Wealth inequality and aggregate homeownership are negatively correlated across the Euro area. We explain this within a quantitative overlapping generations model, where households consume food and shelter and make portfolio decisions. Households purchase real estate for consumption purposes or rent it out to other households on the private rental market. A reduced form wedge – correlated with empirical measures of rent control – governs rental market efficiency. Rental market efficiency is crucial in explaining cross-country variation in aggregate homeownership. Wealth inequality, however, is mainly driven by mortgage market frictions, most importantly an interest rate spread between deposits and mortgages.

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.

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.

We introduce the augmented steady-state Kalman filter (ASKF), a modification of the augmented Kalman filter (AKF) that enhances the likelihood evaluation of linear and time-invariant state-space models. Unlike the standard AKF, the ASKF leverages the steady-state Kalman filter, reducing computational burden while maintaining accuracy. The ASKF requires only that the model is stationary, making it broadly applicable.
In estimating dynamic stochastic general equilibrium (DSGE) models and dynamic factor models, ASKF significantly outperforms competing methods. Applying it to the 2007 Smets and Wouters DSGE model, we find that the ASKF speeds up likelihood evaluation by up to a factor of five compared to the regular Kalman filter. It also outperforms competing algorithms, including the Chandrasekhar recursion and the univariate Kalman filter, in terms of computational efficiency. These performance gains make the ASKF a valuable tool for large-scale likelihood estimation in macroeconomics and finance.

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.

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.