Discrete Choice Research Articles

Preferences for Delivery of HIV Prevention Services Among Healthcare Users in South Africa: A Discrete Choice Experiment.

Progress has been made to scale oral pre-exposure prophylaxis (PrEP) as part of combination HIV prevention, with the WHO recommending differentiated, simplified and demedicalized approaches. This study explored user preferences for components of a PrEP service delivery package, through a discrete choice experiment (DCE) among 307 people accessing primary healthcare services in South Africa between November 2022 and February 2023. Attributes included were: Source of information about HIV prevention and PrEP; Site for PrEP initiation and follow-up; Frequency of follow-up; PrEP pick-up point; HIV testing whilst using PrEP; Contact between appointments. A D-efficient DCE design was created with 16 choice sets in 2 blocks. DCE data were analysed using generalised multinomial logistic models. Compared to printed materials, participants preferred getting information about PrEP online (aOR = 7.73, 95% CI = 5.13-11.66) and through WhatsApp (aOR = 2.23, 95% CI = 0.98-5.55). PrEP initiation at a pharmacy or mobile clinic was valued equally to initiating PrEP at a clinic, but a community pop-up site was less preferred (aOR = 0.46, 95% CI = 0.33-0.64). There was a preference for 6-monthly over 3-monthly follow-up (aOR = 11.88, 95% CI = 5.44-25.94). Participants preferred collecting PrEP from a pharmacy (aOR = 5.02, 95% CI = 3.45-7.31), through home delivery (aOR = 2.18, 95% CI = 1.26-3.78) and from a vending machine (aOR = 1.43, 95% CI = 1.02-1.99) relative to where they initiated PrEP. Participants also preferred HIV self-testing over a healthcare provider test (aOR = 5.57, 95% CI = 3.72, 8.36). WhatsApp or Facebook groups (aOR = 4.12, 95% CI = 3.00-5.67), monthly phone calls (aOR = 2.84, 95% CI = 1.73-4.67) and weekly messages (aOR = 1.47, 95% CI = 1.10-1.97) were preferred contact between appointments, relative to no contact. To meet users' preferences, there is a need to expand decentralised and self-led HIV prevention services.

Plant the pot! Understanding consumer willingness to pay for sustainability in garden shop products

This study explores consumer preferences for various sustainability attributes in gardening pots using a discrete choice experiment. Data were collected from 499 respondents in garden shops across Milan and Monza, Italy. The study examines different aspects of sustainability, focusing on attributes that influence consumer purchasing decisions, such as the use of renewable energy, recycled material usage, ethical certification, and end-of-life options (recyclable, reusable, and biodegradable pots). The primary objectives are to determine consumers' preferences and the relative importance of these sustainability attributes in gardening pots and assess the impact of educational information on these preferences and willingness to pay. A mixed logit model is employed to capture the variations in preferences across the entire sample, providing a detailed analysis of the average willingness to pay for each sustainability attribute. A latent class model aimed to identify distinct segments within the sample, revealing specific groups of consumers with unique preference patterns and varying monetary evaluations for sustainable features. The results indicate strong preferences for reusable and recyclable pots, followed by biodegradable options and products made with recycled materials. Additionally, providing consumers with educational information about the environmental impacts of plastic pots significantly influenced their preferences and willingness to pay. This study contributes to the body of knowledge by offering detailed insights into consumer behaviour towards sustainable gardening products and their relative importance and providing actionable recommendations for policymakers and marketers to foster sustainable consumption practices.

Patient preferences for the provision of NHS medicines helpline services: a discrete choice experiment.

Patient medicines helpline services (PMHS) can reduce harm and improve medicines adherence and patient satisfaction after hospital discharge. There is little evidence of which PMHS attributes are most important to patients. This would enable PMHS providers to prioritise their limited resources to maximise patient benefit. Patient preferences for PMHS attributes were measured using a discrete choice experiment. Seven attributes were identified from past research, documentary analysis and stakeholder consultation. These were used to produce a D-efficient design with two blocks of ten choice sets incorporated into an online survey. Adults in the UK who took more than one medicine were eligible to complete the survey and were recruited via the Research for the Future database. Preferences were estimated using conditional logistic regression. Associations between participant characteristics and preferences were investigated with latent class models. 460 participants completed the survey. The most valued attributes were weekend opening (willingness-to-pay, WTP: £11.20), evening opening (WTP: £8.89), and receiving an answer on the same day (WTP: £9.27). Alternative contact methods, immediate contact with a pharmacist and helpline location were valued less. Female gender and full-time work were associated with variation in preferences. For one latent class containing 27% of participants, PMHS location at the patient's hospital was the most valued attribute. PMHS providers should prioritise extended opening hours and answering questions on the same day. Limitations include a non-representative sample in terms of ethnicity, education and geography, and the exclusion of people without internet access.

