Bank Consolidation and Small Business Lending: The Role of 

Community Banks 

Working Paper 2003-05 

Robert B. Avery and Katherine A. Samolyk* 

October 2003 

JEL Classification Codes: L1, L4, G2 

* Contact information: Robert B. Avery, Federal Reserve Board of Governors, Washington DC 20551, (202)-452-2906, 

ravery@frb.gov; Katherine A. Samolyk, Federal Deposit Insurance Corporation, 550 17th St NW, Washington DC 20429, 

(202)-898-3655, ksamolyk@fdic.gov. The views stated here are those of the authors and do not necessarily reflect those of 

the Federal Deposit Insurance Corporation, the Board of Governors of the Federal Reserve System, or their staffs. We would 

like to thank the following for helpful comments and suggestions on this paper and an earlier paper that uses the same basic 

methodology: participants (particularly Craig Furfine) in seminars presented at the FDIC, the Federal Reserve Board, the 

Basel Committee Workshop on Bank Supervision, and the Federal Reserve Bank of Chicago “Whither the Community 

Bank” Conference; Tim Critchfield, Rich Rosen; Bob DeYoung; and two anonymous referees. 

1 
Bank Consolidation and Small Business Lending: 

The Role of Community Banks 

Robert B. Avery and Katherine A. Samolyk 

Abstract 

This paper examines how bank merger and acquisition activity affected small business lending 

in local U.S. banking markets between 1994 and 2000, focusing particularly on the role that 

community banks played in determining the ultimate effects of consolidation. During the 

1994–1997 period, we find evidence that consolidation activity involving big banks was 

associated with lower loan growth, whereas community bank consolidations and a greater 

presence of community banks in the market were associated with higher loan growth. During 

the 1997–2000 period, consolidation activity was either unrelated to small business loan 

growth or associated with higher loan growth, suggesting that the dynamics of consolidation 

activity had changed. In both periods, we find evidence that consolidation presented an 

opportunity for community banks. Once adjustments are made for reclassifications in the size 

category of organizations due to consolidation or asset growth, we find that the share of small 

business lending funded by community banks rose during both study periods—particularly in 

markets undergoing consolidation. 

JEL Classification Codes: L1, L4, G2 

2 
The U.S. banking industry has undergone a substantial consolidation over the past decade, 

raising questions about the viability of the traditional community bank. Concerns have been 

raised that community banks may not be able to compete effectively against larger organizations 

enjoying the benefits of scale economies in product offerings and cost savings. On the other 

hand, consolidation may also offer opportunities for community banks to take on business 

abandoned by large consolidating organizations. Small business lending is thought to be the area 

in which community banks are most likely to have these niche opportunities because such 

lending is both less likely to evidence economies of scale and more likely to benefit from a local 

presence. 

In this paper we provide evidence addressing the appropriateness of these concerns. We 

study how consolidation activity has been related to changes in small business lending in local 

banking markets and examine whether the presence of community banks in a market can be a 

mitigating factor in offsetting contractions in small business lending that might otherwise take 

place as a result of consolidation. Although the question of the survival of community banks is 

of interest to those concerned about industry structure, the potential loss of valuable products and 

services is the more important social issue. If community banks can be shown to provide 

services and products that would otherwise be lost in consolidation, efforts to ensure their 

survival would be socially appropriate. 

The link between community banking and small business lending has long been 

recognized. Traditionally, this type of lending has been local in nature—often to firms having 

idiosyncratic credit needs and risks tied to the prospects of the local economy. Thus, small 

business lending has generally required the local expertise that personifies the community bank 

in terms of underwriting and monitoring firm-specific risks. Indeed, smaller business borrowers 

3 
 

can find it difficult to obtain credit from lenders that do not have a local presence. This is less 

the case for other bank borrowers. Large commercial borrowers deal with large banks that 

operate in numerous markets and often syndicate loans to share the risks. Even lending to 

households in the form of consumer credit or home mortgages has evolved into increasingly 

standardized products transacted in what have become national markets. These types of loans 

require product-specific expertise, but they do not require the same sort of local presence as 

lending to small businesses. 

The extent to which small business lending suits the inherently more local focus of 

community banks is borne out in general trends evident from 1994 through 2000 (see table 1). 

Community banks continue to hold a disproportionately large share of small business loans, 

compared with their share of total banking-industry assets.1

 However, the community bank share 

of small business loans has been declining—particularly the share of small business loans under 

$100,000 (although, as we argue below, these figures are deceptive). Consolidation is also 

evident during the 1994–2000 period. From mid-1994 through mid-2000, 2,870 of an original 

10,341 banking organizations were consolidated through unaffiliated mergers and acquisitions, 

41 were liquidated, and 864 new institutions were formed. Much of the consolidation of this 

period was driven by the relaxation of geographic banking restrictions, as banks sought to extend 

their geographic scope to other states and regions. By mid-2000, over 30 percent of banking 

institution deposits were in offices located in states other than where the organization was 

headquartered, a percentage that had more than doubled since 1991. 

1

 Here and throughout this paper, we define community banks as independent commercial banks or savings 

institutions or bank or thrift holding companies that control less than $1 billion in assets (in 2000 dollars). 

4 
 

The traditional comparative advantage of community banks as small business lenders 

suggests that what happens in this product area will be critical in determining the impact of bank 

consolidation on the future of community banking. It also suggests that the presence (or potential 

for entry) of community banks may play an important role in determining the impact of 

consolidation on small business lending. Although a fair amount of research has addressed the 

impact of consolidation on banking institutions, little of it has focused specifically on community 

banks. Furthermore, there is almost no research that has looked at the question at a market level. 

Much of the reason for this omission is probably limitations in data. Balance-sheet data on a 

bank’s outstanding small business loans (business loans of less than $1 million at origination) 

have been reported by commercial banks and thrifts since 1993. However, geographic data on 

small business loan originations are reported only by the largest banking institutions, and only 

since 1996.2

 These limitations represent significant hurdles to constructing reliable market-level 

estimates of small business lending. 

In this study, we examine the relationships between the amount and types of 

consolidation activity in local banking markets and changes in inflation-adjusted small business 

lending between 1994 and 2000.3 We deal with the limitations of balance-sheet small business 

loan data by using deposit data reported by banking institutions to impute the geographic 

distribution of each institution’s small business lending. We use these geographic loan estimates 

to examine three interrelated questions: (1) How local consolidation activity (referring to 

2

 Samolyk and Richardson (2003) discuss issues involved in using these data, which are collected under the auspices 

of the Community Reinvestment Act (CRA). 

3

 Although the data on small business loans are available for 1993, we choose not to use these early data because of 

concerns about reporting problems associated with them. 

5 
acquisitions of previously unaffiliated banking institutions or holding companies by other 

independent banks or holding companies) is related to market-level changes in small business 

lending, (2) how the presence of community banks affects the impact of consolidation activity on 

local small business loan markets, and finally (3) how consolidation has affected community 

banks’ role as small business lenders. To better understand the dynamics of observed 

relationships, we study overall changes in small business lending as well as its decomposition 

into loan subproducts, as illustrated in table 1. Because of inherent differences in the 

characteristics and economic environments of urban and rural markets, we conduct separate 

analyses of them for two different study periods: 1994–1997 and 1997–2000. 

By way of preview, in the 1994–1997 study period we find mixed evidence on the 

relationship between bank consolidation and small business lending, with the outcome depending 

critically on the role of community banks. Consolidations involving big banking organizations 

are associated with lower real small business loan growth, whereas consolidations involving only 

community banks are associated with higher loan growth. Furthermore, in markets where 

community banks have a large ex ante market share, we find that the negative effects of 

consolidation activity are mitigated. The 1997–2000 study period reveals quite different 

patterns. In urban markets, consolidation activity involving big banking organizations is 

associated with higher small business loan growth primarily in loans of less than $100,000 and in 

commercial and industrial (C&I) lending. In rural markets, we also find positive effects of big 

bank consolidation activity, but in a different product area—commercial real estate (CRE) 

lending. In both urban and rural markets, we find little evidence that the degree of community 

bank presence influenced the impact of consolidation on small business lending during the 1997– 

2000 study period. 

6 
In both study periods, our analysis indicates that consolidation presented an opportunity 

for community banks. Uniformly, once adjustments are made for economic factors and for 

reclassifications in the size category of organizations due to consolidation or asset growth, we 

find that the small business loan market share of community banks increased. Further, the 

increases in market share tended to be greater in markets undergoing consolidation. These 

patterns are evident for total small business lending as well as for the various small business loan 

subproducts that we study. 

The remainder of this article is organized as follows: The next section outlines the 

conjectures about how bank consolidation affects small business lending, summarizes the 

evidence regarding these conjectures, and relates this evidence to our study. Section 2 describes 

the methodology and the data used for our analysis. Section 3 presents our statistical tests and 

test results. Section 4 reports estimates that decompose small business loan growth and changes 

in community bank small business loan market shares into consolidation-related changes and 

offsetting effects by other firms in the market. Section 5 presents a discussion of robustness 

issues and section 6 concludes. 

1. RELATED LITERATURE 

The goals of this paper are to quantify the relationship between bank consolidation and 

small business lending at the market level and to determine whether the presence of community 

banks influences the relationship. In this section we review evidence and conjectures from the 

literature regarding these questions. Because much of the existing literature has focused on 

evidence at the bank level, we pay particular attention to the few studies that have conducted 

7 
market-level analyses. We also emphasize evidence on the role of bank size in determining the 

impact of consolidation. 

