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In this paper, we investigate the relationship between economic development, investments, savings, insecurity and social conditions in Colombian departments. Using a dynamic heterogeneous panel analysis, we study the effects of insecurity and social conditions on economic development through an estimation of panel data cointegration techniques. The models applied in this study suggest a long-term relationship among economic development, investments, savings, social conditions and insecurity. Investments, savings and human development index have a positive and significant coefficient, which indicates that these variables produce incentives for economic development, whereas GINI and homicides have a negative relationship, demonstrating that these variables undermine economic development. All findings are important in the design of strategies and policies that strengthen income distribution equality, a key factor that determines growth and development through adequate government expenditures that encourage savings and investment decisions with the aim to improve welfare and the standard of living. peerReviewed

This paper studies the socio-economic determinants of violence in the seven most important cities in Colombia. Derived from theories rooted in classic works, including Becker's paradigm, criminal inertia, social disorganisation, urbanism and strain, we formulate several hypotheses on the socio-economic determinants of violence. To test these hypotheses, a dynamic panel data analysis is employed. The analysis shows that cities’ deprivation and high population density are strong predictors of homicide rates. Comparing the results among Colombian cities, we find support indicating that city-level homicide rates are influenced by the city's level of development. Moreover, we find evidence that economic growth, inequality, poverty and human capital influence violence in the cities studied, which could generate negative effects on the economic and social development of Colombia. Copyright © 2012 John Wiley & Sons, Ltd.

This paper analyses some determinants of urban violence in seven major Colombian cities. The empirical research is intended to explore variations in violence across these Colombian cities and the influence of these variations on Colombia's economic development. In this study, several econometric data panel models and various estimate types are applied to control heterogeneity across the cities and to address endogeneity problems among the explanatory variables. The results show that education, poverty, inequality and the labour market are strong predictors of homicide rates in the seven Colombian cities. The results also demonstrate that city-level homicide rates depend on the city's level of development and the tendency of urban violence to persist over time. The findings thus demonstrate that factors such as inequality, poverty, education and the labour market influence urban violence, thereby generating negative effects on Colombia's economic and social development.

In this paper, we analyse economic development and growth through traditional measures (gross domestic product and human development index) and Data Envelopment Analysis (DEA) in Colombian departments over the period 1993–2007. We use a DEA model to measure and rank economic development and growth from different approaches such as poverty, equality and security. The results show considerable variation in efficiency scores across departments. A second-stage panel data analysis with fixed effects reveals that higher levels of economic activity, quality life, employment and security are associated with a higher efficiency score based on the standards of living, poverty, equality and security. All findings of this analysis should demonstrate that economic development and growth could be achieved most effectively through a decrease in poverty, an increase in equality, a reduction in violence, and improved security. This indicates the need to generate effective policies that guarantee the achievement of these elements in the interest of all members of society.

This research evaluates the connection between corruption, economic development, and insecurity in several Colombian departments. This chapter explores the dynamics of these variables using two empirical techniques: the Data Envelopment Analysis (DEA) and the Dynamic Panel Data Model (DPDM). DEA is performed to evaluate social performance in terms of corruption, economic development, and insecurity in Colombian departments with a higher level and risk of corruption and insecurity. Dynamic panel data analysis is performed to define the variables that affect corruption, insecurity, and economic development. The DEA model provides evidence that corruption and insecurity have different trends where economic development, natural resources, and political instability are key factors. The dynamic panel data model applied shows that Colombian departments with a higher level and risk of corruption and insecurity have lower economic growth, development, and social conditions, but higher levels of mineral resources and illegal drug activity, as well as the presence of irregular armed groups.

This work uses several empirical approaches to examine the effects of poverty and inequality on violence in the seven metropolitan areas in Colombia. To this end, this study describes the main determinants of violence in these cities; these determinants are all fundamental features of social instability. For this description, this paper uses several econometric approximations to compare and determine an adequate estimator for the analysis of Colombian urban violence. This hypothesis was supported by evidence showing that factors related to poverty, inequality, and education directly influenced violence in the cities. Because of their effects over time and their incidence rates across society, these factors also had negative effects on the economic and social development of every city analysed. peerReviewed

This research analyses the long run and short run relationships among economic growth, poverty and energy using the Colombian case. In this study, we use the time-series methodologies. The results regarding the relationship among economic growth, poverty and energy show that increases in gross domestic product and energy supply per capita should lead a decrease of poverty, which should demonstrate that access to modern and adequate energy services help to decrease poverty and to increase economic growth. Moreover, the improvements in energy efficiency have contributed to increase economic growth from an approach of sustainable development. These results are important for the adequate design, formulation and application of policies and strategies that encourage a better energy use to improve economic growth and decrease poverty, especially in developing countries. peerReviewed

This study evaluates and compares the trends in CO2 emissions for the manufacturing industries of three countries: two developed countries (Germany and Sweden) that have applied several measures to promote a shift towards a low-carbon economy and one developing country (Colombia) that has shown substantial improvements in the reduction of CO2 emissions. This analysis is conducted using panel data cointegration techniques to infer causality between CO2 emissions, production factors and energy sources. The results indicate a trend of producing more output with less pollution. The trends for these countries' CO2 emissions depend on investment levels, energy sources and economic factors. Furthermore, the trends in CO2 emissions indicate that there are emission level differences between the two developed countries and the developing country. Moreover, the study confirms that it is possible to achieve economic growth and sustainable development while reducing greenhouse gas emissions, as Germany and Sweden demonstrate. In the case of Colombia, it is important to encourage a reduction in CO2 emissions through policies that combine technical and economic instruments and incentivise the application of new technologies that promote clean and environmentally friendly processes. © 2013 The Author(s).

This paper develops an index to evaluate the level of effectiveness of the control of violence based on the data envelopment analysis approach. The index is used to examine the grade of effectiveness of the control of violence at the level of Colombian departments between 1993 and 2007. Comparing the results across Colombian departments, we find that the majority of departments show improvement in their scores of effectiveness. A second stage of the regression model reveals that departments with a higher gross domestic product and higher education and employment are more effective in the control of violence, whereas departments with higher political violence, unemployment rates, unsatisfied basic needs, a displaced population, and hectares cultivated with coca show lower effectiveness in the control of violence. All these findings are of particular interest in the formulation and development of policies against violence, taking into account that organised forms of violence, such as drug trafficking, impede the adequate effectiveness of its control. Moreover, violence decreases social investments, generating alterations in social services that produce long-run deterioration in faith in the government’s ability to govern, which should become an incentive to further violence. peerReviewed

This research evaluates the connection between corruption, economic development, and insecurity in several Colombian departments. This chapter explores the dynamics of these variables using two empirical techniques: the Data Envelopment Analysis (DEA) and the Dynamic Panel Data Model (DPDM). DEA is performed to evaluate social performance in terms of corruption, economic development, and insecurity in Colombian departments with a higher level and risk of corruption and insecurity. Dynamic panel data analysis is performed to define the variables that affect corruption, insecurity, and economic development. The DEA model provides evidence that corruption and insecurity have different trends where economic development, natural resources, and political instability are key factors. The dynamic panel data model applied shows that Colombian departments with a higher level and risk of corruption and insecurity have lower economic growth, development, and social conditions, but higher levels of mineral resources and illegal drug activity, as well as the presence of irregular armed groups.