Consolidation in the U.S. Banking Industry: Is the “Long, Strange Trip” About to End?

Jones, Kevin; Critchfield, Tim

doi:10.1016/b978-044451558-2.50017-9

Cited by 27 publications

(21 citation statements)

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“…Most previous studies of the evolution of the US banking industry focus on banks, rather than BHC (Berger et al, 1995;Jones and Critchfield, 2005). In part this is because many price and non-price decisions are taken at bank level.…”

Section: The Size Distribution Of Us Banksmentioning

confidence: 99%

“…Panels A and B report an analysis in which commercial banks are the units of observation, disregarding ownership. Accordingly, in the 'all commercial banks' population, commercial banks that are constituents of the same BHC are treated as separate observations.Most previous studies of the evolution of the US banking industry focus on banks, rather than BHC (Berger et al, 1995;Jones and Critchfield, 2005). In part this is because many price and non-price decisions are taken at bank level.…”

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confidence: 99%

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The Size Distribution of US Banks and Credit Unions

Goddard

Hong

McKillop

et al. 2014

International Journal of the Economics of Business

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This study examines the firm size distribution of US banks and credit unions. A truncated lognormal distribution describes the size distribution, measured using assets data, of a large population of small, community-based commercial banks. The size distribution of a smaller but increasingly dominant cohort of large banks, which operate a high-volume low-cost retail banking model, exhibits power-law behaviour. There is a progressive increase in skewness over time, and Zipf's Law is rejected as a descriptor of the size distribution in the upper tail. By contrast, the asset size distribution of the population of credit unions conforms closely to the lognormal distribution. JEL Classification: G21; L10; L16Keywords: Firm Size distribution, Zipf's Law, Gibrat's Law, Banks, Credit Unions __________________________________________________________________________ + The authors gratefully acknowledge the helpful comments of two anonymous referees on an earlier draft of this paper. The usual disclaimer applies. IntroductionThis study examines the empirical size distribution of US banks and credit unions. It is well known that most empirical firm-size distributions are highly skewed. If firm sizes are subject to proportional random growth, consistent with Gibrat's Law so that log sizes follow random walks, a lognormal cross-sectional firm-size distribution emerges over time (Gibrat, 1931;Sutton, 1997). There is, however, extensive evidence that the lognormal provides a poor approximation to empirical firm-size distributions in the upper tail, which typically exhibit greater skewness than is consistent with lognormality. Certain modifications toGibrat's Law, however, are capable of producing a cross-sectional size distribution that exhibits power-law behaviour. i A strand in the empirical literature examines the application of lognormal and power-law distributions to cross-sectional firm-size data (Simon and Bonnini, 1958;Quandt, 1966;Lucas, 1978;Cabral and Mata, 2003).Pareto (1897) describes the distribution of a collection of N subjects ranked by size, where the density function, denoted f( ), obeys a power law in the upper tail:where X is size,  is the size threshold above which the Pareto distribution applies, and  is constant. Zipf's Law describes the special case =1 (Zipf, 1949 Estimation MethodLet X i denote the assets of firm i in a particular year, and let x i =ln(X i ). Let X [i] denote the value of the i'th observation when the firms are ranked in descending order of asset size,, and let x [i] =ln(X [i] ). Let  k = X [k] denote some threshold value of k that is, initially, assumed to be pre-selected, and let  k = x [k] .We examine two candidate distributions for X i : , where  is the standard normal density function.For (ii), the likelihood function that would be formed over the two segments of the distribution is discontinuous at the truncation point  k . Accordingly, we estimate the parameters  k , 2 k  , k,  k and  k in two stages. Stage 1and sample variance of allwhere  is the sta...

