8 Tax reforms and simulations
The previous sections have all concentrated on the specification and estimation of the discrete hours labour supply model. This section turns to the use of such models in behavioural tax microsimulation. Microsimulation models are used to examine the effects of hypothetical or actual tax and benefit reforms, using a large cross-sectional data set that reflects the degree of heterogeneity found in the population. Policy changes for which this can be done are mostly of a financial type, such as a change in the amount of benefits, the withdrawal rate, eligibility for benefits, or the range of income where a withdrawal rate applies.[41] Such changes result in a change in net income at each of the discrete hours points, which may result in a shift in the optimal choice for an individual.
First, subsection 1 describes the method of calibration used to place individuals in their (pre-reform) observed discretised hours level under the tax system in operation at the time of the survey. The generation of a post-reform probability distribution of hours worked for each individual, conditional on them being at their observed pre-reform hours, is also described. Secondly, subsection 2 provides a small numerical example of a tax reform, using the three hypothetical individuals used in the illustration of maximum likelihood estimation.
8.1 Individual calibration
Once the parameters of the specified preference functions have been estimated, they can be used to simulate the effects on labour supply of policy changes.[42] A common approach is to use a base data set and start from the labour supply observed in this data set to obtain a starting point for simulation based on the observed labour supply under a particular tax and benefit system. This is achieved by calibration, which means that error terms are drawn from the relevant distribution (for example, the extreme value distribution) and added to the measured utility in each of the hours points. If this results in the observed labour supply being the optimal choice for the individual, the draw is accepted; otherwise another set of error terms is drawn and checked. This is repeated until the required number of sets of error terms is drawn.
These sets of error terms that resulted in the observed labour supply are then used to compute a distribution of labour supply after a specified reform.[43] Given the individual’s characteristics and draws for the error term, utility at each hours level after the change can be determined. In this way, a probability of being in each of the discrete hours points, conditional on the pre-reform labour supply, can be derived for each individual.
Notes
- [41]These contrast with, for example, changes in rules regarding the duration of benefits, residence requirement, willingness to accept training, the ability to refuse job offers, and reasons for job loss. These are important design features of a transfer system, but are difficult to accommodate in microsimulation.
- [42]Creedy et al. (2002) discuss microsimulation modelling in detail. Examples of microsimulation studies are Bingley et al. (1995), Scholz (1996), Blundell et al. (2000), Bingley and Walker (2001), Duncan and Harris (2002), Creedy, Kalb and Kew (2003), Gerfin and Leu (2003).
- [43]The more error terms that are drawn, the more accurate is the computed distribution, especially for those points with low probability.
