Exclusive Interview with Professor Zhao Changwen of Sun Yat-sen University: The greatest potential for China's domestic demand lies in "urban-rural integration," with significant gaps in consumption upgrades in high-quality dining, chain brands, and high-end entertainment facilities.

By @Daily Economic News reporter: Zhang Rui | @Daily Economic News editor: Wei Wenyi

Under the expectation that ordinary people “don’t dare to spend,” how do we expand domestic demand? How do we ensure that AI (artificial intelligence) shifts employment effects from “disrupting” to “empowering”? What role will real estate play during the “15th Five-Year Plan and the 5th” period?

Against the above questions, Zhao Changwen, dean of the Institute of Development Studies at Sun Yat-sen University, and Wu Xiaolan Chair Professor, and Zhao Changwen, a professor at the Lingnan College, gave an exclusive interview to reporters from @Daily Economic News (hereinafter referred to as NBD) during the 2026 annual conference of the China Development High-Level Forum.

Zhao Changwen is an authority in China’s macroeconomy and industrial economics. He has led the completion of multiple major reform plans and policy research and assessment tasks assigned by the Central Government, and for many years has participated in drafting important documents for key Central Economic Work Conferences and other meetings.

Zhao Changwen, dean of the Institute of Development Studies at Sun Yat-sen University | Photo source: provided by the interviewee

The biggest potential of China’s domestic demand lies in “urban-rural integration”

NBD: This year the Government Work Report proposed “expanding new space for growth in domestic demand”—where does this “new space” mainly lie?

Zhao Changwen: This is a very crucial and strongly time-relevant question. Under the new development framework of “dual circulation,” expanding domestic demand is no longer just about simple “stimulating consumption,” but about finding structural growth space. Based on the situation so far, there are mainly the following trends:

First, upgrading from “living and commuting consumption” to “service consumption.” As China’s per-capita GDP breaks through $14,000, it is a general pattern for residents’ consumption to shift from goods to services. The marginal income elasticity of service consumption is higher than that of goods consumption. Traditional demand pillars such as housing and cars have entered a stable phase or even an adjustment phase. The new space lies in people’s experiential and developmental demand for a “better life.”

For example, cultural and tourism and sports industries such as the ice-and-snow economy, marathon events, in-depth travel, and study trips (educational tours) still have very large consumption elasticity. As population aging accelerates, including the health and aging industries such as elderly care and nursing, rehabilitation medicine, senior tourism, age-friendly home renovation, and long-term care insurance—financial services within a broader “healthy aging” and care sector—have become rigid demand.

Second, expanding from “physical goods” to “digital and green new-type consumption.” The carriers of consumption are changing; intangible services and green concepts are reshaping the structure of domestic demand. From the perspective of digital consumption, including paid applications related to AIGC (AI-generated content), high-quality supply of remote work and online education, and whole-home intelligent solutions enabled by smart home technologies—all show an increasingly evident acceleration in recent years. As digital technology matures, a new ecosystem for virtual reality (VR) and augmented reality (AR) devices and their content, as well as regulated consumption around virtual humans and digital collectibles, is forming new transaction scenarios.

From the perspective of green consumption, green building materials and low-carbon energy-saving appliances are becoming new choices. As penetration of new-energy vehicles continues to rise, consumption chains involving charging services, secondhand car circulation, and battery recycling and reuse are taking shape. Consumers are increasingly willing to pay a premium for “low-carbon certifications” and environmentally friendly products.

Third, sinking from “urban agglomerations” to “county-level areas and rural areas.” The biggest potential of China’s domestic demand lies in “urban-rural integration.” In recent years, due to factors such as the contraction effect of the real estate market, the growth rate of social retail sales in first-tier cities has generally been lower than the national average. However, more than 2,000 county-level cities and county-level areas have a large population base and also enormous consumption potential. The problem at present is that supply lags behind demand—for instance, there is a large consumption upgrade gap in high-quality dining, chain brands, and high-end cultural and entertainment facilities.

Looking at modern rural service industries, as rural revitalization advances, demand in rural areas for productive services such as agricultural machinery socialized services, cold-chain logistics, inclusive finance, and information consulting is surging. This is a new space in domestic demand driven by “investment stimulating consumption.”

Fourth, investment shifting from “traditional infrastructure” to “new-quality productive forces and public services.” Domestic demand includes not only consumption but also effective investment. The new investment space is no longer concentrated on “iron, roads, and bridges,” and one of the key focuses in the “15th Five-Year Plan and the 5th” period is new infrastructure such as computing power centers, data centers, and ultra-high-voltage power transmission, as well as public infrastructure that can serve both “normal use and emergency use (平急两用).” These can both boost investment and be transformed into long-term consumption resources.

