Checking in on the 25th Annual Conference of Chinese Economics
The surface-level question is how young scholars can balance academic research and policy research in their career development.
• Universities require their teachers to be all-rounders: they must publish high-level papers, participate in talent cultivation, write think tank reports, and serve policy, etc.
• In evaluations for professional titles and honors, various indicators must be filled out, making it difficult for scholars to focus their attention.
Therefore, individuals need to consider: how to prioritize, manage pace, and coordinate the relationship between academic and policy research at different stages of development?
The core issue lies in the deeper questions (the value of the discipline): what role should economics (and economics and management disciplines) play in today's society? What is its true value to society?
The background to this question includes,
• Business and management disciplines have faced real pressures in recent years, such as declining admission scores and decreased social interest (especially in universities with strong science and engineering programs, such as Shanghai Jiao Tong University).
• There is a misconception in society that economics and management are useless and that it is better to study science and engineering;
However, the discipline itself also needs to reflect: Has our research truly promoted social development? Has it responded to the real needs of the country and its people?
Therefore, the fundamental question is,
In the context of the new era, what should economics do? What irreplaceable value can it create for society? How can academic research and policy research work together to serve this mission?
Teacher Lu Ming's speech:
Dear teachers, I will not mince words and will directly share a few thoughts.
First, regarding the balance between academic research and policy research mentioned in the title, in principle, these two should not need to be deliberately balanced. Academic pursuits should be diverse and vibrant, and good policy research should be built upon a solid foundation of academic research. I oppose both so-called pure academic research that is detached from reality and China's fundamental national conditions, and policy research that arbitrarily expresses viewpoints without any research foundation.
The real contradiction lies not between academia and policy, but in the disconnect between the publication of papers in journals and the impact of policies.
Because of long-standing tradition, our journals place greater emphasis on methodological precision. Empirical research has become a race to identify causal relationships, and theoretical research has become a mere accumulation of dynamic and general equilibrium models. We now rarely see articles like those of the 1980s and 90s, which used only a few additions, subtractions, multiplications, and divisions to present highly insightful viewpoints.
This trend is not only observed abroad, but is also increasingly evident in Chinese journals. For example, everyone has probably noticed some recent trends in quarterly journals. I'm not afraid to offend anyone, but its current direction has already created huge negative externalities. Outsiders will think that this is what economics is all about, and young students in academia will mistakenly believe that this is the kind of good paper that authoritative journals are looking for.
Therefore, the guiding role of journals is extremely important.
The third question – do we care about reality at all?
Ding Kai just mentioned a lot of external criticism, but I'd like to ask a simple question:
Those of you who have read the entire document from the Third Plenary Session of the 20th CPC Central Committee, please raise your hands.
You'll see the results for yourself. If we, as economists, haven't even read through the most important policy documents for China today, how can we expect our published papers to truly connect with the country's most crucial policies?
Therefore, I believe we are not even at the stage of discussing how to balance academia and policy. This is because a large amount of research has absolutely no connection to actual policy.
What does this relate to? It's still related to our overemphasis on so-called precise methods and complete models. The more complex the problem, the more we need to abstract the key factors behind the complexity into simple logic. But what we're doing now is using complex models to simplify what's truly important, and often we're simplifying the most crucial Chinese factors.
In addition, our lack of interest in the policies themselves leads academic research to fall into a kind of historical ornamentation: it looks technically sophisticated, but has nothing to do with reality.
China's economic problems are highly complex, yet many papers use a completely frictionless model devoid of policy and institutional context. What's the result? The model operates in a world without policy; how can you possibly derive conclusions meaningful for real-world policy?
Many of China's economic problems today are caused by policy distortions, but the models, lacking policy input, often conclude that stronger regulation is needed. This leads to an absurd situation—using even stronger regulations to solve problems caused by those regulations.
I have limited time today, and I just rushed over from class, but I want to emphasize one point: the current state of our economics community is very similar to that popular song online recently, "No Wit"—what should be a hurried effort to do important things has turned into a hurried formality. There's also a line in the lyrics about blatantly lying, which I think is also worth reflecting on.
We can no longer blame external factors for the problems. Many of the current problems in academia are our own.
Speech by Teacher Wang Pengfei:
Okay, well—it's a great honor to be here with Professor Lu Ming and several other professors to participate in this seminar on the relationship between policy research and academic research.
I really resonated with what Professor Lu Ming just said. Haha, that's right... I think that academic research and policy research are not conflicting at all—on the contrary, they should be mutually supportive and complementary.
Of course, on the other hand, they are indeed different. I'd like to take some time to elaborate a bit.
