The MA in Global Risk (online) is a part-time, cohort-based program that is completed over 21 months through a sequence of 12 courses (50 credit hours). The coursework is designed to help graduates change careers or build new skills to advance in their current roles. This program will challenge students’ critical thinking skills and their ability to solve incredibly complex, global problems.
The program aligns with the school’s focus on developing a core understanding of international relations and practical application skills, while strengthening the knowledge areas:
- Global economics and international trade
- Approaches and frameworks for understanding risk
- Adapting risk management strategies in dynamic environments
- Primary risk management challenges and opportunities in different areas of the world
In addition to online coursework, the program features two in-person residencies. The first residency is held over one-week at the SAIS Europe campus in Bologna, Italy. The second residency includes the capstone project presentation as well as commencement. Visit our residency experience page for more information.
In order to understand and evaluate risk and uncertainty it is essential to have a strong command of basic statistical concepts and techniques. This course is designed to furnish students with the fundamental tools of statistical analysis, including analysis of descriptive statistics, probability distributions, statistical inference and related tests, correlation and conditional expectation. In addition to providing familiarity with statistical principles, the course will also include an introduction to basic statistical software packages, namely STATA and advanced tools in Excel. It is a prerequisite course for quantitative approaches to risk assessment. Moreover, this course develops the basic quantitative tools that are necessary for risk analysis. It gives a review of basic mathematical concepts used in economics and risk analysis, including pre-calculus and calculus principles. It also develops tools for data management using Excel. The course therefore provides students with a ready-to-use statistical toolbox that can be used during the remainder of the program.
The aim of this course is two-fold. First, we study the microeconomic effects of incentives on the consumer and the producer and their relationship with efficiency. By developing a detailed analysis of the market system, the course provides the framework for policy intervention and the assessment of their effectiveness. Second, we develop an understanding of how the economy works at the aggregate level: this does not only provide the foundations for macroeconomic analysis but, by focusing on the economic interaction of individuals, the course develops the theoretical and empirical foundations required to analyze international trade, its evolution toward global value chains and the challenges to contemporary commercial policy.
This is a course on social science research methods as they apply to decision-making under conditions of uncertainty. In other words, it looks at how the skills of a social scientist can be put to use in the ‘real world’. The course begins by looking at how decision makers anticipate future events, it explores what evidence they consider and what they ignore, and it looks at the standard models they apply in projecting the future based on the present. The case studies applied in this early part of the course focus on seemingly straightforward economic and financial questions.
This course highlights the economic sources of risk in the international arena. Different economies interact by trading goods and services and by exchanging progressively larger capital flows. In the age of globalization, the economic interdependence of countries generates highly novel challenges: exchange rates are not determined solely by capital movements, but also by the evolution of governance in the international monetary system – a system in which the Eurozone, the newest currency union, is emerging as a global and volatile player. The course develops a rigorous analysis of the different arrangements in the international financial system and their effects on trade direction and intensity and international capital flows.
The problem encountered in the Static Models course is that most of the predictions that were made in the areas of finance and economics ended in disaster. Hence this course turns to explore the bias that is built into estimates of the future to understand whether the problem lies in the way the world works or in how we try to understand it. It introduces students to a conceptual vocabulary based on systems theory to make it easier to build more complex relationships into the analysis. And it explores the unintended consequences of policy decisions. Here the case studies move from economics to politics and from crisis to stagnation. This does not offer much of an improvement.
This course allows to exploit the approach developed in “Economics of Global Market” to address the most relevant sources of uncertainty in international economics: the future of gains from trade while new trade agreements are being developed and challenged, the benefits of currency unification and the risks for sovereign debt. It concludes on the heated debate regarding the relationship between global imbalances and the financial crisis of 2007-08 while capital accounts continue to become progressively liberalized.
