The impact of ethanol plants on cropland values in the great plains
Identifieur interne : 001307 ( Istex/Corpus ); précédent : 001306; suivant : 001308The impact of ethanol plants on cropland values in the great plains
Auteurs : Jason Henderson ; Brent A. GloySource :
- Agricultural Finance Review [ 0002-1466 ] ; 2009-05-08.
Abstract
Purpose Corn ethanol plants consume large amounts of corn and their location has the potential to alter local crop prices and surrounding agricultural land values. The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values. Designmethodologyapproach The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the Agricultural Credit Survey administered by the Federal Reserve Bank of Kansas City. Findings The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location. Originalityvalue The paper finds that land markets appear to be rationally adjusting to the location of ethanol plants.
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DOI: 10.1108/00021460910960453
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Gloy</name><affiliation><mods:affiliation>Department of Applied Economics and Management, Cornell University, Ithaca, New York, USA</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Agricultural Finance Review</title><idno type="ISSN">0002-1466</idno><imprint><publisher>Emerald Group Publishing Limited</publisher><date type="published" when="2009-05-08">2009-05-08</date><biblScope unit="volume">69</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="36">36</biblScope><biblScope unit="page" to="48">48</biblScope></imprint><idno type="ISSN">0002-1466</idno></series><idno type="istex">97FCF45B11F58B6E5188FEC871096992797BCE33</idno><idno type="DOI">10.1108/00021460910960453</idno><idno type="filenameID">4210690104</idno><idno type="original-pdf">4210690104.pdf</idno><idno type="href">00021460910960453.pdf</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0002-1466</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Purpose Corn ethanol plants consume large amounts of corn and their location has the potential to alter local crop prices and surrounding agricultural land values. The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values. Designmethodologyapproach The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the Agricultural Credit Survey administered by the Federal Reserve Bank of Kansas City. Findings The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location. Originalityvalue The paper finds that land markets appear to be rationally adjusting to the location of ethanol plants.</div></front></TEI><istex><corpusName>emerald</corpusName><author><json:item><name>Jason Henderson</name><affiliations><json:string>Federal Reserve Bank of Kansas City Omaha Branch, Omaha, Nebraska, USA</json:string></affiliations></json:item><json:item><name>Brent A. 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The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values. Designmethodologyapproach The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the Agricultural Credit Survey administered by the Federal Reserve Bank of Kansas City. Findings The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location. 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The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values. Designmethodologyapproach The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the Agricultural Credit Survey administered by the Federal Reserve Bank of Kansas City. Findings The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location. 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Do Not Edit! --><article dtd-version="1.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">afr</journal-id><journal-id journal-id-type="doi">10.1108/afr</journal-id><journal-title-group><journal-title>Agricultural Finance Review</journal-title></journal-title-group><issn pub-type="ppub">0002-1466</issn><publisher><publisher-name>Emerald Group Publishing Limited</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.1108/00021460910960453</article-id><article-id pub-id-type="original-pdf">4210690104.pdf</article-id><article-id pub-id-type="filename">4210690104</article-id><article-categories><subj-group subj-group-type="type-of-publication"><compound-subject><compound-subject-part content-type="code">research-article</compound-subject-part><compound-subject-part content-type="label">Research paper</compound-subject-part></compound-subject></subj-group><subj-group subj-group-type="subject"><compound-subject><compound-subject-part content-type="code">cat-ECO</compound-subject-part><compound-subject-part content-type="label">Economics</compound-subject-part></compound-subject><subj-group><compound-subject><compound-subject-part content-type="code">cat-AFP</compound-subject-part><compound-subject-part content-type="label">Agricultural/environmental economics</compound-subject-part></compound-subject></subj-group></subj-group></article-categories><title-group><article-title>The impact of ethanol plants on cropland values in the great plains</article-title></title-group><contrib-group><contrib contrib-type="author"><string-name><given-names>Jason</given-names> <surname>Henderson</surname></string-name><aff>Federal Reserve Bank of Kansas City – Omaha Branch, Omaha, Nebraska, USA</aff></contrib><x></x><contrib contrib-type="author"><string-name><given-names>Brent A.