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A,ECONOMIC DATA
there are three kinds of economic data: quantitative (cardinal), ordinal(ordered), qualitative.

the ordinary can not use in the econometrics model. coz they do not express any quatily measures. for example: how much you love your job? 5: very much 4: like 3: do not like or hate 2: do not like 1: hate.

the qualitative sometimes called indicator wariable or binary or Boolean variable. more often, dummy variable.

INSTRUMENTAL VARIABLE ESTIMATORS
three kinds things to violate the zero-conditional-mean assumption: endogeneity, ommitted-variable bias, and errors in cariables. the solution is the same. IV

B,BASIC Model ASSUMPTIONS

一，classic model

For finite model, assumptions are

1,linearity ,to make sure that the model is correct, if the model is not linearly , the estimation methods can not used. Sometimes the model are not linear, we can change it to the linearly one.

2,strict exgoneity ,this is can be violated and cause the series correlation problem.

3,no multicorrelation. This is only for calculation, nothing special

4,homo, this is also can be violated and become the heter problem

If we need test, we need normality assumption. Of course, it is just a popular assumption, somebody pointed out normality is not a perfect assumption

For large sample.

The assumptions are

1, linearity （同FINITE SAMPLE）

2,predetermined, this is weaker than the a2 in finite, but it is more practical.

3ergodic and stationary, this is like the iid which is useful to get the CLT and combind the data with normality

4,g is mds whith 2^nd finite moment, this is to make sure that the s is consistent.

5, rank condition(identification for iv), this is only for calculation, too.

We do not need the normality assumption thanks to the CLT.

And the home assumption makes the estimation much easier.

the clues to study econometrics