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Determinants of Efficiency of Law Firms

Determinants of Efficiency of Law Firms. Presenter: EunYoung Whang Coauthors: Rajiv Banker, Marina Angel Temple University July 11, 2009. Organizational Changes. During last three decades, law firms have changed dramatically

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Determinants of Efficiency of Law Firms

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  1. Determinants of Efficiency of Law Firms Presenter: EunYoungWhang Coauthors: Rajiv Banker, Marina Angel Temple University July 11, 2009

  2. Organizational Changes • During last three decades, law firms have changed dramatically • Total number of lawyer have more than tripled in 2008 compared to 1984 (AmLaw 100) • Transition from “boutique” law firms to “megafirms” that provides specialized and full-line legal services globally • Expansion of partnership structure from one-tier to multi-tier partnership

  3. Megafirms • Some law firms have grown • To provide full line of legal service in different specializations • To have more resources to attract big corporate and institutional clients • To expand geographical reach, especially in international market

  4. Multi-Tier Partnerships • Adopted to retain and motivate talented lawyers with more promotion opportunities • One-tier partnership law firms have only equity partners • Two-tier partnership law firms have both equity and non-equity partners • Only 20% of AmLaw 100 firms have one-tier partnership in 2008, down from 55% in 1994 • Number of non-equity partners is increasing at a faster rate than equity partners and may have diluted the “rain-making” intensity of senior partners

  5. Lawyer Leverage • Unlike manufacturing firms, law firms assets are human capital resources; equity partners, non-equity partners, and lawyers • More lawyers per partners leverages the talent and ability of partners • Very high span-of-control may affect ability to manage effectively

  6. Apparent Contradictions? • Baker & McKenzie ranked first by the number of lawyers but ranked 98 out of 100 firms in terms of revenue per lawyer(RPL)(AmLaw 100, 2008) • Wachtell, Lipton, Rosen & Katz ranked last in terms of the number of lawyers but ranked first in terms of RPL (AmLaw 100, 2008)

  7. Hypotheses • Hypothesis 1: The size of law firms is positively related to productivity • Hypothesis 2: The proportion of non-equity partners has a negative relationship with productivity • Hypothesis 3: Higher leverage (lawyers : partners ratios) is associated with higher productivity

  8. Two-Stage DEA Analysis • Banker & Natarajan(2008) prove the estimator is consistent • 1st stage: Estimate efficiency score with DEA • 2nd stage: Regress efficiency score on contextual variables • Recent Monte Carlo evidence shows this simple approach outperforms the bootstrap approach

  9. Data • AmLaw 100 dataset provides for human capital resource and financial data • Sample period: 2000~2007 • Sample size: 648 firm-year observations (81 law firms * 8 years)

  10. Human Resources Inputs • Equity partners - highest job title (most highly compensated) - have ownership (share profit & loss) - rainmaker and most productive personnel • Non-equity partners - intermediate step to become equity partner - paid fixed salary (do not share profit & loss) • Lawyers - do most of legal work in law firm - paid fixed salary (do not share profit & loss)

  11. Output Variable • Gross revenue: fee income generated from legal work • Deflated by Consumer Price Index(CPI)

  12. DEA Estimation Models • Technical Efficiency: Banker, Charnesand Cooper (BCC) (1984) • Aggregated Efficiency: Charnes, Cooper and Rhodes(CCR)(1978, 1981) • Scale Efficiency = CCR Efficiency/BCC Efficiency • Estimated (1) year-by-year, (2) pooled

  13. Efficiency Trends from Pooled Estimation

  14. Test of Returns to Scale

  15. Returns to Scale Inference Y CRS IRS 0 X

  16. Second Stage Model Log(θ) = f{Size, %Non-equity partners, Leverage, Control Variables} • Controlvariables: - Regional firm - International firm - Geographic regions - Post-merger - Year trend(for pooled analysis)

  17. Variable Measurement

  18. Dealing with Panel Data • Fama-McBeth Regressions: year-by-year cross-sectional model • Prais-WinstenRegression: pooled efficiency

  19. Fama-MacBeth Regression Results

  20. Prais-Winsten Regression Results

  21. Robustness Check • One stage parametric production functions with contextual variables - Translog function - Cobb-Douglas function • Same control variables as in the DEA models

  22. Parametric Function Results

  23. Conclusion • Organizational changes have resulted in productivity improvement in law firms during 2000 – 2007 • Technical efficiency (BCC) increases with - the size of law firm • smaller proportion of non-equity partners • the degree of leverage

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