Economic and Historical Studies as Empirical Research

Economics and History as Empirical Studies

Economics and history are both interpretations and reflections of the empirical world we live in, particularly human society, and thus both have an empirical research aspect. Economics was one of the first to build a mathematical logical system based on probability theory, which "leaps" from empirical observation to theoretical inference, leading to the development of a prominent sub-discipline—econometrics. To this day, econometrics has become a general method for empirical research, widely applied in social sciences such as sociology and political science, and has also encroached on the territory of history. In fact, both history and economics hope to provide causal explanations for observed phenomena. When empirical observations meet basic statistical assumptions such as large samples and randomness, econometrics offers a universal method. It not only helps to make more rigorous inferences but also provides a basis for the confidence level of these inferences. In the past two decades, the application of quantitative methods in interdisciplinary research between economics and history has clearly overshadowed economic theory, also leading to more disputes. Therefore, reflecting on the relationship between economics and history from the perspective of empirical research is a relatively urgent task.

Causal Explanations in History and Economics

It needs to be recognized that there are subtle differences between history and economics in their interest in causal explanations. History tends to focus on the dynamic causal relationships between different subjects or forces in specific processes (both macro and micro), while economics tends to reduce explanations to human behavior, thereby extracting more general principles. This means that the inferences made by different disciplines often target hypotheses of different natures, and thus the choice of methods also needs to be "tailor-made." When various subjects interact in a temporal sequence, the method of textual criticism is the most powerful for explaining the reasons for events. For example, the "Single Whip Law" of the Ming Dynasty was an important fiscal reform, and many studies have been dedicated to explaining it. By examining the deeds and writings of key decision-makers, it is roughly possible to explain the background of this decision and which practices it referred to, thereby inferring who played a decisive role in the reform and what problems their practices were trying to solve. However, when we discuss how the "Single Whip Law" affected local finance or social governance, the method of textual criticism becomes insufficient. This is because policies need to function through the complex behaviors of different subjects in the socio-economic context, and the temporal relationship between the two does not constitute a causal relationship. Moreover, the socio-economic context is influenced by various factors (including random events such as disasters), and it does not speak for itself. Even if historical documents record some causal judgments made by people of the time, they are based on limited observations and are difficult to use as decisive evidence. Therefore, to test the causal explanations between policies and the socio-economic context, it is more meaningful to collect enough samples and make statistical inferences based on quantitative methods.

However, the problem does not end here. Haavelmo, a founder of modern econometrics, introduced the concept of model "autonomy," emphasizing that meaningful tests should target fundamental theoretical relationships because they are the stable core behind the complex empirical observations. It is clear that the relationship between policies and the socio-economic context does not satisfy "autonomy"; it is the result of the combined effects of many factors. The "Single Whip Law" had different impacts on the south and north, different implementation methods would also affect the results, and even the implementation of the "Single Whip Law" itself would change the economic structure, thereby changing the underlying behavioral patterns between policies and the socio-economic context. At this point, even with enough data and careful selection of samples and control of various factors to statistically test the impact of the "Single Whip Law," it only explains the effects of this historical event in the specific context of the sample, and it is difficult to use it to test the hidden government and individual behavioral mechanisms. To explain the mechanisms, it is often necessary to return to the historical process to do the "storytelling" work. Especially when there are some strong structural or institutional factors affecting subject behavior (such as the bureaucratic assessment system, the li-jia system, the clan system, etc.), historical textual criticism of these aspects can sort out an analytical framework for behavioral game theory.

Thus, the "paradox" occurs: quantitative methods are ultimately a tool subordinate to historical narrative, which can assist in verifying the impact of historical events, but may even be further away from economic theory than some profound historical narratives. This is, of course, not a phenomenon unique to cliometrics; empirical research in the real economy often faces similar problems and is increasingly causing alarm in the economics community. However, when faced with history, which has a strong narrative tradition, it is particularly necessary to have a clear understanding of the position of quantitative methods in the research process, in order to maximize their strengths in the research.

