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Title: A neural network auto regression model to forecast per capita disposable income
Authors: Debasish Sena, Naresh K. Nagwani
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2016
Volume: 11
Issue: 22
Language: English
Time series analysis is an important technique for future forecasting of time dependent variables. Keeping future visualization in mind, time series analysis is applicable to a wide variety of applications. In this work, neural network autoregressive (NNAR) model, a non-linear model is applied for forecasting of per capita disposable income. The average available money per person after the deduction of income taxes is called as the per capita disposable income. It is an indicator of the economic condition of a nation. Forecasting of per capita disposable income is essential in helping the government assessing its economic state with respect to the economy of other developing countries of the world. Financial critical situation like inflation can also be assessed by forecasting of per capita disposable income. Future policies and plans can also be formulated by the planning commission of a country upon observations of the results obtained from this work.
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