The study draws on the BES dataset, the Benessere Equo e Sostenibile framework that the Italian National Institute of Statistics, Istat, has maintained since 2013 as an official dashboard of equitable and sustainable well-being. The framework spans twelve domains, ranging from economic well-being, education and health to environment, innovation, landscape and cultural heritage, politics and institutions, quality of services, security, social relations, subjective well-being, and work and life balance. Because the researchers wanted to compare well-being and gender equality on common ground, they restricted the analysis to the 64 indicators for which gender-disaggregated data are consistently available at the regional level, out of the full set of 85. A robustness check confirmed that this restriction barely matters: indices built from the reduced set correlate almost perfectly with those built from the full set, preserving the main territorial patterns.

The methodological core of the paper is its insistence on keeping two concepts separate that most existing indices quietly blend together. Widely used instruments such as the UNDP’s Gender-related Development Index, the Gender Inequality Index, and the European Institute for Gender Equality’s Gender Equality Index combine information about how well a territory performs overall with information about gaps between women and men. The authors, following earlier critiques by scholars such as Iñaki Permanyer, argue that achievement levels can dominate these supposedly equality-focused scores. To quantify the problem, they replicated the GEI methodology on BES data and decomposed each score into an achievement component and an equality component. The result was striking: in 71 percent of cases the achievement component contributed more than half of the final index value, and on average the equality component accounted for only about 42 percent. That finding sits uneasily with official GEI guidelines, which explicitly recommend that the equality contribution should outweigh the correcting factor for every country and variable.

To build their own gender equality measure, the researchers constructed outcome-based gap indicators, comparing women’s and men’s outcomes directly while disentangling parity from overall achievement. Both composite indices were assembled through a careful pipeline of normalisation, aggregation, and sensitivity testing. For the well-being index, the authors tested sixteen alternative specifications, combining four normalisation methods, including z-scores, min-max rescaling, distance-from-best, and Borda scores, with four aggregation schemes mixing linear additive averages and geometric averages. For the gender equality index, which is bounded between zero and one, four aggregation schemes were tested. Regional hierarchies proved remarkably stable across all specifications, with correlations between baseline and average rankings exceeding an R-squared of 0.99, and trimmed-bounds normalisation designed to guard against outliers changed essentially nothing.

The first headline finding concerns geography. Regional well-being follows the familiar North-South gradient that has defined Italian economic life since unification, with northern regions such as Bolzano, Trento, and Emilia-Romagna at the top and southern regions clustered at the bottom. Gender equality, by contrast, displays a far more fragmented geography, with no comparable clean gradient. This divergence matters because it means policymakers cannot assume that lifting a region’s overall standard of living will automatically close the gaps between women and men, nor that prosperous regions are necessarily the most egalitarian ones.

Principal component analysis sharpened the picture. For well-being, the PCA identified a single broad achievement dimension that dominates regional differences, consistent with the idea that prosperous regions tend to do better across the board. For gender equality, the structure was more multidimensional: a first component captured what the authors interpret as a human development and civic dimension, anchored in social relations, health, education, and politics and institutions, while a second, more cautiously interpreted component reflected quality of life and economic gender equality. A bootstrap stability check based on 2,000 resamples of the 21 regions confirmed that the first component is highly stable and that the second is consistently retained as a separate dimension, though its economic anchor is less certain. Combining the retained components yielded exploratory regional profiles in which high well-being and high gender parity do not necessarily coincide, a result the authors present as descriptive rather than a statistically optimal clustering.

The paper also documents which side of the gender gap is advantaged, and where. Across the overall index, male outcomes were more favourable than female outcomes in 57.9 percent of indicators on average, meaning male advantage remains widespread. The pattern varies sharply by domain: men outperform women in 81.0 percent of economic indicators and 74.3 percent of social relations indicators, while education is the most female-favourable domain, with male prevalence of only 31.7 percent. Health and politics and institutions fall in between. Regional variation in overall male prevalence is comparatively modest, ranging from 51.8 percent in Bolzano to 63.3 percent in Umbria, but within specific domains the spread is much wider, as in politics and institutions, where male prevalence runs from 31.0 percent in Bolzano to 69.0 percent in Basilicata.

On dynamics, the study applied three complementary convergence diagnostics, testing whether lower-scoring regions caught up, whether cross-regional dispersion declined, and whether regional rankings shifted. The results split cleanly along the two dimensions. Well-being shows a short-run catch-up pattern, with lower-scoring regions growing faster and aggregate dispersion declining, the main exception being health. Gender equality tells a different story: while several individual domains display negative catch-up coefficients, aggregate catch-up is not statistically significant and there is no evidence of overall convergence in dispersion. Notably, the COVID-19 pandemic produced only limited reordering of regional positions, with rank correlations between consecutive years remaining close to their long-run averages, 0.973 for well-being and 0.765 for gender equality across the pandemic transition years.

