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Background note to Peter Dawkin's presentation "Welfare to work: labour supply responses to work incentives" at the Conference Sustaining Prosperity, 31 March - 1 April 2005, Melbourne.



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Background note to Peter Dawkins’ presentation “Welfare to Work: Labour Supply Responses to Work Incentives” at the Conference Sustaining Prosperity, 31 March - 1 April 2005, Melbourne

The MITTS model: a brief description

The Melbourne Institute Tax and Transfer Simulator (MITTS) is a behavioural tax

microsimulation model allowing detailed examination of the potential effects on

government direct tax revenue and expenditure of policy reforms to the tax and transfer

system.1

The static component of MITTS

MITTS calculates net incomes for individual households for which we have detailed

wage, labour supply, other income and household composition information. The results

for individuals can be weighted and aggregated to represent population level results on

government revenue and expenditure.

The most recent available sample of households represents the Australian population in

2000/2001. The same sample is used to represent populations from later years, where

employment, size, and composition of the population are uprated to the relevant level. A

further difference between the different years is that wage rates are updated with the

average wage index and other incomes are updated with the consumer price index (CPI).

The quarterly indices published by the Australian Bureau of Statistics are used.

The September 2004 social security and tax system of 2004/2005 including the latest

budget changes is used as the basis to construct our alternative systems2. Detailed

descriptions of alternative taxation and social security systems are used to calculate net

incomes in a particular year. The outcomes under the different systems can be compared.

1 For further details of the MITTS model see Creedy et al. (2002, 2004). 2 See publications from the Commonwealth Department of Family and Community Services, and the Department of Education, Science and Training (2004) for details on the social security system. For DVA payments see publications by the Department of Veterans’ Affairs (2004).

Behavioural simulations

Net incomes can be calculated at all possible hours of labour supply, assuming the gross

wage per hour does not change (for example there is no overtime pay in the model). For

workers the observed gross wage (earnings divided by the observed hours of work) is

used and for non-workers a gross wage is predicted from a wage model based on the

individual’s characteristics (such as education level and age).3

Marginal effective tax rates and a budget constraint (showing net incomes across the

possible range of labour supply) can identify potential disincentive effects on labour

supply of the tax and social security system. Disincentive effects can occur whenever an

additional hour of work is not rewarded by a corresponding increase in net income.

MITTS can evaluate incentive effects of alternative policies by predicting whether

individuals are expected to change their hours of work as a result. Only financial

incentives can be studied within MITTS. Individuals who are self-employed, over 65, a

full-time student or disabled are left at their observed labour supply. This group is

expected to behave differently from the other individuals of working age and to be less

responsive to financial incentives.

MITTS calibrates the predicted hours in the base case (the situation in 2000/2001, the

year in which our sample was collected) to the observed hours, to use as a starting point

for the reform. Estimated parameters from a labour supply model, which indicate a

person’s preference for time spent in employment in the labour market versus the

preference for income, are used to evaluate the different levels of net income at the

different levels of labour supply in the alternative tax systems. Several alternative

systems can be compared in this way. The labour supply parameters are based on

observed behaviour in the past. These parameters have been estimated using the best

3 See Kalb and Scutella (2002) for a description of the wage models.

available econometric techniques, using the same database that underpins the MITTS

model. 4

An effort is made to account for differences in preferences between individuals, an

obvious example is the age of the youngest child for mothers5, but of course not all

individual differences can be captured by a statistical model. This means there is

uncertainty associated with the predicted outcomes. Using the model, we can calculate

the probability of particular labour supply and net income combinations being the optimal

combination an individual can attain given their wage, other income and the tax and

social security system. Based on these probabilities, expected labour supply and expected

changes in labour supply can be calculated. Based on the expected labour supply

changes, potential savings or additional costs (compared to the static situation without

behavioural responses to policy changes) can be calculated.

An important assumption in these calculations is that individuals can change their labour

supply according to their preferences. In MITTS it is assumed that all additional labour

supply is met by a sufficient demand for labour.

