How to make rural jobs more attractive to health workers. Findings from a discrete choice experiment in Tanzania

The geographical imbalance of the health workforce in Tanzania represents a serious problem when it comes to delivering crucial health services to a large share of the population. This study provides new quantitative information about how to make jobs in rural areas more attractive to newly educated clinical officers. A unique data set stemming from a discrete choice experiment with clinical officer finalists in Tanzania is applied. The results show that offering continuing education after a certain period of service is one of the most powerful recruitment instruments the authorities have available. Increased salaries and hardship allowances will also substantially increase recruitment in rural areas. Offers of decent housing and good infrastructure, including the provision of equipment, will increase recruitment to rural remote areas but not as much as higher wages and offers of education. Women are less responsive to pecuniary incentives and are more concerned with factors that directly allow them to do a good job, while those with parents living in a remote rural area are generally less responsive to the proposed policies. When the willingness to help other people is a strong motivating force, policies that improve the conditions for helping people appear particularly effective.Human resources for health; Discrete choice experiments; Tanzania

How does additional education affect willingness to work in rural remote areas?

The main objective of this paper is to evaluate the effect of offering educational opportunities as a strategy to recruit health workers to rural areas. Tanzania, like the rest of sub-Saharan Africa, has a very small and unequally distributed health workforce. It has been suggested that rural remote jobs can be made more attractive to health workers with basic clinical skills by offering them the opportunity to upgrade their skills after a certain period of service. A data set capturing stated job preferences among freshly educated Tanzanian health workers with basic and more advanced clinical education is applied in order to investigate how additional education as an incentive mechanism affects willingness to work in rural areas. In order to control for selection effects into the additional education scheme, the two cadres are matched on propensity scores. It turns out that those health workers with advanced clinical education would have been more likely to prefer a job in a rural remote area had they not received the advanced clinical education. This effect (the ATT) is significant and substantial with several different specifications. The result is robust with regards to omitted variables and goes a long way in suggesting that a policy aimed at recruiting health personnel with basic clinical education to rural remote areas by offering jobs that include possibilities of upgrading after a certain period of service may be a temporary measure only.Education; Propensity Score Matching; Human Resources for Health; Mobility

Pro-social preferences and self-selection into the public health sector: evidence from economic experiments

There is growing interest in the role of pro-social motivation in public service delivery. In general, economists no longer question whether people have social preferences, but ask how and when such preferences will influence their economic and social decisions. Apart from revealing that individuals on average share and cooperate even when such actions lower their own material pay-off, economic experiments have documented substantial individual heterogeneity in the strength and structure of social preferences. In this paper we study the extent to which these differences are related to career choices, by testing whether preferences vary systematically between Tanzanian health worker students who prefer to work in the private health sector and those who prefer to work in the public health sector. Despite its important policy implications, this issue has received hardly any attention to date. By combining data from a questionnaire and two economic experiments, we find that students who prefer to work in the public health sector have stronger pro-social preferences than those who prefer to work in the private sector. We also show that the extent to which these students care about others can be conditional and linked to inequality aversion. A systematic selfselection of pro-socially motivated health workers into the public sector suggests that it is a good idea to have two sectors providing health services: this can ensure efficient matching of individuals and sectors by allowing employers in the two sectors to use different payment mechanisms tailored to attract and promote good performance from different types of health workers.pro-social preferences; career choice; economic experiments; health workers

Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment.

Different approaches to modelling the distribution of WTP are compared using stated preference data on Tanzanian Clinical Officers’ job choices and mixed logit models. The standard approach of specifying the distributions of the coefficients and deriving WTP as the ratio of two coefficients estimation in preference space) is compared to specifying the distributions for WTP directly at the estimation stage (estimation in WTP space). The models in preference space fit the data better than the corresponding models in WTP space although the difference between the best fitting models in the two estimation regimes is minimal. Moreover, the willingness to pay estimates derived from the preference space models turn out to be unrealistically high for many of the job attributes. The results suggest that sensitivity testing using a variety of model specifications, including estimation in WTP space, is recommended when using mixed logit models to estimate willingness to pay distributions.WTP space; Stated preference methods; Discrete choice; Mixed logit; Willingness to pay*

Development of a digital advisor to support the decision-making process of acquiring a car

