the health of people and the planet. The course will use a case study approach to examine the policy formulation and implementation process for food policy issues related to economic development, trade, labor, social justice, nutrition, food safety, food security, and the environment.

(Economics and Social and Behavioral Science concentrations)

Game Theory (Burke/Duarte, 1 unit)
This course provides students with an introduction to game theory. It covers the four main types of games: (1) static games of complete information, (2) dynamics games of complete information, (3) static games of incomplete information, and (4) dynamic games of incomplete information. Numerous applications and topics are explored including asymmetric information, moral hazard, bargaining and auctions. Examples are drawn from economics, political science, and biology as well as other fields depending on student interest.

(Economic Analysis and Quantitative Methods)

Governance in Three Domains: Public, Corporate, Non-Profit (Wolf, .5 unit)
Governance has increasingly attracted both practical and theoretical attention in three different, not always connected, domains: corporations, government, and non-profit organizations. To evaluate and compare governance in these domains, this five-week course develops and applies an analytic framework built around several principal constructs, including the following: accountability (to whom, how frequently, with what powers of enforcement?); metrics (for measuring performance in relation to organizational objectives); and data requirements (disclosure, accessibility, reliability, frequency, legal obligations, opportunities and incentives for evasion, fraud, or other malfeasances). One purpose of the framework is to develop separate Report Cards for evaluating governance over time and across the three domains, and among particular firms, government agencies, and NGOs within each domain. The course will include sessions with prominent experts in each of the three flavors of governance. Presentations by fellows in fifth week of course will focus on assessments of governance in one or two specific entities in these domains.

(Economic Analysis and Social and Behavioral Science concentrations)
(Policy Analysis course for cohort years 2011 and beyond.)

Health Economics (Bauhoff/Huckfeldt, 1 unit)
This course emphasizes the application of economic theory and econometric analysis to important health policy questions. students apply standard models from the core curriculum, and then consider how market failures change the expected outcomes. As such, it provides good preparation for the qualifying examinations in economics and in quantitative methods. Topics include modeling the demand for health (and medical care) explicitly, the decision to buy insurance, selection bias in the context of health outcomes and health plan performance, and models of physician behavior. The class consists of a mixture of lectures and discussion of research papers in the field, with an emphasis on topical health policy questions. This course does not address issues of cost-effectiveness or cost-benefit analysis.

(Economic Analysis and Quantitative Methods concentrations)

Healthcare and Healthcare Reform (TBD, .5 unit)
Managed care dominated the health care scene in the United States for decades – reaching its zenith in the late 1990s. Its impact has been felt in a number of ways. Capitation financing, associated with managed care, was seen as an alternative way to pay for health care that would reign in the excesses of fee-for-service payment, which many agree has fueled the explosion of health care costs. The emergence of managed care as the dominant form of health care delivery and financing resulted in an alteration in the way health care was perceived and has impacted the roles of most, if not all, players in the health care system.

Most observers agree, however, that managed care — at least as originally conceived and practiced — is in retreat — and with the advent of health care reform, it’s not entirely clear what our near–term future looks like. Implementation of major aspects of the Affordable Care Act is happening now — and will continue over the next few years — perhaps reshaping our health care market dramatically – and perhaps not.

This course gives you an opportunity to examine issues in health care as the Affordable Care Act is being put into place at the national, state and local levels. The course assumes that you have a basic understanding of the mechanics of the health system; instead we will take on contemporary topics that will allow you to better understand health policy and politics in the current landscape.

(Policy Analysis course)

History and Public Policy (Selvin, 1 unit)

In both the public and private sectors, problem solving often involves historical reasoning. Issues are defined as being "like" earlier issues. Alternatives are gauged on assumptions about past trends and about factors that have previously influenced such trends. Whenever analysts or decision makers reason from analogies, project trend lines, or use time series data they act as historians. Yet explicit training in historical analysis or methods has not been a traditional part of policy analytic training. This course is designed to present history as it is encountered in a policy research or policymaking setting. Students learn basic historical research methods, become sensitive to the broad range of historical sources and learn to evaluate how historical data and analytical techniques have been "used" and "misused" in the policy arena. We can accomplish these methodological goals by exploring the history behind a set of contemporary policy issues. For example, past courses have focused on energy policy, welfare reform, criminal justice, transportation planning, and marriage and family law, among other issues.

