Demography should not rely heavily on data

By Mu Guangzong / 07-22-2021 / (Chinese Social Sciences Today)

Volenteers from Anhui Province perform the art which advocates balance between world population and ecological resource.  Photo: Han Suyuan/CNSphoto

Traditional demography is a quantitative science, and its survival and development depends on analysis of data. However, if given unreliable data and inapplicable methodologies, the analysis and study may not be scientific or deep. The result would be below expectations and require twice the research effort for half the results.
‘Illusory prosperity’
Young scholars are used to adopting regression analysis, empirical modeling, and quantitative methods to study correlations between variables. If correlations are strong, researchers are pleased—and vice visa. Some papers are not problem-analysis based and are therefore illogical and devoid of insights. Their only “academic findings” are the result of computer work and modeling, only prioritizing whether the correlation is significant or not. It can be likened to a leafy fruit tree on which there is no fruit. Many papers become increasingly complex and tediously long, intricate, and hazy. Yet, common-sense conclusions do not need lengthy elaboration. Research papers are easy to write but insightful ideas are hard to come by. 
In some sense, “illusory prosperity” exists within demography. The academic significance of research results and their values for policy making are quite limited. Scientific research, in its essence, should be the free exploration of great truth in simple words. Clarity in arguments and problem analysis are also important. Unfortunately, most papers are fraught with references in similar formats and similar research methods. Their conclusions are largely identical with only minor differences, devoid of novelty. 
Predication is not foresight 
The field of demography is fundamentally the study of demographic statistics or mathematical demographics. However, over-reliance on data, whether the data is accurate or not, would lead to the risk of ignoring the population’s subjectivity and prioritizing numbers over humans themselves. Marx once criticized this as meaningless population abstraction. Population’s innate nature is its social attribute. Therefore, population prediction can be taken as the reference, but should not be the real foresight. 
Prediction can be described as a “data game,” the secret of which lies in the selection of parameters, and the results are automatically given by formulas. However, predictions are often incorrect, and successful predictions are hard to be expected, as the future is full of uncertainty. The aim of prediction is to seek certainty out of uncertainties, so prediction is not foresight. It is merely data-based speculation and estimations of trends. The longer-term the projection of a prediction, the more risks there will be, because there will be more variables and more uncertainties. Therefore, predictive studies are the hardest to do well and the most likely to upset researchers. Computers and formulas which replace human brains in reflecting on general future trends bring risks—as there is always distance between calculation results and scientific conclusions.
It should be noted that the demographic system is open and dynamic. Static parameter setting does not define the obscure, uncertain future, and at most, it describes virtual scenes. For example, research presumes that after the first 20 years of the predicated period, the total fertility rate (TFR) will lower to level A (case 1) or level B (case 2), and the number will maintain that same level until the end of the predicated period. That is to say, TFR is set as a constant which stays the same during 20, 30, or more years. Is this possible? What should logically be considered a variable now becomes a constant. This is a chronic problem that persists in long-term prediction. So demographic predictions should have some presumed hypothesis and constrained conditions, and should not be blindly accepted under the cover of science. 
Population is about social relations 
Humanity is the sum of social relations. In China, an awareness of population totality is not as important as the awareness of demographic structures and ecological sustainability. Population’s essence is not only about the free and comprehensive development of humans, but also about the balance between populations and ecology. 
People often use “tip of the iceberg” to symbolize surfaced and deep layers, the explicit and implicit, or the partial and the whole issue. For population issues, it is the same. We need to pay attention to deep rooted problems, beyond surface level, such as demographic structures, relations, and functions. Demographic structures include gender and age structures, urban and rural population structures, social stratum structures and occupational structures, as well as ethnicity or racial structures. Demographic relations include gender relations, parent-child relationships, intergenerational relationships, and other social relationships between individuals. Demographic functions refer to people’s creativity, productivity, and competitiveness. The demographic dividend may recede, but as long as the population updates and grows, new demographic dividends will be generated. 
Mu Guangzong is a professor from the Institute of Population Research at Peking University. 
Edited by BAI LE