¹ The effects of the 1930 and subsequent banking crises have been most recently studied by Wicker, Elmus R., “A Reconsideration of the Causes of the Banking Panic of 1930,” this JOURNAL, 40 (09. 1980), pp. 571–83;Google ScholarBernanke, Ben S., “Nonmonetary Effects of the Financial Crisis in the Propagation of the Great Depression,” American Economic Review, 73 (06 1983), 257–76;Google Scholar and Brunner, Karl, ed., The Great Depression Revisred (Boston, 1981).CrossRefGoogle Scholar

² There are a number of problems in determining whether this occurred because there was a substantial shift in the composition of banks' loan and investment portfolios. Commercial loans declined relative to loans on securities and real estate. This was the result of several important events, including the increase in the federal government's debt, the large-scale flotation of foreign securities, and the shift by firms from financing with bank loans to the issue of stock and bonds. Friedman, Milton and Schwartz, Anna J., A Monetary History of the United States, 1867–1960 (Princeton, 1963), pp. 244–45.Google Scholar

³ Friedman and Schwartz, A Monetary History, pp. 246–48.Google Scholar

⁴ Ibid., p. 249.

⁵ Ibid., p. 308. Elmus Wicker has revealed that many failures were related to the collapse of CaIdwell and Company of Nashville, Tennessee. This firm had recently created a fragile financial empire including many banks across the South. The failure of Caldwell and Company in November of 1930 caused a run on its banks. Wicker, “A Reconsideration,” p. 572.

⁶ Temin, Peter, Did Monetary Forces Cause the Great Depression? (New York, 1976), pp. 106–07.Google Scholar Temin's sample is apparently dominated by very low grade bonds, and this led Mayer to criticize Temin's results. Mayer, Thomas, “Money and the Great Depression: A Critique of Professor Temin's Thesis,” Explorations in Economic History, 15 (1978), 136–37. This criticism may be unjust, as many banks appear, as will be shown, to have held such bonds.CrossRefGoogle Scholar

⁷ Temin, Monetary Forces, pp. 87–90.Google Scholar

⁸ Mayer, “A Critique,” 144.Google Scholar

⁹ The Comptroller reported bank suspensions. A bank suspension occurs when a bank is temporarily or permanently closed by the supervisory authority or board of directors. A failure occurs when receivers are appointed to take control of the bank and dissolve it. Suspended banks that reopened were excluded. These represented only a small number of all suspended banks.Google Scholar

¹⁰ These rates were calculated with data from the Federal Reserve Bulletin (September. 1937), pp. 907–09. The small number of failing private and mutual savings banks were excluded here. Suspending national banks had 19.5 percent, state member banks of the Federal Reserve, 31.8 percent, and nonmember state banks, 48.7 percent of deposits in all suspended banks.Google Scholar

¹¹ See, White, Eugene Nelson, The Regulation and Reform of the American Banking System, 1900–1929 (Princeton, 1983), pp. 138–40.Google Scholar

¹² The coefficient of correlation is 0.885. Bank failure rates were measured as the number of failures in the year divided by the number of banks on June 30, 1930. The data were taken from the Comptroller of the Currency's Annual Report (Washington, D.C., 1931), pp. 707–20.Google Scholar

¹³ There were 192 observations for 1930, half being failures. In 1929. 1928 and 1927, 18, 21, and 17 banks failed out of a total of 70, 87 and 60 observations. This sampling of non-failing banks was used rather than an unstratefied nationwide random sample. The size and portfolio composition of a rural bank in Iowa or Kansas was usually quite different from that of a New York or a Chicago bank. The Comptroller's data give broad categories of assets and liabilities. Without more detailed balance sheet information, comparison of a failing rural bank with a surviving city bank could be very misleading. The approach used here is similiar to that employed by Sinkey, Joseph F. Jr, Problem and Failed Institutions in the Commercial Banking Industry (Greenwich, Connecticut, 1979), p. 93.Google Scholar

¹⁴ Ibid., p. 93.

