Country Ruggedness and Geographical Data

Data and replication files for 'Ruggedness: The blessing of bad geography in Africa'

by Nathan Nunn and Diego Puga

This site distributes and documents the dataset of terrain ruggedness and other geographical characteristics of countries created by Nathan Nunn and Diego Puga for their article 'Ruggedness: The blessing of bad geography in Africa', published in the Review of Economics and Statistics 94(1), February 2012: 20-36, as well as other variables and computer code required to replicate their results. Users of this dataset are asked to cite the Review of Economics and Statistics article as the source. We would also appreciate it if you let us know the details of any paper in which you use the data by sending an email to Diego Puga (

There are two main components in this dataset:

Country-Level Data

The country-level data on terrain ruggedness and other characteristics of countries includes the following variables:

Grid-cell-level data on terrain ruggedness

Researchers interested in using the terrain ruggedness variables at the level of countries will find these included in the country-level data described above. For those interested in using the terrain ruggedness variables for different geographic units, we also provide the underlying data at the level of individual cells on a 30 arc-seconds grid across the surface of the Earth. Three grid files are available:

To use these ascii grids in ArcGIS, after unzipping each downloaded file, you will need to convert it into a binary grid. You can do this through point-and-click by using the Arc Toolbox and, within Conversion Tools, selecting To Raster, and then ascii to Raster. As input ascii file, specify the text file you unzipped (e.g., tri.txt) and make sure Integer is selected as Output Data Type (at the moment of writing, ArcGIS is still a 32-bit application and a grid covering the Earth with 30 arc-seconds resolution is too large to be handled when values are stored as floating point values instead of integers). Alternatively, at the ArcInfo command line, one can use the ArcInfo Grid command asciigrid (e.g., tri=asciigrid(tri.txt,INT)).

When averaging the Terrain Ruggedness Index or average slope over areas, it is important to take into account that the sea-level surface that corresponds to a 30 by 30 arcsecond cell varies in proportion to the cosine of its latitude (so it starts at 0.860 square kilometres at the equator and approaches 0 square kilometres as one gets sufficiently close to the poles). One should therefore calculate a weighted average, using as weights the values of the area of each cell, provided by the grid cellarea.txt.

Note that the grids are in different units relative to the variables in the country-level data used in the regressions. In particular, the Terrain Ruggedness Index is in milimetres in the 30 arc-seconds grid as opposed to hundreds of metres in the country-level data. This is again due to storage constraints imposed by ArcGIS being a 32-bit application. After calculating the weighted average for an area, divide values by 100,000 to obtain the Terrain Ruggedness Index in hundreds of metres. Average slope is in thousandths of a percentage point in the 30 arc-seconds grid as opposed to percentage points in the country-level data. After calculating the weighted average for an area, divide values by 1,000 to obtain average slope in percent.

Finally, note that to calculate the country-level averages of the Terrain Ruggedness Index or average slope included in the country-level data, in addition to weighting cells by their sea-level surface area, we exclude any land in each country covered by permanent inland water features.


Bratton, Michael and Nicolas van deWalle. 1997. Political regimes and regime transitions in Africa, 1910-1994. Data Collection 6996, Interuniversity Consortium for Political and Social Research.

Collins Bartholomew. 2005. Collins Bartholomew World Premium. Glasgow, UK: Collins Bartholomew.

Fischer, Günther, Harrij van Velthuizen, Mahendra Shah, and Freddy Nachtergaele. 2002. Global Agroecological Assessment for Agriculture in the 21st Century. Laxenburg, Austria: Food and Agriculture Organization of the United Nations and International Institute for Applied Systems Analysis.

Food and Agriculture Organization. 2008. ResourceSTAT. Rome: Food and Agriculture Organization of the United Nations.

Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi. 2008. Governance matters VII: Aggregate and individual governance indicators, 1996-2007. Policy Research Working Paper 4654, World Bank.

Kottek, Markus, Jürgen Grieser, Christoph Beck, Bruno Rudolf, and Franz Rubel. 2006. World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift 15(3): 259-263.

La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert Vishny. 1999. The quality of government. Journal of Law, Economics and Organization 15(1): 222-279.

Maddison, Angus. 2007. Contours of the World Economy, 1-2030 AD: Essays in Macroeconomic History. Oxford: Oxford University Press.

McEvedy, Colin and Richard Jones. 1978. Atlas of World Population History. Harmondsworth: Penguin Books.

Nunn, Nathan. 2008. The long term effects of Africa's slave trades. Quarterly Journal of Economics 123(1): 139-176.

Nunn, Nathan and Diego Puga. 2012. Ruggedness: The blessing of bad geography in Africa. Review of Economics and Statistics 94(1): 20-36.

Oak Ridge National Laboratory. 2001. LandScan Global Population Database 2000. Oak Ridge, tn: Oak Ridge National Laboratory.

Putterman, Louis and David N. Weil. 2010. Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality. Quarterly Journal of Economics 125(4): 1627-1682.

Riley, Shawn J., Stephen D. DeGloria, and Robert Elliot. 1999. A terrain ruggedness index that quantifies topographic heterogeneity. Intermountain Journal of Sciences 5(1-4): 23-27.

Teorell, Jan and Axel Hadenius. 2007. Determinants of democratization: Taking stock of the largeN evidence. In Dirk Berg-Schlosser (ed.) Democratization: The State of the Art. Opladen: Barbara Budrich Publishers, 69-95.

United Nations. 2007. United Nations Common Database. New York, NY: United Nations Statistics Division.

US Bureau of Mines. 1960-1996. Minerals Yearbook. Washington, DC: United States Government Printing Office.

US Geological Survey. 1996. GTOPO30. Sioux Falls, SD: United States Geological Survey Center for Earth Resources Observation and Science (EROS).

US Geological Survey. 1997-2007. Minerals Yearbook. Washington, DC: United States Government Printing Office.

US National Imagery and Mapping Agency. 2000. Vector Map (VMAP) Level 0/Digital Chart of the World. Fifth edition. Fairfax, VA: United States National Imagery and Mapping Agency.

World Bank. 2006. World Development Indicators. Washington, DC: World Bank.