The research team, led by Charles Kwofie of the University of Energy and Natural Resources with colleagues from the University of Ghana and the University of Professional Studies, used a technique known as a discrete choice experiment to probe the preferences of 150 informal sector workers in the Accra Metropolis. Rather than simply asking people whether they would like a pension, the method presents respondents with pairs of hypothetical schemes that differ across several attributes and asks them to choose between each pair. Because every choice involves a trade-off, the researchers can recover the hidden weight that each worker places on individual scheme features, from the size of the contribution to the identity of the fund manager.

The intellectual foundations of the approach stretch back decades. Kevin Lancaster’s characteristics theory of value holds that consumers derive utility not from goods as whole bundles but from the attributes those goods possess, while Daniel McFadden’s random utility theory provides the statistical machinery for modelling choices made under uncertainty. In this framework, the utility a respondent assigns to any pension scheme is decomposed into an observable component driven by the attributes and an unobservable random component. The probability of choosing one scheme over another can then be estimated, in this case with a conditional logit model applied to an impressive 8,400 choice observations generated by 150 respondents each completing 28 binary choice sets.

The four attributes at the heart of the experiment were chosen through a rigorous three-stage process. A review of the informal pension and choice experiment literature identified candidate features known to drive demand, namely cost, benefit structure, payment flexibility and the identity of the scheme administrator. These were refined through consultation with two actuarial and pension specialists and a review of the design of the Social Security and National Insurance Trust’s third-tier Personal Pension Scheme, established under the National Pensions Act of 2008. Finally, a pilot with fifteen respondents from the target population confirmed that the wording was understood and the levels were realistic before the main survey began.

The headline findings are striking. Informal sector workers strongly prefer pension schemes managed by private trustees over those managed by government entities, with the aversion to government management amounting to roughly 53 percent of the utility swing associated with contribution affordability. They also want flexibility in how often they pay, reflecting the irregular and seasonal nature of informal incomes, and they favour affordable contributions over expensive ones. Perhaps most tellingly, the workers chose defined benefit plans over defined contribution plans, signalling that they value certainty about what they will eventually receive more than the prospect of higher but uncertain returns. The full preferred bundle corresponds to an estimated willingness to pay of about 31.43 Ghanaian cedis per member per month, or roughly 37.7 million cedis annually for every 100,000 enrolees.

The statistical evidence behind these conclusions is robust. The conditional logit model produced a chi-square statistic of 972.15 with a p-value at or below 0.001, and all four attributes were statistically significant. The sample size comfortably exceeded the minimum threshold of 55 respondents derived from standard stated-preference formulas, and the two-alternative design required at least 100 decision-makers in total, a bar the study cleared with room to spare. Ethical approval was obtained from the Committee for Human Research and Ethics of the University of Energy and Natural Resources, and all participants gave informed consent before data collection.

When the researchers disaggregated the results by gender, they found that men and women share the same ordering of preferences but differ in intensity. Female respondents, who made up 20 percent of the sample, were less sensitive to an expensive contribution amount than their male counterparts, with coefficients of negative 0.52 versus negative 1.02, suggesting that women are willing to commit a greater share of their income to a scheme they trust. Women also showed a stronger aversion to government fund managers and a stronger preference for defined benefits, indicating greater risk aversion and a higher value placed on benefit certainty. The authors caution, however, that the female estimates rest on only 30 respondents and should be read as indicative rather than conclusive, since women are widely reported to account for a large share of informal sector employment in Ghana.

Education told an equally revealing story. Respondents with no formal education, who constituted 51 percent of the sample, were the most sensitive to contribution costs, with a coefficient approaching negative 1.28, while sensitivity declined steadily among those with senior high school and tertiary education. A plausible explanation is that workers with lower educational attainment typically earn lower and less predictable incomes, so any given contribution represents a larger slice of their earnings. The least educated group also showed the strongest aversion to government-managed funds, at roughly negative 0.66 compared with about negative 0.29 among the tertiary educated, hinting that greater financial literacy softens distrust of public institutions. Even the most educated respondents, however, still preferred defined benefits, underscoring how central certainty is across the entire spectrum.

