IDEAS home Printed from https://ideas.repec.org/a/iag/reviea/v7y2010i2p285-291.html
   My bibliography  Save this article

The Utilization Of The Statistical Techniques In Projecting Gross Value Added In The Agriculture, Hunting And Forestry; Fishery And Pisciculture Sector

Author

Listed:
  • Enache, Calcedonia

    (Academy of Economic Studies, Bucharest, Romania)

Abstract

As a material production branch, agriculture features certain particularities that are essentially different from those of the other sectors of national economy, namely: active role in land operation, which increases the capacity of obtaining high yields by rational land use and use of technical advances; blending the technological process with that of natural (biological) multiplication of living organisms; strong action of weather factors upon the harvest; seasonality and diminution of working time due to the biological processes and non-coincidence with the production time. On the basis of statistical techniques, the present paper intends to reveal the evolution of the gross value added in the sector of agriculture, hunting and forestry; fishery and pisciculture, extrapolating the investigated characteristic.

Suggested Citation

  • Enache, Calcedonia, 2010. "The Utilization Of The Statistical Techniques In Projecting Gross Value Added In The Agriculture, Hunting And Forestry; Fishery And Pisciculture Sector," Agricultural Economics and Rural Development, Institute of Agricultural Economics, vol. 7(2), pages 285-291.
  • Handle: RePEc:iag:reviea:v:7:y:2010:i:2:p:285-291
    as

    Download full text from publisher

    File URL: http://www.eadr.ro/RePEc/iag/iag_pdf/AERD1016_285-291.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Holt Winters method; seasonality; gross value added; exponential smoothing;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iag:reviea:v:7:y:2010:i:2:p:285-291. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/iaacaro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.