Process of Case Selection

The selection of cases followed several steps, guided by the structured focused comparison.⁴⁵ First, a country was selected based on theory guided variables; second, the regions and districts for my within-country-comparison are chosen based on the theoretical analysis.

To answer my research question, the selected country needed to combine various aspects: high levels of drug production and trafficking with relatively low levels of violence. Furthermore, it needs to have an unequal distribution of state presence within the country that allows to select regions in the margins, it needs to be on a drug trafficking route (producer, trafficker or both) and finally represents relatively low levels of violence. For the within-country comparison I identified cases that are similar on most of its variables identified and state marginality but differ in the presence of drug trafficking.

Concerning the factor of drug trafficking, I identified a region that shows changes in drug production in the last five years before start of the analysis as well as another region with continues high levels of drug production

The thematic focus lies on the drug business since it produces an illicit economy that involves many actors needs to be organized and is considered as national challenge. Moreover, drug trafficking is a globally banned criminal activity and it generates the highest profit margins of all considered OC activities. It is also one of the best researched area when it comes to criminal activities. I will focus on

44 The most similar case study has also been called the method of “controlled comparison” (Bennett 2004: 9).

45 based on Patton (2001); Richie and Lewis (2003).

61 cocaine and Pasta Basica de Cocaina (PBC) as they are globally labelled as illegal and offer high profit margins for people involved in the trade and the production. The drug has also additional benefits for the research topic. Since I am interested in marginal regions, the focus on a plant based drug with production in the rural areas and a broader involvement of the rural population in the production process allows to combine the wide extension of the illicit economy with marginal areas into the analysis. The selected regions should have had a long history of absence of state control and presence of an illicit drug economy.

Given the particularities of the research in particular, Peru came out as the most interesting country for the analysis. While Peru gets less attention in both media and academia than neighbouring Colombia concerning drug production, it is nevertheless an important case. Its involvement in the drug trade, the essential role in producing in particular PBC and the development of the state makes the country and important case for studying the results of illicit economies. The country is one of the main production and distribution centers for coca and cocaine. Geographically Peru offers good conditions for the production and trafficking of drugs. The Peruvian rainforest, for example, makes up to around 60% of the countries territory which makes it therefore difficult to access or control and the lacking infrastructural control in marginal areas is visible among others in the inequal distribution of poverty, education or basic services (INEI 2007, 2014: 3). Climatic conditions make the country favourable for growing coca, the basis for cocaine. While I would also have found interesting cases in Colombia for the analysis that match similar conditions, the Colombian peace process might have resulted in a strong influence and affected my research outcome. Additionally, the conflict in Colombia restricted state activities in many regions that were of interest for this study. In Peru the conflict officially ended in 2000 and gave the state various opportunities to intervene in the coca and drug production regions Peru was always one of the biggest coca and cocaine producer in the world (Gootenberg 2008), even though it was also affected by changes. The volatility of coca production is best described by the

“balloon effect”. That is the shift and diversification of production once state restrictions become

“tougher” in one place. Production and trafficking of drugs changed dramatically in the last 20 years.

Peru became again primer producer of coca and cocaine in 2011 when at its peak it produced 62.500 ha (UNODC 2015). Concerning international reports this has changed quite drastically. For 2014 UNODC estimates that still 42.900 ha of coca are produced (Ibd.). It is argued that this decline is mainly due to the extended eradication programs with different regional success. The Peruvian government claims that more than 31.000 ha have been destroyed in 2014. While the absolute number is hard to verify, the data gives a good indication of where to find high amounts of illegal coca and drug production and where to find former hotspots. Thus, also with regard to coca presence and state activity, Peru was an interesting case to study.

62 The within-country comparison has to include some preliminary knowledge of the cases, but this selection cannot presuppose the dependent variable which is the local social order or the relation by the state as those aspects are too complex and need further qualitative investigation. Because I am particularly interested in a specific universe of cases that can answer the research question, the theoretical analysis serves as basis for the theory-guided selection of non-random cases. I narrow my research down to the local level where illicit economies and its externalities can be observed more direct and dynamics resulting from illicit economies become more visible in everyday life. In concentrating on one district at a time allows to analyse in depth these externalities and their importance for social order. This also gives the opportunity to take a closer look on how criminal actors are perceived in comparison to other authorities.⁴⁶

The selection of the within-country cases followed basically two steps. At first the major illicit coca production regions and districts within Peru have been identified and its change in production documented. The levels of coca production serve as an indicator for the regions of illicit drug production, which will be elaborated in the chapter “The Bigger Picture” (chapter 5). By that, I identified not only the major coca producing regions but also those with decreasing numbers in coca production in the last five years.⁴⁷ While in one case the illicit economy is still present, in the other case the economy was recently destroyed. In a second step, I compared socio-economic indicators for the identified districts, which would serve as proxy for state presence in the region. The main characteristics of these sub-national cases are that they have low levels of “state presence”.

