Distribution and Determinants of Fallow Land among Farmers of Central Dry Zone of Karnataka

2020 ◽  
pp. 390-395
Keyword(s):  
Arable Land ◽  
Negative Relationship ◽  
Fallow Land ◽  
Tobit Regression ◽  
Total Size ◽  
High Tendency ◽  
Fertility Status ◽  
Dry Zone ◽  
Land Holdings ◽  
Tobit Regression Model

Farmers in dry regions of India have a high tendency for leaving their land fallow. To decipher this phenomenon, the study was carried out in the Tumkur district of the central dry zone of Karnataka. Results from the study revealed a positive relationship between the size of land holdings and land fallow. The major reason stated by farmers for leaving their fallow land was the scarcity of rainfall or irrigation, and poor land fertility status. The Tobit regression model was fitted to study the determinants of the decision of farmers to keep the arable land fallow, where, dependent variable considered was the share of fallow land in the total size of landholding of farm households. It was found that the availability of water for irrigation and family labour has a negative relationship with fallow land. Other factors determining the extent of fallow land were the distance of land from residences, poor land fertility status and availability of credit.

scholarly journals Microcredit and Farmers’ Productivity in Osun State, Nigeria

2019 ◽  
pp. 1-11
Author(s):  
Omobolaji Olubukunmi Obisesan ◽  
Olusegun Bankole Ojewumi ◽  
Adekunle Akintunde Obisesan
Keyword(s):  
Interest Rate ◽  
Regression Model ◽  
Significant Relationship ◽  
Negative Relationship ◽  
Household Size ◽  
Descriptive Statistics ◽  
Tobit Regression ◽  
Lending Institutions ◽  
Tobit Regression Model ◽  
Planting Season

The present work examined micro-credit and farmers’ productivity in Osun State, Nigeria. A total of 140 respondents were interviewed using structured questionnaires. Data obtained was analyzed using descriptive statistics and Tobit regression model. The research showed there was a significant relationship between household size (β=0.623), farming experience (β=0.858) and loan condition (β=1.29) on the acquisition of credit by farmers. Income generated was used as a proxy for productivity, and it was in the minimum of N20,000 per planting season. Interest rate had a negative relationship with credit acquisition which implied the majority of the farmers patronized the informal sources of credit. The research showed that loan conditions from informal sources was favorable compared to that from formal sources; and a reason for the high patronage. This, therefore, suggests that formal lending institutions should relax agricultural lending condition and provide credit for agricultural purposes to increase the productivity of farmers. 

An Efficiency Analysis of Micro Units in a Fragile Zone: A Panel Study of the Firms in J&K, India

2021 ◽  
pp. 097492922110448
Author(s):  
Javaid Iqbal Khan ◽  
Mehak Majeed ◽  
Saeed Owais Mushtaq
Keyword(s):  
Stochastic Frontier Analysis ◽  
Small And Medium Enterprises ◽  
Panel Study ◽  
Stochastic Frontier ◽  
Negative Relationship ◽  
Jel Classification ◽  
Tobit Regression ◽  
Jammu And Kashmir ◽  
Frontier Analysis ◽  
The Government

The micro, small and medium enterprises (MSMEs) are the backbone of the community development in the developing world. In the fragile and backward regions, it is the micro enterprise that is considered to be the engine of growth and development. Being labour-intensive and requiring lesser capital input, the micro unit start-ups demand lesser investment in plant and machinery, attracting more and more potential entrepreneurs. Over the time, such units gain experience and knowledge becoming more efficient. This article studies the firms located in the fragile and geographically remote region of Jammu and Kashmir. The article uses a panel of 15 years from 2002 to 2016 based on the Annual Survey of Industries data. Using the Stochastic Frontier Analysis, the article studies the MSMEs and the micro units. From the post-estimation, technical efficiency scores are attained for both MSMEs and the micro units. The results reveal that the micro units are more efficient than the MSMEs in general. Tobit regression is used to estimate the technical inefficiency model to determine the factors that contribute to the inefficiency present in the micro units. The results show that there is a negative relationship between the efficiency of the micro unit firms and the asset-liability ratio and the loan-liability ratio, while there is a positive relationship between the private ownership of the firm and the efficiency level. Age of the firm is considered separately to validate the ‘learning theory’ by Jovanovic. The article concludes by suggesting that the government must provide adequate boost and a big-push to the micro units in order to eradicate the widespread unemployment and fragility in the region. JEL Classification: F61, L25

scholarly journals THE ISLAMIC BANKING AND THE ECONOMIC INTEGRATION IN ASEAN

2016 ◽  
Vol 19 (1) ◽  
pp. 81-106
Author(s):  
Solihin Solihin ◽  
Noer Azam Achsani ◽  
Imam T Saptono
Keyword(s):  
Market Power ◽  
Banking System ◽  
Islamic Banking ◽  
Tobit Regression ◽  
Total Size ◽  
Bank Efficiency ◽  
Internal Factors ◽  
Banking Efficiency ◽  
Important Indicator ◽  
The Cost

