IDEAS home Printed from https://ideas.repec.org/p/fip/fedgfe/93-29.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
(This abstract was borrowed from another version of this item.)

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
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Blanchard, Olivier J, 1983. "The Production and Inventory Behavior of the American Automobile Industry," Journal of Political Economy, University of Chicago Press, vol. 91(3), pages 365-400, June.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Hansen, Lars Peter, 1985. "A method for calculating bounds on the asymptotic covariance matrices of generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 203-238.
    4. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    5. Blanchard, Olivier J. & Melino, Angelo, 1986. "The cyclical behavior of prices and quantities: The case of the automobile market," Journal of Monetary Economics, Elsevier, vol. 17(3), pages 379-407, May.
    6. Kocherlakota, Narayana R., 1990. "On tests of representative consumer asset pricing models," Journal of Monetary Economics, Elsevier, vol. 26(2), pages 285-304, October.
    7. Ramey, Valerie A, 1991. "Nonconvex Costs and the Behavior of Inventories," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 306-334, April.
    8. Alan S. Blinder & Louis J. Maccini, 1991. "Taking Stock: A Critical Assessment of Recent Research on Inventories," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 73-96, Winter.
    9. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 145-159, Supplemen.
    10. West, Kenneth D, 1986. "A Variance Bounds Test of the Linear Quadratic Inventory Model," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 374-401, April.
    11. Phillips, Peter C B & Park, Joon Y, 1988. "On the Formulation of Wald Tests of Nonlinear Restrictions," Econometrica, Econometric Society, vol. 56(5), pages 1065-1083, September.
    12. Krane, Spencer D & Braun, Stephen N, 1991. "Production Smoothing Evidence from Physical-Product Data," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 558-581, June.
    13. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
    14. Eichenbaum, Martin, 1989. "Some Empirical Evidence on the Production Level and Production Cost Smoothing Models of Inventory Investment," American Economic Review, American Economic Association, vol. 79(4), pages 853-864, September.
    15. Phillips, P.C.B., 1983. "Exact small sample theory in the simultaneous equations model," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 8, pages 449-516, Elsevier.
    16. West, Kenneth D, 1988. "Asymptotic Normality, When Regressors Have a Unit Root," Econometrica, Econometric Society, vol. 56(6), pages 1397-1417, November.
    17. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 397-416, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Jeffrey C. Fuhrer, 1998. "An optimizing model for monetary policy analysis: can habit formation help?," Working Papers 98-1, Federal Reserve Bank of Boston.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Durlauf, Steven N. & Maccini, Louis J., 1995. "Measuring noise in inventory models," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 65-89, August.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. James H. Stock & Jonathan Wright, 1996. "Asymptotics for GMM Estimators with Weak Instruments," NBER Technical Working Papers 0198, National Bureau of Economic Research, Inc.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
    2. Fuhrer, Jeffrey C. & Moore, George R. & Schuh, Scott D., 1995. "Estimating the linear-quadratic inventory model Maximum likelihood versus generalized method of moments," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 115-157, February.
    3. 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.
    4. Durlauf, Steven N. & Maccini, Louis J., 1995. "Measuring noise in inventory models," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 65-89, August.
    5. Ramey, Valerie A. & West, Kenneth D., 1999. "Inventories," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 13, pages 863-923, Elsevier.
    6. Galeotti, Marzio & Maccini, Louis J. & Schiantarelli, Fabio, 2005. "Inventories, employment and hours," Journal of Monetary Economics, Elsevier, vol. 52(3), pages 575-600, April.
    7. 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.
    8. 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.
    9. Louis J. Maccini & Bartholomew J. Moore & Huntley Schaller, 2004. "The Interest Rate, Learning, and Inventory Investment," American Economic Review, American Economic Association, vol. 94(5), pages 1303-1327, December.
    10. Maccini, Louis J. & Moore, Bartholomew & Schaller, Huntley, 2015. "Inventory behavior with permanent sales shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 290-313.
    11. Louis Maccini, 2013. "Inventory Behavior with Permanent Sales Shocks," Economics Working Paper Archive 608, The Johns Hopkins University,Department of Economics.
    12. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    13. Hamilton, James D., 2002. "On the interpretation of cointegration in the linear-quadratic inventory model," Journal of Economic Dynamics and Control, Elsevier, vol. 26(12), pages 2037-2049, October.
    14. Guariglia, Alessandra, 1999. "An analysis of the inventory behavior in a q-theoretic framework," International Journal of Production Economics, Elsevier, vol. 58(2), pages 131-146, January.
    15. Robert E. Carpenter & Steven M. Fazzari & Bruce C. Petersen, 1994. "Inventory (Dis)Investment, Internal Finance Fluctuations, and the Business Cycle," Macroeconomics 9401001, University Library of Munich, Germany.
    16. Yi Wen, 2007. "Production and Inventory Behavior of Capital," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 95-112, May.
    17. James A. Kahn & Mark Bils, 2000. "What Inventory Behavior Tells Us about Business Cycles," American Economic Review, American Economic Association, vol. 90(3), pages 458-481, June.
    18. Yang, Xiaolou, 2011. "Trade credit versus bank credit: Evidence from corporate inventory financing," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 419-434.
    19. Kenneth West & Ka-fu Wong & Stanislav Anatolyev, 2009. "Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 441-467.
    20. Yi Wen, 2008. "Inventories, liquidity, and the macroeconomy," Working Papers 2008-045, Federal Reserve Bank of St. Louis.

    More about this item

    Keywords

    Econometric models;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedgfe:93-29. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ryan Wolfslayer ; Keisha Fournillier (email available below). General contact details of provider: https://edirc.repec.org/data/frbgvus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.