MODELLING MAJOR ECONOMIC INDICATORS VIA MULTIVARIATE TIME SERIES ANALYSIS

Open Access
Author:
Zhang, Xuanhao
Area of Honors:
Economics
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Patrik Guggenberger , Thesis Supervisor
  • Russell Chuderewicz, Honors Advisor
Keywords:
  • GDP
  • Economics
  • Forecasting
  • Time Series Analysis
  • VARMA
  • ARMA
Abstract:
Gross domestic product (GDP) is a measure of the market value of all goods and services produced by the country. It is one of the most important indicators to measure the performance of a nation’s economy. The indicator has strong influence on the currency market and monetary policy of the central bank. Policy-makers rely on GDP growth to support and justify their decisions. A better forecasted result can help to formulate a more effective policy to keep the economy prosperous. Time series models have been increasingly prominent as forecasting tools in economics. This paper will focus on the predictability of quarterly real GDP growth in the United States. It aims to provide a reasonable model for the GDP growth based on other economic variables via multivariate time series analysis.