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Some evidence on finite sample behavior of an instrumental variables estimator of the linear quadratic inventory model

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  • Kenneth D. West
  • David W. Wilcox

Abstract

We evaluate some aspects of the finite sample distribution of an instrumental variables estimator of a first order condition of the Holt et al. (1960) linear quadratic inventory model. We find that for some but not all empirically relevant data generating processes and sample sizes, asymptotic theory predicts a wide dispersion of parameter estimates, with a substantial finite sample probability of estimates with incorrect signs. For such data generating processes, simulation evidence suggests that different choices of left hand side variables often produce parameter estimates of an opposite sign. More generally, while the asymptotic theory often provides a good approximation to the finite sample distribution, sometimes it does not
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Suggested Citation

  • Kenneth D. West & David W. Wilcox, 1993. "Some evidence on finite sample behavior of an instrumental variables estimator of the linear quadratic inventory model," Finance and Economics Discussion Series 93-29, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:93-29
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    Cited by:

    1. Gilchrist, Simon & Himmelberg, Charles P., 1995. "Evidence on the role of cash flow for investment," Journal of Monetary Economics, Elsevier, vol. 36(3), pages 541-572, December.
    2. Chistiano, Lawrence J & den Haan, Wouter J, 1996. "Small-Sample Properties of GMM for Business-Cycle Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 309-327, July.
    3. Patrick Fève & François Langot, 1995. "La méthode des moments généralisés et ses extensions : théorie et applications en macro-économie," Économie et Prévision, Programme National Persée, vol. 119(3), pages 139-170.
    4. Jeffrey C. Fuhrer, 2000. "Habit Formation in Consumption and Its Implications for Monetary-Policy Models," American Economic Review, American Economic Association, vol. 90(3), pages 367-390, June.
    5. James H. Stock & Jonathan Wright, 1996. "Asymptotics for GMM Estimators with Weak Instruments," NBER Technical Working Papers 0198, National Bureau of Economic Research, Inc.
    6. Peeters, H. M. M., 1997. "The (mis-)specification of production costs in production smoothing models," Economics Letters, Elsevier, vol. 57(1), pages 69-77, November.
    7. West, Kenneth D & Wilcox, David W, 1996. "A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 281-293, July.
    8. Fuhrer, Jeffrey C. & Rudebusch, Glenn D., 2004. "Estimating the Euler equation for output," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1133-1153, September.
    9. Scott Schuh, "undated". "Evidence on the Link between Firm-Level and Aggregate Inventory Behavior," Finance and Economics Discussion Series 1996-46, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    10. Humphreys, Brad R. & Maccini, Louis J. & Schuh, Scott, 2001. "Input and output inventories," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 347-375, April.
    11. Craig Burnside & Martin S. Eichenbaum, 1994. "Small sample properties of generalized method of moments based Wald tests," Working Paper Series, Macroeconomic Issues 94-12, Federal Reserve Bank of Chicago.
    12. Durlauf, Steven N. & Maccini, Louis J., 1995. "Measuring noise in inventory models," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 65-89, August.
    13. Jeffrey C. Fuhrer, 1998. "An Optimising Model for Monetary Policy Analysis: Can Habit Formation Help?," RBA Research Discussion Papers rdp9812, Reserve Bank of Australia.
    14. Robert S. Chirinko & Huntley Schaller, 2001. "Business Fixed Investment and "Bubbles": The Japanese Case," American Economic Review, American Economic Association, vol. 91(3), pages 663-680, June.

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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

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