Urban renewal, the construction of affordable housing, and redevelopment of urban villages are another key area. This is not only a substitute for real estate, but also—by improving the living environment in cities—releases residents’ related consumption in areas such as renovations, home appliances, and community services. In addition, modern productive service industries such as R&D and design, information technology services, modern logistics, legal services, and technology finance are crucial as we move from being a manufacturing powerhouse to a stronger nation. They are also a huge domestic demand market on the enterprise side.

In short, expanding new space for domestic demand essentially means shifting from “whether there is demand” to “whether it is good enough.” Opening up these spaces requires supporting institutional reforms.

Shift the supply system from “selling what we have” to “making what we need”

**NBD: **Under the current expectations that ordinary people “don’t dare to spend,” how should we expand new space for domestic demand?

Zhao Changwen: China’s household consumption rate has long stayed around 40%, indeed lower than developed countries’ 60% or even higher levels. “Don’t dare to spend” is the combined result of three overlapping factors: expectations, income, and wealth. Therefore, policy efforts should focus on the following three areas:

First, enable people to “be able to consume” by increasing their income. This mainly includes formulating and implementing urban and rural residents’ income-increase plans, improving mechanisms for normal wage growth, and raising the share of labor remuneration. We should also focus on stabilizing the real estate market, comprehensively applying policies to stabilize the stock market, broaden channels for property-based income, and form a positive cycle of “wealth growth → consumption expansion → economic growth.”

Second, make people “dare to consume” by reducing burdens. This mainly includes improving the social security system, raising the standards for medical insurance subsidies, developing inclusive childcare services, and easing pressure from rigid expenditures such as education, healthcare, and elder care. We should steadily raise the basic pensions for urban and rural residents and reduce the incentive for precautionary savings. We should clean up unreasonable restrictions in consumption, implement a paid staggered leave system for employees, and let residents “have leisure” to spend. We should increase the proportion of profits turned over by state-owned enterprises to the public finance, with special use for raising the level of social security for all.

Third, make people “willing to consume” by optimizing supply. Carry out action plans to enhance service consumption and benefit the public. Build a batch of new consumption scenarios that have broad reach and high visibility. Foster homegrown brands, promote and upgrade innovative products, and push the supply system to shift from “selling what we have” to “making what we need.” Strengthen consumer rights protection and create an environment where people can consume with confidence.

Recommendation: Launch a “Social Infrastructure Renewal” program, and set up an “AI Transition and Buffer Fund”

NBD: This year, the number of college graduates is expected to reach 12.7 million. With both overall employment pressure and structural “mismatch” existing at the same time,** the impact of AI on employment cannot be ignored.**** How should macroeconomic policy be designed to ensure that**** AI**** shifts from “disrupting” jobs to “empowering” jobs?**

Zhao Changwen: This is a core proposition concerning economic resilience and social stability. Under the dual backdrop of “overall pressure” and “structural mismatch,” macroeconomic policy must go beyond the traditional mindset of “growth equals employment,” and turn toward a systemic plan centered on buffering, matching, and creating—promoting artificial intelligence from an “impact variable” for employment into a “constant that empowers.”

First, use “active creation” to offset “passive substitution,” and build an employment buffer belt. When the speed of technological substitution is faster than workers’ transition speed, the policy’s top priority is to “buy time and build buffers.” It is recommended to launch a “social infrastructure renewal” program, drawing on the approach of “relief through public works,” and transform public investment such as urban renewal, renovation of old residential compounds, construction of age-friendly facilities, and ecological restoration into “skills-retention-type” positions for college graduates. These roles not only provide an employment transition period, but also cultivate “soft skills” that AI is difficult to replace—such as project management and teamwork—through hands-on project practice.

Consider establishing an “AI transition and buffer fund.” For traditional industries shrinking due to technological substitution, co-financed by the public finance and social security systems, provide affected people with income protection for 12 to 24 months and fully dedicated training subsidies. This turns “employment disruption” into a “reassignment window.” Enterprises that use AI at large scale can also be guided through tax policies to set up special funds for employee placement.