One argument advanced in the literature is that since the commercial loans made by 

smaller banks tend to be smaller and more local (because of legal loan limits or the need to 

diversify across borrowers), smaller institutions are more likely to develop an expertise as small 

business “relationship lenders.” Larger banks are viewed as inherently better suited to operating 

in a more standardized fashion, incurring higher fixed costs that can be spread out over a broader 

customer base. Therefore, as banks get larger and more organizationally complex, their focus 

shifts to larger commercial credits or more standardized types of loan products (Berger and 

Udell, 1998). This view implies that as banking institutions merge into larger organizations, they 

are likely to reduce the share of their portfolio that funds “relationship-intensive” small business 

loans. 

It has been argued that larger banks are likely to be more efficient lenders, not only 

because their scale may allow them to lower certain costs but also because they can better 

diversify their portfolios and therefore expand their lending to all customers, including small 

businesses (Strahan and Weston, 1998; Morgan and Samolyk, 2003). Hence, as institutions 

become larger, they may be able to make more loans in general, including more small business 

loans. 

Evidence from studies of bank efficiency and mergers suggests that benefits from 

increased scale are likely to be a feature only of mergers among relatively small institutions— 

community banks as we have defined them here. And although larger banks may be better able 

to use new small business lending technologies (such as credit scoring models) than their smaller 

counterparts, small business loans that are too large or too information intensive (such as 

8 
 

collateralized loans) have not proven to be well suited to credit scoring methods. Thus, because 

consolidation can change the size distribution of banks within a market, it can impact specific 

small business loan products in different ways depending on whether the loans tend to be made 

by institutions of a particular size. 

Peek and Rosengren (1998) also argue that a bank’s credit culture is a key determinant of 

its commercial lending activities. If small business lending is an important product line (or a 

desired product line) for acquiring institutions, they may increase the small business loan focus 

of their acquisitions over the longer term. When it is not an important product line, acquirers are 

likely to cut back on their acquisitions’ small business lending. The difficulty in testing this 

conjecture is that it is not always easy to determine how small business lending fits into the 

culture of acquiring banks, although community banks as a class are more likely to favor such 

lending. 

These arguments suggest that the relationship between bank consolidation and small 

business lending is complex and depends on many factors. A significant amount of empirical 

work has tried to quantify the overall relationship and to determine the importance of control 

factors. Because of data limitations, virtually all of these studies have focused on the lending 

behavior of individual banks (or banking organizations). Bank-level analyses have typically 

involved tests for systematic differences between the small business loan-to-asset ratios of banks 

involved in consolidations and those of a control group of banks that have not merged.4 

Researchers have used this approach to study different types of consolidations, such as mergers 

4

 See Berger, Demsetz, and Strahan (1999), Berger and Udell (1998), and Samolyk (1997) for discussions of these 

studies. 

9 
of institutions that vary in size or that are headquartered in different states. The general picture 

that emerges from these studies is that mergers among smaller institutions and/or banks having 

more of a small business focus tend to be associated with more small businesses lending (as a 

proportion of the bank’s assets), whereas consolidation involving larger banks tends to be 

associated with less. But the focus of bank-level studies on balance-sheet ratios makes it 

difficult to determine the effect of bank consolidation on the level of lending (measured in terms 

of loan dollars). 

As stated above, this paper focuses on assessing the relationship between consolidation 

and small business lending at the market level. Anecdotal evidence suggests that local market 

conditions should matter. It has been argued that since small business lending is the most 

localized banking product, it should be particularly sensitive to market structure (Cyrnak, 1998). 

According to standard structure and performance theory, consolidation activity in highly 

concentrated markets is likely to have a greater effect on lending than consolidation in highly 

competitive markets. Consequently, the same merger may have different impacts in the various 

markets it affects. In markets where both the acquirer and the acquired institution operate 

branches before the merger (within-market mergers), the merger may lead to a reduction in 

lending as the market becomes less competitive and the merged institution eliminates overlap. 

However, the same merger may have no impact in markets where there is no ex ante overlap. 

Even here, some researchers have argued that out-of-market acquirers may not have the same 

informational advantage or interest in the local market as institutions that have a local presence 

(Whalen, 1995; Keeton, 1997). 

Some bank-level studies have recognized the potential importance of market-level factors 

and have attempted to include them in their empirical analyses. These studies recognize that the 

10 
 

behavior of other market participants is an important consideration, since it can potentially offset 

any adverse effects of bank consolidation on small business credit availability. Research on 

other bank products suggests that the reaction of other local lenders is a critical component of the 

overall impact of consolidation on the market and that failure to consider it may lead to 

erroneous conclusions.5

 Two recent studies have tried to incorporate these considerations into 

their analyses of consolidation and small business lending. Berger et al. (1998) use proprietary 

micro loan-level data from the Federal Reserve Board of Governors Survey of the Terms of Bank 

Lending (STBL) to generate bank-level estimates of small commercial loans for each year from 

1980 through 1996.6 The authors use these estimates—in tandem with Call Report data on 

condition and income, structure data on consolidations and acquisitions, and Summary of 

Deposits data on deposits by branch location—to quantify changes in lending attributable to 

mergers and acquisitions, including supply effects attributable to nonmerging banks. Their 

findings are quite dramatic. They estimate that the response of nonmerging banks generally more 

than offsets the decline in small commercial loans attributable to bank consolidations. They do 

not, however, specifically focus on how bank consolidation is related to small business lending in 

particular types of local banking markets. 

5 In studies of bank branching patterns and mortgage lending patterns, Avery et al. (1999a, 1999b) find that the full 

market response to consolidations can be quite different from the response of just the consolidating institutions. 

Generally, Avery et al. find not only that consolidating institutions reduce their activity but also that there is virtually 

always a substantial positive market offset from nonconsolidating institutions. 

6

 The STBL data are reported by approximately 200 banks in a given survey wave; however, smaller independent 

banks are generally not well represented in the survey (there are only about 30 at any one time). Also, the STBL, 

unlike Call Reports, does not include any information about small business loans secured by commercial real estate. 

11 
 

Berger, Goldberg, and White (2001) study whether consolidation activity and entry by 

new banks can generate external effects--that is, systematic responses by other banks in the same 

local market.7

 They use Call Report data from 1993 to 1998 to represent a bank’s small business 

lending and Summary of Deposits data to measure the geographic scope of the bank’s markets. 

They relate a bank’s overall small business lending to its own consolidation activity as well as to 

weighted measures of the consolidation activity of banks in the markets where the bank operates. 

Their study finds only a modest positive external effect in response to bank consolidation. 

To try to address the gap in the literature regarding market-level effects, we conduct a 

market-level, not a bank-level, analysis. This allows us to explicitly address the behavior of 

institutions that are not directly involved in the local consolidation activity but that are affected 

by it. We are particularly interested in situations where these are community banks. We attempt 

to quantify the extent to which the presence (or absence) of community banks influences the 

impact of consolidation on small business lending at the market level both for overall lending 

and for various subproducts. This is the task we address in the next section. 

2. METHODOLOGY AND DATA 

Approximating the definitions used in antitrust analysis, we define local banking markets 

in terms of urban metropolitan statistical areas (MSAs) and rural counties. We study the effects 

of consolidation activity on changes in small business lending during two three-year study 

periods: 1994–1997 and 1997–2000. Related studies suggest that it takes several years for 

7

 De novo banks tend to lend proportionately more to small businesses than mature small banks (DeYoung, 

Goldberg, and White, 1998); thus, they represent an interesting aspect of a market’s competitive structure. Several 

studies have found that consolidation activity is positively related to market entry by de novo banks (Berger et al., 

2000; Keeton, 2000; and Seelig and Critchfield, 2003). 

12 
 

 

consolidating institutions to restructure their behavior. For example, the integration of lending 

operations, including the retraining of staff and coordination of underwriting activities, may 

require considerable effort. Three years seems like a reasonable period in which to look for 

consolidation-related changes in small business lending. 

The core of our statistical analysis is to measure the relationship between consolidation 

activity and changes in total small business lending (and in its components), testing how this 

relationship is affected by the structure of the local market and the nature of the consolidation 

activity. Throughout, we control for an array of banking-market characteristics and local 

economic factors. Although in principle this process seems quite straightforward, in practice 

there are some fairly complex issues of measurement. Here we summarize our data and 

methods.8 

Our small business loan data are from the June Call Reports.9 As noted above, these data 

do not include geographic information about where banks are lending. However, banking 

institutions do report the geographic distribution of their branches and their deposits as a 

8

 A more detailed description of the data sources and measurement issues is presented in the data appendix to this 

study. 

9

 Data for commercial banks are from the Federal Financial Institutions Examination Counsel (FFEIC) Reports of 

Conditions and Income (Call Reports); data for savings institutions are from the Thrift Financial Reports (TFR 

Reports). Since 1993, all commercial banks and savings institutions have been required to report the number and 

current outstanding balance of all commercial and agricultural loans having an original amount of less than $1 

million ($500,000 for agricultural loans) in their June 30 Call Reports. Lenders report separate figures for 

commercial and industrial loans not collateralized by real estate (C&I loans), loans collateralized by commercial real 

estate (CRE loans), and agricultural loans. Our measure of total small business lending equals the sum of C&I and 

CRE lending (and therefore excludes agricultural loans). Lenders also report total nonagricultural small business 

13 
 

supplement to the June Call Reports.10 We use these geographic Summary of Deposits data for 

each commercial bank or savings institution to allocate the institution’s small business loans 

across geographic markets, constructing midyear estimates of outstanding small business loans 

for every institution in each of the markets in which it has branches. Midyear estimates of total 

lending in any given market are then derived as the sum of the local lending by the institutions 

operating in the market. Implicitly, our method assumes that the geographic distribution of a 

bank’s domestic deposits is a reasonable proxy for the geographic distribution of its small 

business lending. As we summarize in the section below on robustness, related work on the 

validation of data suggests that this is a reasonable assumption. 

