University of Amsterdam Faculty of Economics and business
Bachelor specialization Finance and organization
The determinants of the shadow banks’ decision to deleverage the balance sheets during the financial crisis
Name: Chenlu Zhou
Student number: 11001860 Number of credits: 12
Specialization: Finance and organization
Supervisor: Shivesh Changoer
Statement of Originality
This document is written by Chenlu Zhou who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
The main focus of this study is to investigate whether the fluctuated asset prices and the changes in the institutional environment during the financial crisis of 2008 contributed to the deleveraging of the balance sheets of the shadow banks. 170 listed financial firms in the US are selected as a sample, while the study period is from 2004 to 2016 in order to compare both the pre-crisis period and post-crisis period. There are five variables of interest in total. Three of them are firm-level variables, which are firm size, asset tangibility, and growth opportunity. Two of them are intuitional variables which are the growth of the inflation rate and the stock market development. The dependent variable is the leverage ratio of the shadow banks selected.
Several main conclusions are drawn here. The first one is that the asset tangibility has significant influence on the shadow banks’ decisions to deleverage during the crisis. The second one is that the stock market development during the crisis contributed to explaining the deleveraging of the shadow banks. The last but not least, the growth opportunity helps to explain why some shadow banks chose to increase the leverage ratios rather than deleveraging during and after the crisis.
Table of contents Statement of Originality
Abstract
I. Introduction ... 1
1.1 What is shadow banking? ... 1
1.2 Research question and structure ... 2
II. Literature review ... 4
2.1 Background information ... 4
2.2 The importance of the leverage of shadow banks ... 5
2.3 Deleveraging of the shadow banks in the US during the crisis ... 6
2.4 Factors that contribute to the deleveraging of the shadow banks ... 7
2.4.1 Firm Size ... 8
2.4.2 Asset tangibility ... 8
2.4.3 Growth opportunity ... 10
2.4.4 Annual growth of the inflation rate ... 11
2.4.5 Stock market development ... 11
III. Method, data and sample ... 12
3.1 Data ... 12
3.2 Sample description ... 13
3.3 Method ... 16
IV. Result and analysis ... 18
4.1 Empirical results and analysis ... 18
V. Robustness tests ... 24
VI. Conclusion ... 25
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I.
Introduction1.1 What is shadow banking?
The term shadow banking, first defined by the president of Federal Fund Reserve Banks of the US before the crisis, is unregulated financial activities that mainly include derivatives like hedge funds and asset-backed securities
(Munteanu, 2016). However, with the development of the shadow banking, the
definition of the shadow banking is no longer only limited to unregulated financial activities. Moreover, the shadow banking also refers to financial institutions which operate with high financial leverage. These financial institutions are usually financial companies, investment banks, insurance firms and Fintech companies
(Munteanu, 2016). Although the shadow banking system has already existed for
more than 40 years, the importance of the role played by shadow banking has been highlighted since the financial crisis in 2008 (De Rezende, 2011).
During this period, traditional banks suffered considerable losses and were not able to meet the capital demands of investors, especially since some of them were on the verge of collapse (Fernandez & Wigger, 2016). Because traditional banks could not meet the capital demands of investors and the shadow banks offered lower interest rates, more and more investors started to borrow from the
“shadow banking system”.1
At the same time, many firms which are in the
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Due to the lack of supervision, as competitors of the traditional banks, the shadow banks are more willing to lend in lower rates to potential investors (Istiak & Serletis, 2016).
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shadow banking system started to deleverage their balance sheets (Fostel & Geanakoplos, 2012). This is not surprising, since Istiak and Serletis (2016) claim that the leverage of the shadow banks might increase during economic upturns. However, little is known about the factors which might lead the shadow banks to deleverage their balance sheets during and after the crisis. To fill this gap in the
existing literature, this paper will study the financial institutions which stand for
the shadow banks, and the following research question is examined: Do the fluctuation of asset prices and the change in the institutional environment influence the decisions of firms operating in the shadow banking system (hereafter: “shadow banks”) to deleverage their balance sheets during and after the financial crisis in 2008. The shadow banks investigated in this paper are mainly based on the United States’ market for several reasons. Firstly, the shadow banks in the US occupied around 35% of the global total amount, which is one of the largest markets for the shadow banks in the world. Secondly, as birthplace of the shadow banks, America has the most mature shadow bank system. Thirdly, the financial crisis started first in the US due to the collapse of the subprime mortgage market, and gradually spread to other countries. Therefore, studying the shadow banks in the US is more representative than studying the shadow banks in other countries. The influence of the crisis on the balance sheets of the shadow banks
is also more significant in the US than other nations (De Rezende, 2011).
