Ebook How Important are Financial Shocks for the Canadian Business Cycle?
Given the on-going financial crisis precipitated by the sub-prime loan problem in the U.S. financial sector, there has been an increased interest in the linkage between financial activity and real economic activity. In particular, there is a heightened interest in how the shock occurring in direct and/or indirect financial market can affect the real economic activity. Although the Canadian banking sector seems to be weathering the current financial crisis (Northcott et al. (2009)) or have not experienced a major financial turmoil in recent decades, there is no guarantee that the Canadian economy will be free from a large shock in the financial sector in a near future. In order to help the policy makers to understand the consequences of such contingency and to facilitate them in forming a counter-measure, it is crucial to assess how vulnerable (or robust) is the Canadian economy to the shocks originating in the financial sector. As such, we ask the following question in this paper; how important are financial shocks for the Canadian business cycle?
To answer the above question, we need to decide how to model the financial friction and financial shocks. In modeling the financial friction in a general equilibrium setting, there are mainly two approaches. One way is to impose collateral constraint as in Kiyotaki and Moore (1997). This collateral constraint approach is becoming a popular choice, especially when modelling the financial friction in mortgage loan market where residential asset is customary withheld as a collateral until the mortgage loan is repaid in full. Another approach is to model external finance premium as in Bernanke and Gertler (1989), Carlstrom and Fuerst (1997), and Bernanke, Gertler, and Gilchrist (1999). This approach proved extremely useful in modelling the standard debt contract between the corporate sector and financial intermediary which allows us to analyze the relationship between business fixed investment and external financing cost. Both types of financial friction — collateral constraint and external finance premium — are useful in addressing the linkage between financial market and real economic activity such as financial acceleration mechanism in residential investment and business fixed investment. However, since we are more interested in the fluctuation of the business fixed investment — the most important factor in output fluctuation, we will be adopting the external finance premium as the choice of financial friction mechanism in this paper. In particular, we construct a medium-scale dynamic stochastic general equilibrium (denoted DSGE, hereafter) model with financial friction ? la Bernanke, Gertler, and Gilchrist (1999) (denoted BGG, hereafter). Further, reflecting the Canadian context, we extend the model to incorporate the small-open economy feature.
Next, we need to decide the specifications of the financial shocks. In addition to the standard macroeconomic shocks adopted in the empirical DSGE literature, we adopt two types of financial shocks: external finance premium shock and corporate net worth shock. The importance of external finance premium shock has been pointed out by Smets and Wouters (2003, 2007), while the importance of corporate net worth shock has been emphasized by Christiano, Motto, and Rostagno (2007) (denoted CMR, hereafter). In the context of this paper, the external finance premium shock is an exogenous shock that affects the external finance premium (or credit spread) irrespective of corporate leverage ratio and can be interpreted as any shock affecting credit spread without initially affecting corporate balance sheet, such as financial market condition or financial intermediary’s lending attitude. Corporate net worth shock, in our context, is an exogenous shock to turn-over rate of entrepreneurs which, in turn, affects the credit spread through the aggregate leverage ratio of the corporate sector. Following CMR, this shock can be interpreted as an aggregate shock to the entrepreneurial net worth in the economy. Considering the importance of both types of financial shock as in Smets and Wouters (2003, 2007) and CMR, we embed both of them to our benchmark model and compare which type of shock, external finance premium shock or corporate net worth shock, are relatively important in accounting for the Canadian business cycle.
As for the estimation of the model, we adopt the Bayesian estimation methodology which is becoming a standard tool in the empirical DSGE literature. Now, an issue remains. When there are two types of financial shock in the model and both shocks affect the non-financial variables via external finance premium — the only channel that links non-financial variables and financial variables in BGG-type model, inevitably, the qualitative pattern of the impulse response functions under both types of financial shock become similar, especially for the non-financial endogenous variables. Consequently, if the observable data in the estimation are confined to non-financial variables, we will face a difficulty in identifying two financial shocks. In order to avoid this identification problem of two financial shocks, we include financial variables (i.e., leverage ratio) to our observable data set, in addition to the standard non-financial data adopted in the empirical DSGE literature. Since the impulse response functions under two financial shocks imply qualitatively different patterns for these financial variables, we claim that inclusion of financial variables to observed data will ensure the identification of two financial shocks in the estimation.
The main empirical findings of this paper can be summarized as follows. Under the shock specification where both financial shocks — external finance premium shock and aggregate net worth shock — are present in the model, it turned out that both financial shocks are quite important in accounting for the Canadian business cycle. Taking the case of business fixed investment in Canada, our variance decomposition for unconditional forecast error showed that external finance premium shock to be accounting as much as 7.5% and aggregate net worth shock to be accounting as much as 5.6% of the variance. In total, the financial shocks accounted for more than 13% of the variance of the business fixed investment and this magnitude was comparable to that of investment specific technology shock. Based on this result, it will not be an over-statement to say that the financial shocks are as important as the investment-specific technology shock in accounting for the movement in the business fixed investment in Canada.
The remainder of this paper is organized as follows. Section 2 describes the model structure and the shock structure adopted in this paper. Section 3 explains the estimation strategies and also describes the data adopted in this paper. Section 4 reports the estimation results under four different shock specifications of the financial shocks. In particular, the posterior means of the parameters, estimated IRF, variance decompositions and historical decompositions will be reported. Section 5 explores the consequences of using alternative data set. In particular, this section demonstrates the importance of utilization of the financial data, especially leverage ratio data, in identifying the financial shocks. Section 6 summarizes and concludes the paper.
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