We conduct separate analyses for urban and rural markets because systematic differences 

between these types of market suggest that the effects of consolidation in these markets may 

differ. We exclude a number of markets from our study samples because of concerns about the 

validity of results for these markets. We exclude the 20 largest MSA banking markets (defined 

in terms of 1994 population), Charlotte (NC), and markets in Delaware and South Dakota 

because of concerns about the dominance of large institutions and large credit card lenders in 

these areas. We also exclude rural counties that in 1994 had populations below 20,000 or fewer 

than four banking organizations. We estimate that the rural markets included in our study sample 

account for somewhat more than two-thirds of small business lending in rural markets, while the 

originations disaggregated into several categories based on the size of the loan commitment. Here, we differentiate 

between loans with an original commitment of under $100,000 and those of a larger amount. 

10 The location (county) of banking institution depository offices and the reported deposit balances were extracted 

from the annual Summary of Deposits data for commercial banks and from the Branch Office Survey System filings 

for savings institutions reported in the years 1994–2000. 

14 
 

MSA markets we study account for just under two-thirds of small business lending in urban 

markets.11 

As with any bank consolidation study, choosing a metric to quantify consolidation 

activity is a key step in the analysis. We define consolidation activity to include all mergers 

among previously unrelated banking institutions and all acquisitions by bank or thrift holding 

companies of previously independent institutions or holding companies.12 Thus, our definition 

of consolidation activity does not include mergers among institutions that are affiliates of the 

same holding company. Over a three-year period, a surviving organization could have been the 

result of a sequence of mergers or acquisitions. We define its consolidation activity for the 

period as the sum of these transactions. All institutions that were unrelated at the beginning of 

the three-year period but are part of the same organization at the end are viewed as part of one 

consolidation. For a given consolidation, we define the largest of the original organizations (in 

terms of assets) as the acquirer and the others as the acquisitions. Local consolidation activity is 

defined in terms of the local institutions that were acquired; markets where no institutions were 

acquired are considered to have experienced no consolidation activity. Overall consolidation 

activity in a given market is quantified as the beginning-of-period share of the small business 

11 Data describing the breakdown of included and excluded markets are presented in the data appendix to this study. 

12 Transactions and structure information recorded in the Federal Reserve Board’s National Information Center 

(NIC) database were used for these purposes. 

15 
 

loan market held by organizations that were acquired sometime during the subsequent 36 

months.13 

To examine how the effects of bank consolidation depend on the nature of the 

acquisitions taking place, we also quantify local consolidation activity in terms of two key 

characteristics of the parties involved in the transaction. First, we measure consolidation activity 

that is within market as the beginning-of-period share of the small business loan market that was 

acquired by organizations that also had a presence in the market before the acquisition. Second, 

to test if consolidation effects depend on the sizes of the institutions involved, we construct 

variables that decompose total consolidation activity into three components: (1) activity 

involving only community banks, (2) activity involving community banks being acquired by big 

organizations, and (3) activity involving big organizations being acquired by other big 

organizations. Community-bank consolidation activity in a market equals the beginning-ofperiod share of the small business loan market held by community banks that were subsequently 

acquired by other community banks during the study period. Big bank acquisitions of 

community banks equal the beginning-of-period share of the small business loan market funded 

by community banks that were subsequently acquired by big organizations. Finally, big bank 

acquisitions of big banks equal the beginning-of-period share of the small business loan market 

held by big organizations that were subsequently acquired by other big organizations. 

The top segment of table 2 reports the means of the consolidation activity variables for 

the urban and rural samples in each study period. Urban markets are larger and less concentrated 

13 Our consolidation measure effectively weights an acquisition by its ex ante share of local lending in measuring its 

importance to the market. Thus, the acquisition of an institution that does little business lending (such as a thrift) 

will have only a minor impact on our measure of local consolidation activity. 

16 
 

than rural markets, so it is not surprising to see differences across the two groups. Urban markets 

experienced higher average levels of overall consolidation activity in both study periods. And 

not surprisingly given their larger size, urban markets tended to experience more within-market 

consolidation activity than did their smaller rural counterparts.14 

In both types of markets and in both study periods, acquisitions of community banks 

accounted for notable shares of consolidation activity. However, rural markets are characterized 

by more community bank consolidation activity than urban ones, a result that—as we will 

document—reflects the greater presence of community banks in these smaller markets. Indeed, 

although overall consolidation activity was lower (on average) in rural markets, these markets 

experienced higher levels of community bank consolidation activity than did urban markets (on 

average). As noted, bank-level evidence indicates that mergers of small banks have been 

associated with increases in small business lending as a share of the merged entities’ assets, 

whereas mergers involving large banks have been associated with reductions in the small 

business loan share of the surviving organizations. Here we test the extent to which this 

evidence manifests itself in terms of lending at the local market level. 

Given the market-level estimates of small business lending for every bank, total lending 

in a given market is the sum of lending by all institutions in the market. In relating changes in 

small business lending to consolidation activity in a given market, we compare end-of-period 

14 Because most rural markets have a relatively small number of participants, consolidation activity in them was less 

likely to be within-market. Many rural markets experienced no consolidation activity, and in those that did, 

consolidation generally involved a very small number of acquisitions—often only one. Thus a particular type of 

consolidation activity (such as within market) was frequently the only type of consolidation activity in a rural market. 

17 
 

lending with beginning-of-period lending net of any pro forma changes associated with our 

imputation method.15 The change in lending is expressed as a real percentage growth rate that 

equals the ratio of end-of-period lending to pro forma-adjusted beginning-of-period lending (both 

are measured in 2000 dollars). To trace consolidation-related effects on particular types of small 

business loans, we decompose total loan growth into additive components measuring (1) small 

business loans under $100,000 versus small business loans over $100,000, and (2) small business 

CRE lending versus small business C&I lending. Each of these components is expressed as a 

ratio, with pro forma-adjusted beginning-of-period total small business lending as the 

denominator; hence, each set of components additively equals total small business loan growth. 

The middle segment of table 2 reports the means of total small business loan growth and 

its components for each type of market in each study period. In real terms, small business loan 

growth is higher (on average) in our later study period, although the growth of loans under 

$100,000 is lower (in fact, the mean change for these smaller loans in urban markets between 

1997 and 2000 is negative). The C&I component of small business loan growth is comparable 

15 Because we use deposit data to estimate bank lending across markets, the merger of institutions with very different 

small business loan-to-deposit ratios can affect geographic loan estimates. Effectively, our method generates 

geographic loan estimates that reflect the overall ratio of loans to deposits of each bank and its deposits in each 

market. For example, if bank A and bank B lend in market j, then market j’s small business loans (SBL) are 

calculated as SBL(j) = Deposits(a,j)(SBL (a)/Deposits(a) ) + Deposits(b,j)(SBL(b)/Deposits(b)). Suppose A and B 

merge. If their SBL-deposit ratios differ, then SBL(j) would change if recalculated with the merged data for the two 

banks. More generally, if two banks have very different ratios of loans to deposits, patterns estimated using merged 

data for the banks would differ from patterns generated using separate data for the banks. To ensure that our marketlevel measures of loan growth do not reflect changes due purely to our imputation method, we calculate loan growth 

using (pro forma) beginning-of-period loan estimates that reflect end-of-period (post merger) organizational 

structures. Thus, our “adjusted” growth measures use a lending base constructed to net out any computational effects 

due to the combining of bank balance sheets. 

18 
 

(on average) in urban and rural markets and in both study periods, while the CRE component is 

higher for both types of markets in the 1997–2000 period. In the next section, we present tests 

that control for other factors to isolate patterns in these measures that are related to consolidation 

activity. 

The bottom segment of table 2 reports the definitions and means of the control variables 

we include in our statistical tests. Included in our set of control variables are various measures 

representing the structure and competitiveness of local banking markets. One characteristic is 

the presence of community banks in the market, measured as the share of the local small business 

loan market held by community banks at the beginning of the study period. As indicated in table 

2, the mean community bank market share is significantly higher in the rural samples than in the 

urban ones—roughly 60 percent versus 40 percent—a fact we take into consideration in our 

empirical tests. Our set of banking market characteristic control variables also includes a 

Herfendahl index of deposit market concentration, the number of organizations in the market, the 

share of the deposit market held by savings institutions (which tend to do proportionately less 

small business lending than commercial banks), and the number of banking institution branches 

per 10,000 residents. These variables are intended to control for the degree of competitiveness in 

each market at the beginning of each study period.16 Again we find systematic differences 

between urban and rural markets: rural markets tend to be more concentrated and to have fewer 

banking organizations than urban markets. 

16A Herfendahl index based on banking deposits is a standard measure used to assess the competitiveness of banking 

markets. The Federal Reserve Board includes thrift deposits with a weight of 50 percent in calculating Herfendahl 

indices for its bank merger analysis; we do the same here. 

19 
 

 

Our control variables also include several measures of market-level economic conditions. 

These include population, real per capita personal income, the unemployment rate, housing 

prices, and building permits.17 We include levels and contemporaneous and lagged measures of 

change for these variables. Finally and importantly, given our method for estimating geographic 

lending patterns, we include both contemporaneous and lagged deposit growth in the market (as 

reported in the Summary of Deposits data) as control variables. Thus, we are measuring changes 

in small business lending attributable to consolidation activity over and above the changes 

associated with deposit growth in the local market. 

3. STATISTICAL TESTS 

Here we discuss the specific statistical tests used in our study. We begin with a 

discussion of the general form of the tests and follow with the results. 

