Using Time Series Forecasting for Analysis of GDP Growth in India

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Malik Mubasher Hassan 1,* Tabasum Mirza 2

1. Dept. of Information Technology and Engineering, BGSB University Rajouri (J&K)-India

2. Dept. of School Education, Govt. of J&K, India

* Corresponding author.


Received: 19 Oct. 2020 / Revised: 12 Nov. 2020 / Accepted: 3 Dec. 2020 / Published: 8 Jun. 2021

Index Terms

GDP of India, Time Series Analysis, ARIMA model, Time series forecasting, PROPHET


Gross Domestic Product is one of the most important economic indicators of the country and its positive or negative growth indicates the economic development of the country. It is calculated quarterly and yearly at the end of the financial year. The GDP growth of India has seen fluctuations from last few decades after independence and reached as high as 10.25 in 2010 and declined to low of -5.23 in 1979. The GDP growth has witnessed a continuous decline in the past five years, taking it from 8.15 in 2015 to 1.87 in 2020.The lockdown imposed in the country to curb the spread of COVID-19 has caused massive slowdown in the economy of the country by affecting all major contributing sectors of the GDP except agricultural sector. To keep on track on the GDP growth is one of the parameters for deciding the economic policies of the country. In this study, we are analyzing and forecasting the GDP growth using the time series forecasting techniques Prophet and Arima model. This model can assist policy makers in framing policies or making decisions.

Cite This Paper

Malik Mubasher Hassan, Tabasum Mirza, " Using Time Series Forecasting for Analysis of GDP Growth in India", International Journal of Education and Management Engineering (IJEME), Vol.11, No.3, pp. 40-49, 2021. DOI: 10.5815/ijeme.2021.03.05


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