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1.2 Research structure
The research question at the core of this thesis will make an important contribution to this research area. It helps to figure out what factors influenced the shadow banks’ decisions to deleverage their balance sheets during and after the crisis, which is a crucial step to better understand the role of the shadow banks
in the whole financial system. There are two main findings contributed by this
paper. The first is that the asset tangibility of the shadow banks in the US has a significant impact on the deleveraging of their balance sheets, and that the volatility of asset prices due to the crisis can be reflected in the change in the asset tangibility. The second finding is that the stock market development, which is one of the signs of the change in the institutional environment, has a decisive influence on the deleveraging of the shadow banks as well.
The structure of this thesis is organized as follows: In section 2, which is the literature review, detailed background information on the shadow banks will be given which contains a review of prior studies. Following that, explanations regarding all the potential variables which are taken as the proxies to the fluctuation of asset values and the changes in institutional environment will be shown one by one. The motivations behind the hypotheses will also be stated in this section. In section 3, the procedure of selecting data will be described, and the methodology which is used in the models will be introduced. In section 4, the empirical results and analysis are presented. In the final part, conclusions will be drawn, and suggestions for future research and the limitations of this paper will
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also be stated.
II.
Literature review2.1 Background of the shadow banking system
De Rezende (2011) claims that the size of the shadow banks has evolved to nearly 20 trillion dollars until the pre-crisis period, which was much larger than the debts issued by the traditional banks. The increasing demands of investors for the credit market have resulted in the rapid growth of the shadow banks. The derivatives of the shadow banks are regarded as an alternative option to the traditional demand deposits (De Rezende, 2011).
Debate regarding the relationship between the shadow banks and traditional banks has lasted for a long time (Górnicka, 2016). However, whether as a
complement or as a competitor, there is no doubt that the shadow banks have
always played a crucial part in the capital market which help to enhance the liquidity of the whole market. The shadow banks usually serve as financial intermediaries which contain either entities or activities outside of the regular banking system and traditional regulation (Boghean, 2015). Because the shadow banks are subject to less regulatory scrutiny, these financial intermediaries can often make more profits than traditional banks. Munteanu (2016) explains that transforming the maturity of liquid assets, transferring the credit risk and high financial leverage are three crucial facilities for shadow banks to benefit more from the capital market than the traditional banks. Furthermore, to achieve the
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transformation of maturity of assets, transferring the credit risk and high-leverage operation, derivatives like securitization, collateralization, REPO operations are usually taken by the shadow banks as instruments (Acharya et al., 2013; Munteanu, 2016). What distinguishes the shadow banks from the conventional banks is that the shadow banks are tightly marked to the market and follow its economic paradigm (Boghean, 2015).
2.2 The importance of shadow banks’ leverage ratios
The unpredicted collapse of Lehman Brother during the financial crisis was one of the most shocking events in the financial world, and one that has been widely discussed. As one of the representatives of the shadow banks, the sudden collapse of Lehman Brother made people pay attention to the shadow banking system, which had been ignored by many until then (Fernando et al., 2012).
There are two opposing views about the role of the shadow banks in the financial crisis. The first is that the shadow banks created more risks during the crisis. The underlying assumption is that, because the shadow banks do not have to meet stringent requirements, these financial firms invest in risky assets for excessive returns, which leads to more structural risks to the market (Gennaioli et
al., 2013). The institution-specific operations of the shadow banks such as
transforming the maturity of liquid assets also resulted in the increasing of liquid risk during the economic downturns. There is also the underlying assumption that fewer investors are willing to invest and the traditional banks are less willing to lend during the crisis period. Thus, the lack of long-term support of funds and the
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mismatch between liquid debts and illiquid assets in the balance sheets of shadow banks led to the break of capital chain and amplified the risks in the market during this period (Munteanu, 2016).
The other view is that because shadow banks were willing to take more risks than other institutions during the crisis, they provided a boost for the economy (Fernandez & Wigger, 2016). From this point of view, shadow banks served as an alternative source of financing for investors and helped to meet the market demand for financial services, and improved the imbalance of market (Górnicka,
2016; Fernandez & Wigger, 2016).
Although the two arguments represent different opinions as to the role played by the shadow banks in the crisis, they still have a common assumption that the capital structures of the shadow banks are quite crucial for both the shadow banking system and the stability of the whole financial system (Munteanu, 2016; Fernandez & Wigger, 2016). In total, the way how shadow banks leverage their balance sheets has a significant impact on determining the performance and the role of shadow banks in the whole financial market.
2.3 The fact of deleveraging of shadow banks in the US
Due to the fact that the total amount of loans granted by traditional banks is always restricted by regulation. The traditional banks which raise funds mainly from the depositors and other creditors cannot deleverage massively during a crisis. In contrast, the total amount of loans granted by shadow banks is determined on market conditions. Thus, the amount of shadow bank loans is
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always adjusted actively according to the fluctuation of the capital market (Boghean, 2015). There are two potential reasons why some of the shadow banks chose to deleverage during and after the crisis. On the one hand, the fluctuation of the financial market caused volatility in the asset price (Hassan & Wu, 2015). The shadow banks are sensitive to the asset price. For example, shadow banks will increase the leverage when the asset price goes up in order to trade more derivatives instead of keeping constant leverage ratio. On the contrary, the shadow banks will reduce their economic activities by deleveraging when the asset price goes down for avoiding more losses (Istiak & Serletis, 2016). On the other hand, the changes of the macro environment caused by the negative shock are also related to the adjustment of balance sheets. Istiak and Serletis (2016) show that the leverage of shadow banks is pro-cyclical, which tightly follows the financial market’s changes. Thus, the country-specific variables like inflation growth can reflect the macro environment of the market, and further give the interpretation of the deleveraging of the shadow banks.
