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Vol. 12, Issue 1 (2023)

Time series ARIMA forecasting of FDI inflow in India

Author(s):
KY Ingale, SV Bharati and PV Karale
Abstract:
India is a rapidly developing country which is often seen as an investment ground by the industry giants of foreign countries. The recent trends show an exponential increase in the net foreign direct investment in India from the year 2010-2020. Thus, it becomes crucial for the policy makers and the economist to forecast the future inflows of investment in order to produce effective policies and take better decisions. The result of the better policies would help in overcoming the unbalanced market viability. ARIMA modelling is a technique used in statistics and econometrics which harness the advantages of both Auto Regression (AR) and Moving Average (MA) models by integrating them together to form auto regression integrated moving average model. The present study based on data regarding FDI inflow from 2001-2020 which aims to generate a customised box-Jenkins ARIMA model for forecasting and analysing the trend of FDI in India. It proposes ARIMA (0,1,0) model for optimal forecasting of net FDI inflow in India.
Pages: 2454-2456  |  285 Views  201 Downloads


The Pharma Innovation Journal
How to cite this article:
KY Ingale, SV Bharati, PV Karale. Time series ARIMA forecasting of FDI inflow in India. Pharma Innovation 2023;12(1):2454-2456.

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