¹⁵ The SAS logit program was used. The maximum likelihood estimates were computed by the Newton-Raphson method.Google Scholar

¹⁶ The estimated coefficients, B, were calculated from where are the logit MLEs for the principal components and P is the matrix of eigenvectors. The estimated standard errors were obtained from the variance-covariance matrix V(B) = PV ()P′, where V() is the corresponding matrix for the principal component estimates.Google Scholar

¹⁷ This test is equal to -2{L(B) -L(B₀)}, where L(B) is the log of the likelihood function where all the explanatory variables are included and L(B₀) is the log of the likelihood function with only the intercept. This is asymptotically distributed as chi-square. Judge, George G., et al. , The Theory and Practice of Econometrics (New York, 1978), pp. 600–01.Google Scholar

¹⁸ Johnson, H. Thomas, “Postwar Optimism and the Rural Financial Crisis of the 1920s,” Explorations in Economic History, 11 (Winter 1973/1974), 173–74.Google Scholar

¹⁹ Wiecking, E. H., The Farm Real Estate Situation. 1929–1930. Department of Agriculture, Circular No. 150 (Washington, D.C., 11. 1930). pp. 1–13.Google Scholar

²⁰ Popple, Charles Sterling, Development of Two Bank Groups in the Central Northwest (Cambridge, Massachusetts, 1944), p. 105.CrossRefGoogle Scholar

²¹ Meltzer, Allan H., “Monetary and Other Explanations of the Start of the Great Depression,” Journal of Monetary Economics, 2 (1976), 455–71.CrossRefGoogle Scholar

²² The price index of farm goods which had fluctuated little in the late 1920s fell from 58 in 1929 to 49 in 1930 (1967 = 100). Farm incomes fell from $6,152 million to $4,259 million. U.S. Bureau of Census, Historical Statistics of the United States, Colonial Times to 1970 (Washington, D.C., 1975), Vol. 1, p. 483, Series K259, and p. 489, Series K344.Google Scholar

²³ Although information does not exist for individual banks, the increase in defaults and slow payments can be seen in the data for all national banks. For the six-month period ending December 31, 1929. losses on loans and discounts totalled $54 million. Between July I and December 30, 1930, this rose to $85 million, while gross earnings on loans and discounts fell from $475 million to $401 million. Comptroller of the Currency, Annual Report (1930), pp. 695–96, 946–47.Google Scholar

²⁴ Trescott, Paul B., “Federal Reserve Policy in the Great Contraction: A Counterfactual Assessment,” Explorations in Economic History, 19 (07 1982), 211–20.CrossRefGoogle Scholar

²⁵ Wiecking, Farm Real Estate, pp. 62–64.Google Scholar

²⁶ It may be a fairly accurate measure if banks tended to sell only those bonds that would pay close to their book value, minimizing any losses and held depreciated bonds in the hope that they would receive their book value in the future.Google Scholar

²⁷ Friedman and Schwartz, A Monetary History, p. 246. Latin American bonds were all purchased after 1928 and apparently suffered a large decline in value.Google Scholar

²⁸ There is no simple explanation for why this difference existed; however, national banks had been accustomed to holding U.S. bonds as backing for national banknotes and may have preferred to hold them to use for discounting at the Federal Reserve banks.Google Scholar

²⁹ Popple, Development of Two Bank Groups, pp. 102–03.Google Scholar

³⁰ Rodkey, Robert G., State Bank Failures in Michigan, Michigan Business Studies, Vol 7, No. 2 (Ann Arbor, 1935), p. 132.Google Scholar

³¹ Carl Gambs found that branching did not significantly reduce failures across states, but his test was a weak one owing to the fact that branching, even on a limited basis, was established in few states. Where it did exist there were other factors that also reduced failures. Gambs, Carl M., “Bank Failures—An Historical Perspective,” Federal Reserve Bank of Kansas City, Monthly Review (June 1977), 16–19.Google Scholar

³² Friedman and Schwartz, A Monetary History, p. 354. Friedman and Schwartz discuss the factors affecting the depression in Canada, but they do not draw the comparison between the two banking systems.Google Scholar

³³ Urquhart, M. C. and Buckley, K. A. H., Historical Statistics of Canada (Cambridge, 1965), p. 246Google Scholar, Series H289-H294, and U.S. Bureau of Census, Historical Statistics, p. 1037, Series X733. This does not imply that Canadians had access to fewer banking services. One, albeit imperfect measure of services, the number of persons per banking office, was approximately 1800 for Canada and 3500 for the United States in 1920. Beckhart, Benjamin H., “The Banking System of Canada,”Google Scholar in Beckhart, B. H. and Willis, H. Parker, Foreign Banking Systems (New York, 1929), p. 364.Google Scholar

