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Estimating Investment Rigidity Within A Threshold Regression Framework: The Case Of U.S. Hog Production Sector


  • Boetel, Brenda L.
  • Hoffmann, Ruben
  • Liu, Donald J.


As the U.S. hog production sector becomes ever more specialized, the importance of capital inputs has heightened. Given that it is costly to adjust the capital stock and that the associated adjustment cost function may exhibit cost asymmetries between investment and disinvestment, profit-maximizing producers may find themselves trapped in a situation where it is neither profitable investing nor worthwhile disinvesting. This article addresses two issues related to the employment of quasi-fixed input in the U.S. hog production sector: does an inaction or sluggish regime exist in the demand for quasi-fixed input, and, if so, to what extent has this impeded adjustment in quasi-fixed input stock and, hence, hog output supply toward the long-term equilibrium levels? The conceptual framework is based on the work by Abel and Eberly and allows for the existence of an inaction/sluggish regime, alongside an investment regime and a disinvestment regime. Quarterly data from 1976 through 1999 are used to estimate the three-regime investment demand equation, treating breeding sows as the quasi-fixed input. The threshold estimation procedure recently advanced by Hansen is adopted. To provide a linkage between breeding herd investment and hog output supply, a hog supply equation, specified in part as a function of lagged breeding stock, is estimated by a least squares procedure. The dynamic recursive system of investment demand and hog supply is used to simulate the effects on breeding stock and hog supply of changes in the magnitude of investment rigidities. The econometric results strongly support the three-regime breeding herd investment model. More than 10 percent of the observations fall into the sluggish regime, indicating that this regime has occurred sufficiently often to warrant attention. The estimated rate of adjustment toward the long-run equilibrium breeding stock is 2.7 percent per quarter. The existence of a linkage between lagged breeding stock and hog supply is confirmed. Thus, the results suggest that it is important to account for investment rigidity when estimating breeding herd demand and hog supply. Simulation results indicate that the effects on breeding stock and hog supply of continued specialization in the hog production sector may not be as significant as what the hog production sector has experienced in the past decades. More importantly the simulations suggest that the impact of increasing investment rigidity is rather modest, about 3 percent at most and, thus, no policy intervention appears to be needed. However, the econometric results clearly indicate that estimates will be biased if investment rigidity is not explicitly accounted for when estimating breeding herd demand and hog supply.

Suggested Citation

  • Boetel, Brenda L. & Hoffmann, Ruben & Liu, Donald J., 2004. "Estimating Investment Rigidity Within A Threshold Regression Framework: The Case Of U.S. Hog Production Sector," Staff Papers 13790, University of Minnesota, Department of Applied Economics.
  • Handle: RePEc:ags:umaesp:13790

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    1. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    2. Pietola, Kyosti & Myers, Robert J., 1998. "Investment Under Uncertainty And Dynamic Adjustment In Finnish Pork Industry," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20953, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Matthew T. Holt & Stanley R. Johnson, 1988. "Supply Dynamics in the U.S. Hog Industry," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 36(2), pages 313-335, July.
    4. Alfons Oude Lansink & Spiro E. Stefanou, 1997. "Asymmetric Adjustment of Dynamic Factors at the Firm Level," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1340-1351.
    5. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    6. Mundlak, Yair, 2001. "Production and supply," Handbook of Agricultural Economics,in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 1, pages 3-85 Elsevier.
    7. Chang, Ching-Cheng & Stefanou, Spiro E., 1988. "Specification and estimation of asymmetric adjustment rates for quasi-fixed factors of production," Journal of Economic Dynamics and Control, Elsevier, vol. 12(1), pages 145-151, March.
    8. Carl H. Nelson & John B. Braden & Jae-Sun Roh, 1989. "Asset Fixity and Investment Asymmetry in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 970-979.
    9. Robert G. Chambers & Utpal Vasavada, 1983. "Testing Asset Fixity for U.S. Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(4), pages 761-769.
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    Cited by:

    1. Zein Kallas & Teresa Serra & José M. Gil, 2012. "Effects of policy instruments on farm investments and production decisions in the Spanish COP sector," Applied Economics, Taylor & Francis Journals, vol. 44(30), pages 3877-3886, October.
    2. Yu, Ping, 2012. "Likelihood estimation and inference in threshold regression," Journal of Econometrics, Elsevier, vol. 167(1), pages 274-294.
    3. Teresa Serra & Spiro Stefanou & José M. Gil & Allen Featherstone, 2009. "Investment rigidity and policy measures," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(1), pages 103-120, March.
    4. Guastella, G. & Moro, D. & Sckokai, P. & Veneziani, M., 2013. "CAP Effects on Agricultural Investment Demand in Europe," 2013: Productivity and Its Impacts on Global Trade, June 2-4, 2013. Seville, Spain 152256, International Agricultural Trade Research Consortium.
    5. Hoffmann, Ruben, 2006. "Quality policy, market structure and investment behavior in the food marketing chain," Department of Economics publications 1117, Swedish University of Agricultural Sciences, Department of Economics.
    6. repec:ags:aaea13:150610 is not listed on IDEAS
    7. Stutzman, Sarah A., 2016. "U.S. Farm Capital Investment 1996-2013: Differences by Farm Size and Operator Primary Occupation," Dissertations-Doctoral 235179, AgEcon Search.
    8. Delbridge, Timothy A., 2013. "Threshold Effects in Transition to Organic Dairy Production," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150554, Agricultural and Applied Economics Association.
    9. Guastella,Giovanni & Moro, Daniele & Sckokai, Paolo & Veneziani, Mario, 2013. "Investment behaviour of EU arable crop farms in selected EU countries and the impact of policy reforms," Factor Markets Working Papers 154, Centre for European Policy Studies.
    10. Peter Sephton & Janelle Mann, 2013. "Threshold Cointegration: Model Selection with an Application," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(2), pages 54-77.
    11. Wilson, P. & Glithero, N.J. & Ramsden, S.J., 2014. "Prospects for dedicated energy crop production and attitudes towards agricultural straw use: The case of livestock farmers," Energy Policy, Elsevier, vol. 74(C), pages 101-110.

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