First, what is academic research? The pursuit of academic research is to explore long-term, fundamental, and universal questions. It has several core objectives: First, to clarify some important basic facts—this is the starting point and foundation of our entire understanding of economics; second, to continuously discover new facts to expand the boundaries of our knowledge; and third, based on these facts, to extract logically consistent and original theories—this is the true standard of academic research.
And these research findings must then undergo rigorous peer review. For example, many of my own articles take seven or eight years to write—my longest one started in 2006 and wasn't published until 2015, a full nine years! Why? Because it has to pass the journal's hurdle: no matter how good your idea or how solid your data, you have to explain it clearly and write it in a way that is acceptable to your peers. This isn't being difficult; it's a self-imposed requirement of the academic community.
What about policy research? It's quite different from academic research.
The biggest difference is that it has extremely high timeliness.
For example, in 2015, when the Chinese economy encountered certain problems, the leaders immediately needed a feasible policy solution. They couldn't wait for you to spend three years analyzing the data, determining the endogenous factors, and conducting a round of robustness checks—they needed to see a solution and options immediately!
Moreover, policy research often cannot pursue perfect identification like academic papers. You don't have enough time, samples, or conditions to test various competing hypotheses. You have to propose actionable, practical, and implementable recommendations under the constraints of incomplete information and frequent friction.
At this point, I'd like to add something: I disagree with the claim that theoretical models are free of friction. In fact, a major advancement in economics over the past few decades has been the gradual incorporation of increasing friction—information asymmetry, transaction costs, institutional rigidity—into mainstream models. However, the problem is that theoretical friction and real-world friction are entirely different things! The mechanisms that work in your model may simply not work in reality; the optimal solution you derive may be distorted in practice.
Therefore, we cannot expect to use a clean model to directly command a dirty and chaotic real world.
So, should all research be geared towards policy? — Absolutely not.
Economics should also encourage some seemingly metaphysical research. For example, neoclassical economics—it assumes a completely frictionless world, and all it takes is writing the Bellman equation on a blackboard. Is this useful? Yes! It's like a vacuum experiment in physics: we never live in a vacuum, but designing rockets and airplanes relies on the physical laws of a vacuum. Similarly, understanding the operating principles of a frictionless world is precisely the theoretical foundation for evaluating current policies and constructing a frame of reference.
This point has long been a consensus internationally. For example, after the 2008 global financial crisis, the Federal Reserve launched a series of unconventional monetary policies—policies underpinned by Bernanke's decades of academic research on the Great Depression. Conversely, these policy practices spurred a wealth of new research on topics such as the zero lower bound on interest rates, debt sustainability, and expectation management—this is how academia and policy spiral upwards.
Take climate economics, for example: Nordhaus began researching climate change as early as the 1970s, when almost no one paid attention to him, and even publishing his work was difficult. His colleagues thought he was strange, researching unconventional topics. But he persevered, and later, climate economics as a whole rose to prominence, and he himself won the Nobel Prize. Then there's Bernanke—a top scholar and a successful central bank governor. And what about in China? We have one sitting right here: Professor Lu Ming—excellent in both academia and policy, and he excels in both.
Therefore, I would like to say to young students and teachers: never set academic research and policy research against each other. Policy issues often inspire us to study truly important and significant problems—while academic training helps us transform these problems into verifiable, reasonable, and generalizable knowledge.
But—not everyone has to take the same path. One of the most important concepts in economics is comparative advantage. You need to ask yourself: What am I good at?
• If you are extremely strong in mathematics, have meticulous logic, and enjoy the beauty of derivation—then you can definitely delve into theory and create abstract models, which is truly remarkable.
• If you are extremely sensitive to reality, enjoy conducting research, can sniff out clues from the news, and are full of curiosity about policy trends, then you can completely transform a specific policy issue into a rigorous academic proposition.
The key is to find your own comparative advantage and then bravely cultivate it.
Teacher Wei Chu's speech:
We have actually participated extensively in various political consultations and deliberations related to the governance of the country by the Communist Party of China, so we all have a very deep feeling that there must be a mechanism for mutual interaction between academic research and national governance.
I'd like to share three very simple perspectives: how to view it, how to proceed, and what to do.
First, how do we view this?
Today, we are all attending the China Economics Annual Conference. When we talk about economics, our initial aim is to govern the world and benefit the people—to explain the world, to solve its problems, and ultimately to address the livelihood issues of the people. If we deviate from this initial aim, then all academic research may need to reflect: have we returned to this original purpose?
In this sense, including our Principal Ding Kai—who participated in the Premier's symposium—everyone is actually working towards this goal.
Indeed, as Professor Lu Ming just mentioned, I feel that the connection between academia and the needs of real-world policy seems to have reached a dead end, or rather, gone astray. Current academic research focuses excessively on technical details and relies too heavily on data.
