Improving the accuracy of macroeconomic time series forecast by incorporating functional dependencies between them
    
    
  
  
  
      
      
      
        
Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 160 (2018) no. 2, pp. 350-356
    
  
  
  
  
  
    
      
      
        
      
      
      
    Voir la notice du chapitre de livre provenant de la source Math-Net.Ru
            
              A parametric approach to forecasting vectors of macroeconomic indicators, which incorporates functional dependencies between them, has been considered in this paper. As it is possible to functionally bind together most indicators, we believe that this information can help to substantially decrease their forecast error. In this paper, we have proposed to readjust the traditionally obtained forecasts given the known analytical form of the relationship between the considered indicators by the maximum likelihood method. We have also derived a standard form of the readjusted probability density function for each analyzed indicator by normalizing its marginal distribution. In order to prove the efficiency of the proposed method, an empirical out-of-sample investigation has been carried out regarding a simple example for such macroeconomic indicators as gross domestic product (GDP), GDP deflator, and GDP in constant prices.
            
            
            
          
        
      
                  
                    
                    
                    
                        
Keywords: 
regression analysis, GDP, monetary base, maximum likelihood method, probability density function, functional dependencies of macroeconomic indicators.
Mots-clés : inflation
                    
                  
                
                
                Mots-clés : inflation
@article{UZKU_2018_160_2_a15,
     author = {N. A. Moiseev},
     title = {Improving the accuracy of macroeconomic time series forecast by incorporating functional dependencies between them},
     journal = {U\v{c}\"enye zapiski Kazanskogo universiteta. Seri\^a Fiziko-matemati\v{c}eskie nauki},
     pages = {350--356},
     publisher = {mathdoc},
     volume = {160},
     number = {2},
     year = {2018},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/UZKU_2018_160_2_a15/}
}
                      
                      
                    TY - JOUR AU - N. A. Moiseev TI - Improving the accuracy of macroeconomic time series forecast by incorporating functional dependencies between them JO - Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki PY - 2018 SP - 350 EP - 356 VL - 160 IS - 2 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/UZKU_2018_160_2_a15/ LA - en ID - UZKU_2018_160_2_a15 ER -
%0 Journal Article %A N. A. Moiseev %T Improving the accuracy of macroeconomic time series forecast by incorporating functional dependencies between them %J Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki %D 2018 %P 350-356 %V 160 %N 2 %I mathdoc %U http://geodesic.mathdoc.fr/item/UZKU_2018_160_2_a15/ %G en %F UZKU_2018_160_2_a15
N. A. Moiseev. Improving the accuracy of macroeconomic time series forecast by incorporating functional dependencies between them. Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 160 (2018) no. 2, pp. 350-356. http://geodesic.mathdoc.fr/item/UZKU_2018_160_2_a15/