Animal welfare has priority: Swiss consumers’ preferences for animal welfare, greenhouse gas reductions and other sustainability improvements in dairy products

Animal welfare is at the forefront of the debate on sustainable food systems. However, animal welfare improvements often imply higher costs for producers. We explored whether Swiss consumers are willing to contribute monetarily to such improvements through an increase in prices of butter or milk. Based on a discrete choice experiment on 986 Swiss consumers, we investigated preferences for two animal welfare improvements in the dairy industry – loose housing and farm killing – as well as for organic production, origin of product, and greenhouse gas (GHG) reductions. Furthermore, we investigated how consumers perceive a potential conflict between of GHG reductions and animal welfare concerns. Half of our sample faced increases in milk prices; the other half faced increases in butter prices. Findings indicate that animal welfare is of higher importance to consumers when compared to the other attributes under analysis. Consumers oppose GHG reductions associated with deteriorations in animal welfare and are willing to pay for improvements in housing conditions and a less stressful killing of the animals. Improvements in animal welfare could be crucial for dairy industry actors and provide strong arguments in communicating the benefits of dairy products to consumers.

Patient Preferences for Attributes of Androgen Deprivation Therapies in Prostate Cancer: A Discrete Choice Experiment with Latent Class Analysis.

Medical androgen deprivation therapy (ADT) options have expanded for patients with advanced prostate cancer (PC). Historically, ADT was primarily available in long-acting injectable formulations. In 2020, the first oral formulation was US Food and Drug Administration-approved for adults with advanced PC. This study's aim was to assess patient preferences for attributes of medical ADT, including mode of administration, side effects, impact on sexual interest, and out-of-pocket (OOP) costs, and to segment respondents into distinct groups based on their treatment choice patterns. A cross-sectional survey was conducted among US residents aged > 40years with PC, employing a discrete choice experiment to assess preferences for ADT attributes. For each choice task, respondents were asked to select the hypothetical treatment profile that they preferred out of two presented. Latent class analysis (LCA) was conducted to estimate attribute-level preference weights and calculate attribute relative importance for groups of respondents with similar treatment preferences. A total of 304 respondents completed the survey (mean age 64.4years). LCA identified four preference groups, named according to the attribute each group considered most important: Sexual interest, Cost-sensitive, Favors daily pill, and Favors injection. Most respondents in the Sexual interest group were < 65years, while the Cost-sensitive group was mostly ≥ 65years. Favors daily pill had the highest proportion of ADT-naïve individuals. On average, respondents in these groups preferred an oral medication. Favors injection, which had the highest proportion of ADT-experienced individuals, preferred infrequent intramuscular injections, lower chance of post-ADT testosterone recovery, and lower OOP cost. Respondents differed in their preferences regarding ADT attributes, highlighting the need for patient involvement in their treatment decisions. Effective communication between healthcare providers and patients about the benefits and risks of available therapies should be encouraged to ensure that patients receive the PC treatment that best meets their needs.

Personalised electric vehicle charging stop planning through online estimators

AbstractIn this paper, we address the problem of finding charging stops while travelling in electric vehicles (EVs) using artificial intelligence (AI). Choosing a charging station is challenging, because drivers have very heterogeneous preferences in terms of how they trade off the features of various alternatives (for example, regarding the time spent driving, charging costs, waiting times at charging stations, and the facilities provided at the charging stations). The key problem here is eliciting the diverse preferences of drivers, assuming that these preferences are typically not fully known a priori, and then planning stops based on each driver’s preferences. Our approach to solving this problem is to develop an intelligent personal agent that learns preferences gradually over multiple interactions. This study proposes a new technique that utilises a small-scale discrete choice experiment as a method of interacting with the driver in order to minimise the cognitive burden on the driver. Using this method, drivers are presented with a variety of routes with possible combinations of charging stops depending on the agent’s latest belief about their preferences. In subsequent iterations, the personal agent will continue to learn and refine its belief about the driver’s preferences, suggesting more personalised routes that are closer to the driver’s preferences. Based on real preference data from EV drivers, we evaluate our novel algorithm and show that, after only a few queries, our method quickly converges to the optimal routes for EV drivers [This paper is an extended version of an ECAI workshop short paper (Shafipour Yourdshahi et al., in: ECAI 2023 workshops, Kraków, Poland, 2023)].

