Hostname: page-component-54dcc4c588-rz4zl Total loading time: 0 Render date: 2025-09-11T21:12:59.123Z Has data issue: false hasContentIssue false
  • English
  • Français

Panel Data Estimation Methods on Supply and Demand Elasticities:The Case of Cotton in Greece

Published online by Cambridge University Press:  26 January 2015

Christina Kotakou
Christina Kotakou*
Affiliation:
Department of Economics, University of Macedonia, Thessaloniki, Greece
Get access Rights & Permissions [Opens in a new window]

Abstract

This article examines the effects of the application of panel dataestimation methods on a system of equations with unbalanced panel data. Weapply pooled, random-effects, and fixed-effects estimation in three datasets: small, medium, and large farms to examine the relationship betweenfarm size and the elasticity of cotton supply with respect to cotton price.Our results indicate that the adoption of various estimation methods entailsdifferent estimated parameters both in terms of their absolute value and interms of their statistical significance. Additionally, the elasticity ofcotton supply with respect to price varies according to farm size.

Keywords

farm sizepanel datasupply elasticitysystems of equationsC33D21Q18

Information

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 1 , February 2011 , pp. 111 - 129
Copyright
Copyright © Southern Agricultural Economics Association 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Abrar, S., Morrissey, O., and Rayner, T. “Aggregate Agricultural Supply Response in Ethiopia: A Farm-level Analysis.” Journal of International Development 16(2004):605–20.10.1002/jid.1110Google Scholar
Adesoji, O.A. “Price Changes, Supply Elasticities, Industry Organization, and Dairy Output Distribution.” American Journal of Agricultural Economics 73(1991):89–102.10.2307/1242886Google Scholar
Arnade, C, and Kelch, D. “Estimation of Area Elasticities from a Standard Profit Function.” American Journal of Agricultural Economics 89(2007):727–37.10.1111/j.1467-8276.2007.01004.xGoogle Scholar
Avery, B.R. “Error Components and Seemingly Unrelated Regressions.” Econometrica 45(1977):199–209.10.2307/1913296Google Scholar
Bakucs, Z., and Fert, I.ô. “The Growth of Family Farms in Hungary.” Agricultural Economics 40(2009):789–95.10.1111/j.1574-0862.2009.00415.xGoogle Scholar
Baltagi, B.H. “Pooling Cross-sections with Unequal Time-series Lengths.” Economics Letters 18(1985):133–36.10.1016/0165-1765(85)90167-3Google Scholar
Baltagi, B.H. Econometric Analysis of Panel Data. London: John Wiley & Sons, Ltd., 2005.Google Scholar
Biørn, E. “Regression Systems for Unbalanced Panel Data: A Stepwise Maximum Likelihood Procedure.” Journal of Econometrics 122(2004):281–91.10.1016/j.jeconom.2003.10.023Google Scholar
Bun, J.G.M. “Testing Poolability in a System of Dynamic Regressions with Nonspherical Disturbances.” Empirical Economics 29(2004):89–106.10.1007/s00181-003-0191-3Google Scholar
Cai, Y., Alviola, RA., Nayga, R.M., and Wu, X. “The Effect of Food-Away-from-Home and Food-at-Home Expenditures on Obesity Rates: A State-Level Analysis.” Journal of Agricultural and Applied Economics 40(2008):507–21.Google Scholar
Carlberg, J.G. “Effect of Ownership Restrictions on Farmland Values in Saskatchewan.” Journal of Agricultural and Applied Economics 34(2002):248–358.Google Scholar
Csajbok, I., Lansink, A.O., and Huirne, R. “Effects of Management Information from FADN on Profitability of Dutch Potted-Plant Firms.” Agricultural Economics 33(2005):325–31.10.1111/j.1574-0864.2005.00071.xGoogle Scholar
El-Osta, H.S., and Mishra, A.K. “Dimensions of Wealth Dispersion among Farm Operator Households: An Assessment of the Impact Farm Subsidies.” Journal of Agricultural and Applied Economics 37(2005):187–208.Google Scholar
European Commission. “Study on the Cotton Sector in the European Union.” Final Report, 2007. Internet site: http://ec.europa.eu/agriculture/analysis/external/cotton/index_en.htm (Accessed February 12, 2010).Google Scholar
Fousekis, P., and Revell, B.J. “Meat Demand in the UK: A Differential Approach.” Journal of Agricultural and Applied Economics 32(2000):11–19.Google Scholar
Guajarati, D. “Use of Dummy Variables in Testing for Equality between Two Sets of Coefficients in Two Linear Regressions: A Note.” The American Statistician 24(1970):50–52.Google Scholar
Hausman, J.A. “Specification Tests in Econometrics.” Econometrica 46(1978):1251–71.10.2307/1913827Google Scholar
Hsiao, C. Analysis of Panel Data. Cambridge, MA: Cambridge University Press, 1986.Google Scholar
Kaltsas, I.K., Bosch, D.J., and McGuirk, A. “Residential Land Values in Urbanizing Areas.” Journal of Agricultural and Applied Economics 40(2008):635–47.Google Scholar
