Questions from Econometrics

Q: Limited Information Maximum Likelihood Estimation. Consider a bivariate distribution for x

Limited Information Maximum Likelihood Estimation. Consider a bivariate distribution for x and y that is a function of two parameters, and b. The joint density is f(x, y | , ). We consider maximum l...

Q: Using the gasoline market data in Appendix Table F2.2,

Using the gasoline market data in Appendix Table F2.2, use the partially linear regression method in Section 7.4 to fit an equation of the form

Q: Show that the likelihood inequality in Theorem 14.3 holds for

Show that the likelihood inequality in Theorem 14.3 holds for the Poisson distribution used in section 14.3 by showing that / is uniquely maximized at θ = θθ. (Hint: First show that the expectation...

Q: For random sampling from the classical regression model in (14-

For random sampling from the classical regression model in (14-3), reparameterize the likelihood function in terms of / Find the maximum likelihood estimators of  and δ and obtain the asymptotic cov...

Q: Consider sampling from a multivariate normal distribution with mean vector /

Consider sampling from a multivariate normal distribution with mean vector and covariance matrix 2I. The log-likelihood function is show that the maximum likelihood estimators of t...

Q: The exponential distribution has density / How would you

The exponential distribution has density / How would you obtain a random sample of observations from an exponential population?

Q: The Weibull population has survival function / How would you

The Weibull population has survival function How would you obtain a random sample of observations from a Weibull population? (The survival function equals one minus the cdf.)

Q: Derive the first-order conditions for nonlinear least squares estimation of

Derive the first-order conditions for nonlinear least squares estimation of the parameters in (15-2). How would you estimate the asymptotic covariance matrix for your estimator of /

Q: Suppose the distribution of yi |  is Poisson,

Suppose the distribution of yi |  is Poisson, We will obtain a sample of observations, yi, , yn. suppose our prior for is the inverted gamma, whic...

Q: A binomial probability model is to be based on the following index

A binomial probability model is to be based on the following index function model: The only regressor, d, is a dummy variable. The data consist of 100 observations that have the following: Obtain th...