• DocumentCode
    721167
  • Title

    Application of time series based prediction model to forecast per capita disposable income

  • Author

    Sena, Debasish ; Nagwani, Naresh Kumar

  • Author_Institution
    Comput. Technol., Nat. Inst. of Technol. Raipur, Raipur, India
  • fYear
    2015
  • fDate
    12-13 June 2015
  • Firstpage
    454
  • Lastpage
    457
  • Abstract
    Time series analysis is one of the major prediction techniques for forecasting of time dependent variables. These days the time series analysis is applicable to a variety of applications. In this work the time series analysis technique using ARIMA model is applied on per capita disposable income for future forecasting. Per capita disposable income is the average available money per person after income taxes have been accounted for. It is an indicator of the overall state of an economy. Forecasting of per capita disposable income is necessary as it may help government assess country´s economic condition in comparison with the economy of other countries of the world. Forecasting per capita disposable income may also help assess inflation and financial critical situation. The results obtained from this work can be used by the planning commission of a country to formulate future policies and plans.
  • Keywords
    autoregressive moving average processes; economics; financial management; forecasting theory; time series; ARIMA model; economic condition; financial critical situation assessment; inflation assessment; per capita disposable income forecasting; time dependent variable forecasting; time series based prediction model; Analytical models; Forecasting; Load modeling; Mathematical model; Noise; Predictive models; Time series analysis; ARIMA model; Forecasting; Prediction model; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advance Computing Conference (IACC), 2015 IEEE International
  • Conference_Location
    Banglore
  • Print_ISBN
    978-1-4799-8046-8
  • Type

    conf

  • DOI
    10.1109/IADCC.2015.7154749
  • Filename
    7154749