POSICIONAMIENTO

The literature that addresses the implications of financial conditions of borrow- ers and lenders has boomed in the recent years. There is a long list of works that replicate the standard models with friction at firm or bank level and focus on estimation of parameters for different economies. In this section I focus on a selected list of studies that contribute in the literature with new models or that are closely related to my work. A short list of studies are related to models with a friction at firm level or with a friction arising due to credit constrained bank. I save more space for the studies with constraints arising at both, firm and bank level.

In the financial accelerator literature, my works is related to Fuerst et al.

(2016) who modify the BGG framework to allow for the sharing of aggregate risk by the lender and the entrepreneur. Unlike in BGG where the return to the lender does not depend on realization of aggregate risk, in their contract the average return to the lender varies with macroeconomic conditions. In my framework I let the lender share the idiosyncratic risk. Both lender and borrower share some of the risk.

Similar to Fuerst et al. (2016) I conclude that the financial accelerator is weak compared to the bank friction. That firm friction is weak is also consistent with the results ofSuh and Walker(2016). They estimate three different models with credit constraint firms and find that financial frictions at firm level are not able to explain large fluctuations seen during the financial crisis.

A notable contribution is the paper byChristiano et al.(2010). At firm level, they replicate the financial accelerator mechanism and let banks issue working loans to make bank’s net worth fluctuate. Their object of research is not a com- parison of the relative significance of bank and firm friction for the external finance premium. Banks are designed as entities that own a technology to con-

vert labor and capital into deposit accounts, and short term security accounts. These liabilities are then offered to firms as debt loans and working capital loans. The latter transmit the impact of firm default on bank financial health. A direct exposure of bank net worth to asset price fluctuations does not take place. The model is estimated with 16shocks. They add two financial shocks,

one on firm net worth and the other on the idiosyncratic project returns of the borrowing firm. They find the latter, named risk shock, important for the dy- namics of the model and in particular for the correlation of credit flows with output.

Finally, in the financial accelerator literature, my work in chapter 4.1 is

related to the work by Galvao et al.(2016) who estimate a time varying DSGE model only with a financial accelerator and find that volatility of financial friction shock has changed during2007-2011compared to1985-2006.

More recent bank channel models emphasize the collateral value of bank net worth. Among these studies there is a strong support to the role of financial sector leverage for the risk premium or macroeconomic stability.

Nuno and Thomas (2017) analyze the dynamics of bank leverage subject to aggregate and idiosyncratic shocks on bank asset returns. In their model banks borrow in the form of short-term collateralized risky debt and own the firms. Due to a moral hazard problem on the part of the banks, leverage is endogenously evolving. They conclude that idiosyncratic shocks, rather than aggregate technology ones, help replicate the procyclicality of bank leverage and the size of its volatility. The similarity with my framework is that they make banks subject to both aggregate and idiosyncratic shocks while I evaluate the impact of sudden a change in the long-run value of idiosyncratic shock.

My framework is related to the work of Boissay et al. (2013) with two fric- tions in the bank-depositor relationship and in the interbank market. Banks

are credit constrained as they can divert the non-collateralized funds (against a diversion cost). Interbank market arises due to private information on banker skills as a borrower giving rise to asymmetric information. The difference is that they evaluate the probability of endogenously arising banking crisis.

My paper is related to He and Krishnamurthy (2013) who analyze the dy- namics of risk premia during crisis in asset markets where the investor (bor- rower) is a financial intermediary. In continuous time model the authors eval- uate the probability of change in risk premium in equilibrium rather than in a loglinearized model around the steady state. In a similar framework,Brunner- meier and Sannikov(2014) analyse the links between intermediaries’ financing positions to risk premia while Phelan (2016) investigates implications of finan- cial sector leverage for macroeconomic instability and welfare5

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The recent literature with two-sided (double) frictions has blossomed in the recent years. While most double friction models have some similarities in common with my work there are two papers,Kühl (2017) and Rannenberg (2016), that share many features with my model framework. I dedicate more space in this section to those two studies and discuss the remaining studies shortly.

My work is closely related to the work of Kühl (2017). The similar fea- tures are that both banks and the small firms with loans on their balance sheet are financially constrained by assuming a limited enforcement problem as in

Gertler and Kiyotaki (2010). Similar to my framework, banks hold a combi- nation of state contingent assets - 100% of the equity securities of large firms-

and non-state contingent loans issued to smaller firms.

My work differs from his as in my framework firms can default (as in a

Bernanke et al. (1999) model), while he abstracts from loan defaults in his

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Continuous-time models with frictions at intermediary-level allow the authors to set up highly non-linear relationship between the financial health of intermediary and the risk premium (He and Krishnamurthy(2013),Brunnermeier and Sannikov(2014) andPhelan(2016)).

model. With some modifications as in Fuerst et al. (2016), this feature allows me to pass some losses to the banks. In Kühl (2017) banks suffer losses only from equity securities. In his framework only (small) firms that take a loan are financially constrained and accumulate net worth.

