Explaining The Climate-Dependent Distribution Of Crops In Space –The Example Of Corn And Corn-Cob-Mix In Baden-Württemberg
AbstractThis article analyses the current climate-dependent spatial distribution of corn and corn-cob-mix in Baden-Württemberg using 2007 data at the county and community level. We use OLS and spatial econometric models to estimate the effects of different climate and non-climate variables on the share of grain maize in UAA. Whereas the temperature effect is missed by means of OLS regression, the adequate spatial error model at the county level yields a highly significant positive effect of mean annual temperature. Additionally, it displays a temperature cut-off point after which corn share is less likely to rise due to temperature increase. These effects are supported by a non-spatial multinomial logit model at the community level. The latter further indicates that soil quality also plays a role. The positive effect of annual precipitation remains ambiguous.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by German Association of Agricultural Economists (GEWISOLA) in its series 51st Annual Conference, Halle, Germany, September 28-30, 2011 with number 114504.
Date of creation: Sep 2011
Date of revision:
Spatial distribution of corn; spatial econometrics; multinomial logit; climate change; Agribusiness; Crop Production/Industries;
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- P. Wilner Jeanty, 2010. "SPLAGVAR: Stata module to generate spatially lagged variables, construct the Moran Scatter plot, and calculate Moran's I statistics," Statistical Software Components S457112, Boston College Department of Economics, revised 09 Aug 2012.
- P. Wilner Jeanty, 2010. "ANKETEST: Stata module to perform diagnostic tests for spatial autocorrelation in the residuals of OLS, SAR, IV, and IV-SAR models," Statistical Software Components S457113, Boston College Department of Economics, revised 11 Mar 2010.
- Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
- Seo, S. Niggol & Mendelsohn, Robert, 2008. "An analysis of crop choice: Adapting to climate change in South American farms," Ecological Economics, Elsevier, vol. 67(1), pages 109-116, August.
- P. Wilner Jeanty, 2010. "SPWMATRIX: Stata module to generate, import, and export spatial weights," Statistical Software Components S457111, Boston College Department of Economics, revised 11 Mar 2010.
- Hausman, Jerry & McFadden, Daniel, 1984.
"Specification Tests for the Multinomial Logit Model,"
Econometric Society, vol. 52(5), pages 1219-40, September.
- D. McFadden & J. Hausman, 1981. "Specification Tests for the Multinominal Logit Model," Working papers 292, Massachusetts Institute of Technology (MIT), Department of Economics.
- P. Wilner Jeanty, 2010. "SPMLREG: Stata module to estimate the spatial lag, the spatial error, the spatial durbin, and the general spatial models by maximum likelihood," Statistical Software Components S457135, Boston College Department of Economics, revised 25 Dec 2013.
- Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-71, September.
- Gunnar Breustedt & Hendrik Habermann, 2011. "The Incidence of EU Per‐Hectare Payments on Farmland Rental Rates: A Spatial Econometric Analysis of German Farm‐Level Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(1), pages 225-243, 02.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search).
If references are entirely missing, you can add them using this form.