Do Competitive Advantages Lead to Higher Future Rates of Return?

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1 Do Compeiive Advanages Lead o Higher Fuure Raes of Reurn? Vicki Dickinson Universiy of Florida Greg Sommers Souhern Mehodis Universiy 2010 CARE Conference Forecasing and Indusry Fundamenals April 9, 2010

2 Research Quesions Wha is a compeiive advanage? Do compeiive advanages lead o increased fuure profiabiliy? Using ex-pos realizaions of profiabiliy, we measure success of compeiive advanages as: Explanaory power Persisence

3 Why is I Imporan? Managerial decision-making Where should he firm concenrae is resources and effor? Analysis conex Examining he behavior of operaing income by compeiive advanages refines he predicive value of is componens Seady sae versus posiive/negaive growh raes (implicaions for runcaion period) Imporan for boh equiy invesors and crediors

4 Compeiive Advanage Candidaes Tradiional Economies of Scale Produc Differeniaion Innovaion Capial Requiremens Expanded Power over Suppliers Power over Cusomers Credible Threa of Expeced Realiaion (financial flexibiliy)

5 Pariculars Profiabiliy Reurn on Ne Operaing Asses (RNOA) Adjus for Risk Wihin Indusry Analysis Sudy mean effecs and condiion on level of compeiive advanage effor o sudy over-ime effecs One-year and five-years ahead horizon Sample 1972 o ,220 firm-year observaions

6 Overview of Resuls Larges reurns come from power over suppliers and he credible hrea of expeced realiaion Resul in a 3% risk- and indusry-adjused RNOA premium even afer 5 years Bargaining power over cusomers resuls in modes long-erm gains Tradiional advanages such as produc differeniaion, innovaion and capial inensiy are no effecive a proecing fuure profiabiliy

7 Reurn on Ne Operaing Asses (RNOA) Measure of operaing profiabiliy (Nissim and Penman 2001) Shown o be more relevan for forecasing fuure profiabiliy han ROE or ROA (Fairfield e al 1996) Effecs of financial leverage are eliminaed Zero NPV aciviies ha canno be a susainable source of profiabiliy

8 Risk-Adjused Profiabiliy Differences in risk among firms may conribue o he level of profiabiliy needed o generae a normal reurn or o non-convergence of profiabiliy over ime Imporan o risk-adjus profiabiliy o separae differences in risk from effecs of compeiive advanages Risk-adjusmen process is innovaion in his paper

9 Risk of Operaions Mos prior sudies focus on equiy risk Need a measure of operaional risk Cos of capial for operaions versus cos of capial for equiy Operaional risk will no be depend on source of financing

10 Risk-Adjusmen Mehod Use mehod from Eason and Sommers (JAR 2007) as saring poin Can esimae he cos of equiy capial using curren accouning daa eps bps p bps j δ ζ j j = 0 δ1 j 1 bps j 1 where δ 0 = r E, δ 1 = (r E g)/(1 g) j

11 Risk-Adjusmen Mehod (Coninued) This is ransformed o allow for esimaion of he cos of capial of operaions via he following regression equaion: OI NOA where V NOA Oper j j j = δ 0 δ1 e j j 1 NOAj 1 Oper δ 0 = r, δ ( r Oper g) 1 = ( 1 g) where V Oper = MVE NFO

12 Summary Saisics Median RNOA before risk-adjusmen = 10.4% Nissim and Penman (2001) repored 10.0% Median RNOA afer risk-adjusmen = 3.3% Implied cos of capial for operaions of 7.1%

13 Indusry Adjusmen Conrolling for indusry eliminaes differences in operaing cycle, business model, resources, growh, and echnology across indusries Allows for generalizabiliy across indusries wihin economy Use Fama and French (1997) 48 classificaions o adjus dependen and independen variables

14 Descripive Saisics Table 2 Median RNOA RA is 3.3% Highes RNOA RA indusries: Tobacco (10.1%), Trading (9.4%), Insurance (8.3%), Defense (7.2%), Prining (5.8%), Consumer Goods (5.2) Lowes RNOA RA indusries: Coal (0.9%), Medical Equipmen (1.1%), Precious Meals (1.1%), Communicaions (1.2%), Real Esae (1.3%), Agriculure (1.5%), Peroleum (1.7%), Lab Equipmen (1.7%), Candy (1.7%)

15 Base Model RA RA RA NOA RNOA 1 = 0 1RNOA 2 RNOA 3G 4 Age 5OpSize ε Conrol for curren level and change in profiabiliy Serially correlaed wih fuure profiabiliy (Fairfield and Yohn 2001) Conrol for growh in NOA (denominaor) Firm-level conrols Age Size of operaions (MVE NFO) Vary dependen variable by horizon 1, 5

16 Expanded Models ε = NOA RA RA RA ExFunds FLev MkShr ARTurn InvTurn OLLev CapIn Innov AdvIn CoS OpSize Age G RNOA RNOA RNOA ε = NOA RA RA RA ExFunds ExFunds FLev FLev MkShr MkShr ARTurn ARTurn InvTurn InvTurn OLLev OLLev CapIn CapIn Innov Innov AdvIn AdvIn CoS CoS OpSize Age G RNOA RNOA RNOA Tradiional: Expanded: Diminishing Reurns: ε = NOA RA RA RA CapIn Innov AdvIn CoS OpSize Age G RNOA RNOA RNOA

17 % Increases in Explanaory Power (Adj. R 2 ) 1 % Inc. over: Tradiional Expanded Dim. Reurns Base 6.72% 25.15% 32.53% Tradiional Expanded % Inc. over: Tradiional Expanded Dim. Reurns Base 35.68% 78.12% % Tradiional Expanded 17.26

18 Regression Resuls: RNOA 1 (Model 4) Base & Conrols Tradiional Expanded Coeff. -sa Coeff. -sa Coeff. -sa Inercep CoS OLLev RNOA ΔCoS ΔOLLev ΔRNOA AdvIn InvTurn G NOA ΔAdvIn ΔInvTurn Age Innov ARTurn OpSize ΔInnov ΔARTurn CapIn MkShr ΔCapIn ΔMkShr FLev ΔFLev ExFund ΔExFund Adjused R 2 =.2196

19 Convergence Analysis Deermines wheher curren level of compeiive advanage resuls in susainable fuure profiabiliy over five subsequen years Inheren survivorship bias Should bias oward convergence (and herefore agains resuls)

20 Convergence of Indusry- and Risk- Adjused RNOA over 5-Year Horizon 0.30 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

21 Convergence based on Economies of Scale 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

22 Convergence based on Adv. Inensiy Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid High

23 Convergence based on Innovaion 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low o Mid-Low M id M id-high High

24 Convergence based on Capial Inensiy 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

25 Convergence based on Operaing Liabiliy Leverage 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

26 Convergence based on 1 / Invenory Turnover 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

27 Convergence based on 1 / Receivables Turnover 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

28 Convergence based on Marke Share 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

29 Convergence based on Financial Leverage 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid-Low M id M id-high High

30 Convergence based on Excess Funds 0.08 Risk-Adjused Reurn on Ne Operaing Asses % Year Relaive o Porfolio Formaion Year Low Mid High

31 Concluding Remarks Greaes long-erm benefis come from power over suppliers and he credible hrea of expeced realiaion Proxies for radiional compeiive advanages such as produc differeniaion, innovaion, and capial inensiy are no effecive a proecing fuure profiabiliy