Another difference is that the objective ofKühl(2017) work is to investigate the implications of state contingency of bank assets by changing the equilib- rium composition of bank balance sheets. He analyses how bank net worth evolution depends on the composition of bank assets (in equilibrium) and how this composition matters for the transmission of shocks and for the procycli- cal behaviour of bank leverage. His key result is that amplification of shocks depends on bank balance sheet composition. In my framework, I compare the propagation of shocks in a two-sided (double) friction model relative to the financial acclerator model and the simple GK model. I do not explore the im- plications of different compositions of bank balance sheet. Another difference is that I estimate the model in two subsamples to evaluate how certain friction parameters may have changed during the recent recession in US.

The second paper that my work is related to is Rannenberg (2016). In his work both banks and firms are constrained as in my framework (GK and BGG respectively). In a similar wayRannenberg(2016) models firms as inBernanke

et al. (1999) and adds a set-up borrowed from Gertler and Karadi (2011) to model banks. He analyzes the dynamics of cyclical behaviour of bank and firm leverage as well as the dynamics of external finance premium. He makes a horse-race of (exogenous) firm and bank net worth shocks. I differ from his paper in that I include two types of financing for the firm which become two assets on bank’s balance sheet. In addition, Rannenberg includes within

period working loans which pay no interest and are of a negligible amount to make bank leverage procyclical6

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A second difference is that, these studies rely on capital quality shocks or exogenous net worth shocks to simulate the fluctuations on bank or firm net worth during the recent crisis. I assess the propagation of standard technology and policy shocks as driving forces of the model through the interaction of the two frictions. Finally, a critical part of my work which is different from Ran- nenberg(2016) is that I estimate the parameters for two different sub-samples,

1985-2004 and 2005-2014, which allows me to identify shifts in deep parame-

ters to explain the dynamics during the recent crisis.

To bring in a role for the bank net worth Zhang (2009) modifies the BGG model by introducing fixed lending rate contract (instead of state-contingent). In his framework both borrowers and lenders share aggregate systemic risk. The capital stock has to be maintained to keep the required return on de- posits and on equity at low levels. Though there is loan supply channel in his framework, the bank is only exposed to the friction due to agency costs. Bank balance sheet in his model is not exposed to changes in asset prices which are the main cause triggering the loan supply channel in US.

Finally, a common feature between the above papers, Zhang (2009), Ran-

nenberg (2016) and Fuerst et al. (2016), and in my framework is that we use predetermined contractual loan rate which allows for some the aggregate risk to be shared between the banker and the firm. Bernanke et al. (1999) assume the entrepreneurs will absorb all the aggregate risk, as lenders get risk free rate by issuing state contingent (not fixed) contract.

My work is related to Hirakata et al.(2011) and Hirakata et al.(2013) who employ a costly state verification contract (financial accelerator mechanism) to

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While the author mentions loans within the period which are critical for the procyclical be- haviour of bank leverage, they are not explained in the model section.

model frictions at firm and bank level. Their work is different first because they rely on exogenous net worth shocks, and second because their objective is to explain fluctuations in output and investment and to analyze optimal Taylor rules, respectively7

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My thesis is related to Hristov and Hülsewig (2017), Bonciani and van

Roye (2015) and Iacoviello (2015) who set up two-sided friction models. The objective of Hristov and Hülsewig (2017) is to replicate the procyclicality of bank profitability, counter-cyclicality of firm default rates and credit spreads to monetary policy shocks. Their FA mechanism allows banks to share the losses. Bonciani and van Roye(2015) set up a double moral hazard framework with aKiyotaki and Moore (1997) (hereby KM) type constraint on firms and a monopolistic banking sector. Their model is different as they investigate the effects of uncertainty shocks on economic activity in the euro area. Iacoviello

(2015) builds a framework with credit-constrained banks, firms and house- holds in the form of collateral constraints as in KM. He evaluates the impact of financial shocks for the business cycles. Clerc et al. (2015) also bring three credit constraint agents, households, banks and firms, in a general equilibrium framework. Unlike in my thesis, they analyse the implications of default for capital regulation.

My work has a common feature with other papers that consider two-sided financial frictions allowing for interaction between constrained borrowers (or firms or households) and financial shocks arising in interbank market as in

Gertler and Kiyotaki(2015),Dib(2010a),Ajello(2016). A series of other papers evaluate the interaction between frictions due to credit constraints of borrower and intermediary at a more theoretical level (Rohan(2016),Sandri and Valencia (2013), Zeng(2013)).

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Another difference of my framework is that the wholesale producer finances the purchase of capital stock with standard debt and by selling equity stake securities.

Finally, my work is related to Verona et al.(2017) who consider two types of financing, bonds and loans. While the loan market works as in the financial accelerator of BGG, the bond market is slightly different from the equity secu- rities market used in my framework. The objective of their work is to evaluate interest rate rules in the presence of financial frictions.

None of the studies addresses the relative significance of financial and non- financial sectors in propagating fundamental shocks. Where lender net worth is modeled, in one stream of literature, the authors are interested on policy im- plications of exogenous fluctuations in (lender) net worth. Alternatively, most studies compare propagation of exogenous firm and bank net worth shocks rather than propagation of fundamental, tfp, istand monetary shocks.