The authors are candid about limitations. The binary women-men structure of the analysis reflects the form in which BES indicators are consistently available at the regional level, a constraint of the empirical setting rather than a claim that gender inequality can be reduced to a binary comparison, a point that resonates with decades of intersectionality scholarship. Missing data affecting 11 of the 64 indicators were handled by carrying forward last available values at the end of series and imputing internal gaps with adjacent observations. The authors also stress that the five regional profiles are an exploratory refinement of a coarser two-cluster structure that statistical diagnostics actually favour, reflecting the dominant separation between higher- and lower-well-being regions.

The broader implication is methodological as much as substantive. Unified gender-sensitive indices, the authors conclude, are useful for communication but tend to obscure the trade-offs between achievement and parity that matter for policy. Keeping regional well-being and gender equality as distinct measurements, while examining their interaction, reveals patterns that a single blended score would hide: a country where average living standards are slowly converging from South to North, but where the geography of gender equality is scattered, multidimensional, and showing no sign of aggregate convergence. As governments worldwide search for alternatives to GDP in the wake of the Stiglitz-Sen-Fitoussi commission and the 2030 Agenda’s Sustainable Development Goals, this Italian experiment offers a template, and a warning, about what happens when equality and achievement are finally counted separately.

Subject of Research: Measurement of regional multidimensional well-being and gender equality in Italy using composite indicators

Article Title: Regional Well-Being and Gender Equality Beyond GDP: A Dual Measurement Framework

Article References: Mariani, M., Pietropaoli, A., & Rughi, T. (2026). Regional Well-Being and Gender Equality Beyond GDP: A Dual Measurement Framework. Social Indicators Research, 185(1), Article 4. https://doi.org/10.1007/s11205-026-03942-5

Image Credits: AI Generated

DOI: 10.1007/s11205-026-03942-5

Keywords: beyond GDP, multidimensional well-being, gender equality, composite indicators, Italy, regional disparities, BES framework, principal component analysis, convergence analysis, social indicators, Istat, gender gap

The problem the project tackled is deceptively simple to state and notoriously hard to solve. Timely, disaggregated, and accessible statistical data are essential for evidence-based policymaking, from allocating health budgets to planning school construction and tracking the Sustainable Development Goals. But many national statistical offices, particularly in resource-constrained settings, still rely on static dissemination: PDF tables, spreadsheets buried on websites, or summary publications that resist reuse. Open Data Watch’s 2021 review of data portals in IDA-eligible countries documented how widespread this limitation remains, and the United Nations Statistics Division’s handbook on dissemination makes clear that the gap between collecting data and making it genuinely usable is one of the persistent weak links in official statistics. A census that cannot be queried by a district health officer, a journalist, or a researcher is a census whose value decays with every year it remains locked away.

What distinguishes the Kenyan project is its deliberate philosophy of restraint. Rather than proposing to replace comprehensive, enterprise-grade statistical platforms, the Istat team set out to close specific information gaps using lightweight, open-source tools that fit within the skills and resources already available inside KNBS. This is a methodological stance as much as a technical one. Large commercial dissemination systems can cost substantial sums in licensing and maintenance, and when donor-funded deployments outstrip local capacity to operate them, they tend to fall silent after the consultants leave. The Kenyan model inverts that logic: it starts from the tools KNBS staff already used daily and builds outward, ensuring that every component added to the pipeline could be understood, maintained, and extended by the institution itself. Full institutional ownership, the authors emphasize, was not an afterthought but a design requirement.

The technical architecture rewards a closer look, because its components are individually modest and collectively powerful. Kenya’s census processing, like that of many countries, relies on CSPro, the census and survey processing system developed by the U.S. Census Bureau. Istat’s cooperation teams had previously built two open-source bridges for this ecosystem: CSPro2csv, which transforms CSPro tabulations into structured data, and CSPro2sql, which migrates CSPro microdata into a relational database. Both are publicly available on GitHub under the IstatCooperation organization. In the Kenyan pipeline, these tools convert census outputs into machine-readable structures that can then be exposed through modern dissemination interfaces. The project also drew on JSON-stat, a lightweight standard for statistical data dissemination designed to make multidimensional data easy to transmit and consume, alongside established frameworks such as the W3C’s RDF Data Cube vocabulary and the SDMX technical standards that underpin much of international statistical exchange.

On top of this data layer sits the user-facing deliverable: the KNBS Open Data Browser, an interactive web application whose source code is published in the knbs-databrowser repository. The system allows policymakers, researchers, and civil society users to explore census indicators interactively, filter by geographic and demographic dimensions, and retrieve data in structured, reusable form through an application programming interface. That API layer matters as much as the visual interface. A dashboard serves human curiosity; an API serves the entire ecosystem of downstream tools, from statistical software and business intelligence packages to machine-learning pipelines and mobile applications. By making census data available in structured form through a documented interface, the pipeline turns a one-off publication into live infrastructure. The live deployment can be consulted at data.knbs.or.ke, where the 2019 census results are now openly explorable by anyone with an internet connection.

