Monetary Policy and Speculative Stock Markets
Using an estimated model with credit constraints in which excess volatility of stock markets is endogenously amplified through behavioral speculation, I study whether monetary policy can mitigate spillovers. Endogenous speculation and its feedback to the price level are central features to replicate empirical key moments. Standard monetary policy rules are shown to amplify stock price volatility. Numerical analysis suggests that asset price targeting can offset the impact of speculation on either output or inflation (but not on both) and can dampen excess volatility. The dampening effect of this policy is limited due to its undesirable response to non-financial shocks.
Can Taxation Predict US-Top-Wealth Share Dynamics?
The degree of capital gains taxation can retrace the dynamics of wealth inequality in the US since the 1920s.
Precisely matching up- and downturns and levels of top shares, it has high overall explanatory power.
This result is drawn from an estimated, micro-founded portfolio-choice model where idiosyncratic return risk and disagreement in expectations on asset returns generate an analytically tractable fat-tailed Pareto distribution for the top-wealthy.
This allows us to decompose the sample into periods of transient and stationary wealth concentration.
The model generates good out-of-sample forecasts. As an addition we predict the future evolution of inequality for different tax regimes.
The ETACE Virtual Appliance: An Exploratory for the Eurace@Unibi model
This paper presents the Etace Virtual Appliance. The purpose of the software package is, among others, to provide researchers the possibility to explore the dynamics of the Eurace@Unibi agent-based macroeconomic model and to encourage the reproducibility and transparency of research. The package contains various components that allow the user to initialize, simulate and analyze the model. We also give a short overview of what can be done with the Etace Virtual appliance.
On the Evolutionary Fitness of Rationality
This work analyses the interaction of perfectly rational agents in a market with coexisting boundedly rational traders. Whether an individual agent is perfectly rational or boundedly rational is determined endogenously depending on each types market performance. Perfect rationality implies full knowledge of the model including the non-linear switching process itself. Policy function iteration is used to find a recursive minimal state variable solution of the highly nonlinear system
and I show that this solution is not necessarily bounded. Depending on the parameterization, agents' interaction can trigger complicated endogenous fluctuations that are well captured by the solution algorithm.
In such financial market setup rational agents might adapt sentiment beliefs and so fail to mitigate speculative behavior, and boundedly rational agents are not necessarily driven out of the market. While up to a certain point the presence of fully rational agents tends to have stabilizing effects it may later amplify endogenous fluctuations.
Efficient Filtering and Estimation of Models with OBCs
[draft upon request, code on github ]
This work proposes a solution method and a Bayesian smoother to filter and estimate rational expectations models with occasionally binding constraints quickly and accurately. This stands in contrast to the rest of the literature, that is unable to perform these tasks in reasonable time. The quasi-analytic solution method avoids matrix inversions and simulations at runtime and processes about 80k particles per second for medium scale models (e.g. Smets and Wouters, 2007). The suggested nonlinear iterative path-adjusting Ensemble-RTS Smoother (IPAS) returns precise estimates of the state distributions which can fully re-simulate the data. While only requiring the states to be approximately Gaussian distributed, a very small number of particles (about 250 for medium scale models) suffices to obtain high accuracy. An efficient implementation in combination with contemporary MCMC methods allows the estimation of medium to large scale DSGE models featuring the ZLB in very tolerable computation time. I review the benchmark implementation and efficient parallelization. As an example, I estimate and analyse the simple New Keynesian model, in particular with regard to the effects of unconventional monetary policy during the US-ZLB period.
US Monetary Policy at the Zero Lower Bound
draft upon request]
Using counterfactual analysis we investigate the dynamics of the US economy during the Great Recession. For that purpose we estimate the exogenous processes using
a nonlinear filter applied to a medium scale DSGE model featuring the zero lower bound (ZLB). We find that the 2008-trough was mainly caused by exogenous increases in the risk-premium. High risk premiums also weighed heavily on real activity and inflation in the aftermath of the Great Recession. Our findings suggest that the long duration of the zero lower bound was a reaction to weak economic development as opposed to an commitment by the central bank to actively keep interest rates lower than a Taylor-rule implied rate. However, our identified forward guidance shocks suggests that keeping the expected interest rate low had a stimulating effect on aggregate demand and prevented a deeper and longer recession. We introduce a novel, tractable method for handling occasionally binding constraints that can be used in combination with the Unscented Kalman Filter to filter and estimate models with a large state space at low computational costs.
Noise Induced Stationarity in Explosive Dynamic Feedback Systems
Cees Diks, draft upon request]
We show that under certain circumstances adding noise to an explosive dynamic expectations feedback system can decrease the probability of explosive dynamics and make stationary behavior more likely.
We build a small toy model of a market with positive expectations feedback, such as a housing or an asset market, and assume that agents form heterogeneous boundedly rational expectations. Identifying regions in the parameter space where the dynamics are explosive, we give conditions under which adding further stochastic noise can potentially stabilize the market.
We provide intuition for this result and discuss the economic implications.
For instance, this implies that policy measures that presumingly increase market volatility, such as a Tobin Tax, are not necessarily destabilizing.
Collateral Value and Credit Cycles
[work in progress]
This work studies the dynamic feedback between collateral prices and aggregate credit volume by formulating a simple non-linear model of a market for a durable good that can be used as collateral to finance expenditures. A finite number of agents that are heterogeneous in wealth maximize utility by deciding over the stock of the good, consumption expenditures and borrowing volumed. We assume that agents form boundedly rational mean-reverting expectations with risk-learning component. The individual borrowing conditions are determined by each agent's leverage ratio and the probability distribution of expected future prices of collateral. The use of projection methods allows agents to realistically anticipate for policy effect and effects of macroprudential regulation even though their expectations are not formed fully rationally. We show that this leads to non-trivial dynamics that are fed by the dynamic feedback of expectations on collateral value, credit and the prices of collateral. Running detailed numerical simulations, we analyze the dynamic stability properties and show how macroprudential policy is able to improve stability properties and decrease the magnitude of unwanted feedback effects.
The General Equilibrium Effects of a Basic Income Guarantee
[work in progress]
In this exploratory project I take a simple Walrasian economy with agents heterogeneous in skills as a starting point to compare the macroeconomic equilibrium outcome of a minimum wage and unemployment benefit with that of a basic income guarantee regime. Treating individual labor supply as a binary and using standard preferences, I focus on a labor-intensive real economy that embeds decreasing returns to scale and imperfectly competitive firms. This simple structure allows to study the distribution of employment, consumption and production among agents as well as aggregate measurements. While the introduction of minimum wages and/or unemployment benefit yields textbook results, a moderate basic income guarantee can increase labor market participation and output. The binary nature of employment is crucial to generate this result. I show analytically under which restrictions on the parameter space the above conclusion holds and when it does not. Furthermore, any combination of a basic income guarantee with minimum wages and/or unemployment benefits is harmful for employment and output.
In brief, I completed my PhD at the
University of Amsterdam
Bielefeld University, supervised jointly by
Cars Hommes and
I won the 2017 Student Price of the Society for Computational Economics.
During my PhD I was financed by a scholarship from the Bielefeld Graduate School in Economics and Management. Before, I was holding a scholarship from the German Research Foundation.
I obtained my MSc in economics from the University of Granada (top of class) and studied economics at Humboldt University Berlin at undergraduate level. I have worked as a professional guitar player and as an IT consultant for several start-up companies.
You can find most of my codes in my repositories on
Downloads related to the The ETACE Virtual Appliance (joint work with
P. Harting and
S. van der Hoog):