</given-names> <surname>Gloy</surname></string-name><aff>Department of Applied Economics and Management, Cornell University, Ithaca, New York, USA</aff></contrib></contrib-group><pub-date pub-type="ppub"><day>08</day><month>05</month><year>2009</year></pub-date><volume>69</volume><issue>1</issue><fpage>36</fpage><lpage>48</lpage><permissions><copyright-statement>© Emerald Group Publishing Limited</copyright-statement><copyright-year>2009</copyright-year><license license-type="publisher"><license-p></license-p></license></permissions><self-uri content-type="pdf" xlink:href="00021460910960453.pdf"></self-uri><abstract><sec><title content-type="abstract-heading">Purpose</title><x> – </x><p>Corn ethanol plants consume large amounts of corn and their location has the potential to alter local crop prices and surrounding agricultural land values. The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values.</p></sec><sec><title content-type="abstract-heading">Design/methodology/approach</title><x> – </x><p>The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the <italic>Agricultural Credit Survey</italic> administered by the Federal Reserve Bank of Kansas City.</p></sec><sec><title content-type="abstract-heading">Findings</title><x> – </x><p>The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location.</p></sec><sec><title content-type="abstract-heading">Originality/value</title><x> – </x><p>The paper finds that land markets appear to be rationally adjusting to the location of ethanol plants.</p></sec></abstract><kwd-group><kwd>United States of America</kwd><x>, </x><kwd>Fuels</kwd><x>, </x><kwd>Farms</kwd><x>, </x><kwd>Crops</kwd><x>, </x><kwd>Property finance</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>peer-reviewed</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>academic-content</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>rightslink</meta-name><meta-value>included</meta-value></custom-meta></custom-meta-group></article-meta><ack><p>The views expressed are those of the author and do not necessarily reflect the positions of the Federal Reserve Bank of Kansas City or the Federal Reserve System.</p></ack></front><body><sec><title>The impact of ethanol plants on cropland values in the great plains</title><p>In 2006, ethanol production emerged as a dominating influence on the US farm economy. Changes in US energy policy in 2005 bolstered the demand for ethanol. In 2006, the surge in crude oil and gasoline prices boosted ethanol profits. The result was a perfect storm for the farm community, where ethanol and bio‐fuel production fueled sharp gains in corn prices that spilled over into other agricultural commodities. As expectations of sustainable, high crop prices began to firm, so did expectations of higher economic returns to cropping and farmland values.</p><p>Farmland is a capital or long‐term asset and its value is derived from the discounted value of future earnings that it is expected to produce. Ethanol production can increase farmland values by increasing the demand for agricultural crops and the expected returns to cropping. Given the recent increases in farmland values, there is evidence that the rise in corn prices and the prices of other agricultural crops has been capitalized into farmland values across the country.</p><p>Ethanol production, however, should also be expected to have a spatial impact on land value gains. Ethanol is produced in large plants that create relatively large local demand for corn. Economic theory would suggest that the presence of a large local demand such as an ethanol plant should impact local basis patterns (<xref ref-type="bibr" rid="b21">McNew and Griffith, 2005</xref>). Decreases in the basis would increase the returns to crop production in the area around the plant. As such, ethanol plant locations might have local impacts on farmland values. To the extent that ethanol production alters basis patterns, one would expect that it would lead to stronger land value gains near ethanol plants.</p><p>The impact of ethanol plant locations on local farmland values is critically dependent upon farmers' expectations regarding the size and lasting impact of basis changes. However, because the industry is still in its infancy, it is difficult to form expectations regarding basis changes. It is important to understand whether ethanol plant locations have an impact on local farmland values and whether the changes in land values are consistent with reasonable expectations. It is possible that the large increases in land values in ethanol production regions are not consistent with reasonable expectations of basis changes. If this is the case, then attention should be called to the exuberance in land value gains in order to avert or forestall future contractions in land values. Alternatively, if these spillover impacts in the land market are substantial, this could provide a substantial wealth effect for local communities with ethanol plants.</p><p>Farmland is by far the largest asset on the farm balance sheet, accounting for roughly 86 percent of farm assets in 2007[1]. As a result, understanding changes in farmland values is critical to understanding the behavior of farmers and the financial performance of the agricultural sector. Although a number of studies have examined the economic impacts of ethanol production, few have explicitly examined how ethanol production has impacted land values.</p><p>This paper analyzes the local economic impact of ethanol plant locations on farmland values. Specifically, we examine the relationship between land price changes and the presence of ethanol production. In addition to estimating the economic impact of ethanol plants on farmland values, the paper estimates the impacts across geographic space. In other words, how far do the economic impacts of ethanol plants reach? The paper will examine the magnitude of the influence as well as the distance over which the impact can be observed. Lastly, the size of the impact on land values is examined in relationship to transportation costs and the implied basis changes associated with an ethanol plant. The results indicate that basis changes implied from the land values are equal to or less than the transportation costs observed from existing literature examining basis changes and ethanol plant location.