3.1 Tests 

The basic reduced-form model that we estimate can be described by 

[Small Business Loan Growth (t,t+3), m ]= f(Consolidation Activity(t,t+3), m , Banking Market 

Characteristics t, m , Deposit Growth(t-3,t ; t,t +3), m , Economic Controls(t-3,t ; t,t +3), m ) + error, 

17 Data sources for the economic control variables are described in more detail in the data appendix to this study. 

The economic variables are constructed from annual county-level data on population and personal income (U.S. 

Bureau of the Census), annual county-level (establishment) data on the labor force and unemployment (U.S. Bureau 

of Labor Statistics), weighted-repeat-sales 1–4 family housing price indices (Fannie Mae, Freddie Mac), and annual 

county-level building permits (U.S. Bureau of the Census). 

20 
where t is the beginning of the three-year study period; Small Business Loan Growth (t,t+3), m equals 

loan growth measured (as described above) in market m from year t through year t+3; and 

Consolidation Activity (t,t+3), m measures the nature of acquisitions in market m between year t and 

year t+3. Banking Market Characteristics t, m is the set of variables measuring the characteristics 

of banking market m in the beginning of the study period, before the consolidation activity 

occurs. Deposit Growth(t-3,t; t,t+3), m and Economic Controls(t-3,t; t,t+3), m are the controls for local 

deposit growth and local economic conditions, respectively, during the three years before the 

study period (year t-3 through year t) and during the study period (year t through year t+3). 

We test how the level and nature of consolidation activity and community bank presence 

are related to small business loan growth and its components in the following manner: First, we 

run regressions that include only the overall consolidation activity variable as a treatment 

variable. Then we run comparable regressions that replace the overall consolidation activity 

variable with the variables measuring the particular types of consolidation activity: (1) withinmarket consolidation activity, (2) big organization acquisitions of other big organizations, (3) big 

organization acquisitions of community banks, and (4) community bank consolidation activity. 

This second set of tests allows us to measure potentially differential effects of different types of 

consolidation activity—effects that be obscured when only the overall consolidation variable is 

included. 

To explore the possibility that the impact of consolidation activity may differ in certain 

types of markets, we run two other sets of tests. First, we split each urban and rural sample on 

the basis of each market’s degree of concentration, using the beginning-of-period Herfendahl 

index summarized in table 2. Markets having a beginning-of-period deposit Herfendahl index of 

21 
 

1800 or more are classified as high Herfendahl markets; all others are low Herfendahl markets.18 

This split allows a test of the conjecture that consolidation activity has more pronounced effects 

on small business credit availability in highly concentrated markets than in more competitive 

ones.19 Second, we split the urban and rural samples on the basis of the prominence of 

community banks in the local small business loan market before the consolidation activity 

occurs. Rural markets where community banks have a beginning-of-period small business loan 

market share of 60 percent or more are classified as high community bank share markets; those 

where the community bank market share is less than 60 percent are classified as low community 

bank share markets. In the urban samples, MSAs where community banks have a beginning-ofperiod small business loan market share of 40 percent or more are classified as high community 

bank share markets, and those where the community bank market share is below 40 percent are 

classified as low community bank share markets. This split allows an examination of the 

potential mitigating impact that community banks may have on consolidation effects. 

3.2 Test Results 1994–1997 

Table 3 presents results for urban markets during the 1994–1997 study period. In the 

interest of brevity, only coefficients for the consolidation and community bank market share 

variables are presented. Complete regressions are presented for a representative subset of 

regressions in appendix tables A.2 and A.3. Here we find a negative association between overall 

18 The Department of Justice’s lower cutoff in its definition of highly concentrated markets is 1800. 

19 We continue to include the Herfendahl index as an explanatory variable in these tests to control for differences in 

concentration within the high Herfendahl and low Herfendahl subsamples. 

22 
consolidation activity and small business loan growth (panel A). This relationship is most 

evident in the high Herfendahl and the low community bank share subsamples. The coefficient 

of the community bank market share variable is positive and significant in only a few cases, and 

interestingly these occur in the low Herfendahl subsamples. In terms of specific types of 

consolidation activity (panel B), we find a consistent negative association between consolidation 

activity involving big organizations and small business loan growth, particularly in the high 

Herfendahl and low community bank share subsamples. There is some evidence of a positive 

effect associated with community bank consolidation activity, and again, this tends to be in the 

high Herfendahl and low community bank share subsamples. 

Table 4 presents the results for rural markets for the 1994–1997 study period. Here we find 

little or no relationship between overall consolidation activity and small business loan growth, 

but we do find evidence of a positive effect associated with community bank market share, 

particularly in the low Herfendahl and the high community bank share subsamples (panel A). 

The only evidence of a significant overall consolidation effect is in the low community bank 

share subsample. The tests of specific types of consolidation activity suggest that the overall 

consolidation activity variable masks differential effects of different types of consolidation in 

rural markets during the 1994–1997 period (panel B). We find consistent evidence of a negative 

effect associated with consolidation activity involving big organizations and a positive effect 

associated with community bank consolidation activity; and again, these effects are most evident 

in the high Herfendahl and low community bank share subsamples. Overall, these effects appear 

to cancel each other out, leaving an insignificant relationship between overall consolidation 

activity and small business loan growth. 

23 
3.3 Test Results 1997–2000 

The dynamics in small business credit markets appear to have changed in the 1997–2000 

study period. Table 5 presents the results for urban markets for this period. In contrast to what 

we found for the 1994–1997 period, we find a positive association between overall consolidation 

activity and small business loan growth—a result that is evident in each of the subsamples 

classifying urban markets in terms of their Herfendahl index and community bank market share 

(panel A). These effects are evident for all subproducts but are strongest for loans under 

$100,000 and for C&I loans. The tests of specific types of consolidation activity (panel B) 

indicate that the positive overall consolidation effects are driven by consolidation activity 

involving big organizations. We do find negative effects associated with within-market 

consolidation activity in low community bank share markets, but we find no significant effects 

associated with community bank consolidation activity. And we find a negative association 

between beginning-of-period community bank market share and small business loan growth in 

the high Herfendahl urban subsample during the 1997–2000 period. 

Table 6 presents the results for rural markets in the 1997–2000 study period. Here we find 

little evidence of any significant relationship between overall consolidation activity and small 

business loan growth (panel A). Tests of specific types of consolidation activity (panel B) 

indicate that big organization acquisitions of community banks are associated with higher growth 

in small business loans under $100,000 and in CRE lending. We find no significant effects 

associated with community bank consolidation activity and little evidence of a relationship 

24 
between beginning-of-period community bank market share and small business loan growth in 

rural markets during the 1997–2000 period. 

4. THE IMPACT OF CONSOLIDATION ON COMMUNITY BANKS 

In the previous section, we focused on assessing the impact that the presence of 

community banks had on small business loan growth in markets experiencing consolidation 

activity. In this section, we look at a different but closely related issue—the impact of 

consolidation on community banks’ role as small business lenders. We argued above that 

contractions by consolidating institutions may create opportunities for community banks as small 

business lenders. This can come about if existing institutions expand their lending or if new 

entrants come into the market. We study this issue in two ways. First, we measure changes in 

community bank market share for different types of small business loans in different types of 

markets. Then we examine the composition of small business loan growth in terms of the 

contributions of consolidating institutions, of existing nonconsolidating institutions, and of new 

market entrants. We conduct each of these investigations with data adjusted for market and 

economic conditions, using the same control variables as in the previous section. 

Our method for examining changes in the market share of community banks as small 

business lenders follows. First we decompose the gross change in the share of small business 

loans held by community banks in a given market into three components: the pro forma change 

due to reclassifications in the size of organizations as a result of consolidation activity; the pro 

forma change due to size reclassifications resulting from asset growth (other than through 

acquisitions); and the change in community bank market share measured net of these pro forma 

25 
 

changes.20 Comparable market share change measures are constructed for each of the small 

business loan components measuring CRE loans, C&I loans, loans under $100,000, and loans 

over $100,000. We then regress each set of market share change measures against the set of 

economic and banking market control variables used in the previous section, running separate 

regressions for urban and rural markets in each of the two study periods. We include no 

variables for consolidation activity in these regressions. Predictions from each set of regressions 

are subtracted from their respective dependent variables to obtain gross, pro forma, and net pro 

forma-adjusted community bank market share changes, all adjusted for economic and banking 

market conditions. The resulting market share change variables are scaled to preserve the means 

of their respective original variables. 

We use a similar methodology to examine small business lending by particular types of 

institutions at the local market level. First, we decompose the growth of total small business 

lending and each of its subproducts into components attributable to the following groups: 

consolidating institutions (within-market consolidations, out-of-market acquirers, and 

acquisitions by out-of-market acquirers) differentiated by the beginning-of-period size of the 

consolidated organization, existing nonconsolidating community banks, existing 

nonconsolidating big organizations, community bank new market entrants, and big organization 

new market entrants. The resulting set of loan growth variables are then regressed against the 

20 If the organization resulting from the consolidation of community banks is larger than $1 billion, the market share 

of community bank lending will necessarily decrease. The pro forma variable for consolidations captures changes in 

market share due purely to this effect. Similarly, when community banks have asset growth large enough to “grow 

out” of the community bank classification during the measurement period, a shift in share from community banks to 

large organizations is created. Yet this is not a real shift in market share because it does not represent a movement of 

lending from one institution to another. The adjusted change variable reflects the change in market share netting out 

both of these effects. 