2.4 Factors that contribute to the deleveraging of the shadow banks in the US The firm-level variables, which are asset tangibility, growth opportunity, and the firm size, are chosen as the determinants to the deleveraging of the shadow banks. All these three variables are measured by the asset price in different ways. Thus, they can be taken as proper proxies to reflect the fluctuation of the asset (Parsons & Titman, 2009). Annual growth of the inflation rate and the stock market development serve as the institutional variables here which might contribute to
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explaining the adjustment of the balance sheet of the shadow banks (Istiak & Serletis, 2016).
2.4.1 Firm size
Istiak and Serletis (2016) outline the reasons why the leverage ratio of the shadow banks is pro-cyclical and will decline during the crisis. One explanation is that when the economy is in bad shape, bad news will spread rapidly among the investors in the market. This bad news will lead to an increase of tail risk and further reduce the expectations of investors and consumers. Due to the lower expectations, consumers and investors in the market will be less willing to make expenditures, resulting in the decline of the total asset prices. As asset prices decline, the risk of going bankrupt increases. Given this fact, the shadow banks often decide to deleverage their balance sheets (Istiak & Serletis, 2016).
Because larger firms usually hold more marketable securities (Parsons & Titman, 2009), these firms are more likely to go bankrupt during the downturns. Given this fact, larger firms are more likely to deleverage their balance sheets during the crisis. Therefore, if the shadow banks expand their sizes during and after the crisis, the leverage ratio of the shadow banks is still expected to increase. In other words, the firm size is negatively related to the deleveraging of the shadow banks.
Hypothesis 1: Firm size is positively related to the leverage ratio of shadow banks during and after the crisis
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2.4.2 Asset tangibility
Parsons and Titman (2009) claim that the asset tangibility implies the liquidity of assets and further measures the risk of it. High asset tangibility means the reduction of liquidity of assets. Shadow banks usually have more intangible assets compared to the conventional banks for three crucial reasons. The first reason is that holding more intangible assets other than the tangible assets ensures the liquidity of the shadow banks’ assets. During the crisis, the shadow banks can easily trade these liquid assets in order to avoid the financial distress caused by the liquid risk. The second reason is that derivatives like asset-backed securities which are issued by shadow banks need sufficient liquidity of the assets to support them. Lastly, more investors are now willing to invest their cash into the shadow banks. These investments make investors profits in a short time, and increase the liquidity of the shadow banks’ assets (Gennaioli et al., 2013). However, many problems occur when a firm in the shadow banking system has many intangible assets. It is more likely to go bankrupt during the economic downturns because the market values of the intangible assets often decrease significantly, as the market becomes less liquid and investors are less willing to buy assets (Istiak & Serletis, 2016). The debt-equity holder conflicts also increase significantly for firms with many intangible assets during economic downturns. Because the values of these intangible assets are always hard to measure, the claims for the assets are not clear when shadow banks meet financial distress (Parsons & Titman, 2009).
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intangible assets in order to ensure the proper liquidity is essential for the shadow banks during and after the crisis. Gennaioli et al (2013) state that It is better to hold sufficient liquid assets sometimes rather than the tangible assets.
Hypothesis 2: Asset tangibility is negatively related to the leverage ratio of the shadow banks during and after the crisis
2.4.3 Growth opportunity
The growth opportunity of the shadow banks is measured as the ratio of shadow banks’ market value to the total assets. Firms in the shadow banking system are less willing to decrease their derivatives during the crisis if they have relatively high growth opportunity (Kayo & Kimura, 2011). On the one hand, Shadow banks with the higher market value which consists of financial debt and equity market value have better prospects than the shadow banks with relatively low growth opportunity. These firms are more willing to make investments in the future and are more likely to keep the level of financial debt as the source of funds (Parsons & Titman, 2009). On the other hand, the shadow banks usually have more information than non-shadow banking firms, so the managers of the shadow banks with good growth opportunities prefer to maintain financial debt like securities even during the crisis, as the stability of financial debt can work as a signal in order to show their confidence to face with the financial crisis. Moreover, investors will have good expectation for the future development of these firms during the crisis (Boghean, 2015). Therefore, the shadow banks with good growth
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opportunities are less likely to deleverage during the crisis.
