July 2, 2026 · 《Ming Pao》
Hong Kong’s formal embrace of “targeted poverty alleviation” is a significant step. But what exactly do the two characters “精準” (“targeted”) signify? The government published the Hong Kong Targeted Poverty Alleviation Results Report last month, breaking down beneficiaries into subgroups such as subdivided-flat households, single-parent households, and elderly-only households, and examining the measures and outcomes item by item — the effort invested is plain to see. The direction is right, and the effort is real. But the question that really matters is: how to take “targeted” poverty alleviation further?
This question matters more than any of the debates currently in the air. Recent public discussion has rightly focused on whether to keep the poverty line and on the choice of indicators, but it has still not reached the core: the prerequisite for “targeted” is a data infrastructure that Hong Kong has yet to fully build.
1. How the Country Achieves ‘Targeted’ Poverty Alleviation
The term “targeted poverty alleviation” (精準扶貧) was put forward by President Xi Jinping in 2013 at Shibadong village in Hunan. Its core is “precise identification, precise assistance, and precise management” of the poor. On the mainland, “targeted” is not a slogan but a massive data project: through “建檔立卡” (household-by-household registration), a file is created and tracked over the long term for every household; this is paired with “dynamic management,” which recognises that poverty alleviation is not a one-shot task — a household that escapes poverty this year may slide back the next, so the records must be constantly updated and reverified.
Take Guangxi as an example. Local authorities once pooled data from the traffic police, civil affairs, and housing departments, and cross-checked them against household-survey results, flagging more than 500,000 households with questionable records. They then verified them one by one, removing more than 200,000 “fake poor households” — those that had cars, property, or a company registered in their names. The country’s “targeted” approach is, beneath the surface, supported by a full set of data that can recognise people, track them, and verify their true circumstances. Hong Kong has borrowed the language of “targeted poverty alleviation” and the framework of “target groups,” but to truly connect with the national model, what it needs is more than those four characters — it also needs the data substrate that supports them.
2. Hong Kong Cannot Answer the Question of ‘Change’
To be “targeted,” we must first answer several basic questions: Who is poor? Where are they? Is their poverty a temporary setback or a structural trap? Do they truly escape poverty after receiving assistance? And might they fall back later? These are all questions of “change” — and they cannot be answered by a single year’s static data alone. We must follow the same group of people, year after year. Hong Kong’s designation in 2023 of subdivided-flat households, single-parent households, and elderly-only households as three target groups is, in itself, a direction that places high demands on data.
Hong Kong has not slackened on poverty alleviation in recent years. From the “Strive and Rise” programme targeting intergenerational poverty, to the Care Teams’ visits to over 110,000 households, the government has put in considerable work. But the current narrative on outcomes still dwells mostly on service volume and immediate change; it is hard to say whether poverty itself has actually decreased, how many have truly escaped it, and how many have only been temporarily propped up. At root, the problem is not a lack of measures but a lack of capacity to measure outcomes — and this capacity gap stems from two data gaps.
3. Gap One: Administrative Data Is Not Effectively Used
Government departments accumulate vast records of income, welfare, housing, education, and healthcare in their daily operations — material that ought to be a treasure trove for poverty research. But Hong Kong still has no clear statutory mechanism that allows vetted researchers, under privacy safeguards, to safely access and link the data scattered across departments. The data clearly exist, yet the channels for connecting and using them are missing. The result: the government sits on the most comprehensive social data in the city, yet almost none of it is used to verify the actual effectiveness of poverty-alleviation policies.
In 2015, the Financial Secretary’s Office took the lead, using data from the Student Financial Assistance Agency and the Inland Revenue Department to analyse the income trajectories of more than 50,000 graduates, in order to understand the role of education in youth upward mobility. This proves administrative data can be put to use; the problem is that, in the decade since, no comparable, institutionalised study has been carried out. If every such effort requires top-level leadership to get started, the direction and pace of research will inevitably be constrained.
International experience is already well ahead. Nordic countries have, by statute, authorised their statistical agencies to draw on data from different departments, and then, using a common personal identifier, linked income, employment, education, and health records into long-term trajectories. The United Kingdom, also a common-law jurisdiction, has an administrative-data research system that allows certified researchers to use and link government data in secure environments to evaluate public policy. Linking administrative data, protecting privacy, and opening secure research channels are not novelties in advanced economies — Hong Kong should not keep lingering outside the door.
