Väkilannoitteiden kysyntä: Jakautuneita viiveitä sisältävien mallien sovellutuksia Suomen väkilannoitteiden käyttömäärien vaihteluiden selittämisessä ja ennakoinnissa

Authors

• Markku Nevala Maatalouden taloudellinen tutkimuslaitos, Rukkila, 00001 Helsinki 100

DOI: https://doi.org/10.23986/afsci.71904

Abstract

Different types of distributed lag models were constructed for the aggregate fertilizer consumption in Finland. The main attention was focused upon those models that could be used for forecasting variations in fertilizer consumption. Before specification of the demand models, a method of time series analysis (EPA-method consisting of several subsequent moving averages) was applied to quarterly time series data on the quantities of the main plant nutrients to divide them into three components: 1) trend cycle-, 2) seasonal- and 3) irregular components. In addition, the average growth rates for fertilizer consumption were computed for different periods. In the formulation of demand models it was assumed that the variations in fertilizer consumption depend on the variations in the prices of fertilizer, agricultural products and other farm inputs as well as on the variations in the farm cash receipts. Two types of distributed lag models were used: 1) polynomial lag models (formulated by Almon) and 2) Nerlovian partial adjustment models. Polynomial lag formulations seemed to give the best results as compared to a priori hypotheses. The demand for fertilizer was found to be rather elastic with respect to the price ratio between fertilizer and agricultural products. The response of the farmers, however, spreads with respect to time: at its highest, the response is about two economic years after the change in the price ratio. Also, the variations in farm cash receipts were found to be an important determinant of the variations in fertilizer consumption. In order to test the validity of the constructed models for forecasting purposes, expost forecasts of total fertilizer consumption were computed for the economic year 1973/74and ex-ante forecasts for the economic year 1974/75 by means of some models.