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³ Collier, Paul and Rohner, Dominic, ‘Democracy, Development, and Conflict’, Journal of the European Economic Association, 6 (2008), 531–540 Google Scholar

⁴ Authors’ calculations based on the National Elections across Democracy and Autocracy Dataset (Hyde and Marinov, ‘Which Elections Can Be Lost?’) and the Armed Conflict Dataset (Gleditsch et al., ‘Armed Conflict 1946–2001’).

⁵ Collier, Paul and Vicente, Pedro C., ‘Votes and Violence: Evidence from a Field Experiment in Nigeria’ (Working paper, Department of Economics, Oxford University, 2011)Google Scholar

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¹⁰ For more general treatments of what strategies are chosen under which conditions, see e.g. Collier and Vicente, ‘Votes and Violence’.

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¹⁷ UNDP ELECT Afghanistan. Annual Progress Report – 2009. Available at http://www.undp.org.af/Projects/2009AnnualReports/ELECT_APR09.pdf.2009.

¹⁸ We provide some evidence against the second explanation below by showing that our results are robust to the inclusion of the share of planned polling stations that actually operated into the regression.

¹⁹ Collier and Vicente, ‘Violence, Fraud, and Bribery’; Collier and Vicente, ‘Votes and Violence’; Ellman and Wantchekon, ‘Electoral Competition under the Threat of Political Unrest’; Wilkinson, Votes and Violence.

²⁰ Gandhi, Jennifer and Lust-Okar, Ellen, ‘Elections under Authoritarianism’, Annual Review of Political Science, 12 (2009), 403–422 Google Scholar

²¹ See also Ichino and Schündeln, ‘Deterring or Displacing Electoral Irregularities?’

²² For more information about the electoral process, see National Democratic Institute, The 2009 Presidential and Provincial Council Elections in Afghanistan (technical report available at http://www.ndi.org/files/Elections_in_Afghanistan_2009.pdf.2010).

²³ National Democratic Institute, The 2009 Presidential and Provincial Council Elections in Afghanistan.

²⁴ See e.g. ‘Afghanistan imposes censorship on election day’, New York Times, 18 August 2009. http://www.nytimes.com/2009/08/19/world/asia/19afghan.html.

²⁵ Bill Greer, Dataset of the Day: Impact of Violence on the Afghanistan Elections (online report, 26 August 2009. Available at http://blog.geoiq.com/2009/08/26/dataset-of-the-day-impact-of-violence-on-the-afghanistan-elections/.2009).

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²⁹ Sharan, ‘The Dynamics of Elite Networks and Patron–Client Relations in Afghanistan’.

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³¹ Lehoucq, ‘Electoral Fraud’.

³² Ziblatt, ‘Shaping Democratic Practice and the Causes of Electoral Fraud’.

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³⁸ Beber and Scacco (‘What the Numbers Say’) propose additional forensic tests. However, we find that they correlate less well with our recount-based fraud measure (see next section), so we do not use it in the core empirical analysis.

³⁹ Beber and Scacco, ‘What the Numbers Say’.

⁴⁰ Mebane, ‘Election Forensics’.

⁴¹ Lacking information about the precise location of polling stations, we are unable to estimate fraud at lower levels, for example, cities. Moreover, many of the covariates used in our regression analysis below are available only at the district level.

⁴² Mebane, Walter R., ‘Comment on Benford's Law and the Detection of Election Fraud’, Political Analysis, 19 (2011), 269–272 Google Scholar

⁴³ Beber and Scacco, ‘What the Numbers Say’; Deckert, Myagkov and Ordeshook, ‘Benford's Law and the Detection of Election Fraud’.

⁴⁴ The stations were divided into five categories, as follows: (A1) 600 or more valid votes were cast, (A2) 600 or more total votes were cast, (B1) more than 100 votes were cast and one candidate received 95 per cent or more of the total votes, (B2) one candidate received 95 per cent or more of the total valid votes cast, and (C1) 600 or more valid votes were cast and one candidate received 95 per cent or more of the total votes.

⁴⁵ The IEC reports investigating 343 boxes, but categories B1 and C1 described above contain a mutual observation which was overlooked.

⁴⁶ In the recount, the shares of boxes exhibiting some physical evidence of fraud are as follows. A1: 0.655 (sd = 0.480); A2: 0.7 (sd = 0.466); B1: 0.721 (sd = 0.450); B2: 0.462 (sd = 0.505); C1: 0.939 (sd = 0.241). The sample of 342 stations was drawn randomly and so by the weak law of large numbers the sample mean for each category provides a consistent estimate of the share of fraudulent polling stations in that category at the national level.

⁴⁷ The IEC publicly posted the data in three waves. They reported returns from 27,163 distinct polling stations on 19 September, 23,300 stations on 10 October and 22,853 polling stations on 20 October. Of the original 27,163, 4,305 are missing or record no votes. This brings us to 22,858 (almost the 20 October number). We use the earliest data release in order to be able to control for the number of missing/closed polling stations.

⁴⁸ Clionadh Raleigh et al. ‘Introducing ACLED: An Armed Conflict Location and Event Dataset’, Journal of Peace Research, 47 (2010), 651–660 Google Scholar

⁴⁹ In the case of the WITS dataset, the location of an event is provided by the town or village it occurred in. We added geographic co-ordinates to events by looking up these place names in a gazetteer.

⁵⁰ US Geological Survey. GTOPO30 Digital Elevation Model. Available at http://edc.usgs.gov/products/elevation/gtopo30/gtopo30.html.2007.

⁵¹ Oak Ridge National Laboratory, LandScan Global Population database, 2008.

⁵² Our results are additionally robust to clustering at the province level; there are a sufficient number of provinces that clustered standard errors are likely to resemble their asymptotic distribution.

⁵³ For examples, see Ellman and Wantchekon, ‘Electoral Competition under the Threat of Political Unrest’; Wilkinson, Votes and Violence.

⁵⁴ C. Christine Fair and Seth G. Jones, ‘Securing Afghanistan: Getting on Track’ (Working paper, United States Institute of Peace, available at http://library.usip.org/articles/1012068.1022/1.PDF,2009).

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