Working Paper: NBER ID: w1913
Authors: Alan S. Blinder
Abstract: When empirical stock-adjustment models of manufacturers' inventories of finished goods are estimated, there appear to be two local minima in the sum of squared residuals functions. At one local minimum, the estimated adjustment speed is typically quite high; at the other, it is typically quite low. Furthermore, finding two sets of estimates that fit the data almost equally well does not appear to be a quirk of this particular application. Rather, it stems from a fundamental identification problem that afflicts partial adjustment models of all kinds. In the specific context of manufacturers' inventories of finished goods, the estimation procedure employed by Maccini and Rossana seems to pick out the solution with rapid adjustment (and high serial correlation in the disturbances) whereas the solution with slow adjustment (and little serial correlation) is more often the global minimum.
Keywords: inventory models; adjustment speeds; econometric techniques
JEL Codes: E22; C51
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Estimation methods yield local minima (C51) | High adjustment speeds and high serial correlation (C22) |
| Identification problem complicates distinction (D00) | Models with strong serial correlation and fast adjustment vs. Models with little serial correlation and slow adjustment (C22) |
| Low p solution (F16) | Global minimum (C62) |
| Estimation method (C51) | Perceived speed of adjustment (F32) |