Prediction of Urban Unemployment Rate in India using Grey Model
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Authors
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Pradip Basak
Uttar Banga Krishi Viswavidyalaya, Cooch Behar
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Mrinmoy Ray
ICAR-Indian Agricultural Statistics Research Institute, New Delhi
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Kanchan Sinha
ICAR-Indian Agricultural Statistics Research Institute, New Delhi
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Anuja A.R.
ICAR-Central Marine Fisheries Research Institute, Kochi
Keywords:
Grey model; Periodic Labour Force Survey; Urban unemployment rate; Forecast model.Abstract
Urban Unemployment Rate (UR) is a crucial indicator representing the livelihood of people in India. In India, the quarterly estimates of urban UR in the Current Weekly Status (CWS) are released by National Statistics Office (NSO) through Periodic Labour Force Survey (PLFS). At present, the urban UR estimates are available in India from the quarter April-June 2018 to January-March 2023 at the state and national level. Accurate forecasting of the UR is essential for early identification of the socio-economic problems so that timely and targeted intervention, and proper policy planning can be done to reduce the same. Time series methodology utilised so far for the forecasting of UR require monthly or quarterly data of sufficient length. Therefore, the usual methods of forecasting of UR may not yield reliable forecast in this type of small time series as the assumption on the data requirement will be violated. As a superiority to conventional statistical models, grey models require very limited data to build a forecast model (Deng, 1989). In this article, application of grey model has been considered on the quarterly estimates of urban UR for forecasting the unemployment in urban India. The Grey model shows excellent performance in forecasting the urban UR at the national level and at the state level, it shows good performances for most of the states.
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