scholarly journals EFFECTS OF AGRICULTURAL SUBSIDIES ON INCOME RISK IN LITHUANIAN DAIRY FARMS

2016 ◽  
Vol 38 (4) ◽  
pp. 351-358 ◽  
Author(s):  
Imre Ferto ◽  
Aldona Stalgienė
Keyword(s):  
Panel Data ◽  
Positive Impact ◽  
Dairy Farms ◽  
Econometric Models ◽  
Farm Size ◽  
Farm Income ◽  
Income Risk ◽  
Agricultural Subsidies ◽  
Coefficients Of Variation ◽  
Income Variability

The aim of the paper is to investigate the effects of agricultural subsidies on income variability of Lithuanian dairy farms. In addition, the observed heterogeneity in income risks across farms and time is explained in terms of farm characteristics. It was employed balanced farm-level panel data of the Lithuanian farm accountancy network (FADN) was used to construct coefficients of variation of five-year gross farm revenues over the period 2010 to 2014. Various econometric models are applied to measure the effect of off-farm income, total subsidies, farm size, and financial immobility on the variability of gross farm incomes. Estimations suggest that agricultural subsidies, liquidity have positive impact on income risk. The age of farmers negatively influences the income risk. There is non-linear relationship between farm size and income risk.

From rainfall to farm incomes—transforming advice for Australian drought policy. II. Forecasting farm incomes

2007 ◽  
Vol 58 (10) ◽  
pp. 1004 ◽  
Author(s):  
Rohan Nelson ◽  
Philip Kokic ◽  
Holger Meinke
Keyword(s):  
Rural Communities ◽  
Risk Model ◽  
Rural Livelihoods ◽  
Companion Paper ◽  
Farm Income ◽  
Income Risk ◽  
Income Sources ◽  
Bioeconomic Modelling ◽  
Effects Of Drought ◽  
Income Variability

Australian drought policy is focussed on providing relief from the immediate effects of drought on farm incomes, while enhancing the longer term resilience of rural livelihoods. Despite the socioeconomic nature of these objectives, the information systems created to support the policy have focussed almost exclusively on biophysical measures of climate variability and its effects on agricultural production. In this paper, we demonstrate the ability of bioeconomic modelling to overcome the moral hazard and timing issues that have led to the dominance of these biophysical measures. The Agricultural Farm Income Risk Model (AgFIRM), developed and tested in a companion paper, is used to provide objective, model-based forecasts of annual farm incomes at the beginning of the financial year (July–June). The model was then used to relate climate-induced income variability to the diversity of farm income sources, a practical measure of adaptive capacity that can be positively influenced by policy. Three timeless philosophical arguments are used to discuss the policy relevance of the bioeconomic modelling. These arguments are used to compare the value to decision makers of relatively imprecise, integrative information, with relatively precise, reductionist measures. We conclude that the evolution of bioeconomic modelling systems provides an opportunity to refocus the analytical support for Australian drought policy towards the rural livelihood effects that matter most to governments and rural communities.

scholarly journals Valor bursátil de los bancos europeos: Determinantes económico-financieros y de gobierno corporativo

2020 ◽  
Vol 32 (2) ◽  
pp. 677
Author(s):  
Iván Muñoz Jiménez ◽  
José Miguel Rodríguez Fernández
Keyword(s):  
Corporate Governance ◽  
Panel Data ◽  
Empirical Study ◽  
Capital Structure ◽  
Positive Impact ◽  
Market Value ◽  
Econometric Models ◽  
Banking Institutions ◽  
European Banks ◽  
Asset Quality

The objective of this empirical study is to investigate the influence of the economic, financial and corporate governance characteristics on stock market value of a sample of European banks in recent years. To this end, several theoretical hypotheses are tested by various estimates econometric models with different specific techniques for panel data, considering as dependent variable Tobin's Q ratio. It detects that there is a positive impact of good asset quality, adequate capital structure, operational efficiency, liquidity and corporate governance of banking institutions.

scholarly journals Profitability on dairy farms with automatic milking systems compared to farms with conventional milking systems