A Discrete-Choice Experiment Assessing the Patient Preferences and Real-World Experiences of Patients with Migraine in Japan.

Migraine is a debilitating headache disorder with a high prevalence in Japan that imposes significant societal burden. Although the Japanese Clinical Practice Guideline for Headache Disorders 2021 recommends both acute and preventive migraine treatments, the usage of preventive treatments is still limited. Therefore, it is crucial to understand the treatment preferences of patients with migraine pertaining to both acute and preventive treatments. A mixed-methods study including a discrete choice experiment (DCE) was conducted with Japanese patients with migraine (10 for the qualitative interviews, and 400 for the DCE) who were recruited from the Rakuten Insight panel. The DCE presented hypothetical treatment options including oral acute, oral preventive, and injectable preventive medications. Six attributes (method of delivery, reduction of pain, impact of headaches on daily routines, dosage adjustability, and temporary and persistent side effects) each with three levels were included in the survey. A hierarchical Bayesian model was used to estimate relative attribute importance scores (RAI) for all attributes. For the 400 participants in the DCE, the most common age bracket was 40-49years old, and the majority were female (66.75%). RAI estimates indicated that "method of delivery" was the most important attribute for patients (RAI 51.92, SD = 10.20), followed by "reduction of pain when experiencing a headache" (RAI 17.00, SD = 7.74). Oral preventive treatments were preferred over injectable preventive treatments. The qualitative interviews showed that patients prefer oral medications to injectable treatments, and a lack of awareness regarding preventive treatments. This study found that the "method of delivery" was the most important driver of treatment preferences of patients with migraine in Japan, with oral acute medications being preferred. Oral preventive treatments were found to be preferred over injectable treatments. These results may indicate the need for increased education regarding preventive treatments, as well as the need for further development of these treatments.

H‐2A workers' preferences for job attributes: Evidence from an experiment

AbstractDiminishing labor availability is a pressing issue for US farmers. We surveyed H‐2A farmworkers and conducted a discrete choice experiment to estimate their willingness to accept different job benefits. Respondents identified the opportunity to return home as the most valuable perk. The second highest valued job attribute was training in both English and machinery operation, followed by the employer offering housing amenities. The least valued benefit was the opportunity to earn overtime pay. This study provides new insights about the type of program modifications that might be valued more by workers in the context of proposals to modify labor rules.

Portuguese Textiles and Apparel Industry: Assessing the Effect of International Trade on Employment and Green Employment

This study examines the impact of international trade activities on employment in the Portuguese textiles and apparel industry from 2010 to 2017. It finds evidence that imports and exports have a persistent, negative, and significant effect on overall job creation, with this impact intensifying over the long-run. Additionally, the increasing elasticity of substitution between imports and exports indicates that private companies of this industry have benefited from a win–win situation characterised by higher production volumes and lower marginal costs. By applying an unsupervised machine-learning method, followed by a discrete choice analysis to infer the firm-level propensity to possess green capital, we identify a phenomenon termed the green international trade paradox. This study also reveals that international trade activities positively influence green job creation in firms lacking green capital if and only if these players are engaged in international markets while negatively affecting firms already endowed with green technologies. As such, empirical results suggest that the export-oriented economic model followed over the last decade by the Portuguese textiles and apparel industry has not necessarily generated new domestic employment opportunities but has significantly altered the magnitude and profile of skill requirements that employers seek to identify in new workforce hires.

Comparison of four approaches in eliciting health state utilities with SF-6Dv2.