Hypothesis 3: Growth opportunity is positively related to the leverage ratio of the shadow banks during and after the crisis
2.4.4 Annual growth of Inflation rate
During the financial crisis, the US government implemented an expansionary monetary policy, which is often referred to as quantitative easing, to stimulate the financial market. This policy of quantitative easing created an oversupply of domestic currency and consequently increased the inflation rate in the US during the crisis. The rising inflation rate during the crisis led to the bubbles in the asset (Istiak & Serletis, 2016). The bubbles in the asset prices further destabilized the capital market. During periods of high inflation, the unemployment rate massively increases, and the purchase power of the currency declines (Alves & Francisco, 2015). Thus, the wealth of investors shrinks. Investors then would like to make investments into the assets which can preserve value, rather than the liquid assets like derivatives issued by the shadow banks (Istiak & Serletis, 2016). Therefore, as the inflation rate increases, the shadow banks often alter their original financing decisions in order to face the insufficient investment into the derivatives (Lewellen & Kracaw, 1987). The expectation is the growth in inflation rate will lead to the decline of leverage ratio of shadow banks.
Hypothesis 4: Inflation rate growth is negatively related to the leverage ratio of the shadow banks during and after the crisis
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2.4.5 Stock market development
On the effect of the growth of the stock market on the firms’ leverage (especially the shadow banks), there exists the intersection between the development of the stock market and the decisions to the leverage of the shadow banks. Kayo and Kimura (2011) define the stock market development as the ratio of the total stock market capitalization to GDP. The ratio of the stock market capitalization to GDP can indicate the development level of the whole capital market. The higher the ratio, the more advanced the capital market is. Therefore,
the innovative financial products issued by the shadow banks enter the capital
market more easily (Kayo & Kimura, 2011).
Hypothesis 5: Stock market development is positively related to the leverage ratio of the shadow banks during and after the crisis
III.
Method, data and sample3.1 Data
In order to examine the research question by estimating the models, the data for three firm-level variables which are asset tangibility, firm size, and growth opportunity are firstly collected from different sources. To be more specific, the data for these three variables are mainly downloaded from DataStream and COMPUSTAT global which is on the WDRS database. The main data sets needed for firm-specific variables are based on the balance sheets of the shadow banks. Thus, some missing data for the firm-level variables are also collected individually
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from the annual reports of the shadow banks (Kayo & Kimura, 2011). The data for the institutional variables which are inflation growth rate and stock market development are downloaded from the World Bank’s World Development Indicators database (Altuntas et al., 2015).
The sample covers the period from 2004 to 2016. I use this sample period to ensure that there are about the same number of observation in the pre- and post-crisis periods in order to compare the effect of these variables on the deleveraging of the shadow banks. The initial sample consists of 431 listed-firms from the US which meet the definition of the shadow banks. The listed firms chosen in the sample include insurance companies, investment banks and other various financial firms (Munteanu, 2016). From this sample, the shadow banks with massive missing data are deleted. Secondly, all firms that are listed in the US, but are headquartered in another country are excluded from the sample. In the end, 170 observations are left after screening
3.2 Sample description
panel A
firm level obs mean std.dev min max
leverage 1000 0.693 0.238 0.005 1.689 Firm size 1000 22.947 2.56 16.869 31.404 growth opportunity 1000 1.202 9.451 0.000 133.479 asset tangibility 1000 0.026 0.053 0.000 0.339 macroeconomic indicator inflation growth 1006 1.938 1.252 -0.365 3.839 stock market development 1006 125.156 22.035 78.746 151.385 Table I: Descriptive statistics Shadow banks which increase leverage (Continued)
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panel B
firm level obs mean std.dev min max
leverage 913 0.645 0.281 0.000 3.656 Firm size 913 22.289 2.359 17.173 28.414 growth opportunity 913 1.141 7.625 0.000 118.377 asset tangibility 913 0.016 0.056 0.000 0.972 macroeconomic indicator inflation growth 913 1.932 1.251 -0.365 3.839 stock market development 913 125.146 22.067 78.746 151.385 panel C
firm level obs mean std.dev min max
leverage 1913 0.670 0.260 0.000 3.656 Firm size 1913 22.633 2.487 16.869 31.404 growth opportunity 1913 1.173 8.625 0.000 133.479 asset tangibility 1913 0.021 0.055 0.000 0.972 macroeconomic indicator inflation growth 1919 1.935 1.251 -0.365 3.839 stock market development 1919 125.151 22.045 78.746 151.385 Shadow banks which decrease leverage Total Note: Table 1 shows the descriptive statistics for three sample sets. Panel A shows statistics for the sample which contains the shadow banks with increasing leverage during the crisis period; Panel B contains the descriptive statistics for the sample with decreasing leverage; Panel C shows the descriptive statistics for the total sample.
Table I presents the summary statistics for the variables. Panel A presents the descriptive statistics for shadow banks with increasing leverage ratio during the crisis. Panel B gives the descriptive statistics for the shadow banks with reduced leverage ratios during the crisis, which is also the main body of the investigation here. Panel C shows the descriptive statistics for the total sample which contains both the shadow banks with increasing leverage and the shadow banks with reduced leverage during the economic downturns.
With the comparison of panel A and panel B, it can be shown that there are 1000 observations for the shadow banks with increasing leverage during and after the crisis, and there are 913 observations for the shadow banks with reduced leverage. Although the main trend for shadow banks is to deleverage during and after the crisis, there are several possible reasons to explain why the observations
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for the shadow banks which deleveraged are less than the observations for increasing leverage ratio (Istiak & Serletis, 2016). Firstly, there exists the problem of lagging. Not all the shadow banks react to the crisis at the same time and take actions to deleverage immediately when the crisis happens. Some of them might take the longer time to adjust their balance sheets to adapt to the sudden shock compared to other shadow banks. However, the time periods chosen by this study is limited, so the comparison of figures based on the limited time periods here is a bit misleading. Secondly, the debt-to-asset ratio of the shadow banks experienced a sharp decline during the crisis and then increased significantly in the following years. Thus, it is possible that the observations with growing leverage during and after crisis are more than the observations with decreasing leverage ratio. The third possible reason is that the data for the observations are all based on the firms’ balance sheets. However, some actions which also contribute to the deleveraging are off-balance which cannot be found from the database (Istiak & Serletis, 2016; Munteanu, 2016).
There are several important findings from the summary statistics. In the panel A, the average for the firm size is 22.947 which is 0.658 higher than the average of the firm size shown in panel B. This result proves that the shadow banks intend to increase their leverage during and after the crisis when the firm size is large enough (Parsons & Titman, 2009). The stock market development in the panel B is less than the result in panel A, which implies that when the development of the capital market slows down, the shadow banks are more willing to deleverage. This
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result proves that the shadow banks are pro-cyclical (Istiak & Serletis, 2016). 3.3 Method
First, the Winsor is run by the STATA for dealing with the outliers in the sample. Then, in order to test the hypotheses, I estimate several versions of the following models which are based on prior studies (Altuntas et al., 2015; Alves & Francisco, 2015).
Based on panel data, seven regression models are structured in the paper for each of the three sample sets:
𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B ∗ 𝐴𝑠𝑠𝑒𝑡 𝑡𝑎𝑛𝑔𝑖𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝜀' (1) 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B ∗ 𝐴𝑠𝑠𝑒𝑡 𝑡𝑎𝑛𝑔𝑖𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽] ∗ firm size ∗ Dummy + 𝜀' （2） 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B ∗ 𝐴𝑠𝑠𝑒𝑡 𝑡𝑎𝑛𝑔𝑖𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽] ∗ asset tangibility ∗ Dummy + 𝜀' (3) 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B ∗ 𝐴𝑠𝑠𝑒𝑡 𝑡𝑎𝑛𝑔𝑖𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽] ∗ growth opportunity ∗ Dummy + 𝜀' (4) 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B∗
Asset tangibility + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽]∗ 𝑔𝑟𝑜𝑤𝑡ℎ 𝑜𝑓 𝑖𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 ∗ Dummy + 𝜀' (5)
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𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B∗
Asset tangibility + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽]∗
𝑠𝑡𝑜𝑐𝑘 𝑚𝑎𝑟𝑘𝑒𝑡 𝑑𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡 ∗ Dummy + 𝜀' (6)
𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',)* 𝛽-+ 𝛽/∗ 𝐷𝑢𝑚𝑚𝑦 + 𝛽5 ∗ 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒 + 𝛽: ∗ 𝐺𝑟𝑜𝑤𝑡ℎ 𝑜𝑝𝑝𝑜𝑟𝑡𝑢𝑛𝑖𝑡𝑦 + 𝛽B∗
Asset tangibility + 𝛽G ∗ growth of inflation rate + 𝛽T ∗ stock market development + 𝛽]∗ 𝑠𝑡𝑜𝑐𝑘 𝑚𝑎𝑟𝑘𝑒𝑡 𝑑𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡 ∗ Dummy + 𝛽h∗ 𝑔𝑟𝑜𝑤𝑡ℎ 𝑜𝑓 𝑖𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 ∗ Dummy + 𝛽i ∗
growth opportunity ∗ Dummy + 𝛽/- ∗ asset tangibility ∗ Dummy + 𝛽// ∗ firm size ∗ Dummy + 𝜀'
(7)
𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒',j is the dependent variable here which is the debt-to-assets ratio
of bank i at the end of year t. The dummy variable is introduced in the models to show the effect of the crisis on the leverage ratios of the shadow banks. Therefore, the dummy is equal to one for years between 2007 and 2016, and zero for all other years. The independent variables contain three firm-level variables and two institutional variables. Three firm variables are chosen because the adjustment of these variables can reflect the fluctuation of the asset prices caused by the crisis.
The firm size is measured as the natural logarithm of total asset. The asset
tangibility is the ratio of fixed asset and the total asset. The ratio of the market value and the total asset is to measure the growth opportunity which is also called market-to-book ratio. The institutional variables are the growth of annual inflation rate and stock market development. For the stock market development, it is calculated as the ratio of total stock market capitalization and GDP.
