does a particularly good job in matching eective tax rates across sectors and in accounting for the dispersion in capital and marginal product of capital for public rms. In summary, I consider the results coming from this table as a success of the calibration strategy. Next, I discuss the calibration of the shock.

# 5.4 Credit Crunch Shock

## Evidence

Between the second quarter of 2008 and the second quarter of 2010, small business loans made by commercial banks declined by over $40 billion (Duygan-Bump et al. (2015)). While this could be a result of a change in the demand for credit, evidence provided by Ivashina and Scharfstein (2010) suggests that there was a change in the supply of credit. Using data on syndicated new loans they nd strong evidence of a reduction in lending around the 2007-2009 recession.<sup>47</sup> Between 2007 and 2008 they found that loans targeted for investment in equipment and machinery fell 48 % _._ Another piece of evidence can be found in the responses to the Federal Reserve's Senior Loan Ocer Survey on Bank Lending Practices. The surveyed banks indicated that they signicantly increased the requirements to approve new commercial or industrial loans to rms around that period of time. More convincing evidence of an exogenous shock to the supply of credit is provided by Almeida et al. (2009), Duchin et al (2010) and Huang and Stephens (2011). Based on the evidence, I take a stand on the nature of the shock and model it as a credit supply shock that will aect the collateral constraint in the model.

## Calibration

In order to replicate the dynamics of the credit conditions of the economy, I hit the model with an aggregate nancial shock modeled as an unexpected decrease in the collateral constraint parameter _λ._ After the initial shock, the future path of _λt_ is perfectly known by all agents. This experiment is similar to the credit crunch in Khan and Thomas (2013), Buera et al. (2015) and Shourideh and Zetlin Jones (2016).

The calibrated shock reduces the value of _λ_ upon impact and the eect of this shock decays over time until the economy returns to the pre-crisis level (under perfect foresight). The initial shock implies a reduction of almost 20 % to the value of the parameter _λ,_ which is consistent with the actual decline in the ratio of external nance to capital observed in the data between the end of 2007 and the rst quarter of 2010.<sup>48</sup> Figure (8) depicts the evolution of the credit conditions in the model and in the data. The left panel shows the ratio of external nance to capital stock using the denitions described in subsection (5.1). For the model, I compute percentage deviations from steady state values. For the data, I show the dierence with respect to the value in the fourth quarter of 2007 of the percentage deviation from HP-lter trend (in Q4-2007, the ratio was 4.8 % above the HP trend).

> 47This market is the main vehicle through which banks lend to large corporations.

> 48The values for the collateral constraint are, _{_ 4 _._ 21 _,_ 2 _._ 95 _,_ 2 _._ 21 _,_ 2 _._ 71 _,_ 3 _._ 8 _}_ . After that, _λt_ = _λt−_ 1 + 0 _._ 2 ( _λt−_ 1 _− λ∗_ ) where _λ_<sup>_∗_</sup> is the steady state value, which is equal to 4.21 in _t_ = 0 . The rst period of the transition is 2007.

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