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After years of painstaking negotiations and political obstacles, the end to the conflict between the Revolutionary Armed Forces of Colombia (FARC) and the Colombian government appears irreversible. Daunting challenges to the implementation of the agreement remain, however. The five pieces in this special issue rigorously examine those challenges. In doing so, they explore how the field of peace science can help us understand Colombia's transition from war to peace and how Colombia raises new unexplored questions for scholars. This introduction describes the principal findings of the special issue before offering tangible advice to peacebuilders working in Colombia.

This paper studies the effect of strengthening democracy, as captured by an increase in voting rights, on the incidence of violent civil conflict in nineteenth-century Colombia. Empirically studying the relationship between democracy and conflict is challenging, not only because of conceptual problems in defining and measuring democracy, but also because political institutions and violence are jointly determined. We take advantage of an experiment of history to examine the impact of one simple, measurable dimension of democracy (the size of the franchise) on con- flict, while at the same time attempting to overcome the identification problem. In 1853, Colombia established universal male suffrage. Using a simple difference-indifferences specification at the municipal level, we find that municipalities where more voters were enfranchised relative to their population experienced fewer violent political battles while the reform was in effect. The results are robust to including a number of additional controls. Moreover, we investigate the potential mechanisms driving the results. In particular, we look at which components of the proportion of new voters in 1853 explain the results, and we examine if results are stronger in places with more political competition and state capacity. We interpret our findings as suggesting that violence in nineteenth-century Colombia was a technology for political elites to compete for the rents from power, and that democracy constituted an alternative way to compete which substituted violence.

This is a critical review of the empirical literature on the relationship between violence and economic growth in Colombia, an interesting case study for social scientists studying violence, conflict, crime, and development. We argue that despite the rapid development of this literature and the increasing use of new quantitative techniques, there is still much room for research. After assessing the contribution of the most influential papers on the subject, we suggest directions for future research.

Abstract
Corruption has pervasive effects on economic development and the well-being of the population. Despite being crucial and necessary, fighting corruption is not an easy task because it is a difficult phenomenon to measure and detect. However, recent advances in the field of artificial intelligence may help in this quest. In this article, we propose the use of machine-learning models to predict municipality-level corruption in a developing country. Using data from disciplinary prosecutions conducted by an anti-corruption agency in Colombia, we trained four canonical models (Random Forests, Gradient Boosting Machine, Lasso, and Neural Networks), and ensemble their predictions, to predict whether or not a mayor will commit acts of corruption. Our models achieve acceptable levels of performance, based on metrics such as the precision and the area under the receiver-operating characteristic curve, demonstrating that these tools are useful in predicting where misbehavior is most likely to occur. Moreover, our feature-importance analysis shows us which groups of variables are most important in predicting corruption.

La crisis de salud pública causada por la pandemia de COVID-19, junto con la subsiguiente emergencia económica y la agitación social, ha empujado a los gobiernos a aumentar el gasto de manera sustancial y rápida. Debido a la naturaleza apremiante de la crisis, las normas y procedimientos de contratación pública se han relajado en muchos lugares para acelerar las transacciones. Sin embargo, esto también puede crear oportunidades para la corrupción. Utilizando información a nivel de contrato sobre el gasto público de la plataforma de compras electrónicas de Colombia, y una estrategia de identificación de diferencias en diferencias, encontramos que los municipios clasificados por un algoritmo de aprendizaje automático como tradicionalmente más propensos a la corrupción reaccionan al aumento del gasto liderado por una pandemia. utilizando una mayor proporción de contratos discrecionales no competitivos y aumentando su valor promedio. Esto es especialmente así en el caso de los contratos para adquirir bienes y servicios relacionados con la crisis. Nuestra evidencia sugiere que los grandes shocks negativos que requieren un gasto rápido y masivo pueden aumentar la corrupción, compensando al menos parcialmente los efectos atenuantes de este instrumento fiscal. ; The public health crisis caused by the COVID-19 pandemic, coupled with the subsequent economic emergency and social turmoil, has pushed governments to substantially and swiftly increase spending. Because of the pressing nature of the crisis, public procurement rules and procedures have been relaxed in many places in order to expedite transactions. However, this may also create opportunities for corruption. Using contract-level information on public spending from Colombia's e-procurement platform, and a difference-in-differences identification strategy, we find that municipalities classified by a machine learning algorithm as traditionally more prone to corruption react to the pandemic-led spending surge by using a larger proportion of discretionary non-competitive contracts and increasing their average value. This is especially so in the case of contracts to procure crisis-related goods and services. Our evidence suggests that large negative shocks that require fast and massive spending may increase corruption, thus at least partially offsetting the mitigating effects of this fiscal instrument.

Well-intended policies often have negative unintended consequences if they fail to foresee the different ways in which individuals may respond to the new set of incentives. When widespread and persistent, these may lead to a net reduction of social welfare. Focusing on the case of anti-drug policies, in this paper we show that the recent unprecedented surge in the growing of illicit coca crops in Colombia was the result of a naive and untimely policy announcement during peace negotiations between the government and the FARC guerrillas. On May 2014, the parties¿ peace delegations issued a press release announcing that coca-growing farmers would receive material incentives for voluntary crop substitution once a final agreement had been reached. To evaluate the anticipation effect of this announcement we exploit the cross sectional variation on both the cost advantage of growing coca (using an ecological measure of coca suitability) and the expected benefits of doing so (using a predicted measure of where the material benefits would h ave b een t argeted). Coca plantations levels remained high even after the implementation of the announced incentives¿ scheme. We explain this persistence by documenting that the surge in coca growing is differentially higher in areas with presence illegal armed groups, that benefited financially from availability of a key input in the drug trade.