# Xavier Fernández i Marín # dg abr 21 15:52:57 CEST 2013 # Explain percentage of regulatory agencies in countries model { for (i in 1:d.I) { d.y.perc.betareg[i] ~ dbeta(a[i], b[i]) a[i] <- mu[i] * phi[d.ic[i]] b[i] <- (1 - mu[i]) * phi[d.ic[i]] logit(mu[i]) <- (theta[d.time[i]] ) + (beta[1, d.id.r[i]] * log.gdp.cap.reg.sc[i]) + (beta[2, d.id.r[i]] * igo.uniregional.number.sc[i]) + (beta[3, d.id.r[i]] * d.W.dist.reg.sc[i]) + (beta[4, d.id.r[i]] * d.W.imp.reg.sc[i]) + (beta[5, d.id.r[i]] * d.W.igo.uniregional.sector.economic.sc[i]) + (beta[6, d.id.r[i]] * d.W.hist.sc[i]) } # phi factor for (c in 1:d.C) { phi[c] ~ dgamma(0.001, 0.001) } # theta by time theta[1] ~ dnorm(0, 0.001) for (yr in 2:d.Y) { theta[yr] ~ dnorm(theta[yr-1], tau.theta) } tau.theta <- pow(sigma.theta, -2) sigma.theta ~ dunif(0, 10) # control variables by region for (r in 1:d.R) { #beta[1:5, r] ~ dmnorm(b0[1:5], B0[1:5,1:5]) for (b in 1:6) { beta[b, r] ~ dnorm(b0[b], tau.beta[b]) } } for (b in 1:6) { b0[b] ~ dnorm(0, 0.01) tau.beta[b] <- pow(sigma.beta[b], -2) sigma.beta[b] ~ dunif(0, 10) } # missing values for (i in 1:d.I) { log.gdp.cap.reg.sc[i] ~ dnorm(0, 1) } }