(Social Science concentration)
(Policy Analysis course for cohort years 2011 and beyond)

Inform, Influence, and Persuade: U.S. Government Public Diplomacy, Public Affairs, Strategic Communication, Information Operations, and Psychological Operations (Paul, 1 unit)
What does the U.S. government do to inform, influence, and persuade foreign populations in pursuit of American policy goals? This course examines existing and historical U.S. government and U.S. Department of Defense efforts in this arena, as well as exploring the shape of things to come. The tortured lexicon and variety of government activities will be plumbed, with students learning to distinguish (in principle and in practice) between strategic communication, public diplomacy, information operations, public affairs, psychological operations, military information support operations, and civil-military operations. The course also explores the relationships between these different efforts, capabilities, and organizations, as well as exploring theoretical and ethical tensions such as the distinction between inform and influence, propaganda, the use of falsehood or manipulation, and the role of actions and images in this domain. Finally, the explores challenges faced by government efforts to inform, influence, and persuade, and seek to identify solutions to some of those challenges.

(Social and Behavioral Science)

Labor Economics (Heaton, 1 unit)
Labor economics as a field has grown enormously in the past several decades. Although originally focused on the interactions between firms and works, modern labor research examines diverse areas such as crime, family interactions, time-use, and education. The purpose of this course is to review a number of topics of interest to labor economists, outlining the relevant theoretical work and empirical evidence. Particular emphasis will be given to identifying data sources that will be useful for students in their own empirical work, as well as furthering students' understanding of the empirical methods used by labor economists.

(Economic Analysis)

Large-Scale Optimization with Applications (Nowak, .5 unit)
Optimization problems involving large numbers of variables or constraints arise frequently in problems concerning transportation policy, manpower and production planning, design of complex systems, logistics, data mining, and others. Furthermore, the number of variables often used to ensure a problem formulation is tractable (e.g., convex). Efficient algorithms are required to solve large-scale optimization problems since the number of computations grows by at least the cube of the number of variables or constraints. In this five-week advanced course, we will introduce students to efficient methods for formulating and solving large-scale optimization problems and describe applications where these problems may be encountered. In addition, we will introduce a heuristic method commonly employed to solve non-convex problems.

(Quantitative Methods)

Leadership (Hoffman, .5 unit)
The objective of this course is to inspire a deeper understanding of the complex art of leadership, and to help student reflect on their unique traits and skills and experiences as they develop their own, personal leadership philosophy. This five-week course explores leadership and its fundamental principles: leaders, groups, goals, and guidance. It reviews the literature on leadership theories that have tried to define "good" leadership, and examines why there is little consensus on any one theory. The course further explores the broad factors involved in guiding groups towards goals; including the leader, the group, the goals, and the guidance or policies that direct them.

(Social Science and Behavioral Science)

Modern Prediction and Modeling Methods (Meeker, .5 unit)
This course will discuss modern innovations in statistical modeling, prediction methods, and software to expand the students' analytical toolbox. In public policy analysis data of mixed types (continuous, ordinal, nominal, and simply missing) are the rule rather than the exception. In addition, model inputs often have non-linear relationships to the outcome. Recent developments have greatly expanded the collection of viable analytical methods. In addition to classroom lectures and laboratory assignments, the course will host some of the world's leading experts on the subject as guest speakers.

(Quantitative Methods)

Operations Research II (Bennett, 1 unit)
This course expands on the material presented in Operations I by exploring operations research modeling techniques in greater breadth and depth. Theoretical underpinnings are discussed for several techniques including simulation, dynamic programming, networks, and integer programming. Stylized case studies are used to provide contexts, and emphasis is placed throughout on interpreting and modeling the decision-makers' problem. A number of overarching issues are also discussed, including a top-down approach to decision making, advantages and disadvantages of various methods for solving the same problem; verifying, validating, and accrediting models; and dealing with problems having multiple objectives and criteria.