This thesis explores how consumers behave in the process of acquiring a car and aspires to solve the main challenge that consumers are facing in the decision-making process. The mobility landscape is rapidly evolving and offering consumers more choices than ever before in meeting their transportation needs. The rise of sharing economy and the development of new technologies has facilitated the entrance of new business models and thereby new car ownership types. With the increased use of internet as an information source, much documentation is at the consumer’s disposal. Still, the number of alternatives may lead to confusion, stress and sub-optimal decision-making. The goal of the thesis is to develop a digital advisor that would provide the end-user with unbiased decision support for acquiring a private car. To achieve the described goal, the study was designed to collect data and test concepts through four phases, in line with design thinking. A theoretical review of the trends in the mobility market, environmental drivers, sharing economy, and the psychology of the decision-making processes was conducted to form the framework. The first phase of the thesis explored the car loan application process through testing current solutions and interviewing consumers. The results showed the car loan application process was not considered problematic for consumers, and that the main challenge was to search, navigate and evaluate information and thereby deciding on an ownership type. The second phase explored the consumers’ information search and decision-making process through interviews. This resulted in a simple prototype for a digital advisor that could solve the identified challenges in the process. The prototype was tested in the third phase, and the content of the digital advisor was defined together with consumers. The fourth and last phase resulted in a definition of the characteristics of each ownership type based on data collection through a survey.Denne masteroppgaven utforsker hvordan forbrukere oppfører seg i prosessen med å anskaffe en bil og ønsker å løse hovedutfordringen som forbrukerne står overfor i beslutningsprosessen. Mobilitetslandskapet er i rask utvikling og gir forbrukerne mange valgmuligheter for å dekke behovet for transport. Utviklingen av ny teknologi har bidratt til en vekst i delingsøkonomien, noe som har resultert i at nye forretningsmodeller har blitt til og tilført nye typer bilhold i markedet. Med den økte bruken av internett som informasjonskilde har forbrukeren tilgang på mye dokumentasjon. Derimot kan antallet alternativer føre til forvirring, stress og et suboptimalt beslutningsgrunnlag. Målet med oppgaven er å utvikle en digital rådgiver som vil gi sluttbrukeren upartisk beslutningsstøtte for å anskaffe bil. For å oppnå det beskrevne målet ble data samlet og konsepter testet gjennom fire faser, i tråd med Design thinking. En teoretisk gjennomgang av trendene i mobilitetsmarkedet, miljødrivere, delingsøkonomi og psykologien i beslutningsprosesser ble gjennomført for å danne rammeverket. Den første fasen av oppgaven utforsket søknadsprosessen for billån gjennom å teste nåværende løsninger og intervjue forbrukere. Resultatene viste at søknadsprosessen for billån ikke ble ansett som problematisk for forbrukerne, og at hovedutfordringen var å søke, navigere og evaluere informasjon og derved bestemme seg for typen bilhold. Den andre fasen utforsket forbrukernes informasjonssøk og beslutningsprosess gjennom intervjuer. Dette resulterte i en enkel prototype for en digital rådgiver som kunne løse de identifiserte utfordringene i prosessen. Prototypen ble testet i tredje fase, og innholdet i den digitale rådgiveren ble definert sammen med forbrukerne. Den fjerde og siste fasen resulterte i en definisjon av egenskapene til hver type bilhold, basert på datainnsamling gjennom en undersøkelse.This resulted in a simple prototype for a digital advisor that could solve the identified challenges in the process. The prototype was tested in the third phase, and the content of the digital advisor was defined together with consumers. The fourth and last phase resulted in a definition of the characteristics of each ownership type based on data collection through a survey.M-E

Wrong schools or wrong students? The potential role of medical education in regional imbalances of the health workforce in the United Republic of Tanzania

<p>Abstract</p> <p>Background</p> <p>The United Republic of Tanzania, like many other countries in sub-Saharan Africa, faces a human resources crisis in its health sector, with a small and inequitably distributed health workforce. Rural areas and other poor regions are characterised by a high burden of disease compared to other regions of the country. At the same time, these areas are poorly supplied with human resources compared to urban areas, a reflection of the situation in the whole of Sub-Saharan Africa, where 1.3% of the world's health workforce shoulders 25% of the world's burden of disease. Medical schools select candidates for training and form these candidates' professional morale. It is therefore likely that medical schools can play an important role in the problem of geographical imbalance of doctors in the United Republic of Tanzania.</p> <p>Methods</p> <p>This paper reviews available research evidence that links medical students' characteristics with human resource imbalances and the contribution of medical schools in perpetuating an inequitable distribution of the health workforce.</p> <p>Existing literature on the determinants of the geographical imbalance of clinicians, with a special focus on the role of medical schools, is reviewed. In addition, structured questionnaires collecting data on demographics, rural experience, working preferences and motivational aspects were administered to 130 fifth-year medical students at the medical faculties of MUCHS (University of Dar es Salaam), HKMU (Dar es Salaam) and KCMC (Tumaini University, Moshi campus) in the United Republic of Tanzania. The 130 students represented 95.6% of the Tanzanian finalists in 2005. Finally, we apply probit regressions in STATA to analyse the cross-sectional data coming from the aforementioned survey.</p> <p>Results</p> <p>The lack of a primary interest in medicine among medical school entrants, biases in recruitment, the absence of rural related clinical curricula in medical schools, and a preference for specialisation not available in rural areas are among the main obstacles for building a motivated health workforce which can help correct the inequitable distribution of doctors in the United Republic of Tanzania.</p> <p>Conclusion</p> <p>This study suggests that there is a need to re-examine medical school admission policies and practices.</p

