Uneven Regional Development Under Balanced Development Strategies: Space‐Time Paths of Regional Development in Guangdong, China

Abstract

Many questions regarding local economic phenomena involve issues of spatial and temporal dependence and heterogeneity. One of the main ideas of the socialist market economic system which was set up in 1978 in China is 'those becoming rich earlier bring along other people, all achieving the common richer eventually'. However, after several decades, having performed a series of balanced development strategies and policies, is this purpose true or not? How about the outcome of regional level of planning strategies under the socialist-market system? This paper focus on the intra provincial development, and uses per capita GDP of Guangdong, one of the most developed provinces in China to analyse the economic development of prefecturelevel cities from 1978 to 2013 with a new exploratory space-time method. Three conclusions can be drawn as follows: first, the degree of regional economic development is gradually deepening along with rapid economic development in Guangdong province and the per capita GDP difference is gradually widening between the Pearl River Delta region and the non-Pearl River Delta region. The core-periphery relation is clear within the provincial level's development. Second, the trend and position of space-time paths are different across regions. Third, the space-time paths have not intersected across poor and rich regions during the last 33 years. Widening uneven development is concealed by the 'fast growth' economic phenomenon. The macro-economic environment has had some effects on different regions, with the effect on fast growing areas, such as the core region of the Pearl River Delta the most obvious. There is a lag effect on other undeveloped areas. At the same time, under the socialist market economic system, the market is the main motivation behind regional discrepancies, and some policies and strategies aimed at narrowing the gap have had limited success.

Evaluation of Operational Efficiency of Grassroots CDC Laboratories- A Case Study in China

“…Western China is at a disadvantage in terms of economic level and geographic location. Differences in economic level and regional geographic location will affect the operating efficiency of grassroots CDC laboratories [32] ，Problems such as economic backwardness, wide jurisdiction and inconvenient transportation will all cause western regions. The basic-level CDC laboratories are difficult to work, and the actual output is difficult to compare with the central and eastern regions, and it is difficult to effectively use the input resources.…”

Analysing Long Term Spatial Mobility Patterns of Individuals and Large Groups Using 3D‐GIS: A Sport Geographic Approach

“…migration), the approach is rarely used (Liversage 2009). Due to the emergence of useful methods, technics of GIStechnologies and detailed individual pattern data, a more detailed analysis of human activity patterns is possible today (Rey & Janikas 2005;Neutens et al 2011;Gu et al 2016). Data or data collection for spatio-temporal studies are diverse.…”

“…A recent work in the area of everyday human mobility using Big data is the analysis of Ebrahimpour et al (2020). The benefits of spatio-temporal analyses are also applied in other fields such as economic geography (Gu et al 2016) and inequity research (Li & Wei 2010;Liao & Wei 2012;Liao & Wei 2015). Jen et al (2010) use a macroscale analysis method to identify spatio-temporal trends at the country level based on characteristics at different points in time.…”

Untitled

“…Whereas sustainability used to be criticized for being too broad in its scope to become a reality as it does not refer to any concrete tools that might help realize it in practise (e.g., Naudé 2011, etc. ), balanced development as a strategy for regional development is recognized as a promising approach for rural sustainability (Bochko 2015;Gu et al 2016). At the same time, it is often stressed that the collaboration of stakeholders is crucial to making these strategies work, and for enabling them to meet the priorities of Europe 2020: becoming a smart, sustainable, and inclusive economy (Naldi et al 2015).…”