Pictures Flashcards
What is the estimate for αhat in this equation: yt=αyt-1+ut
what is the weighted least squares model
E(ui^2|xi)=σ^2h(xi)
Equation for F test based on R^2
Equation for Logit
Equation for probit model
φ(.) is the standard normal cumulative distribution function
what is the densitiy of the logit
what is the marginal effects of the Logit
what is the marginal effects of the Probit
what is the probability P(X=x) for a Bernoulli distribution
what is the little tricks that help you derive the OLS estimator
what are the conditions for Pooled OLS to be consistent and normally distributed in large samples
what are the conditions for random effects GLS to be consistent and normally distributed in large samples
what are the conditions for Fixed Effects OLS to be consistent and normally distributed in large samples
what are the conditions for FIirst Differenced OLS to be consistent and normally distributed in large samples
what is the random effects GLS conditional variances with strong exogeneity assumption E(ui|Xi)=0
What is the estimator for the variance of βRE given conditional homoskedasticity and no serial correlation of uit, E(uituis|Xi)=0
what is the between estimator
What is the fixed effects OLS equation that takes into account endogeneity
What is the further assumption on Fixed Effects OLS to make it efficient
That the uit are further conditionally homoskedastic and not serially correlated. uiui’ because its a matrix
what is the setting for the first differenced OLS
What is the process of first differenced OLS
Given this equation what is the condition for the OLS estimator for β to be consistent and normally distributed in large samples
Given this equation, assuming there is feedback from ui,t-1 to xit, show that the FD OLS model is biased and inconsistent
How is the endogeneity problem of the fixed effects OLS solved
First differenced model is a good starting point. Then use xi,t-j as an instrument as it satisfies the exogeneity condition as it is not correlated with (uit-ui,t-1) and is clearly correlated with the endogenous variable (xit-xi,t-1) as x responds to past realised shocks
what is the density of the standard logistic distribution
what is the density of the standard normal distribution function (probit)
what are the marginal effects of the logit model
what is the marginal effect of the probit model
what is the maximum likelihood estimation for the probit model
Maximum likelihood for the probit: the conditional distribution yi | xi is Bernoulli
what is βhat in matrix form
how do you work out the conditional log-likelihood function (with picture)
write down the conditional density, then take logs
what is the derivative of the logistic function
what is the derivatives of logL wrt beta for logit
derivation ex lec 6
what is the derivative of the logL wrt beta for probit
what is the conditional log-likelihood function
what is the density of a random variable
the derivative of its sumulative distribution function
what is the derivative of LogL wrt beta for the probit model
what is the AR(1) correlogram for equation yt=ρyt-1+et
is AR(1) weakly dependent
AR(1) is weakly stationary and automatically satisfies weak dependence because Var=
equation for an f test
what is the White robust variance estimator
equation for the average marginal effect of probit
what is the marginal effects of probit at means
average marginal effect of probit when binary variable
what is the hausman test
what is the covariance in an AR(1) process
how do you get to the covariance for an AR(1) process
substitute for ytyt-1 then ytyt-2, but don’t substitute the whole equation in
what is the variance covariance matrix of an AR(1) process
E(εtεt-j)=
what is the variance covariance matrix for heteroskedasticity