</p></sec><sec><title>Literature review</title><p>A farmland value model is needed to analyze the relationship between ethanol plant locations and farmland values. The traditional capitalization model (1) is perhaps the most straight‐forward model for calculating the value of farmland. <xref ref-type="fig" rid="F_4210690104006">(Equation 1)</xref></p><p>In this formulation, the value of farmland at time <italic>t</italic> is defined by today's expectations (<italic>E</italic><sub><italic>t</italic></sub>) over the future returns to farmland, <italic>r</italic>, and the discount rate &dgr;.</p><p>In the context of this paper, the parameters of interest are those that impact farmers' expectations of the returns to farmland, namely, the impact of higher commodity prices and changes in local basis levels. To the extent that higher commodity prices are experienced by all farmers, these impacts should be felt equally across the entire farm sector. However, the impacts of ethanol production on local basis patterns would be expected to vary with the proximity to an ethanol plant. If farmers believe that price changes associated with tighter local basis levels are permanent, land values should increase accordingly. This fact allows us to relate the relative magnitude of land price changes associated with ethanol production to the implied basis changes. These implied basis changes are then compared to those available in the existing literature.</p><p>The rise in ethanol production has stimulated a host of economic studies on the ethanol industry. Among other things, some of these studies examined issues related to the economic feasibility of producing ethanol (<xref ref-type="bibr" rid="b9">Eidman, 2007</xref>; <xref ref-type="bibr" rid="b14">Gallagher 2006</xref>; <xref ref-type="bibr" rid="b12">Gallagher <italic>et al.</italic>, 2007</xref>) and the economic impacts of ethanol production (<xref ref-type="bibr" rid="b24">Parcell and Westhoff, 2006</xref>; <xref ref-type="bibr" rid="b33">Swenson, 2007</xref>). More relevant to the determination of land values is the impact of ethanol production on local commodity prices. At this point there appear to be two studies that are directly relevant to how ethanol production would impact land values near an ethanol plant.</p><p><xref ref-type="bibr" rid="b21">McNew and Griffith (2005)</xref> examined how the establishment of an ethanol plant impacts local basis patterns. In their analysis of basis patterns associated with the opening of 12 ethanol plants over the period of 2000 to 2003, they found that, on average, basis values increased 5.9 cents per bushel over the 150 square mile region around a plant. However, they also noted that the price increase tended to be greater at the location of the plant. In this case, the average impact was a $0.125 per bushel higher price, with a range of $0.046 to $0.193 per bushel. Given the magnitude of these price changes, one might expect that the local impact on land values would be substantial. For instance, using the valuation model in (1) and assuming a 4 percent discount rate, a national corn yield of 150 bushels per acre, and a permanent $0.125 per bushel price increase, the value of land near an ethanol plant could be expected to increase by $468.75 per acre[2].</p><p><xref ref-type="bibr" rid="b13">Gallagher <italic>et al.</italic> (2005)</xref> also examined the impact of ethanol plants on basis levels in Iowa during 2003. Their analysis considered how prices offered by ethanol plants were influenced by local surpluses of grain and the presence of export demand. They found that some ethanol plants in Iowa showed increased basis levels that were in relationship to truck transportation costs to the plant. However, in other cases they found no change in basis levels associated with the plants. They attribute these differences to the modes of transport available at the demand center, specifically whether the demand center is near a terminal market.</p><p>The findings of these studies would seem to indicate that one should expect some basis changes near ethanol plants. As a result, one would expect to find that ethanol plant locations would have some impact on land values. However, both studies point out that the magnitude of basis changes can be quite variable and dependent upon a variety of factors including proximity to terminal market points. At this point it is an open empirical question as to the extent to which an ethanol plant would impact land values. However, given the importance of land values to the financial health and soundness of the farm sector, the question is of great importance. We are currently unaware of any studies which have explicitly examined the impact of ethanol plant location on land values.</p></sec><sec><title>Empirical model and results</title><p>Economists have used econometric models to analyze various market characteristics influencing farmland values. These models typically relate variation in a number of characteristics to the price of farmland. In general, studies have identified a variety of factors that consistently impact the value of farmland. These factors include the agricultural productivity of farmland, the presence of urban influences, and recreation and amenity factors. In order to estimate the impact of ethanol production on land values, it is important to control for these factors. The next section describes some of the characteristics that have frequently been found to impact land values. It should also be noted that farmers are assumed to be price takers. Thus, the overall impact of ethanol production on land values that results from increased commodity prices is assumed to impact all agricultural lands.