26 
economic and banking market control variables, with separate regressions run for urban and rural 

markets in each of the two study periods. Predictions from these regressions are subtracted from 

their respective dependent variables and scaled to preserve the original means, yielding small 

business loan growth variables adjusted for economic and market factors. It should be noted that 

since total small business loan growth and its components are computed using the same 

denominator (beginning-of-period total small business lending in the market), using regressions 

to adjust the variables for economic and banking market factors does not change additivity: the 

adjusted components will still add up. Similarly, since the decompositions of loan growth into 

components attributable to different types of lenders use the small denominator, these 

components are also additive. 

The results of these two procedures are presented in table 7. Values presented in the table 

are the sample means of the variables described above. The first eight columns report means for 

the 1994–1997 period and the second eight report means for the 1997–2000 period. To isolate 

patterns associated with consolidation activity, table 7 includes separate estimates for urban and 

for rural markets that are further subdivided into (1) markets experiencing no consolidation 

activity or a low level of it (less than 5 percent of the small business loan market was acquired), 

and (2) markets experiencing a high level of consolidation activity (more than 25 percent of the 

small business loan market was acquired). We do not report results for markets experiencing an 

average level of consolidation activity–that is, those where 5–25 percent of the small business 

loan market was acquired. Within each of these subsamples, we further classify markets in terms 

of whether they had a low or a high beginning-of-period community bank market share (as 

defined above in the section “Methodology and Data”). 

27 
The top segment of table 7 presents results for changes in community bank small business 

loan market shares. The average community bank share of total small business lending in urban 

and rural markets fell by 1.0 and 1.3 percentage points, respectively, between 1994 and 1997, and 

by 2.0 and 0.5 percentage points, respectively, between 1997 and 2000 (not shown in the table). 

But these figures are deceptive. When pro forma changes due to size-category reclassifications 

(because of consolidations or asset growth) are removed, we find that on average, community 

bank market shares increased by 7.2 and 6.2 percentage points in urban and rural markets, 

respectively, during the 1994–1997 study period; and by 8.5 and 7.2 percentage points in urban 

and rural markets, respectively, during the 1997–2000 period. Thus, observed declines in 

community bank small business loan market shares can be attributed entirely to pro forma sizecategory reclassifications, as community banks consolidate or grow into larger organizations, 

rather than to any fundamental contraction in community bank lending. 

The data in table 7 show fairly consistent patterns in how community bank market share 

changes are related to consolidation activity and beginning-of-period community bank presence. 

In both urban and rural markets, in both study periods, and across all types of small business 

loans, we find that increases in community bank market share (measured net of pro forma 

changes) are larger in high consolidation markets than in low consolidation markets having a 

similar ex ante community bank presence. We also find that the difference between net market 

share growth in low consolidation and high consolidation markets is greater in markets where the 

ex ante community bank presence is high. 

These patterns suggest that the period we study was a good one for community banks as 

small business lenders, particularly those operating in markets undergoing consolidation. 

Moreover, a high ex ante community bank presence does not appear to have impeded further 

28 
growth in market share; indeed, it may have enhanced such growth. Finally, we do not find 

evidence supporting conjectures that large organizations were taking market share from 

community banks by using standardized small business credit scoring technologies. Changes in 

community bank market share measured net of pro forma effects are generally smaller for the 

loans in the under $100,000 category than for larger small business loans, but in all cases their 

mean change is positive. 

The data in the bottom segment of table 7 provide further support for the view that the 

1994–2000 period was good for community banks as small business lenders, particularly in 

markets where consolidation was occurring. The growth of total small business lending 

attributable to community banks (“total all CBs”) is almost always higher in high consolidation 

markets than in low consolidation markets having a comparable ex ante community bank 

presence, even where total loan growth is lower (for example, in urban markets experiencing 

high consolidation activity during the 1994–1997 period). The various decompositions of small 

business loan growth indicate a broad-based pattern of growth by community banks in markets 

experiencing high levels of consolidation activity. The loan growth came from all types of 

community banks, including new market entrants, existing nonconsolidating institutions, and 

consolidating institutions whose combined size still defined them as community banks. 

During the 1994–1997 period, the greater community bank lending in high consolidation 

markets contrasts with contractions by large consolidating organizations, supporting the view 

that there was an “offset.” However, although not shown in table 7, the data suggest that it was 

in markets experiencing the acquisitions of big organizations by other big organizations where 

most of the contraction in small business lending took place. During this period, we generally 

find that average lending by large organizations that had acquired community banks either rose or 

29 
fell only slightly in the markets where the community bank had operated. The only exceptions 

are markets where consolidation activity was low and ex ante community bank presence was 

high. In these markets, the declines in lending appear to be driven by within-market 

consolidations, suggesting that these areas may have been overbanked areas. Thus, it was in the 

consolidations of big organizations with other big organizations where significant cutbacks in 

small business lending occurred, creating the opportunity for community banks. 

5. VALIDATION AND ROBUSTNESS 

The validity of our evidence about bank consolidation and local credit availability hinges 

on the accuracy of the method we use to estimate the geographic distribution of small business 

lending. This method assumes that deposit-taking patterns are a good proxy for the geographic 

distribution of a bank’s small business lending, both at a point in time and over time. To the 

extent that these patterns are dissimilar, our strategy assumes that distributional differences in 

lending and deposit taking are not systematically related to consolidation activity. 

To assess the validity of these assumptions, we conducted two tests. First, we ran all of our 

statistical tests both with and without the deposit-growth control variables to examine the extent 

to which deposit patterns affect the results. As indicated above, deposit growth is a key factor 

explaining local small business loan growth—although its explanatory power varies across 

market subsamples. However, there is essentially no change in the estimated sign, magnitude, 

and significance of the key consolidation variables in the regressions estimated without the 

deposit variables. This indicates that our cross-market and cross-time measures of small business 

lending reflect more than merely variations in deposit-taking activity. 

30 
 

We also indirectly test the validity of our geographic loan estimates using data on small 

business loan originations collected under the auspices of the Community Reinvestment Act 

(CRA). 21 Since 1996, larger banks have been required to report the number and amount of their 

annual small business loan originations by census tract. Unfortunately we cannot directly 

replicate our study using the CRA data, since they are not reported by many of the institutions 

(community banks) with which we are most concerned. However, we use 1997 CRA and 

deposit-based small business loan measures to perform a simple comparison test for institutions 

that reported both types of data. Specifically, we compute the correlation of lending across 

markets implied by the CRA data with the distribution of loans implied by our deposit-based 

measures. Overall there was a .87 correlation between the two variables in the urban markets 

used in our study and .80 in the rural markets used, indicating a reasonable correspondence 

between geographic distribution of the two measures. 22 

6. CONCLUSIONS 

Questions about the evolving U.S. financial environment are likely to become increasingly 

important as bank deregulation moves to new plateaus. Still, evidence about how factors such as 

bank consolidation affect the provision of traditional banking services is hard to produce. Bank 

21CRA loan origination data use loan definitions comparable to those used for the small business data reported in the 

June Call Reports, including loan size categories and the separate reporting of agricultural and nonagricultural small 

business loans. Institutions representing about 70 percent of the stock of outstanding small business loans reported 

CRA data in 1997. 

22 More information about our comparison of geographic banking patterns evident in the Summary of Deposits and 

CRA data are reported in an earlier study that uses this same basic method for generating market-level small business 

loan estimates (Avery and Samolyk, 2000). 

31 
consolidation is inherently a complex phenomenon that affects bank customers in the particular 

markets for the banking services that they seek. Given the evolution of bank product markets, 

small business lending is likely to be one of the few products that will remain relatively local in 

nature. 

The characterization of local consolidation activity we present in this paper yields 

interesting evidence about consolidation-related loan growth patterns at the local market level. In 

the 1994–1997 study period, we find that big organization consolidations had adverse effects on 

small business loan growth, whereas community bank presence and community bank merger 

activity were positively related to local small business credit availability. These results are 

broadly consistent with bank-level evidence on the effect of scale and credit culture on small 

business lending. The presence of community banks also appears to have mattered for local 

credit availability in this period, as does the competitiveness of the markets where acquisitions 

were taking place. We find less in the way of negative consolidation effects in markets where the 

ex ante community bank market share was high and market concentration was low. These 

findings suggest that competition in general or through a strong community bank presence can 

play a significant role in determining the effects of bank consolidation on the local market. 

The general dynamics associated with consolidation activity in small business credit 

markets appear to have been quite different in the 1997–2000 study period. The relationships we 

do find indicate that consolidation activity involving big organizations was associated with 

higher local small business loan growth. 

When we look at the impact of consolidation activity on community bank small business 

loan market shares, we find pretty consistent evidence that the 1994–2000 period in general and 

consolidation in particular were good for community banks. Gross market share calculations 

32 
 

show a decline in community bank shares. But adjusted for size-category reclassifications due to 

consolidation or asset growth and for local market conditions, community bank small business 

loan market shares have increased during the 1994–2000 period. And the increases in 

community bank market share have been larger in markets undergoing consolidation. 

Going forward, more research on small business lending at the local market level is needed 

to extract evidence about the role that small business lending should play in the regulation of 

bank consolidation. Data limitations will hamper this effort. The bank loan data we use are 

reported by the size of the loan rather than by the size of the borrowing firm. In addition, 

nonbank business lenders, such as finance companies, do not report data on their small business 

lending and therefore are not included in most statistical analyses of bank consolidation. Finally, 

researchers and policy makers must deal with issues involved in integrating the new CRA data 

with the other banking data traditionally used to analyze bank merger activity. 

