1. About This Course

This is a course for the student intending to continue on to a serious Master’s degree involving economics in general, and macroeconomics in particular. The target student is one who will be a deep thinker and a thought leader who will be capable of understanding modelling techniques. This is not a course for the student intending to get another diploma for the sole purpose of career promotion, nor for the consumer of superficial or imprecise economic “intuitions”.

We will be introduced to some core macroeconomic models that help to address some of the major empirical and policy questions in macroeconomics. These question relate to business cycles, long term growth, short-run fiscal and monetary policies, long-run or intergenerational fiscal policies, and to institutions such as fiat money and financial intermediation that facilitate trade.

1.1. What will we study?

Business Cycles and Monetary Policies: Two Flavors. We will begin our study of some common stories behind observed data on economic fluctuations. Technically, the simplest approach would be to model economic behavior/outcomes as they get revealed in observational data over time or over the business cycle. For example, a most naive approach would be to write down a statistical correlation model that fits the observed data: This is the hallmark of most textbook models of Keynesianism. Keynes’ was an approach that attempted to divorce Macroeconomics from Classical Economics (i.e., microeconomics or price theory).

Note

There are later generations of this approach with slightly more microeconomic foundations, known as the New Neoclassical Synthesis or New Keynesianism. We won’t have the time or the technical apparatus, yet, to look into this more recent literature. This will be taken up in a subsequent Macroeconomic Theory course.

Once we’re done with the Keynesian way of thinking, we will revisit some similar business cycle questions again using a model that has more detail in terms of how agents’ behavior arise in the aggregate. The simplest version we’ll use is an overlapping generations (OLG) model, where there is an explicit mapping from agents’ underlying choices, through their choice interactions in markets, to the resulting aggregate behavior of the economy. A crucial and contrasting lesson here is as follows: The aggregate rules (functions) governing behavior in the Keynesian model is assumed unchanged in the presence of policy change, whereas in the more microfounded model (monetary) policy change can confound what a Keynesian would have predicted to be stable aggregate behavior. We shall see that the linchpin in the conflict of these models is how one goes about modelling the crucial relations that may affect a policy maker’s trade off: In this instance, it is the so-called Phillips curve. Should one assume that it is a stable statistical relation, or, should one suspect that that relation may be transient and may depend on something deeper and reactive to policy changes?

Warning

In practice, the policy consultant has a tendency to take the short cut of making policy conclusions via statistical relations. The lessons here will present a grave warning to such temptations of instant gratification in policy modelling and practice.

Fiscal Policies: Two Flavors. We will also study various forms of fiscal policy in the short run, initially in the Keynesian setting, and later, in the OLG setting. In the latter case, the model provides an explicit and natural environment to rationalize government intervention because the model has a natural sense of agent heterogeneity and market imperfection.

Facilitating Trade in Missing Markets: Dynamic Redistribution and Other Institutions. We’ll also learn about how various forms of institutions: money, financial intermediation or banks, social security and fiscal policies can play a role in making economic outcomes “better” for the agents. This is studied through the lens of the OLG model economy.

1.2. How do we do it?

In this course, we’ll often begin our stories with pictorial or geometric representations of models. We will then get you ready for more advanced study using more rigorous mathematical representations, analysis and arguments. The purpose of doing so is to ensure that our logic is well-disciplined, so we don’t end up making rationalizations and policy conclusions outside of the premise of our underlying model. Another purpose of this is to prepare you for the serious careers that will require modelling, analytical and computational skills—i.e., insuring you to be more future-proof.

The student will be expected to be comfortable with elementary algebra, calculus, optimization (mathematical programming) and some linear algebra. The instructor will not be teaching you these basic skillsets again here. All these were taught to you in the Mathematics for Economists A course. In fact, much of the calculus and optimization applications here have almost identical counterparts in your study in Diploma Microeconomics. If you are weak on microeconomics, then you are advised to either first enrol in Diploma Microeconomics or to take that course concurrently. The student should also have an aptitude to learn a programming language.

These seminars have been based on several books and other sources. There is not one set textbook. The successful student in this course will be one who attends classes physically, who engages in discussions, and who independently follows up on readings referred to from these notes. Last-minute study before the end of term is a bad idea for this course. The instructor in this course is not responsible for lecture recordings.

Warning

Students are encouraged to hone their live-listening and note-taking skills and not to rely on lecture recording technologies that promise instant gratification but weaken deep learning.