Since 2009 the US Department of Agriculture (USDA) has funded over 2600 local food initiatives. However, the economic impacts of these policies remain unclear largely due to data deficiencies that preclude the understanding of differential expenditure patterns of farms participating in these local market channels (both in terms of what inputs they require, and where the inputs are purchased—local or not). This paper utilizes two unique data sets from samples of producers in New York State (NYS) to build expenditure profiles for local food system participants. We employ USDA Agricultural Resource Management Survey data as a robustness check on our results. The primary contribution of this paper is to provide preliminary evidence that local food system participants in NYS have different expenditure patterns than farmers who do not sell through local food markets. We show that farmers with local food sales have higher reliance on local labor and other variable expenses as primary inputs than farms without local food sales, and that local food producers spend a higher percentage of total expenditure in the local economy. Based on our results, we recommend that future economic impact assessments utilize revised expenditure profiles that more accurately reflect inter-industry linkages of the local food sector.

Our study examines a stochastic R&D model with flexible termination time and without rivalry. Specifically, we assume a stochastic relationship between expenditures rate and the project's status. Furthermore, the termination time of the project is incorporated into the R&D model as a decision variable by allowing the controller to ‘sell' the obtained technology from the project at any point of time. The proposed framework extends the classical approach in the R&D literature.

The main purpose of our study is to determine the optimal stopping time of the project and to characterize qualitatively the firm's expenditure strategy. We show that under certain realistic conditions, the optimal stopping strategy is a control limit policy. Furthermore, the research effort increases monotonically over the development time of the project.