scholarly journals Does the Construction of a Water Ecological Civilization City Improve Green Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China

Author(s):  
Hongzhong Fan ◽  
Shuang Tao ◽  
Shujahat Haider Hashmi

Taking Water Ecological City Pilot (WECP) policy as a quasi-natural experiment, this paper adopts the PSM-DID method to investigate the impact of the WECP policy on the green total factor productivity (GTFP) of China’s prefecture-level cities. The results show that the implementation of the WECP policy significantly inhibits the improvement of GTFP. Furthermore, we find the implementation of the WECP policy has squeezed out government technological expenditures to some extent and aggravated the compliance cost of enterprises, which has not caused the “innovation compensation effect”, thus failing to improve GTFP. The heterogeneity analyses show that the policy effects vary with the imbalance of China’s regional development and resource endowments. Developed regions can better overcome the possible negative impact that comes with policy implementation. Governments need to formulate different policy strategies and plans from an overall macro perspective.

2019 ◽  
Vol 11 (18) ◽  
pp. 4892
Author(s):  
Chang Xu ◽  
Jianbing Guo ◽  
Baodong Cheng ◽  
Yu Liu

With the increase in labor costs in China and the tremendous changes in the international trade environment, upgrading the total factor productivity of Chinese furniture export enterprises faces a great challenge. Lots of studies have explored the interaction of exports or misallocation on the total factor productivity (TFP) of furniture enterprises, however, there is little knowledge on the impact and interaction of both exports and misallocation on the TFP. Based on panel data of Chinese furniture enterprises, this paper measures the TFP and the distortion of labor and capital resources in Chinese furniture enterprises. A two-way fixed-effects model is used to analyze the impact of exports and misallocation on the TFP of Chinese furniture enterprises. The paper reveals several important findings. First, the TFP of Chinese furniture export enterprises is lower than that of non-export enterprises, this phenomenon is called the “export–productivity paradox”. Chinese furniture export enterprises are processing trade-oriented and labor-intensive enterprises at the low end of the value chain, exports have a negative effect on improving the TFP of furniture enterprises in the short term. Second, the distortion of labor and capital resources in Chinese furniture enterprises promotes improvements to the TFP of furniture enterprises rather than reducing the TFP of furniture enterprises. Last but not the least, we find that misallocation has a positive moderating effect on exports and can weaken the negative impact of exports on TFP by the “forced mechanism”, which is that the higher the distortion of the misallocation, the higher the cost of acquiring capital and labor, and enterprises are forced to enhance their productivity when facing market competition, thus promoting improvements to the TFP of furniture enterprises.


Author(s):  
Wuliu Zhang ◽  

The impact of capital deepening on total factor productivity (TFP) is a significant and controversial issue. Based on the calculation of relevant indicators, this study adopts a Bayesian time-varying parameter model, Bayesian quantile regression, and adaptive Bayesian quantile models for in-depth statistical analysis. TFP was found to have a complex non-linear structure, and physical and human capital deepening indicators show a significant upward trend. The deepening of physical capital has a negative impact on TFP, while the deepening of human capital has a positive impact. In the capital deepening structure, the level of TFP has been improved and its structure optimized. Primary human and non-production physical capital deepening has no significant effect on TFP, while secondary human capital deepening has some significant effects on TFP. Tertiary and productive human capital deepening of TFP present two different forms of significant effect: the influence coefficient of the former declines in the increasing quantile and the change is larger, while the latter has a stable negative impact. The results of this study provide insights in terms of the improvement of China’s productivity.


2021 ◽  
Vol 4 (2) ◽  
pp. 146-156
Author(s):  
Kusuma Wardani (Universitas Indonesia) ◽  
Muhammad Halley Yudhistira (Universitas Indonesia)

