Table 3

Binomial models estimated by generalised estimating equations—ORs

Dependent variable—illegal cigarettes 1, legal cigarettes 0
VariableModel 1Model 2
AllMenWomenAllMenWomen
Tax per pack
 2008 reference
  20102.09*2.74*1.79*
  20123.34*4.61*2.85*
  20143.28*3.90*3.10*
Gender # tax per pack
 0 # 2008 reference
  0 # 20102.07*2.16*
  0 # 20122.82*3.08*
  0 # 20142.15*2.42*
  1 # 20080.63*
  1 # 20101.56*
  1 # 20121.49*2.29*
  1 # 20141.40*2.10*
Gender # city
 0 # Montevideo reference
  0 # Durazno0.750.82
 0 # Maldonado0.640.83
  0 # Rivera14.2*14.3*
  0 # Salto1.86‡1.88‡
 1 # Montevideo1.04
  1 # Durazno0.32§0.34§
 1 # Maldonado0.900.89
  1 # Rivera12.9*10.40*
  1 # Salto0.92
City region1.49‡1.76*1.18*
Illegal cigarettes offer1.07*1.08*1.08*0.990.991.00
Age1.17*1.31*1.081.20*1.34*1.11§
Gender1.40*2.62*
Education0.56*0.79§0.45*0.57*0.79§0.46*
Income0.54*0.45*0.63*0.53*0.45*0.60*
Consumption intensity1.04*1.05*1.04*1.04*1.05*1.04*
Margins effects (the Stata option dy/dx(varlist) estimate marginal effect of variables in varlist)
Tax per pack
 2008 reference
 20100.065*0.078*0.055*0.051*0.072*0.049*
 20120.121*0.137*0.111*0.093*0.105*0.092*
 20140.118*0.117*0.123*0.074*0.083*0.082*
Gender
 0 reference
 10.034*
City
 Montevideo reference
 Durazno−0.059*−0.019−0.118
 Maldonado−0.020−0.044−0.013
 Salto0.0240.059‡−0.009
 Rivera0.432*0.249*0.258*
City region0.044*0.055*0.019
Illegal cigarettes offer0.007*0.007‡0.008*0.0000.0000.000
Age0.017*0.027*0.0090.019*0.027*0.011§
Gender0.037*0.100*
Education−0.063*−0.023§−0.093*−0.058*−0.022§−0.085*
Income−0.064*−0.077*−0.054*−0.066*−0.075*−0.057*
Consumption intensity0.005*0.005*0.005*0.005*0.004*0.005*
Observations380416132191380416132191
  • Significant at

  • *1%.

  • †In model 2 women, reference is 1#2008 and 1#Montevideo (women=1).

  • ‡5%.

  • §10%.