Cite as: U. Colombino; 2013; A new equilibrium simulation procedure with discrete choice models; International Journal of Microsimulation; 6(3); 25–49. doi: 10.34196/ijm.00087
Abstract
Many microeconometric models of discrete choice include alternative-specific constants meant to account for (possibly besides other factors) the density or accessibility of particular types of alternatives. A notable area of application is labour supply, where for example part-time jobs vs. full-time jobs might be more or less accessible. The most common use of these models is the simulation of tax-transfer reforms. The simulation is usually interpreted as a comparative statics exercise, i.e. the comparison of different equilibria induced by different policy regimes. The simulation procedure, however, typically keeps fixed the estimated alternative-specific constants. In this note we argue that this procedure is not consistent with the comparative statics interpretation. Since the constants reflect the number of jobs and since the number of people willing to work changes as a response to the change in tax-transfer regime, the new equilibrium induced by the reform implies that the constants should also change. A structural interpretation of the alternative-specific constants leads to the development of a simulation procedure consistent with the comparative statics interpretation. The procedure is illustrated with a simulation of alternative reforms of the income support policies in Italy.
This article contains 1 table.
Tables
Table 1. Effects of the reforms according to the different simulation procedures.
Rank based on the Gini Social Welfare Function
Monthly Average Household Net Income
Top Marginal Tax Rate (%)
Head-Count Poverty Ration (%)
N. E.
η=0
η=0.5
η=1
η=∞
N. E.
η=0
η=0.5
η=1
η=∞
N. E.
η=0
η=0.5
η=1
η=∞
N. E.
η=0
η=0.5
η=1
η=∞
Pre-Reform
7°
7°
7°
7°
3°
2234
2228
2231
2231
2214
43.7
43.7
43.7
43.7
43.7
4.33
4.33
4.33
4.33
4.42
GMI-50
4°
4°
4°
4°
2°
2,185
2,366
2,198
2,200
2,163
45.9
44.9
45.8
45.7
45.9
2.26
2.95
2.48
2.48
2.44
GMI-75
6°
2°
5°
5°
5°
2,176
2,421
2,189
2,192
2,134
48.2
45.7
47.3
47.2
47.7
0.87
1.32
0.81
0.81
0.72
GMI-100
5°
1°
6°
6°
7°
2,168
2,476
2,169
2,173
2,091
51.3
48.2
50.9
51.1
52.1
0.01
0.26
0.00
0.01
0.00
UBI-50
2°
3°
1°
1°
1°
2,185
2,334
2,195
2,199
2,162
50.9
50.0
50.9
50.8
50.9
0.52
0.62
0.52
0.52
0.46
UBI-75
1°
5°
2°
2°
4°
2,173
2,244
2,180
2,186
2,127
55.4
54.7
55.3
55.2
55.5
0.04
0.06
0.04
0.04
0.02
UBI-100
3°
6°
3°
3°
6°
2,158
1,986
2,164
2,170
2,087
59.9
62.0
59.8
59.7
60.3
0.00
0.00
0.00
0.00
0.00
N.E. = No-equilibrium simulation procedure;
Head-Count Poverty Ratio = percentage of households below the Poverty Level (as defined in Section 5.2);
