Mathematical economics is concerned with economic theory and its formulation in a mathematical style, but it stops there, as this is done without testing its conformity with economic logic. Economic statistics, on the other hand, is concerned with collecting and classifying economic data, and it also does not give any importance to analyzing the results of this data. However, what distinguishes econometrics from economic statistics and mathematical economics is its focus on standard foundations and experimental tests of economic hypotheses. The relationship between these sciences is strong, as econometrics uses available data provided by economic statistics to determine and interpret relationships between economic variables, then uses the results for prediction and analysis. In turn, econometrics relies on mathematical economics to describe hypotheses based on theoretical reasoning in a numerical form, and then evaluates them. In short, econometrics attempts to benefit from the combination of economic theory and mathematical methods within the framework of mathematical economics, and then uses statistical methods to obtain quantitative estimates for use in decision-making, forecasting, and studying structural changes. The theory of econometrics is presented in this book in eleven chapters. The first chapter includes an introduction to define econometrics, its objectives, and its relationship with other sciences. The second chapter deals with simple linear regression analysis using the least squares method and hypothesis testing in the third chapter. The fourth chapter is dedicated to describing multiple linear regression and testing its hypotheses. The problems of the linear model, namely autocorrelation, multicollinearity, and heteroscedasticity, are reviewed in the fifth, sixth, and seventh chapters respectively. To explain the nature of simultaneous equations, the problem of simultaneous bias, and estimation methods, the eighth chapter is titled 'Simultaneous Equation Models'. The ninth chapter is a stop to present the problem of specification, explaining its nature and conditions. The tenth chapter reviews time-lagged variables in detail. The eleventh chapter is a final stop to present three regression models that include dummy variables, titled 'Dummy Variables'.

• Weight: 0.82 kg
• Dimensions: 17 × 24 cm