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Section: The Size Distribution Of Us Banksmentioning

confidence: 99%

mentioning

confidence: 99%

The Size Distribution of US Banks and Credit Unions

Goddard

Hong

McKillop

et al. 2014

International Journal of the Economics of Business

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“…These changes, and particularly those related to the permission of interstate branching and combinations of banks, securities firms, and insurance companies, stimulated the decade-long consolidation in the industry characterized by the dramatic rise in merger and acquisition activities, the rapid decline in the number of commercial banks and the increasing concentration of industry assets among the very large banks (see Jones and Critchfield, 2005). On the other hand, various innovations in technology and applied finance were widespread and intensively adopted by the US banking industry.…”

Section: Introductionmentioning

confidence: 99%

Efficiency and productivity of the US banking industry, 1998–2005: evidence from the Fourier cost function satisfying global regularity conditions

Feng

Serletis

2008

J of Applied Econometrics

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SUMMARYThis paper provides estimates of bank efficiency and productivity in the United States, over the period from 1998 to 2005, using (for the first time) the globally flexible Fourier cost functional form, as originally proposed by Gallant (1982), and estimated subject to global theoretical regularity conditions, using procedures suggested by Gallant and Golub (1984). We find that failure to incorporate monotonicity and curvature into the estimation results in mismeasured magnitudes of cost efficiency and misleading rankings of individual banks in terms of cost efficiency. We also find that the largest two subgroups (with assets greater than 1 billion in 1998 dollars) are less efficient than the other subgroups and that the largest four bank subgroups (with assets greater than $400 million) experienced significant productivity gains and the smallest eight subgroups experienced insignificant productivity gains or even productivity losses.

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“…Banks consolidations are effected with the intent of building a banking industry that is strong, technological advanced, efficient in service delivery, capable of generating high level of profit, adequately positioned for competition and globalization (Adegbaju and Olokoyo, 2008). Over the last few decades, studies tend to be more concerned with the impact created by banks' consolidation (Jones and Critchfield, 2005). One area that has received the attention of scholars in bank consolidation is competition.…”

Section: Literature Reviewmentioning

confidence: 99%

Banking Sector Capitalization and Deposit Money Banks’ Profitability in Nigeria

Konboye

Nteegah

2016

Int J Soc Sci Mgt

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The incessant bank distress coupled with the poor financial intermediation capacity of the banking sector has been identified as the main problems of the banking subsector in Nigeria. This underscores the continue quest for increase capital base of banks as possible remedy to these problems. This development makes it imperative for us to examine how capitalization has affected banks profitability in Nigeria. To achieve our objectives, both panel and Partial Frontier efficiency analyses were utilized in this investigation. Using gross profits of 18 DMBs as dependent variable while capital base of DMBs, real income (GDP), financial deepening, interest rate and inflation rate are independent variables, we found that: capitalization has a significant impact on profitability of banks, while financial development, real income level were found to had contributed less to profitability of banks in Nigeria. It was further discovered that, interest rate has less implication on the profitability, while the impact of inflation on profitability of banks was positively but insignificantly. We also found that 58 % of the total variation in profitability is influenced by capital base, financial deepening, interest rate, GDP and price level in Nigeria over the period. The study further revealed that impact of capitalization on profitability of banks is the same across the banks. Finally, using the partial efficiency frontier analysis, we found that Unity Bank and UBA performed better with improved capital base while Union and Heritage Banks performed abysmally with high capital base given the very low efficiency scores. Based on these findings, the study recommends; periodic upward review of capital base of banks, stable macroeconomic policy, and creating enabling environment for investments as ways of enhancing an efficient financial sector and growth of the Nigerian economy.

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Consolidation in the U.S. Banking Industry: Is the “Long, Strange Trip” About to End?

Cited by 27 publications

References 70 publications

The Size Distribution of US Banks and Credit Unions

The Size Distribution of US Banks and Credit Unions

Efficiency and productivity of the US banking industry, 1998–2005: evidence from the Fourier cost function satisfying global regularity conditions

Banking Sector Capitalization and Deposit Money Banks’ Profitability in Nigeria

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