Sources of Agricultural Growth in Communist China

1968 ◽  
Vol 27 (4) ◽  
pp. 721-737 ◽  
Author(s):  
Chi-Ming Hou
Keyword(s):  
Chinese Economy ◽  
Food Crops ◽  
Nineteen Fifties ◽  
Animal Products ◽  
Agricultural Output ◽  
Agricultural Growth ◽  
Percent Increase ◽  
Official Figure ◽  
Communist China ◽  
Per Capita Consumption

In this paper, I shall try to examine and identify the factors responsible for the increase in agricultural output in Communist China in the nineteen fifties. Then I shall try to discuss the implications of my findings in relation to future agricultural growth.Agricultural Output 1949–1957. Agricultural statistics remain the Achilles' heel in evaluating the performance of the Chinese economy in quantitative terms. For foodgrains, the official statistics show an increase of nearly 43 percent from 1949 to 1952, and nearly 20 percent from 1952 to 1957. These claims are generally regarded as exaggerated. Based on per capita consumption requirements, Liu and Yeh regard the pre-1956 official figures as gross understatements. They accept, however, the official figure for 1957. They allow for no more than 5 percent increase from 1952 to 1957 for the production of food crops. After adjustment of reported cultivated area has been made, Wu's estimate shows virtually no increase in foodgrains from 1952 to 1957. Hollister, after suggesting official understatements for earlier years, accepts the official 1955 figure and estimates that the 1957 production of basic food crops and animal products was 14 percent higher than that of 1952. Jones and Poleman also maintain that the official estimates of grain production were underestimates for 1952–54; they accept the 1955–57 figures. Their estimates put the 1957 level about 12 percent higher than that in 1952. Choh-ming Li, though without making any independent estimates of his own, regards the official figure for 1955 as more reliable or least unsatisfactory for the whole period 1949–57, while considering the pre-1955 years as underestimates and the post-1955 years (that is, 1956 and 1957) as overestimates.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI OUTPUT PERTANIAN TANAMAN PANGAN DI INDONESIA

2021 ◽  
Vol 3 (2) ◽  
pp. 11
Author(s):  
Rafi Hidayat ◽  
Sri Ulfa Sentosa
Keyword(s):  
Quantitative Research ◽  
Secondary Data ◽  
Food Crops ◽  
Panel Regression ◽  
Land Area ◽  
Agricultural Output ◽  
Fertilizer Use ◽  
Insignificant Effect ◽  
Result Show ◽  
The Government

This study aims to systematize and explain the effect of land area, fertilizer use and labor on agriculture output of food crops in Indonesia. This type of research is quantitative research, the data used is secondary data which is analyzed using panel regression analysis. The estimation result show that land area has a negative and insignificant effect on agricultural output of food crops in Indonesia, the amount of fertilizer use has a positive and significant effect on agricultural output of food crops in Indonesia and labor has a negative and insignificant effect on agricultural output of food crops in Indonesia. Therefore this study proposes the government to be able to run a program that can increase land production power and labor production power in order to increase agricultural output of food crops.

Agrarian Distress under Global Integration: Impoverishing Growth and "Perverse" Supply Response

2009 ◽  
pp. 45-73
Author(s):  
J. Mohan Rao ◽  
Vamsi Vakulabharanam
Keyword(s):  
Economic Integration ◽  
South India ◽  
Value Added ◽  
Development Economic ◽  
Food Crops ◽  
Global Integration ◽  
Food Crop ◽  
Markets And Institutions ◽  
Per Capita ◽  
Per Capita Consumption

- This paper aims to explain theoretically two apparently paradoxical phenomena witnessed in the Telangana region of South India between 1985 and 2000. First, despite the rapid growth of real agricultural output during this period, per-capita consumption of the majority of the agricultural population declined during the 1990s (when agricultural liberalization policies were introduced in India) after steadily rising during the 1980s. Second, non-food crop supply elasticities, which had been positive, turned "perversely" negative during the 1990s. Employing a model of a peasant economy with an effort supply function originally proposed by Leibenstein, we explain the two puzzles in terms of the interplay between the conditions of global integration (falling value-added prices) and the nature of local credit markets and institutions (including the practice of requiring collateral in the form of non-food crops).EconLit Classification: P160, O100, F150, Q100Keywords: Capitalist Systems, Political Economy, Economic Development, Economic Integration, Sustainable DevelopmentParole chiave: Sistemi capitalistici, Politica economica, Sviluppo economico, Integrazione economica, Sviluppo sostenibile

Underemployment in Agriculture

New India ◽  
2020 ◽  
pp. 33-55
Author(s):  
Arvind Panagariya
Keyword(s):  
Agricultural Policy ◽  
Animal Husbandry ◽  
Gdp Per Capita ◽  
Agricultural Output ◽  
Agricultural Growth ◽  
Long Period ◽  
Self Sufficiency ◽  
History Of ◽  
Per Capita ◽  
The Way