The efficiency level of the banking industry is the most important indicator to identify the soundness of banking system. This paper use non parametric frontier approach, DEA, to analyze the Islamic bank efficiency in ASEAN. We use price of deposit from customers, deposits and placements of banks, labor, and others operational expenditures as control variabel, and using financing, deposits and placements on other insitution, securities, others investment as output variabel. We found that the mix bank is the most efficient group within the observation period. Furthermore, the average Islamic banking efficiency in Indonesia, on intermediation approach, is lower than the average of ASEAN, unless they can reduce the cost of labor and other operational expenses. This paper also examines the determinant of efficiency of the Islamic Banking in ASEAN. Internal factors are Total Aset, ROA, BOPO, and ETA, and external faktor are Market Power and Inflation. Using Tobit regression, the result shows the factors that most influence to the Islamic banking efficiency in Indoneisa is the total size of the bank or its assets, OPEX/OR, and Market Power.

scholarly journals Assessment of fertility status of soils under land use types in Egbema Area, Imo State, Nigeria

2020 ◽  
Vol 17 (2) ◽  
pp. 1-13
Author(s):  
C. Chikere-Njoku
Keyword(s):  
Land Use ◽  
Bulk Density ◽  
Soil Ph ◽  
Oil Palm ◽  
Fallow Land ◽  
Cultivated Land ◽  
Fertility Status ◽  
Oil Palm Plantation ◽  
Land Use Types ◽  
Land Use System

The study was conducted to investigate fertility status under four different land use types (oil palm plantation, pineapple orchard, cassava cultivated land and fallow land use system) in Umuekem, Ohaji/Egbema of Imo State, Nigeria. Composite samples were collected from various depths (10-15cm, 15-30cm, 30-45cm) across these land use patterns and analyzed in the laboratory using the standard procedure. Data generated were subjected to statistical analysis. Results obtained showed significant differences (p ≥ 0.05) in silt-clay ratio, bulk density, total porosity, water holding capacity, soil pH, organic carbon, available phosphorus, TN and ECEC across the four land use types studied. The soils were predominantly loamy sand surface and sandy clay loam in the subsoil exception of pineapple orchard with sandy loam topsoil over sandy clay loam subsoil. The silt clay ratio (SCR) showed ranges of 0.10-0.30, 0.10-0.36, 0.07 – 0.30, and 0.06- 0.20 in land use types of oil palm plantation, pineapple orchard, cassava cultivated land and fallow land respectively. The bulk density ranged of (1.61 – 1.77 g/cm3) for oil palm, (1.34 – 1.58 g/cm3) for pineapple (1.42 – 1.49 g/cm3) cassava and (1.45 – 1.48 g/cm3) in forest land use system. The soils of the four land use types were generally acidic. The mean values of soil pH (H20) were oil palm plantation (5.11), pineapple orchard (5.03), cassava cultivated land (5.35) and fallow land (5.40). The soil pH recorded low variation in all the land use types. The organic carbon and total nitrogen recorded high variation (>52.57% < 85.67%, >79.19 < 95.77) in all the different land use types. Calcium-magnesium ratio (Ca: Mg) recorded high variation (37.36%) in forest land use system, low variation (18.77%) in pineapple orchard and moderate in cassava (27.51%) and oil palm plantation (28.23). The low Ca: Mg ratio inhibits uptake and causes Ca deficiency thereby resulting in low fertility status of the soil. C: P recorded high variation (≥ 53.77% ≤ 77.73%) in all the studied land use types. O.C correlated positively and highly significant with available phosphorus, ECEC and T.N. The findings also indicated that bulk density correlated positively with ECEC and percentage base saturation. It is recommended that land use approach should be adopted for effective and sustainable management of the soil fertility. Keywords: Fertility status, Soils, Land use types

scholarly journals Analysis of Severe Injury Accident Rates on Interstate Highways Using a Random Parameter Tobit Model

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Minho Park ◽  
Dongmin Lee
Keyword(s):  
Regression Model ◽  
Unobserved Heterogeneity ◽  
Random Parameter ◽  
Tobit Model ◽  
Severe Injury ◽  
Parameter Estimates ◽  
Random Parameters ◽  
Tobit Regression ◽  
Accident Rates ◽  
Tobit Regression Model

In this study, a random parameter Tobit regression model approach was used to account for the distinct censoring problem and unobserved heterogeneity in accident data. We used accident rate data (continuous data) instead of accident frequency data (discrete count data) to address the zero cell problems from data where roadway segments do not have any recorded accidents over the observed time period. The unobserved heterogeneity problem is also considered by using random parameters, which are parameter estimates that vary across observations instead of fixed parameters, which are parameter estimates that are fixed/constant over observations. Nine years (1999–2007) of panel data related to severe injury accidents in Washington State, USA, were used to develop the random parameter Tobit model. The results showed that the Tobit regression model with random parameters is a better approach to explore factors influencing severe injury accident rates on roadway segments under consideration of unobserved heterogeneity problems.

