| Title |
Mixed frequency data sampling regression models: the R package midasr / |
| Authors |
Ghysels, Eric ; Kvedaras, Virmantas ; Zemlys, Vaidotas |
| DOI |
10.18637/jss.v072.i04 |
| Full Text |
|
| Is Part of |
Journal of statistical software.. Innsbruck : Foundation for Open Access Statistics. 2016, Vol. 72, no 4, p. 1-35.. ISSN 1548-7660 |
| Keywords [eng] |
MIDAS ; regression model ; specification test. |
| Abstract [eng] |
When modeling economic relationships it is increasingly common to encounter data sampled at different frequencies. We introduce the R package midasr which enables esti- mating regression models with variables sampled at different frequencies within a MIDAS regression framework put forward in work by Ghysels, Santa-Clara, and Valkanov (2002). In this article we define a general autoregressive MIDAS regression model with multiple variables of different frequencies and show how it can be specified using the familiar R formula interface and estimated using various optimization methods chosen by the re- searcher. We discuss how to check the validity of the estimated model both in terms of numerical convergence and statistical adequacy of a chosen regression specification, how to perform model selection based on a information criterion, how to assess forecasting accuracy of the MIDAS regression model and how to obtain a forecast aggregation of different MIDAS regression models. We illustrate the capabilities of the package with a simulated MIDAS regression model and give two empirical examples of application of MIDAS regression. |
| Published |
Innsbruck : Foundation for Open Access Statistics |
| Type |
Journal article |
| Language |
English |
| Publication date |
2016 |