The practical implications for Ghana’s pension architecture are considerable. The third-tier scheme created under Act 766 already relies on licensed private trustees and pension fund managers, a structure that aligns closely with what informal workers say they want. The findings also support product designs built around mobile-money platforms that enable micro-contributions, several of which are being piloted across other African countries, since flexible payment schedules match the volatile cash flows of petty traders and artisans far better than rigid monthly instalments. A hybrid product combining affordable contributions with higher returns delivered with certainty emerges from the analysis as the ideal target, one that would also be financially sustainable for providers.

The study arrives at a politically charged moment. After the December 2024 general elections, Ghana’s governing party has intensively championed pension contributions among informal sector workers, and a proposed pension product for cocoa farmers, announced in the 2018 budget, has completed preparatory work but has yet to be implemented. By quantifying the specific attributes that drive willingness to contribute, the research offers SSNIT, the National Pensions Regulatory Authority, private trustees and fund managers actionable guidance on the scheme features most likely to attract enrolment. The authors also frame an agenda for future work, asking how preferences vary by income and location, whether specifying contributions directly in cedis would change the valuations, how funding and longevity risks can be reconciled with the demand for defined benefits, and whether behavioural factors such as trust, financial literacy and mobile-money convenience can be integrated into stated-preference models. For a sector where the majority of the workforce operates outside formal social protection, the answers could shape the retirement security of millions.

Subject of Research: Willingness to pay for pension contributions among informal sector workers in Ghana using a discrete choice experiment

Article Title: Using discrete choice experiment to investigate willingness to pay for pension contributions in the informal sector of Ghana

Article References: Kwofie, C., Nortey, E. N. N., Tetteh, B. N. A., & Kumi, W. (2026). Using discrete choice experiment to investigate willingness to pay for pension contributions in the informal sector of Ghana. Discover Global Society, 4(1), Article 229. https://doi.org/10.1007/s44282-026-00574-5

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00574-5

Keywords: pension, informal sector, Ghana, discrete choice experiment, willingness to pay, conditional logit, SSNIT, defined benefit, fund managers, social protection, random utility theory, Accra

The study, led by Balázs Kertesz of the Doctoral School of Business and Management at the University of Debrecen, together with Klára Bíró of the Institute of Health Economics and Management and Péter Balogh of the Institute of Methodology and Business Digitalization, was designed to fill a stubborn evidence gap. Hungary’s public system has faced well-documented underfunding, leading to long waiting lists and constrained access to specialists. Those frictions have become the engine of private-sector growth, as households increasingly pay directly for consultations, diagnostics and elective procedures. Yet until now, policymakers have had little rigorous information about which attributes of private services actually matter to the general adult population, rather than to existing private clinic customers. Understanding those preferences matters for anyone planning service networks, setting prices, or designing policies aimed at narrowing regional inequalities in access.

Methodologically, the researchers deployed a two-stage approach that is considered state of the art in stated-preference research. Before constructing the main choice experiment, they conducted a best-worst scaling (BWS) exercise to identify which candidate attributes of private healthcare were most relevant to respondents. BWS asks participants to repeatedly identify the best and worst options in small sets of attributes, producing a ranking of relative importance that is less vulnerable to the scale distortions of simple rating scales. From this preparatory work, five attributes survived into the final experimental design: the cost of the service, the distance to the provider, the availability of appointments, the reputation of the provider, and the type of clinic or provider.

The main survey then confronted each of the 1,014 respondents with a series of realistic decision scenarios. In each of eight choice situations, participants saw three hypothetical private healthcare offers described by varying combinations of the five attributes, alongside a fourth option: to decline all of them and remain in public healthcare. This opt-out alternative is methodologically crucial. Because Hungarian adults can always default to the public system, a well-designed experiment must allow them to express that preference rather than forcing them to choose among private options they might reject in real life. Including a no-choice option anchors the experiment in the genuine decision architecture of Hungary’s dual system and prevents the overstatement of demand that plagues forced-choice designs.

