Name
Abstract | ||
|---|---|---|
In this paper we present a consistent estimator for a linear filter (distributed lag) when the independent variable is subject to observational error. Unlike the standard errors-in-variables estimator which uses instrumental variables, our estimator works directly with observed data. It is based on the Hilbert transform relationship between the phase and the log gain of a minimum phase-lag linear filter. The results of using our method to estimate a known filter and to estimate the relationship between consumption and income demonstrate that the method performs quite well even when the noise-to-signal ratio for the observed independent variable is large. We also develop a criterion for determining whether an estimated phase function is minimum phase-lag. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1016/0165-1684(94)90104-X | Signal Processing |
Keywords | Field | DocType |
ERRORS-IN-VARIABLES,HILBERT TRANSFORM,LINEAR FILTER,MINIMUM PHASE-LAG,PHASE UNWRAPPING | Errors-in-variables models,Mathematical optimization,Linear filter,Instrumental variable,Minimum mean square error,Variables,Hilbert transform,Mathematics,Estimator,Consistent estimator | Journal |
Volume | Issue | ISSN |
37 | 2 | 0165-1684 |
Citations | PageRank | References |
1 | 0.53 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Melvin J. Hinich | 1 | 91 | 71.30 |
| Warren E. Weber | 2 | 2 | 0.93 |