Spatial and Cultural Autocorrelation in International Datasets
Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can be defined in many different dimensions. In a cross-section of nations, it can be defined using physical distance, cultural similarity, ecological similarity, or using frequency and intensity of interaction, such as trade relationships or enemy and ally relationships. Autocorrelation of regression residuals presents well-known problems in least-squares estimation, but autocorrelation also provides useful information for exploratory data analysis and model specification. The paper shows that autocorrelation is widespread in international datasets. The paper demonstrates the usefulness of autocorrelation in uncovering stylized facts about international relations, and in specifying a least-squares model.
|Date of creation:||Feb 2004|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html|
More information through EDIRC
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.:
- Andrew Rose, 2005.
"Which International Institutions Promote International Trade?,"
Review of International Economics,
Wiley Blackwell, vol. 13(4), pages 682-698, 09.
- Rose, Andrew K, 2003. "Which International Institutions Promote International Trade?," CEPR Discussion Papers 3764, C.E.P.R. Discussion Papers.
- Easterly, William & Levine, Ross, 1997.
"Africa's Growth Tragedy: Policies and Ethnic Divisions,"
The Quarterly Journal of Economics,
MIT Press, vol. 112(4), pages 1203-50, November.
- Easterly, W & Levine, R, 1996. "Africa's Growth Tragedy : Policies and Ethnic Divisions," Papers 536, Harvard - Institute for International Development.
- King, Gary & Lowe, Will, 2003. "An Automated Information Extraction Tool for International Conflict Data with Performance as Good as Human Coders: A Rare Events Evaluation Design," International Organization, Cambridge University Press, vol. 57(03), pages 617-642, June.
When requesting a correction, please mention this item's handle: RePEc:mts:wpaper:200401. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (E. Anthon Eff)
If references are entirely missing, you can add them using this form.