Conservation Reserve Program Participation and Acreage Enrollment of Working Farms

Among Conservation Reserve Program (CRP) participants, there is a distinction between farm households using the program to ease out of farming and those using the program to augment production receipts. We find evidence that factors other than farm profitability and environmental factors may influence program participation of farmers who continue agricultural production. Program payments and farm size positively correlate with the amount of land enrolled in the CRP, and characteristics of participants in land retirement and working-lands CRP components are similar.Environmental Economics and Policy,

Short-run Birth and Death of U.S. Manufacturing Firms: 2000 - 2005

Attracting manufacturing investment remains a viable regional development policy. Previous research in the location literature has informed policymakers which factors are most important for attracting new firm investment. Far less is known about the dynamics of firm death and the possible interaction with firm birth. A conceptual model of county-level investment in the U.S. manufacturing sector is developed from location theory and subsequent literature. Specifically, we test the relative importance of location factors influencing firm investment, and if these factors influence firm birth and death differently. Local factors include labor quality, availability, and cost, market conditions, agglomeration due to localization and urbanization economies, infrastructure, and fiscal policy. This study covers the time period 2000 to 2004 for U.S. counties in the lower 48 states. Firm data are from the U.S. Census Bureau’s Dynamic Firm Data Series, which links establishments across space and time. Regional adjustment models are used to show how ceteris paribus changes in location factors affect the birth and death rates in a county.location factors, manufacturing, creative destruction, Community/Rural/Urban Development, L60, R11, R12,

ANALYSIS OF GOVERNMENT FARM SUBSIDIES ON FARMLAND CASH RENTAL RATES USING A FIXED EFFECT SPATIAL DISTRIBUTED LAG MODEL AND A TRANSLOG COST MODEL

The objective of this study is to examine how factors such as government payments, soil productivity ratings, commodity selling price, corn and soybean production, and spatial attributes affect cash rental rates. Baseline estimates of the effects of government payments on cash rents are determined using a fixed effect, distributed lag model. The results of this model are compared to a distributed lag model that incorporates spatial effects. A second model estimates the impact of government subsides on farm cost structure. This is accomplished estimating a fixed effect, translog cost function that also incorporates spatial effects. The data used in the analysis is the Illinois Farm Business Farm Management (FBFM) Economic Management Analysis (EMA), containing more than five thousand Illinois FBFM clients annually from 1996 to 2001.Farm Management,

Regionalism in World Agricultural Trade: Lessons from Gravity Model Estimation

Relative to trade in non-agricultural goods, progress in achieving agricultural trade liberalization under the GATT/WTO has been slow. Agricultural trade is characterized by persistently high levels of protection on a scale that is uncommon in non-agricultural trade. Article XXIV of the GATT, 1994 permits a group of countries to form a trade union whereby trade barriers are reduced or removed on all sectors of trade. Within regional trade agreements however, agricultural trade often receives special treatment, and in some cases, agriculture is completely exempt. Typically, debates over the effects of regional trade agreements have focused on welfare. In this study we seek to answer a more fundamental question of what effect these agreements have had on agricultural trade.International Relations/Trade,

Exploring Farm Business and Household Expenditure Patterns and Community Linkages

Farm operators are an integral part of some rural economies. The businesses they operate often hire seasonal and full-time employees and purchase goods and services from local farm implement dealers, input suppliers, and financial institutions. Farm household spending on food, furniture and appliances, trucks and automobiles, and a range of consumer goods also support local jobs and retail businesses in some communities. Based on the 2002 agricultural census and the 2004 Agricultural Resource Management Survey, this paper explores the linkages between farm household/ business expenditures and local communities.Farm business expenditures, farm household spending, employment, community linkage, Consumer/Household Economics, Farm Management, Community/Rural/Urban Development,

Structural Conservation Practices in U.S. Corn Production: Evidence on Environmental Stewardship by Program Participants and Non-Participants

This study used the 2005 ERS CEAP-ARMS data for corn production to first compare key operator, field, farm, economic, and environmental characteristics of conservation program participants with non-participants, by farm-size class. We then estimate a cost-function based technology adoption model of producer decisions regarding the allocation of field-level acres between corn production and infield and perimeter-field conservation structures to examine how these conservation choices differ between program participants and non-participants, while accounting for differences in other field, farm, and environmental factors. Our null hypothesis is that the average conservation structural practice acres across U.S. corn acres supplied by growers participating in a conservation program are not different from non-participants. Infield conservation structures include terraces, grassed waterways, vegetative buffers, contour buffers, filter strips, and grade stabilization structures. Perimeter-field conservation structures include hedgerow plantings, stream-side forest and herbaceous buffers, windbreaks and herbaceous wind barriers, field borders, and critical area plantings. Because the dependent variable in this analysis is continuous, we use a Generalized Estimating Equations (GEE) procedure to estimate two models. The GEE estimation procedure (Liang and Zeger, 1986) accounts for correlation between adoption decisions measured as a continuous variable while maintaining the theoretical integrity of a multinomial discrete-choice model typically used in technology adoption studies. The cost-function models estimate field-level, producer acreage allocation decisions for corn, first, as a function of normalized production input costs (prices) and structural technology class and installation time-period attributes (Model 1), and second, as a function of Model 1 variables plus socio-environmental variables reflecting the potential influence of a variety of field, farm, and environmental characteristics (Model 2). Evidence indicates significant characteristic differences exist between conservation program participants and non-participants across U.S. corn production, that non-program factors do heavily influence producer conservation practice decisions, and that farm-size matters. In addition, results suggest that program non-participants tend to adopt infield conservation structures much more intensively while program participants emphasize the adoption of perimeter-field conservation structures. Finally, these results seem to suggest that because perimeter-field structural practices can involve differential productivity/cost effects and off-site benefits, program incentives may need to play a greater role in encouraging their adoption than they do for infield structural practices.Crop Production/Industries, Environmental Economics and Policy,

