Question 1 Explain if the following statements are either true or false and give reasons for each statement true and false. If you can answer all atleast start from 1.4 1.1 The error term is a component of measurable variables which had been omitted in the course of econometric modeling. 1.2 Every estimated parameter in econometric modeling is equally important for policy formuation. 1.3 Theoretical propositions in economics are often limited by data issues thereby limiting the extent to which they could be subjected to econometric verification. 1.4 A ependent variables in a particular model cannot be used as independent variable in another model depending on the problem of investigation. 1.5 Forecasting ability of estimated parameters in econometric analysis implies that over a long period of time, the estimated parameters is not changing. 1.6 The sampling requirements for all kind of data whether cross-section, time series or panel are always the same. 1.7 Efficiency and sufficiency attributes of our estimator are the most important factors for ensuring their suitability for forecasting purposes. 1.8 Violation of the efficiency attribute of estimators leads to commitment of type 1 error. 1.9 Regression analysis is not necessary since statisticians have developed correlation analysis. 1.10 Agricultural Economists only require more knowledge of Statistics, Econometrics is not so important.
Question 1
Explain if the following statements are either true or false and give reasons for each statement true and false.
If you can answer all atleast start from 1.4
1.1 The error term is a component of measurable variables which had been omitted in the course of econometric modeling.
1.2 Every estimated parameter in econometric modeling is equally important for policy formuation.
1.3 Theoretical propositions in economics are often limited by data issues thereby limiting the extent to which they could be subjected to econometric verification.
1.4 A ependent variables in a particular model cannot be used as independent variable in another model depending on the problem of investigation.
1.5
1.6 The sampling requirements for all kind of data whether cross-section, time series or panel are always the same.
1.7 Efficiency and sufficiency attributes of our estimator are the most important factors for ensuring their suitability for forecasting purposes.
1.8 Violation of the efficiency attribute of estimators leads to commitment of type 1 error.
1.9 Regression analysis is not necessary since statisticians have developed correlation analysis.
1.10 Agricultural Economists only require more knowledge of Statistics, Econometrics is not so important.
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