<p> This study examines 43 farms in Seneca Township, and considers a number of social and economic factors which may influence farm management and levels of farm performance. </p> <p> A model of the farm manager is formulated to serve as a basic research directive. Data are obtained by means of farm interviews. Multiple regression analysis is used to estimate a standard production function, and to group farmers into performance categories, on the basis of production function residuals. Farmers of each performance group are compared in terms of relevant biographical characteristics, attitudes, farm decisions, and pertinent farm practices. </p> <p> It is concluded that major variations in farm performance can be explained in terms of differences among farmers in personal and family aspirations, differences in past and present economic opportunities, and differences in the extent to which farm adjustment and equilibrium levels of production have been achieved. </p> <p> Little evidence was found of important differences in managerial competence among full-time farmers. </p> <p> Location with respect to soil type, and associated differences in cost-return ratios appear to have some bearing upon the investment behaviour of farmers. This question however, warrants further investigation. </p> / Thesis / Master of Arts (MA)

Recent hurricanes have made it clear that housing is the single greatest component of all losses in terms of economic value and buildings damaged. Housing damage resulting from floods has increased in the United States, despite local, state and federal encouragement to mitigate flood hazards and regulate development in flood-prone areas (Atreya, 2013). The two primary causes of these increased costs are: (1) a rise in the occurrence and strength of the extreme weather events, and (2) increased development and value of property in physically vulnerable areas. The overlap of the above two factors resulted in tremendous losses of property in Staten Island and other coastal communities along the Atlantic Coast. Hurricane Sandy was a reminder of how vulnerable such areas could be. After hurricane Sandy, damaged properties experienced higher than usual housing sales and changed property values. This research, seeks to improve the current state of knowledge about housing market following a major disaster through examining single-family housing sales and prices in Staten Island, New York. The housing price recovery rate was much slower for the properties that sustained damage, and the impacts lasted for at least four years after the storm. Researchers studying housing recovery have utilized a variety of indicators like financial characteristics, government policies, social parameters, damage, housing characteristics, etc. to capture the dimensions of recovery. In Sandy's case damage was the major influencing parameter, and it completely changed the housing dynamics of the affected coastal regions. Housing market, in terms of damage, restoration, and recovery, is a fundamental indicator of disaster resilience. Every community is different and so are the effects of disasters on residential markets. This study clearly highlights this point and underscores the importance of using contextual methods and data sets in conducting the research. / Master of Urban and Regional Planning / Recent hurricanes have made it clear that housing is the single greatest component of all losses in terms of economic value and buildings damaged. Housing damage resulting from floods has increased in the United States, despite local, state and federal encouragement to mitigate flood hazards and regulate development in flood-prone areas (Atreya, 2013). The two primary causes of these increased costs are: (1) a rise in the occurrence and strength of the extreme weather events, and (2) increased development and value of property in physically vulnerable areas. The overlap of the above two factors resulted in tremendous losses of property in Staten Island and other coastal communities along the Atlantic Coast. Hurricane Sandy was a reminder of how vulnerable such areas could be. After hurricane Sandy, damaged properties experienced higher than usual housing sales and changed property values. This research, seeks to improve the current state of knowledge about housing market following a major disaster through examining single-family housing sales and prices in Staten Island, New York. The housing price recovery rate was much slower for the properties that sustained damage, and the impacts lasted for at least four years after the storm. Researchers studying housing recovery have utilized a variety of indicators like financial characteristics, government policies, social parameters, damage, housing characteristics, etc. to capture the dimensions of recovery. In Sandy’s case damage was the major influencing parameter, and it completely changed the housing dynamics of the affected coastal regions. Housing market, in terms of damage, restoration, and recovery, is a fundamental indicator of disaster resilience. Every community is different and so are the effects of disasters on residential markets. This study clearly highlights this point and underscores the importance of using contextual methods and datasets in conducting the research.