(Quantitative Methods concentration)
Pre-requisite: Operations Research I or permission from the professor

Performance Measurement: Social, Behavioral and Political Science Perspectives on Design and Implementation (Nelson, 1 unit)
Performance measurement has been an enduring part of the policy and programmatic landscape for decades. Professional policy analysts are frequently called up on to help organizations design and implement performance measurement systems at the individual, group, and organizational levels, and to use performance data to inform decision-making. Design and implementation of effective performance measurement systems is an inherently multidisciplinary activity and requires a firm grasp of the science of measurement and an ability to leverage a wide variety of social and behavior science constructs to understand the nature of the systems we seek to measure.

In this course we examine performance measurement both as a means to represent systems and as strategies for changing and improving systems. By the end of the course, students will have improved their ability to: (a) assess the appropriateness of performance measurement in a variety of contexts, (b) identify the uses and users of performance data, (c) identify and select system elements worth measuring, (d) identify, select, and develop feasible data sources, (e) develop approaches for linking performance data to consequences, and (f) develop approaches to using performance data to support decision-making. The course has a practical “design and implementation” orientation, and will use real-world cases to understand how performance measurement systems operate in operational, organizational, and political contexts. Examples will come from a variety of variety of policy areas, including education, health, public safety, defense, and others.

(Social and Behavioral Science)

Policy Analysis and the Modeling of Complex Problems (Davis, 1 unit)
This course teaches advanced methods of planning and resource allocation while accounting for uncertainty, risk, and choice in complex policy problems. It includes modeling, simulation, and tuning results of analysis to support high-level decision makers, who need to understand the implications of their choices. This tuning should reflect not only allegedly "objective" analysis, but also subjective values and judgments, including strategic judgments that decision makers are paid to make. The course will include case studies of current and past RAND policy analysis in transportation, health, defense, counterterrorism, and strategic and program planning. This will be a hands-on course with analytic homework and considerable class discussion of subtleties.

(Quantitative Methods)

Predictive Analytics for Public Policy (Hollywood, 1 unit)
This class will discuss predictive analytics (also known as data mining) for public policy. The class will cover major families of predictive analytics models, but will also cover end-to-end business processes for building models, history of data mining, and policy implications (privacy, civil rights, etc.) of predictive analytics in the policy arena.

We will cover the mathematics of the models, although we will not delve into the math in detail. Instead, the focus is on understanding of what the methods do, what their practical advantages and disadvantages are, and where they might be most useful. Prior coursework in probability, statistics, and basic linear algebra (i.e., knowing what a vector and a matrix are) are prerequisites.

Class readings will be drawn from open-source materials on predictive analytics. The software we will use is KNIME, one of the leading open-source predictive analytics packages. Assignments will include several problem sets in which students will be put in the role of an analyst and asked to decide which models would best apply and why, in addition to applying those models directly. The final project will be a paper and a brief presentation in which students will present their results of applying predictive analytics to a public policy problem.

(Quantitative Methods concentration)

Principles of Client Oriented Policy Analysis (Wasserman, 1 unit)
The main premise of this course is that policy analysis (in contrast to policy research) is inextricably linked to client relationships. A second premise is that some analysis is better than no analysis, and that policy analysts are often asked to confront difficult policy issues with far fewer resources at their disposal than they would like.

To improve the quality of public policy decisions, policy analysts must cultivate clients, often serving as their counselors and confidantes. At the same time, policy analysts must not compromise the integrity of their work and work products. Balancing client needs while maintaining professional standards can often be challenging, and at times even infuriating. This tension can be exacerbated when time and other resources are in short supply.