SPATIAL REGRESSION MODELS FOR YIELD MONITOR DATA: A CASE STUDY FROM ARGENTINA

Precision agricultural technology promises to move crop production closer to a manufacturing paradigm, but analysis of yield monitor, sensor and other spatial data has proven difficult because correlation among neighboring observations often violates the assumptions of classical statistical analysis. When spatial structure is ignored variance estimates tend to be inflated and significance levels of test statistics are reduced. The gap between data analysis and site-specific recommendations has been identified as one of the key constraints on widespread adoption of precision agriculture technology. This paper compares four approaches that explicitly incorporate spatial correlation into regression models: (1) a spatial econometric approach; (2) a polynomial trend regression approach; (3) a classical nearest neighbor analysis; and (4) and a geostatistic approach. In the Argentine data studied, the spatial econometric, geostatistical approach and spatial trend analysis offered stronger statistical evidence of spatial heterogeniety of nitrogen response than the ordinary least squares or nearest neighbor analysis. All the spatial models led to the same economic conclusion, which is that variable rate nitrogen is potentially profitable. The spatial econometric analysis can be implemented on relatively small data sets that do not have enough observations for estimation of the semivariogram required by geostatistics. The spatial trend analysis can be implemented with ordinary least squares functions that are already available in some GIS software. In this study, the main benefit of using spatial regression analysis is increased confidence in the corn yield response estimates by management zone, and conclusions about the profitability of precision agriculture technologies.Crop Production/Industries,

U.S. Corn Producer’s Response to Increased Energy Prices: Evidence from Producer Surveys in 2001 and 2005

Crop Production/Industries, Risk and Uncertainty,

BANDWIDTH SELECTION FOR SPATIAL HAC AND OTHER ROBUST COVARIANCE ESTIMATORS

This research note documents estimation procedures and results for an empirical investigation of the performance of the recently developed spatial, heteroskedasticity and autocorrelation consistent (HAC) covariance estimator calibrated with different kernel bandwidths. The empirical example is concerned with a hedonic price model for residential property values. The first bandwidth approach varies an a priori determined plug-in bandwidth criterion. The second method is a data driven cross-validation approach to determine the optimal neighborhood. The third approach uses a robust semivariogram to determine the range over which residuals are spatially correlated. Inference becomes more conservative as the plug-in bandwidth is increased. The data-driven approaches prove valuable because they are capable of identifying the optimal spatial range, which can subsequently be used to inform the choice of an appropriate bandwidth value. In our empirical example, pertaining to a standard spatial model and ditto dataset, the results of the data driven procedures can only be reconciled with relatively high plug-in values (n0.65 or n0.75). The results for the semivariogram and the cross-validation approaches are very similar which, given its computational simplicity, gives the semivariogram approach an edge over the more flexible cross-validation approach.spatial HAC, semivariogram, bandwidth, hedonic model

A TWO-STEP ESTIMATOR FOR A SPATIAL LAG MODEL OF COUNTS: THEORY, SMALL SAMPLE PERFORMANCE AND AN APPLICATION

Several spatial econometric approaches are available to model spatially correlated disturbances in count models, but there are at present no structurally consistent count models incorporating spatial lag autocorrelation. A two-step, limited information maximum likelihood estimator is proposed to fill this gap. The estimator is developed assuming a Poisson distribution, but can be extended to other count distributions. The small sample properties of the estimator are evaluated with Monte Carlo experiments. Simulation results suggest that the spatial lag count estimator achieves gains in terms of bias over the aspatial version as spatial lag autocorrelation and sample size increase. An empirical example deals with the location choice of single-unit start-up firms in the manufacturing industry in the US between 2000 and 2004. The empirical results suggest that in the dynamic process of firm formation, counties dominated by firms exhibiting (internal) increasing returns to scale are at a relative disadvantage even if localization economies are presentcount model, location choice, manufacturing, Poisson, spatial econometrics