What affects the career choices of health workers? Four essays on preferences, incentives and career choices in a low-income context

The geographical imbalance of the health workforce in Tanzania represents a serious problem when it comes to delivering crucial health services to a large share of the population. TheTanzanian health system, like many others in low-income countries, needs better incentivesystems to attract dedicated workers to the health sector, to bring more qualified healthworkers to rural areas, and to induce them to use their knowledge and skills efficiently.However, creating better incentive and recruitment systems requires thorough knowledge ofhealth workers’ motivations and preferences, as well as the relative valuations of different jobattributes. The aim of this Ph.D. project has been to contribute to the base of knowledge abouthealth workers’ individual motivations and preference structures. It has also been animportant goal to examine how jobs with different characteristics can be matched with thesepreferences in order to provide high-quality health services on a larger scale.The first essay, ‘How to make rural jobs more attractive to health workers: findings from adiscrete choice experiment in Tanzania’, published in ‘Health Economics’ (2010), providesnew quantitative information about how health authorities can make jobs in rural areas moreattractive to newly educated clinical officers. A data set stemming from a discrete choiceexperiment with clinical officer finalists in Tanzania is applied. The results show that offeringadditional education after a certain period of service is one of the most powerful recruitmentinstruments the authorities have available. Increased salaries and hardship allowances are alsolikely to substantially increase recruitment in rural areas. Offers of decent housing and goodinfrastructure, including the provision of equipment, can also increase recruitment to ruralremote areas but not as much as higher wages and offers of education.In the second essay, ‘Mixed logit estimation of willingness to pay distributions: a comparisonof models in preference and WTP space using data from a health-related choice experiment’,co-authored with Arne Risa Hole, different approaches to modelling the distribution of WTPare compared using mixed logit models and the same data set as in essay 1. The standardapproach of specifying the distributions of the coefficients and deriving WTP as the ratio oftwo coefficients (estimation in preference space) is compared to specifying the distributionsfor WTP directly at the estimation stage (estimation in WTP space). The results suggest thatsensitivity testing using a variety of model specifications, including estimation in WTP space,is highly recommended when using mixed logit models to estimate willingness to paydistributions.In the third essay, ‘How does additional education affect willingness to work in rural remoteareas?: an application to health workers in a low-income context’, the main objective is toevaluate the effect of offering education opportunities as a strategy to recruit health workersto rural areas. A dataset capturing stated job preferences among freshly educated Tanzanianhealth workers with basic and more advanced clinical education is applied in order toinvestigate how additional education as an incentive mechanism affects the willingness towork in rural areas. In order to control for selection effects into the additional educationscheme, the two cadres are matched on propensity scores. It turns out that the health workerswith advanced clinical education would have been more likely to prefer a job in a rural remotearea had they not received the advanced clinical education. The result goes a long way insuggesting that a policy aiming at recruiting health personnel with basic clinical education torural remote areas by offering jobs that include possibilities of upgrading after a certain periodof service, may be a temporary measure only.The fourth essay, “Pro-social preferences and self-selection into the public health sector:evidence from economic experiments” co-authored with Ida K. Lindkvist, studies the extent towhich differences in pro-social preferences are related to career choices. We test whetherpreferences vary systematically between Tanzanian health worker students who prefer towork in the private health sector and those who prefer to work in the public health sector.Despite its important policy implications, this issue has received hardly any attention to date.By combining data from a questionnaire and two economic experiments, we find that studentswho prefer to work in the public health sector have stronger pro-social preferences than thosewho prefer to work in the private sector. We also show that the extent to which these studentscare about others can be conditional and linked to inequality aversion. A systematic selfselectionof pro-socially motivated health workers into the public sector suggests that it is agood idea to have two sectors providing health services: this can ensure efficient matching ofindividuals and sectors by allowing employers in the two sectors to use different paymentmechanisms tailored to attract and promote good performance from different types of health workers