Second, tackle the “structural mismatch” by improving “matching between supply and demand,” and reshape the “education-employment” closed loop. The sharpest contradiction today is the “time lag” of 3 to 5 years between college major offerings and industry technology needs. It is recommended to establish a dynamic adjustment mechanism for “industry-education integration,” forcibly linking forecasts of talent demand on the industry side—especially the skill maps for AI-related roles—with university enrollment plans. Provide tilted per-student funding to universities that add urgently needed majors such as artificial intelligence, data science, and intelligent equipment. For majors whose employment rates remain consistently low, implement enrollment reduction and early-warning measures.

Explore and promote a “micro-credential system after earning a degree.” For university undergraduates and graduate students who have already graduated but have skill mismatches, public finance can purchase micro-credential courses from high-quality training institutions featuring “AI + industry.” This enables rapid skill reformation within 3 to 6 months. Completion certificates jointly certified by leading enterprises and universities can open up the “last 100 meters” of the employment pathway.

Third, use “human-AI collaboration” to rebuild the meaning of jobs and cultivate a new ecosystem of quality employment. AI’s true value is not in replacing people, but in improving people’s labor productivity, thereby creating higher-value jobs. It is recommended to implement a “thousand industries and hundred trades AI empowerment project,” using approaches such as tax deductions and special subsidies to incentivize small and medium-sized enterprises to introduce AI tools while retaining and upgrading existing positions.

For example, after retail enterprises deploy intelligent recommendation systems, require that saved labor be used to transition into roles such as user experience designers and private-domain (own-channel) operations specialists—forming a positive cycle of “technology upgrade → efficiency improvement → job upgrade.” We should support “AI-native” new business models and focus on developing emerging occupational clusters such as AI content creation, intelligent robot operations and maintenance, data labeling and governance, and model training and tuning. These jobs match the knowledge-structure advantages of college graduates.

Fourth, use “institutional innovation” to build a “safety foundation” and create inclusive employment security. Include unemployed people caused by AI substitution within the coverage of unemployment insurance, and study establishing “skill transition accounts,” allowing individuals to convert unemployment insurance benefits into training funds so they can independently choose learning directions. Improve protection for new employment forms. For platform-based and flexible employment spawned by AI, require platform companies to pay workers’ injury insurance and occupational pensions for practitioners, eliminating workers’ worries that they “don’t dare to switch” or “aren’t willing to switch.”

In summary, the relationship between AI and employment is essentially a race between the speed of technological iteration and the speed of workers’ transition. The wisdom of macro policy lies in achieving a historical leap from “machines replacing people” to “machines augmenting people,” ultimately through a strategy of “trading space for time.”

During the “15th Five-Year Plan and the 5th” period, it is officially in the decisive stage of taking on the responsibility of new growth drivers

NBD: This year’s report and the “15th Five-Year Plan Outline” both mention “emerging pillar industries.” Does this mean that in the future, strategic emerging industries will contribute more incremental growth to economic expansion? Correspondingly, what role will old drivers like the real estate sector play?

Zhao Changwen: The shift from “strategic emerging industries” to “emerging pillar industries” indicates that China’s economic growth narrative during the “15th Five-Year Plan and the 5th” period is moving from the transitional phase of “conversion between old and new growth drivers” into the decisive stage of “new growth drivers carrying the main burden.”

Strategic emerging industries emphasize forward-looking layout, technological breakthroughs, and future potential. Emerging pillar industries mean that these industries have already crossed over from the laboratory to production lines and formed large-scale industrial output. For example, the “new three” represented by new-energy vehicles, photovoltaics, and power batteries, as well as artificial intelligence, biological manufacturing, and commercial space—all have long industrial chains, strong linkages, and strong job absorption capacity. They already have the scale characteristics that were once associated with real estate and automobiles as “pillar industries.”

At the same time, these industries still have huge room for growth and for enabling other sectors in the future. Emerging pillar industries represent an increase in total-factor productivity and are the carriers of new-quality productive forces. Their contribution is no longer just “growth in quantity,” but also “improvement in quality,” with technology spillovers driving upgrades across the entire economic system.

As emerging pillar industries move onto center stage, the role of real estate will inevitably undergo a fundamental transformation. In the future, industries such as real estate will experience a fundamental remolding of functions—from “engine” to “stabilizer,” shifting from the past “growth engine” role to “a foundation for people’s livelihood” and “a risk bottom line.”

Therefore, the emphasis on “emerging pillar industries” sends a very clear signal. China is looking for and establishing new growth momentum to replace traditional growth drivers. But this does not mean they will completely withdraw from the historical stage; rather, in the new development stage, they should find the right way to coexist with new-quality productive forces, and use their soft landing to buy time and space for the rise of emerging industries.

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Cover image source: provided by the interviewee