Macroeconomic Forecasting with Bayesian Vector Autoregression

Student: Zazulin Alexander

Educational Programme: Economics and Statistics (Bachelor)

Year of Graduation: 2017

VAR has become one of the most popular forecast method in modern applied researches due to its relative simplicity and capability to explain results through IRF. Nevertheless, quite often researches deal with problem of overparametrization in attempts to build forecasts. BVAR is method based on application of prior information that allows to solve this problem. This research provides theory and application of BVAR on Russian data. The results show that BVAR forecasts on Russian data is significantly more accurate than VAR forecasts.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses