Analysis and Forecast of Resource-based City GDP Based on ARIMA Model

DOI

10.2991/icfied-19.2019.39How to use a DOI?

Keywords

ARIMA model, GDP predicted, stable development, strategic adjustment

Abstract

As an important indicator to measure a country or region, GDP is often used to measure the level of economic development of a country or region. Doing a good GDP forecast is beneficial to the real-time and adjustment of government policies, and has important theoretical and guiding significance. This paper selects the GDP data of Dongying City from 1978 to 2016 as a research sample, and predicts the GDP of Dongying City from 2017 to 2020 by constructing a time series ARIMA model. The research results show that Dongying City's GDP has a first-order single-integration nature, and the current GDP will be affected by the interference of the last four periods of GDP and the last three disturbances. Due to the influence of uncertain factors such as the international situation, economic foundation and scientific and technological progress, the accuracy of model prediction decreases, and the actual GDP is underestimated. However, the future trend of the time series can be roughly judged according to the prediction of the ARIMA model, preparations can be made in advance to ensure the smooth development of the city's economy, and provide decision-making reference for resource-based city governments, relevant institutional policy formulation, and strategic adjustment.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hao Huang
PY  - 2019/02
DA  - 2019/02
TI  - Analysis and Forecast of Resource-based City GDP Based on ARIMA Model
BT  - Proceedings of the 2019 4th International Conference on Financial Innovation and Economic Development (ICFIED 2019)
PB  - Atlantis Press
SP  - 210
EP  - 216
SN  - 2352-5428
UR  - https://doi.org/10.2991/icfied-19.2019.39
DO  - 10.2991/icfied-19.2019.39
ID  - Huang2019/02
ER  -