scholarly journals Evaluation and Study on influencing factors of agricultural products logistics efficiency based on DEA-Tobit model -- from panel data from 2010 to 2019

2021 ◽  
Vol 1941 (1) ◽  
pp. 012070
Author(s):  
Hongshen Yu ◽  
Yundi Dai ◽  
Lihong Zhao
Keyword(s):  
Panel Data ◽  
Influencing Factors ◽  
Tobit Model ◽  
Agricultural Products

scholarly journals Big Data Analysis of e-Commerce Efficiency and Its Influencing Factors of Agricultural Products in China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yi Wen ◽  
Lingxi Kong ◽  
Gaoxiu Liu
Keyword(s):  
Influencing Factors ◽  
Tobit Model ◽  
Agricultural Products ◽  
Scale Efficiency ◽  
Agricultural Mechanization ◽  
Internet Users ◽  
Correlation Degree ◽  
Rural Revitalization ◽  
Dea Analysis ◽  
High Level

At present, the e-commerce industry of agricultural products plays a pivotal role in promoting income growth and helping rural revitalization. This paper collected relevant data in the recent 8 years (2012 to 2019) and used the DEA model and Tobit model to analyze the correlation degree between the efficiency and various influencing factors in China. DEA analysis results show that, in recent years, three efficiencies are quite different: the comprehensive efficiency and scale efficiency show an upward trend, while the pure technical efficiency remains at a high level. Tobit model results show that the number of urban Internet users, rural Internet users, logistics practitioners, the development of national economy are negatively correlated with e-commerce efficiency; the length of traffic construction has no significant correlation; the level of agricultural mechanization has a significant positive correlation. Hence, the paper puts forward four suggestions.

scholarly journals The Formation of AFTA and Trade Diversion: Evidence from China’s Agricultural Exports

2016 ◽  
Vol 17 (1) ◽  
pp. 25-36
Author(s):  
Nguyen Khanh Doanh ◽  
Jeehoon Lee ◽  
Yoon Heo
Keyword(s):  
Panel Data ◽  
Free Trade Agreement ◽  
Bilateral Trade ◽  
Trade Agreement ◽  
Trade Diversion ◽  
Trade Flows ◽  
Agricultural Products ◽  
Agricultural Exports ◽  
Trading Partners ◽  
Bilateral Trade Flows

This study analyzes the impacts of the formation of AFTA (ASEAN Free Trade Agreement) on China’s agricultural exports. The Hausman-Taylor analysis is applied to panel data collected from China and its 68 trading partners from 1993–2012. Our major findings areas follows. First, the discrimination in tariffs imposed by AFTA diverts trade in agricultural products from China toward AFTA’s member countries. Second, at the sectoral level, the trade diversion effects of AFTA’s formation on China’s exports are significant in the case of beverage and tobacco industries. AFTA and China need to focus more on diversifying and differentiating their farming products. To gain better access to AFTA’s market, more investment in research and development activities is recommended as a cure for Chinese farmers. Moreover, this study implies that more efforts in reducing tariff and non-tariff barriers to further liberalize trade between China and AFTA could enhance their bilateral trade flows.

Calculation of regional agricultural production efficiency and empirical analysis of its influencing factors-based on DEA-CCR model and Tobit model

2021 ◽  
pp. 1-14
Author(s):  
Pengfei Zhou ◽  
Siyuan Yang ◽  
Xiaohang Wu ◽  
Yang Shen
Keyword(s):  
Empirical Analysis ◽  
Influencing Factors ◽  
Agricultural Production ◽  
Production Efficiency ◽  
Malmquist Index ◽  
Tobit Model ◽  
Annual Growth Rate ◽  
Productivity Level ◽  
Agricultural Modernization ◽  
Ccr Model

The improvement of agricultural production efficiency and the transformation of production mode are the core of promoting agricultural modernization. Taking Chongqing as a sample case, this paper uses DEA-CCR Model, Malmquist Index and Tobit Model to calculate and analyze its agricultural production efficiency and its influencing factors, and accurately identifies the problems existing in its agricultural transformation and development. It has an important policy reference value for improving agricultural innovation and competitiveness, promoting the steady development of rural revitalization, and realizing agricultural modernization, which also provides some reference and enlightenment for countries or regions with similar characteristics of mountain agriculture development in the world to enhance regional agricultural production efficiency. Through empirical analysis and investigation, it is found that the overall agricultural production efficiency of Chongqing remains at the productivity level of 0.8 from 2009 to 2018, with an average annual growth rate of 12.8%, but there is a large gap in the level of regional development. Through Malmquist Index decomposition, it is found that agricultural technology progress has the greatest contribution to the improvement of production efficiency. Financial support for agriculture, urbanization level, regional economic development level and highway mileage have a significant positive impact on production efficiency, while the level of farmers’ disposable income has a negative impact on the increase of production efficiency, and the income gap between urban and rural residents fails to pass the significance test.

