Using Time Series Forecasting for Analysis of GDP Growth in India

Using Time Series Forecasting for Analysis of GDP Growth in India

Автор: Malik Mubasher Hassan, Tabasum Mirza

Журнал: International Journal of Education and Management Engineering @ijeme

Статья в выпуске: 3 vol.11, 2021 года.

Бесплатный доступ

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.

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

Короткий адрес: https://sciup.org/15017847

IDR: 15017847   |   DOI: 10.5815/ijeme.2021.03.05

Список литературы Using Time Series Forecasting for Analysis of GDP Growth in India

  • “The Power of a Single Number: A Political History of GDP on JSTOR.” https://www.jstor.org/stable/10.7312/lepe17510 (accessed Aug. 24, 2020).
  • “What is Gross Domestic Product (GDP)? - The Financial Express.” https://www.financialexpress.com/what-is/gross-domestic-product-gdp-meaning/1619044/ (accessed Aug. 24, 2020).
  • “Gross Domestic Product | U.S. Bureau of Economic Analysis (BEA),” www.bea.gov, Accessed: Aug. 24, 2020. [Online]. Available: https://www.bea.gov/data/gdp/gross-domestic-product.
  • “Measuring the Economy 1: Gross Domestic Product (GDP) | SparkNotes.” https://www.sparknotes.com/economics/macro/measuring1/section1/ (accessed Aug. 24, 2020).
  • “(1) (PDF) Estimation, Analysis and Projection of India’s GDP.” https://www.researchgate.net/publication/228304100_Estimation_Analysis_and_Projection_of_India’s _GDP (accessed Aug. 24, 2020).
  • P. Lepenies, The Power of a Single Number. Columbia University Press, 2016.
  • “What Is GDP and Why Is It So Important to Economists and Investors?” https://www.investopedia.com/ask/answers/what-is-gdp-why-its-important-to-economists-investors/ (accessed Aug. 24, 2020).
  • “It’s Your Business: GDP (Business Reference Services, Library of Congress).” https://www.loc.gov/rr/business/its-your-business/gdp.html (accessed Aug. 24, 2020).
  • “Principles of Macroeconomics , 2.”
  • Centre for the Advancement of the Steady State Economy, “GDP and Indicators of Economic Wellbeing.”
  • X. Wang, “The Income of Nations: Defining and Measuring Macroeconomic Aggregates,” 2017, [Online]. Available: https://www.brookings.edu/wp-content/uploads/2018/08/WP43-8.23.18.pdf.
  • K. Dynan and L. Sheiner, “GDP as a Measure of Economic,” pp. 1–53.
  • M. Feldstein, “Underestimating the real growth of GDP, personal income, and productivity,” J. Econ. Perspect., vol. 31, no. 2, pp. 145–164, 2017, doi: 10.1257/jep.31.2.145.
  • J. S. Landefeld, E. P. Seskin, and B. M. Fraumeni, “Taking the pulse of the economy: Measuring GDP,” J. Econ. Perspect., vol. 22, no. 2, pp. 193–216, 2008, doi: 10.1257/jep.22.2.193.
  • R. Chn et al., “Gross domestic product 2019 , PPP Gross domestic product 2019 , PPP,” no. July, pp. 1–4, 2020, [Online]. Available: https://databank.worldbank.org/data/download/GDP_PPP.pdf.
  • R. N. A. Raja Aziz and A. Azmi, “Impact of Foreign Direct Investment ( FDI ) inflow on Gross Domestic Product ( GDP ) of India — an Empirical study .,” World Appl. Sci. J., vol. 3, no. 10, pp. 1358–1361, 2013, doi: 10.5829/idosi.wasj.2013.24.10.229.
  • Prof. Dr. Zubair Hasan, “[WIP] Mp r a,” Econ. Policy, no. 2116, pp. 0–33, 2011, doi: 10.1227/01.NEU.0000349921.14519.2A.
  • M. Maliszewska, A. Mattoo, and D. Van Der Mensbrugghe, “The Potential Impact of COVID-19 on GDP and Trade : A Preliminary Assessment,” vol. 1, no. April, 2020.
  • R. Nagaraj, “Growth Rate of India’s GDP, 1950-51 to 1987-88, Examination of Alteranative Hypothesis,” Econ. Polit. Wkly., vol. 25, no. 26, pp. 1396–1403, 1990.
  • “India GDP Rate: India’s GDP growth could plummet to -15.2% y-o-y from 3.1% in Q1: Nomura - The Economic Times.” https://economictimes.indiatimes.com/news/economy/indicators/indias-gdp-growth-to-plummet-to-15-2-y-o-y-from-3-1-in-q1-nomura/articleshow/77759863.cms (accessed Aug. 26, 2020).
  • “India GDP forecast: Indian economy expected to contract by around 25 per cent in the first quarter of FY’21: Report - The Economic Times.” https://economictimes.indiatimes.com/news/economy/indicators/indian-economy-expected-to-contract-by-around-25-per-cent-in-the-first-quarter-of-fy21-report/articleshow/77739356.cms (accessed Aug. 26, 2020).
  • B. Maity and B. Chatterjee, “FORECASTING GDP GROWTH RATES OF INDIA: An Empirical Study,” Int. J. Econ. Manag. Sci., vol. 1, no. 9, pp. 52–58, 2012.
  • S. L. Ho and M. Xie, “The use of ARIMA models for reliability forecasting and analysis,” Comput. Ind. Eng., vol. 35, no. 1–2, pp. 213–216, Oct. 1998, doi: 10.1016/s0360-8352(98)00066-7.
  • “Lesson 3: Identifying and Estimating ARIMA models; Using ARIMA models to forecast future values.” https://online.stat.psu.edu/stat510/book/export/html/665 (accessed Jul. 29, 2020).
  • R. Nau, “Mathematical structure of ARIMA models,” vol. 1, no. c, pp. 1–8, 2014.
  • “Time Series Regression and ARIMA Models | SpringerLink.” https://link.springer.com/chapter/10.1007/978-1-4757-3261-0_2 (accessed Jul. 29, 2020).
  • A. C. Harvey, “ARIMA models,” New Palgrave Dict. Econ., p. 1, 2011, doi: 10.1057/9780230226203.1992.
  • R. H. Shumway and D. S. Stoffer, “Time Series Regression and ARIMA Models,” Springer, New York, NY, 2000, pp. 89–212.
  • S. J. Taylor and B. Letham, “Business Time Series Forecasting at Scale,” PeerJ Prepr. 5e3190v2, vol. 35, no. 8, pp. 48–90, 2017, doi: 10.7287/peerj.preprints.3190v2.
  • E. Žunić, K. Korjenić, K. Hodžić, and D. Đonko, “Application of Facebook’s Prophet Algorithm for Successful Sales Forecasting Based on Real-world Data,” Int. J. Comput. Sci. Inf. Technol., vol. 12, no. 2, pp. 23–36, 2020, doi: 10.5121/ijcsit.2020.12203.
  • Dominique Guegan, Patrick Rakotomarolahy,” Alternative methods for forecasting GDP””, HAL Id: halshs-00511979; https://halshs.archives-ouvertes.fr/halshs-00511979; 2010
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