نقدینگی، افق های نامتناهی و نوسانات اقتصاد کلان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|12979||2006||26 صفحه PDF||سفارش دهید||9712 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : European Economic Review, Volume 50, Issue 5, July 2006, Pages 1105–1130
This paper develops a computable dynamic general equilibrium model in which corporate demand for liquidity is endogenously determined. In the model, liquidity demand is motivated by moral hazard, as in Holmström and Tirole (J. Politic. Econom. 106 (1998) 1). As a result of incorporating agency cost and endogenously determined liquidity demand, the model can replicate an empirical business cycle fact, the hump-shaped dynamic response of output, which is seldom observed in standard RBC dynamics. Further, in the model the corporate demand for liquidity from a financial intermediary (credit line, for instance) is pro-cyclical, while the degree of liquidity dependence (defined as liquidity demand divided by corporate investment) is counter-cyclical. These business cycle patterns are consistent with a stylized fact empirically verified in the lending view literature.
This paper develops a computable dynamic general equilibrium model in which the role of liquidity over the business cycles can be analyzed. My focus is especially on the corporate demand for liquidity and its influence on business cycles via investment decision rules. It is an empirical fact that corporations rely heavily on short-term debt for working capital expenses in the United States as well as in Japan.1 Corporate finance and the role of the banking sector have recently caught considerable attention of business cycle researchers. In this stream of literature, the real business cycle (RBC) framework with a financial intermediary developed by Fuerst (1992)2 is a pioneering work. It was intensively studied by Christiano (1991), Christiano and Eichenbaum (1993), and Einarsson and Marquis (2001), among others. These models are well capable of explaining empirical business cycle facts, including bank loans and other financial variables. However, they fail to replicate the actual auto-correlation patterns of output and investment.3 One advantage of the model introduced in this paper is its superior performance compared with the Fuerst-Christiano style of RBC models in mimicking actual auto-correlation patterns. Another stream of studies on the interaction of corporate finance and the business cycle extends agency cost models, which were originally developed in microeconomic contract theory, to macroeconomics and dynamic general equilibrium analysis. Roughly speaking, the difference between the value of the firm in what would be an ideal contracting situation and what is viable through negotiation is referred to as agency cost. 4 In agency cost models, the net present value (NPV) of an investment project is not maximized, simply because lenders and borrowers (entrepreneurs) have divergent incentives, so that for each agent NPV maximization could be suboptimal. The financial contract between lender and borrower is characterized by the nature of the concessions necessary to achieve at least a second-best solution. This study is in the stream of dynamic general equilibrium (DGE) analysis with agency cost. The key feature of my model, a unique financial contract structure, is taken from Holmström and Tirole (1998) (denoted as HT, hereafter). The paper extends the HT model to an infinite horizon environment using a modeling strategy similar to that of Carlstrom and Fuerst (1997), so that it can aid in the analysis of business cycle dynamics that result from such liquidity-dependent corporate financing. The first notable result of the paper is that my model generates a hump-shaped impulse response very similar to that in Carlstrom and Fuerst (1997), which is reported as an empirical fact in earlier business cycle studies.5 Further, my DGE model provides several insights into other aspects of corporate liquidity demand and business cycles. Figs. 1 and 2 show empirical evidence that corporate firms’ working capital expenses are pro-cyclical, while the degree to which firms rely on bank loans to finance their working capital expenses, measured as the volume in commercial and industrial loans relative to output, is counter-cyclical in both the US and Japan.6 My DGE model replicates this corporate financing structure over business cycles, in the sense that it successfully generates pro-cyclical demand for liquidity, while the degree of liquidity dependence (measured as liquidity demand divided by investment expenditure) is counter-cyclical. Moreover, this outcome exhibits clear similarity to existing empirical studies in the lending view literature, which claim that corporate firms become highly dependent on bank loans during recessions.Among the existing DGE studies with agency costs, there are two studies that attempt a very similar task to my model. One is Carlstrom and Fuerst (1997) and the other is Kiyotaki and Moore (1997), both of which model infinitely lived agents with agency problems to analyze business cycle dynamics. What distinguishes my model is the structure of the financial contract.7 In their models, there is no role for credit lines or corporate demand for liquidity. In contrast, since the HT style financial contract entails an explicit role for liquidity, my DGE model can analyze business cycle facts regarding corporate demand for liquidity along with dynamics of output and investment. This paper is organized as follows. Section 2 develops the DGE model, extending a variant of the HT model to infinite horizons. Section 3 presents calibration and simulation results. Section 4 discusses some model-based interpretations of empirical facts and how they relate to lending view studies. I conclude the paper in Section 5.
نتیجه گیری انگلیسی
Although the HT model is highly stylized, it requires a much less specific environment than might appear to be the case. Recall the calibration in Section 3. I need to specify only two parameters and one distribution for entrepreneurial technology, namely ω1ω1, ω0ω0 and ΦΦ. Actually, as long as we are adhering to one-to-one transformation technology in capital production, ω1Φ(ω1)ω1Φ(ω1) must be set at one, and therefore only one parameter and one distribution need to be calibrated. This implies that the hump-shaped dynamics of output are robust for a broad class of models in which the investment process is characterized by leakage due to moral hazard or imperfect information. My guess is that any reasonable theory that yields an investment function similar to Eq. (8) is consistent with hump-shaped dynamics of output. However, of course, this must await further research on this issue to be verified. A weakness of my model is that it lacks the ability to analyze the role of public liquidity, since there is no aggregate uncertainty present in the economy. Intuitively, the role of the government is to eliminate the aggregate uncertainty to achieve at least the second-best outcome on the production side of the economy. Incorporating aggregate uncertainty and hence the role of government-supplied liquidity is potentially interesting for two reasons. One is that such a model could provide much richer insight into economic welfare. The other is that it would allow us to analyze the business cycle patterns of liquidity premiums for government-supplied securities, such as T-bills. These issues remain open for future research.