To empirically compare four preference elicitation approaches, the discrete choice experiment with time (DCETTO), the Best-Worst Scaling with time (BWSTTO), DCETTO with BWSTTO (DCEBWS), and the Standard Gamble (SG) method, in valuing health states using the SF-6Dv2. A representative sample of the general population in Quebec, Canada, completed 6 SG tasks or 13 DCEBWS (i.e., 10 DCETTO followed by 3 BWSTTO). Choice tasks were designed with the SF-6Dv2. Several models were used to estimate SG data, and the conditional logit model was used for the DCE or BWS data. The performance of SG models was assessed using prediction accuracy (mean absolute error [MAE]), goodness of fit using Bayesian information criterion (BIC),t-test, Jarque-Bera (JB) test, Ljung-Box (LB) test, the logical consistency of the parameters, and significance levels. Comparison between approaches was conducted using acceptability (self-reported difficulty and quality levels in answering, and completion time), consistency (monotonicity of model coefficients), accuracy (standard errors), dimensions coefficient magnitude, correlation between the value sets estimated, and the range of estimated values. The variance scale factor was computed to assess individuals' consistency in their choices for DCE and BWS approaches. Out of 828 people who completed SG and 1208 for DCEBWS tasks, a total of 724 participants for SG and 1153 for DCE tasks were included for analysis. Although no significant difference was observed in self-reported difficulties and qualities in answers among approaches, the SG had the longest completion time and excluded participants in SG were more prone to report difficulties in answering. The range of standard errors of the SG was the narrowest (0.012 to 0.015), followed by BWSTTO (0.023 to 0.035), DCEBWS (0.028 to 0.050), and DCETTO (0.028 to 0.052). The highest number of insignificant and illogical parameters was for BWSTTO. Pain dimension was the most important across dimensions in all approaches. The correlation between SG and DCEBWS utility values was the strongest (0.928), followed by the SG and BWSTTO values (0.889), and the SG and DCETTO (0.849). The range of utility values generated by SG tended to be shorter (-0.143 to 1) than those generated by the other three methods, whereas BWSTTO (-0.505 to 1) range values were shorter than DCETTO (-1.063 to 1) and DCEBWS (-0.637 to 1). The variance scale factor suggests that respondents had almost similar level of certainty or confidence in both DCE and BWS responses. The SG had the narrowest value set, the lowest completion rates, the longest completion time, the best prediction accuracy, and produced an unexpected sign for one level. The BWSTTO had a narrower value set, lower completion time, higher parameter inconsistency, and higher insignificant levels compared to DCETTO and DCEBWS. The results of DCEBWS were more similar to SG in number of insignificant and illogical parameters, and correlation.

The Effect of Gambling Outcomes on Casino Return Times with Scalable DDC

Enabled by modern interaction-logging technologies, managers increasingly have access to outcome data from customer interactions. We consider the direct marketing targeting problem in situations where 1) the customer’s outcomes vary randomly and independently from occasion to occasion, 2) the firm has measures of the outcomes experienced by each customer on each occasion, and 3) the firm can customize marketing according to these measures and the customer’s behaviors. A primary contribution of this paper is a framework and methodology to use data on customer outcome data to model a customer’s evolving beliefs related to the firm and how these beliefs combine with marketing to influence purchase behavior. Thereby, this paper allows the manager to assess the marketing response of a customer with any specific outcome and behavior history, which in turn can be used to decide which customers to target for marketing. This research develops a novel, tractable way to estimate and introduce flexible heterogeneity distributions into Bayesian dynamic discrete choice learning models on large datasets. The model is estimated using data from the casino industry, an industry which generates more than $60 billion in U.S. revenues but has surprisingly little academic, econometric research. The counterfactuals suggest that casino profitability can increase substantially when marketing incorporates gamblers’ beliefs and past outcome sequences into the targeting decision.

Choice-based macroscopic lane-change prediction model for weaving areas

This paper introduces two macroscopic lane change models, separately for small vehicles (passenger cars and vans) as well as heavy vehicles. The model is structured using a Nested Logit discrete choice framework. The model was estimated and validated using unique trajectory data collected from a busy weaving section in Antwerp, Belgium. The models exhibit an average and maximum rate of inaccurate prediction results, amounting to 11% and 16%, respectively. Additionally, the model underestimates the total number of lane change maneuvers, with a margin of no more than 4.1–7.7%. This study aims to fill the gap in macroscopic lane change models, which mainly depend on theoretical underpinnings, by including empirical data from the analysis of more than 31,000 observed maneuvers. Furthermore, it differentiates among three maneuver intents, a unique alternative-specific discrete choice framework. This differentiation allows for the consideration of drivers’ systematic taste variations. In contrast to other models that utilize empirical datasets and are heavily dependent on expensive video-based data, including the entire traffic flow, this study introduces a novel approach for estimating the position and frequency of maneuvers by using just a small fraction (1–2%) of vehicle trajectories, supplemented by loop detector data, therefore eliminating the need for information from surrounding vehicles. Additionally, the work’s uniqueness is its validation methods extending beyond just numerical evaluations. The practical usability and usefulness of the model are shown in real-world traffic circumstances. Finally, the model is integrated in the context of a macroscopic simulation that represents a highly consistent lane balance based on the Scalable Quality Value statistics.

