Ralph Luetticke is an Assistant Professor of Economics at UCL and affiliated with the Centre for Economic Policy Research and the Centre for Macroeconomics.
His research addresses core questions in macroeconomics about the conduct of fiscal and monetary policy as well as the sources of business cycles with new tools that allow us to take household heterogeneity into account in models and data.
PhD in Economics, 2016
University of Bonn, Germany
MSc in Economics, 2014
University of Bonn, Germany
BSc in International Economics, 2010
University of Maastricht, The Netherlands
The following lecture is a short-course on how to use perturbation methods to solve heterogeneous agent models.
You can find the codes to implement this on GitHub:
Comparison of Perturbation vs MIT shock solution for Krusell-Smith model (Matlab) https://github.com/ralphluet/KS_Perturbation_vs_MIT
Perturbation solution with our reduction method for Krusell-Smith and HANK models (Matlab) https://github.com/ralphluet/perturbation_codes
Perturbation solution with our reduction method for HANK models (Python) https://github.com/econ-ark/BayerLuetticke
Perturbation solution with our reduction method for estimating HANK models (Julia) https://github.com/BenjaminBorn/HANK_BusinessCycleAndInequality
We use the Survey of Income and Program Participation to estimate a household income process with time-varying variance of persistent income shocks (1980-2012). See Bayer, Luetticke, Pham-Dao, Tjaden (2019) for details.
Our structural model in Bayer, Born, Luetticke (2020) allows us to generate a quarterly time series for US inequality from 1954-2019. The model replicates the annual observations on the US top 10% wealth and income shares from the World Inequality Database, and we can use the Kalman smoother to create a quarterly time series (done with the HANKXPlus model).
Annual and quarterly measure of tax progressivity in the US, 1954-2019. In Bayer, Born, Luetticke (2020) we first extend the Mertens and Montiel Olea (2018)-calculations of average (ATR) and average marginal tax rates (AMTR) to the years 2013-2017 and with these calculate tax progressivity as in Ferriere and Navarro (2018) using the average and average marginal tax rate: P = (AMTR - ATR)/(1 - ATR). This provides us with annual observations for the estimation of our HANK model, and we can use the Kalman smoother to create a quarterly time series (done with the HANKXPlus model).
Replication code: https://github.com/ralphluet/Tax-Progressivity-Construction
These writings provide an accessible summary to my research.
Macroeconomics and Computational Methods at all levels.
I supervise theses in the area of macroeconomics. To apply for supervision, please email me an up-to-date transcript, a short CV, and a rough description of what you are interested in.