This course is an introductory course in finance. It serves two purposes. First it is an introduction to corporate finance and provides a framework for understanding and analysing investment and financial decisions of corporations. Second, it introduces topics in the investments area of finance that are important for the understanding of how prices are set and markets behave. The course is divided into four parts. The first part provides the basic knowledge and understanding of the firm, its financial statements and working environment together with standard tools to analyse future projects and firm performance. The second part introduces the main modern portfolio theories used as a basis to properly price the cost of capital accounting for risk and exploit the risk return trade off. The third part applies the tools acquired in the previous two parts and considers the implications of different capital structures and how they can be used to create value in the firm. In addition, models, principles and measures to evaluate a firm’s performance and its ability to create value through time will be discussed. Part IV introduces the main risks the firm faces during its operating activities and project management. It presents basic financial techniques and strategies to hedge risk and ensure stable value creation.
The classical approach to decision theory builds on a three-step iterative process: decision-makers assign probabilities to different possible outcomes, they generate welfare estimates depending upon the different outcomes (relative costs and benefits) for the decision-makers involved, and they calculate the expected values of different contingencies. The process is iterative in the sense that decision-makers reassess probabilities as they gain more information (it is Bayesian), they also make assessments as they learn more about the welfare implications for other important actors (it is game-theoretical), and they learn more about their own possibilities to control events (it is causal). The purpose of this course is to introduce students to the quantitative techniques used in each stage of this process. The course begins by exploring the assignment of probabilities both on the basis of prior assumptions and using more advanced techniques (like Monte Carlo simulations). It then shows how these probabilities can be updated in a Bayesian manner as a result of new information. It looks at how these probabilities can be fed into decision making with multiple actors (through game theory). And it concludes with techniques to evaluate the overall success of the decision-making process.
In this course, the student is asked to make a third analytic turn to bring the dynamics of human interaction more firmly into focus. It looks at negotiation, communication, and culture as possible sources of error or misunderstanding. The case studies focus on conflict, terrorism, and popular protest. By the end of the course students have a better grasp of where their predictions are likely to falter. They will also understand why such predictions must nevertheless be made. Risk in the international political economy derives from decision-making under conditions of uncertainty. The problem is that uncertainty is inevitable, but decisions must be made regardless of this.
Europe, Eurasia, Americas, Africa and Asia: Discuss and identify the main challenges to the stability and the most relevant opportunities for development in the different regions.
Students will choose their region of specialization (Europe/Americas/Asia/Africa), deepen their understanding of the political and economic context and begin working towards the completion of their capstone project. The student will be in residence to initiate and complete a risk analysis project, working within a team of classmates under direct faculty supervision. The project will combine a conceptual area and a region of the world.
|Block 1||Mathematics & Statistics||8/30/21 – 10/24/21 (8 weeks)|
|Micro Econ & International Trade Theory||10/25/21 – 12/23/21 (8 weeks)|
|Thanksgiving Break||11/22/21 – 11/26/21 (1 week)|
|Winter Break||12/24/21 – 1/2/22 (1 week)|
|Block 2||Static Models for Understanding Risk||1/3/22 – 2/27/22 (8 weeks)|
|Economics of Global Markets||2/28/22 – 5/1/22 (8 weeks)|
|Spring Break||3/21/22 – 3/25/22 (1 week)|
|Systemic Approaches to Understanding Risk||5/2/22 – 6/26/22 (8 weeks)|
|Statistical Analysis and Financial Management||6/27/22 – 8/21/22 (8 weeks)|
|Residency||Europe Residency||8/22/22 – 8/26/22 (1 week)|
|Block 3||Risk and Crisis in the Global Economy||8/29/22 – 10/23/22 (8 weeks)|
|Quantitative Models for Risk Assessment||10/24/22 – 12/23/22 (8 weeks)|
|Regions of the World 1||10/24/22 – 12/23/22 (8 weeks)|
|Thanksgiving Break||11/21/22 – 11/25/22 (1 week)|
|Winter Break||12/24/22 – 1/1/23 (1 week)|
|Block 4||Understanding Risk in Complex Environment||1/2/23 – 2/26/23 (8 weeks)|
|Regions of the World 2||1/2/23 – 2/26/23 (8 weeks)|
|Capstone||2/27/23 – 5/14/23 (10 weeks)|
|Spring Break||3/20/23 – 3/24/23 (1 week)|
|Residency||Washington DC Residency||5/22/23 – 5/24/23 (3 days)|
Dates are subject to change