</p><p>Empirical research confirms that farmland values are based on the productivity and the resulting economic returns from agricultural production. A large number of studies have analyzed the capitalization of agricultural income streams into farmland values (<xref ref-type="bibr" rid="b1">Barnard <italic>et al.</italic>, 1997</xref>; <xref ref-type="bibr" rid="b3">Burt, 1986</xref>; <xref ref-type="bibr" rid="b4">Castle and Hoch, 1982</xref>; <xref ref-type="bibr" rid="b5">Chavas and Shumway, 1982</xref>; <xref ref-type="bibr" rid="b10">Featherstone and Baker, 1987</xref>; <xref ref-type="bibr" rid="b16">Herriges <italic>et al.</italic>, 1992</xref>; <xref ref-type="bibr" rid="b19">Just and Miranowski, 1993</xref>; <xref ref-type="bibr" rid="b23">Moss, 1997</xref>; <xref ref-type="bibr" rid="b22">Miranowski and Hammes, 1984</xref>; <xref ref-type="bibr" rid="b25">Phipps, 1984</xref>; <xref ref-type="bibr" rid="b34">Weersink <italic>et al.</italic>, 1999</xref>). Several of these studies have analyzed the economic impact of agricultural income streams derived from the market and from government payments.</p><p>Various studies have found that urbanization factors influence farmland values (<xref ref-type="bibr" rid="b6">Chicoine, 1981</xref>; <xref ref-type="bibr" rid="b7">Clonts, 1970</xref>; <xref ref-type="bibr" rid="b8">Dunford <italic>et al.</italic>, 1985</xref>; <xref ref-type="bibr" rid="b11">Folland and Hough, 1991</xref>; <xref ref-type="bibr" rid="b28">Reynolds and Tower, 1978</xref>; <xref ref-type="bibr" rid="b31">Shi <italic>et al.</italic>, 1997</xref>; <xref ref-type="bibr" rid="b32">Shonkwiler and Reynolds, 1986</xref>; <xref ref-type="bibr" rid="b20">Livanis <italic>et al.</italic>, 2006</xref>). These studies used cross‐sectional data to analyze the spatial variation in farmland values. In general, they found that the potential for urban development was being capitalized into farmland values as regions closer to large and growing urban centers experienced higher land values.</p><p>Recreation and amenity characteristics have been found to influence property values, primarily residential property, with a few studies analyzing the impact of amenities on farmland values. For instance, residential property values in Maryland were found to be higher in areas with more open space (<xref ref-type="bibr" rid="b18">Irwin and Bockstael, 2001</xref>; <xref ref-type="bibr" rid="b17">Irwin, 2002</xref>). Using data on Texas and Wyoming land values, other studies have found land values to be higher in areas with scenic views and more plentiful wildlife amenities (<xref ref-type="bibr" rid="b27">Pope <italic>et al.</italic>, 1984</xref>; <xref ref-type="bibr" rid="b26">Pope, 1985</xref>; <xref ref-type="bibr" rid="b2">Bastian <italic>et al.</italic>, 2002</xref>; <xref ref-type="bibr" rid="b15">Henderson and Moore, 2006</xref>).</p><p>The empirical model represented by the following equation is used to analyze farmland values: <xref ref-type="fig" rid="F_4210690104007">(Equation 2)</xref> where LV is land value, <bold><italic>A</italic></bold> is a vector of agricultural characteristics, <bold><italic>U</italic></bold> is a vector of urbanization measures, <bold><italic>R</italic></bold> is a vector of recreation or amenity characteristics, and <bold><italic>E</italic></bold> is a vector of characteristics associated with ethanol plant location. Because ethanol plants tend to locate in areas of high corn production it is possible that spatial autocorrelation models such as those described by <xref ref-type="bibr" rid="b30">Sarmiento and Wilson (2005)</xref> could potentially improve the results. However, ordinary least squares (OLS) models that included measures of corn production did not significantly improve upon the results presented here.</p><sec><title>Farmland values</title><p>Farmland values were measured by non‐irrigated cropland values obtained from the quarterly <italic>Agricultural Credit Survey</italic> from the Federal Reserve Bank of Kansas City. The Federal Reserve Bank of Kansas City covers the states of Nebraska, Kansas, Oklahoma, Colorado, Wyoming, western Missouri, and northern New Mexico. In the second quarter of 2007, 360 lenders at agricultural banks were surveyed. Of these, 254 respondents provided an estimate of non‐irrigated farmland values in their market area. When combined with the other variables required for the study, the final sample included 199 usable responses. The responses do not cover every county of the seven state region of the Federal Reserve Bank of Kansas City.</p><p>One drawback of the agricultural credit data is that it is obtained from an opinion survey. However, the prominent role bankers have in financing agricultural land sales in their region and the use of farmland as collateral in agricultural operating loans provides them with a unique and highly knowledgeable perspective on farmland values and is expected to mitigate some of the challenges to using an opinion survey. In fact, survey results are quite consistent with results found in other farmland value surveys. For example, non‐irrigated cropland values for the state of Nebraska are quite consistent with United States Department of Agriculture (USDA) estimates and estimates reported by the University of Nebraska‐Lincoln (<xref ref-type="fig" rid="F_4210690104001">Figure 1</xref>).