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Econometrcs - Essay Example

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Your Full Name: Topic: Econometrics, Essay Subject: Question 1. log(Urea Amount) = 9.760-0.182 log(Previous years application)-0.0561 log (Urea Price)+0.459 log(Open Market Price of Paddy)- 0.261log(Wages)-0.145log(Oil Price) Table 1: Econometrics Estimates (1) (2) Urea Amount(Mt) Log Urea amount Lag dependent -0.137 (0.305) Urea Price (Rs/Kg) -0.00218 (0.0125) Open Market Price of Paddy (Rs/Mt) -91.73* (32.53) Wages (Rs/Day) 44.99 (67.63) Oil Price(Rs/Bbl) 4.822* (2.117) Log- Lag dependent -0.182 (0.320) Log-Urea Price (Rs/Kg) -0.0561* (0.0621) Log- Open Market Price of Paddy (Rs/Mt) 0.459* (0.131) Log- Wages (Rs/Day) -0.261 (0.188) Log- Oil Price(R…
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Download file to see previous pages... Accordingly the log-log model was found consistent with the economic theory. For example, the coefficient of own price was not significant while the coefficient of output price was negatively correlated in the linear-linear model. Cost minimizing farmers’ input demand however, should be positively correlated to the output price i.e. with increasing output price which in turn increase farmer’s profit the demand for inputs also should increase. Therefore, in the urea fertilizer demand model the paddy price should be positively correlated with the fertilizer demand. And also the price of urea should be negatively and significantly correlated to the demand for urea. Hence the log-log model is consistent with the economics theory. Therefore, it was used for interpretation as follows. Table2: Test for Autocorrelation Breusch-Godfrey LM test for autocorrelation lags(p) chi2 df Prob > chi2 1 0.520 1 0.4709 H0: no serial correlation N*R2 = 23*0.516 = 11.868 N*R2 > chi2 Therefore reject H0. There is auto correlation in the model. Thus the robust estimates were taken. Table3: Test for Multicolinarity Variable VIF 1/VIF Log-Urea Price (Rs/Kg) 2.67 0.37453 Log- Open Market Price of Paddy (Rs/Mt) 2.42 0.41322 Log- Wages (Rs/Day) 2.08 0.48072 Log- Lag dependent 1.58 0.63344 Mean VIF 2.19 ii) In log-log equations the coefficients reflects the price elasticity of the respective variables. For example in the above model the own price elasticity of urea demand is -0.0561 i.e. with 1 percentage proportion decrease in urea price the increase the demand for urea by 5.6 percentage proportion. Similarly, the elasticity of urea demand for paddy price is 0.459 i.e. 1 percentage proportion increase in open market price of paddy can increase the demand for urea fertilizer by 45.9 percentage proportion. In the model the largest, significant coefficient was associated with the open market price of paddy. This shows that paddy farmers production decisions are influenced highly by the output price compared to the price of other factors of production such as fertilizer, labor and crude oil. However both own price elasticity and output price elasticitys are less than one and hence are inelastic. The demand for fertilizer is negatively correlated to the wage rates and crude oil prices. With increasing wage rates and oil prices the cost of production increase and hence these variables are negatively correlated in the demand model. The elasticity of demand with respect to wage rates is -0.261 while the elasticity of demand with respect to crude oil price is -0.145. therefore the demand for urea fertilizer decrease by 26.1 and 14.5 percentage proportions with respect to 1 percentage proportion increase in wage rates and crude oil prices respectively. Crude oil price represent the transport cost and also paddy processing costs. The goodness of fit as denoted by the adjusted R2 value of the above model is 51.6 percentage proportion and the probability value of the f statistic was 0.00. Therefore the model is statistically significant ...Download file to see next pagesRead More
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