# Compilation of a City-Level & Four-Digit Industry Code MRIO Table Based on Firm-Level Data
## 1 Introduction
The most recent is the national IO table for 2017, with a refined sector classification of 149 product sectors. Based on the \"Classification of National Economic Industries\" (GB/T4754), the national economic production activities in the 2017 table are divided into 149 product sectors. Among them are 5 departments of agriculture, forestry, animal husbandry, and fishery, 95 departments of industry, 4 departments of the construction industry, and 45 departments of service activities. Before 2012, not all provinces in China construct the provincial single region IO (SRIO) tables. SRIO tables are usually compiled and published by official provincial agencies. In 2016, the NBS released the \"China Regional Input-Output Table 2012\" containing SRIO tables for all 31 provinces. Almost all available Chinese MRIO tables are constructed based on provincial SRIO tables. The existing Chinese MRIO table involves the input-output relationship of China's 31 provinces or the IO table of China's 8 regions. For example, [PERSON] and [PERSON] [15] compiled MRIO tables for China into eight regions for the years 2002 and 2007 on the basis of the IO tables published by each province in the corresponding year. [PERSON] et al. [16; 17] compiled MRIO tables for 30 provinces (except Tibet, because Tibet started to compile input-output tables for the first time in 2012) and 30 economic sectors for 2007 and 2010. The MRIO table has become one of the most valuable approaches to analyzing various regions' economic ties and interdependence. Through MRIO, we can identify the economic impacts along the domestic value chain. The MRIO table is also an essential tool for national and subnational economic planning. It can not only directly reflect the trade relations and trade patterns among different industries from each region but also provide a data basis for the analysis of inter-regional interactions. However, currently available Chinese MRIO tables have a very low resolution, both at the regional and sectoral levels. Databases at the provincial level contradict the reality that China is an enormous country with a large domestic economy where huge variation and industrial diversity exist inside a province. For example, Guangdong province, one of the most developed provinces in China, has 40 of the 41 industrial categories listed in the United Nations Industrial Classification, which basically constitute the entire industrial chain of specific industries. Analysis of the existing database might result in a large estimation bias considering the huge heterogeneity among different regions or cities in China, such as economic level, income disparities, geographical location and the role of local governments. Therefore, compiling an MRIO table with more subdivided sectors and smaller spatial units is beneficial for a reliable and robust economic analysis of China. The study by [PERSON] et al. [18] is the only work to date that proposes a method to construct an MRIO table among all prefecture-level cities in China. Although their MRIO tables have been refined to the city level, they are still limited to 42 economic sectors. The aim of this paper is to develop an MRIO table that accounts for prefecture-level cities with more segmented sectors. Unlike the entropy-based method and data they used, we apply an expanded direct decomposition method and develop an optimization model to estimate an MRIO table that reports intersector transactions between different cities in an economy, using information from two large-scale enterprise-level datasets, the China Annual Survey of Industrial Firms (CASIF) survey and the China Customs Data (CCD) database from 2000 to 2013. This paper contributes to the existing literature in the following ways. First, to the best of our knowledge, compared with previous related studies, our study is the first attempt to examine the IO relationship among the four-digit code industry at the prefecture-city level in China, which is helpful for deepening IO-related research.