Implicit Labour Supply Elasticities

The discrete labour supply model, which is used in the simulation of behavioural

responses to policy changes, does not provide straightforward wage elasticities with

regard to labour supply.6 However, elasticities can be calculated by comparing the

expected labour supply for an individual after a one-percent wage increase with the

expected labour supply under the original wage. The percentage change in labour supply

is an approximation of the elasticity. By doing this for each individual in the sample, the

4 The labour supply models on which the current behavioural responses in MITTS are based are described in Kalb (2002). Creedy and Kalb (2005) describe in detail how these parameters are estimated and how they are used to calculate labour supply responses in behavioural simulations. They also give a few simplified numerical examples to illustrate the procedures. 5

Having a preschool child decreases the predicted preference for employment in the labour market for mothers.

6 This wage elasticity is defined as follows: percentage change in labour supply percentage change in wage rate

average elasticity across the sample (or population when making use of the weights) can

be computed.

Table 1 presents these uncompensated wage elasticities for those in the population that

are allowed to change labour supply in MITTS. For self employed, full-time students,

disabled individuals and people over 65 it is assumed this elasticity is zero. In addition to

using predicted labour supply alone, we can use calibration and calculate the elasticity

starting from the observed labour supply for those already in work. For non-workers, the

elasticity cannot be computed because a percentage change starting from zero hours is

not defined. The two final columns in Table 1 present the predicted participation rate

changes resulting from a one-percent wage increase.

Table 1 Implied average uncompensated wage elasticities across the population for which labour supply is simulated7 Elasticity

derived from expected labour supply

Elasticity using calibrated labour supply (for positive hours only)

Change in participation derived from expected labour supply (in percentage points)

Change in participation derived from calibrated labour supply (in percentage points)

Married men 0.25 0.02 0.14 0.30

Married women 0.54 0.68 0.19 0.25

Single men 0.28 0.03 0.18 0.45

Single women 0.34 0.11 0.18 0.48

Lone parents 1.58 1.38 0.42 0.47

These implicit labour supply elasticities are similar to what is generally found within the

international literature on such elasticities. The results for married and single men and

women are well within the range of results usually found. The range of elasticities

published in the literature is fairly wide, with large differences between studies using

different data and/or approaches.8

7 This excludes the people over 65, disabled individuals, full-time students and the self employed. 8 See for example, overviews given by Killingsworth (1983), Killingsworth and Heckman (1986), Pencavel (1986) or more recently by Blundell and MaCurdy (1999) or Hotz and Scholz (2003).

The effect for lone parents is often found to be larger than for other groups and this is

what we find in MITTS. The elasticity implicit in MITTS is on the higher end of this

range internationally, although we will see evidence below that a high labour supply

responsiveness for lone parents in Australia has been found before by Murray (1996),

Duncan and Harris (2002), and Doiron (2004). Relatively few labour supply studies have

been done for Australia, but two relatively recent exceptions for lone parents are two of

the above mentioned papers: Murray (1996) and Duncan and Harris (2002).

Murray (1996) found values between 0.13 and 1.64, depending on the exact specification,

for part-time working lone mothers. The elasticities she finds, for full-time workers and

lone parents out of the labour force, are much smaller (at most 0.30). Murray used 1986

data, where only 13 per cent of all lone mothers worked part time and about 23 per cent

worked full time. In the 2001 data used here, around 50 per cent of lone parents work,

and about half of the workers work in between 1 and 35 hours per week.

Duncan and Harris (2002) analysed the effect of four hypothetical reforms, using a

previous version of the labour supply models underlying the behavioural responses in

MITTS. Two of these reforms are close to being a 10 per cent increase and 10 per cent

decrease in lone parents’ wage rates. The first one is to decrease the withdrawal rate for

lone parents by 10 per cent, which increases their marginal wage rate while they are on

lower levels of income. Duncan and Harris report that this is expected to increase labour

force participation by 2.5 percentage points and increase average hours by 0.55 hour. The

second reform increases the lowest income tax rate from 20 to 30 per cent. This is

expected to decrease participation by 2.8 percentage points and decrease average hours

by 1.2 hours. Comparing this to the effect of a 10 per cent wage increase using our latest

labour supply parameters, effects of a similar magnitude are found. That is, participation

is expected to increase by 3.0 percentage points and the average hours are expected to

increase by 1.3 hours.

