# Promotion Effects of High-Speed Rail on Urban Development: Evidence from Three Lines in China
## 2 Materials and Methods
### Methods  
This study proposes a systematic approach for evaluating the promotion effects of HSR on promoting urban development. The research methodology framework is shown in Figure 3.  
First, it is necessary to determine the experimental and control group cities. The cities with stations on the Beijing-Shanghai, Beijing-Guangzhou, and Harbin-Dalian HSR lines are designated as the experimental group cities in this study. Nearby cities that do not have HSR (or only recently gained HSR access) are selected as the control group cities. Each experimental group city is matched with a unique control group city. The basic principles for selecting control group cities are as follows: (1) A pair of control and experimental group cities should be as spatially close as possible, with a maximum distance of 200 km. (2) Given the crucial importance of administrative levels in the Chinese urban system, the control group city must have the same administrative level as the experimental group city. (3) The control group city should be as similar in size to the experimental group city as possible, given the first two principles. Since the number of municipalities, provincial capitals, and sub-provincial cities in the Chinese urban system is limited, it is not feasible to select control cities for these types of cities based on the aforementioned principles. Therefore, this study excludes municipalities, provincial capitals, and sub-provincial cities (a total of 14 cities)  
Figure 2: Spatial distribution of the three HSR lines selected in this study. (Note: the base map of China uses data from the Standard Map Service Website of the Ministry of Natural Resources of China, with the number GS(2019)1651). and focuses only on prefecture-level cities, county-level cities, and counties. As a result, this study ultimately identifies 60 pairs of experimental and control cities (Figure 4). Due to the rapid construction of HSR in China, some regions have now achieved city-to-city and even county-to-county HSR connectivity. Therefore, it is impossible to require that all control cities have no HSR access to date. This study compares data from 2010 and 2020; so, within the screening criteria, it is necessary to choose cities that still did not have HSR access by 2020 as control cities whenever possible. If no such cities are available, cities with later HSR access should be selected. According to statistics, among the 60 control cities selected for this study, 41 did not have HSR by 2020, 7 had HSR access in 2020, 8 had it in 2019, 3 had it in 2018, and 1 had it in 2017. Additionally, the average distance between the experimental and control cities is 95 km, with a maximum of 199 km (Wuxi and Yancheng) and a minimum of 14 km (Gaoyi and Baixiang). Figure 3: Framework Diagram of the Research Methodology. Next, it is necessary to determine two key time points along the time dimension. One time point is before or shortly after the HSR starts operating; the other time point is after the HSR has been in operation for a period of time. The two time points should be spaced apart to more clearly identify the differences and similarities in the development of the two groups of cities. Considering the opening dates of the three HSR lines selected for this study and the availability of data such as population censuses, 2010 and 2020 are chosen as the two time points. Figure 4: Spatial distribution of experimental group cities on the three HSR lines and nearby control group cities. In the third step, it is necessary to determine the specific dimensions of urban development that the study will focus on. For this study, urban development will be measured by the growth in resident population, employment population, economic scale, and construction land area. Appropriate data sources for each of these dimensions need to be selected. For population data, priority is given to the census data conducted every ten years in China. This study selects the resident population and employment population data from county-level statistics for the years 2010 and 2020 [56; 57].