The project did not emerge from a vacuum. It is the product of a long-running Italian cooperation program in statistical capacity building, with documented precedents in Ethiopia, where Istat-supported teams developed metadata-driven monitoring for census data collection, and in Palestine, where similar toolchains supported the country’s pathway toward the 2030 Agenda for Sustainable Development. Earlier work published by the same Istat group, including a 2025 chapter on open-source innovation in statistical data dissemination, framed the Kenyan case as a proof of concept for a broader approach. The lineage also includes internal Istat modernization efforts such as the Stat2015 programme, and concrete implementations of the Common Statistical Production Architecture, the international blueprint for interoperable statistical production systems. In Kenya, that accumulated experience was distilled into a pipeline small enough to be sustainable and robust enough to carry a national census.

The stakes of this kind of work extend well beyond technical convenience. Morten Jerven’s influential book Poor Numbers argued that weak African statistical systems distort development policy itself, because decisions worth billions of dollars rest on indicators that are outdated, fragmented, or inaccessible. The Cape Town Global Action Plan for Sustainable Development Data, adopted by the UN Statistical Commission in 2017, explicitly calls for modernized dissemination and better use of open data, and PARIS21’s 2022 report on the digital transformation of national statistical offices catalogued both the ambition and the shortfall. The World Bank’s 2023 assessment of the next generation of statistical capacity reached a similar conclusion: transformation fails when it is imposed from outside rather than grown from within. The Kenyan model speaks directly to that diagnosis, because its central design principle is that capacity building succeeds when the beneficiary institution can run, repair, and evolve the system with its own staff.

There is also a governance dimension that the authors take seriously. Open government data research, including the systematic literature review by Wirtz, Weyerer, and Rösch published in Government Information Quarterly, has shown that publication alone does not guarantee use; data must be discoverable, documented, and machine-readable to generate civic and economic value. The Kenyan pipeline addresses this by attaching metadata management to dissemination, following the unified approach to statistical metadata articulated by Signore, Scanu, and Brancato in the Journal of Official Statistics. Structured metadata mean that a user downloading a census table knows what the numbers measure, how they were collected, and what their limitations are. The project also aligns with European interoperability profiles such as StatDCAT-AP, used for describing statistical datasets in data portals, which eases the path toward cross-national discoverability of Kenyan official statistics.

The sustainability argument deserves particular attention, because it is where many digital development projects quietly fail. The Kenyan system carries no licensing cost, which removes the recurring financial burden that so often kills donor-built platforms when funding cycles end. Its components are open source, which means the code can be audited, forked, and reused by any other statistical office facing the same constraints, and the GitHub repositories make that reuse practical rather than theoretical. Its architecture is deliberately lightweight, so it runs on the infrastructure and skills a national office actually possesses rather than on an idealized IT department it does not. And it is embedded in Kenya’s own strategic planning: the second Kenya Strategy for the Development of Statistics, covering 2023/24 to 2027/28, positions data dissemination modernization within the country’s broader statistical agenda, giving the pipeline an institutional home rather than a donor deadline.

For other national statistical offices contemplating a similar path, the Kenyan experience offers a concrete checklist rather than an abstract aspiration. Start from the tools already in daily use, in this case CSPro, and build connectors rather than replacements. Adopt lightweight, open standards such as JSON-stat and SDMX so that data remain portable across systems and decades. Publish the dissemination interface as an interactive browser backed by a real API, and release the source code so that peers can replicate it. Fund the work through cooperation frameworks, as AICS did, but structure it so that ownership and operational responsibility transfer fully to the national institution. Measure success not by the launch event but by whether researchers, journalists, and civil society can independently pull disaggregated census data years later. By those measures, Kenya’s 2019 census has become more than a count of its population; it is now a working demonstration that democratizing official statistics is neither expensive nor dependent on proprietary technology, and that the tools to open up a nation’s data may already be sitting, free and open source, waiting to be assembled.

Subject of Research: Open-source dissemination of Kenya's 2019 census data through statistical capacity building

Article Title: Democratizing Access to Official Statistics Data: A Sustainable Model from Kenya’s 2019 Census

Article References: Bruno, M., Grassia, M., Quaresima, C., Patruno, V., & Zindato, D. (2026). Democratizing Access to Official Statistics Data: A Sustainable Model from Kenya’s 2019 Census. Social Indicators Research, 184(3), Article 51. https://doi.org/10.1007/s11205-026-03943-4

Image Credits: AI Generated

DOI: 10.1007/s11205-026-03943-4

Keywords: official statistics, open data, Kenya 2019 census, KNBS, Istat, open-source software, statistical dissemination, capacity building, CSPro, JSON-stat, SDGs, data APIs