• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Using Google Trends Data to Forecast Migration in Russia

Student: Pushchelenko Iuliia

Supervisor: Dean Fantazzini

Faculty: International College of Economics and Finance

Educational Programme: Financial Economics (Master)

Year of Graduation: 2020

This paper studies the applicability of Google Trends data to interregional migration modelling and forecasting in Russia. Monthly migration, search volume data, and macro variables are used in ARIMA, ARIMAX, VAR and VECM models in two Russia cities with the largest inflow of migrants – Moscow and Saint-Petersburg. The results do not provide evidence that the more people search online, the more they relocate to other regions. However, adding Google Trends data to a model helps predict migration inflow into the region. Evidence is provided by the fact that forecast errors are lower for most models with internet search data included. What is more, Model Confidence Set (MCS) procedure reveals that most models with superior predictive ability include Google Trends variable in both Moscow and Saint-Petersburg sample.

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