The method of ordinary least squares (OLS) is applied to the regression models. In order to estimate my hypotheses, I will run seven models in the case of three samples individually. All the samples will be tested under 1%, 5%, and 10%
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significance level separately.
IV.
Result and analysis4.1 Empirical results and analysis
leverage leverage leverage leverage leverage leverage leverage
Firm size 0.050*** 0.055*** 0.051*** 0.050*** 0.051*** 0.051*** 0.056*** (20.300) (9.830) (20.200) (20.300) (20.300) (20.200) (9.370) Dummy 0.004 0.129 0.012 0.004*** -0.246 0.009 -0.113 (0.220) (0.860) (0.550) (0.170) (-1.140) (0.410) (-0.460) growth opportunity 0.000 -0.001 -0.001 -0.003*** -0.001 -0.001 -0.002 (-1.220) (-1.270) (-1.200) (-4.950) (-1.210) (-1.200) (-0.890) asset tangibility -1.210 -1.200*** -0.969 -1.210*** -1.210*** -1.130*** -0.935** (-11.900) (-11.700) (-2.600) (-11.800) (-11.980) (-6.100) (-2.520) inflation growth 0.000 0.000 0.000 0.000 -0.082 0.000 -0.091 (-0.020) (0.000) (0.000) (0.030) (-1.170) (-0.010) (-1.320) stock market development -0.001* -0.001* -0.001* -0.001* -0.001* -0.001* -0.001* (-1.760) (-1.720) (-1.760) (-1.680) (-1.870) (-1.750) (-1.740) Firmsize*Dummy -0.005 -0.007 (-0.880) (-1.020) Assettangibility*Dummy -0.280 -0.235 (-0.730) (-0.550) growthopportunity*Dummy 0.002*** 0.002 (3.100) (0.770) Inflationgrowth*Dummy 0.081 0.091 (1.170) (1.330) stockmarketdevelopment*Dummy -0.066 -0.056 (-0.740) (-0.570) constant -0.327*** 0.430*** 0.338*** -0.331*** -0.075 0.337*** -0.193 (-3.470) (-2.800) (-3.580) (-3.510) (-0.320) (-3.570) (-0.780) *** denotes significance at 1 percent ,** at 5 percent, and * at 10 percent Note: Table 2 describes the regression results for the sample which consists of the shadow banks with increasing leverage ratios during and after the crisis. The firm size, asset tangibility, growth opportunity and the stock market development are statically significant. The main effect of the crisis is shown by the dummy variable, which is only significant in regression 4. The significant interaction variable here is growth opportunity* dummy, which is significant at 1% significance level. Table II Regression for the sample with increasing leverage
Table II shows the regression results for the sample of the shadow banks which decided to increase their leverage ratios during and after the crisis. The results in this table are constructed to contrast with the shadow banks with
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decreasing leverage ratios in order to further explain why some of the shadow banks chose to increase the leverage during the crisis rather than deleveraging. There is a noteworthy finding in table II. The coefficient on the interaction variable (growth opportunity*Dummy) is positive. It is also statistically significant at 1% significance level. This positive and significant coefficient suggests that the reason why some of the shadow banks chose to increase the leverage ratios rather than deleveraging during the crisis can be explained by the growth opportunity. Istiak and Serletis (2016) outline the possible reason for these abnormal observations; that the decline of the asset prices resulting from the financial crisis contributed to the increasing of the market-to-book ratio. The shadow banks with sufficient growth opportunities are more willing to invest for the future even if they are experiencing the downturns (Gennaioli et al., 2012). Moreover, investors show more confidence in the firms with greater growth opportunities (Parsons & Titman, 2009). As one of the proxies of the fluctuation of the asset price during the crisis, the growth opportunity has a significant impact on the shadow banks which decided to increase the leverage during the crisis. This result is consistent with H3, which states that the growth opportunity is positively related to the leverage ratios of the shadow banks during and after the crisis. Due to the fact that no other significant interaction variables except the growth opportunity*Dummy exists, it can be concluded that the only possible reason why some of the shadow banks didn’t choose to deleverage their balance sheets during the crisis is that these firms had greater growth opportunities than other firms as support for them to
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deal with the crisis.
