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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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number
0139.
Length: Date of creation: Jul 1993 Date of revision: Handle: RePEc:nbr:nberte:0139
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Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions E22 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Capital; Investment; Capacity
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Brad R. Humphreys & Louis J. Maccini & Scott Schuh, 1997.
"Input and output inventories,"
Working Papers
97-7, Federal Reserve Bank of Boston.
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