Finally, Doiron (2004) evaluates a policy reform, which affected lone parents in the late

1980s, to find large labour supply effects that are likely to be due to this reform. In her

conclusion, she compares the effect she finds through her natural experiment approach

with predicted effects of policy changes from the MITTS model (as can be found in

Duncan and Harris (2002) or Creedy et al. (2003)). Based on the results from her

evaluation, she argues that observed shifts in labour supply of lone parents can equal or

even surpass the predictions based on behavioural microsimulation.

The above suggests that lone parents’ labour supply elasticities may be substantial. This

is not so surprising, given the low participation rate of lone parents and the tendency to

work low part-time hours, an increase in labour supply by one hour is going to be a larger

increase, percentage wise, than the same increase for a married man. For the other

demographic groups, elasticities amongst those working few hours are generally higher

than for those (in the same group) working more hours as well.

It should also be borne in mind that the lone parent group is the smallest demographic

group in our population. Thus, a change in their labour supply responsiveness would have

a relatively small effect on the overall result.

References

Blundell R. and MaCurdy, T. (1999), “Labor Supply: A Review of Alternative

Approaches”, in Handbook of Labor Economics, volume 3, eds.: O.C. Ashenfelter and D.

Card, North-Holland, Amsterdam, 1559-1695.

Commonwealth Department of Family and Community Services, and the

Department of Education, Science and Training (2004). A guide to Commonwealth

Government payments.

Creedy, J., Duncan, A.S., Harris, M., and Scutella, R. (2002) Microsimulation

Modelling of Taxation and The Labour Market: The Melbourne Institute Tax and

Transfer Simulator. Cheltenham: Edward Elgar.

Creedy, J., Kalb, G., and Kew, H. (2003) “Flattening the Effective Marginal Tax

Rate Structure in Australia: Policy Simulations Using the Melbourne Institute Tax and

Transfer Simulator”, The Australian Economic Review, 36(2), 156-172.

Creedy, J., Duncan, A.S., Kalb, G., Kew, H. and Scutella, R. (2004) The Melbourne

Institute Tax and Transfer Simulator (MITTS). The latest version of this User’s manual

can be downloaded from the Melbourne Institute web site:

http://www1.ecom.unimelb.edu.au/iaesrwww/lsfs/mitts.html

Creedy, J. and Kalb, G. (2005), “Discrete Hours Labour Supply Modelling:

Specification, Estimation and Simulation”, forthcoming in the Journal of Economic

Surveys, (an earlier version available as Melbourne Institute Working Paper no. 16/2003).

Department of Veterans’ Affairs (2004). DVA FACTS, DP 43, IS 21, IS 22, IS 30.

Doiron, D.J. (2004), “Welfare Reform and the Labour Supply of Lone Parents in

Australia: A Natural Experiment Approach”, The Economic Record, 80(249), 157-176.

Duncan, A. and Harris, M.N. (2002), “Simulating the Behavioural Effects of

Welfare Reforms Among Sole Parents in Australia”, The Economic Record, 78(242),

264-276.

Hotz, V.J., and Scholz, J.K. (2003), “The Earned Income Tax Credit”, in Means-Tested Transfer Programs in the United States, R. Moffitt (ed.), The University of

Chicago Press, 141-197.

Kalb, G. (2002), “Estimation of Labour Supply Models for Four Separate Groups in

the Australian Population”, Melbourne Institute Working Paper no. 24/2002.

Kalb, G. and Scutella, R. (2002), “Estimation of Wage Equations in Australia:

Allowing for Censored Observations of Labour Supply”, Melbourne Institute Working

Paper no. 8/2002.

Killingsworth, M.R. (1983), Labor Supply, Cambridge Surveys of Economic

Literature, Cambridge University Press, New York.

Killingsworth, M.R. and Heckman, J.J. (1986) “Female Labor Supply”, in

Handbook of Labor Economics, volume 1, eds.: O.C. Ashenfelter and R. Layard, North-Holland, Amsterdam, 103-204.

Murray, J. (1996), “Modelling the labour supply behaviour of sole parents in

Australia”, in Proceedings of the Econometric Society Australasian Meeting 1996,

Volume 4: Microeconometrics, eds. M. McAleer, P. Miller, C. Ong, 507-546.

Pencavel, J. (1986) “Labor Supply of Men”, in Handbook of Labor Economics,

volume 1, eds. O.C. Ashenfelter and R. Layard, North-Holland, Amsterdam, 3-102.