New Keynesian DSGE Models, Financial Frictions and Bayesian Estimation

By Lawrence J. Christiano




This is a graduate-level course on tools for macroeconomics. It is geared to people interested in applying the tools in situations not necessarily considered previously in the literature. For this reason, the course will not shy away from the technical details. At the same time, there will be a constant focus on the intuition.

We begin by describing the basic New Keynesian closed economy model with no capital. The simplicity of this model will allow us to highlight core principles that apply more generally across models with price-setting frictions. It will also allow us to focus on a core technical problem in the New Keynesian model, how to aggregate across heterogeneous firms.

We then turn to a discussion of the econometric tools for estimating dynamic, stochastic, general equilibrium models like the New Keynesian model.

Finally, we consider financial frictions. We will examine in detail the consequences of incorporating financial frictions on the asset side of banks’ balance sheets. We will also discuss, at a more informal level, financial frictions on the liability side of banks’ balance sheets.

Computer exercises will give students hands-on practice in the use of Dynare to solve, estimate and analyze dynamic models.

Background readings: handbook chapterJournal of Economic Perspectivesinterview and this.





1.     The simple New Keynesian (NK) model without capital. We will build the model (almost) from its foundations and describe its properties and implications for policy. Most of the implications for policy will be ‘discovered’ in MATLAB exercises. (2.5 days)

a) First, we (i) derive carefully the model’s equilibrium conditions; (ii) talk about the classical dichotomy and how it does not occur when there are sticky prices; (iii) discuss the apparent absence of `money’ from New Keynesian models; (iv) define the natural equilibrium, a benchmark for policy analysis.

b) Second, we derive the log-linearized equilibrium conditions around a zero-inflation steady state. (Though we will not do a detailed derivation of the linearized Phillips curve, that is covered here. A more in-depth discussion appears  here.) We will then do the series of Dynare exercises described in NK_exercise.pdf, which accomplish three things (you can find the pdf file, as well as the associated Dynare code, cgg.mod, here):

i)    Convey basic intuition about the working of the New Keynesian model.

ii)   Show how under ‘news’ shocks, inflation targeting might drive the interest rate in the ‘wrong’ direction and inadvertently trigger an inefficient stock market boom (Slidesmanuscript; and section 3.2 of handbook chapter).

iii)        This Dynare code contains the seven non-linear equilibrium conditions of the Simple New Keynesian model. It can be used to show how Dynare handles this case, and to investigate the accuracy of the linearization strategy used in parts (i) and (ii).

c)  Third, we will show how the model can be used with simple pencil and paper methods to put structure on two debates among economists and policymakers:

i)    The debate between Fisherians and anti-Fisherians over how to get inflation down when it is too high (or, up when it is too low). We’ll see how a blend of the two viewpoints can be used to understand the dynamics of the Volcker disinflation in the US in the 1970s;

ii)  Discussions of the so-called forward guidance puzzle which has been used to motivate proposals for modifying the type of NK model studied in this course.

d) Finally, we will use the model to discuss three types of conditional forecasting situations. They allow one to answer questions like `what will happen if we keep the interest rate high over the next year’, or `what will happen to our economy if the world economy begins to weaken?’

i)    How to compute Odyssean forecasts. The code for this can also be used for other things, such as quantifying the forward guidance puzzle or studying the impact on the government spending multiplier when the interest rate is held constant (say, because the effective zero lower bound is binding). Application: characterizing `forward guidance puzzle’ (see this code, as well as the commentary at the start of the code; see also the second topic covered in this handout.).

ii)   How to compute two more standard types of conditional forecast. The code in (i) above can be used to compare all three types of conditional forecasts.  

2.  Estimation of DSGE models (the handout makes some references to this note on model solution and here is a note on the appropriate acceptance rate for the MCMC algorithm). (1.5 days)

a) State space representation of a model.

b) Elements of Bayesian inference (Bayes’ rule, MCMC algorithm).

c)  A simple example to illustrate Bayes’ rule.

d) Exercise that illustrates the MCMC algorithm is in the pdf file, MCMC_exercise that can be found in the zip file found here).

e)     We will use Dynare to estimate a version of the closed economy model using macroeconomic data from India. We will use the estimated model to do conditional forecasting.

3.     Financial frictions originating outside banking sector: Costly State Verification in Business Cycles. (0.75 day)

a) Micro foundations for the Costly State Verification (CSV) approach (zip file with code for the computations, and a version of the  slides with more extensive derivations). The CSV model is used as a friction on the asset side of a bank’s balance sheet.

b) Integrating CSV into a New Keynesian model and the results of Bayesian estimation of the model using US data (CMRJMCB 2003AER 2014, longer version of handout). Here is carefully documented (thanks to Ben Johannsen) Dynare code for replicating the material in this presentation.

4.     Financial frictions originating inside the banking sector: an informal review. (0.25 day) Summary of Gertler-Kiyotaki AER2015 (here is a more extended set of lecture notes). The focus here will be on shadow banking, which grew very large in the US in the 2000s. Here is a three period version of the model which explores some of the implications for macro prudential policy.