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2015 | OriginalPaper | Buchkapitel

12. Bank Lending and Firm Activities: Overcoming Identification Problems

verfasst von : Kaoru Hosono, Daisuke Miyakawa

Erschienen in: The Economics of Interfirm Networks

Verlag: Springer Japan

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Abstract

This chapter presents an overview of the extant literature on the real impact of financial constraints, with a particular focus on financial constraints originating from adverse shocks to bank lending. While there has been significant progress in theoretical research on the causal link between negative fund supply shocks and various firm activities, there are relatively few empirical studies that successfully identify loan supply shocks. The first part of this chapter reviews the large body of literature on this topic and details how recent studies have attempted to overcome the important identification challenge of disentangling fund supply and demand shocks. Following the discussion of various attempts to overcome this challenge ranging from the use of natural experiments to the employment of extensive panel datasets, two studies by the authors of this chapter are discussed in detail, which employ a natural disaster in Japan as a natural experiment to examine the real impact of financial constraints on the capital investment and export behavior of firms.

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Vorheriges Kapitel What do Cash Holdings Tell us About Bank-Firm Relationships? A Case Study of Japanese Firms

Note, however, that Brewer et al. (2003a) also found that the magnitude of these negative effects on the value of borrower firms was not significantly different from that on all other firms in their sample.

Using matched bank-firm data for Japan from 1987 to 1994, Kline et al. (2002) found that financial difficulties of banks significantly reduced the number of foreign direct investment projects by Japanese firms in the United States. Using data of listed Japanese firms for 1993–1999, Peek and Rosengren (2005) found that banks expanded loans to unprofitable firms during this period. See also Caballero et al. (2008) for such “zombie” lending practices by Japanese banks in the 1990s.

For this part of their analysis, they used bank-level (i.e., micro) data.

The study by Amiti and Weinstein (2011), which is described in Section 12.3.5 below, deals with this problem of endogenous matching by adding a full set of bank fixed effects. Specifically, they add a dummy variable indicating whether or not the firm is the bank’s client in that year and its interaction term with the change in banks’ market-to-book value.

They utilized information on a firm’s successive loan applications to different banks when they controlled for loan-level fixed effects.

Hosono and Miyakawa (2014) applied a similar identification strategy to data on outstanding loans for bank-firm pairs in Japan and found that banks with more liquidity or capital tended to lend more to their client firms. Moreover, the size of these effects tended to be larger when economic growth was lower. The study further found that the transmission of the shock had a direct impact on firms’ capital investment.

Popov and Udell (2010) did not use observations on actual bank-firm matches, but instead matched firms and banks based on their locality.

Fiscal year t begins in April of year t and ends in March of year t + 1.

Table 12.1 reports the results when firms are classified into six industries, namely, mining and construction; machinery manufacturing; other manufacturing; wholesale, retail and restaurants; finance, insurance, real estate, transportation, and communications; and other), and consequently five industry dummies are added. In the discussion paper version, firms are classified into five industries, yielding similar results.

The reason for not estimating (2) using probit or logit estimation is that the marginal effects and standard errors of the interaction term of F_DAMAGED and B_DAMAGED in these nonlinear models would need to be corrected (see, e.g., Norton et al. 2004). Angrist and Pischke (2008) have shown that the coefficients obtained using OLS estimation are virtually the same as the marginal effects using probit estimation.

The positive coefficient on B_HQDAMAGED in FY1997 may also reflect the survival bias arising from only selecting firms that survived over the three observation years. However, the dropout rate was not significantly different in FY1997 between firms with damaged main banks and firms with undamaged main banks.

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Titel: Bank Lending and Firm Activities: Overcoming Identification Problems
verfasst von: Kaoru Hosono
Daisuke Miyakawa
Verlag: Springer Japan
Buch: The Economics of Interfirm Networks
Print ISBN: 978-4-431-55389-2

Electronic ISBN: 978-4-431-55390-8

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-4-431-55390-8_12

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