Abstract

The three papers in the session will highlight the fundamental methodology of data accounting. Prof. Xiang will construct a new data accounting framework within the System of National Accounts to demonstrate how traditional concepts, definitions, classifications and calculating methods in SNA are suitable for data flows and stocks when they are put into practice for data accounting. He will provide a consistent account sequence including balance sheet for data capital assets. An empirical case from China will be put forward as an attempt to carry out the possibility of the new data accounting framework.
The second paper from Dr Chen shows that the covid-19 crisis has driven timely and reliable data to be incorporation into the data infrastructure of national account. It using input-output accounting as an illustrating example to show that the crisis requires high-frequency information by location and type of production activities from Big Data to track producing information occurred in industrial chains and supply chains. It also show that consistent and near-real-time data also contribute to the estimation of economic loss from the covid-19 pandemic.
The third paper from Prof. Xu will demonstrate that how Big Data are incorporation into the production of Chinese official statistics and show that modern data science methods for using Big Data have advanced sufficiently to make the more systematic incorporation of these data into official statistics feasible. It will discuss the threats to the current measurement model from traditional survey data and the growing difficulties of keeping pace with a rapidly changing economy. It will also address issues and challenges in supplementing and replacing traditional survey with alternative Big Data sources for China’s official statistical programs.