Assessment of Quantitative Methods

Even when quantitative methods are theoretically more applicable, how to assess their relative advantages? The reason for this question is that quantitative methods have higher costs in data collection and model diagnosis. Especially for historical research, systematic data are often lacking, and various historical materials need to be pieced together to obtain data that can proxy a certain variable. The ambiguity in the construction of proxy variables and the inherent rigor of statistical inference are often asymmetric, making the robustness of the entire research difficult to measure. At this time, it is necessary to weigh the cost-benefit.

For example, many regions in history have built water conservancy facilities. How to judge whether they have a positive effect on the local economy? Logically, these water conservancy facilities have withstood various vicissitudes or random shocks, and people still maintain them under different backgrounds, not because of some special interests, but because they have universal positive significance. As long as case analysis shows how different subjects maintain these facilities, the above logic can be basically verified. If we can find a few cases where the differences between them are long-term and continuous, and the changes in other aspects are occasional or independent of these differences, we can even discuss the key mechanisms for maintaining water conservancy facilities. These analyses do not constitute statistical inference, but if there is a thorough understanding of concepts such as randomness, exogeneity, and ceteris paribus in econometrics, it will undoubtedly help to design the research more meticulously. However, to directly conduct quantitative analysis is much more difficult because there are too few samples with detailed records of water conservancy facilities, and the data is also very fragmented. A simple remedy is to interpolate data at a certain frequency before and after the construction of water conservancy facilities, thereby expanding into a much larger panel data. However, this only superficially increases the credibility of statistical inference, and greater uncertainty is transferred to the data construction process. Compared with the aforementioned case analysis, it is difficult to judge whether the overall reliability has been improved, and more tailoring is needed for the research object, which inevitably feels like a chicken bone.Where Lies the Vitality of Empirical Research?

If we sometimes need to accept quantitative analyses that only have historical narrative significance, and even accept some empirical studies that do not reach the level of strict falsification, this will face certain evaluation issues under a specific disciplinary paradigm. It is clear that no matter how interesting historical stories are, economists have no inherent reason to care about historical narratives, but not entirely so! A typical example is Weber's study on the Protestant ethic and the rise of capitalism. Weber discusses the "accidental" revolutionary role played by the "worldly asceticism" in the Protestant ethic against the background of traditional ethics dominating, which is a historical narrative even in terms of causal explanation. However, this change is so significant and its impact is so far-reaching that it still attracts many economists to test the so-called "Weber's proposition". It can be seen that there are always some historical turning points that change human society, which are the eternal themes of social science. We care about them not to take them as decorations for general theories, but in history itself—even if there is only contingency in it.

For example, the "fiscal-military state" theory that has attracted attention in economic research in recent ten years is actually a certain ideal model and explanatory framework summarized from the fiscal history of modern Europe, which is quite different from the behavioral theory of economics. Moreover, the "fiscal-military state" theory depicts the dynamic process of fiscal capacity changes caused by warfare and the formation of modern states, each link of which is connected with different factors and does not have "self-sufficiency". It is also very difficult to truly carry out statistical inference falsification. However, on the one hand, this theory provides a strong logical explanation for the fundamental issue of the formation of modern states, and on the other hand, it connects warfare, which appears to be opposed on the surface, with modern development, providing theoretical inspiration for the "return of the state" in economics. In fact, this inspirational research is based on a solid sorting of facts in different aspects, and at the same time, it connects these aspects that are not easy to be integrated with creative ideas. The basic theoretical research in economics usually starts from the paradoxes in typical facts and explains them with as simple theories as possible, which is similar to it. Therefore, accepting such research does not mean lowering academic standards, on the contrary, it is a manifestation that empirical research still has vitality.

We should not forget that economics and history each have their own essence beyond empirical research. The purpose of history is to seek the meaning and resonance of people in the changes of the world, while economics is dedicated to the axiomatic system of human behavior. Cross-disciplinary research mainly based on empirical research should not exclude these two aspects. On the contrary, having more opportunities to contact the two different poles is the privilege of cross-disciplinary researchers. If we can reflect the light of these two poles at the same time in the "inspirational" works that are rare to encounter, it is the supreme gift that those who are diligent in it will receive!