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Bank Holding Company Diversification and Production Efficiency Elyas Elyasiani Temple University Yong Wang Western New E

Bank Holding Company Diversification and Production Efficiency Elyas Elyasiani Temple University Yong Wang Western New England College. 1. 1. Background of Legislation Change.

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Bank Holding Company Diversification and Production Efficiency Elyas Elyasiani Temple University Yong Wang Western New E

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  1. Bank Holding Company Diversification and Production EfficiencyElyas ElyasianiTemple UniversityYong WangWestern New England College 1 1

  2. Background of Legislation Change Glass-Steagall Act (1933) and Bank Holding Company Act (1956) prohibit BHCs from getting involved in securities and insurance business. In1987, Federal Reserve allowed BHCs to establish Section 20 subsidiaries and deal in “bank-ineligible” securities. The limit of revenue from such activities to the subsidiary’s total revenue was raised from 5% to 10% in 1989, and then to 25% in 1997. Gramm–Leach–Bliley Act of 1999 (GLBA) allowed BHCs to become FHCs and to get involved into brokerage, advisory, underwriting, and insurance. This serves as a vehicle for product diversification. 2

  3. Trend of Diversification • At year-end 2007, 660 BHCs had elected to become FHCs. (Federal Reserve). Not all of these FHCs actually engage in investment banking and insurance activities. • From 2000 to 2003, assets of securities underwriting and dealing subsidiaries of FHCs grew by two-third, assets of their insurance underwriting and dealing subsidiaries tripled. (Report to the congress of FHCs under the GLBA, 2003). • 16% of FHCs total revenue in 2004 came from the newly permissible activities. (Yeager et al, 2007). • Former Senator Phil Gramm referred to GLBA as: “the most important banking bill in 60 years”, and one that “opens up new competition”.

  4. Motivation Is activity diversification beneficial to BHCs? Literature shows a mixed picture: Stiroh and Rumble (2006): Diversification increases risk but lowers return Laeven and Levine (2007): Diversification lowers Tobin’s Q. Baele et al. (2007): Diversification leads to a higher franchise value (long term potential). Deng et al. (2007): Diversification lowers cost of debt. Our question of interest: Does diversification affect BHCs’ production efficiency? Is it efficiency-enhancing or efficiency-reducing? 4

  5. Motivation (continued) Exploring whether activity diversification changes production efficiency offers an alternative way for testing the differences between diversified vs. focused BHCs. The results will help explaining the possible value difference of diversified BHCs. The results also have implications on the vast literature on corporate diversification discount, which remains a puzzle. There are implications for bank managers, investors in bank stocks and bank regulators about BHCs’ diversification vs focus strategy after GLBA. Specifically, is diversification or focus the way to improving efficiency? What are thepros and cons? 5

  6. Diversification May Improve Efficiency: Channels Increased competition and pressure from takeover markets due to the fact that the borders among banks, IBs and ICs are blurred (Prowse, 1997; Mester, 1989; Jayaratne and Strahan, 1998). Competition intensifies because there will be more players e.g., in insurance activities and investment banking from the FHCs. There will be a threat of takeover from a broader set of entities because FHCs ca now takeover IBs and ICs. 6

  7. Diversification May Improve Efficiency: Channels • Economies of scale and scope (Berger et al., 1999; Hughes et al., 2001; Stiroh, 2000) because of: • Technology indivisibility • Input reutilization, e.g., Information sharing, • Joint account maintenance • long term relationship (Denis and Mihov, 2003; Saunders and Walter, 1994; Kashyap et al., 2002). • Department-store type convenience for customers

  8. Diversification May Hinder Efficiency: Channels • Potential diseconomies of scale and scope: Scale economies may have been exhausted before GLBA. (Reichert and Wall, 2000; Yeager et al., 2007; Wheelock and Wilson, 2001) • More complex structure, bureaucracy and red tape, less effective monitoring and less effective regulation (Elyasiani and Wang, 2008; Barth et al., 2000) • More firms qualify as “Too-big-to-fail” (Mester, 2007; Barth et al., 2000). Some IB-ICs may become BHCs (fin crisis 08) • Dilution of core competencies (Prahalad and Hamel, 1990; Capon et al., 1988; Markides and Williamson, 1994) 8

  9. Are BHCs with Section 20 Subsidiaries Special? • At year end 1999, there were 45 domestic BHCs with Section 20 Subsidiaries. • Mamunet al. (2005) show that BHCs with section 20 subsidiaries demonstrated a stronger positive market reaction to GLBA. What is the rationale? These BHCs may have benefited from first mover advantages or suffered disadvantages: • First Mover Advantages (Lieberman & Montgomery, 1998): • Established relationships and reputation • Technological leadership, • Preemption of scarce assets, • Switching costs and buyer choice uncertainty 9

  10. Are BHCs with Section 20 Subsidiaries Special? • First Mover Disadvantages (Lieberman & Montgomery, 1998): • Free-rider effects, • Resolution of technological or market uncertainty over time, • Shift in technology (obsolesence) • Shift in customer needs, • Incumbent inertia

  11. Production Efficiency of BHCs • The aim is to look inside the “black box” of the conglomerates and examine their production units. (Schoar, 2002) • Obstacles in construction of efficiency measures at FHC level: • Heterogeneous outputs, • Different regulation for different segments of FHCs, • Numerous M&As • To avoid these problems, we examines the production efficiency of the lead CB. This allows us: • To define a relatively homogeneous inputs and outputs, • To examine the efficiency of largest entity of BHCs (average 87% of assets) 11

  12. Hypothesis • H1: Activity diversification of the BHCs improves the productive efficiency of their largest subsidiary commercial bank. • H2: BHCs that had Section 20 subsidiaries benefited more from (or were hurt less by) activity diversification than BHCs that did not have such subsidiaries. 12

  13. Efficiency Studies • Berger et al. (1993), Berger and Mester (1997), Berger and Humphrey (1997) offer excellent surveys. • Nonparametric approaches: • Data Envelopment Analysis (DEA): (Banker, 1996; Isik and Hassan, 2003; Cummins and Xie, 2008) • Free Disposal Hull Approach : (Fried et al., 1993; Fried and Lovell, 1994) • Parametric approaches • Stochastic Frontier Approach, Distribution-Free Approach, and Thick Frontier Approach.