</p><p>The survey covers a region with a large ethanol industry. According to the Renewable Fuels Association (RFA) and the American Coalition for Ethanol (ACE), in April 2007, the Kansas City Federal Reserve District contained 30 ethanol plant locations with a capacity of roughly 1.1 billion gallons per year, or approximately 18 percent of the national production capacity (<xref ref-type="fig" rid="F_4210690104002">Figure 2</xref>).</p><p>The district, however, has substantial spatial variation in ethanol plant locations. For example, 13 ethanol plants were in operation in Nebraska with an annual production capacity of approximately 583 million gallons of ethanol per year with 976 million gallons of ethanol production capacity under construction at and additional 13 sites. In contrast, Oklahoma had no ethanol plants in operation or under construction. Visual inspection of land value gains and ethanol plant locations suggests that land value gains were stronger in locations closer to ethanol plants. For example, non‐irrigated cropland values in Nebraska rose 17.4 percent annually in the first quarter of 2007, while non‐irrigated cropland values in Oklahoma rose a more modest 5.7 percent annually.</p></sec><sec><title>Agricultural production factors</title><p>Various county level measures are used to describe the characteristics of local cropland markets that are expected to influence non‐irrigated cropland values. Land values are expected to be higher in locations with higher farm income levels. The average gross farm income per acre from crop revenues (CROPS), livestock revenues (LIVESTOCK), and government payments (GOV) from 2002 to 2005 were used to measure agricultural revenues and productivity[3].</p></sec><sec><title>Urbanization factors</title><p>Urbanization influences that boost the probability of farmland conversion to non‐farm use also lead to higher farmland values. Urbanization factors include the size of the local communities and the distance to metropolitan areas. For example, USDA measures rurality with rural‐urban continuum codes based on local urbanization and distance to metropolitan areas. The county population density in 2005 (POP<sub>DEN</sub>) and county population growth from 2001 to 2005 (POP<sub>GROW</sub>) were used to measure urbanization pressures emerging from the size and growth of local communities[4]. The proximity to urban areas was measured by identifying metropolitan counties and non‐metropolitan counties adjacent to metropolitan areas with dummy variables, (METRO) and (ADJACENT), respectively[5].</p></sec><sec><title>Amenity factors</title><p>USDA natural amenity data were used to derive a variable to measure recreation and amenity characteristics in local markets. The standardized <italic>z</italic>‐scores of topography and surface water area were summed to create an overall measure of natural amenities (AMENITY)[6]. Places with more abundant natural amenities are assumed to have higher probability of recreational activity. In the Kansas City Federal Reserve District, counties with higher levels of amenity values had more farms earning recreation service income in 2002.</p></sec><sec><title>Ethanol plant location</title><p>Proximity to ethanol plants was measured as the Euclidian distance between the nearest ethanol plant location and the bank location of survey respondents (<italic>E</italic><sub>DIST</sub>). The locations were calculated on the basis of zip codes. Plant locations were those identified by the Renewable Fuels Association (RFA) and the ACE as plants in operation as of 3 April 2007. Given the surge in ethanol production in 2006 and 2007, the ethanol plant information may not be fully inclusive of all ethanol plants, but this is the most consistent and comprehensive data available to the authors. The minimum distance between an ethanol plant location and survey respondent averaged 65 miles for a single plant, 93 miles for two ethanol plants, and 112 miles for three plants. For example, on average a circle with a radius of 93 miles from a bank respondent would include two plants. <italic>E</italic><sub>DIST</sub> is expected to be negatively related to cropland values because farmland locations with greater distance from an ethanol plant are expected to have lower land values, ceteris paribus[7].</p><p>To further examine this issue, a model was estimated to determine the impact of the number of ethanol plants located within a 50 mile radius of the bank respondent. This was done by constructing a series of indicator variables that identified locations with no plants within 50 miles (Ed0, omitted from the regression), those with one plant within 50 miles (Ed1), those with two plants within 50 miles (Ed2), and those with more than 3 plants within 50 miles (Ed3). It is expected that more plants operating in an area will have a larger impact on land values. <xref ref-type="fig" rid="F_4210690104003">Table I</xref> provides descriptive statistics for the data used in the empirical model.