Performing Department
(N/A)
Non Technical Summary
Agricultural land in the United States is increasingly being converted to non-agricultural uses, jeopardizing the viability and competitiveness of small and medium-sized farms. When rural areas lose a critical mass of agricultural activity, individual producers suffer from land fragmentation, higher production costs, and fewer agricultural businesses to support their farm operation. Similarly, food processors and manufacturers are more likely to relocate to areas with more concentrated agricultural production. State-level farmland preservation policies--including planning, zoning, preservation agreements, and tax credits--seek to keep agricultural land in agricultural use. In this project, we will analyze the effectiveness and efficiency of Wisconsin's farmland preservation policies in (1) encouraging landowners to sign farmland preservation agreements, (2) preventing the conversion of agricultural land to other uses, and (3) supporting the local agribusiness sector. We will also analyze how these policies differentially affect farms of different sizes. Leveraging detailed geospatial data about farmland preservation plan areas, preservation zoning boundaries, agricultural enterprise areas, preservation agreements, and individual land parcels, we will analyze land use change using satellite imagery and analyze local economic conditions of the agribusiness sector using data from the Business Dynamics Research Consortium and U.S. Census. Additionally, we will assess how Wisconsin's farmland preservation tax credits affect preservation behavior, thereby estimating the public cost of future farmland preservation. By better understanding how government preservation policies affect the agricultural sector, policymakers will be better equipped to ensure the rural economy can support the sustainability and profitability of the next generation of small and medium-sized farmers.
Animal Health Component
50%
Research Effort Categories
Basic
25%
Applied
50%
Developmental
25%
Goals / Objectives
Our goal is to rigorously analyze multipleaspects of Wisconsin's farmland preservation program and determine how different policies causally affect farmland transition, farm size, and the local agricultural economy. Our specific objectives are to:build a geospatially linked panel dataset of annual farmland preservation policies, preservation agreements, land uses, farm sizes, and agricultural businesses in Wisconsin since 2010,estimate the supply curve for farmers to enter into a binding farmland preservation agreement,estimate the causal effects of establishing an Agricultural Enterprise Area (AEA) on land use, farmland transition, and farm size, andestimate the causal effects of establishing an Agricultural Enterprise Area (AEA) on thelocal agricultural economy and agribusiness sector.
Project Methods
In order to achieve Objectives 2, 3, and 4, we must first link a number of different geospatial datasets. Data on farmland preservation policies and farmland preservation agreements will be sourced from Wisconsin's Department of Agriculture, Trade and Consumer Protection (DATCP), data on land uses will be sourced from satellite data sources such as the Cropland Data Layer (CDL) or National Land Cover Database (NLCD), data on farm size must be constructed based on parcel-level data from the Wisconsin Statewide Parcel Map Initiative, and data on agricultural businesses may be gathered from several sources including the Business Research Data Consortium and the U.S. Census.To achieve Objective 2,we will analyze individual agricultural parcels near and within Wisconsin Agricultural Enterprise Areas (AEAs) both before and after those AEAs were instituted. We will then determine which parcels enter into a farmland preservation agreement and when. Finally, we will determine how far each parcel is from the nearest farmland preservation zoning district border. Having generated this information, we will use a parcel's distance from the zoning district border as an instrumental variable for the potential tax credit the landowner could claim. Since distance to this border is a smooth-running variable and the tax credit changes discontinuously at the border, this setup provides an ideal application of the "sharp" regression discontinuity method.To achieve Objective 3,we will employ another regression discontinuity (RD) approach to estimate local average treatment effects of AEAs on our outcomes of interest.Ultimately, we will use our RD approach to estimate the causal impact of AEAs on outcomes such as land use, farmland transition, and farm size. Additionally, we will be able to conduct heterogeneity analyses where we explore whether the effects of AEAs on farmland transition are stronger or weaker for land in small and medium-sized farms compared to land in large farms.To achieve Objective 4, wewill first estimate the correlation between whether a county or other geographic area has an AEA, and the change in the number, revenue, and employment of ag-linked businesses in that area. While this correlation is suggestive, we are also interested in the causal impact of an AEA on local agribusiness. Weplan to use the instrumental variables estimator where we instrument for whether an area has an AEA.For this analysis, we plan to use detailed establishment data from the Business Dynamics Research Consortium (BRDC).We will also perform a similar analysis using County Business Patterns data from the U.S. Census.