  14. Pros and Cons of DEA • DEA does not require specification of the production function. • DEA production efficiency does not require prices of inputs and outputs. • Malmquist productivity index considers efficiency cross-sectionally, and efficiency change over time. • Decomposition of Malmquist index reveals detailed information on efficiency change. • Disadvantage: no random error specification.

  15. Production Specification • Input Oriented Data Envelopment Analysis (DEA) Best practice DMU: no other DMUs or linear combination of DMUs can use as little or less inputs to produce the same amount of outputs. Production frontier: piecewise linear combination that connects the set of best practice DMUs. Technical Efficiency: the ratio of inputs by a DMU to inputs by the DMU on production frontier in order to generate the same amount of outputs.

  16. Efficiency and Productivity One input one output industry Average Productivity (AP) = OA”/OA’ CRS: Technical Efficiency (TEC)=A”I/A”A VRS: Technical Efficiency (TEV)=A”J/A”A Y (Output) CRSt VRSt I A(xt,yt) A” J X (Input) O A’ 16

  17. Efficiency and Productivity Change Over Time One input one output industry Average Productivity Change (TFPCH) = APt+1/APt= (OB”/OB’) / (OA”/OA’) Pure Efficiency Change (PEFFCH) = TEVT+1/ TEVT =(B”D/B”B) / (A”J/A”A) Y (Output) CRSt+1 VRSt+1 CRSt C VRSt B” D B(xt+1,yt+1) A” A(xt,yt) I J X (Input) O A’ B’ 17

  18. Sample Selection • BHC and CB dataset from Fed Chicago: Call Reports • Sample period: 1997-2007. • CB with assets > $500M • Data available every year • Largest entity of the ultimateparent BHC • Did not change ultimate parent BHC in sample period • Sample: balanced dataset of 164 CB-BHCs for 11 yrs.

  19. Inputs and Outputs • We follow the intermediation approach of bank production (Hughes and Mester, 1993; Elyasiani and Mehdian, 1990) • Four inputs-three outputs model Inputs: labor; fixed assets; deposits; other non-interest expenses Outputs: loans; securities; non-interest income • Four inputs-four outputs model Same inputs Outputs: loans; securities; trading; non-interest income 19

  20. The format of the FR Y-9C form changes in recent years>>, to construct consistent data across time, income diversification include: 1) interest income; 2) income from fiduciary activities; 3) service charges, commissions, and fees; 4) trading revenue; and 5) other non-interest income Hirschman- Herfindahl Index (Hughes et al., 1999; Deng et al., 2007) Diversification Measure 20 20

  21. Sample Description 21

  22. Group Means Comparison Note: *, **, and *** denote the significance of 10%, 5%, and 1%, respectively 22

  23. Average Technical Efficiency Each YearVRS, 4-inputs-3-outputs production model Note: c denotes the significance of 1% 23

  24. Diversification and Production Efficiency *, **, and *** denotes significant at 10%, 5%, and 1% level, respectively.

  25. TFPCH and PEFFCH Each YearVRS, 4-inputs-3-outputs production model TFPCH: Total Factor Productivity Change; PEFFCH: Pure Efficiency Change 25

  26. Figure 3: Cumulative Pure Efficiency Change Over Time Figure 2: Cumulative Total Factor Productivity Change Over Time Others Section20 Others Section20 Cumulative Cumulative TFPCH PEFFCH 1.2 1.2 1.15 1.1 1.1 1 1.05 1 0.9 0.95 0.8 0.9 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Year Year

  27. Diversification, TFPCH, and PEFFCH *, **, and *** denotes significant at 10%, 5%, and 1% level, respectively.

  28. Robustness Tests • Technical Efficiency (TE) is also constructed under constant returns to scale (CRS). Total Factor Productivity Change (TFPCH) and Pure Efficiency Change (PEFFCH) are identical under CRS and VRS. • TE, TFPCH, and PEFFCH are constructed in four-inputs-four-outputs production model under both CRS and VRS. • Diversification measure is constructed using 13 different income items (2001-2007) of FR Y-9C.

  29. Conclusions • Activity diversification is negatively associated with technical efficiency. The effect is primarily driven by BHCs that did not have Section 20 subsidiaries before GLBA. • Change in diversification over time is not associated with total factor productivity change. • Change in diversification over time is negatively associated with pure efficiency change. This effect is also driven by BHCs didn’t have Section 20 subsidiaries before GLBA. • First mover advantage of BHCs with Section 20 subsidiaries helps to alleviate the negative effect of diversification on technical efficiency.

  30. Contribution and Implication • Look inside the “black box” of BHCs by examining their subsidiaries’ production efficiency and link it to diversification. • The finding is conceptually consistent with the diversification discount argument in Laeven and Levine (2007). Lower efficiency results in value discount. • Post-GLBA business strategy for BHCs, with and without Section 20 experience matters. • Activity diversification may not be a remedy for improving production efficiency, especially it is not a one-size-fit-all solution.

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