leverage leverage leverage leverage leverage leverage leverage Firm size 0.064*** 0.066*** 0.063*** 0.064*** 0.064*** 0.063*** 0.061*** (16.800) (11.910) (16.500) (16.800) (16.800) (16.600) (10.300) Dummy -0.025 0.013 -0.058*** -0.025 0.028 -0.050*** 0.023 (-1.030) (0.080) (-2.360) (-1.030) (0.130) (-2.080) (0.100) growth opportunity -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001* (-4.540) (-4.560) (-4.700) (-3.170) (-4.530) (-4.710) (-0.960) asset tangibility -0.819*** -0.819*** -3.200*** -0.819*** -0.819*** -2.320*** -3.270** (-3.470) (-3.470) (-4.800) (-3.470) (-3.460) (-6.700) (-4.790) inflation growth 0.004 0.004 0.003 0.004 0.021 0.003 0.051 (0.320) (0.330) (0.270) (0.320) (0.300) (0.280) (0.750) stock market development 0.000 0.000 0.000 0.000 0.000 0.000 0.000 (0.710) (0.730) (-0.640) (0.710) (0.720) (0.540) (0.550) Firm size*Dummy (0.731) 0.003 (0.732) (0.370) asset tangibility*Dummy 2.470*** 1.180 (3.560) (1.530) growth opportunity*Dummy 0.000 0.000 (0.260) (0.250) Inflation growth*Dummy -0.017 -0.048 (-0.250) (-0.720) stock market development*Dummy 0.770*** 0.670*** (5.180) (4.440) constant -0.818*** -0.848*** -0.761*** -0.818*** -0.871*** -0.741*** 0.821*** (-5.230) (-4.840) (-4.850) (-5.220) (-3.290) (-4.740) (-3.230) Table III Regression for the sample with decreasing leverage *** denotes significance at 1 percent ,** at 5 percent, and * at 10 percent Note: Table 3 describes the regression results for the sample which consists of the shadow banks with decreasing leverage ratios during and after the crisis. The observations in this sample are the main body of studying. The firm size, asset tangibility and growth opportunity are statically significant. The main effect of the crisis is shown by the dummy variable, which is significant in regression 3 and 6. The significant interaction variables here are asset tangibility* dummy and the stock market development*dummy. Both of them are significant at 1% significance level.
Table III presents regression results based on the sample of the shadow banks which deleveraged during and after the crisis. The analysis constructed for table III mainly contributes to answering the research question by figuring out which variables might influence the shadow banks’ decisions to deleverage their balance sheets. Firstly, the coefficient on the asset tangibility*dummy is positive and significant at 1% significance level. Although this interaction variable is significant, the coefficient on it shows that the result is not consistent with H2,
21
which states that the asset tangibility has a negative relationship with the leverage ratios of the shadow banks during and after crisis. Istiak & Serletis (2016) state that the total asset prices of the shadow banks shrank during and after crisis, which led to the proportion of fixed assets increasing relatively and the liquidity of shadow banks’ assets decreasing relatively (Fostel & Geanakoplos, 2012). The increasing asset tangibility of the shadow banks during and after the crisis actually mitigated the effect of deleveraging for two reasons. On the one hand, it is difficult for the shadow banks to get enough loans from the market during and after the crisis, and the potential possibility of the breaking of the capital chain exposes the
shadow banks to the risk of bankruptcy like Lehman Brother (Fernando et al.,
2012). During this period, the higher the asset tangibility the shadow bank has,
the more interests for debtholders and shareholders of the shadow banks will be guaranteed, and the proper debts resulting from the innovative finance products are tolerated and admitted (Nersisyan & Dantas, 2017). On the other hand, the extra costs brought by the liquid assets cannot be ignored. The shadow banks reacted to the extra costs by reducing the total debt in their balance sheets during economic downturn (Parsons & Titman, 2009). Although the sufficient liquidity of the assets supports the issuance of the financial innovative products by the shadow banks, the shadow banks focused more on long-term operation by increasing the asset tangibility when they were faced with the crisis. The shadow banks with higher asset tangibility during the crisis had less risk of going bankrupt. These firms were more willing to not deleverage because they have sufficient
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tangible assets as an alternative guarantee to confront the crisis (Gennaioli et al., 2013).
Secondly, the dummy in regression 6 is shown to be significant at 5%
significance level, which proves that the change of the stock market development resulted from the crisis also led the shadow banks to deleverage their balance sheets during and after the crisis. The coefficient on the interaction between the dummy and the stock market development is 0.77, which shows the positive relation between the stock market development and the leverage ratio of the shadow banks during and after the crisis. This result is consistent with H5, which predicts that the stock market development is positively related to the leverage ratios. As Altuntas et al (2015) state, the proxy of the stock market development reflects the development of the capital market. The more advanced the stock
market development is, the more open and tolerant the market is to innovative
financial products. If the ratio of stock market development increases during the economic downturn, it implies that there are still many investors and other institutions active in the financial market, which encourages the shadow banks to keep a relatively high-leverage operation (Alves & Francisco , 2015). Thus, the stock market development is negatively related to the deleveraging of the shadow banks during the crisis.
