N. Ashktorab; Gh. Layani; Gh.R. Soltani
Abstract
Introduction: The area under cultivation and yield of crops are affected by various factors, some of which are controllable and some others are uncontrollable. Controllable factors are divided into two types of price and non-price factors. Among the price factors, prices of agricultural products and ...
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Introduction: The area under cultivation and yield of crops are affected by various factors, some of which are controllable and some others are uncontrollable. Controllable factors are divided into two types of price and non-price factors. Among the price factors, prices of agricultural products and inputs play an important role in expanding the cultivation area. Uncontrollable factors also have great effects on increasing the cultivation area of agricultural products. Two of the most important factors that affect yield are weather and climate conditions. The agricultural sector that is one of the sectors that is most vulnerable to climate changes has often been used for political debates and research projects. In the agricultural sector, cereal and especially maize, have a special place in the world both in production and in the area under cultivation. Therefore, given the importance of this product, investigating the effects of climate changes on cultivation area and yield of maize needs careful examination.
Material and Method: Panel data in econometrics has many advantages over using cross-sectional data and time series. The Hausman test is used to determine the fixed and random effects in the panel data. Also panel data unit root tests will be necessary. In this study, several price and non-price factors are considered:
(1) Cit = f(Wit, RPit-1, Rit, Tit, Cit-1)
where Cit: maize cultivation area in province i in year t
Wit : wheat irrigated area and dry area in province i in year t
RPit-1: relative imposed price of maize and wheat in t-1.
Rit : rainfall in province i in year t
Tit : temperature in province i in year t
Cit-1: maize cultivation area in province i in year t-1
(2) Cit = α1 Wit + α2 RPit-1+ α3Rit+ α4 Tit+ α5 Cit-1+ uit
In addition, in this study the Ricardian model was used to examine the impact of climate change on maize yield.
(3)
: Yield per hectare of maize in province i in year t
: Temperature in province i in year t
: Rainfall in province i in year t
: Latitude and height above sea level, respectively.
The data used in this study were for the provinces of Fars, Khuzestan, Kerman, Kermanshah and Elam for the period 1993-2011.
Results and Discussion: According to Table 1, all variables are significant at the one percent level of confidence. Therefore, all of the variables are stationary.
Table 1- Results of stationary test for variables
variables Levin-Lin & chow stat. Pesaran& Shin stat. Stationary state
Cultivation area of maize 2.51*** ***1.13 I(0)
Cultivation area of Irrigated wheat 2.45*** 2.89*** I(0)
Cultivation area of Dry wheat 5.02*** 3.76*** I(0)
rainfall 8.74*** 6.09*** I(0)
Temperature 5.78*** 3.40*** I(0)
Relative imposed price of maize to wheat 2.74*** 1.36*** I(0)
Source: Research calculations
Based on the results shown in Table 2, all variables are significant. The highest and the lowest estimated coefficient is for the relative imposed price of maize to wheat (6.68) and cultivation area of dry wheat (0.01).
Table2- Results of the factors affecting the maize cultivation area in selected provinces
Variables coefficient Standard deviation T-statistics
Constant -2.49* 1.23 -2.03
Imposed price ratio with a lag 6.68*** 1.32 5.06
Cultivation area of Irrigated wheat -0.42* 0.22 -1.88
Cultivation area of Dry wheat -0.01* 0.006 -1.98
Cultivation area of maize with a lag 0.66*** 0.06 10.28
Rainfall 0.17*** 0.06 2.86
R-squared 0.97 Durbin-Watson stat 1.84
Adjusted R-squared 0.96 F-statistic 184.5
Source: Research calculations
Table 3 indicates the results of the Ricardian model by using the panel data method. R2 in this model is equal to 86 % and it shows that %86 of the variation of maize yield is explained by variables. According to the results,the rainfall altitude, the rainfall height above sea, the square of rainfall and latitude have significant effects on maize yield.
Table 3- Results of climatic factors on maize yield in selected provinces
Variables coefficient Standard deviation T-statistics
Constant 12.73*** 2.55 4.99
Temperature -0.11 0.20 -0.52
Rainfall 0.002*** 0.0002 7.32
Height above sea level -0.0004*** 0.0001 -3.51
Square of temperature 0.001 0.005 0.17
Square of rainfall -2.62*** 2.45 -10.71
Latitude -0.07*** 0.02 -3.05
R-squared 0.86 Durbin-Watson stat 1.59
Adjusted R-squared 0.81 F-statistic 5.15
Source: Research calculations
Conclusions: In this study, the factors affecting maize cultivation area and yield as a plant that uses a lot of water in Fars, Khuzestan, Kerman, Kermanshah and Elam provinces were investigated. The results showed that non-price factors such as rainfall and temperature have a significant impact on the cultivation area of maize. Due to the emphasis placed on the policy of self-sufficiency in wheat, irrigated and dry cultivation area of wheat and imposed price of wheat, mentioned by Garshasbi et al., have a significant impact on the cultivation area of maize in the selected provinces. The results indicated that according to specific climatic conditions in these provinces, irrigated wheat can be a proper alternative product for maize. Due to Vaseghi and Esmaeili, climate changes could have adverse effects on maize yield and can lead to a reduction of maize cultivation area. Due to the inevitability of global warming, further investigation of this issue is very important.
Keywords: Maize, Rainfall, Temperature, Yield, Cultivation area, Ricardian model, Panel data method
