Estimation and forecasting of the inflation, interest,literacy and unemployment rate of Pakistan using nonlinear regression models

A A Ghoto; G H Mir Talpur; S A Kamboh

doi:10.17485/IJST/v14i3.1812

Article

Estimation and forecasting of the inflation, interest,literacy and unemployment rate of Pakistan using nonlinear regression models

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v14i3.1812

Year: 2021, Volume: 14, Issue: 3, Pages: 251-258

Original Article

Estimation and forecasting of the inflation, interest,literacy and unemployment rate of Pakistan using nonlinear regression models

A A Ghoto^1*, G H Mir Talpur², S A Kamboh¹

¹Department of Mathematics and Statistics, QUEST, Nawabshah, 67480, Pakistan. Tel.: 0092- 333-2794950
²Department of Statistics, University of Sindh, Jamshoro, 76080, Pakistan

*Corresponding Author
Tel: 0092-333-2794950
Email:[email protected]

Received Date:10 October 2020, Accepted Date:12 January 2021, Published Date:01 February 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Background/Objectives: To analyze and investigate the relationships for the inflation rate, interest rate, literacy rate and unemployment rate of Pakistan with a high level of accuracy. Methods/Statistical analysis: Method of nonlinear least squares have been adopted to fit the nonlinear regression models to estimate the present and future trends for the inflation rate, interest rate, literacy rate and unemployment rate of Pakistan based on the data from the year 2000 to 2019. Various nonlinear regression models were tested by changing their degree and number of coefficients. For each trial, the goodness of fit was set at a 95% confidence level. The best regression models were selected on basis of goodness of fit, the correlation with the present data and the logical trend of future forecasts. Findings: The proposed nonlinear regression models are quite different from the conventional linear and nonlinear polynomial regression models. The fitted and forecasting graphs show very realistic results that can be used by policymakers with good accuracy. Novelty/Applications: Since the periodic abrupt changes in the quantitative response variables like inflation rate, interest rate, literacy rate and the unemployment rate of Pakistan have been smoothly incorporated; therefore, the government or other socio-economic practitioners may use the results for future planning and management of the resources depending upon these factors.

Keywords: Inflation rate; literacy rate; interest rate; unemployment rate; nonlinear regression; forecasting

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Copyright

© 2021 Ghoto et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)