scholarly journals What Is the Focus of Structural Reform in China?—Comparison of the Factor Misallocation Degree within the Manufacturing Industry with a Unified Model

2018 ◽  
Vol 10 (11) ◽  
pp. 4051 ◽  
Author(s):  
Laiqun Jin ◽  
Changwei Mo ◽  
Bochao Zhang ◽  
Bing Yu

The misallocation of production factors, with structural misallocation as an important aspect, is a key instigator of low total factor productivity (TFP) growth rate in China, but one important question is which structural misallocation of what factor is more serious in China. Using China’s manufacturing industrial enterprise data from 1998 to 2013, we calculated and compared the factors misallocation degree among industries, ownerships and regions. The results indicated that, the misallocation among industries was most serious, which led to a TFP loss of 8.12% annually. The misallocation among ownerships ranked second, which led to a TFP loss of 5.49%. The least degree of the misallocation recorded among provinces led to TFP loss of 3.05%. By using the relative severity index, the rank is the same. As to the capital, the misallocation among ownerships was most serious, which led to TFP loss of 4.62%. But as to the labor, the misallocation among industries was most serious, which led to TFP loss of 4.58%. Moreover, the misallocation among ownerships alleviated rapidly from 1998 to 2007, while alleviated slower among industries and regions. However, from 2008 to 2013, all three types of structural misallocation have become worse, especially in labor. These conclusions are important to identify the focus of structural reform in China.

Cereal crops provide essential nutrients and energy in the everyday human diet through direct human consumption and meat production since they comprise a major livestock feed. In the current study, the Tornqvist Theil Index was used to compute the total output index, total input index, and total factor productivity index. The Tornqvist Index is exact for the homogenous translog production function that can deliver a second-order approximation to an arbitrary twice differentiable homogenous production function. This study has indicated moderate TFP in wheat (1.45percent), and the contribution of TFP to output growth was high, about 87 percent for wheat in Rajasthan state. The annual compound growth rate of the TFP of barley increased at the rate of 1.65 percent per annum (moderate growth), and the contribution of TFP to output growth was average, at about 63.47. In comparison, the compound growth rate of TFP of annual maize crop increased at 1.80 percent per annum (moderate growth), while its TFP to output growth was about 73.09 percent. The annual compound growth rate of the TFP of bajra increased by 2.56 percent per year. The contribution of TFP to output growth was 61.29 percent for bajra in Rajasthan. The real cost of production of barley and maize increased by 0.88 and 1.59 percent, which decreased for wheat and bajra by -0.93 and -0.21 percent per annum, respectively. It was revealed that in the bajra crop, Rajasthan state showed good performance of TFP growth among the selected cereal crops. The technology, including agronomical practices, plant protection measures, and mechanization, helped to sustain TFP growth in the bajra crop.


2021 ◽  
pp. 232102222110244
Author(s):  
Mohammad Zeqi Yasin

In this paper, we examine the contribution of openness variables such as import, export, absorptive capacity and foreign-shared capital to Indonesian firms’ technical efficiency and total factor productivity (TFP) growth. We use the most recent firm-level panel data of 23 subsectors in the manufacturing industry over the period from 2008 to 2015. We employ time-varying stochastic production frontier to examine factors affecting technical efficiency and to decompose the components of TFP growth. The results reveal that export and absorptive capacity alone contribute to the efficiency improvement of the firms under study. To speak specifically of foreign firms, they contribute to improving efficiency if they interact with absorptive capacity and imported raw material intensity. We identify that, on an average, the manufacturing industry in Indonesia experienced positive TFP growth. However, among 23 subsectors, there are only few subsectors that benefitted from the openness variables. In 2014, 15 out of 23 subsectors experienced negative TFP growth. This implies that, in 2014, there were some macroeconomic issues regarding the contracted policy, for example, the subsidy removal and the basic electricity tariff. JEL Classification: C23, D24, F23, O14


2021 ◽  
Vol 72 (04) ◽  
pp. 443-448
Author(s):  
ZHANG JIANLEI ◽  
AN NA ◽  
CHENG LONGDI

Agglomeration is an important characteristic in China’s textile industry development. But regional textile industry isseriously unbalanced, only eastern location entropy (LQ) is greater than 1 and is the highest of all, followed by thecentral, western and north-eastern regions. Total factor productivity (TFP) is an important indicator to measure theeconomic growth efficiency. The average annual growth rate (AAGR) of eastern textile industry TFP is the least andcentral TFP growth rate is the fastest. In order to investigate the relationship between agglomeration and TFP of China’stextile industry, especially at region level, this paper applies panel model to study how agglomeration influences TFPduring 2005–2018. The results show that increasing agglomeration degree restrains the TFP growth of China’s textileindustry. The coefficients of LQ on textile industry in China and four regions are all negative. There exists crowded effectin eastern textile industry. It has not formed the significant agglomeration effect in western and north-eastern textileindustry for very low agglomeration degree. So it implies that eastern textile industry can accelerate the implementationof industrial transfer and structural adjustment to lower agglomeration and maintain sustained profitability of textileenterprises. Western textile industry can strengthen agglomeration by undertaking industrial transfer from eastern regionto form agglomeration effect to promote TFP growth.