Assessing willingness to pay for children's COVID-19 vaccination among healthcare providers and users using a theory-based discrete choice experiment

Improving vaccine coverage among children is crucial to prevent the long-term consequences of COVID-19 infections and the emergence of resistant COVID-19 variants, especially in resource-scarce settings. This study determined factors influencing the willingness to take and pay for COVID-19 vaccine for children among Vietnamese healthcare professionals and the public. A Theory-Based discrete-choice experiment was focused on a different topic related to vaccines, including the COVID-19 vaccine for children, Monkeypox, the adult COVID-19 booster, the HIV vaccine, and a potential future pandemic. The recruitment period was from April to August 2022, and a total of 5700 Vietnamese individuals aged 16 and above from various regions of the country participated in the study. The data for the sub-study on the COVID-19 vaccination for children was completed by 891 of these participants. Most participants agreed on vaccination for all children. Among healthcare professionals it was 76.2% and 69.3% for the general population. Healthcare professionals were the main source of vaccine information (70.7%). Payment options of 50%, 100%, and full subsidy were the most popular. Concerns about vaccine characteristics were associated with lower acceptance among healthcare professionals and the general public. The burden of historical medical expenses negatively correlated with willingness to pay for vaccination, while service satisfaction positively correlated with willingness to pay. To develop an effective vaccination program among children in Vietnam, providing accurate information and satisfying vaccine services, primarily through knowledgeable and professional healthcare providers, can improve the willingness to vaccinate and pay for the COVID-19 vaccine.

Valuation of the EORTC Quality of Life Utility Core 10 Dimensions (QLU-C10D) in a Multi-ethnic Asian Setting: How Does Having Cancer Matter?

The aim of the study was to develop and compare utility value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30, using the preferences of the general public and cancer patients in Singapore, and to assess their measurement properties. A total of 600 individuals from the general public were recruited using a multi-stage random sampling, along with 626 cancer patients with clinically confirmed diagnoses from outpatient clinics of the largest tertiary cancer hospital. Each participant valued 16 pairs of EORTC QLU-C10D health states using a discrete choice experiment (DCE). Conditional logit models were used to analyze the DCE responses of the general public and cancer patients separately. Utility values were assessed for known-group validity and responsiveness in the cancer patients by comparing mean values across subgroups of patients and calculating standardized response means using longitudinal EORTC QLQ-C30 data, respectively. Physical functioning and pain had the most impact on utility for both cancer patients and general public groups. Worst health state utility values were -0.821 and -0.463 for the general public and cancer patients, respectively. Cancer patients' values were lower for mild-to-moderate health states but higher for moderately-to-highly impaired states compared with the general public's values. Both value sets discriminated between patients with differing characteristics and responded equally well to improved health status, but the cancer patients' value set was slightly more responsive to deteriorated health. EORTC QLU-C10D value sets based on the preferences of the Singaporean general public and cancer patients exhibited differences in values but similar psychometric properties.

Clients prefer collaborative decision-making with veterinarians regardless of appointment type.

To determine clients' preferences for veterinarians' communication during decision-making in relation to 3 clinical contexts: preventive care, general problem (eg, illness or injury), and urgent appointments. A cross-sectional online questionnaire was distributed by use of snowball sampling to veterinary clients owning a pet. Demographic information was collected, and participants were then randomly assigned to a scenario reflecting one of the following clinical contexts (appointment types): preventive, general problem, or urgent. Discrete choice exercises were used to solicit client preferences for 5 aspects of veterinarians' communication approach to decision-making with clients in clinical contexts: amount of information, presentation of plan (options or a recommendation), communication of value, nature of client involvement, and communication of financial cost. Relative-preference scores were calculated using hierarchical bayesian modeling. Responses for 1,614 participants were included in the final analysis. The majority were female, lived in Canada, and were financially stable. Across clinical decision-making contexts, participants preferred to collaborate with the veterinarian, be offered options with a clear recommendation, be informed of present and future costs, and have benefits of any action regarding their pet's health explained to them. For the general-problem context, participants preferred veterinarians' communication to focus solely on concerns; in contrast, in preventive care and urgent contexts, participants preferred that communication include both normal findings and concerns. Irrespective of clinical decision-making context, participants preferred collaborative decision-making with a veterinarian. Veterinary professionals should consider, when possible, communication that supports a collaborative approach to decision-making with clients.

