The financial sector plays a key role in macroeconomic fluctuations. The goal of the two six-week second year PhD courses is to provide an introduction to Macro-Finance, defined as the interaction between macro, or the real economy (think GDP, employment, consumption etc.), and finance or financial markets (think credit, asset prices etc.).
The two courses provide an “introduction to macro-finance”. Ernest Liu will teach the theory half, and Atif Mian will teach the empirical half. Ernest Liu’s course is part of second year Finance PhD sequence (and is officially titled “Corporate Finance”) and Atif Mian’s course is part of second year Macro sequence (titled “Empirical Macro-Finance”). We strongly encourage students taking either of these classes to sit in both courses. Each six-week course will have 12 lectures based on the following topics. For each topic, Ernest will cover the relevant theory in the morning class and Atif will cover the related empirical work in the afternoon class. The course first focuses on the business cycle linkages between macro and finance, and ends with a discussion of the long-run interplay between the two.
The project is explicitly open-source and all code is available on GitHub. We encourage teachers, researchers, and students to contribute or create their own versions of the course. All lecture materials are available here, including the LaTeX source code used to create them. We provide a range of ready-to-use code and datasets that replicate empirical patterns found in the literature, which can be used as starting point for student presentations or research projects.
Are you planning to use these materials? Do you have feedback or suggestions? We are always trying to improve and expand the course. Please get in touch: macrofinance@princeton.edu.
Lecture Materials
Why macro-finance, i.e. why should finance matter for the macroeconomy? We start in the theoretical module with a two-period version of the New Keynesian model to illustrate key issues in the literature. Finance is largely a side-show for the macroeconomy, particularly for understanding business cycles.
We then discuss broader empirical evidence that suggests a strong link between finance and the macroeconomy. We split this evidence into, (a) the business cycle and (b) long-run. The evidence rejects the benchmark macro models that imply finance is not relevant for macro economy. We also briefly discuss the technical properties of local projection versus VAR method for time-serience macro-finance analytics.
So how should we model the macroeconomy to incorporate finance? We discuss the basic insights at a high level. Distribution matters, sometimes across firms and banks, and sometimes across creditor and debtor households. Heterogeneity matters, households differ in their MPC, firms differ in their productivity and liquidity constraints. All this makes policy relevant, macro-prudential policy, monetary policy, tax policy, fiscal policy and lender of last resort policy. The rest of the course is dedicated to understanding these linkages, with a keen eye on empirical facts.
Why macro-finance, i.e. why should finance matter for the macroeconomy? We start in the theoretical module with a two-period version of the New Keynesian model to illustrate key issues in the literature. Finance is largely a side-show for the macroeconomy, particularly for understanding business cycles.
We then discuss broader empirical evidence that suggests a strong link between finance and the macroeconomy. We split this evidence into, (a) the business cycle and (b) long-run. The evidence rejects the benchmark macro models that imply finance is not relevant for macro economy. We also briefly discuss the technical properties of local projection versus VAR method for time-serience macro-finance analytics.
So how should we model the macroeconomy to incorporate finance? We discuss the basic insights at a high level. Distribution matters, sometimes across firms and banks, and sometimes across creditor and debtor households. Heterogeneity matters, households differ in their MPC, firms differ in their productivity and liquidity constraints. All this makes policy relevant, macro-prudential policy, monetary policy, tax policy, fiscal policy and lender of last resort policy. The rest of the course is dedicated to understanding these linkages, with a keen eye on empirical facts.
Theory slides
Theory video
We start with the most traditional way of linking finance with macro: the bank lending channel. Banks are “special” in providing intermediary services that finance the investment needs of business and entrepreneurs. The specialness of banks means that their net-worth or capital matters for aggregate investment. Thus, a shock to net worth of banks filters through to how much firms can invest and hence the rest of the economy. Maintaining adequate net worth of the banking sector is key under this framework. We also discuss the frictions needed to translate bank lending channel shock at the bank level into aggregate fluctuation in investment and GDP.
The key challenge in identifying the bank lending channel is isolating “credit supply shocks” and estimating their pass through to firms at the loan level. We discuss empirical methodology for doing so, including estimation of possible spurious bias and estimating general equlibrium effects at the firm and industry level. For example, is the overall impact of bank lending channel “crowded out” due to firms’ ability to access alternative sources of funding?
In the bank lending channel, finance interacts with macro by impacting the supply-side of the real economy, i.e. real investment. We next discuss the household balance sheet channel that highlights how financial shocks to household balance sheet can impact consumer spending and hence the demand-side of the real economy.
We discuss theoretical microfoundations, such as liquidity constraints, precautionary savings or hyperbolic discounting, that gives rise to household consumption responding to balance sheet shocks and heterogeneity in marginal propensity to respond in the cross-section. When do these responses at the individual level “add up” to matter at the macro level? We discuss frictions at the macro level needed to translate household balance sheet shocks into aggregate demand fluctuations. We also introduce the idea of a “liquidity trap”, something we will keep coming back to. We discuss the role of balance sheet strength as a determinant of the effectiveness of monetary policy transmission.
