Analysis and Forecast of Shaanxi GDP Based on the ARIMA Model

Ning, Wei; Kuanjiang, Bian; Zhi-fa, Yuan

doi:10.22004/ag.econ.93238

Cited by 6 publications

(1 citation statement)

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“…There are numerous studies that forecast economic activity and growth using ARIMA model and following the 'Box and Jenkins' method. GDP is a macroeconomic measurement directly linked to a country's development; hence, it is crucial to investigate its statistics and predict future data (Ning et al 2010). Previous studies can be classified into three groups.…”

Section: Literature Reviewmentioning

confidence: 99%

Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model

FAKHREDDINE,

ISHKER,

YOUSSEF

2021

JAES

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Gulf Cooperation Council (GCC) members are considered one of the fastest growing economies. This paper aims to empirically forecast the economic activity of the biggest GCC countries: Qatar, Saudi Arabia, and the United Arab Emirates. An Auto-Regressive Integrated Moving Average (ARIMA) model of the Gross Domestic Product in the three countries is obtained using the Box-Jenkins methodology during the 1980-2020 period. The appropriate models for the three economies are of ARIMA (0,2,1), the forecasts are at a 95% confidence level and predicts a growth in the three understudy countries for the upcoming five years.

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Section: Literature Reviewmentioning

confidence: 99%

Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model

FAKHREDDINE,

ISHKER,

YOUSSEF

2021

JAES

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Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA) Models

Wabomba¹

2016

SJAMS

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The Gross Domestic Product (GDP) is the market value of all goods and services produced within the borders of a nation in a year. In this paper, Kenya's annual GDP data obtained from the Kenya National Bureau of statistics for the years 1960 to 2012 was studied. Gretl and SPSS 21 statistical softwares were used to build a class of ARIMA (autoregressive integrated moving average) models following the Box-Jenkins method to model the GDP. ARIMA (2, 2, 2) time series model was established as the best for modeling the Kenyan GDP according to the recognition rules and stationary test of time series under the AIC criterion. The results of an in-sample forecast showed that the relative and predicted values were within the range of 5%, and the forecasting effect of this model was relatively adequate and efficient in modeling the annual returns of the Kenyan GDP. Finally, we used the fitted ARIMA model to forecast the GDP of Kenya for the next five years.

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Forecasting Egyptian GDP using ARIMA models

Abonazel¹,

Abd-Elftah²

2019

Reports on Economics and Finance

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The Gross Domestic Product (GDP) is that the value of all product and services made at intervals the borders of a nation in an exceedingly year. In this paper, the Box-Jenkins approach has been used to build the appropriate Autoregressive-Integrated Moving-Average (ARIMA) model for the Egyptian GDP data. Egypt's annual GDP data obtained from the World-Bank for the years 1965 to 2016. We find that the appropriate statistical model for Egyptian GDP is ARIMA (1, 2, 1). Finally, we used the fitted ARIMA model to forecast the GDP of Egypt for the next ten years.

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Analysis and Forecast of Shaanxi GDP Based on the ARIMA Model

Cited by 6 publications

References 0 publications

Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model

Economic Forecast of the Wealthiest Gulf Countries Using ARIMA Model

Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA) Models

Forecasting Egyptian GDP using ARIMA models

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