illustrate a multiple comparison model where both fixed and random effects approaches to the permanent subject effect may be relevant, consider data from Horrace and Schmidt (2000) applied to loglinear production functions.

In Example 11.6 (Indonesian rice farm data) assess gain from introducing AR1 errors (in addition to unstructured errors) in both random and fixed effects bi models. Also find the posterior probabilities that farms 1 to 171 are the best – in terms of having highest bi after allowing for inputs. Which farm has the highest probability of being best?

Multiple comparison with the best To illustrate a multiple comparison model where both fixed and random effects approaches to the permanent subject effect may be relevant, consider data from Horrace and Schmidt (2000) applied to loglinear production functions. The observations are rice outputs for n = 171 Indonesian farms over T = 6 seasons with inputs being

1.       metric variables: seed in kg (KGS), urea (KGN) and trisodium phosphate (KGP), labourhours (LAB) and land in hectares (LAND).

2.       categorical variables: namely B P = 1 if pesticides used, 0 otherwise; VAR (1 if high-yield rice varieties planted, 2 if mixed varieties planted, 3 if traditional varieties planted); and BWS (1 for wet season).

What are the multiple correlations of three sets of predictors and overall state of health?

What are the multiple correlations of three sets of predictors and overall state of health? The first set of predictors contains demographic variables (age and years of education). The second….

What conclusions might you draw from these data?

According to the Death Penalty Information Center, death penalty states record higher murder rates than non-deathpenalty states. On January 1, 2014, the average murder rate among death penalty states was….

How would you defend these reforms to persons who advocate for tough-on-crime approaches?

The 10-member Colson Task Force on Federal Corrections is composed of Republican and Democrat federal and state congressional leaders, a federal judge, a U.S. attorney, a state warden, a professor,….