On the empirical side, we discuss how the 2008 financial crisis brought to the forefront the importance of household balance sheet shocks for the macro economy. We present evidence on how household balance sheet shocks affected aggregate demand and hence output and unemployment. We also discuss Irving Fisher’s famous “debt deflation hypothesis” in the context of the Great Depression, and evidence that the same force was operative in the 2008 global crisis.
We have seen how investment and consumption can be affected by financial shocks. If these shocks were unanticipated or “random”, they would provide a very simple theory of finance-related business cycles: whenever an unforeseen “MIT” shock hits financial markets, the macroeconomy is at risk of slowing down. However, what we see in the data is that credit booms are systematically followed by busts. Why do credit booms predict busts? Why do households and firms not anticipate the bust and appropriate hedge against it?
The empirical section formally tests for the presence of boom-bust cycles. We discuss the relative
importance of household balance sheet versus traditional bank lending channel in generating the
boom bust cycle. We also test if market has rational expectations over the business cycle. On the
technical side, we discuss how to compute standard errors that account for possible correlations
both in the cross-section and time-series.
One common characteristic of boom-bust cycles is the “frenzy” seen in markets during the boom.
Given the no trade theorem with common beliefs, it is natural to appeal to models with heterogeneous beliefs to explain the volume of trading. It turns out that these models also naturally deliver
an amplifying force for credit: credit allows agents with differing beliefs to “bet more” against each
other, leading to more amplified trading and boom-bust cycles. We discuss both theoretical work
and empirical evidence scoring this point - heterogeneous beliefs are central to understanding the
link between financial market innovations and asset prices.
The credit intermediation process may suffer from moral hazard and agency conflicts - e.g. borrowers may lie on their application and lenders may try to pass-on risk to others / “greater fools”. We discuss such issues and why they may become particularly relevant during waves of “financial innovation”.
A key implication of prominent macro-finance models is that risk-sharing matters for aggregate behavior, with better risk-sharing limiting how much the economy suffers in a downturn and easing recovery. We discuss implications for security design, regulation and macro-prudential policies and some related empirical work.
Traditional discussion of monetary policy and its impact on the real economy largely abstracted from financial or balance sheet conditions in the economy. However, more recent literature and empirical evidence has highlighted the role of balance sheet strength as a determinant of the effectiveness of monetary policy transmission. At the macro level, this translates into debt and balance sheet strength acting as a “state variable” in the transmission of monetary policy.
Credit market disruptions can have negative effect on the macro economy for reasons we have already discussed. Relatedly, credit market disruptions can lead to “fire sale prices” that can then have real effects through the usual balance sheet channels. In such scenarios, there is a possible role for lender of last resort (LOLR), or liquidity provision during the down cycle. Is this quantitatively important?
A major question in recent empirical work is how to aggregate estimates from regional cross-sectional analysis at the macro level. This is a difficult question as one needs to take into account possible general equilibrium feed back forces that could reduce or amplify cross-sectional estimates. We discuss various approaches in the literature to address this issue.
We now switch from business cycle to longer run macro-finance questions. One of the more recent macro-finance questions is the apparent “Japanification” of advanced economies and the associated “secular stagnation”. Three macro variables, high level of debt to GDP, very low interest rates, and low productivity growth define this environment.
We start by looking at this question from the supply-side of the real economy. The traditional New Keynesian framework attributes short-run output gaps to nominal rigidities - but these should not last over prolonged periods of time. Relatedly, in macro models the “natural” rate of interest drops to generate expansion equilbriate supply and demand. Yet we see very low interest rates and a prolonged slowdown in productivity growth.
We revisit the relationship between low rates and productivity growth in a model that allows for market competition. The key insight is that very low rates can be contractionary due to their negative impact on market competition. We discuss the theory and empirical evidence.
We then introduce financial intermediation and discuss additional reasons that financial frictions in the intermediation process can make it harder for competition to thrive in a very low rate envrironment. Taken together, this framework provides an alternative non-Keynesian reason for growth sluggishness - one that does not rely on nominal rigidities biting over prolonged periods.
We focus on the demand-side in explaining the rise in long-term secular rise in credit to GDP across the world since 1980, and the accompanying fall in interest rate. We discuss how tendency of the very rich to save at a higher rate, combined with rising top-share inequality sets in a process of “indebted demand”, i.e. the reliance on credit as demand for the economy that ultimately leads into debt and liquidity traps. We also discuss the implications of this long-term trend for redistributive policy, monetary policy and fiscal policy. The empirical lecture presents evidence that shows how rising inequality has expanded credit supply.
We discuss the somewhat under-explored international dimension of macro-finance. What drives cross border capital flows, and what is the real economy impact of such flows? This question has become all the more important given the rise in global flows (both gross and net) since 1980, e.g. the rise of global savings glut. Do such flows distort trading patterns? Do they add to risk, or help us hedge it? What are the implications for effective macro-prudential regulations, including capital controls, for emerging markets?