**Abstract**

We incorporate two structural shocks associated with balance sheets of both the financial and nonfinancial firms in a medium scale New Keynesian dynamic stochastic general equilibrium (DSGE) model. The structural shocks in the model are assumed to possess stochastic volatilities with a leverage effect. Then, we estimated the model using a data-rich estimation method and utilized up to 40 macroeconomic time series. We found the following three pieces of empirical evidence in the Great Recession (Dec. 2007–Jun. 2009) worsened further by the collapse of Lehman Brothers in September 2008. First, the net-worth shock of financial firms had gradually declined prior to a huge decrease of net-worth of nonfinancial firms. Second, the net worth shock of nonfinancial firms accounted for large weight of the business cycles after the Great Recession, in terms of the data-rich approach with the SV of structural shocks, unlike the standard DSGE model. Third, the Troubled Asset Relief Program would have immediately worked to improve balance sheets of financial institutions, although it would not have stopped worsening those of the corporate sector for a while.

**Keywords:** new Keynesian model, DSGE model, data-rich approach, Bayesian estimation, financial friction, stochastic volatility, net-worth shock

### **1. Introduction**

The Great Recession (Dec. 2007–Jun. 2009) is thought to have deeply worsened by simultaneous collapse of several big financial institutions besides many bankrupts of the corporate firms and households in the US economy. Recently, a couple of survey papers researching causes of the Great Recession by prominent economists (i.e., Gertler and Gilchrist [1], Kehoe et al. [2]) are published in terms of macroeconomic models, say dynamic stochastic general equilibrium (DSGE) models. Since we obtained a broad consensus that solvency and liquidity problems of the financial institutions are chief among the fundamental factors causing the recession itself, as described in above papers, it is plausible to incorporate financial frictions in both the banking and the corporate sectors of a New Keynesian (NK) DSGE model in order to analyze the recession. Meanwhile, Mian and Sufi [3] analyzed the Great Recession from the aspect of household balance sheets and employment.

The purpose of this study is to identify what structural exogenous shocks contributed to the Great Recession by analyzing the mutual relationship among macroeconomic and financial endogenous variables in terms of business cycles from the point of view of a DSGE model. In fact, according to Ireland [4], there are three sets of considerations that are premature for existing DSGE models. First, failures of financial institutions and liquidity drain should be endogenously described with other fundamental macroeconomic variables for producing economic insights. Second, most recessions have been associated with a rise in bankruptcies among banking and corporate sectors alike. And recessions have featured systematic problems in the banking and loan industry. And third, declines in housing prices and problems in the credit markets might have played an independent and causal role in the Great Recession's severity. Our study challenges to struggle with the former two exercises of Ireland [4], by identifying two different unobservable net-worth shocks of both banking and corporate sectors in a medium scale NK-DSGE model, into which two different financial frictions are newly embedded. And, we estimate time-varying volatility of these structural shocks in order to examine rapid changes of uncertainty and risk for financial crisis across financial markets and the economy as a whole.

**2. Model**

*Source of the Great Recession*

*DOI: http://dx.doi.org/10.5772/intechopen.90729*

**Figure 1.**

**35**

We adopt the stylized DSGE model, often referred to as the medium-scale New

Keynesian (NK) model, following Christiano et al. [7] and Smets and Wouters [5, 6], which focused on the nominal rigidities of price level and wage as well as the quadratic adjustment cost of investment and habit formation of consumption as blue arrows shown in **Figure 1(a)**. In this NK model, it is generally assumed that

*Our NK model. (a) Flowchart of economy. (b) Two financial frictions. Notes: Panel (a) shows the mediumscale NK model, following Christiano et al. [7] and Smets and Wouters [5, 6], which assume the nominal rigidities of price level and wage as well as the quadratic adjustment cost of investment and habit formation of*

*are modeled to reflect the two different relationship between the balance sheets of the corporate and banking*

*<sup>t</sup> and deposit*

*<sup>t</sup> in between, and which*

*consumption. Panel (b) shows two financial frictions in which the spread between lending rate R<sup>E</sup>*

*rate Rt is divided into two portions by introducing the risk-adjusted return for banks R<sup>F</sup>*

*sectors and the borrowers' agency costs against the lenders, respectively.*

As advanced econometric tool, we adopt a data-rich environment to estimate a NK DSGE model following Smets and Wouters [5, 6] but adding above two financial frictions for the US economy. The advantage of incorporating a data-rich environment into a NK DSGE model is that we can more robustly identify two different net-worth shocks generated by two financial frictions because of decomposing comovements of model variables and idiosyncrasy of measurement errors from observable variables of big macroeconomic panel dataset. And this advantage is also useful to estimate a time-varying stochastic volatilities (SVs) of the structural shocks including financial shocks in the DSGE model and to estimate contributions of financial frictions on the real economy both during the Great Recession and after it, because this framework allows the structural shocks to relax the specifications thanks to big dataset.

By adopting the data-rich environment and SV shocks, we will consider four alternative cases, based on the number of observation variables (11 vs. 40 observable variables) and the specification of the volatilities of the structural shocks (constant volatility vs. time-varying volatility). By comparing the four cases, we report the following three findings of empirical evidence in the Great Recession: (1) the net-worth shock of financial institution had gradually declined prior to a huge decrease of net-worth of corporate sector. (2) The net worth shock of nonfinancial firms played an important role during the Great Recession and after it, in terms of the data-rich NK DSGE model with the SV of structural shocks, unlike the standard NK DSGE model. (3) The Troubled Asset Relief Program (TARP) would have immediately worked to improve balance sheets of financial institutions, although it would not have stopped worsening those of the corporate sector for a while. These findings suggest that it is effective to strengthen the regulation, supervision and risk management of banks for preventing financial crisis. And they seem to support the Basel III framework developed by the Basel Committee in response to the global financial crisis of 2007–2009.

As describing our estimation results, introducing structural SV shocks to a DSGE model has their credible interval narrower than half of the model with constant volatilities that indicates a realistic assumption of the time-varying structural shocks. And it is plausible that the uncertainty is trivial in ordinary times but it becomes to a huge size at the turning points of recessions.

The chapter is organized as follows. Section 2 illustrates two financial frictions of the New Keynesian model. Section 3 presents the estimation technique and data description. Sections 4 and 5 discuss the estimation results and interpretation of the Great Recession in terms of the New Keynesian model. Section 6 concludes the paper.
