Advanced Search
MyIDEAS: Login

Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming

Contents:

Author Info

  • Viliam Druska

    (Charles Univeristy)

  • William C. Horrace

    (Syracuse University)

Abstract

We consider estimation of a panel data model where disturbances are spatially correlated in the cross-sectional dimension, based on geographic or economic proximity. When the time dimension of the data is large, spatial correlation parameters may be consistently estimated. When the time dimension is small (the usual panel data case), we develop an estimator that extends the cross-sectional model of Kelejian and Prucha. This approach is applied in a stochastic frontier framework to a panel of Indonesian rice farms where spatial correlations represent productivity shock spillovers, based on geographic proximity and weather. These spillovers affect farm-level efficiency estimation and ranking.

Download Info

If 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.
File URL: http://128.118.178.162/eps/em/papers/0206/0206004.pdf
Download Restriction: no

Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0206004.

as in new window
Length: 37 pages
Date of creation: 19 Jun 2002
Date of revision: 11 May 2003
Handle: RePEc:wpa:wuwpem:0206004

Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP; pages: 37; figures: included. Spatial GMM for panel data applied to a stochastic frontier model
Contact details of provider:
Web page: http://128.118.178.162

Related research

Keywords: autocorrelation; Moran I; productivity; stochastic frontier; spatial dependence;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
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.:
as in new window
  1. J. Bradford De Long & Lawrence H. Summers, 1990. "Equipment Investment and Economic Growth," NBER Working Papers 3515, National Bureau of Economic Research, Inc.
  2. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  3. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  4. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-65, July.
  5. Hausman, Jerry A. & Taylor, William E., 1981. "Panel data and unobservable individual effects," Journal of Econometrics, Elsevier, vol. 16(1), pages 155-155, May.
  6. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-98, November.
  7. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  8. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1989. "Production Frontiers With Cross-Sectinal And Time-Series Variation In Efficiency Levels," Working Papers 89-18, C.V. Starr Center for Applied Economics, New York University.
  9. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-38, May.
  10. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  11. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Moscone, Francesco & Tosetti, Elisa, 2009. "GMM estimation of spatial panels," MPRA Paper 16327, University Library of Munich, Germany.
  2. Mick Silver, 2009. "The Hedonic Country Product Dummy Method and Quality Adjustments for Purchasing Power Parity Calculations," IMF Working Papers 09/271, International Monetary Fund.
  3. Harald Badinger & Peter Egger, 2009. "Estimation of Higher-Order Spatial Autoregressive Panel Data Error Component Models," CESifo Working Paper Series 2556, CESifo Group Munich.
  4. Mario Larch & Janette Walde, 2009. "Finite sample properties of alternative GMM estimators for random effects models with spatially correlated errors," The Annals of Regional Science, Springer, vol. 43(2), pages 473-490, June.
  5. Pavlyuk, Dmitry, 2012. "Maximum Likelihood Estimator for Spatial Stochastic Frontier Models," MPRA Paper 43390, University Library of Munich, Germany.
  6. Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
  7. Anthony D. Becker & Rebecca P. Judge, 2012. "Measuring the Effects of Decoupled Payments on Indica Rice Production Under the 1996 and 2002 Farm Bills," Working Papers 201201, St. Olaf College, Department of Economics.
  8. Harald Badinger & Peter Egger, 2011. "Estimation of spatial autoregressive M-way error component panel data models," The Annals of Regional Science, Springer, vol. 47(2), pages 269-310, October.
  9. Anthony J. Glass & Karligash Kenjegalieva & Robin Sickles, 2012. "The Effects of Efficiency and TFP Growth on Nitrogen and Sulphur Emissions in Europe: A Multistage Spatial Analysis," Discussion Paper Series 2012_11, Department of Economics, Loughborough University, revised Oct 2012.
  10. Arnold, Matthias & Wied, Dominik, 2010. "Improved GMM estimation of the spatial autoregressive error model," Economics Letters, Elsevier, vol. 108(1), pages 65-68, July.
  11. Moscone, F. & Tosetti, E., 2011. "GMM estimation of spatial panels with fixed effects and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 41(5), pages 487-497, September.
  12. Frantisek Brazdik, 2005. "Oriented stochastic data envelopment models: Ranking comparison to stochastic frontier approach," CERGE-EI Working Papers wp271, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  13. Pei Li, 2008. "Metropolitan economic growth and spatial dependence: Evidence from a panel of China," Psychometrika, Springer, vol. 3(2), pages 277-295, June.
  14. Lambert, Dayton M. & Griffin, Terry W., 2004. "Analysis Of Government Farm Subsidies On Farmland Cash Rental Rates Using A Fixed Effect Spatial Distributed Lag Model And A Translog Cost Model," 2004 Annual meeting, August 1-4, Denver, CO 19977, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  15. Yang, Juan & Mitchell, Paul D. & Gray, Michael & Steffey, Kevin, 2007. "Unbalanced Nested Component Error Model and the Value of Soil Insecticide and Bt Corn for Controlling Western Corn Rootworm," Staff Paper Series 510, University of Wisconsin, Agricultural and Applied Economics.
  16. Moscone, Francesco & Tosetti, Elisa, 2010. "GMM estimation of Spatial Panels with Fixed Effects," MPRA Paper 20152, University Library of Munich, Germany.
  17. Steven Yamarik, 2011. "Human capital and state-level economic growth: what is the contribution of schooling?," The Annals of Regional Science, Springer, vol. 47(1), pages 195-211, August.
  18. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
  19. Arnold, Matthias, 2007. "GMM estimation of the autoregressiveparameter in a spatial autoregressive errormodel using regression residuals," Technical Reports 2007,25, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  20. Frantisek Brazdik, 2006. "Non-Parametric Analysis of Technical Efficiency: Factors Affecting Efficiency of West Java Rice Farms," CERGE-EI Working Papers wp286, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  21. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpem:0206004

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.