</p></sec><sec><title>Empirical results</title><p>The models were estimated with ordinary least squares using SAS V8 (SAS Institute Inc., 1999). The parameter estimates and model fit statistics for the models are shown in <xref ref-type="fig" rid="F_4210690104004">Table II</xref>. In <xref ref-type="fig" rid="F_4210690104004">Table II</xref>, the first model examines the impact of distance from the nearest ethanol plant with the variable <italic>E</italic><sub>DIST</sub> and the second examines how the number of plants operating within 50 miles of the plant impact land values. In all cases, the <italic>F</italic>‐statistic for the joint significance of the parameters was large enough to reject the hypothesis that the parameters explain no variation in the dependent variable[8]. The models have relatively good fit with adjusted <italic>R</italic>‐square measures ranging from 51 to 60 percent and multicollinearity does not appear to be an issue as most of the variance inflation factors were below two. The exception was crop and government revenues per acre, where variance inflation factors were above seven. High levels of multicollinearity between crop and government revenues, however, were expected as government revenues are based on crop production acres and crop production levels.</p><p>Most of the independent variables were found to be statistically related to non‐irrigated cropland values with the expected sign. The amount of crop production, CROP, was positive and significantly related to non‐irrigated values and the amount of livestock production was negatively related to non‐irrigated land values. The urbanization characteristics, METRO and ADJACENT, also had a positive impact on non‐irrigated cropland values as did population density (POPDEN). On the other hand, population growth, POPGROW did not have a significant impact on non‐irrigated land values.</p><p>The results in the first column of <xref ref-type="fig" rid="F_4210690104004">Table II</xref> indicate that cropland values were higher in places in closer proximity to an operating ethanol plant. Distance to ethanol plants (<italic>E</italic><sub>DIST</sub>) was negative and significant at the 0.01 level. Non‐irrigated cropland values declined by $1.88 per acre for each additional mile from an ethanol plant.</p><p>Although the distance to an ethanol plant appears to be related to farmland values, the level of competition could also play an important role in farmland value gains. For example, the impact of ethanol plant locations on cropland values could be higher in areas that have multiple ethanol plants bidding for local crop production. This is consistent with <xref ref-type="bibr" rid="b21">McNew and Griffith (2005)</xref> who found that ethanol plant locations impacted grain prices up to 68 miles away from the plant.</p><p>The second column of results in <xref ref-type="fig" rid="F_4210690104004">Table II</xref> shows the impact of replacing the variable for distance to the nearest ethanol plant with a series of indicator variables identifying the number of plants operating within 50 miles of the respondent. This set of variables was significant as a group and showed that the impact was greatest when two plants were operating within 50 miles.</p><p>The previous results all consider the case of non‐irrigated farm land values. Because there are significant amounts of irrigation in this region, another analysis was conducted to examine the impact for irrigated farmland values (<xref ref-type="fig" rid="F_4210690104005">Table III</xref>). Like the previous case, crop production and distance to the nearest ethanol plant had a significant impact on irrigated land values[9]. As expected, the impact of distance to the nearest ethanol plant is greater in the case of irrigated land. The irrigated regression results indicate that for every mile of increased distance, irrigated cropland values would fall by $2.62 per acre, a significantly larger decline than the results for non‐irrigated cropland (<xref ref-type="fig" rid="F_4210690104004">Table II</xref>).</p><p>Likewise, the second column of results in <xref ref-type="fig" rid="F_4210690104005">Table III</xref> shows that the number of plants operating within 50 miles of the plant has an important impact on irrigated land values. Irrigated cropland values were $540 per acre higher when two ethanol plants were located within 50 miles as opposed to no plants within 50 miles.</p></sec></sec><sec><title>Implications</title><p>The results indicate substantial variation in farmland values based on the proximity to ethanol plant locations. Ethanol plant locations can have considerable impacts on farmland values. For example, based on the $1.88 per acre marginal impact of distance to a plant, a parcel 50 miles from a plant would have a price $94 less per acre than an equivalent parcel of land next to an ethanol plant. This is approximately 7.2 percent of the average non‐irrigated farmland value of $1,298 per acre. Similarly, for an irrigated parcel, the marginal impact of $2.62 per acre would suggest that the land price for a parcel over 50 miles from an ethanol plant would be $131 per acre less than a parcel next to an ethanol plant or 6.6 percent of average irrigated farmland values of $1,966 per acre.</p><p>The results also suggest that proximity to multiple ethanol plants may further boost farmland values. As opposed to areas with no plants within 50 miles, non‐irrigated farmland values were $586 per acre higher for areas within 50 miles of two plants. This impact is substantially larger than the impact derived by only calculating the distance to the nearest ethanol plant. As a result, it would appear that the presence of competition due to multiple plants in a given area can have a strong impact on land value changes.</p><p>The spatial relationship between farmland values and ethanol plant locations is expected to be driven by changes in local crop basis patterns. In efficient markets, the difference between two points is bounded by transportation costs. As a result, transportation costs or the avoidance of grain shipping costs are expected to explain the most of the relationship between cropland values and the distance to ethanol plants. <xref ref-type="bibr" rid="b13">Gallagher <italic>et al.