VC - A Program for Estimating Time-Varying Coefficients

Schlicht, Ekkehart (2021): VC - A Program for Estimating Time-Varying Coefficients. Version 6.

Abstract

VC implements Schlicht's method for estimating a linear regression with time-varying coefficients. The variances are estimated by a moments estimator that does not require the disturbances to be Gaussian, but if they are, it coincides with the corresponding maximum likelihood estimate in large samples. It has a direct descriptive interpretation and performs better than the corresponding likelihood estimator in small samples. The program runs under Windows.

• Item Type: Software
• Keywords: Time-series analysis; linear model; state-space estimation; time-varying coefficients; moments estimation; Kalman filtering; penalized least squares.
• Faculties: Economics; Economics > Munich Discussion Papers in Economics; Economics > Munich Discussion Papers in Economics > Statistical Methods; Economics > Chairs > Chair of Institutional Economics (closed)
• Subjects: 300 Social sciences > 300 Social sciences, sociology and anthropology; 300 Social sciences > 310 Statistics; 300 Social sciences > 330 Economics
• JEL Classification: C2, C22, C51, C52
• Language: English

References

Gretl - Gnu Regression, Econometrics and Time-Series Library. http://gretl.sourceforge.net/.

Jalles (2018), João Tovar. “On the Time-Varying Relationship Between Unemployment and Output: What shapes it?” Scottish Journal of Political Economy 2018, vol. 66, pp. 605–630. https://doi.org/10.1111/sjpe.12200.

Schlicht, Ekkehart (2021), "VC - A Method For Estimating Time-Varying Coefficients in Linear Models", Journal of the Korean Statistical Society, https://link.springer.com/article/10.1007/s42952-021-00110-y.