Privacy Slider: Fine-Grain Privacy Control for Smartphones

Today, users are constrained by binary choices when configuring permissions. These binary choices contrast with the complex data collected, limiting user control and transparency. For instance, weather applications do not need exact user locations when merely inquiring about local weather conditions. We envision sliders to empower users to fine-tune permissions. First, we ran two online surveys (N=123 &amp; N=109) and a workshop (N=5) to develop the initial design of Privacy Slider. After the implementation phase, we evaluated our functional prototype using a lab study (N=32). The results show that our slider design for permission control outperforms today's system concerning all measures, including control and transparency.

Understanding the preferences of young women in self-sampling interventions for sexually transmitted infection diagnosis: a discrete choice experimental protocol

IntroductionSexually transmitted infections (STIs) are a significant public health concern globally, particularly affecting young women. Early diagnosis and treatment are essential to reducing or stopping the continuous spread of infections...

Antecedents for Consumer’s Switching Behavioural Intention Retail Banks in Zimbabwe: Integrating the Theory of Planned Behaviour

The purpose of this research is to examine the antecedents of the behavioural intention of consumers to switch a retail bank for another in Zimbabwe. The study used positivism research philosophy where quantitative data was collected from a purposively chosen sample of 150 participants. Data was analyzed using logistic regression equation with two dependent variables. Our study confirms the probability of switching retail banks in Zimbabwe was driven by factors such as; brand image, changing demographics, brand loyalty, brand image, ease of use, and the perceived usefulness. The recommends that retail banks should invest more in building brand image to retain loyal customers. A combination of technological innovations and transaction cost reductions could help to increase brand loyalty, brand image, and the attraction of new customers while retaining the old ones. The study contributes to the literature on bank switching behaviour by pioneering the use of binary choice models.

Preferences for Tapering Biologic Disease-Modifying Antirheumatic Drugs Among People With Rheumatoid Arthritis: A Discrete Choice Experiment.

Little is known about the preferences of people with rheumatoid arthritis (RA) regarding tapering of biologic disease-modifying antirheumatic drugs (bDMARDs). The aim of this study was to assess the preferences of people with RA in relation to potential treatment-related benefits and risks of bDMARD tapering and the health care service-related attributes that affect tapering. Participants with RA who had experience taking a bDMARD completed an online discrete choice experiment. Participants were asked their preferences when given three hypothetical treatment scenarios in which varying the frequency of treatment might alter their chance of adverse effects, of regaining disease control, and of other health care service-related effects. Preference weights were estimated using a multinomial logit model. There were 142 complete responses. Reduced dosing frequency of bDMARD treatment had the largest impact on preference (mean 1.0, 95% confidence interval [CI] 0.8-1.2), followed by chance of disease flare (mean 0.7, 95% CI 0.6-0.9). Participants were willing to accept an increased risk of flare between 10.6% (95% CI 3.2-17.9) and 60.6% (95% CI 48.1-72.9) in exchange for benefits associated with tapering bDMARDs. Participants with better quality of life were more likely to choose to remain on current treatment. The predicted uptake of bDMARD tapering was high among people with RA, suggesting bDMARD tapering was a favored option. For individuals with RA, making decisions about tapering bDMARDs involves considering several factors, with the most important determinants identified as dosing frequency and the risk of disease flare. Understanding patient perspectives of bDMARD tapering may enable physicians to make patient-focused shared health care decisions.

More childcare for the poor? Budgetary impacts and female labour supply responses in Italy, Austria and Hungary

ABSTRACT This paper examines the economic implications of achieving three different childcare targets (45%, 50%, and 55%) on children from disadvantaged families in Italy, Austria and Hungary. Using a discrete choice structural labour supply model that considers childcare options, we evaluate the impact of increasing childcare slots for children under 3 in poor households, defined as those in the bottom half of the income distribution. Reaching the revised Barcelona targets of 45% formal childcare participation for children under 3 would notably boost mothers’ workforce engagement in all three countries, particularly in Austria. Moreover, the initial costs of creating additional childcare slots are nearly balanced out by the rise in income tax and social security contributions resulting from increased female labour market participation.