Research
Home Research Vitae
– Johannes Huber –
Job Market Paper
Rental Markets and Wealth Inequality in the Euro-Area
(with Fabian Kindermann and Sebastian Kohls), [slides].
Wealth inequality and aggregate homeownership are negatively correlated across the Euro area. The ECB's Household Finance and Consumption Survey shows a strong and significant negative relationship between these two factors. The data suggest that in countries with many renters, many households have very little wealth, which fuels wealth inequality.
We explain these facts using a quantitative overlapping generations model, where households consume food and shelter and make portfolio decisions. In our model, households can purchase real estate for both consumption and investment. Non-owners must rent shelter from owners in a private rental market. A (reduced-form) wedge governs rental market efficiency and correlates with empirical measures of rent control. Rental market efficiency is crucial in explaining cross-country variation in the aggregate homeownership rate. Wealth inequality, however, is mainly driven by mortgage market characteristics. The interest rate spread between deposits and mortgages encourages young owners to accumulate wealth quickly. Additionally, loan-to-value (LTV) requirements compel owners to gradually pay off their mortgages. Our model quantitatively accounts for approximately 85% of the observed cross-country variation in wealth inequality.
Refereed Publications
Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models
(with Daniel Fehrle and Christopher Heiberger), Computational Economics (2025), [earlier version] [code files].
The Fiscal and Intergenerational Burdens of Brakes and Subsidies for Energy Prices
(with Christian Scharrer), International Tax and Public Finance (2024), [earlier version].
Working Papers
Solving Linear DSGE Models With Structure-Preserving Doubling Methods
(with Alexander Meyer-Gohde and Johanna Saecker), [earlier version] [code files].
This paper applies Structure-Preserving Doubling Algorithms (SDAs) to solve the matrix quadratic that underlies the solution of linear DSGE models. We present and compare two SDAs to other competing methods – the QZ method, a Newton algorithm, and an iterative Bernoulli approach – as well as the related cyclic and logarithmic reduction algorithms included in Dynare. Our comparison is completed using 99 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that both SDAs generally provide more accurate solutions computed in less time than QZ. We provide theoretical convergence evidence of quadratic convergence to a unique stable solution and appropriate (re)initialization of the algorithms when there is a breakdown due to a singularity in the recursion. The SDAs perform particularly well in refining solutions provided by other methods and for large models.
Hone the Neoclassical Lens and Zoom in on Germany's Fiscal Stimulus Program 2008-2009
(with Daniel Fehrle), [earlier version].
The paper refines and extends Business Cycle Accounting - the complete neoclassical lens. Methodologically, we gain robustness and efficiency by proposing a novel likelihood evaluation strategy and separating growth and cycles. Contentwise, we gain insights by choosing the aggregation level case-dependent and discussing the results conditional on economic and political events. Monte-Carlo studies show sizable methodological improvements and an application to the Great Recession in Germany content-related ones. Efficiency, net exports, and the business investment wedge account mainly for the recession. The government spending and durables wedges acted counter-cyclically, which we attribute to conventional and unconventional fiscal policy.
An Augmented Steady-State Kalman Filter to Evaluate the Likelihood of Linear and Time-Invariant State Space Models
We propose a modified version of the augmented Kalman filter (AKF) to evaluate the likelihood of linear and time-invariant state space models (SSMs). Unlike the regular AKF, this augmented steady-state Kalman filter (ASKF), as we call it, is based on a steady-state Kalman filter (SKF). We show that to apply the ASKF it is sufficient that the SSM at hand is stationary. We find that the ASKF can significantly reduce the computational burden to evaluate the likelihood of medium- to large-scale SSMs, making it particularly useful to estimate dynamic stochastic general equilibrium (DSGE) models and dynamic factor models. Tests using a medium scale DSGE model, namely the 2007 version of the Smets and Wouters model, show that the ASKF is up to five times faster than the regular Kalman filter (KF). Other competing algorithms, such as the Chandrasekhar recursion (CR) or a univariate treatment of multivariate observation vectors (UKF), are also outperformed by ASKF in terms of computational efficiency.
Work in Progress
Early Retirement in Wealth and Health Recessions
(with Fabian Kindermann and Dirk Krueger).
In this paper we study the retirement decisions of older workers in wealth recessions (such as the Great Recession) and in health recessions (such as the COVID19 recession). We show quantitatively that the retirement decision is shaped by two main forces, the labor market and the asset market. While the first influences current income earning opportunities, the second determines the value of retirement portfolios. We use the model to explain the qualitatively different trends after 2009 and after 2020, and derive its consequences for the long-run fiscal situation of the U.S. social security system.
The 401(k) Program and its Impact on Household Financial Investment and Knowledge
(with Fabian Kindermann, Krzysztof Makarski, Joanna Tyrowicz, Piotr Zoch, and Marcin Lewandowski).
How do 401(k) plans shape households' savings behavior and financial knowledge? We build a life-cycle model of household savings behavior under idiosyncratic income and investment risk. Households in our model can acquire financial knowledge through costly time investment in order to increase the return on their regular financial portfolio. We calibrate the model to replicate the features of the US economy and the 401(k)-like programs and study a counterfactual world without this vehicle. We study assets accumulation and financial knowledge with and without the availability of a 401(k)-like vehicle. We explore both the regular crowding-out of financial assets as well as the crowding-out of financial knowledge associated with the availability of tax-favored retirement accounts.