The chapter begins with a history of agricultural policy in India. It goes on to argue that policies aimed at improving outcomes within agriculture alone cannot bring prosperity to those engaged in it. Today, agriculture employs 44 percent of India’s workforce but produces at most 17 percent of GDP. With the overall GDP per capita itself low, agricultural output per worker is extremely low, indicating gross underemployment of labor. Therefore, marketing reforms that shift prices in favor of the farmer and against intermediaries cannot go very far. With self-sufficiency in agriculture, increases in productivity will likely result in lower prices rather than higher revenues. Besides, agricultural growth rarely exceeds 4.5 percent over even a decade-long period. Scope for increased incomes through diversification within agriculture into horticulture, fisheries, and animal husbandry is also limited. The upshot is that the only avenue to increasing agricultural incomes rapidly is to pave the way for half or more of the farm workforce to migrate into industry and services.

Effects of government supports and credits on Turkish agriculture

2019 ◽  
Vol 9 (4) ◽  
pp. 391-401 ◽  
Author(s):  
Ahmet Ali Koç ◽  
T. Edward Yu ◽  
Taylan Kıymaz ◽  
Bijay Prasad Sharma
Keyword(s):  
Spillover Effect ◽  
Value Added ◽  
Spillover Effects ◽  
Data Set ◽  
Agricultural Output ◽  
Content Type ◽  
Spatial Spillover ◽  
Percent Increase ◽  
Spatial Spillover Effects ◽  
The Impact

Purpose Domestic supports on Turkish agriculture have substantially increased over the past decade while empirical evaluation of their output impact is limited. Also, the existing literature often neglects potential spatial spillover effects of agricultural policies or subsidies. The purpose of this paper is to quantify the direct and spillover effects of Turkish agricultural domestic measures and agricultural credits use on the added agricultural value. Design/methodology/approach This study applied a spatial panel model incorporating spatial interactions among the dependent and explanatory variables to evaluate the impact of government support and credit on Turkish agricultural output. A provincial data set of agricultural output values, input factors and government subsidies from 2004 to 2014 was used to model the spatial spillover effects of government supports. Findings Results show that a one percent increase in agricultural credits in a given province leads to an average increase of 0.17 percent overall in agricultural value-added per hectare, including 0.05 percent from the direct effect and 0.12 percent from the spillover effect. Contrary to agricultural credits, a one percent increase in government supports in a province generates a mixed direct and spillover effects, resulting in an overall reduction of 0.13 percent in agricultural value-added per hectare in Turkey. Research limitations/implications This study could be extended by controlling for climate, biodiversity and investment factors to agricultural output in addition to input and policy factors if such data were available. Originality/value This study fills the gap in the literature by determining the total effect, including direct and spatial spillover effect, of domestic supports and credits on Turkish agricultural value. The findings provide crucial information to decision makers regarding the importance of incorporating spatial spillover effects in the design of agricultural policy.

Conditions and Prospects for Economic Growth in Communist China

1955 ◽  
Vol 7 (3) ◽  
pp. 434-447
Author(s):  
Alexander Eckstein
Keyword(s):  
Industrial Revolution ◽  
Social Power ◽  
Chinese Economy ◽  
World War ◽  
Industrial Base ◽  
The Past ◽  
Long Run ◽  
Communist China ◽  
Rate Of Recovery ◽  
Point Of Departure

Regardless of whether a detailed Five-Year Plan is in operation or not, there is in Communist China every indication of a determined, relentless, and massive effort to pursue a program of industrial expansion. The rapid rate of recovery, the restructuring of the institutional framework, the possession of an industrial base in Manchuria, the termination of hostilities in Korea, and, above all, the application of political and social power to the mobilization of resources in the hands of the state are all factors that have enabled the regime to raise the rate and level of investment considerably above that of the past. At the same time, the regime is mobilizing not only capital, but technique and entre-preneurship as well. In essence, the Chinese economy—after being more or less stationary for centuries, with only erratic and partial spurts of growth in recent decades—seems to be entering, for better or for worse, a self-sustaining growth process.Barring another world war or a major agricultural crisis in China, the long-run question before us is not whether the Chinese Communist economy will grow at all, but whether the rate of growth will be sufficiently rapid so that the forces of the industrial revolution will be in a position to defeat the Malthusian counterrevolution. Given the previously discussed conditions and limitations, how rapidly may industrialization be expected to proceed? Obviously, these questions can only be answered conditionally and hypothetically. However, before approaching this problem, it may be well to take a schematic look at the “size” and “structur” of the Chinese mainland economy in 1952, which may be considered as the point of departure for the upward climb.

scholarly journals Pola Konsumsi dan Permintaan Pangan Sumber Protein Hewani di Provinsi Nusa Tenggara Barat dan Nusa Tenggara Timur

2019 ◽  
Vol 17 (1) ◽  
pp. 1
Author(s):  
Esty Asriyana Suryana ◽  
Drajat Martianto ◽  
Yayuk Farida Baliwati
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Animal Protein ◽  
Animal Products ◽  
Fresh Fish ◽  
Income Elasticities ◽  
Self Sufficiency ◽  
Participation Level ◽  
Livestock Products ◽  
Per Capita Consumption