4. Gap Two: No Long-term Tracking Survey
To this day, Hong Kong lacks a household tracking survey that follows the same group of families over many years, tracking their changes. Without it, the “why” questions can only be guessed at: Do public-housing tenants’ lives actually improve after moving in, and why? Why do Comprehensive Social Security Assistance (CSSA) recipients leave or return to the safety net? After young people enter the workforce, do they gradually stabilise or slide further? These questions cannot be answered accurately by administrative data alone.
Hong Kong has not been without attempts. The “Hong Kong Panel Study of Social Dynamics,” led by the Hong Kong University of Science and Technology, ran four waves from 2011 to 2017/18, with the first wave covering more than 7,000 adults and nearly 1,000 children, each followed up individually. Unfortunately, it relied on competitive grants from the Research Grants Council, one application at a time, rather than a stable standing budget; after the final wave, there was no way to continue. One of the original purposes of setting it up was to compare with similar tracking surveys in Taiwan and mainland China; others have since kept their data lines going, while Hong Kong has let the carefully forged thread snap again.
5. How to Close the Two Gaps
To close these two gaps, at least two practical steps can be taken. First, legislate an administrative-data research mechanism that allows vetted researchers to access and link government data in a secure environment, transforming data now dormant in various departments into a public asset that can be used to evaluate policy. Second, establish a long-term household tracking survey with a standing budget, making it a fixed foundation for Hong Kong’s social statistics — rather than something that goes round by round, year by year, waiting for grants each time.
Neither can be done without. Administrative data has wide coverage, is automatically updated, and is relatively low in cost — it can accurately tell us “what happened to whom.” The long-term tracking survey, though smaller in sample, can capture dimensions that administrative records cannot see — for instance, why a family remains trapped in poverty for so long, or why eligible households do not apply for assistance. The first gives an accurate “what”; the second adds an in-depth “why.” Only together can they tell us whether poverty alleviation is truly working.
Neither can be done without. Administrative data has wide coverage, is automatically updated, and is relatively low in cost — it can accurately tell us “what happened to whom.” The long-term tracking survey, though smaller in sample, can capture dimensions that administrative records cannot see — for instance, why a family remains trapped in poverty for so long, or why eligible households do not apply for assistance. The first gives an accurate “what”; the second adds an in-depth “why.” Only together can they tell us whether poverty alleviation is truly working.
This naturally raises two questions: does it invade privacy, and how much will it cost? Take privacy first. Allowing vetted researchers to use administrative data does not mean handing over citizens’ personal information wholesale. The mature international practice is “data does not leave the building; researchers come in”: identifiers such as names and ID numbers are stripped, researchers can only analyse within a monitored secure environment, they cannot download or take anything out, and the entire process is logged. Hong Kong already has a precedent: the Hospital Authority’s data-sharing platform, which places de-identified clinical data in a controlled environment for research use. Privacy and research have never been a zero-sum game — the key is whether the system design is rigorous enough.
Now on cost. The long-term tracking survey has ready-made templates, and universities are hardly short of research talent; what an administrative-data research channel most needs is legislation, governance, and cross-departmental coordination — an outlay of resolve more than money. Compared with the government’s HK$130.4 billion in recurrent social-welfare spending in 2025–26, this investment is not large. More importantly, once outcomes can be measured, the government will finally know which measures work and which are merely running in place — and can put resources where they truly make a difference.
6. The Key Is at Hand
Linking data is, in fact, the very direction the government is already pursuing. Since its establishment in 2024, the Digital Policy Office has been driving departmental data catalogues, open data, and data sharing, and has been trying to eliminate “information silos.” But poverty research needs more than general open data — it needs the safe linking, at the individual or household level, of CSSA and allowance data from the Social Welfare Department, public-housing records from the Housing Department, income data from the Inland Revenue Department, and schooling data from the Education Bureau. That step requires a common identifier, clear authorisation, and strict oversight.
The key is, in fact, already in Hong Kong’s hand. What is missing is neither data nor technology, but the institutional arrangement to bring a few key departments to the table and connect the lines. Targeted poverty alleviation without precise measurement will, in the end, remain no more than a vision; with data infrastructure in place, we will at last be able to know who truly benefits, who is still being missed, and which policies deserve to be scaled up. Hong Kong has the determination to alleviate poverty and the will to align with the national strategy. The next step is to build the infrastructure that supports those two characters, “targeted.”
(Translation supported by AI)
