Chapter 7 Flashcards
What is the definition of a consistant and strongly consistant estimator? What do they rely on?
What is the definition of pointwise and uniform convergence? Which one is stronger?
What is the definition of identifyable uniqueness? Why is it important?
What is the definition of a metric? (name all four)
What is the definition of a norm? (name all three)
When is an estimator consistant? (name both conditions)
When is an estimator strongly consistant? (name both conditions)
What are the two conditions for uniform convergence?
What are the two conditions for uniform almost sure convergence? What does it imply?
How can we simply show stochastic equicontinuity (theorem)?
Which three do you need to state to simply state stochastic equicontuity?
How can we simply show stochastic equicontinuity in time varying parameter models?
What is the definition of parameter identification?
What is the definition of observational equivilance?
How can be shown that ML estimators are unique?
How can be shown that the LS estimators are unique?
What is the consistence under misspecification?
What is the Set consistency of extremum estimators theorem?