</italic> (2005)</xref> indicate the cost of transporting a bushel of corn to an ethanol plant by truck is $0.002316 per bushel per mile. This value was compared with the estimated impact of ethanol plant locations on farmland values in the Kansas City Federal Reserve District.</p><p>The estimated marginal impacts on farmland values were converted from per acre to per bushels for comparison. In the Kansas City Federal Reserve District, corn yields on non‐irrigated cropland averaged 90 bushels per acre in 2006. Using the marginal impact of $1.88 per acre in and a capitalization rate of 4 percent, would result in implied transportation costs of $0.000836 per bushel per mile ($1.88/90 * 0.04 = $0.000836). Thus, the estimated marginal impact derived from the land values was 36 percent of the cost of transportation found by <xref ref-type="bibr" rid="b13">Gallagher <italic>et al.</italic> (2005)</xref>. Alternatively, the capitalization rate would need to be roughly 11 percent for the estimated marginal impacts derived from land values to equal the costs of transportation impacts found by Gallagher <italic>et al.</italic></p><p>Using the estimated impacts of ethanol plants within 50 miles on farmland values produces results closer to those found in past literature. <xref ref-type="bibr" rid="b21">McNew and Griffith (2005)</xref> found that ethanol plants within 150 square miles raised corn prices by 12.5 cents per bushel on average, ranging from 4.6 cents to 19.3 cents per bushel. In our analysis, non‐irrigated farmland values were estimated to be $52.44 higher when one ethanol plant was within 50 miles. Using a capitalization rate of 4 percent and a 90 bushel per acre average yield, the annual impact of an ethanol plant would be 2.3 cents per bushel, or slightly less that the range of McNew and Griffith's findings. If one assumes a capitalization rate of 11 percent the impact would be 6.4 cents per bushel and within their range.</p></sec><sec><title>Conclusion</title><p>The recent surge in ethanol production has fueled higher corn prices and led to higher crop prices as the market bid for production acres. Higher crop prices quickly translated into higher farmland values across the country, but the magnitude of these gains were highly variable. Based on land values derived from a survey of agricultural bankers in the Kansas City Federal Reserve District, farmland values are higher in locations in close proximity to ethanol plant locations.</p><p>Economic theory suggests that spatial variations in farmland values would be derived from the difference in local crop basis and transportation costs. The estimated impact of ethanol plants on farmland values appears to be equal or less than the impact of ethanol plants on local basis prices found in existing literature. These results indicate that the recent run‐up in farmland values associated with location is consistent with expected revenue gains from higher basis levels. While agricultural bankers expressed concern about the sustainability of farmland value gains, these results suggest that the component of land value price increases due to changes in transportation costs appear reasonable.</p></sec><sec><title>Notes</title><list list-type="order"><list-item><label>1. </label><p>Data obtained from the Economic Research Service, USDA, Farm Income Briefing Room, available at: <ext-link ext-link-type="uri" xlink:href="http://www.ers.usda.gov">www.ers.usda.gov</ext-link></p></list-item><list-item><label>2. </label><p>According to National Agriculture Statistics Service (NASS), the 2006 national corn yield was 149.1 bushels per acre. According to the Economic Research Service, 2007 cropland values averaged $2,700 per acre and cropland cash rents averaged $89 per acre for a capitalization rate of 3.3 percent.</p></list-item><list-item><label>3. </label><p>Data was obtained from the Regional Economic Information System at the Bureau of Economic Analysis, available at: <ext-link ext-link-type="uri" xlink:href="http://www.bea.gov">www.bea.gov</ext-link>. Government payments include all government payments received by farmers.</p></list-item><list-item><label>4. </label><p>Population data was obtained from the Bureau of Economic Analysis, available at: <ext-link ext-link-type="uri" xlink:href="http://www.bea.gov">www.bea.gov</ext-link>, and land area was obtained from the US Counties data provided by the Census Bureau, available at: <ext-link ext-link-type="uri" xlink:href="http://www.census.gov">www.census.gov</ext-link>. The data are only available through 2005.</p></list-item><list-item><label>5. </label><p>Metro and adjacent dummy variables were created from USDA's rural‐urban continuum codes based on the 2000 Census of Population available at: <ext-link ext-link-type="uri" xlink:href="http://www.ers.usda.gov">www.ers.usda.gov</ext-link>.</p></list-item><list-item><label>6. </label><p>County level data on water surface area and topography were obtained from the USDA's natural amenity index available at: <ext-link ext-link-type="uri" xlink:href="http://www.ers.usda.gov">www.ers.usda.gov</ext-link>.</p></list-item><list-item><label>7. </label><p>Models were also estimated to examine the impact of plant capacity and that allowed a non‐linear distance impact. The results of these models did not significantly improve upon the results presented in the paper.</p></list-item><list-item><label>8. </label><p>The models were also estimated with a log‐linear formulation. The linear model is of most interest because it allows one to directly examine the relationship between implied basis changes and land values.