33 
 

DATA APPENDIX 

The data used in this study combine information from sources covering three areas of 

commercial bank and thrift activity: (1) branch office location and deposit balances; (2) bank 

condition and income (including outstanding small business loans); and (3) records of bank 

structure (including structure changes such as failures, mergers, and acquisitions). We also use 

data on population, income, housing prices, employment, and building permits (issued) to 

measure economic conditions in local banking markets. This appendix discusses our data 

sources and measurement issues, including the measurement of small business loan growth and 

changes in community bank market share. 

Data sources 

The location (county) of banking institution depository offices and reported deposit 

balances were extracted from the annual Summary of Deposits data for commercial banks, and 

from the Branch Office Survey System filings for savings institutions, reported in the years 1991 

through 2000. The office list includes all locations qualifying as separate institution deposittaking offices under federal guidelines as of June 30 of each year. It does not necessarily include 

all drive-ins, ATMs, or loan production offices; however, virtually all staffed deposit-taking 

offices are reported. The geographic deposit data used in this study may differ slightly from the 

publicly available files as a result of limited data cleaning required for the analysis.24 

24 For example, some offices were added for a few institutions that did not submit a Summary of Deposits or Branch 

Office Survey System filing, and some addresses were corrected for a limited number of offices for which incorrect 

county location was reported. Similarly, deposit balances were imputed for some branches that reported zero 

34 
 

Information on outstanding small business loans was obtained from the Federal Financial 

Institutions Examination Counsel (FFEIC) Reports of Conditions and Income (Call Reports) and 

from the Thrift Financial Reports (TFR Reports) for June of each year from 1994 through 2000. 

Since 1993, all commercial banks and savings institutions have been required to report the 

number and current outstanding balance of all commercial and agricultural loans having an 

original amount of less than $1 million ($500,000 for agricultural loans) in their June Call 

Reports. Lenders report separate figures for nonagricultural small business loans not 

collateralized by real estate (C&I loans), loans collateralized by commercial real estate (CRE 

loans), agricultural loans collateralized by real estate, and other agricultural loans. Only data on 

C&I and CRE loans are included in our measure of small business loans. Lenders also 

differentiate loans by the size of the commitment. Nonagricultural loans having commitment 

values below and above $100,000 are differentiated in our study. 

Finally, other bank-level information was needed for this study to determine the 

appropriate structure to use in classifying banking institutions and to determine which institutions 

were involved in consolidations during the study periods. Transactions and structure information 

recorded in the Federal Reserve Board’s National Information Center (NIC) database is used for 

these purposes. All federally insured commercial banks and savings institutions in existence on 

June 30 of each year and reporting at least some small business lending are included in this study, 

with several exceptions. Institutions classified as wholesale, strategic-plan, or limited-purpose 

institutions under guidelines of the Community Reinvestment Act or as special-purpose 

institutions (for example, nonbank banks) by the NIC system at any point in the 1994–2000 

deposits (some banks consolidate their deposits into a few offices and report zero deposit balances for the remaining 

offices). 

35 
 

period are dropped from our analysis for both study periods. Most of the excluded institutions 

are banks that engaged exclusively in wholesale or credit card activities. Dropped institutions are 

not used in computing organization sizes or in determining whether a merger or acquisition took 

place. 

Data for most of the economic control variables were obtained from the Bureau of 

Economic Analysis REIS data files (annual county-level data on population and personal 

income), the Bureau of Labor Statistics (annual county-level [establishment] data on the labor 

force and unemployment), and the U.S. Bureau of the Census (county-level data on the number 

and dollar value of new building permits for residential homes).25 Data on 1–4 family residential 

house prices are computed from the Fannie Mae and Freddie Mac weighted-repeat sales index.26 

Variables measuring consolidation activity, small business loan growth, and economic and 

banking `market controls are aggregated to the market level for the analysis. All dollar-based 

measures used in the study—including institution size classifications—are converted to 2000 

dollars using the consumer price index. 

Measurement issues 

This study defines markets in terms of metropolitan statistical areas (MSAs) for urban 

areas and in terms of counties for rural areas.27 Hence, to construct market-level variables from 

25 In some cases the Census Bureau combines information for small counties or for cities in Virginia that are not 

included in any of the adjacent counties, and we align our data to match Census Bureau information. 

26 The index was available for a little more than one-half the MSAs, about 150 larger counties, and for states. The 

lowest level of aggregation possible was used to determine price changes. 

27 NECMAs (county aggregates) are used to define urban markets in New England. 

36 
 

county-level data, we simply aggregate data for the all counties in a given MSA. Year 2000 

definitions are used to determine MSA boundaries. In all, 2,593 markets were defined, with 

annual information for 1994 to 2000; however, as described in this study, we exclude some 

markets from our study samples because of concerns about the validity of findings for very large 

or very small markets.28 Overall we study 1,052 markets, including 292 MSAs and 760 rural 

counties. 

We use the Summary of Deposits data to geographically allocate Call Report balances of 

outstanding small business loans as reported by a given commercial bank or savings institution 

across each of the markets where it operates branches. The share of an institution’s total loans 

allocated to a given market is simply equal to the share of its total (domestic) deposits that it 

reports having in that MSA or county in its midyear Summary of Deposits filing. Total small 

business lending for a given market is therefore the sum of market-level lending estimated for 

each institution included in our study. 

For each of the three-year periods used in our analysis, institutions are classified by their 

membership in banking organizations as of June 30 of the first year of the study period (1994 or 

28 Banking data for the largest MSAs are dominated by the behavior of the large money-center institutions 

concentrated in these areas. Many of these institutions have national lending programs, which may mean that our 

method of loan allocation is suspect. Consequently we decided to drop from the analysis the 20 largest MSAs (by 

deposits). Charlotte (NC) and MSAs in Delaware and South Dakota were also dropped because of the concentration 

of large national lending institutions in these areas. We also dropped all rural county markets that in 1994 had 

populations of less than 20,000 or fewer than four banking organizations having branches. These areas were felt to 

be too small for the impact of consolidations to be meaningfully measured. All Delaware and South Dakota rural 

counties were also dropped. Of the 2,593 markets in the United States, 1,522 rural counties and 25 MSAs were 

dropped from our analysis by the above criteria. 

37 
 

1997).29 The size of an organization is computed as the sum of the domestic assets (2000 

dollars) reported on the June Call Reports by all affiliated banking institutions included in our 

study.30 Commercial banks or savings institutions that are not part of a larger banking 

organization are treated as independent organizations. These beginning-of-period classifications 

are used to construct control variables that measure banking market structure, such as the deposit 

Herfendahl indices (constructed using the Summary of Deposits data), and to classify banking 

organizations as community banks (organizations having assets of less than $1 billion). 

We also classify commercial banks and savings institutions in terms of these affiliations 

when measuring consolidation activity occurring during a given study period. We identify the 

organizational membership of each institution at the end of a given three-year study interval and 

determine whether institutional affiliations changed within that interval. Institutions that were 

unaffiliated at the beginning of the study period and are affiliated three years later are deemed to 

have been part of a consolidation.31 

29 These organizations included bank and thrift holding companies and foreign bank payment groups (U.S. chartered 

banks that are subsidiaries of a common foreign bank). 

30 This may differ somewhat from the total assets reported by bank and thrift holding companies for their combined 

operations. However, consolidated information was not available for foreign bank payment groups; consequently we 

decided to use a common basis in forming size. As stated above, special-purpose institutions excluded from the 

study were not used in calculating organization sizes. 

31 Note that this definition of a consolidation includes mergers of previously unaffiliated institutions, acquisition of 

one holding company by another, or acquisition of a previously independent institution by an existing holding 

company. It does not include “consolidation” of common members of a bank or thrift holding company into a single 

bank, as these institutions would not have been deemed to be independent at the start of the period. Note as well that 

an organization acquiring a de novo bank would not be treated as having undergone a consolidation, since the de 

novo institution did not exist at the beginning of the period. 

38 
For much of our analysis it is necessary to differentiate between the acquirer and the 

acquisition in a given consolidation. These determinations are not always apparent from the 

record. Consequently, we decided to designate the largest component of a consolidating entity 

(as measured by its size at the beginning of the period) as the acquirer. All other components 

were treated as acquisitions. Thus, if four previously unrelated banks merged into a common 

holding company within a given period, the bank with the most assets at the beginning of the 

period would be deemed to have acquired the other three. In characterizing different types of 

consolidation activity, we also classify acquirers and acquired organizations by their size. 

Organizations having total domestic assets of $1 billion or more (in 2000 dollars) are considered 

to be big; those having less are considered to be community banks. 

Within a given market, a consolidation is deemed to have occurred when a bank (or 

organization) with small business lending in that market at the beginning of the period is 

acquired by another bank (or organization) during the period. For a given consolidation, if it 

involves a larger institution that had offices in the market before the consolidation, the 

consolidation is deemed to be within market; otherwise the acquisition is treated as an out-ofmarket consolidation. Overall consolidation activity in a market is computed as the share of the 

market’s beginning-of-period total small business lending held by organizations that were 

acquired during the subsequent three-year study period. If no organization in the market was 

acquired, the market is deemed to have had no consolidations, and consolidation activity equals 

zero. Implicitly our measures of consolidation activity do not count acquisitions of institutions 

that report no small business lending. For example, the acquisition by a bank holding company 

of an independent thrift that does no small commercial lending is not counted in our measures of 

consolidation activity. 