To improve the quality of public policy decisions, policy analysts must cultivate clients, often serving as their counselors and confidantes. At the same time, policy analysts must not compromise the integrity of their work and work products. Balancing client needs while maintaining professional standards can often be challenging, and at times even infuriating. This tension can be exacerbated when time and other resources are in short supply. This course will explore ways to develop and maintain good client relationships and to conduct "quick and dirty" analyses that allow the analyst to both meet client expectations and to maintain their personal and professional integrity. Specifically, the course will:

  • Acquaint students with various tricks of the trade for conducting quick turnaround work.
  • Suggest various ways to develop and maintain strong and productive client relationships.
  • Provide students with an opportunity to step outside of RAND and to participate in a short-term project with a local client. students will conduct these assignments in teams of three. The products of these client engagements will be both a briefing and a memorandum.

(Economic Analysis, Quantitative Methods and Social Science concentrations)
(Policy Analysis course for cohort years 2011 and beyond)

Program Evaluation (Hunter, .5 unit)
Not all policies or programs "work" and a significant amount of money is spent to evaluate them. This course will teach you the tools used to determine whether programs and policies achieve their objectives. This course focuses on the design and implementation of formative and summative evaluations of programs and policies including assessment of fidelity to a model and assessment of impact. This short course is interactive, with a mix of lecture and student led discussion to provide examples and applications of course concepts.

(Social and Behavioral Science)

Public Finance (Light, .5 unit)
This course is intended to provide an overview of public finance theory as well as a review of current research in a number of applied public finance areas. The first part of the course will cover the theory of public goods, externalities, and optimal taxation. This portion of the course is intended to give students exposure to concepts and analytical methods which are often used and referenced in public finance research. These tools are useful for both analyzing existing policies and guiding the development of new policies.

The second part of the course is designed to give students broad exposure to current research on public finance issues. In this section of the course, we will study transfer programs for the poor, education and transportation finance policy, policy options for dealing with environmental externalities, and the regulation of addictive goods. Additionally, students will give presentations during the last two lectures on public finance research they have conducted in areas of their choice.

(Economic Analysis)

Publication Workshop (Khodyakov, .5 unit)
This workshop is about the art and craft of scientific writing and the process of journal publication. My teaching goals in this course are:

  • To help students strengthen their writing skills;
  • To introduce students to the journal review process;
  • To teach students how to write good article reviews;
  • To help students choose the right outlet for their work;
  • To help students publish their work in peer-reviewed journals;
  • To help students prepare a conference presentation.

(Economic Analysis, Quantitative Methods and Social and Behavioral Science)

Qualitative Research (Ryan, .5 unit)
This course focuses on the use of one of the most basic qualitative techniques; the semi-structured interview. We will cover all the basic stages for effectively using semi-structured interviews, including: formulating a comparative research question, developing frameworks and interview protocols, conducting interviews, managing and analyzing interview data, and presenting the results. This is a hands-on course and each participant is expected to develop their own research project. Classes will be divided between methodological discussions and in-class presentations to demonstrate each of the data collection and analysis steps.

(Social and Behavioral Science)

Quality Assessment/Making the Business Case for Quality (Brook, 1 unit)
The purpose of this course is to acquaint students with the principles of quality assessment, health status, and how to improve value in health care at both the policy and operational level. At the completion of the course students will be required to write a paper that would be addressed either to the President of the United States, a CEO of a health system, or the head of a health services research agency who is trying to produce new knowledge about improving value in the U.S. health system.

(Social and Behavioral Science)

Quantitative Methods with Applications in Intelligence, Surveillance and Reconnaissance (ISR) Policy (Alkire, .5 unit)
ISR systems, such as the drone technology used to great effect in recent conflicts, provide military commanders and Washington policymakers with information on developments in combat areas in great detail. Whereas it’s possible to plan for combat aircraft, ships or tanks that can be used for decades, it is doubtful that today’s ISR systems will still be the right mix a few years from today. For this reason, ISR system needs and capabilities need to be reassessed frequently. This course teaches quantitative methods for assessing ISR system needs and capabilities. The methods are useful for assessing the right mix and quantity of ISR systems to meet emerging demands; for finding new ways of employing ISR capabilities to improve the effectiveness of the resulting intelligence products and/or generate them more efficiently; for identifying sensor updates needed to enable a particular surveillance capability. This half-unit course is designed for Fellows with interests in: ISR policy issues such as those commonly addressed at RAND Project AIR FORCE; technology policy; national security research; careers in intelligence; OJT in the national security FFRDCs. Prerequisites are OR1 (or permission from the instructor), and a willingness to learn new quantitative methods.