For example, some researchers buy data from Taobao. But have they truly understood how this data was produced? What are the institutional implications behind it? Take customs data—which is widely used—for instance—has anyone really understood how this data was generated? What kind of disputes have actually occurred between the customs and the National Bureau of Statistics regarding data definitions?
If you learn about such stories, you'll have a big question mark about your writing and the topics you choose—does the question really come from reality? Where did the topic come from?
Professor Lu just asked an excellent question: How many of you have carefully read the documents from the Third and Fourth Plenary Sessions of the 18th CPC Central Committee? This is actually a very real question: Are the issues we are addressing the most pressing needs in China today, and the issues that policymakers most need to understand?
Having participated in numerous social surveys over the past few years, I've come to a very strong impression: industry is actually at the forefront. They are the first to identify problems, and the government subsequently responds—this process typically takes anywhere from six months to a year, depending on the severity of the problem. In cutting-edge fields like AI, the response cycle can even be measured in weeks.
The government's decision-makers are actually very intelligent; many are top students from prestigious universities like Tsinghua, Peking University, Fudan, and Shanghai Jiao Tong University who have entered government departments. They are highly capable, and once they identify a problem, they immediately organize various special investigations. Following these investigations, a series of new ideas, proposals, concepts, and solutions are developed internally, and then disseminated to various ministries for further refinement into policies.
Only after policies are introduced and documents are released do our university's experts and scholars have the opportunity to participate in the evaluation and realize that, oh, they were paying attention to this issue. But by then, one to two years have already passed between the emergence of the problem and the start of our research; if we wait until we apply for social science grants, undertake key projects, and actually begin research, another two to three years may have passed.
Therefore, academia is currently lagging far behind industry. Against this backdrop, we need to delve deeper into China to understand the real problems.
In the past, we emphasized models and data because our methodological foundation was weak; but now that foundation has been built. Therefore, technology, methods, models, and data should no longer be the core of a paper. The core should be providing ideas.
I also frequently exchange ideas with government think tanks. As you know, government think tanks are expanding very rapidly, recruiting a large number of highly educated graduates; central and state-owned enterprises are also establishing their own research institutes to conduct policy research.
So, what are the advantages of our university academic institutions compared to these government think tanks? I believe there are three points:
1. Advantages of the theoretical system: Our understanding of general economic theories is more systematic and solid;
2. Advantages of international experience: We are more familiar with how different countries localize general theories and understand their individual characteristics;
3. Advantages of scientific empiricism: We can use rigorous data and methods to verify or refute hypotheses, rather than just doing descriptive statistics, which is more scientific.
Second, what about it?
How can we bridge the gap between academic research and policy practice? As President Ding Kai just mentioned, Renmin University started early in promoting its own knowledge system and talent cultivation system.
Let me give you some specific examples of our college's practices. We have several clear requirements for doctoral students:
• First, you must be able to lecture: A PhD in economics must be able to independently teach one course in microeconomics, macroeconomics, or econometrics.
• Second, you need to be able to publish in top journals, such as the domestic journal "Economic Research", to prove that you have academic ability;
• Third, you must be able to write proposals: be able to apply for national social science, natural science, or Ministry of Education projects;
• Fourth, and most importantly, is the ability to translate language: to transform a 15,000-word academic paper into a 3,000-word internal report, a 1,500-word briefing, or even a 500-word policy recommendation that decision-makers can understand at a glance.
• Fifth, you also need to be able to communicate with the public: be able to translate the language of scientists into newspaper columns that even a vegetable vendor on the street can understand—the simpler the better.
We give academic recognition to these student achievements (such as internal reports, policy reports, and media articles) and encourage them to develop in multiple ways.
As the editor-in-chief of two journals, I am also exploring similar approaches: placing all technical details in the appendix and having reviewers ensure scientific rigor; while the main text focuses on logical framework and readability, allowing non-specialist readers to understand the core ideas.
Third, what should we do?
These explorations require the joint efforts of university colleagues across the country. On the one hand, we need to accelerate the construction of China's independent knowledge system and truly bridge the last mile between academic research and policy impact; on the other hand, we also hope that university teachers can lead by example, guiding students to find real problems in the real world, conduct research using scientific methods, and ultimately propose solutions that can serve China's modernization.
Speech by Teacher Lin Jianhao:
My research actually focuses on policy issues, but I rarely conduct policy research—I study monetary policy, expectation management, and other issues from an academic perspective. These topics are inherently very practice-oriented, but I rarely present my research findings in the form of policy reports. Therefore, I have many insights and also many questions regarding how academic research can be translated into policy impact.
