Sources of Economic Growth in Zambia, 1970–2013: A Growth Accounting Approach

Mulungu, Kelvin; Ng’ombe, John N.

doi:10.3390/economies5020015

Cited by 11 publications

(11 citation statements)

References 31 publications

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“…Considering that TFPG is an important source of economic growth, the crisis also tends to reduce TFPG and TFPGC. In this vein, it has been widely confirmed by many empirical studies both at the national level (Dias et al , 2016; Feng et al , 2017; Mulungu and Ng'ombe, 2017) and the industry level (Hu and Liu, 2016; Medal-Bartual et al , 2016; Soltane Bassem, 2014).…”

Section: Literature Reviewmentioning

confidence: 66%

Total factor productivity growth and its contribution: lessons from the Chinese construction industry pre- and post-2008 financial crisis

Wang

Zhang

et al. 2020

ECAM

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PurposeIn response to the 2008 financial crisis, the performance of the Chinese construction industry seems to be more successful, especially in total factor productivity growth (TFPG) and its contribution (TFPGC). Hence, the purpose of this paper is to investigate and reveal the potential successful lessons in this regard.Design/methodology/approachThis study is conducted innovatively based on a special comparative analysis of TFPG and TFPGC between pre- and post-2008 financial crisis. Solow Residual Approach is used to measure TFPG and TFPGC for the period 2002–2016. Given that the crisis hit China at the end of 2008, the pre-2008 financial crisis period is from 2002 to 2008, and the post-2008 financial crisis period is limited to 2009–2016.FindingsThe results indicate that the industry indeed has better performance in promoting TFPG and TFPGC, TFP thus achieved significant accumulative growth before and after the crisis. However, from an evolutionary perspective, both TFPG and TFPGC presented an overall downward trend from before the crisis to after the crisis. Further, the game between the centrally planned economy and the market-oriented economy was identified and revealed as the essential reason behind the evolution of TFPG and TFPGC.Practical implicationsSome valuable lessons for policies and practices in promoting TFPG and TFPGC were summarized and learned from the Chinese experience, such as reducing administrative intervention and making the construction market play a decisive role.Originality/valueThis study provides some new empirical evidence to enrich the overall body of knowledge on growth theory, especially in promoting TFPG and TFPGC.

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Section: Literature Reviewmentioning

confidence: 66%

Total factor productivity growth and its contribution: lessons from the Chinese construction industry pre- and post-2008 financial crisis

Wang

Zhang

et al. 2020

ECAM

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“…The DDF and the GML productivity index method belongs to data envelopment analysis (DEA) of nonparametric frontier analysis. Measuring TFP by DEA has the following advantages compared with the Growth Accounting Approach [ 60 , 61 ], which is widely used [ 62 , 63 , 64 , 65 ]. As we know, the Growth Accounting Approach is a parametric method, which is limited by the function form.…”

Section: Methodsmentioning

confidence: 99%

Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities

Liu

Yang

Li³

et al. 2022

IJERPH

252

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The digital economy is an important engine to promote sustainable economic growth. Exploring the mechanism by which the digital economy promotes economic development, industrial upgrading and environmental improvement is an issue worth studying. This paper takes China as an example for study and uses the data of 286 cities from 2011 to 2019. In the empirical analysis, the direction distance function (DDF) and the Global Malmquist-Luenberger (GML) productivity index methods are used to measure the green total factor productivity (GTFP), while Tobit, quantile regression, impulse response function and intermediary effect models are used to study the relationship among digital economy development, industrial structure upgrading and GTFP. The results show that: (1) The digital economy can significantly improve China’s GTFP; however, there are clear regional differences. (2) The higher the GTFP, the greater the promotion effect of the digital economy on the city’s GTFP. (3) From a dynamic long-term perspective, the digital economy has indeed positively promoted China’s GTFP. (4) The upgrading of industrial structures is an intermediary transmission mechanism for the digital economy to promote GTFP. This paper provides a good reference for driving green economic growth and promoting the environment.

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“…Agriculture continues to be the key to economic development for many countries [1][2][3][4][5]. In Nigeria, Ike and Ugwumba [6], Egbetokun et al [7], and Obianefo et al [8] contend that no less than 70% of Nigerians earn their living from the agricultural sector.…”

Section: Introductionmentioning

confidence: 99%

Technical Efficiency and Technological Gaps of Rice Production in Anambra State, Nigeria

et al. 2021

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The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic frontier model in such cases, a stochastic meta-frontier (SMF) analysis is recommended to account for environmental factors between regions. It follows that differences in environmental factors between the upland and lowland regions in Anambra State, Nigeria, may result in farmers producing rice under different production and environmental conditions. Using the SMF model, this study, for the first time, determines technical efficiency (TE) and technological gap ratios (TGRs) of rice production from the upland and lowland regions in the Awka North Local Government Area of Anambra State, Nigeria. Our data are from a cross-section sample of randomly selected rice farmers. Results reveal that lowland regional rice producers are on average, significantly more technically efficient (91.7%) than their upland counterparts (84.2%). Additionally, mean TGRs associated with lowland rice farmers are higher (92.1%) than their corresponding upland producers (84.7%). While the upland rice producers are less technically efficient and further away from their full potential, results indicate that both sets of farmers do not use advanced technologies to match the industry’s potential. We suggest that agricultural policy should focus on providing regionally specific technologies, such as improved rice varieties that fit the working environment of the lagging area, to help rice farmers improve their resource efficiency and minimize technological gaps.

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Sources of Economic Growth in Zambia, 1970–2013: A Growth Accounting Approach

Cited by 11 publications

References 31 publications

Total factor productivity growth and its contribution: lessons from the Chinese construction industry pre- and post-2008 financial crisis

Total factor productivity growth and its contribution: lessons from the Chinese construction industry pre- and post-2008 financial crisis

Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities

Technical Efficiency and Technological Gaps of Rice Production in Anambra State, Nigeria

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