Volatility in US bank credit series

Bank credit and business loans are two of the most important variables in financial markets and the macroeconomy. The time-series properties of these two series are investigated in this paper. The Federal Reserve tracks both credit variable in two series: bank credit and commercial and industrial loans. Both variables are found to display heteroskedastic variance. The findings here are important for modelling and forecasting bank credit and business loans, as well as for developing theoretical models that incorporate bank credit and business loans. Keyword: Credit, volatility, ARCH, GARCH, macroeconomy Copyright statement: Authors retain the copyright to the manuscripts published in AABRI journals. Please see the AABRI Copyright Policy at http://www.aabri. com/copyright.html 213370 – Journal of Finance and Accountancy Volatility in US bank credit series INTRODUCTION Nearly 900 US chartered banks report balance sheet data to the Federal Reserve on a weekly basis. The Federal Reserve then adjusts the data to control for large nonbank activity and off-balance-sheet activity. One of the biggest drivers of the economic activity is credit. The Federal Reserve follows credit data closely in the economy and rightfully so, since the largest and most punitive recessions in the United States (US) economy have all started with problems in the credit markets. The Great Depression started with a banking crisis and the Financial Crisis of 20072009 began with problems in the subprime mortgage market that soon spilled over into banking sector in general. Credit itself, however, is not a simple variable; there are numerous types of credit. Two credit variables that are closely followed by market participants are bank credit and commercial and business loans. This paper examines these series in a time-series framework. Specifically, the volatility of these series is the area of major concern. Some data exhibit volatility clustering where periods of calmness are coupled with turbulence. This type of variance makes it difficult to study and forecast these types of series. While both of these credit variables are important, most of the studies conducted on bank credit and commercial and industrial loans do not look at the volatility of these series. These studies tend to be theoretical or they are conducted to determine the importance of bank credit on other variables. Here the bank credit and commercial and industrial loan series are examined with respect to their variance. The findings suggest that both series exhibit heteroskedastic variance, or volatility clustering. These findings are important. For modelling and for forecasting it is crucial to understand the behavior of the variance of a series. This finding could also help in theoretical models of credit. For example, any theoretical model of bank credit would have to incorporate the different behaviors of the variance seen in these series in order to describe the volatility clustering properly. This result contributes to the literature by suggesting that while many macroeconomic studies use a one-size-fits-all cookie cutter approach to credit, a more detailed specification is necessary. In section 2, a background on the credit series is given as well as a statement of the hypotheses to be tested. Section 3 describes the data used in this paper and section 4 looks at the time series properties of the data. The methodology used here are described in section 5. In section 6 the results are given and section 7 concludes. BANK CREDIT AND COMMERCIAL AND INDUSTRIAL LOANS Bank credit includes Treasury securities as well as securities issued by other US government agencies; it includes mortgage-backed securities issued by US government agencies or enterprises sponsored by the US government (Government National Mortgage Association, Federal National Mortgage Association, and Federal Home Loan Mortgage Corporation); it 1 Large, as per the Federal Reserve, is defined as over $5 billion. 2 For an overview of the Great Depression, see Bernanke (1983); for the Financial Crisis of 2007-2008, see Cecchetti (2009). 3 For examples of these, see Orr and Mellon (1961), Rajan (1994), Dell’Ariccia and Marquez (2004), Hirtle (2009) and Gorton and He (2008). 4 See Heath (2018). 213370 – Journal of Finance and Accountancy Volatility in US bank credit series includes loans and leases in bank credit, but not loans to commercial banks nor federal funds bought or sold. Commercial and industrial loans are loans made to businesses. It is usually backed by collateral and short-term. They are very important for small businesses. Both of these series are thought to be pro-cyclical. In this paper, the variance associated with these credit series is examined and compared. Specifically, the three hypotheses to be tested are: H1: Bank credit exhibits homoskedastic variance. H2: Commercial and industrial loan series exhibits homoskedastic variance. H3: These credit series exhibit the same type of variance. The literature does not provide any expectations as to what one would expect from the variance of these series. Gorton and He (2008) and De Soto (2006) look at credit cycles using bank credit. Mulligan (2005) look at commercial and industrial loans as to how they relate to the business cycle. Melitz and Pardue (1973) look at the demand and supply of commercial bank loans. While these papers might be helpful in modelling bank credit and commercial and industrial credit as well as answering the question of how these two series behavior compares, they do not look at the macroeconomic time series properties of these series. The goal of this study is simply to explore the volatility of these series so that forecasters, analysts, and theorists can incorporate these findings in their work.