Code & Data


Below you can find replication files for our numerical and empirical work.

The income of a household varies substantially over time and the uncertainty households face with respect to future incomes is large. This leads household to accumulate precautionary savings. In the past, most standard business cycle models, in particular models of monetary and fiscal policy have disregarded this point.

Our ERC project has contributed to the burgeoning literature that includes market incompleteness into the workhorse model of stabilization policy, the New Keynesian business cycle model. Introducing market incompleteness changes the way stabilization policy works, alters its welfare consequences and gives room to uncertainty and redistribution policies immediately affecting the business cycle.

Numerical Models:

Bayer, Christian, and Falko Juessen,2015. “Happiness and the Persistence of Income Shocks.” American Economic Journal: Macroeconomics, 7(4): 160-87.

Link: Numerical Codes and Regressions, for Data contact DIW

Bayer, Christian and Lütticke, Ralph and Pham-Do, Lien and Tjaden, Volker, 2015. “Precautionary Savings, Illiquid Assets, and the Aggregate Consequences of Shocks to Household Income Risk”Revised and Resubmitted to Econometrica.

Link: Numerical CodesEmprical material w/o estimation of the income process , Estimation of income process using SIPP Data (2GB of data)

Some of the most well known facts among macroeconomists are that labor market flows are large and employment fluctuates over the business cycle. For the performance of an economy it is important how efficiently it can reallocate workers and jobs. With continual idiosyncratic and sector-specific shocks it is essential that the workforce can be reallocated to its most productive uses quickly and with minimal use of resources. Put differently, the size of labor market flows contain important information on the amount of frictions involved in the labor market.

Part of our ERC project is to gain a better understanding of the size of these frictions and their implications for aggregate productivity. At the same time, we aim at understanding cross-sectional wage inequality, as this constitutes an important building block of any model of household consumption, saving and financial decisions.

Numerical Models:

Tjaden, Volker, and Felix Wellschmied, 2014. “Quantifying the Contribution of Search to Wage Inequality.” American Economic Journal: Macroeconomics, 6(1): 134-61.

Link: Numerical Replication Files and Data

Data Work:

Bachmann, Rüdiger, Bayer, Christian, Seth, Stefan, and Wellschmied, Felix, 2013. “Cyclicality of Job and Worker Flows: New Data and a New Set of Stylized Facts”

Link: Aggregate Worker and Job Flow Rates Germany 1972-2006 (.xls)

Mecikovsky, Ariel, and Wellschmied, Felix, 2015. “Wage Risk, Employment Risk, and the Rise in Wage Inequality”

Link: Stata Do-Files

Efficient allocations of production factors equalize revenue productivities across productive units (in a static environment). However, frictions in investment and technology adjustment lead to differences in factor productivities across production units and market outcomes might (or might not) be inefficient. In fact, a number of empirical studies shows that some firms operate with significantly higher capital or labor productivity ratios than others.

Part of the ERC project is to investigate what role adjustment costs to capital and technology play in generating this evidence, how this interacts with competition and how this finally feeds back into aggregate productivity.

Numerical Models:

Bayer, Christian, and Tjaden, Volker, 2016. “Large Open Economies and Fixed Costs of Capital Adjustment” Review of Economic Dynamics, forthcoming.

Link: Replication Files: Numerics and Data

Bayer, Christian, Mecikovsky, Ariel, and Meier, Matthias, 2015. “Productivity Dispersions: Could it Simply be Technology Choice?”

Link: MATLAB Codes

Data Work:

Bayer, Christian, Mecikovsky, Ariel, and Meier, Matthias, 2015. “Productivity Dispersions: Could it Simply be Technology Choice?”

Link: Stata Do-Files

Mecikovsky, Ariel, and Meier, Matthias, 2015. “Do Plants Freeze Upon Uncertainty Shocks?”

Link: Stata Do-Files

For all software items (except data) the following “MIT license” applies, where AUTHORS has to be replaced with the specific authors of the paper as named above.

Copyright (c) 2015, AUTHORS

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.