Revisiting the Matching Function

December 4, 2014

By Britta Kohlbrecher, Christian Merkl and Daniela Nordmeier

This paper shows analytically and numerically that there are two ways of generating an observationally equivalent comovement between matches, unemployment, and vacancies in dynamic labor market models: either by assuming a standard Cobb-Douglas contact function or by combining a degenerate contact function with idiosyncratic productivity shocks for new jobs. Despite this observational equivalence, we provide several reasons for why it is important to understand what happens inside the black box of job creation. We calibrate a combined model with both mechanisms to administrative German wage and labor market flow data. In contrast to the model without idiosyncratic shocks, the combined model is able to replicate the observed negative time trend in estimated matching functions. In addition, the full nonlinear combined model generates highly asymmetric business cycle responses to large aggregate shocks.

Matching functions are used a little bit blindly and indiscriminately, so it is useful to be reminded that they are really black boxes. If you use a matching function, you should understand what it assumes and implies. This paper shows nicely how we can think of matching function and where there specification matters or does not matter.


Overlending and Macroprudential Tools

December 1, 2014

By Natalie Tiernan and Pedro gete

This paper is a quantitative study of two frictions that generate banks’ underinvestment in screening borrowers and, thus, overlending: 1) Limited liability, and 2) Banks failing to internalize that their credit decisions alter the pool of borrowers faced by other banks. The resulting lax lending standards overexpose banks to negative economic shocks and amplify the effects of economic fluctuations. They generate excessive volatility in credit, banks’ capital and output. We study a calibrated model whose predictions concerning the quantity and quality of credit are in line with recent U.S. business cycles. Quantitatively, limited liability is the friction that generates laxer lending standards. It induces 27% excess volatility in output relative to 8% from the other friction. Then we study three policy tools: capital requirements and taxes on banks’ lending and borrowings. The three tools encourage banks to screen more and should be state-contingent because the frictions vary with macroeconomic conditions. In quantitative terms, we find that taxes are better tools than capital requirements because they do not reduce credit going to the more productive agents.

Nice paper that shows that taxes, when uses judiciously, can have a beneficial impact in unexpected ways. While it is quite obvious that impose a tax reduce the level of that something, it is not clear it influences its volatility. It appears to be so efficient at this that it even counterweights the loss of loans in the average.