(Quantitative Methods concentration)

Regulation Networks Systems (Vogelsang, .5 unit)
This course deals with public regulation of industries. It puts particular emphasis on the regulatory reform movement and the compatibility of regulation and competition. The main focus is on network industries, telecommunications and electricity in particular. Other network industries include postal services, railroads, gas pipelines, water supplies, or even ATM and credit card services. While the US and European contexts receive particular attention, inferences are drawn to other countries. We will try to balance theoretical and policy questions in the course.

(Economic Analysis)

Research Methods in Empirical Economics (Heaton, 1 unit)
This course will go through the nuts and bolts of how to do research in order to successfully write a dissertation or publish research to include where to get data, how to structure a paper, and how to use econometrics to make the paper more convincing. The new course would build upon some of the skills developed in Labor Economics and capture what the students were looking for when they asked for a follow-on, but hopefully also draw in other advanced students who may not have taken that course.

(Economic Analysis and Quantitative Methods)

Robust Decision Making (Lempert, .5 unit)
Over the last decade RAND researchers have been at the forefront of developing new quantitative approaches to informing decisions under conditions of deep uncertainty. These Robust Decision Making methods seek to identify and assess policies that perform well over a wide range of plausible futures. Such robustness is often achieved through adaptivity, that is, evolving over time in response to new information. This course will introduce these robust decision making methods, situate them among a variety of approaches which address robustness and ambiguity in decision making, and present some applications of their use.

(Quantitative Methods)

Social Network Analysis (Green, 1 unit)
Network analysis has grown in prominence over the past fifteen to twenty years, moving from a largely academic pursuit to one with applications in business strategy and organizational behavior, public health and health systems, international affairs and international security, and counterterrorism and homeland security, to name a few. As such, its policy relevance has grown immensely and will likely continue to increase as new analytic methods are developed and understanding of the approach grows.

This elective course introduces social network analysis methods, theories, and applications, focusing on complete, ego-centered, and personal network approaches. We will explore how social network analysis developed from and contributes to the behavioral sciences in general, and specifically to the disciplines of sociology, anthropology, political science, public health, graph theory and statistics. The course will consist of lecture and laboratory exercises. Lectures will introduce social network concepts, theories and applications. Laboratory exercises will introduce methods in a hands-on manner. Individual work will allow students to explore the ways social network analysis can enhance their own research. Please be prepared to discuss reading assignments and concepts in lecture and to participate in lab exercises.

(Economic Analysis, Quantitative Methods, and Social and Behavioral Science)

Pre-requisite: A general understanding of social science research design and methods of data collection is required for this course. Thus, students are expected to have completed the majority of the PRGS core curriculum, particularly Social Science Methods and Qualitative Research Methods. Without these prerequisites, permission of the instructor is required. Specific knowledge of social network concepts is not required; however, initial discussions with class members will help focus the technical level and substantive focus of the course.

Survey Sampling I (Han, .5 unit)
This course introduces the basic statistical aspects of surveys. Survey is an important data sources for policy studies. Researchers often design and conduct their own surveys to collect information for specific research aims. Publicly available survey data serving more general purposes, in particular, national and state surveys conducted by governmental agencies, are the basis for many secondary studies. This course consists of two components: sampling design and survey data analysis. We will start with an introduction of the basic statistical framework of survey. We will cover the following basic designs: simple random sampling, simple probabilistic sampling, stratified sampling, and cluster sampling. We will mainly introduce model-based analysis methods, but also discuss the traditional design-based analysis methods for some simple designs.

(Quantitative Methods concentration)

Survey Sampling II (Han, .5 unit)
This course introduces the more advanced designs and analysis of complex surveys based on the previous course. On the design side, we will discuss the two-stage design and complex design. We will also discuss the nonresponse issue. On the analysis side, we will mainly focus on model-based and model-assist methods, including GLM, small-area estimation, and nonparametric regression.

