Sayed Mohibul Hossen
Lecturer, Department of Statistics, Mawlana Bashani Science & Technology University, Santosh, Tangail-1902, BANGLADESH
Chili, Production, Prospect, Bangladesh
Department of Statistics, Mawlana Bashani Science & Technology University, Santosh, Tangail-1902, BANGLADESH
Socio-economic and Policy
The first and the main step for the econometrician are to study if there is any relationship with the variables and to express this relationship in precise form. That is to specify the model, with which the fiscal incident explore empirically.
Regression analysis Regression analysis is a branch of statistical theory that is widely used in almost all the scientific disciplines. In economics, it is the technique for measuring or estimating the relationship with economic variables that constitute the essence of economic theory and economic life. With the help of regression analysis, we are in a position to find out the average probable change in one variable given a certain amount of change in another (Gujrati, D.N; 1995).
Reason for using regression analysis The regression analysis helps in three significant ways: 1. It provides estimates of values of the dependent variables from values of independent variables. The device used to accomplish the estimation procedure is the regression line that describes the average relationship existing between x and y variables. 2. The second goal of regression analysis is to obtain a measure of the error involved in using the Regression line as a basis for estimations. For this purpose, the standard error of the estimate is calculated. If the line fits the data closely, that is, if there is relatively little scatter of the observations around the regression line, a good estimate can be made of the y variable. On the other hand, if there is a great deal of scatter of the observations around the fitted regression line, the line will not produce accurate estimates of the dependent variable? 3. With the help of regression analysis, we can obtain the measure of the degree of association or correlation that exists between the two variables. The coefficient of determination calculated for this purpose measures the strength of the relationship that exists between the variables. It assesses the proportion of variance by the regression equation.
Hypothesis A basic economic theory is that for many commodities as price rises; the corresponding quantity supplied rises; as price falls, the quantity supplied also falls. That is there is a direct relationship between the price of the commodity and the quantity supplied. H0: There is no relationship between price and production H1: There is a significant relationship between price and production.
Coefficient of determination The ratio of the unexplained variation to the total variation represents the proportion of variation in y that is not explained by regression on x. Subtraction of this from 1 gives the amount of variation in y that is explained by regression on x. The statistic used to express this proportion is called the coefficient of determination and is denoted by R2. It may be written as follows: R2 =1- (variation in y remaining after regression on x)/total variation in y R2 =1- (error sum of squares)/total sum of squares The value 2 R is the proportion of the variation in the dependent variable y explained by regression on the independent variable x.
Factors affecting the supply model ? The own price of the commodity: Quantity supply is influenced by the own price of the product under consideration. The quantity supplied, and prices are directly related. That is if the cost of a goods increase, quantity supplied increases and vice versa. ? The state of production technology: Any technological chance that decreases (increases) production costs will increase (decrease) the profits be able to earn at any given charge of the commodity under consideration. Since increased (decreased) profitability tends to lead to increased (decreased) production, this change will shift the curve to right (left). Indicating an increased (decreased) willingness or ability to produce the commodity and offer it for sale at each possible price. ? The cost of factors of production: A change in expenses of factors of production changes the Producers willingness to sell because it changes the cost of production and hence profit. A rise (fall) in the costs of factors of production sift supply curve of the commodity to the left (right), indicating that less (more) will be abounding at any given price. ? Price expectation: Expectations concerning the future price of a commodity can also affect the Producers current willingness to supply that product. Farmers might withhold some of their current chili harvests, from the current market or a higher guava price in future, which causes a shift in the supply curve to left. ? The number of buyers in the market: The larger the number of buyers in the market of the goods, the greater will be the market supply for that commodity.
Global Disclosure of Economics and Business, Volume 4, No 1/2015
Journal