2019 ◽  
Vol 22 (2) ◽  
pp. 215-228 ◽  
Author(s):  
Bjørn Gunnar Hansen ◽  
Hans Olav Herje ◽  
Jonas Höva
Keyword(s):  
Dairy Farms ◽  
Ordinary Least Squares ◽  
Transitional Period ◽  
Farm Size ◽  
Farm Income ◽  
Least Squares Regression ◽  
Farm Production ◽  
Automatic Milking ◽  
The Difference ◽  
Automatic Milking Systems

The objective of this study was to explore differences in profitability between farms with automatic milking systems (AMS) and farms with conventional milking systems (CMS). To explore profitability, we analysed the gross farm income from dairy cows. Accounting and production data for over a thousand dairy farms were collected. Using kernel-matching, we made CMS farms more comparable to AMS farms. We then used ordinary least squares regression to estimate the effect of AMS relative to farm size and time passed since last investment in milking systems. The results show that farms must have 35 to 40 cows before AMS becomes more profitable than CMS. Further, any profitability gains will only be visible after a transitional period of approximately four years. Milk revenues are higher on AMS farms, and the difference increases with the size of the farm. Production-related costs are also higher on AMS farms.

scholarly journals Factors influencing the adoption of improved cultivars: a case of peach farmers in Pakistan

2018 ◽  
Vol 48 (11) ◽  
Author(s):  
Arif Ullah ◽  
Dilawar Khan ◽  
Shaofeng Zheng ◽  
Uzair Ali
Keyword(s):  
Financial Services ◽  
Choice Model ◽  
Positive Impact ◽  
Climatic Factors ◽  
Farm Size ◽  
Farm Income ◽  
Related Factors ◽  
Khyber Pakhtunkhwa ◽  
Factors Influencing ◽  
Improved Cultivars

ABSTRACT: This study aimed to investigate factors influencing the adoption of improved cultivars (ICs) in peach production in Khyber Pakhtunkhwa province of Pakistan. A total of 270 respondents were randomly selected from the three different cultivated areas of Khyber Pakhtunkhwa, namely, Peshawar, Nowshera and Swat. Binary choice model was used in this study to categorise the ICs of peach farmers into adoption and non-adoption. The study identifies that socio-economic, institutional farm resources, and climatic factors are influencing the adoption of ICs of peach production. Results of the estimated model reveal that farmer’s age, education, household size, membership, cell phone, farm size, extension services and the role of the non-government organization have a positive effect on adoption of ICs. In addition, farmer’s experience, off-farm income, livestock and machinery ownership, credit access and inputs prices have a positive and significant impact on ICs adoption. Moreover, results of the logit model demonstrate that climatic related factors have a highly significant and positive impact on the adoption of ICs. These results suggested that institutional services should be strengthened to provide managerial and technical skills on ICs technology adoption and on time provision of financial services to enhance the productivity of peach farmers.

scholarly journals Economic implication of contract farming on small-scale rice farmers in Kwara State, Nigeria

Agrosearch ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 26-40
Author(s):  
S.O. Akanbi ◽  
W.I. Alarape ◽  
O.S. Olatunji
Keyword(s):  
Technical Efficiency ◽  
Positive Impact ◽  
Stochastic Frontier ◽  
Farm Size ◽  
Farm Income ◽  
Small Scale ◽  
Economic Implication ◽  
Contract Farming ◽  
Productivity Level ◽  
Rice Farmers

This study examines the implication of contract farming on Olam Out-growers farming scheme in Kwara State, Nigeria. The objectives of the study are to determine the costs and returns to production of rice, assess the productivity level of rice, evaluate the technical efficiency of rice farm and identify the determinants of the technical inefficiency of the rice farms in contract farming. In this study, the average net farm income of the rice farmers under the scheme was N191,862.56 and the land productivity level was 2,006.04kg/ha. The technical efficiency of the rice farm was estimated using Cobb-Douglas Stochastic Frontier Production function which shows that likelihood coefficients for quality of seeds, hired labour and farm size were statistically significant at 1% level. Likewise, the determinants of technical efficiency among the farmers were household size and farming experience. The results further show that the contract farming scheme has a positive impact on the lives of rice farmers. Therefore, there is a need for partnership with private contract farming outfits in order to improve the current level of access to inputs by rice farmers. Keywords: Contract farming, Out-growers rice farmers, Technical efficiency, Farm income

scholarly journals A Panel Data Analysis Model to Assess the Impact of Institutional Factors on Crop Diversification of Assam, India

