Understanding US firm efficiency and its asset pricing implications

  • Giovanni Calice
  • Levent KutluEmail author
  • Ming Zeng


We investigate the link between firm-level total factor productivity (TFP) growth, technical efficiency change, and their implications on firm-level stock returns. We estimate total factor productivity growth of US firms between 1966 and 2015 and decompose TFP growth into returns to scale, technical progress, and technical efficiency change components. We show that most of the variation in TFP growth is explained by variation in technical efficiency change. Moreover, we examine the effects of important macro- and micro-level factors on inefficiency as well as its asset pricing implications. We find that low-efficiency firms are more vulnerable to a wide class of aggregate economic shocks, and the well-known five stock return anomalies (Fama and French in J Financ Econ 116(1):1–22, 2015) are more pronounced among those firms. Our results also emphasize the role of macroeconomic determinants of efficiency, and the stability effects of many useful policy targets on firm-level TFP.


Asset prices Efficiency Frictions Stock return anomalies Total factor productivity 

JEL Classification

D22 D24 G12 



  1. Aigner DJ, Lovell CAK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econom 6:21–37CrossRefGoogle Scholar
  2. Avramov D, Chordia T, Jostova G (2013) Anomalies and financial distress. J Financ Econ 108:139–159CrossRefGoogle Scholar
  3. Barro RJ, Lee J-W (1993) International comparisons of educational attainment. J Monet Econ 32:363–394CrossRefGoogle Scholar
  4. Barro RJ, Lee J-W (1996) International measures of schooling years and schooling quality. Am Econ Rev 32:363–394Google Scholar
  5. Battese GE, Coelli TJ (1992) Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. J Prod Anal 3:153–169CrossRefGoogle Scholar
  6. Battese GE, Coelli TJ (1995) A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empir Econ 20:325–332CrossRefGoogle Scholar
  7. Bernanke BS, Gertler M, Gilchrist S (1999) The financial accelerator in a quantitative business cycle framework. Handb Macroecon 1:1341–1393CrossRefGoogle Scholar
  8. Brunnermeier MK, Sannikov Y (2014) A macroeconomic model with a financial sector. Am Econ Rev 104:379–421CrossRefGoogle Scholar
  9. Caudill SB, Ford JM, Gropper DM (1995) Frontier estimation and firm-specific inefficiency measures in the presence of heteroskedasticity. J Bus Econ Stat 13:105–111Google Scholar
  10. Christiano LJ, Eichenbaum M, Evans CL (2005) Nominal rigidities and the dynamic effects of a shock to monetary policy. J Polit Econ 113:1–45CrossRefGoogle Scholar
  11. Cochrane JH (2011) Presidential address: discount rates. J Financ 66(4):1047–1108CrossRefGoogle Scholar
  12. Demerjian P, Lev B, McVay S (2012) Quantifying managerial ability: a new measure and validity tests. Manag Sci 58:1229–1248CrossRefGoogle Scholar
  13. Espinoza RA, Prasad A, Leon MHL (2010) Estimating the inflation-growth nexus: A smooth transition model (No. 10–76). International Monetary FundGoogle Scholar
  14. Fama EF, French KR (1993) Common risk factors in the returns on stocks and bonds. J Financ Econ 33:3–56CrossRefGoogle Scholar
  15. Fama EF, French KR (2015) A five-factor asset pricing model. J Financ Econ 116(1):1–22CrossRefGoogle Scholar
  16. Fama EF, French KR (2016) Dissecting anomalies with a five-factor model. Rev Financ Stud 29:69–103CrossRefGoogle Scholar
  17. Fare R, Grosskopf S, Norris M, Zhang Z (1994) Productivity growth, technical progress, and efficiency change in industrialized countries. Am Econ Rev 84:66–83Google Scholar
  18. Gilchrist S, Sim JW, Zakrajšek E (2014) Uncertainty, financial frictions, and investment dynamics (No. w20038). National Bureau of Economic ResearchGoogle Scholar
  19. Gorodnichenko Y, Weber M (2016) Are sticky prices costly? Evidence from the stock market. Am Econ Rev 106:165–199CrossRefGoogle Scholar
  20. Habib MA, Ljungqvist A (2005) Firm value and managerial incentives: a stochastic frontier approach. J Bus 78:2053–2094CrossRefGoogle Scholar
  21. Hadlock CJ, Pierce JR (2010) New evidence on measuring financial constraints: moving beyond the kz index. Rev Financ Stud 23:1909–1940CrossRefGoogle Scholar
  22. Hall BH (1990) The manufacturing sector master file: 1959–1987 (No. w3366). National Bureau of Economic ResearchGoogle Scholar
  23. Hall BH, Mairesse J (1995) Exploring the relationship between R&D and productivity in French manufacturing firms. J Econom 65:263–293CrossRefGoogle Scholar
  24. Hong H, Sraer DA (2016) Speculative betas. J Finance 71:2095–2144CrossRefGoogle Scholar
  25. Imrohoroglu A, Tuzel S (2014) Firm-level productivity, risk, and return. Manag Sci 60:2073–2090CrossRefGoogle Scholar
  26. Kumbhakar SC, Lovell CK (2003) Stochastic frontier analysis. Cambridge University Press, CambridgeGoogle Scholar
  27. Kung H, Schmid L (2015) Innovation, growth, and asset prices. J Finance 70:1001–1037CrossRefGoogle Scholar
  28. Levinsohn J, Petrin A (2003) Estimating production functions using inputs to control for unobservables. Rev Econ Stud 70:317–341CrossRefGoogle Scholar
  29. Lin X (2012) Endogenous technological progress and the cross-section of stock returns. J Financ Econ 103:411–427CrossRefGoogle Scholar
  30. Meeusen W, van den Broeck J (1977) Efficiency estimation from Cobb Douglas production functions with composed error. Int Econ Rev 18:435–444CrossRefGoogle Scholar
  31. Nguyen GX, Swanson PE (2009) Firm characteristics, relative efficiency, and equity returns. J Financ Quant Anal 44:213–236CrossRefGoogle Scholar
  32. Nishimizu M, Page J (1982) Total factor productivity growth, technological progress, and technical efficiency change: dimensions of productivity change in Yugoslavia, 1965–78. Econ J 92:920–936CrossRefGoogle Scholar
  33. Olley S, Pakes A (1996) The dynamics of productivity in the telecommunications equipment industry. Econometrica 64:1263–1297CrossRefGoogle Scholar
  34. Petkova R (2006) Do the Fama–French factors proxy for innovations in predictive variables? J Finance 61:581–612CrossRefGoogle Scholar
  35. Simon HA (1955) A behavioral model of rational choice. Quart J Econ 69:99–118CrossRefGoogle Scholar
  36. Simon HA (1957) Models of man, social and rational: mathematical essays on rational human behavior in a social setting. Wiley, New YorkGoogle Scholar
  37. Wang H-J (2002) Heteroskedasticity and non-monotonic efficiency effects of a stochastic drontier model. J Prod Anal 18:241–253CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Business and EconomicsLoughborough UniversityLoughboroughUK
  2. 2.Department of Economics and FinanceUniversity of Texas Rio Grande ValleyEdinburgUSA
  3. 3.Department of Economics and Centre for FinanceUniversity of GothenburgGothenburgSweden

Personalised recommendations