AbstractThis study aims to analyze the impact of agglomeration in the form of localization economies and urbanization economies on the productivity of manufacturing industrial companies in Indonesia. Unlike previous studies, this study will look at the effect of technology level on the relationship between productivity and agglomeration by classifying research samples into low-tech and high-tech industries. In addition, this study also improves the estimation technique by addressing the endogeneity problem that has the potential to arise in estimating the relationship between productivity and agglomeration to be overcome by using instrument variable (IV). The study was conducted in two stages of estimation using company-level panel data from 2010 to 2014. First, productivity was measured at the company level using Total Factor Productivity (TFP). Then, the company productivity is estimated together with the company and industry characteristic variables, including the agglomeration measurement variable which represents localization economies and urbanization economies. The regression results show a positive impact from localization economies and a negative impact from urbanization economies.AbstrakPenelitian ini bertujuan menganalisis dampak aglomerasi berupa localization economies dan urbanization economies terhadap produktivitas perusahaan industri manufaktur di Indonesia. Berbeda dengan penelitian terdahulu yang juga meneliti dampak aglomerasi industri terhadap produktivitas perusahaan, pada penelitian ini akan melihat pengaruh tingkat teknologi terhadap hubungan produktivitas dan aglomerasi dengan mengklasifikasikan sampel penelitian ke dalam industri berteknologi rendah dan industri berteknologi tinggi. Selain itu, peneltian ini juga memperbaiki teknik estimasi dari penelitian sebelumnya dengan menangani masalah endogenitas yang berpotensi muncul dalam mengestimasi hubungan produktivitas dan aglomerasi akan diatasi dengan penggunaan instrument variable (IV). Penelitian dilakukan dalam dua tahap estimasi dengan menggunakan data panel level perusahaan dari tahun 2010 sampai 2014. Pertama, produktivitas diukur pada level perusahaan dengan menggunakan Total Factor Productivity (TFP). Kemudian, produktivitas perusahaan diestimasi bersama variabel karakteristik perusahaan dan industri, termasuk variabel pengukuran aglomerasi yang mewakili localization economies dan urbanization economies. Hasil regresi menunjukkan adanya dampak positif dari localization economies dan dampak negatif dari urbanization economies.


2017 ◽  
Vol 56 (4) ◽  
pp. 319-348
Author(s):  
Gulzar Ahmed ◽  
Muhammad Arshad Khan ◽  
Tahir Mahmood ◽  
Muhammad Afzal

This study examines the impact of trade liberalisation on the industrial productivity for a panel of twenty seven 3-digit manufacturing industries in Pakistan over the period 1980-2006. Using a variant of the Cobb-Douglas production function for industrial sector, we estimated output elasticities. The results show positive output elasticities with respect to labour, capital and raw materials for the pre-trade liberalisation period (1981 –1995) as well as post-trade liberalisation period (1996-2006). For the pre-liberalisation period, we observe positive output elasticity with respect to energy, while it turns out to be negative in the post-liberalisation period probably due to energy crisis in Pakistan. In the second stage, we calculate total factor productivity (TFP) and examine the impact of trade liberalisation on TFP for pre-and post-trade liberalisation periods. The results reveal that trade liberalisation proxied by import duty has positive but negligible impact on the TFP in the pre-as well as post-liberalisation periods. On the other hand, effective rates of protection exert large negative impact on the TFP in the post-liberalisation than the pre-liberalisation period. JEL Classifications: F14, F13, O53, L60 Keywords: Trade Liberalisation, Total Factor Productivity, Manufacturing Sector of Pakistan


2017 ◽  
Vol 08 (02) ◽  
pp. 1750008 ◽  
Author(s):  
Yihan Liu ◽  
Niklas Westelius

Is Japan’s aging and, more recently, declining population hampering its growth and reflation efforts? Exploiting the demographic and economic variation in the prefectural data between 1990 and 2007, we find that aging of the working age population has had a significant negative impact on the total factor productivity (TFP). Moreover, prefectures that aged at a faster pace experienced lower overall inflation, while prefectures with higher population growth experienced higher inflation. The results give strong support to the notion that demographic headwinds can have a non-trivial impact on the TFP and deflationary pressures.


2021 ◽  
Vol 13 (11) ◽  
pp. 5829
Author(s):  
Xinfei Li ◽  
Baodong Cheng ◽  
Qiling Hong ◽  
Chang Xu

Based on the panel data of 216 prefecture-level cities in China from 2003 to 2016, this study selected five emission-reduction indicators (industrial SO2 removal rate, soot removal rate, comprehensive utilization rate of industrial solid waste, domestic sewage treatment rate, and harmless treatment of domestic waste rate) to quantify the intensity of urban environmental regulations. Based on the intensity of environmental regulations, the authors further studied the impact of environmental regulations on economic quality (green total factor productivity) and environmental quality (PM2.5). The test results showed that the impact of environmental regulation on PM2.5 is a U-type change that first declines and then rises, while the impact of the implementation of environmental regulation on green total factor productivity is an inverted U-shaped change, which first increases and then decreases. On the one hand, appropriate environmental regulations are conducive to improving environmental quality and improving urban green total factor productivity. On the other hand, excessive environmental regulations have not only failed to improve environmental quality, but also have a negative impact on the improvement of economic quality. In addition, there are regional differences in the impact of environmental regulations, so it is necessary to formulate appropriate and local environmental regulatory policies.


Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference


ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.


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