Karagiannis, G., and Sarris, A. “Measuring and Explaining Scale Efficiency with the Parametric Approach: The Case of Greek Tobacco Growers.” Agricultural Economics 33(2005):441–51.10.1111/j.1574-0864.2005.00084.xGoogle Scholar
Katranidis, S., and Velentzas, K. “The Markets of Cotton Seed and Maize in Greece: Welfare Implications of the Common Agricultural Policy.” Agricultural Economics Research 1(2000):82–95.Google Scholar
Lee, D.S., Kennedy, P.L., and Fletcher, S.M. “An Analysis of Latin American Peanut Trade.” Journal of Agricultural and Applied Economics 38(2006):1–16.Google Scholar
Lianos, T., and Rizopoulos, G. “Estimation of Social Welfare Weights in Agricultural Policy: The Case of Greek Cotton.” Journal of Agricultural Economics 39(1988):61–68.10.1111/j.1477-9552.1988.tb00562.xGoogle Scholar
Melfou, K., Theocharopoulos, A., and Papanagiotou, E. “Assessing Productivity Change with SFA in the Sheep Sector in Greece.” Operations Research 9(2009):281–92.10.1007/s12351-009-0051-9Google Scholar
Mills, E.D., and Schumann, L. “Industry Structure with Fluctuating Demand.” The American Economic Review 75(1985):758–67.Google Scholar
Moro, D., and Sckokai, P. “Modelling the CAP Arable Crop Regime in Italy: Degree of Decoupling and Impact of AGENDA 2000.” Cahiers D'économie et Sociologie Rurales 53(1999):50–73.Google Scholar
Papke, L.E., and Wooldridge, J.M. “A Computational Trick for Delta-Method Standard Errors.” Economics Letters 86(2005):413–17.10.1016/j.econlet.2004.07.022Google Scholar
Platoni, S., Sckokai, P., and Moro, D. “Panel Data Estimation Techniques for Farm-level Data Model.” Paper presented at the 12th Congress of the European Association of Agricultural Economists, Ghent, Belgium, August 26-29, 2008.Google Scholar
Pope, R.D., LaFrance, J.T., and Just, R.E. “Imperfect Price Deflation in Production Systems.” American Journal of Agricultural Economics 89(2007):738–54.10.1111/j.1467-8276.2007.00986.xGoogle Scholar
Poudel, B.N., Paudel, K.P., and Bhattarai, K. “Searching for an Environmental Kuznets Curve in Carbon Dioxide Pollutant in Latin American Countries.” Journal of Agricultural and Applied Economics 41(2009):13–27.Google Scholar
Reidsma, P., Ewert, F., Boogaard, H., and van Diepen, K. “Regional Crop Modelling in Europe: The Impact of Climatic Conditions and Farm Characteristics on Maize Yields.” Agricultural Systems 100(2009):51–60.10.1016/j.agsy.2008.12.009Google Scholar
Rezitis, A.N., Tsiboukas, K., and Tsoukalas, S. “Measuring Technical Efficiency in the Greek Agricultural Sector.” Applied Economics 34(2002):1345–57.10.1080/00036840110099261Google Scholar
Sckokai, P., and Moro, D. “Modeling the Reforms of the Common Agricultural Policy for Arable Crops under Uncertainty.” American Journal of Agricultural Economics 88(2006):43–56.10.1111/j.1467-8276.2006.00857.xGoogle Scholar
Serra, T., Zilberman, D., Goodwin, B.K., and Featherstone, A.M. “Decoupling Farm Policies: How Does This Affect Production?” Paper presented at the American Agricultural Economics Association Annual Meeting, Providence, RI, July 24-27, 2005a.Google Scholar
Serra, T., Zilberman, D., Goodwin, B.K., and Hyvonen, K. “Replacement of Agricultural Price Supports by Area Payments in the European Union and the Effects of Pesticide Use.” American Journal of Agricultural Economics 87(2005b):870–84.10.1111/j.1467-8276.2005.00775.xGoogle Scholar
Serra, T., Zilberman, D., Goodwin, B.K., and Featherstone, A.M. “Effects of Decoupling on the Mean and Variability of Output.” European Review of Agriculture Economics 33(2006):269–88.10.1093/erae/jbl014Google Scholar
Shumway, C.R. “Supply, Demand and Technology in a Multiproduct Industry: Texas Field Crops.” American Journal of Agricultural Economics 65(1983):748–60.10.2307/1240463Google Scholar
Sidhu, S.S., and Baanante, A.C. “Estimating Farm-Level Demand and Wheat Supply in the Indian Punjab Using a Translog Profit Function.” American Journal of Agricultural Economics 63(1981):237–416.10.2307/1239559Google Scholar
Vilezca-Becerra, A.P., and Shumway, C.R. “State-Level Output Supply and Input Demand Elasticities for Agricultural Commodities.” Journal of Agricultural Economics Research 44(1994):22–34.Google Scholar
Weaver, D.R. “Multiple Input, Multiple Output Production Choices and Technology in the Wheat U.S. Region.” American Journal of Agricultural Economics 65(1983):45–56.10.2307/1240336Google Scholar
Zanias, G. “An Estimation of the Supply Response of Cotton in Greece from 1950-1979.” Oxford Agrarian Studies 10(1981):196–211.10.1080/13600818108423916Google Scholar
Zellner, A. “An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias.” Journal of the American Statistical Association 57(1962):348–68.10.1080/01621459.1962.10480664Google Scholar