Always. Especially when the data are from China. Two economists from the University of Waikato (New Zealand) explain how research can go very wrong when data are accepted uncritically by researchers.
Briefly, Chinese per capita GDP numbers for cities, provinces and regions are calculated dividing estimated GDP by the number of household registrations, not by the number of actual residents. These inaccurate data show sharp increases in inter-regional inequality. Correcting the denominator of the GDP/population ratio for non-hukou migrants – who are registered in their village or city of birth even though they do not work there – yields a more accurate picture of changes in the geography of income inequality in China.
A growing literature uses sub-national data from China to measure trends in regional inequality and to test models of economic growth and convergence. Most published studies use provincial-level data although finer spatial scales, such as prefectures (Roberts et al. 2012) and counties (Banerjee et al. 2012), are starting to be used. ….
Unlike in most countries, China’s local populations can be counted in two ways; by how many people have hukou household registration from each place and by how many people actually reside in each place. The counts differ by the non-hukou migrants – people that move from their place of registration – who have grown from fewer than five million when reform began in 1978 to over 200 million by 2010. For most of the first three decades of the reform era, the hukou count was used to produce per capita GDP figures. In coastal provinces the hukou count is many millions more than the resident count, while for migrant-sending inland provinces it is the reverse, creating a systematic and time-varying error in provincial GDP per capita.
For example, at the time of the 2000 census, Guangdong province had a registered population of 75 million but residents numbered 86 million, so the hukou count overstates GDP per capita by 15%. At finer spatial scales, such as for individual counties and cities, the error is much larger. The city of Shenzhen provides an extreme example; its registered population was just over one million by the time of the 2000 census but its residents numbered seven million, so per capita GDP was overstated by almost 600% in the official data of the time (Chan 2009). ….
Putting the corrected data for the last two decades into the context of the entire reform era, … the only sustained episode of rising inequality … was from 1990 to 1993, representing just three out of 33 years since liberalisation began.
John Gibson and Chao Li, “Rising regional inequality in China: Fact or artefact?”, VoxEU, 9 Aug 2012.
Here are relevant extracts from abstracts for the two studies that Gibson and Li cite.
Our results show that proximity to transportation networks have … no effect on per capita GDP growth. We provide a simple theoretical framework with empirically testable predictions to interpret our results. We argue that our results are consistent with factor mobility playing an important role in determining the economic benefits of infrastructure development.
Banerjee, A, E Duflo, and N Qian (2012), “On The Road: Access to Transportation Infrastructure And Economic Growth In China”, NBER Working Paper No. 17897.
Well-known MIT economists Banerjee and Duflo were joined by Yale economist Qian for this research.
China has embarked on an ambitious program of expressway network expansion. By facilitating market integration, this program aims to promote efficiency at the national level and contribute to the catch-up of lagging inland regions. …. [W]e find no significant reduction in disparities across prefectures and no reduction in urban–rural disparities. If anything, the expressway network appears to have reinforced existing patterns of spatial inequality; although, over time, these will likely be reduced by enhanced migration.
Roberts, M, U Deichmann, B Fingleton, and T Shi (2012), “Evaluating China’s Road to Prosperity: A New Economic Geography Approach”, Regional Science and Urban Economics 42(4):580-594.
Roberts and Shi are from the University of Cambridge; Deichmann is with the World Bank, and Fingleton is from the University of Strathclyde.
Large numbers of economists, students and seasoned researchers alike, at this very moment are no doubt revising their Chinese data to see if transportation infrastructure might have a positive effect on regional development, after all.