Dynamic causality among urban agglomeration, electricity consumption, construction industry, and economic performance: generalized method of moments approach

  • Munir AhmadEmail author
  • Gul JabeenEmail author
Research Article


This paper is a maiden empirical attempt to analyze the dynamic causal linkages among urban agglomeration, electricity consumption, construction industry, and economic performance, making use of simultaneous structural equations. A national panel of 30 provinces and three sub-national panels of China, for time span 2000 to 2016, have been estimated employing system and difference generalized method of moments (GMM) estimator. A construction industry-augmented model of economic growth has been proposed, incorporating construction industry and urban agglomeration as exogenous shocks to the aggregate production and electricity consumption as the input of production function. The core empirical results are first, the urban agglomeration and construction industry positively cause electricity consumption but are not caused by the same. It revealed the critical role played by urban agglomeration along with construction industry in boosting electricity consumption. Second, the economic performance positively causes electricity consumption, urban agglomeration, and construction industry and is also caused by the same. Third, urban agglomeration causes the construction industry and is caused by the same. It exposed the mutual role of urban agglomeration and urban industry in reinforcing each other in the times of high economic performance. Finally, among the three regions, the eastern zone is found to be strongest in terms of linkages among urban agglomeration, construction industry, electricity consumption, and economic performance. The intermediate zone is moderately strong, while the western zone is found to have the least strong linkages as compared with the two regions. These results are in line with the sub-national level of economic development of China. These findings, in terms of statistical significance, are highly robust across all the panels. Furthermore, depending upon empirical results, the related strategies are proposed.


Urban agglomeration Electricity consumption Construction industry Economic performance Construction industry-augmented growth model China 



Economic performance


Urban agglomeration


Construction industry


Electricity consumption

Sys. GMM

System based generalized method of moments

Dif. GMM

Difference based GMM



AR (2)

Autoregressive of second-order



The authors are thankful to the editor and anonymous reviewers as their suggestions have improved this manuscript to great extent.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of EconomicsZhejiang UniversityHangzhouChina
  2. 2.School of Economics and ManagementNorth China Electric Power UniversityBeijingChina

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