Guyonne Kalb

Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation

The assumption behind discrete hours labour supply modelling is that utility-maximising individuals choose from a relatively small number of hours levels, rather than being able to vary hours worked continuously. Such models are becoming widely used in view of their substantial advantages, compared with a continuous hours approach, when estimating and their role in tax policy microsimulation. This paper provides an introduction to the basic analytics of discrete hours labour supply modelling. Special attention is given to model specification, maximum likelihood estimation and microsimulation of tax reforms. The analysis is at each stage illustrated by the use of numerical examples. At the end, an empirical example of a hypothetical policy change to the social security system is given to illustrate the role of discrete hours microsimulation in the analysis of tax and transfer policy changes.

Estimating the Effect of Counseling and Monitoring the Unemployed Using a Job Search Model

This paper examines the impact of the Counseling and Monitoring program for the unemployed with particular reference to their job finding rate, application intensity, and matching probability. The effectiveness of Counseling and Monitoring is measured by using a job search model in which the job finding rate is equal to the product of the application intensity and the matching probability. Counseling and Monitoring is an intensive job search assistance program designed to help unemployed people receiving unemployment benefits to find a job as quickly as possible. The empirical analysis is based on data from a social experiment. A sample of the inflow into unemployment was randomly assigned to a treatment and a control group. The empirical results, based on formal reduced-form models, show that Counseling and Monitoring does reduce the time taken to find a job because people participating in the program make more applications than those who are not participating, although no differences are found in matching probabilities.

A randomised trial and economic evaluation of the effect of response mode on response rate, response bias, and item non-response in a survey of doctors

BackgroundSurveys of doctors are an important data collection method in health services research. Ways to improve response rates, minimise survey response bias and item non-response, within a given budget, have not previously been addressed in the same study. The aim of this paper is to compare the effects and costs of three different modes of survey administration in a national survey of doctors.MethodsA stratified random sample of 4.9% (2,702/54,160) of doctors undertaking clinical practice was drawn from a national directory of all doctors in Australia. Stratification was by four doctor types: general practitioners, specialists, specialists-in-training, and hospital non-specialists, and by six rural/remote categories. A three-arm parallel trial design with equal randomisation across arms was used. Doctors were randomly allocated to: online questionnaire (902); simultaneous mixed mode (a paper questionnaire and login details sent together) (900); or, sequential mixed mode (online followed by a paper questionnaire with the reminder) (900). Analysis was by intention to treat, as within each primary mode, doctors could choose either paper or online. Primary outcome measures were response rate, survey response bias, item non-response, and cost.ResultsThe online mode had a response rate 12.95%, followed by the simultaneous mixed mode with 19.7%, and the sequential mixed mode with 20.7%. After adjusting for observed differences between the groups, the online mode had a 7 percentage point lower response rate compared to the simultaneous mixed mode, and a 7.7 percentage point lower response rate compared to sequential mixed mode. The difference in response rate between the sequential and simultaneous modes was not statistically significant. Both mixed modes showed evidence of response bias, whilst the characteristics of online respondents were similar to the population. However, the online mode had a higher rate of item non-response compared to both mixed modes. The total cost of the online survey was 38% lower than simultaneous mixed mode and 22% lower than sequential mixed mode. The cost of the sequential mixed mode was 14% lower than simultaneous mixed mode. Compared to the online mode, the sequential mixed mode was the most cost-effective, although exhibiting some evidence of response bias.ConclusionsDecisions on which survey mode to use depend on response rates, response bias, item non-response and costs. The sequential mixed mode appears to be the most cost-effective mode of survey administration for surveys of the population of doctors, if one is prepared to accept a degree of response bias. Online surveys are not yet suitable to be used exclusively for surveys of the doctor population.

Getting Doctors into the Bush: General Practitioners' Preferences for Rural Location

A key policy issue in many countries is the maldistribution of doctors across geographic areas, which has important effects on equity of access and health care costs. Many government programs and incentive schemes have been established to encourage doctors to practise in rural areas. However, there is little robust evidence of the effectiveness of such incentive schemes. The aim of this study is to examine the preferences of general practitioners (GPs) for rural location using a discrete choice experiment. This is used to estimate the probabilities of moving to a rural area, and the size of financial incentives GPs would require to move there. GPs were asked to choose between two job options or to stay at their current job as part of the Medicine in Australia: Balancing Employment and Life (MABEL) longitudinal survey of doctors. 3727 GPs completed the experiment. Sixty five per cent of GPs chose to stay where they were in all choices presented to them. Moving to an inland town with less than 5000 population and reasonable levels of other job characteristics would require incentives equivalent to 64% of current average annual personal earnings (

Moving from Unemployment to Permanent Employment: Could a Casual Job Accelerate the Transition?

116,000). Moving to a town with a population between 5000 and 20,000 people would require incentives of at least 37% of current annual earnings, around

Children, Labour Supply and Child Care: Challenges for Empirical Analysis

68,000. The size of incentives depends not only on the area but also on the characteristics of the job. The least attractive rural job package would require incentives of at least 130% of annual earnings, around

Accounting for population ageing in tax microsimulation modelling by survey reweighting

237,000. It is important to begin to tailor incentive packages to the characteristics of jobs and of rural areas.

Demand for Childcare Services and Labour Supply in Australian Families

This article compares the time taken to exit from unemployment to permanent work with the time taken to exit from unemployment to permanent work through casual work.

Who should receive recruitment and retention incentives? Improved targeting of rural doctors using medical workforce data

The aim of this paper is to give an overview of the important issues relating to labour supply of the primary carer in a household. Childcare plays a central role in allowing the primary carer time away from young children in the household. Therefore, childcare use is a central topic of this paper as well. There are a number of different aspects to childcare, such as price, quality, availability and type of service. This paper discusses analytical problems and challenges, taking Australian data, policy and experience as a focus, but drawing on a wide range of international empirical studies. It reports results from previous research on childcare use and labour supply, and it outlines areas requiring more study. The focus of the paper is on economic research.

How do rural GPs' workloads and work activities differ with community size compared with metropolitan practice?

This paper investigates the use of sample reweighting in a behavioural tax microsimulation model, to examine the implications for government taxes and expenditure of population ageing in Australia. First, a calibration approach to sample reweighting is described, producing new weights which achieve specified population totals for selected variables, subject to the constraint that there are minimal adjustments to the weights. Second, the performance of the Australian Bureau of Statistics’ (ABS) weights provided with the 2001 Survey of Income and Housing Cost (SIHC) was examined and it was found that reweighting does not improve the simulation outcomes for the 2001 situation, so the original ABS weights were retained for 2001. Third, the implications of changes in the age distribution of the population were examined, based on population projections to 2050. A ‘pure’ change in the age distribution was examined by keeping the aggregate population size fixed and changing only the relative frequencies in different age-gender groups. Finally, the effects of a policy change to benefit taper rates in Australia were compared for 2001 and 2050 population weights. It is suggested that this type of exercise provides an insight into the implications of changes in the population on government income tax revenue and social security expenditure, indicating likely pressures for policy changes.