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Examples of application of econometric methods

Page history last edited by editor 7 years, 11 months ago

 


 

 

Methods for Forecasting demand and supply


 

 

The section catalogs some methods used in forecasting demand and supply of products.

 

Study1: Supply and Demand for Cereals in Nepal, 2010-2030

Reference: Prasad, Pullabolta and Ganesh-Kumar. Supply and Demand for Cereals in Nepal, 2010-2030. IFPRI. September 2012. Link

Motivation: The study attempts to estimate supply and demand models for the 3 most important  cereals: rice, wheat, and maize.

Methods Overview:

1) Supply projection - based on a single-crop production function (using data from 1995-2008)

2) Demand function/projection - based on the data from NLSS II (2003-04)

 

Methods in Detail:

 

1) SUPPLY PROJECTION

 

A. Building a model:

  • Model: Three single-crop production functions
  • Model specification:
    • Y: crop production amount (tons)
    • Xs:
      • area under  crop (A)
      • improved seed quantity (S)
      • gross irrigated area (I)
      • total fertilizer supply (F)
      • annual average rainfall (R)
  • Functional form: Double-log Cobb-Douglas production function models is prepared for each of the 3 crops
  • Multicollinearity & Heteroskedasticity:
    • For each, Durbin-Watson d-statistic was used to test for autocorrelation, and if AC present, the regression model was estimated through a Prais-Winstein regression
  • Final production function:
    • Only significant variables were retained for each model and the model was re-estimated

 

B. Use the model for projection:

 

  • Build auxiliary models to first build the future values of X-variables; then use these to predict Y
    • Identify policy variables
      • Variables that the government can manipulate - such as  irrigation level, fertilizer supply and seed supply)
      • Since these are manipulated by the government, we can assume several scenarios and determine future X-values accordingly.
        • Business as usual: We can examine the growth rate and assume this growth rate will continue (Business as Usual); for this we need to regress each of the three policy variables with time variables (years) and calculate growth rate (b-coeff in double log auxiliary regression - b/c log allows us to interpret in % terms)
        • Other growth rate assumptions: We can also assume certain growth rate and use that in the model.
    • Identify behavioral variables
      • Variables that depend on farmer choices and preferences, such as crop acreage
      • Here, we can regress crop acreage with other X-variables and see which ones have what kind of influence on farmer's preference of how many acres of crop to plant (X-vars include - irrigation, rainfall, fertilizer, seed supply)
  • Now predict Y
    • Now, determine which years you want to forecast for: 2010, 2015, 2020, 2025 and 2030
    • Now use the time trends of policy variables --> predict crop acreages (behavioral variable)
    • Then use crop acreages & policy variables --> predict Ys
      • This can be done for several scenarios:
        • Business as Usual
        • Pessimistic
        • Optimistic

 

2) Demand Projection

  • Theory/background:
    • Total domestic demand for 3 cereals consists of:
      • Direct demand by households
      • Indirect demand for processing (ex: seed, feeds, wastage)

 

  • To determine direct demand by households
    • Use Household demand model - Linear Approximate - Almost Ideal Demand System (AIDS) Model
      • Formulation:
        • Start with AIDS model 
        • Use linear price index (Stone price index) to use LA-AIDS
        • Parameters
          • Y: wi = % of HH expenditure on food items
          • pi = price of i good
          • y = total expenditure on all goods
          • P = price index
      • Estimate the model
        • Use seemingly unrelated regression (SUR) procedure
        • B/c of possible cross-equation correlations
      • Compute elasticities 
        • Expenditure elasticity
        • Price elasticity
  • To determine indirect demand for processing
    • Use Food budget model 
      • B/c AIDS model captures % expenditure on food items only and not the budget itself
    • Estimate seed, feed and wastage 
  • Data:
    • Nepal Living Standards Survey (Household survey)
       

 

 

 

 

 

 

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