39 
Table A.1: Aggregate Statistics for Subsets of Markets 

Excluded rural markets Included rural markets Included urban markets Excluded urban markets 

1994 1997 1994 1997 1994 1997 1994 1997 

Population (millions) 19.4 20.0 34.1 35.1 126.3 131.2 83.4 86.3 

Domestic deposits (billions of $2000) 2,050.9 2,162.4 3,972.6 4,003.0 16,089.0 16,276.9 14,170.9 14,696.8 

Small business loans (billions of $2000) 283.9 328.5 576.2 622.9 1,802.1 1,930.7 1,107.6 1,226.7 

Percentage of small business loans

 Held by community banks 73.6 72.6 58.1 57.2 34.9 33.5 36.3 31.2

 Acquired during subsequent three years 13.9 15.1 16.2 19.0 21.8 22.2 21.4 22.1

 Acquired by within-market acquirer 1.2 1.0 2.8 3.9 11.0 9.7 16.1 13.6 

Mean Herfendalh index 4,656.7 4,574.4 2,262.4 2,239.4 1,627.7 1,626.4 1,364.8 1,476.7 

Number of markets 1,522 1,521 760 760 292 292 25 25 

Note: Statistics, except the mean Herfendahl index, are computed as aggregates for each group of markets. All variables except population are 

measured as of June 30 of the year. Small business lending includes C&I and commercial real estate loans that had an original denomination of 

less than $1 million as reported in the June 30 Call Reports and is allocated to markets using methods described in this data appendix. 

Community banks are organizations having beginning-of-period assets of less than $1 billion (in 2000 dollars). Acquisitions refer to the 

acquisitions of independent banks, savings institutions, and bank or thrift holding companies by previously unaffiliated organizations, as 

described in this data appendix. 

Table A.1 describes the subsamples of markets that we include in our study and the 

markets that we exclude in terms of some of our key analysis variables. As noted in the paper, 

the rural markets we include in our study samples account for roughly two-thirds of small 

business lending in rural markets, while the MSA markets we study account for just under twothirds of small business lending in urban markets. 

Measuring small business loan growth 

We measure changes in small business lending during a given three-year study period as 

the ratio of end-of period lending to beginning-of-period lending, with one important adjustment. 

Because we use the reported geographic distribution of a bank’s (or thrift’s) deposits to allocate 

its small business loans across markets, the allocation can be affected by merger activity at the 

bank level that changes the distribution of deposits for the merged entity. Accordingly, we 

calculate the beginning-of-period allocation of small business loans across markets using deposit 

40 
 

patterns that reflect end-of-period bank-level affiliations. That is, for all banks and thrifts 

involved in mergers at the bank level (the level at which the Summary of Deposits and Call 

Report data are reported), we construct pro forma (merger-adjusted) beginning-of-period 

estimates of local small business lending on the basis of the geographic distribution implied by 

the merged entity’s deposit data. These pro forma beginning-of-period small-business-loan 

estimates are used as the basis for measuring changes in small business lending (and in its 

components) over time throughout our study. The reason for this adjustment is to net out 

calculated changes in lending that result solely from the way bank-level mergers impact our 

constructed geographic loan estimates.32 

We also decompose market-level changes in small business lending (and its components) 

into the parts attributable to consolidating institutions and the parts that reflect the response of 

other firms in the markets. Here we measure the change in lending attributable to consolidating 

organizations as equal to the difference between the beginning-of-period (pro forma) estimates of 

local lending by all consolidating parties (including acquirers) and the end-of-period lending 

reported by the now-consolidated organizations. Because this calculation includes the lending of 

acquirers, it differs somewhat from our calculation of consolidation activity in a market, which is 

based solely on the lending of the acquired components of the organization. Consequently, in 

computing loan growth attributable to consolidating institutions, we further differentiate between 

32 Note that holding company acquisitions do not affect our geographic loan calculations because the holding 

company affiliates report separate bank-level Summary of Deposits and Call Report data at both the beginning and 

the end of the study period; thus, the adjustment is not necessary. In contrast, although mergers of holding company 

affiliates are not considered consolidations by our definition, these mergers can affect the estimates of local small 

business lending and are therefore they are adjusted for in the computing of beginning-of-period local small business 

loan measures used to study changes in lending over time. 

41 
situations in which the organization had more than one component operating in the market at the 

beginning of the period (a within-market acquisition) and situations in which only one 

component operated. In the latter case, we can differentiate according to whether the market 

participant was the acquirer or was acquired. 

In measuring the contribution of nonconsolidating institutions to market-level small 

business loan growth, we differentiate between institutions that operated in the market at the 

beginning of the period (existing institutions) and those that did not (new entrants). New entrants 

could be either institutions that operated in other markets at the beginning of the period and 

added de novo branches in the market or de novo institutions that did not operate in any market 

at the beginning of the period. Within the group of consolidating and nonconsolidating 

institutions, we further differentiate between the contributions of community banks and the 

contributions of large banking organizations. 

Changes in community bank market share 

As noted above, in studying changes in community bank small business loan market 

shares in local banking markets (for small business loans and each of their components: C&I 

loans and CRE loans, loans under $100,000, and loans over $100,000), we distinguish between 

pro forma changes due to reclassifications in bank size and community bank market share 

changes net of these pro forma changes. We measure the change in community banks’ share of 

small business lending for a given market in a given study period in the manner that follows. For 

a given small business loan measure, each of the pro forma change components (attributable to 

community banks’ being absorbed into larger institutions or to community banks’ growing out of 

the $1 billion asset-size cutoff is calculated by use of the beginning-of-period pro forma market 

42 
 

share that reclassifies the loans of community banks that will no longer be community banks by 

the end of the period. Note that if a community bank merger results in an institution that still has 

assets below the $1 billion dollar size threshold, the merger will not affect the pro forma merger 

calculation. The same is true for community banks that are growing but remain below the assetsize threshold at the end of the period. The pro forma change is then computed as the difference 

between the pro forma market share and the beginning-of-period community bank market share 

(technically the pro forma change could be positive if a large banking organization contracted 

into a community bank, but generally the pro forma change components are not positive).33 The 

net change in community bank market share is thus equal to the end-of-period community bank 

market share less the two pro forma change components. Netting out the pro forma components 

due to size reclassifications allows us to examine the extent to which community banks have 

grown their market share—growth that is obscured if one looks only at the gross change in 

community bank market shares over time. 

33 As with the computation of our small business loan growth measures, we adjust the small business loan allocations 

used to compute beginning-of-period community bank market share measures to remove any possible changes due 

only to the merging of bank charters. Specifically, the beginning-of-period local small business lending of a bank 

that merges with another bank during the study period is estimated on the basis of the pro forma distribution of 

beginning-of-period deposits implied by the merger. The classification of this lending as community bank lending as 

opposed to large organization lending is then determined by the asset size of the bank’s organization at the beginning 

of the period. 

43 
 

REFERENCES 

Avery, R. B., R. W. Bostic, P. S. Calem, and G. B. Canner. “Consolidation and Bank Branching 

Patterns.” Journal of Banking and Finance 23 (1999a), 497-532. 

———. “Trends in Home Purchase Lending: Consolidation and the Community Reinvestment 

Act.” Federal Reserve Bulletin 85(1999b), 81-102. 

Avery, R. B., and K. A. Samolyk. “Bank Consolidation and the Provision of Banking Services: 

The Case of Small Commercial Loans.” Working Paper 2000-01, Federal Deposit 

Insurance Corporation, 2000. 

Berger, A. N., S. D. Bonime, L. G. Goldberg, and L. J. White. “The Dynamics of Market Entry: 

The Effects of Mergers and Acquisitions on De Novo Entry and Small Business Lending in 

the Banking Industry.” Working Paper, Board of Governors of the Federal Reserve System, 

2000. 

Berger, A. N., R. Demsetz, and P. E. Strahan. “The Consolidation of the Financial Services 

Industry: Causes, Consequences, and Implications for the Future.” Journal of Banking and 

Finance 23 (1999), 135-194. 

Berger, A. N., L. G. Goldberg, and L. J. White. “The Effects of Dynamic Changes in Bank 

Competition on the Supply of Small Business Credit.” European Finance Review 5 

(2001), 115-139. 

Berger, A. N., A. Saunders, J. M. Scalise, and G. F. Udell. “The Effects of Bank Mergers and 

Acquisitions on Small Business Lending.” Journal of Financial Economics 50 (1998), 

187-229. 

Berger, A. N., and G. F. Udell. “The Economics of Small Business Finance.” Journal of 

Banking and Finance 22 (1998), 613-673. 

Cyrnak, A. W. “Bank Merger Policy and the New CRA Data.” Federal Reserve Bulletin 84 

(1998), 703-715. 

DeYoung, R., L. G. Goldberg, and L. J. White. “De Novo Banks and Lending to Small 

Businesses.” Journal of Banking and Finance 22 (1998), 463-492. 

Keeton, W. R. “The Effects of Mergers on Farm and Business Lending at Small Banks: New 

Evidence from Tenth District States.” Working Paper, Federal Reserve Bank of Kansas 

City, 1997. 

44 
 

———. “Are Mergers Responsible for the Surge in New Bank Charters?” Federal Reserve 

Bank of Kansas City Economic Review, Quarter 1 (2000), 21-41. 

Morgan, D. P., and K. A. Samolyk. “Geographic Diversification in Banking: Implications for 

Bank Portfolios and Performance.” Working Paper, Federal Deposit Insurance 

Corporation, 2003 (forthcoming). 

Peek, J., and E. S. Rosengren. “Bank Consolidation and Small Business Lending: It’s Not Just 

Size That Matters.” Journal of Banking and Finance 22 (1998), 799-819. 

Samolyk, K. A. “Small Business Credit Markets: Why Do We Know So Little About Them?” 

FDIC Banking Review 10:2 (1997), 14-32. 

Samolyk, K. A., and C. Richardson. “Bank Consolidation and Small Business Lending within 

Local Banking Markets.” Working Paper 2003-02, Federal Deposit Insurance Corporation, 

2003. 