Tobit model-based analysis on the influencing factors of wheat loss during harvesting by the combine harvester

2021 ◽  
pp. 1-14
Author(s):  
Hong Ji ◽  
Xun He ◽  
Li Ding ◽  
Zhe Qu ◽  
Wenkang Huang ◽  
...  
Keyword(s):  
Regression Model ◽  
Influencing Factors ◽  
Loss Rate ◽  
Henan Province ◽  
Normal Operation ◽  
Tobit Regression ◽  
Wheat Field ◽  
Combine Harvester ◽  
Main Factors ◽  
Tobit Regression Model

Based on the investigation data of wheat mechanized harvest in eight major wheat producing areas from the south to the north of Henan Province, the main factors affecting wheat mechanized harvest loss were identified and the influence of each factor was decomposed. In this article, the loss rate of wheat mechanical harvest was calculated by using the method of artificial measurement of wheat yield in the field, and the influencing factors of wheat mechanical harvest operation in 8 regions of Henan province were treated and analyzed by using Tobit regression model. In this paper, the loss rate of wheat mechanical harvest was calculated by using the method of wheat field artificial yield measurement and the influencing factors of wheat mechanical harvest operation in eight regions of Henan province were treated and analyzed by using Tobit regression model. The results show that the average harvest loss rate in the field amounts to 2.96%, the average harvest loss rate at the edge of field amounts to 3.06%, whereas the loss rate in the normal operation area amounts 2.86%. The main factors that caused the harvest loss of wheat field machinery were the maturity of wheat, the area of operation field, the diseases and pests, weather conditions and the accumulated working hours of harvester drivers in a single day. Therefore, the main technical measures to reduce the operation loss of wheat combine harvester were put forward to provide a theoretical basis for promoting the deep integration of agricultural machinery and agronomy.

Operating Efficiency Analysis of Energy Industries in Taiwan

2013 ◽  
Vol 869-870 ◽  
pp. 612-620 ◽  
Author(s):  
Nattanin Ueasin ◽  
Anupong Wongchai
Keyword(s):  
Regression Model ◽  
Stock Exchange ◽  
Efficiency Score ◽  
Operating Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Factors Affecting ◽  
Taiwan Stock Exchange ◽  
Energy Companies ◽  
Tobit Regression Model

The energy business has played an important role in an economic growth of Taiwan because the market share is in the high value that can make a significant contribution towards regional and local employment. However, Taiwan is lack of energy resources, making the country highly relies on an import for more than 98 percent of its all energy. At present, a top priority of the countrys policy is to develop clean, sustainable, independent, and efficient energy in order to eliminate the vulnerability from external disruption. Therefore, this research aims to assess the operating efficiency and to analyze factors affecting the efficiency scores of the registered energy companies in the Taiwan Stock Exchange (TWSE) recorded during 2003-2012. The super-efficiency data envelopment analysis (SE-DEA) was initially applied to reveal the additional efficiency scores, followed by the Tobit regression model used to analyze what factors determine the efficiency scores. The empirical results showed that seven DMUs performed efficiently, ranking from 7.29 to 1.02. The company with the best operating performance was Taiwan Cogeneration Corporation (TCC), while the Great Taipei Gas Corporation (GTG) revealed the worst efficiency score. Furthermore, the Tobit regression model explained that the higher number of the local employees, the greater the efficiency scores were. Besides, the lower number of the shareholders, the greater the efficiency scores were. As a result, the Taiwans government is supposed to encourage all energy companies to have a higher number of local employees and shareholders to increase their efficiency scores.

scholarly journals An Experimental Investigation of Consumer Willingness to Pay for Non-GM Foods When an Organic Option Is Present

2006 ◽  
Vol 35 (2) ◽  
pp. 374-385 ◽  
Author(s):  
John C. Bernard ◽  
Chao Zhang ◽  
Katie Gifford
Keyword(s):  
Experimental Investigation ◽  
Willingness To Pay ◽  
Regression Model ◽  
Tobit Regression ◽  
Milk Chocolate ◽  
Gm Foods ◽  
Consumer Demographics ◽  
Tortilla Chips ◽  
Marginal Effects ◽  
Tobit Regression Model

This research compared bids that consumers placed on non genetically modified (GM), organic, and conventional versions of food products in order to determine if the organic market well serves those seeking to avoid GM foods. Auction experiments using potato chips, tortilla chips, and milk chocolate were conducted with 79 subjects. Bids were modeled as a function of consumer demographics using a heteroskedastic tobit regression model. Results with the non-GM attribute nested into the organic characteristic showed that the latter's marginal effects were insignificant. This suggested the potential to further develop non-GM products for consumers not willing to pay extra for the remaining organic attributes.

Sign in / Sign up

Export Citation Format

Share Document