scholarly journals Ketahanan Pangan di Kawasan Timur Indonesia

2012 ◽  
Vol 13 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Triana Rachmaningsih ◽  
D. S. Priyarsono
Keyword(s):  
Food Security ◽  
Panel Data ◽  
Tobit Model ◽  
Poor People ◽  
Eastern Indonesia ◽  
Per Capita ◽  
Years Of Schooling

AbstractThis study aims at analyzing the dynamics of food security and the factors that influence food security in Eastern Indonesia. The methodology used is panel data tobit model of 190 districts/municipalities in the Eastern Indonesia from 2008 to 2010. Based on the classication of the food security degree, the majority of households in Eastern Indonesia are categorized as the vulnerable. Food security is affected by percentage of poor people, GRDP per capita, female illiteracy rate and average years of schooling. Based on the elasticity, education has the highest contribution in improving food security in the Eastern Indonesia.Keywords: Food Security, Eastern Indonesia, Panel Data Tobit Model AbstrakStudi ini bertujuan untuk menganalisis dinamika ketahanan pangan, serta faktor-faktor yang memengaruhi ketahanan pangan di Kawasan Timur Indonesia (KTI). Ketahanan pangan dibagi tiga pilar, yaitu ketersediaan, aksesibilitas, dan pemanfaatan pangan. Metode yang digunakan adalah model tobit dengan data panel dari 190 kabupaten/kota di KTI Tahun 2008-2010. Berdasarkan klasikasi derajat ketahanan pangan, sebagian besar rumah tangga di KTI termasuk kategori rentan terhadap kerawanan pangan. Ketahanan pangan dipengaruhi oleh persentase penduduk miskin, PDRB per kapita, angka buta huruf perempuan, dan rata-rata lama sekolah. Berdasarkan nilai elastisitas, pendidikan memiliki pengaruh terbesar terhadap ketahanan pangan di KTI.Kata kunci: Ketahanan Pangan, Kawasan Timur Indonesia, Model Tobit Data Panel

scholarly journals Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3081 ◽  
Author(s):  
Zeng ◽  
Lu ◽  
Liu ◽  
Zhou ◽  
Hu
Keyword(s):  
Influencing Factors ◽  
Regional Differences ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Tobit Model ◽  
Policy Implications ◽  
Dea Model ◽  
Emission Efficiency ◽  
Unit Root Testing ◽  
Technology Level

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.

scholarly journals Research on the Measurement and Path of Urban Agglomeration Growth Effect

2019 ◽  
Vol 11 (19) ◽  
pp. 5179 ◽  
Author(s):  
Jing Han ◽  
Ming Gao ◽  
Yawen Sun
Keyword(s):  
Human Capital ◽  
Panel Data ◽  
Influencing Factors ◽  
Dynamic Panel Data ◽  
Sustainable Growth ◽  
Urban Agglomeration ◽  
Growth Effect ◽  
Continuous Growth ◽  
Urban Agglomerations ◽  
The Core

This paper employed dynamic generalized method of moment methods to measure the growth effect of 202 prefecture-level cities covered by 14 national urban agglomerations in China from 2007 to 2016. Based on this, this paper further explored the main factors affecting the growth of urban agglomeration and the path to achieving sustainable growth from the aspects of system, technology, structure, and influencing factors, and used the dynamic panel data (DPD) model and threshold panel data to empirically test the growth effect of urban agglomerations. The empirical results showed the following. (1) From the perspective of influencing factors, the improvement of technology and the increase in technology expenditure had a good growth effect on urban agglomeration, and this growth effect became more and more significant as the economic development level within the urban agglomeration narrowed; moreover, the increase of the agglomeration degree could alleviate the negative externality caused by the expansion of the urban scale and produce the dispersion effect to relieve the pressure of urban agglomeration. (2) From the results of the growth effect of urban agglomerations, the growth effect of multi-core urban agglomerations was more significant than that of single-core and dual-core urban agglomerations, and technology, agglomeration degree, foreign direct investment and human capital all significantly promoted the growth of urban agglomerations. Compared with trans-provincial urban agglomerations, provincial urban agglomerations have less resistance due to administrative jurisdiction, and the growth effect was obvious. (3) From the perspective of regional differences, the growth momentum of urban agglomerations in the eastern region was significantly stronger than that in the central and western regions, and the growth effect of agglomeration degree, technology, and human capital on urban agglomeration were all stronger than that in the central and western regions. Considering that the spatial distance between the edge cities and the central cities of the urban agglomeration will have an important impact on the overall growth of the urban agglomeration, this paper then used the panel threshold method to deeply discuss the influence mechanism and path dependence of the agglomeration degree on the growth of urban agglomerations. The results showed that within a certain spatial scale, a higher agglomeration degree of an urban agglomeration creates a stronger radiation effect of the core city and more obvious growth momentum of the urban agglomeration. In the future development of urban agglomerations, it is necessary to clarify the functions of the core city, vigorously develop new technologies, strengthen the construction of the core city as well as maximize its radiation and driving effect on the surrounding cities. Meanwhile, the government should improve transportation, increase the construction of urban expressways and railways, strengthen the connection between cities, strengthen regional integration and cooperation, and give play to the role of human capital in promoting growth to achieve the stable and continuous growth of urban agglomerations.

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