</p></list-item><list-item><label>9. </label><p>The urbanization variables, METRO, ADJACENT, POPDEN, and POPGROW were insignificant, which is not surprising given that irrigated land is concentrated in the sparsely populated areas of the Tenth District. As expected, the amenity variable was positive and significantly related to irrigated cropland values. AMENITY is composed of surface water variable and may be identifying some regions that use surface water for irrigation.</p></list-item></list><fig position="float" id="F_4210690104001"><label><bold>Figure 1<x> </x></bold></label><caption><p> Nebraska non‐irrigated cropland values</p></caption><graphic xlink:href="4210690104001.tif"></graphic></fig><fig position="float" id="F_4210690104002"><label><bold>Figure 2<x> </x></bold></label><caption><p> Ethanol plants and agricultural bank respondents</p></caption><graphic xlink:href="4210690104002.tif"></graphic></fig><fig position="float" id="F_4210690104003"><label><bold>Table I<x> </x></bold></label><caption><p> Descriptive statistics for land values and characteristics, 2007</p></caption><graphic xlink:href="4210690104003.tif"></graphic></fig><fig position="float" id="F_4210690104004"><label><bold>Table II<x> </x></bold></label><caption><p> Regression results: non‐irrigated land values and ethanol plant location</p></caption><graphic xlink:href="4210690104004.tif"></graphic></fig><fig position="float" id="F_4210690104005"><label><bold>Table III<x> </x></bold></label><caption><p> Regression results: irrigated land values and ethanol plant location</p></caption><graphic xlink:href="4210690104005.tif"></graphic></fig><fig position="float" id="F_4210690104006"><caption><p>Equation 1</p></caption><graphic xlink:href="4210690104006.tif"></graphic></fig><fig position="float" id="F_4210690104007"><caption><p>Equation 2</p></caption><graphic xlink:href="4210690104007.tif"></graphic></fig></sec></body><back><ref-list><title>References</title><ref id="b1"><mixed-citation><person-group person-group-type="author"><string-name><surname>Barnard</surname>, <given-names>C.H.</given-names></string-name></person-group>, <person-group person-group-type="author"><string-name><surname>Whittaker</surname>, <given-names>G.</given-names></string-name></person-group>, <person-group 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Gloy can be contacted at: bg49@cornell.edu</p></app></app-group></back></article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>The impact of ethanol plants on cropland values in the great plains</title></titleInfo><titleInfo type="alternative" lang="en" contentType="CDATA"><title>The impact of ethanol plants on cropland values in the great plains</title></titleInfo><name type="personal"><namePart type="given">Jason</namePart><namePart type="family">Henderson</namePart><affiliation>Federal Reserve Bank of Kansas City Omaha Branch, Omaha, Nebraska, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Brent A.</namePart><namePart type="family">Gloy</namePart><affiliation>Department of Applied Economics and Management, Cornell University, Ithaca, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="research-article"></genre><originInfo><publisher>Emerald Group Publishing Limited</publisher><dateIssued encoding="w3cdtf">2009-05-08</dateIssued><copyrightDate encoding="w3cdtf">2009</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract>Purpose Corn ethanol plants consume large amounts of corn and their location has the potential to alter local crop prices and surrounding agricultural land values. The purpose of this paper is to analyze the local economic impact of ethanol plant locations on farmland values. Designmethodologyapproach The relationship between ethanol plant location and agricultural land prices is examined using data obtained from the Agricultural Credit Survey administered by the Federal Reserve Bank of Kansas City. Findings The findings indicate that ethanol plant location has had an impact on land values. The portion of land price changes attributable to location is consistent with previous estimates of basis changes associated with ethanol plant location. Originalityvalue The paper finds that land markets appear to be rationally adjusting to the location of ethanol plants.</abstract><subject><genre>keywords</genre><topic>United States of America</topic><topic>Fuels</topic><topic>Farms</topic><topic>Crops</topic><topic>Property finance</topic></subject><relatedItem type="host"><titleInfo><title>Agricultural Finance Review</title></titleInfo><genre type="journal">journal</genre><subject><genre>Emerald Subject Group</genre><topic authority="SubjectCodesPrimary" authorityURI="cat-ECO">Economics</topic><topic authority="SubjectCodesSecondary" authorityURI="cat-AFP">Agricultural/environmental economics</topic></subject><identifier type="ISSN">0002-1466</identifier><identifier type="PublisherID">afr</identifier><identifier type="DOI">10.1108/afr</identifier><part><date>2009</date><detail type="volume"><caption>vol.</caption><number>69</number></detail><detail type="issue"><caption>no.</caption><number>1</number></detail><extent unit="pages"><start>36</start><end>48</end></extent></part></relatedItem><identifier type="istex">97FCF45B11F58B6E5188FEC871096992797BCE33</identifier><identifier type="DOI">10.1108/00021460910960453</identifier><identifier type="filenameID">4210690104</identifier><identifier type="original-pdf">4210690104.pdf</identifier><identifier type="href">00021460910960453.pdf</identifier><accessCondition type="use and reproduction" contentType="copyright">© Emerald Group Publishing Limited</accessCondition><recordInfo><recordContentSource>EMERALD</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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