
doi: 10.1002/jae.2678
handle: 2158/1147539
SummaryWe derive computationally simple expressions for score tests of misspecification in parametric dynamic factor models using frequency domain techniques. We interpret those diagnostics as time domain moment tests which assess whether certain autocovariances of the smoothed latent variables match their theoretical values under the null of correct model specification. We also reinterpret reduced‐form residual tests as checking specific restrictions on structural parameters. Our Gaussian tests are robust to nonnormal, independent innovations. Monte Carlo exercises confirm the finite‐sample reliability and power of our proposals. Finally, we illustrate their empirical usefulness in an application that constructs a US coincident indicator.
Kalman filter, LM tests, Spectral maximum likelihood, Wiener-Kolmogorov filter., jel: jel:C52, jel: jel:C12, jel: jel:C13, jel: jel:C32, jel: jel:C38
Kalman filter, LM tests, Spectral maximum likelihood, Wiener-Kolmogorov filter., jel: jel:C52, jel: jel:C12, jel: jel:C13, jel: jel:C32, jel: jel:C38
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
