“All along the curves”: Bridging the gap between comparative statics and simultaneous econometric models

  • Eivind Hestvik BrækkanEmail author
  • Øystein Myrland


A simultaneous econometric model of supply and demand provides estimates of own-price effects and the effect of exogenous variables on supply or demand. Most of the time economists use elasticities derived from econometric analysis in a ceteris paribus context, more seldom in a total elasticity setting (Buse in J Farm Econ 40:881–891, 1958). Perhaps even more seldom net effects of exogenous changes on prices and quantities are determined in a Muth (Oxf Econ Pap 16:221–234, 1964) type model. In this paper, we replicate the econometric model by Epple and McCallum (Econ Inq 44:374–384, 2006) and use it to specify a comparative static model that quantifies the period-to-period net effects on price and quantity from observed changes in the exogenous variables. Furthermore, we extend (Brækkan et al. in Eur Rev Agric Econ 45:531–552, 2018) approach for computing unexplained demand shifts by also calculating unexplained shifts in supply. This bridges the gap between comparative statics and simultaneous econometric models. Unexplained supply and demand shifts account for the unexplained variation in the endogenous variables. The data used in this application are from the US broiler chicken market.


Simultaneous equations Poultry Comparative statics Demand and supply shifts 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

181_2019_1793_MOESM1_ESM.pdf (297 kb)
Supplementary material 1 (PDF 296 kb)


  1. Abramovitz M (1993) The search for the sources of growth: areas of ignorance, old and new. J Econ Hist 53:217–243CrossRefGoogle Scholar
  2. Aigner D, Lovell CAK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econ 6:21–37CrossRefGoogle Scholar
  3. Alston JM, Norton GW, Pardey PG (1998) Science under scarcity—principles and practice for agricultural research evaluation and priority setting. CABI Publishing, CambridgeGoogle Scholar
  4. Brækkan EH, Thyholdt SB, Asche F, Myrland Ø (2018) The demands they are a-changin’. Eur Rev Agric Econ 45:531–552CrossRefGoogle Scholar
  5. Brumm HJ, Epple D, Mccallum BT (2008) Simultaneous equation econometrics: some weak-instrument and time-series issues. Working paperGoogle Scholar
  6. Bugos GE (1992) Intellectual property protection in the American chicken-breeding industry. Bus Hist Rev 66:127–168CrossRefGoogle Scholar
  7. Buse RC (1958) Total elasticities. A predictive device. J Farm Econ 40:881–891CrossRefGoogle Scholar
  8. Buzby JC, Hodan AF (2006) Chicken consumption continues longrun rise. Amber Vawes 4:5Google Scholar
  9. Chalfant JA, Alston JM (1988) Accounting for changes in tastes. J Polit Econ 96:391–410CrossRefGoogle Scholar
  10. Epple D, Mccallum BBT (2006) Simultaneous equation econometrics: the missing example. Econ Inq 44:374–384CrossRefGoogle Scholar
  11. Frisch R (1934) More pitfalls in demand and supply curve analysis. Q J Econ 48:749–755CrossRefGoogle Scholar
  12. Gilbert CL (2010) How to understand high food prices. J Agric Econ 61:398–425CrossRefGoogle Scholar
  13. Gilbert CL, Morgan CW (2010) Food price volatility. Philos Trans R Soc Lond B Biol Sci 365:3023–3034. CrossRefGoogle Scholar
  14. Haley MM (2001) Changing consumer demand for meat: the U.S. example, 1970–2000. In: Regmi A (ed) Changing structure of global food consumption and trade. USDA, Agriculture and Trade Report WRS-01-1. Washington, DC, pp 41–48Google Scholar
  15. Hill RC, Griffiths WE, Lim GC (2008) Principles of econometrics, 3rd edn. Wiley, HobokenGoogle Scholar
  16. Meeusen W, van Den Broeck J (1977) Efficiency estimation from Cobb–Douglas production functions with composed error. Int Econ Rev Phila 18:435CrossRefGoogle Scholar
  17. Moschini G, Meilke KD (1989) Modeling the pattern of structural change in US meat demand. Am J Agric Econ 71:253–261CrossRefGoogle Scholar
  18. Muth RF (1964) The derived demand curve for a productive factor and the industry supply curve. Oxf Econ Pap 16:221–234CrossRefGoogle Scholar
  19. Piggott RR (1992) Some old truths revisited. Aust J Agric Econ 36:117–140Google Scholar
  20. R Development Core Team (2018) R: a language and environment for statistical computingGoogle Scholar
  21. Renema RA, Rustad ME, Robinson FE (2007) Implications of changes to commercial broiler and broiler breeder body weight targets over the past 30 years. Worlds Poult Sci J 63:457–472CrossRefGoogle Scholar
  22. Solow R (1957) Technical change and the aggregate production function. Rev Econ Stat 39:312–320CrossRefGoogle Scholar
  23. Taylor WE, Taylor LD (1993) Postdivestiture long-distance competition in the United States. Am Econ Rev 83:185–190Google Scholar
  24. The Poultry Site (2008) How the Cobb 500 changed the US market. Accessed 19 Jan 2019
  25. Tomek WG (2000) Commodity prices revisited. Agric Resour Econ Rev 29(2):125–137CrossRefGoogle Scholar
  26. Warren WJ (2007) Tied to the great packing machine: the midwest and meatpacking. University of Iowa Press, Iowa CityGoogle Scholar
  27. Wohlgenant MK (2011) Consumer demand and welfare in equilibrium displacement models. In: Lusk JL, Roosen J, Shogren JF (eds) The oxford handbook of the economics of food consumption and policy. Oxford University Press, OxfordGoogle Scholar
  28. Zhao X, Mullen JDJ, Griffith GRG (1997) Functional forms, exogenous shifts, and economic surplus changes. Am J Agric Econ 79:1243–1251CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Capia ASTromsøNorway
  2. 2.The School of Business and Economics, Faculty of Biosciences, Fisheries and EconomicsUiT – The Arctic University of NorwayTromsøNorway

Personalised recommendations