<p>Animal protein intake determines food consumption quality for healthy, active, and productive life. Objectives of this study were to analyze consumption patterns and demand for animal protein sources in cattle producing centers in West Nusa Tenggara (NTB) and East Nusa Tenggara (NTT) provinces. This study employed 2014 Susenas data. Animal protein consumption levels in both provinces were below the recommended daily nutritional adequacy. Beef consumption participation level was very low (6.06%). Demand elasticities for animal products in rural areas were higher than those in urban areas, except for fresh fish. Income elasticities in urban areas were higher in terms of beef, chicken, milk, fresh fish and preserved fish. Income elasticities of meats and eggs in rural areas were higher for meats and eggs. Beef per capita consumption in 2020 is estimated to be 0.44 kg and in 2025 will reach 0.51 kg. Total demand for beef are projected to be 4,720 kg and 5,734 kg in 2020 and 2025, respectively. To achieve self-sufficiency in animal protein, in addition to beef self-sufficiency program currently implemented, it is necessary to increase other livestock products such as poultry with protein content equal to beef but with cheaper prices.</p><p> </p><p>Abstrak</p><p>Asupan protein hewani menentukan kualitas konsumsi makanan yang diperlukan untuk mendukung hidup sehat, aktif, dan produktif. Penelitian ini bertujuan untuk menganalisis pola konsumsi dan permintaan pangan sumber protein hewani di daerah sentra produsen sapi di provinsi NTB dan NTT. Model AIDS digunakan untuk mengestimasi elastisitas permintaan pangan dan persamaan linear untuk mengestimasi proyeksi permintaan pangan hewani tahun 2020-2025. Data yang digunakan adalah data Susenas tahun 2014 dari BPS. Hasil penelitian menunjukkan bahwa konsumsi pangan sumber protein hewani masyarakat di dua provinsi di Nusa Tenggara  belum memenuhi angka kecukupan gizi yang dianjurkan.Tingkat partisipasi konsumsi pangan sumber protein hewani untuk daging sapi cukup rendah, yaitu sebesar 6,06 %. Nilai elastisitas permintaan pangan di pedesaan lebih tinggi dibandingkan di perkotaan untuk seluruh komoditas kecuali ikan segar. Elastisitas pendapatan masyarakat perkotaan lebih tinggi untuk daging sapi, daging ayam, susu, ikan segar, dan ikan awetan, sedangkan bagi masyarakat pedesaan untuk daging lainnya dan telur lebih besar. Hasil proyeksi menunjukkan permintaan daging sapi dalam periode tahun 2020-2025 terus meningkat. Konsumsi daging sapi per kapita di kedua provinsi tersebut tahun 2020 diperkirakan sebesar 0,44 kg/tahun dan tahun 2025 mencapai 0,51 kg/tahun, sehingga  permintaan daging sapi tahun 2020 dan 2025 diproyeksikan masing-masing sebesar 4.720 kg dan 5.734 kg. Dalam rangka mewujudkan upaya swasembada protein hewani, selain program pencapaian swasembada daging sapi yang sudah berjalan, sebaiknya perlu diupayakan peningkatan komoditas pangan hasil ternak lainnya seperti unggas yang memiliki kandungan protein yang tidak kalah dengan daging sapi dengan harga yang lebih murah.</p>

scholarly journals AgriBot: Agriculture-Specific Question Answer System

2019 ◽  
Author(s):  
Naman Jain ◽  
Pranjali Jain ◽  
Pratik Kayal ◽  
Jayakrishna Sahit ◽  
Soham Pachpande ◽  
...  
Keyword(s):  
Call Center ◽  
Electronic Device ◽  
Plant Protection ◽  
Agricultural Practices ◽  
Hard Work ◽  
Entity Extraction ◽  
Specific Question ◽  
Agricultural Output ◽  
Agricultural Growth ◽  
System P

India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24*7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal.

Rural Infrastructure and Agricultural Output Nexus

2021 ◽  
pp. 249-273
Author(s):  
A. Narayanamoorthy
Keyword(s):  
Empirical Studies ◽  
Recent Time ◽  
Infrastructure Development ◽  
Regression Analyses ◽  
Agricultural Output ◽  
Agricultural Growth ◽  
Rural Infrastructure ◽  
Time Points ◽  
The Impact ◽  
Over Time

This chapter systematically addresses how rural infrastructure development can impact agricultural output using a large canvas of literature and district-wise data. Though a number of empirical studies have established the nexus between the infrastructure development and agricultural growth, not many studies are available using large number of districts and covering different time-points in recent time in the Indian context. Despite the fact that the infrastructure development cannot make impact instantaneously on agricultural output, most available studies have analysed the impact of infrastructure factors on the agricultural output without using them as lagged variables. While addressing the impact of infrastructure factors on agricultural output over time, this chapter brings out the real nexus between infrastructure development and the agricultural output covering 256 districts using both descriptive and regression analyses.

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