I would like to share my thoughts from three aspects.
I. Academic issues and policy issues are inherently intertwined in some areas.
First, I believe that in some areas of economics—particularly macroeconomics—academic and policy issues are essentially intertwined. For example, expectations theory and expectations management practice are mutually reinforcing.
As is widely known, the breakthroughs in expectations theory by Lucas, Sargent, and others directly propelled significant changes in monetary policy practice; conversely, the difficulties encountered in policy practice have continuously spurred new theoretical innovations. Therefore, in this field, academic research and policy practice are highly consistent, even two sides of the same coin. From this perspective, there is no fundamental contradiction between the two.
II. However, translating academic research into policy recommendations still faces three major challenges.
Despite the same research subjects, there are still several difficult obstacles to effectively transforming my academic findings into policy recommendations:
(1) Insufficient understanding of the constraints of the policy
In our academic training, we often overlook the real institutional environment in which policies operate, leading to a disconnect between research conclusions and reality. Two key aspects in particular receive insufficient attention:
First, there is a lack of understanding of China's political and economic system. For example, I study monetary policy and communication with the central bank, but the People's Bank of China differs fundamentally from the Federal Reserve and the European Central Bank in their systems. Applying the theoretical framework we've learned directly to the Chinese context when making policy recommendations often leads to misunderstandings.
More importantly, local governments in China are not merely providers of public services, but also actors with market-oriented characteristics. Aggregate policies, when transmitted to the local level, are significantly influenced by the behavior of local governments. However, our understanding of this transmission mechanism is very limited, and relevant research is extremely scarce.
Second, there is a neglect of international political factors. Mainstream economic theory almost entirely excludes international political variables, but today, any policy formulated by China must pay close attention to changes in the international situation. Once the international political landscape shifts, the logic behind existing policies may need to be completely adjusted. However, we have virtually no training in how to integrate international political factors into theoretical models and enhance policy sensitivity.
These two points are the most obvious knowledge gaps I felt when conducting academic research on macroeconomic policies.
(2) Lagging understanding of the policy objective system
Our understanding of policy objectives largely comes from textbooks—such as stabilizing inflation and promoting employment. However, in reality, China faces extremely diverse and dynamically changing objectives at different stages of development. For example, how should we balance objectives such as reform, security, development, and equity? Which objectives are of priority at the current stage?
If we lack an accurate grasp of these true objectives, even rigorous academic research may go astray when translated into policy recommendations. This lack of understanding of policy objectives is fatal at the policy application level.
(3) There is a huge gap in the discourse system.
Academic language differs greatly from policy language. For example, macroeconomic models use terms like heterogeneous agents or the DSGE framework, but policy reports require clear, concise, and actionable language. Translating the insights from complex models into language that policymakers can understand and use is a crucial hurdle for scholars to overcome.
Professor Wei Chu's earlier point about condensing a 15,000-word paper into a 500-word brief perfectly illustrates this challenge. Currently, our capabilities in this area are generally insufficient.
Third, a deeper problem: increasingly less research into real issues, detached from practice.
I believe a fundamental reason for the decline in the influence of current economic research is that our generation of scholars is paying less attention to major practical issues.
Looking back at the 1980s and 90s, that generation of economists were deeply involved in China's reforms, studying real and pressing issues such as the land system, price liberalization, and state-owned enterprise reform, thus wielding significant influence. Today, however, many of us engage in purely academic research, rarely focusing on specific reform topics like the current difficulties in land system reform and the interaction between local government finances and financial risks.
Similarly, we rarely delve into specific industries. Everyone talks about AI, but how many people actually go into companies to understand the real logic behind industry investment, the anxieties of entrepreneurs, and the bottlenecks in technology implementation? Our understanding often remains at the level of secondary information, superficial.
Why does this happen? The root cause lies in the evaluation system. Current academic evaluation does not require research to solve practical problems, nor does it target industry and policymakers as its audience. Our papers are only written for our peers, naturally neglecting the needs of the key audiences who truly drive China's development—entrepreneurs, grassroots officials, and industry experts.
In the future, economics research may need a clearer division of labor: some will focus on basic theory, some on policy application, and some on communication and translation. At the same time, the entire academic evaluation system needs adjustment to encourage scholars to focus on real-world problems and engage with the real world.
These are some of my preliminary thoughts. Thank you.
https://mp.weixin.qq.com/s/0sm44_SscbKiexL24VzpUg
its so strange tho... some of the least educated people on the internet, on this very site no less, have proclaimed that this sort of criticism would get the academics organs harvested.
surely the organ harvesters are just very busy this time of year, it cant possibly just be case of pathologically incurious white males believing everything their republican christian overlords feed them, can it?