Seelig, S. A., and T. Critchfield. “Determinants of De Novo Entry in Banking.” Working Paper 

2003-01, Federal Deposit Insurance Corporation, 2003. 

Strahan, P. E., and J. Weston. “Small Business Lending and the Changing Structure of the 

Banking Industry. Journal of Banking and Finance 22 (1998), 821-845. 

Whalen, G. “Out-of-State Holding Company Affiliations and Small Business Lending.” 

Economic and Policy Analysis Working Paper 95-4, Office of the Comptroller of the 

Currency, 1995. 

45 
Table A.3: Effects of Overall Consolidation Activity (CA) and Local Community Bank (CB) Market Share on Small Business Loan Growth: 1997-2000 

Effects on small business loan (SBL) growth and its decompositions into loans under and over $100,000 and CRE versus C&I loans. Estimated coefficients and standard 

errors (reported in parentheses) for all explanatory variables 

Urban Markets Rural Markets 

Total SBL <$100K SBL >$100K SBL CRE SBL C&I SBL Total SBL <$100K SBL >$100K SBL CRE SBL C&I SBL 

Intercept 29.961 

(10.34) 

*** 2.778 

(7.050) 

27.182 

(7.761) 

*** 16.456 *** 

(5.827) 

13.504 

(8.009) 

* 55.449 

(10.38) 

*** 29.772 

(8.384) 

*** 25.676 

(8.938) 

*** 35.310 

(7.666) 

*** 20.138 

(5.483) 

*** 

Overall CA 

CB SBL mkt share 

0.102 

(0.052) 

-0.016 

(0.046) 

* 0.084 ** 

(0.036) 

-0.025 

(0.032) 

0.018 

(0.039) 

0.009 

(0.035) 

0.002 

(0.030) 

-0.015 

(0.026) 

0.100 

(0.041) 

0.000 

(0.036) 

** 0.021 

(0.042) 

-0.003 

(0.032) 

0.057 

(0.034) 

-0.047 

(0.026) 

* 

* 

-0.036 

(0.036) 

0.044 

(0.028) 

0.016 

(0.031) 

-0.005 

(0.024) 

0.005 

(0.022) 

0.002 

(0.017) 

Number of banks 

Deposit Herfendahl 

Offices per-capita 

Deposits per-capita 

Deposit growth lagged 

Deposit growth current 

Thrift deposit share 

Population lagged 

Pop. growth lagged 

Pop. growth current 

Per-cap income lagged 

PC income growth lagged 

PC income growth current 

UE rate lagged 

UE rate change lagged 

UE rate change current 

House price index chg lagged 

House price index chg current 

Bldg permits % chg lagged 

Bldg permits % chg current 

0.104 

(0.120) 

0.002 

(0.002) 

-0.559 

(1.575) 

-4.389 

(4.337) 

-0.002 

(0.062) 

0.785 

(0.061) 

0.033 

(0.087) 

-0.052 

(0.038) 

-0.037 

(0.632) 

0.728 

(0.710) 

-6.257 

(3.337) 

0.452 

(0.321) 

0.231 

(0.317) 

-0.443 

(0.414) 

1.633 

(0.898) 

1.749 

(1.015) 

0.125 

(0.157) 

-0.004 

(0.155) 

-0.002 

(0.048) 

-0.106 

(0.045) 

*** 

* 

* 

* 

** 

0.069 

(0.082) 

0.001 

(0.001) 

0.377 

(1.074) 

-1.776 

(2.957) 

-0.059 

(0.042) 

0.343 *** 

(0.042) 

0.005 

(0.059) 

-0.008 

(0.026) 

-0.075 

(0.431) 

0.238 

(0.484) 

-1.842 

(2.275) 

0.302 

(0.219) 

-0.008 

(0.216) 

-0.244 

(0.283) 

0.386 

(0.613) 

0.890 

(0.692) 

-0.158 

(0.107) 

0.022 

(0.105) 

-0.009 

(0.033) 

-0.046 

(0.031) 

0.035 

(0.090) 

0.001 

(0.001) 

-0.936 

(1.182) 

-2.613 

(3.255) 

0.056 

(0.047) 

0.442 

(0.046) 

0.029 

(0.065) 

-0.044 

(0.028) 

0.039 

(0.474) 

0.490 

(0.533) 

-4.415 

(2.504) 

0.150 

(0.241) 

0.239 

(0.238) 

-0.199 

(0.311) 

1.247 

(0.674) 

0.859 

(0.762) 

0.283 

(0.118) 

-0.026 

(0.116) 

0.007 

(0.036) 

-0.060 

(0.034) 

*** 

* 

* 

** 

* 

0.019 

(0.068) 

0.000 

(0.001) 

0.312 

(0.888) 

-3.963 

(2.444) 

0.028 

(0.035) 

0.174 *** 

(0.035) 

-0.009 

(0.049) 

-0.028 

(0.021) 

0.489 

(0.356) 

0.266 

(0.400) 

-1.918 

(1.880) 

0.020 

(0.181) 

-0.059 

(0.179) 

-0.175 

(0.234) 

0.795 

(0.506) 

0.579 

(0.572) 

0.106 

(0.089) 

0.097 

(0.087) 

0.016 

(0.027) 

-0.037 

(0.025) 

0.085 

(0.093) 

0.003 

(0.002) 

-0.871 

(1.220) 

-0.425 

(3.359) 

-0.030 

(0.048) 

0.611 

(0.048) 

0.042 

(0.067) 

-0.024 

(0.029) 

-0.526 

(0.489) 

0.462 

(0.550) 

-4.339 

(2.584) 

0.432 

(0.249) 

0.290 

(0.246) 

-0.268 

(0.321) 

0.838 

(0.696) 

1.171 

(0.786) 

0.019 

(0.122) 

-0.101 

(0.120) 

-0.018 

(0.037) 

-0.068 

(0.035) 

* 

*** 

* 

* 

* 

-0.133 

(0.487) 

-0.006 

(0.002) 

1.238 

(0.856) 

-25.47 

(3.170) 

0.092 

(0.114) 

1.199 

(0.056) 

0.021 

(0.063) 

-1.293 

(0.493) 

0.239 

(0.373) 

-0.515 

(0.446) 

6.467 

(3.470) 

0.151 

(0.241) 

0.331 

(0.269) 

-0.603 

(0.414) 

-0.022 

(0.533) 

0.277 

(0.606) 

0.154 

(0.157) 

-0.391 

(0.174) 

-0.056 

(0.032) 

-0.036 

(0.032) 

*** 

*** 

*** 

*** 

* 

** 

* 

0.023 

(0.393) 

-0.004 

(0.001) 

0.460 

(0.691) 

-12.20 

(2.560) 

0.180 

(0.092) 

0.593 

(0.045) 

0.004 

(0.051) 

-1.085 

(0.398) 

-0.186 

(0.302) 

-0.322 

(0.360) 

1.913 

(2.802) 

-0.091 

(0.194) 

0.117 

(0.218) 

-0.128 

(0.334) 

-0.549 

(0.431) 

0.360 

(0.490) 

-0.168 

(0.126) 

-0.200 

(0.140) 

-0.019 

(0.026) 

-0.042 

(0.026) 

*** 

*** 

* 

*** 

*** 

-0.155 

(0.419) 

-0.003 

(0.001) 

0.778 

(0.737) 

-13.28 

(2.729) 

-0.088 

(0.098) 

0.605 

(0.048) 

0.017 

(0.054) 

-0.207 

(0.425) 

0.424 

(0.321) 

-0.192 

(0.384) 

4.554 

(2.987) 

0.242 

(0.207) 

0.214 

(0.232) 

-0.475 

(0.356) 

0.528 

(0.459) 

-0.082 

(0.522) 

0.322 

(0.135) 

-0.191 

(0.150) 

-0.037 

(0.027) 

0.007 

(0.028) 

* 

*** 

*** 

** 

-0.332 

(0.360) 

-0.005 

(0.001) 

0.828 

(0.632) 

-14.73 

(2.341) 

0.091 

(0.084) 

0.748 

(0.042) 

0.002 

(0.047) 

-0.690 

(0.364) 

0.255 

(0.276) 

-0.096 

(0.330) 

4.398 

(2.562) 

-0.027 

(0.178) 

0.176 

(0.199) 

-0.239 

(0.306) 

-0.461 

(0.394) 

0.562 

(0.448) 

0.075 

(0.116) 

-0.249 

(0.128) 

-0.051 

(0.023) 

-0.038 

(0.024) 

*** 

*** 

*** 

* 

* 

* 

** 

0.199 

(0.257) 

-0.002 

(0.001) 

0.410 

(0.452) 

-10.75 

(1.674) 

0.001 

(0.060) 

0.451 

(0.030) 

0.019 

(0.033) 

-0.603 

(0.261) 

-0.016 

(0.197) 

-0.419 

(0.236) 

2.069 

(1.833) 

0.177 

(0.127) 

0.156 

(0.142) 

-0.364 

(0.219) 

0.440 

(0.282) 

-0.284 

(0.320) 

0.079 

(0.083) 

-0.142 

(0.092) 

-0.005 

(0.017) 

0.002 

(0.017) 

** 

*** 

*** 

** 

* 

* 

R-Square 

Sample size 

Dependent variable mean 

0.486 

292 

16.344 

0.272 

292 

-0.573 

0.414 

292 

16.918 

0.302 

292 

8.944 

0.440 

292 

7.401 

0.432 

760 

18.980 

0.226 

760 

0.220 

0.231 

760 

18.760 

0.366 

760 

12.040 

0.272 

760 

6.937 

Note: *, **, *** indicate significance levels of 10%, 5%, and 1%, respectively.