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Numerical Methods in Macroeconomics

October 22-23, 2024

Goethe University Frankfurt
Campus Westend
Casino 1.801 / 1.802

Summary

This two half-day workshop brought together researchers involved in the development and application of numerical methods in macroeconomics. This workshop is supported by the DFG through grant nr. 465469938 “Numerical diagnostics and improvements for the solution of linear dynamic macroeconomic models” and the Deutsche Bundesbank and was hosted by the Institute for Monetary and Financial Stability (IMFS) and Goethe University Frankfurt.

In a continuously changing world with global financial, epidemiological and climate crises, researchers are developing new models to capture macroeconomic relationships and interactions with individual and distributional behaviors and assessing existing models’ ability to shed light on these challenges. In a complex world, these models and their methods are almost invariably numerical. New models and new perspectives frequently call for new methods, improved methods or reflection on existing methods limits and capabilities, for both analysis and empirical verification. This workshop brought together researchers with insights in these developments with a keynote contribution from Prof. Harald Uhlig, Ph.D., University of Chicago.

Topics included solution methods, estimation methods, and machine learning applications for DSGE and other structural macroeconomic/-metric models, from linear representative agent to nonlinear and heterogeneous agent models, frequentist and Bayesian.

Program, October 22, 2024

12:45 - 13:00

Opening Remarks (Casino 1.801)
13:00 - 14:00

Parallel Session

Casino 1.801

Abeer Reza, Bank of Canada
Finite-Sample Identification-Robust Inference for Non-Linear DSGE Models

Yucheng Yang, University of Zurich and SFI
Deep Learning for Search and Matching Models

Casino 1.802

Gregor Boehl, University of Bonn
HANK on Speed: Robust Nonlinear Solutions using Automatic Differentiation

Chris Naubert, Bank of Canada
Differentiable, Filter Free Bayesian Estimation of DSGE Models Using Mixture Density Networks
14:00 - 14:15

Break
14:15 - 15:15

Plenary Session (Casino 1.801)

Harald Uhlig, University of Chicago
Solving Dynamic Heterogeneous Agent Models: Taking Stock
15:15 - 15:45

Break
15:45 - 16:45

Plenary Session (Casino 1.801)

Thorsten Drautzburg, Federal Reserve Bank of Philadelphia
Filtering with Limited Information
16:45 - 17:45

Plenary Session (Casino 1.801)

Kenneth Judd, Hoover Institution, Stanford University
Optimal Dynamic Stochastic Fiscal Policy with Endogenous Debt Limits

Program, October 23, 2024

09:00 - 10:00

Plenary Session (Casino 1.801)

Michael Reiter, Institute for Advanced Studies, Vienna
State Reduction and Second-order Perturbations of Heterogeneous Agent Models
10:00 - 10:15

Break
10:15 - 11:15

Parallel Session

Casino 1.801 

Douglas Araujo, Bank for International Settlements
Synthetic Controls With Machine Learning: Application on the Effect of Labour Deregulation on Worker Productivity in Brazil

Alexandros Gilch, University of Bonn
“Small Data”: Efficient Inference with Occasionally Observed States

Casino 1.802

Oskar Arnt Juul, Copenhagen Business School
Taylor Projection under Tail Risk

Hanno Kase, European Central Bank
Estimating Nonlinear Heterogeneous Agent Models with Neural Networks
11:15 - 11:30

Break
11:30 - 12:30

Plenary Session (Casino 1.801)

Alexander Meyer-Gohde, Goethe University Frankfurt
Numerical Stability Analysis of Linear DSGE Models: Backward Errors, Forward Errors and Condition Numbers
12:30 - 13:30

Plenary Session (Casino 1.801)

Marco Ratto, Joint Research Centre, European Commission
Efficient and Robust Inference of Models With Occasionally Binding Constraints
13:30 - 13:45

Closing Remarks (Casino 1.801)

Veranstaltungen