The statistical engine behind the analysis was a conditional logit (CL) model, the workhorse specification for discrete choice data. Conditional logit assumes that the utility an individual derives from a given healthcare option is a linear function of its attributes plus a random error term, and that the probability of choosing any one option is proportional to its estimated utility relative to the full choice set. From the estimated coefficients, the team could compute both the relative importance of each attribute and—critically for health economics—willingness-to-pay (WTP) figures. WTP calculations translate abstract utility weights into monetary terms: they answer the question of how much more a patient would be willing to pay for, say, a provider located half as far away, or an appointment available a week sooner.

The results are unambiguous in their hierarchy. Provider distance emerged as the single most important attribute, accounting for 40.01% of the explained preference structure. Cost followed at 32.31%, and appointment availability took third place at 19.13%. Together, these three practical attributes dominated roughly nine-tenths of the preference weight in the model. Institutional reputation and provider type—the attributes often emphasized in private clinics’ own marketing, from glossy branding to physician celebrity—were far less influential. In other words, Hungarian patients are not primarily buying prestige when they enter the private market; they are buying proximity, affordability and speed. The willingness-to-pay estimates reinforce this picture, quantifying exactly how much shorter travel times and faster appointments are worth relative to each other and to price.

These findings carry a counterintuitive edge that helps explain the trajectory of Hungary’s private healthcare market. Many observers might assume that private care functions as a status good, with patients choosing flagship downtown clinics and renowned specialists. The data suggest something more mundane and, arguably, more consequential: demand behaves like a market for convenience. A private clinic that opens closer to where people live or work, prices its services within reach of median households, and offers appointments without long delays will capture preference share even if its reputation is unremarkable. Conversely, a prestigious institution located far from patients, or charging fees well beyond their comfort zone, leaves much of the market on the table—or sends it back to the public system entirely, where the no-choice option remains a real and frequently exercised alternative.

For policymakers, the study’s implications extend beyond marketing strategy into questions of equity and system design. Distance as the dominant attribute is a red flag for regional inequality: patients in smaller towns and rural areas face systematically longer travel to private providers, meaning the convenience premium of private care is distributed unevenly across the country. If accessibility, rather than quality perception, is what patients weigh most heavily, then the geography of private investment decisions will shape health access patterns for years to come. The findings can inform service-planning discussions about where new capacity should be located, how pricing structures affect uptake among lower-income groups, and how the public system’s waiting times—the very frictions that push patients private—might be reduced to rebalance the two sectors. The authors frame their results as input for exactly these policy conversations on access, affordability and regional disparities in Hungary’s mixed public-private healthcare system.

The research also exemplifies a broader methodological trend in health services research: the pairing of best-worst scaling with discrete choice experiments to build more realistic, behaviorally grounded preference models. By using BWS to prune the attribute set before the DCE, the researchers reduced cognitive burden on respondents and improved the interpretability of the final estimates. The inclusion of the public-care opt-out, the quota-representative sampling frame, and the translation of utilities into willingness-to-pay values together produce evidence that speaks directly to both economics and policy. The study received ethical approval from the Research Ethics Committee of the Faculty of Economics at the University of Debrecen and was conducted under the ethical principles of the Declaration of Helsinki, with all participants providing informed consent. Open access funding was provided by the University of Debrecen, and the authors thank Dr. Péter Czine for verifying the analytical methods. As Hungary’s private healthcare sector continues to expand against the backdrop of public-sector strain, this experiment provides a rare quantitative answer to a deceptively simple question: what makes a Hungarian adult choose to pay for care? The answer—closer, cheaper, sooner—may disappoint brand strategists, but it should energize anyone committed to making healthcare genuinely accessible.

Subject of Research: Patient preferences for private healthcare services among the Hungarian adult population, measured with a discrete choice experiment

Article Title: Understanding patient preferences for private healthcare services among the general Hungarian adult population using discrete choice experiment

Article References: Kertesz, B., Bíró, K., & Balogh, P. (2026). Understanding patient preferences for private healthcare services among the general Hungarian adult population using discrete choice experiment. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00482-8

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00482-8

Keywords: discrete choice experiment, private healthcare, Hungary, patient preferences, willingness to pay, best-worst scaling, conditional logit, healthcare access, regional inequality, health policy, University of Debrecen, out-of-pocket spending