Use of dummy variables in estimating the fixed effects models of the panel data

Abdel-Latif Pharaoh, Hisham; Ibrahim Mahdi, Djla

	Use of dummy variables in estimating the fixed effects models of the panel data
Journal of Research Diyala humanity
Article 1, Volume 0, Issue 47, 2017, Pages 83-136
Authors
Hisham Abdel-Latif Pharaoh; djla ibrahim mahdi
Abstract
Published statistical data in two forms: two major annual data and data scan first one is the order of the numbers aggregated annual published regularly every year; either the data scan is data issued between the time periods may be equal or groups equal in this case is called data section balanced balanced panel or periods and groups unequal and this is called a data section unbalanced unbalanced panel data and according to the nature of the activities reflected in these data has been drawn in this research on the data scan balanced represented by sector (public, mixed, cooperative, private) for the period 2000_2005 term industrial large in Iraq has been relying on This research on the data scan balanced represented by sector (public, mixed, cooperative, private) for the period 2000_2005 term industrial large in Iraq, note that the form and nature of production for the period 2000-2002 differ from the period 2003-2005, and hence the importance of research to demonstrate the efficacy of a model (Least square dummy variables) fixed effects for the periods and totals are estimated in a manner endocrine variables (Pooled least square) and compare the model estimated in a manner least squares combined . In the extraction results (Eviews 5.1, limdep 2.0) has been relying on programs Econometrics The most important conclusions reached by the researchers is Ka follows: - - Fixed effects test results for the periods and groups Calculated non-moral, however, that the potential value of the test is greater than a significance level of F1. That the value of (0.05) and this means accepting the null hypothesis that the effects of fixed periods and totals equal to zero In other words, the model estimated by least squares style combined the best style of the model estimated fixed effects for the periods and groups. - The results of statistical analysis of the model in general. F1. Test Less the amount of (0.0) the level of moral F to test the potential value Moral (0.05) This means that the estimated model significantly. Any independent variables, namely b (number of workers, the value of production requirements, the value of sales) have a significant effect on the variable-based (the value of production). T2. Test Shows the model estimated above, that the moral value of the items below (0.05) and to the fact that the potential value. The amount of (0.0001) less than the level of moral .0.05 T to test 3. The value of the rate coefficient of determination The value of the rate coefficient of determination of the model estimate (0.993) and this means that the independent variables explain (99.3%) of the changes in the productive process and the remaining amount (0.7%) is attributable to factors which are listed in random error - Standard analysis by sector 1. The number of workers: - The number of workers was not significant in each sector (public, mixed, cooperative Greater than the significance level (0.05). T, private). So that the potential values to test 2. The value of the items: - The value of moral requirements in the cooperative sector and to the fact that the potential values Greater than the significance level (0.05). T to test 3. The value of sales: - That the value of sales was not significant in each sector (public, mixed, cooperative Greater than the significance level (0.05). T, private). So that the potential values to test And Ballenbp of the recommendations was as follows: - 1. As a component of work and the number of workers was not significant in each sector (public, mixed, cooperative, Private) should therefore be the increased attention through training and rehabilitation, raising wages and incentives and rewards 2. The need to provide the requirements of production and (b fuel - raw materials - packing materials - supplies services) at affordable prices in order to increase its contribution to the production process 3. Development and stimulate the industrial sector in various forms and through interest in investing and financing for this sector i
Keywords
Statistical data; balanced cross; sectional data; represented by sector; mixed; cooperative; private

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