(Quantitative Methods concentration)

Systematic Reviews (Hempel, .5 unit)
This course will introduce students to literature overviews ranging from finding key articles for a background section to comprehensive systematic reviews. We will focus on the research methodology applied to literature overviews that aim to enable a reproducible and unbiased summary of the existing information. Systematic reviews synthesize the available evidence to answer a research or policy question. Meta-analysis is a statistical technique used to pool data across primary studies. There will be special emphasis on evidence-based medicine as systematic reviews are a common research tool in this field, and new research is guided by identified gaps in the existing evidence base. However, the methodology is equally applicable to any subject area where there is a body of evidence to be summarized, and standards for literature overviews and meta-analyses are rising in all research areas.

(Quantitative Methods and Social and Behavioral Science)

Taking a Systems Approach to Policy Analysis (Hollywood, 1 unit)
This class will examine approaches to public policy projects similar to management consulting. Rather than conduct a classic study somewhat in isolation, this growing type of project involves addressing and integrating a large number complex issues, and working directly with the client and a large number of other stakeholders to design and manage improved government processes.

(Quantitative Methods concentration)

Technology Foresight and Public Policy (Popper/Silberglitt, 1 unit)
It is a truism to say that technology is changing our world and doing so with increasing speed. Less well explored is the degree to which this transformation is affecting democratic government and policy institutions in their ability to operate effectively. This course will explore policy aspects of the dynamics of technological change directly by considering foresight methods and their use (and misuse) in informing policy decision-making. We focus on circumstances in which an understanding of technology development and implementation is critical to effective policy for human and economic development. The desired educational outcomes are to give students the ability to:

  • Understand the implications of technology development and innovation on the analysis and implementation of policy;
  • Utilize multiple foresight methods in practical applications;
  • Formulate and prosecute a foresight analysis and elicit policy-relevant insights;
  • Identify and analyze drivers and barriers to implementation of policies based on foresight results and develop action plans;
  • Understand the responsibilities of the analyst in the use of technology foresight.

(Policy Analysis course)

Transportation Planning and Policy in the U.S. (Wachs, 1 unit)
How responsibilities for transportation investments are divided among local, regional, state, and federal bodies and how these organizations perspectives differ. Evolution of transportation policy over time (over 200 years). Fundamental differences among nations in transportation policy—the U.S. versus, England, New Zealand, Scandinavian Countries, developing nations (India and China). Return on investment in infrastructure and principles that can be applied to financing transportation. User fees and hypothecation versus general fund financing. Measuring the performance of transportation systems and using performance indicators in resource allocation. The growing fiscal crisis in transportation. Evolution of Federal transportation policy and laws. Appropriations, federal funding formulas and local/state/federal funding disputes. The role of public-private partnerships. Earmarking in transportation programs. Dealing with externalities: case studies of air pollution and greenhouse gases. Multimodalism: how can policy reflect balance between automobile oriented societies and the need for alternatives like transit and cycling? How can societies balance the needs for goods movement against those for people movement? Advocacy groups, politics and analysis in transportation—the example of regional comprehensive transportation planning.

(Social Science concentration)
(Policy Analysis course for cohort years 2011 and beyond)

Understanding Macroeconomic Policy II (Neu, .5 unit)
Course is being developed.

Workshop on Quantitative Methods and Education (Goldman, 1 unit)
Students study a selection of advanced quantitative analyses of policy topics in K-12 and higher education, with an emphasis on public-private cooperation in education. Topics include measuring productivity and outcomes at all levels of education as well as public and private finance of education. These basic topics lead to an examination of the implications of portable financial aid in higher education and vouchers in K-12. Part of the quarter is devoted to guiding each student through a small but complete empirical research project using computer databases introduced in class by the professors. students employ microeconomics, econometrics, and statistics throughout the course.

(Quantitative Methods and Social and Behavioral Science)

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