#### Econometrics Assignment Help, Homework Help

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Econometrics:

Econometrics is a specialized branch of social sciences in which various tools of mathematics and statistics are used and it helps in analyzing economic problems. Econometrics is basically concerned with the experimental verification of economic theory. It is method to define the relationship between key economic factors such as wages, capital, population, bank interest rates, and fiscal & monetary policies. It is a method to study economic relationships formed by a combination of economic theory and statistical techniques.

The author Wooldridge has defined Econometrics as:

"The development of statistical methods for estimating testing economic theories, economic relationships, and evaluating and implementing government and business policies."

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Scope for Students:

Mastering in econometrics helps an individual in determining and successfully carrying out the procedure which includes correct specification of models, manipulation of data to avoid errors knowledge of various methods of estimation, and testing of hypothesis.

In real practice economic relationships are tested by using combination of statistics and economic theory.

Statistical methods which are used in Econometrics are as follows:

• Linear regression
• Regression analysis

Various Data Sets to which Econometric Analyses can be applied:

• Time-series data
• Panel data
• Cross-sectional data
• Multidimensional panel data

Classification of Econometric analysis (based on number of relationships modeled):

• Simultaneous equation methods
• Single equation methods

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Topics covered by our Econometrics Assignment Help experts:

• Regression Equation
• Conditional Variance
• Linear Regression
• Least Squares Estimation
• Normal Regression Model
• Model in Matrix Notation
• Gauss-Markov Theorem
• Multicollinearity
• Sampling Distribution
• Asymptotic Normality
• Covariance Matrix Estimation
• T-Tests
• Confidence Intervals
• F-Tests
• Monte Carlo Simulation
• Testing for Heteroskedasticity
• Forecast Intervals
• NonLinear Least Squares
• Quantile Regression
• The Bootstrap
• Asymptotic Expansions
• Univariate Time Series
• Multivariate Time Series
• Kernel Density Estimation
• Asymptotic Transformations

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