Black Farm Operators and Farm Population, 1900-1970: Alabama and Kentucky

1979 ◽  
Vol 40 (4) ◽  
pp. 387 ◽  
Author(s):  
A. Lee Coleman ◽  
Larry D. Hall
2008 ◽  
Vol 35 (2) ◽  
pp. 71-100 ◽  
Author(s):  
Douglas K. Barney ◽  
Tonya K. Flesher

Farmers have benefited from unique tax treatment since the beginning of the income tax law. This paper explores agricultural influences on the passage of the income tax in 1913, using both qualitative and quantitative analysis. The results show that agricultural interests were influential in the development and passage of tax/tariff laws. The percentage of congressmen with agricultural ties explains the strong affection for agriculture. Discussion in congressional debates and in agricultural journals was passionate and patriotic in support of equity for farmers. The quantitative analysis reveals that the percentage farm population was a significant predictor of passage of the 16th Amendment by the states and of adoption of state income taxes in the 20th century.


1938 ◽  
Vol 16 (3) ◽  
pp. 233
Author(s):  
Carl C. Taylor ◽  
Conrad Taeuber

2013 ◽  
Vol 19 (1) ◽  
pp. 77-103 ◽  
Author(s):  
Majda Černič Istenič ◽  
Duška Knežević Hočevar

Abstract The ageing in farm population in Slovenia is accompanied by a diminishing interest of the younger generation in farming. Hence, measures for early retirement of farmers and assistance to young farmers were introduced in 2004 and 2005. Some results of two ensuing studies are presented here: the survey Generations and Gender Relations on Slovenian Farms (2007) and ethnographic study on intergenerational solidarity (2009). The survey findings reveal that through intergenerational assistance farm population, especially the beneficiaries of both measures, shows specific characteristics compared to other observed groups (nonfarmers): stronger reliance on their own family resources and weaker dependence on state resources. The survey findings are further upgraded by the ethnographic results, explaining more in-depth from a life-course perspective the complex dynamics and background of intergenerational assistance on family farms.


2013 ◽  
Author(s):  
Madhur A. Khadabadi ◽  
Karen B. Marais

Wind turbine maintenance is emerging as an unexpectedly high component of turbine operating cost and there is an increasing interest in managing this cost. Here, we present an alternative view of maintenance as a value-driver, and develop an optimization algorithm to maximize the value delivered by maintenance. We model the stochastic deterioration of the turbine in two dimensions: the deterioration rate, and the extent of deterioration, and view maintenance as an operator that moves the turbine to an improved state in which it can generate more power and so earn more revenue. We then use a standard net present value (NPV) approach to calculate the value of the turbine by deducting the costs incurred in the installation, operations and maintenance from the revenue due to the power generation. The application of our model is demonstrated using several scenarios with a focus on blade deterioration. We evaluate the value delivered by implementing blade condition monitoring systems (CMS). A higher fidelity CMS allows the blade state to be determined with higher precision. With this improved state information, an optimal maintenance strategy can be derived. The difference between the value of the turbine with and without CMS can be interpreted as the value of the CMS. The results indicate that a higher fidelity (and more expensive) condition monitoring system (CMS) does not necessarily yield the highest value, and, that there is an optimal level of fidelity that results in maximum value. The contributions of this work are twofold. First, it is a practical approach to wind turbine valuation and operation that takes operating and market conditions into account. This work should therefore be useful to wind farm operators and investors. Second, it shows how the value of a CMS can be explicitly assessed. This work should therefore be useful to CMS manufacturers and wind farm operators.


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