Paneldata and OLS estimation help
Posted: Thu Mar 17, 2016 10:16 am
Hi guys,
I'm a Student of economics and I really need some help with the following excercise. I did not have the lecture yet. Still I want to solve the excercise before the lecture. It would be great if you could help me.
I'm sorry for the bad structured text, but I'm new here and I have no clue how to structure it better.
1. A researcher investigating the determinants of crime in the United Kingdom has data for 42 police regions over 22 years. She estimates by OLS the following regression
ln(cmrt)it = alphai + deltat + 1unrtmit + 2proythit + 3ln(pp)it + uit i = 1,...,42; t = 1,...,22
where cmrt is the crime rate per head of population, unrtm is the unemployment rate of males, proyth is the proportion of youths, pp is the probability of punishment measured as (number of convictions)/(number of crimes reported). alpha and delta are area and year fixxed effects, where i equals one for area i and is zero otherwise for all i, and t is one in year t and zero for all other years for t = 2,...,22. 1 is not included.
(a) What is the purpose of excluding 1? What are the Terms alpha and delta likely to pick up?
(b) Estimation by OLS using heteroskedasticity and autocorrelation-consistent standard errors results in the following output, where the coefficients of the fixxed effects are not reported: ln(cmrt)it = 0:063unrtmit + 3,739proythit 0,588ln(pp)it; R2 = 0,904; Standarderror for unrtm=(0,109); standard error for proyth= (0,179); standard error for pp= (0,024)
What is the effect of a ten percent increase in the probability of punishment?
I'm a Student of economics and I really need some help with the following excercise. I did not have the lecture yet. Still I want to solve the excercise before the lecture. It would be great if you could help me.
I'm sorry for the bad structured text, but I'm new here and I have no clue how to structure it better.
1. A researcher investigating the determinants of crime in the United Kingdom has data for 42 police regions over 22 years. She estimates by OLS the following regression
ln(cmrt)it = alphai + deltat + 1unrtmit + 2proythit + 3ln(pp)it + uit i = 1,...,42; t = 1,...,22
where cmrt is the crime rate per head of population, unrtm is the unemployment rate of males, proyth is the proportion of youths, pp is the probability of punishment measured as (number of convictions)/(number of crimes reported). alpha and delta are area and year fixxed effects, where i equals one for area i and is zero otherwise for all i, and t is one in year t and zero for all other years for t = 2,...,22. 1 is not included.
(a) What is the purpose of excluding 1? What are the Terms alpha and delta likely to pick up?
(b) Estimation by OLS using heteroskedasticity and autocorrelation-consistent standard errors results in the following output, where the coefficients of the fixxed effects are not reported: ln(cmrt)it = 0:063unrtmit + 3,739proythit 0,588ln(pp)it; R2 = 0,904; Standarderror for unrtm=(0,109); standard error for proyth= (0,179); standard error for pp= (0,024)
What is the effect of a ten percent increase in the probability of punishment?