2020 ◽  
Vol 9 (6) ◽  
pp. 167-173
Keyword(s):  
Panel Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Value Added ◽  
Institutional Factors ◽  
Macro Level ◽  
Farm Size ◽  
Crop Diversification ◽  
The Impact

The process of crop diversification is generally used in agriculture to mitigate both production and price risk. Crop diversification is a process through which farmers diversify his farm activities from one crop to different value added crops so that he minimizes the existing risk in his farm operation. Most of the studies in literature in context to crop diversification have identified different factors that influence crop diversification in their study area. However, very few studies have attempted to examine the impact of institutional factors on crop diversification at macro level by using district level panel data in Assam. Therefore, this study makes an attempt to examine the impact of institutional factors on crop diversification through panel analysis. To fulfill the objective of this paper secondary data have been collected from different issues of Statistical Hand Book of Assam, assamstate.com, RBI, etc. The overall results of this paper show that institutional factors like farm size have positive impact on crop diversification except institutional credit. Institutional credit has negative impact on crop diversification. This paper will definitely help to bring some policy changes in the macro level to optimize crop diversification in the region.

scholarly journals Labour-use pattern on Swiss dairy farms

2013 ◽  
Vol 59 (No. 4) ◽  
pp. 149-159
Author(s):  
M. Lips ◽  
D. Schmid ◽  
P. Jan
Keyword(s):  
Spatial Data ◽  
Dairy Farms ◽  
Farm Size ◽  
Farm Income ◽  
Marginal Effect ◽  
Farm Work ◽  
Farm Family ◽  
Wage Labour ◽  
Use Pattern ◽  
On Farm

Abstract: Analysing the labour-use pattern on Swiss dairy farms, we apply a typology scheme with two criteria: on-farm wage labour and off-farm family labour. The resultant four farm types are analysed based on the data from the Swiss Farm Accountancy Data Network (FADN) as well as the spatial data on available jobs. Only 17% of dairy farms have neither on-farm wage labour nor off-farm family labour. 60 % have family members involved in off-farm activities. On average, 0.3 annual work units (AWU) are employed in off-farm activities, earning double the on-farm income per AWU. In line with the literature, we found that the likelihood of on-farm wage labour increases with the farm size and the degree of diversification. Involvement in off-farm activities is more likely if the farm manager is young and has a spouse with a non-agricultural education. Furthermore, private consumption per consumer unit has a positive marginal effect on the likelihood of off-farm work. Finally, no evidence was found of available jobs within a range of 10 kilometres acting as a proxy for the local labour demand for off-farm activities, leading us to the conclusion that involvement in off-farm work is an option for most of the analysed dairy farms.  

scholarly journals Comparative analysis of chickpea with boro rice in drought-prone areas of Bangladesh

2021 ◽  
Vol 10 (2) ◽  
pp. 21-28
Author(s):  
ST Siddique ◽  
M Kamruzzaman ◽  
SC Sharna
Keyword(s):  
Positive Impact ◽  
Farm Size ◽  
Farm Income ◽  
Cost Ratio ◽  
Probit Regression ◽  
Negative Effects ◽  
Benefit Cost Ratio ◽  
Human Labor ◽  
Benefit Cost ◽  
Boro Rice