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leverage leverage leverage leverage leverage leverage leverage
Firm size 0.057*** 0.060*** 0.057*** 0.057*** 0.057*** 0.057*** 0.059*** (25.700) (14.900) (25.600) (25.700) (25.700) (25.700) (14.400) Dummy -0.010 0.063 -0.019 -0.010** -0.120 -0.016 -0.074 (-0.610) (0.560) (-1.180) (-0.640) (-0.780) (-1.000) (-0.430) growth opportunity 0.000 0.000 0.000 -0.001*** 0.000 0.000 -0.001 (-1.230) (-1.250) (-1.240) (-3.330) (-1.230) (-1.230) (-0.920) asset tangibility -0.995*** -0.994*** -1.420*** -0.996*** -0.996*** -1.190*** -1.400*** (-6.280) (-6.290) (-3.840) (-6.280) (-6.280) (-6.560) (-3.780) inflation growth 0.002 0.002 0.002 0.002 -0.034 0.002 -0.034 (0.800) (0.300) (0.250) (0.310) (-0.680) (0.250) (-0.680) stock market development -0.002 0.000 0.000 0.000 0.000 0.000 0.000 (-0.470) (-0.430) (-0.500) (-0.420) (-0.520) (-0.530) (-0.510) Firm size*Dummy -0.003 -0.003 (-0.680) (-0.530) asset tangibility*Dummy 0.466 0.279 (1.160) (0.660) growth opportunity*Dummy 0.001** 0.001 (2.170) (0.770) Inflation growth*Dummy 0.036 0.036 (0.730) (0.730) stock market development*Dummy 0.125 0.097 (1.250) (0.106) constant -0.568*** -0.627*** -0.554*** -0.571*** -0.457*** -0.552*** -0.485*** (-6.330) (-5.350) (-6.190) (-6.360) (-2.580) (-6.200) (-2.670) Table IV Regression for the total sample *** denotes significance at 1 percent ,** at 5 percent, and * at 10 percent Note: Table 4 describes the regression results for the sample which consists of the total shadow banks with both increasing leverage ratios and decreasing leverage ratios during and after the crisis. The firm size, asset tangibility and growth opportunity are statically significant. The main effect of the crisis is shown by the dummy variable, which is significant in regression 4. The significant interaction variable here is growth opportunity* dummy, which is significant at
Table IV shows the results for the total sample. Several conclusions can be drawn from this table. Firstly, the asset tangibility has significant influence on all the shadow banks in the sample regardless of the pre-crisis period or post-crisis period, which is in line with the study of Kayo and Kimura (2011). Secondly, the interaction between the annual growth of the inflation rate and dummy is statistically insignificant, which is not consistent with H4. Thirdly, the interaction between the firm size and the dummy is also statistically insignificant, which is not
24
consistent with H1. The firm size cannot reflect the effect of the crisis on the shadow banks’ deleveraging decisions. Lastly, the coefficient on the growth opportunity*dummy is statistically significant and positive at 5% significance level, which is in line with the regression result in table II.
V.
Robustness tests
The robustness test here is constructed by the different classifications of the data. The first classification method is based on whether the shadow banks choose to deleverage or not. The second classification method is to distinguish the time period for the sample. The model in second classification method consists of the shadow banks with decreasing leverage ratios, and the post-crisis period is chosen instead of using dummy variable to show the effect of the crisis on the deleveraging of the shadow banks. When comparing the table III and the table V, it can be concluded that the significance of the inflation growth rate, asset tangibility, and growth opportunity do not change. The p-value for firm size is less than the significance level (5% here), which is different from the result in the
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table III. The significance of the stock market development also changes when different classification method applied to data.
VI.
ConclusionAs a component of the whole financial system, the importance of the shadow banks to the entire financial system cannot be neglected after the crisis. On the one hand, shadow banks are considered to be the replacement of traditional banks as long-term lenders to the private sector by providing alternative source of lending to investors. On the other hand, derivatives issued by the shadow banks depend on different short-term funding sources which make the shadow banks more vulnerable and fragile to the volatility of the financial market, which might cause more risks to the market. In order to distinguish the role of the shadow banks during the crisis, an investigation to the leverage of shadow banks is necessary (Boghean, 2015). Therefore, the central question has been tested and answered here.
From the results of the models, it can be concluded that firm size, growth opportunity, and asset tangibility all have the significant impacts on the leverage ratio of the shadow banks. However, during and after the crisis, only the asset tangibility which is the proxy of the fluctuation of asset price influences the shadow banks’ decision to deleverage. This result further implies that the liquidity of asset is one of the key determinants for the shadow banks to adjust their leverage ratios during the crisis. If the asset tangibility is too high, there will
26
be a problem of debt-equity holder conflicts. Therefore, a moderate level of the asset tangibility can encourage the shadow banks to serve a better role as an alternative funding source for stabilizing the financial market (Parsons & Titman, 2009). For the two institutional variables, only the stock market development influences the decision of the shadow banks to deleverage. Thus, further strengthening the supervision of the stock market can have a good impact on financial institutions. For example, the reduction of speculation in the stock market can help shadow banks to take more rational decisions on whether to deleverage their balance sheets during the crisis.
There are still several limitations in this paper. Firstly, the data collected is only based on the listed firms from the US. More countries would have to be included in the investigation for a more comprehensive study of the shadow banks. Secondly, the financial firms chosen here only represent a small part of the whole shadow banking system. Future research can focus on the off-balance sheet activities of the shadow banks in order to study the shadow banking system more exhaustively.
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