Ebook The Procyclical Leverage Effect of Collateral Value on Bank Loans — Evidence from the Transaction Data of Taiwan
In the financial contract literature collateral has been identified as serving as a screening device and sorting mechanism (Bester, 1985; Berger and Udell, 1990). The practical significance of collateral is recognized in recent studies on financial contracts in securing repayments, which put collateral as a primarily important factor in determining external financing and investment (Bernanke and Gertler, 1989; Kiyotaki and Moore, 1997; Chen, 2001a). In particular, Kiyotaki and Moore (1997) investigate exogenous shocks’ transmission mechanism of collateral channel through the interaction of credit constraints and the value of collateralized assets. Fluctuations in asset prices change the value of the collateral and affect the firm’s ability to obtain external financing, thus magnifying business fluctuations. Chen (2001a) extends the connection of collateral value and bank loans by taking banks’ financial characteristics into consideration, emphasizing the role of banks in affecting the amount of collateral-secured loans. Their models hence provide a theoretical link between fluctuations of collateral value, firms’ credit constraint, and the capacity of bank lending. Their models further imply that the leverage per dollar value of collateral is positively correlated with the (expected) value of the collateral.
The significance of firms’ collateral value on bank lending has been empirically examined in the literature, and most of the analyses are based on macro data. For instance, Kiyotaki and West (1996) and Ogawa et al. (1996) use macro time-series data to explain the investment behavior of Japanese firms in the 1990s and find that land value significantly affects investment behavior. Among those few that apply micro-data in their analysis, Ogawa and Suzuki (1998, 2000) use Japanese firm-level data and find that Japanese land value has a significant effect on the degree of borrowing constraint. These works, however, do not fully control for bank heterogeneity which can be important in explaining observed lending behavior and the collateral requirement.
In this paper we use a panel transaction dataset from Taiwan to investigate the empirical relationship between a firm’s collateral value and land/real estate secured loans (land-secured loans henceforth) over asset price cycles. In particular, along the line of Kiyotaki and Moore (1997) and Chen (2001a), we examine whether collateral’s leverage on bank credits exhibits procyclicality to asset price cycles. The unique dataset used in this study combines detailed loan transaction information with the borrowers’ and the lenders’ financial profiles. Based on the dataset, we estimate a simultaneous equation model of demand and supply to investigate determinants of land-secured loans from the demand side and also from the supply side. Among the determinants, we are most interested in the collateral effect and the procyclicality therein. The transaction-level dataset allows us to control for bank heterogeneity by taking into account the financial stances of the lending banks, and by including unobserved bank-specific effects in the model.
Collateral-based lending for the business investment closely relates to the issue of lending procyclicality that is, lending increases significantly during business cycle expansions and then falls considerably during subsequent downturns, occasionally so drastically to be considered a “credit crunch” (e.g., Bernanke and Lown, 1991; Berger and Udell, 1994; Hancock et al., 1995). A large body of evidence has shown that changes in bank credits have strong impacts on aggregate fluctuations via the credit channel (e.g., Bernanke and Lown, 1991; Oliner and Rudebusch, 1996; Kashyap and Stein, 2000), and the impacts are particularly amplified by movements of asset prices and collateral values (e.g., Peek and Rosengren, 2000; Chen, 2001b; Iacoviello, 2005; Goyal and Yamada, 2004). Concerns of the potentially substantial impact from the procyclicality of bank credits have been raised by central bankers, practitioners, and researchers, most notably in the debate regarding the IRB (internal-ratings-based) approach in the Basel II regulatory framework (Kashyap and Stein, 2004; Gordy and Howells, 2004).
On the issue of bank lending procyclicality, various theories and empirical studies have been proposed (Rajan, 1994; Ruckes, 2004; Asea and Blomberg, 1998; Lown et al., 2000; Berger and Udell, 2004a, Matsuyama, 2004). The recent study by Berger and Udell (2004b) argues that issues of business financing should be examined in the context of the financial institution structure (lending technologies employed by different types of financial institutions) and lending infrastructure (laws regarding creditor rights and judicial enforcement, regulations, and taxes) of that economic environment. In this perspective our study conforms to the framework by considering the economic environment in Kiyotaki and Moore (1997) where financial contracts are imperfectly enforceable, and creditors then protect themselves from the threat of repudiation by collateralizing borrowers’ debt, thus employing the collateral-based lending technology. In such an environment, poor judicial enforcement and insufficient protection for creditor rights (lending infrastructure) directly affect the use of collateral-based lending (lending technology). This would be particularly true for economies with less-developed financial systems where bank loans are frequently secured by real estate and land.
The unique dataset used in this study helps us to gain several advantages over existing studies on collateral effects and on the procyclicality of bank lending. Firstly, even though previous works employ firm level and bank level data, to our knowledge this is the first study to provide evidence of the collateral effect at the transaction level. Secondly, the transaction data allows us to control for the effect of bank heterogeneity. For a given loan transaction, the collateral effect is better identified if banks’ financial circumstances and other unobserved bank effects are taken into account. Thirdly, since the dataset identifies the types of collateral in the loan transaction, we are able to focus our analysis exclusively on land-secured loans, which are immediately related to the value of land/real estate. This is in contrast to existing micro-based studies where total loans, instead of the more specific land-secured loans, are used in the analysis of the collateral effect. Finally, we estimate a simultaneous equation model of the demand and supply of bank loans from which we examine factors affecting loan transactions from both sides. Correlations between equations are taken into account in the estimation. Unlike the single-equation approach, our full-information approach utilizes all the information in the demand and supply system, rendering more efficient estimates.
We use the dataset to test the hypothesis that, after controlling for the financial status of the corresponding bank (lender), increases in a firm’s collateral value relax the credit constraint faced by the firm, enabling the firm to borrow more. We find that, in general, the value of collateral significantly and positively affects the amount of a land secured loan. Furthermore, during the period of 1991-1994 when Taiwan’s real estate prices exhibited an uprising trend, the empirical evidence shows that banks were willing to lend more for each collateral dollar. This is in contrast to the result for the 1995-2001 period whereby real estate prices experienced a steady decline. The evidence indicates that the leverage per dollar value of collateral is procyclical, which is consistent with Kiyotaki and Moore (1997) in that the leverage per dollar value of collateral is positively correlated with the (expected) value of the collateral. The implication is that during asset price run-ups, firms are not only able to pledge larger amount of collateral owing to the improved net worth, but are also given higher advance rates on bank loans for each dollar of the collateral.
We also investigate whether the role of collateral value in determining business loans is homogeneous across industries. In particular, since the electronics industry is Taiwan’s star industry during the sample period with the highest growth rate among industries, it was much favored by investors (e.g., Liu et al., 1999; Wang, 2002). It is thus informative to see whether the market’s favoritism would cause banks to impose different collateral requirements on the industry’s borrowing firms. The results show that the electronics industry is able to borrow more for each marginal dollar of collateral.
The organization for the rest of the paper is as follows. Section 2 explains the data source and provides a descriptive analysis of the trends of loans in Taiwan. Specifications for the demand and the supply equations are also given here. Section 3 presents the estimation results. Section 4 concludes the paper.
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