³⁴ Jamieson, A. B., Chartered Banking in Canada (Toronto, 1953), p. 54.Google Scholar

³⁵ Board of Governors of the Federal Reserve System, Banking and Monetary Statistics, 1914–1941. (Washington, D.C., 1943), pp. 52–53.Google Scholar

³⁶ Calculated from Urquhart and Buckley, Historical Statistics, p. 246. In addition, seven weak banks were absorbed by stronger firms. This was an orderly process that had evolved in Canada whereby the relatively small number of banks recognized the importance of maintaining public confidence in the banking system and often took over troubled institutions rather than panic the public. The functioning of this informal system of mutual insurance is described in White, Regulation and Reform, Ch. 4.Google Scholar

³⁷ Calculated from U.S. Bureau of Census, Historical Statistics, Vol 1, p. 1035, Series X717.Google Scholar

³⁸ Marcus, Edward, Canada and the International Business Cycle, 1927–1933 (New York, 1954), pp. 11–17.Google Scholar and Safarian, A. E., The Canadian Economy in the Great Depression (Toronto, 1959), pp. 44–54.Google Scholar

³⁹ Morrison, George R., Liquidity Preferences of Commercial Banks (Chicago, 1966), pp. 74–75.Google Scholar

⁴⁰ The likelihood ratio test used here is , where L(B) is the log of the likelihood function when the data for all years are combined and Σ L(B_i) is the sum of the log of the likelihood functions for each year estimated individually. The degrees of freedom for this asymptotic chi-square test are equal to the number of constraints. See. Amemiya, Takeshi, “Quantitative Response Models: A Survey,” Journal of Economic Literature, 19 (12. 1981), pp. 1498, 1505.Google Scholar

⁴¹ Westin, Richard B., “Prediction from Binary Choice Models,” Journal of Econometrics, 2 (1974), 12–14. This test requires the selection of some arbitrary probability, z, so that a bank is classified as failing or non-failing depending on whether its predicted probability, p, is greater or less than this value. The proportion of correctly identified banks in P(C) where and the 95 percent confidence interval is where n is the number of observations. In selecting z, it seems appropriate here to use the approach of the Federal Deposit Insurance Corporation, which is willing to misclassify sound banks to ensure that most problem banks are correctly identified. This implies picking some arbitrarily low z. This differs from the usual choice of 0.5 which implies no prior information or preferences. The value 0.25 was chosen and performed well under the FDIC criterion for identifying banks.CrossRefGoogle Scholar

⁴² There were 210 observations for 1931 and 194 observations for 1932, half of each being failures.Google Scholar

⁴³ Temin, Monetary Forces, pp. 91–92.Google Scholar Other urban banks were also brought to grief by heavy investments in real estate. In Chicago, many banks outside the Loop were hurt not only by the financing of many questionable local real estate projects but also by the sale of mortgages and mortgage bonds to the public with repurchase provisions. When the value of these assets declined, banks were obliged to buy them back. This source of weakness would not have been evident from an examination of their balance sheets. James, Cyril F., The Growth of Chicago Banks (New York, 1938), p. 993.Google Scholar

⁴⁴ Boughton, James M. and Wicker, Elmus R., “The Behavior of the Currency Deposit Ratio During the Great Depression,” Journal of Money, Credit, and Banking, 11 (11. 1979), p. 415.CrossRefGoogle Scholar

⁴⁵ Wicker, Elmus R., “Interest Rate and Expenditure Effects of the Banking Panic of 1930,” Explorations in Economic History, 19 (10. 1982), 435–45.CrossRefGoogle Scholar

⁴⁶ See Friedman and Schwartz, A Monetary History, Ch. 7,Google Scholar and Wicker, Elmus R., Federal Reserve Monetary Policy, 1917–1933 (New York, 1966), Chs. 10 and 11.Google Scholar

⁴⁷ Friedman and Schwartz, A Monetary History, p. 270.Google Scholar

⁴⁸ Ibid., p. 358.

⁴⁹ White, Regulation and Reform, pp. 152–65.Google Scholar