Refereed publications

Hedging Against Inflation: Housing vs. Equity [open access][code files], Empirical Economics (2023).

Housing and the Business Cycle Revisited [accepted manuscript], Journal of Economic Dynamics and Control 99 (2019), February 2019, pp. 103-115.

Working Papers

The return on everything and the business cycle in production economies (with Christopher Heiberger) [earlier version].

Motivated by recent empirical evidence on the returns on equity, bonds, and housing, we study the interaction between an economy’s total risky capital portfolio consisting of housing and equity, the business cycle, and different types of productivity risk: standard, long-run, and disaster risk. Preferences include habits or follow a generalized recursive form. Procyclical housing adjustments reduce consumption risk, preventing the versions with habits or long-run risk from simultaneously replicating risk premia, investment volatility, and housing demand. The disaster risk version replicates these targets. In all versions, a perfect negative correlation between equity returns and the marginal utility of consumption excludes Sharpe ratios of housing larger than for equity.

Polynomial chaos expansion: Efficient evaluation and estimation of computational models (with Christopher Heiberger and Johannes Huber) [earlier version][code files].

Polynomial chaos expansion (PCE) provides a method that enables the representation of a random variable, the quantity of interest (QoI), as a series expansion of other random variables, the inputs. Traditionally, uncertain parameters of the model are treated as random inputs, and the QoI is an element of the model’s solution, e.g., the policy function, the second moments of observables, or the posterior kernel. PCE then surrogates time-consuming repetition of model solutions and evaluations for different values of the inputs. Additionally, PCE allows to discretize the space of square-integrable distributions, including those containing mass points. The paper discusses the suitability of PCE for computational economics. We, therefore, introduce to the theory behind PCE, analyze the convergence behavior for different elements of the solution of the standard real business cycle model as illustrative example, and check the accuracy, if standard empirical methods are applied. The results are promising, both in terms of accuracy and efficiency.

Hone the Neoclassical Lens and Zoom in on Germany’s Fiscal Stimulus Program 2008-2009 (with Johannes Huber) [version: Business cycle accounting for the German fiscal stimulus program during the Great Recession].

Business Cycle Accounting (BCA) by Chari, Kehoe, and McGrattan (2007, Econometrica) completes the “…through the lens of a neoclassical model”-approach. This paper refines and extends the methodology in four primary dimensions, creating a manual. i) the choice of the level of aggregation is critical and thus must be case-dependent. ii) a strict distinction between growth and cycle is beneficial. iii) BCA requires Maximum-Likelihood, even if it is difficult. Given these difficulties, we introduce a procedure that reliably and quickly locates the maximum and enables a detailed evaluation of the likelihood function and robustness checks. iv) it is revealing to discuss the results in the context of economic and political events. To illustrate the necessity and benefits of the refinements, we apply BCA to the Great Recession in Germany. The main driver was efficiency, followed by net exports and distortions in the markets for business investments. Government consumption and durable consumption acted counter-cyclically. We attribute the latter to a high subsidy for new cars or, more generally, for durables.