Using mostly the latest available figures for all regions (INEI 2007), my control variables are first of all socio-economic. To operationalize them by concentrating on variables that express state infrastructural power (Mann 1984) thus, factors that describe the state reach such as education (school attendency), access to communication services as well as levels of poverty and extreme poverty to control for the economic capacities of the region. Analyzing newspaper articles, official national reports, illicit crop monitoring reports and international drug reports will serve as a controlling factor in analyzing the scope of drug trafficking in the region.⁴⁸ At first I came up with 15 districts, which I lowered down to four with similar socio-economic indicators but differences in the level of coca production. That selection process resulted in the districts of Monzón, Subde de San Jorge and Padre

46 That could be connected to de jure statehood (the amalgator of institutions legally constituting the state), and de facto statehood (represented by actors recognized as components of the state) (Stel and Ndayiragije 2014: 17; Brinkerhoff 2011:

139).

47 That leads to districts in the departments of Huánuco, Ayacucho, and Cuzco For follow up studies Puno might be of interest as it borders Bolivia and is considered as a main smuggling gateway. Also data suggest the “balloon effect” drives coca production towards this area.

48 El Comercio, Diario Correo, IDL-R, Insight Crime, Nexis-Lexis; Police Reports.

63 Abad (Huipoca) as examples for decreasing coca production. Both are in the area of Alto Huallaga. The region is historically the center of coca production not only in Peru but played an essential role first for licit and later also for illicit coca and cocaine production. Recently, coca was destroyed in the region and only few coca plantations are left. Therefore, the region makes a good example for analyzing changes after the destruction of an illicit economy. The region for comparison is the VRAEM, the current epicenter of coca production, in particular Llochegua, Santa Rosa, and Cumunpiari. The VRAEM is one of the biggest coca and PBC producing regions in the world and even if state presence has increased in recent years, coca production remains the highest in the country. Llochegua and Santa Rosa are two districts with the highest amounts of illicit coca and drug production. The development in these two regions allows to study the consequences of a sharp decline coca production and compare it to areas that continue to produce large quantities of coca and PBC. In other words, it is a comparison of a district with a former illegal economy to one with a still very strong presence of an illicit economy.⁴⁹ While doing field research in all of the mentioned districts, I further narrowed down my research on the districts of Monzón, Santa Rosa and Llochegua. This was because I found Monzón as a perfect fit for a region where the coca and drug economy has been destroyed recently and a growing state involvement, where we can analyze the local reaction on both. As comparative cases I used two districts in the VRAEM where the state also recently increased its presence, but did not destroy the illicit economy – Llochegua and Santa Rosa. I decided to use two core districts in the VRAEM since it is a difficult to reach environment, which makes data availability and reliability more difficult.

Furthermore, we see high similarities in the important variable of coca presence but variances in the levels of poverty, which is an interesting element for controlling for the results (see table 2). This selection of three core cases allows to give a detailed and focused analysis on the research questions.

In addition, and in order to have the possibility to further compare the data, I include three additional cases, which allows for validity checks and further comparison. These cases will be not analyzed in depth but primarily compared in the survey. Hence, this results in six cases: three core cases and three comparative cases.

49 Obviously research in an area dominated by an illegal economy has its limits concerning security issues. The findings presented below are preliminary and do not represent the complete results of the study.

64 Map 1 Coca Production Areas in Peru

UNODC 2015 (The red circles resemble the areas of field research)

65

66 This comparative research design will be beneficial in various ways. I will have the opportunity to compare in total six cases from two areas in Peru with each other. Three from a former epicenter of drug trafficking and three from the current center of drug trafficking. This allows for controlling the result of the in-depth case study. The main focus will be given to three focus districts: Monzón as the case of currently low drug and coca production, Santa Rosa and Llochegua as the cases for high levels of drug and coca production. The analysis of a case with no more illicit economy provides first-hand information of the changes for local order and the state-society relation. This will then be compared to the cases where the illicit economy is still prevalent. This research design will give us information on the cases in particular and highlight causal mechanisms. By using a comparative small-N case comparison I will be able to provide a deeper understanding on these understudied research topics and environments. It allows us to compare patterns and highlight differences as well as similarities.