The study is conveyed to compare the profitability of chickpea and boro rice in Rajshahi district, which is one of the most drought-prone areas of Bangladesh. In this study, a total of 180 farmers (90 chickpea growers and 90 boro rice growers) are used as sample respondents, and data were collected by using a structured questionnaire in 2019. A probit regression model is used to find out the determinants that affect the cultivation of chickpea and boro rice. The important finding of this study is that the Benefit-Cost Ratio for chickpea and boro rice production is 1.88 and 1.05, respectively. The results indicate that chickpea cultivation is more profitable than boro rice cultivation. Besides, the study reveals that occupation, farm size, and seed have a positive impact while family size, human labor, and irrigation have negative effects on farmer’s decision to cultivate chickpea cultivation rather than boro rice. It is, therefore, concluded that the farmers should be encouraged to grow more chickpea rather than boro rice as a means of increasing farm income through crop diversification program. Int. J. Agril. Res. Innov. Tech. 10(2): 21-28, December 2020

scholarly journals Adoption of Agricultural Marketing Technologies by Farmers of Northern Bangladesh: A Binary Logistic Analysis to Determine the Factors Influencing Farmers' Decision

2019 ◽  
Vol 6 (2) ◽  
pp. 169-178
Author(s):  
Md. Ziaul Haque
Keyword(s):  
Formal Education ◽  
Positive Impact ◽  
Economic Status ◽  
Binary Logistic Regression ◽  
Farm Size ◽  
Impact Factors ◽  
Farm Income ◽  
Binary Logistic Regression Model ◽  
Agricultural Marketing ◽  
Logistic Analysis

Low adoption of agricultural marketing technologies in the field of agricultural commodities marketing is one of the main reasons for profit loss of the farmers in Bangladesh. This paper examines the factors that influence farmers' decision of modern agricultural marketing technologies adoption in Northern Bangladesh. By using questionnaire survey the researcher collect data from 216 farmers in Dinajpur and Naogaon district in Northern Bangladesh and the binary logistic regression model was estimated to find out the factors influence farmers decision. Seven independent variables i.e. age of the farmer, formal education of the farmer, farm size, level of expected benefits, off-farm income generating activities, access to institutional credit and training about use of marketing technologies are statistically significant factors that influence the decision of farmers to adopt modern agricultural marketing technologies in Northern Bangladesh. So it is concluded that the farmers' decision to adopt modern agricultural marketing technologies depends on their socio-economic status and organizational effectiveness. We recommend that such policies should be made so that the positive impact factors on technologies adoption are properly utilized and negative issues are reduced.  

scholarly journals Measuring Technical Efficiency and Returns to Scale in Indian Agriculture Using Panel Data: A Case Study of West Bengal

2019 ◽  
Vol 6 (6) ◽  
pp. 1
Author(s):  
Debasis Mithiya ◽  
Simanti Bandyopadhyay ◽  
Kumarjit Mandal
Keyword(s):  
Maximum Likelihood ◽  
Panel Data ◽  
Technical Efficiency ◽  
West Bengal ◽  
Positive Impact ◽  
Returns To Scale ◽  
Maximum Likelihood Estimates ◽  
Farm Size ◽  
Stochastic Production Frontier ◽  
Truncated Normal

The study investigates farm level technical efficiency (TE) and its determinants in the state of West Bengal in India. A stochastic production frontier model has been applied for determining technical efficiency by using panel data on 17 agricultural production units over a period of 23 years. Maximum-likelihood estimates of the Cobb-Douglas stochastic frontier production function in a time-variant truncated normal distribution is appropriate for the measurement of technical efficiency of West Bengal agriculture in India. The estimated variance ratio indicates that 48.90 percent of the differences between the observed and the estimated output is caused by differences in farms’ technical inefficiencies. However, the remaining variation is due to factors beyond farmers’ control. The study shows that the agricultural farms in West Bengal exhibit increasing returns to scale in production. The study finds that farmers’ education and agricultural extension are important determinants of technical efficiency. Other prominent determinants that have a significant contribution are farm size, crop diversification, number of available agricultural markets, the proportion of small landholders and input intensity. All these determinants, excluding the proportion of small landholders, have a largely positive impact on technical efficiency. The maximum-likelihood estimation (MLE) and principal component analysis (PCA) are applied to determine the effects of determinants on TE. Both methods give similar results.

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