2021 ◽  
Vol 9 ◽  
pp. 41-46
Author(s):  
Lies Maria Hamzah

The development of the manufacturing industry in Indonesia becomes a top priority because the manufacturing industry is a leading sector that can encourage other sectors and has forward and backward linkage between sectors.The difference in the use of technologythat still relatively low compared to the productivity of capital and labor will lead to differences in efficiency and productivity of each manufacturing industry sub-sector. The textile industry sub-sector contributes high amount to GDP and continues to increase every year. Total factor productivity (TFP) is considered a very comprehensive measure of productivity and efficiency.This measure explains the changes in production caused by changes in the amount of inputs used, changes in technology, capacity utilization and the quality of production factors. This study aims to analyze the effect of capital, labor, raw materials and energy to the output of the textile industry and textile products (TPT) (KBLI 14.15) with the Solow residual TFP approach. Another aim is to look at the efficiency and productivity of the textile industry sub-sector.The research used panel data regression with OLS model. The results of TFP estimation and TPT industry efficiency are different between TPT sub-sectors. TPT has integrity between downstream industries and upstream industries. Some of the obstacles in the textile industry in Indonesia include the high dependence of the Indonesian industry (TPT) on imported raw fiber materials (90%). Most of the age of the machines used by the TPT industry was old, this affects the TFP value.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3429
Author(s):  
Svetlana Balashova ◽  
Apostolos Serletis

This paper uncovers linkages between oil price uncertainty, total factor productivity (TFP) growth, and critical indicators of knowledge production and spillovers. It contributes to the literature by investigating the effects of oil price volatility on TFP growth, controlling for two different channels for TFP growth; benefits from the quality of the national innovation system and from adopting new technologies. We use an unbalanced panel for 28 European Union countries for the period from 1990 to 2018. We find that oil price uncertainty has a negative and statistically significant effect on TFP growth, even after we control for technological advancements and the effects of globalization. We also find that the scale of research and innovation and international trade are positive contributors to TFP growth.


2021 ◽  
Author(s):  
Mateus C. R. Neves ◽  
Felipe De Figueiredo Silva ◽  
Carlos Otávio Freitas

In this working paper, we estimate agricultural total factor productivity (Ag TFP) for South American countries over the period 19692016 and identify how road density affect technical efficiency. In 2015, Colombia, Peru, Venezuela, Ecuador, and Bolivia, the Andean countries, had 205,000; 166,000; 96,000; 89,000; and 43,000 kilometers of roads, respectively. A poor-quality and limited road network, along with inaccessibility to markets, might limit the ability of farms to efficiently manage production inputs, raising technical inefficiency. We find that the Ag TFP growth rate per year for South American countries, on average, is 1.5%. For the Andean countries, we find an even smaller growth rate per year of 1.4% on average. Our findings suggest that higher road density is associated with lower technical inefficiency.


2017 ◽  
Vol 24 (7) ◽  
pp. 1937-1955 ◽  
Author(s):  
Nitin Arora ◽  
Preeti Lohani

Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.


2011 ◽  
Vol 11 (19) ◽  
pp. 75
Author(s):  
Stevo Pucar ◽  
Zoran Borovic

Summary: Why are some countries so much richer than others? Why do some countries produce so much more output per worker than others? Influential works by Klenow & Rodriguez-Clare (1997), Hall and Jones (1999), and Parente & Prescott (2000), among others, have argued that most of the cross country differences in output per worker is explained by differences in total factor productivity. Total factor productivity measurement enables researchers to determine the contribution of supply-side production factors to economic growth. Development Accounting is a first-pass attempt at organizing the answer around two proximate determinants: factors of production and efficiency. It answers the question “how much of the cross-country income variance can be attributed to differences in (physical and human) capital, and how much to differences in the efficiency with which capital is used’’?In this article, we will outline framework for growth accounting to account for cross-country difference in income of Republic of Srpska, Republic of Croatia and Republic of Serbia. The current consensus is that differences in income per worker across countries do not arise primarly from differences in quantities in capital or labour, but rather from differences in efficiency with which are these factors used. We find that total factor productivity is very important for the growth of output per worker, but only in cases of Serbia and Croatia. In case of Srpska the most important factor for the growth of output per worker is growth of capital.Резиме: Зашто су неке земље толико богатије од других? Зашто неке земље остварују много већи обим производње по раднику од других? Утицајни радови Klenow и Rodriguez-Clare (1997), Hall и Jones (1999), и Parente и Prescott (2000), између осталих, тврдили су да је највећи број међудржавних разлика у обиму производње по раднику резултат разлика у Укупној Факторској Продуктивности. Мјерење Укупне Факторске Продуктивности омогућава истраживачима да утврде допринос фактора на страни понуде привредном расту. Развој ‘’рачуноводства раста’’ представља први покушаја анализирања двије сродне детерминанте раста: фактори производње и ефикасности.  Ова анализа даје одговор на питање “колико су међудржавне разлике у оствареном БДП-у резултат међудржавних разлика у (физичком и људском) капиталу, а колико су резултат разлика у ефикасности којом се капитал користи’’?У овом раду ћемо приказати оквир за “рачуноводство раста’’ који ће се примјенити за обрачун међудржавних разлика у БДП-у по раднику за Републику Српску, Републику Хрватску и Републику Србију. Тренутни консензус међу ауторима је да разлике у БДП-у по раднику између земаља не настају првенствено због разлика у количинама капитала или рада, него због разлика у ефикасности са којом се ови фактори користе. Анализом смо дошли до закључка да је Укупна Факторска Продуктивност веома важна за раст производње по раднику, али само у случајевима Србије и Хрватске. У случају Српске најважнији фактор за раст производње по раднику је раст техничко-технолошке опремљености рада капиталом.


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