Estimate a linear probability model:

Consider the multiple regression model:

y = β₀+β₁x₁+.....+β_kx_k +u

Suppose that assumptions MLR.1-MLR4 hold, but not assumption MLR.5

(a) Are the standard t and F-statistics valid if the sample is suf?ciently large? If not, what would you do about it?

(b) Suppose that the sample is very small. What is the implication for the heteroscedas-tic robust standard errors? Suppose that someone said that you instead should use Feasable Generalized Least Squares to correct for heteroscedasticity in small samples. What would be your response?

(a) Estimate a linear probability model that explains whether a man was arrested in 1986 by his prior criminal and employment record (pcnv, avgsen, tottime, ptime86, qemp86). Use robust standard errors. Why do you need to correct for heteroscedasticity? Justify

(b) What is the interpretation of the intercept?

(c) Interpret the effect of time locked up in 1986 (ptime86) on the probability of arrest. Is this a big effect?

(d) Set all explanatory variables to zero, except for ptime86, and compute the predicted probability of arrest in 1986 for a man who was locked up in all 12 months in 1986. Does this prediction make sense?

(e) Test whether avgsen and tottime are jointly statistically signi?cant at the 5% level. Would your test be valid if you had not used robust standard errors in (a)?

(f) Calculate the predicted probabilities and verify that all the ?tted values are between 0 and 1. What is the smallest value you observe? And the largest?

Posted Date: 2/14/2013 2:21:36 AM | Location : United States

Ask an Expert

Related Discussions:- Estimate a linear probability model, Assignment Help, Ask Question on Estimate a linear probability model, Get Answer, Expert's Help, Estimate a linear probability model Discussions

Write discussion on Estimate a linear probability model
Your posts are moderated

Write your message here..

Related Questions

Control chart, construction of control chart,n chart construction of control chart,n chart

Multivariate statistical methods, As one of the oldest multivariate stati... As one of the oldest multivariate statistical methods of data reduction, Principal Component Analysis (PCA)simplifies a dataset by producing a small number of derived

Standard gaussian random variable , You will recall the function pnorm() fr... You will recall the function pnorm() from lectures. Using this, or otherwise, Dteremine the probability of a standard Gaussian random variable exceeding 1.3.  Using table(), or

Bernoulli''s theorem, Bernoulli's Theorem If a trial of an experiment c... Bernoulli's Theorem If a trial of an experiment can result in success  with probability p and failure with probability q (i.e.1-p) the probability of exactly r success in n tri

Measures of dispersion, Measures of Dispersion ... Measures of Dispersion Box 3: Food vs. Oil Below are the figures for foodgrain procurement   and cr

Convenience sampling, Convenience Sampling It means a convenient sample... Convenience Sampling It means a convenient sample is obtained by selecting convents units from the universe. Convenient sample is also known as chunk. It   means a fraction of

#title.partial market equilibrium, what is non linear modl what is non linear modl

Correlation matrix table, A.    Do the correlation matrix table. B.    W... A.    Do the correlation matrix table. B.    Which variable (s) has the largest correlation coeffieient which is not a perfect correlation? C.    Which variable (s) has the s

Calculate the frequency distribution, The Neatee Eatee Hamburger Joint spec... The Neatee Eatee Hamburger Joint specializes in soyabean burgers. Customers arrive according to the following inter - arrival times between 11.00 am and 2.00 pm: Interval-arriva

Purposive or judgement sampling, Purposive or Judgement Sampling Under ... Purposive or Judgement Sampling Under this method of sampling, the choice  of selection of sample  items from the universe  depends exclusively on the judgement  of the investi