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Crime in Colombia: more law enforcement or more justice?

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Abstract

This study considers the effect that judicial and police efficiency exercised on crime in 25 of the 33 political-administrative divisions in Colombia during the period 2000–2011. Specifically, the study seeks to determine whether the reduction of crime was the result of increases in the cost of crime as a result of the strengthening of the country’s security forces, especially the National Police, or instead was due to the greater efficiency of the penal system resulting from a structural change stemming from Act 906 of 2004. To view this we propose a model of dynamic panel data that not only includes the individual and temporal effects of the variables of interest, but also allows us to understand the inertia in criminal behavior. The results indicate an inverse relationship between the number of crimes and the greater efficiency of the police and judicial action, which is consistent with the evidence reported in other international work. Robustness checks confirmed the validity of the findings.

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Notes

  1. It is noteworthy that literature has considered additional causes that have an impact on the deterrence of crime: informal institutions, civic norms, and building social capital (see [5, 6]). This approach assumes that civic norms may attach guilt and shame to criminal behavior, thus increasing its opportunity cost. Besides, associated networks may increase returns to noncriminal activities and raise detection probabilities. Despite the relevance of this analysis, the interest of this paper is to study the effects of two approaches mentioned above, which are directly related to police and justice efficiency.

  2. Arbeláez [7] states that in 2002, there was “[...] a daily average of 79 murders, eight kidnappings, six terrorist attacks; 14% of municipalities without police presence; one of three mayors exiled from his jurisdiction by threats from guerrilla groups, which had a presence in 30 of the 32 departments of Colombia, or paramilitary forces, present in 27 of them.”

  3. Article 250, Colombian Political Constitution. The change was introduced by the Constitution of 1991 and therefore it is not an essential part in this research, it is mentioned only as illustratively.

  4. The analysis presented in this paper is related to a period where the Defense and Democratic Security Policy (DSP) was prevailing. Thus, the main objective of police and justice was in reducing high-impact crimes such as murder, kidnapping, extortion, and theft. Some alternative crimes like corruption, fraud, money laundering and other “white collar” crimes, are not taken into account in this investigation. Probably, the deterrent effect of social control (informal institutions, civic norms) can be much clearer in those cases.

  5. Deterrence refers to the reduction of crime that occurs due to police presence, and incapacitation is the reduction of crime after catching criminals and therefore the emergence of minor criminals engaging in criminal activity.

  6. No individual data are available for eight departments because in these branches, there is no attorney’s office. These departments include Amazonas, Arauca, Casanare, Guainía, Guaviare, Vaupes, Vichada and San Andrés, Providencia and Santa Catalina.

  7. The last two are introduced as control variables used in the econometric specification because their behavior is guided more by characteristics of the internal armed conflict (public safety) than by crimes commonly associated with citizen safety, which is the subject of police action more than of military forces.

  8. The rate of police operation, iop j , t , results from the weighted sum of apprehension for the five different types of crime committed. The variable iop j , t considers the same 11 crimes as delj , t but groups together two types of homicides and six types of robberies, resulting in five major types: homicide, theft, terrorism, extortion and kidnapping. The relative weight of apprehensions associated with each type of crime are given by a standard indicator from the rate of police efficiency, indicatori , j , t, here understood as the number of captures for crimes committed for each offense type, in each year and department. Thus,

    $$ {\mathrm{i}\mathrm{op}}_{\mathrm{j},\mathrm{t}}=\frac{\sum_{\mathrm{i}=1}^{\mathrm{n}}\left({\mathrm{Apprehensions}}_{\mathrm{i},\mathrm{j},\mathrm{t}}\ast {\mathrm{Indicator}}_{\mathrm{i},\mathrm{j},\mathrm{t}}\right)}{\sum_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{Apprehensions}}_{\mathrm{i},\mathrm{j},\mathrm{t}}} $$

    where apprehensionsi , j , t is the number of seizures associated with criminal type i in department j in year t, and the average weight of seizures is defined as

    $$ {\mathrm{Indicator}}_{\mathrm{i},\mathrm{j},\mathrm{t}}=\frac{{\mathrm{EfficiencyRate}}_{\mathrm{i},\mathrm{j},\mathrm{t}}-{\mathrm{Min}}_{\mathrm{i},\mathrm{j}}\left({\mathrm{EfficiencyRate}}_{\mathrm{i},\mathrm{j},\mathrm{t}}\right)}{{\mathrm{Max}}_{\mathrm{i},\mathrm{j}}\left({\mathrm{EfficiencyRate}}_{\mathrm{i},\mathrm{j},\mathrm{t}}\right)-{\mathrm{Min}}_{\mathrm{i},\mathrm{j}}\left({\mathrm{EfficiencyRate}}_{\mathrm{i},\mathrm{j},\mathrm{t},}\right)} $$

    This, by construction, shows a measure whose range is between 0 and 1, where 0 represents a combination of no seizures and the worst relative efficiency rate for all crimes and 1 the best efficiency rate for each offense. The rate of police efficiency is defined as

    $$ {\mathrm{EfficiencyRate}}_{i, j, t}=\frac{Seizures_{i, j, t}}{Crimes_{i, j, t}} $$

    which may be greater than 1 when the number of seizures is greater than the number of crimes committed, either because there are more arrests or because seizures are made for crimes committed in prior periods.

  9. The index of judicial efficiency is defined as

    $$ {iej}_{j, t}=\frac{EvacuatedP_{j, t}}{NewP_{j, t}+{PriorP}_{j, t}} $$

    where EvacuatedP j , t refers to the processes that leave the system in the department j and year t, NewP j , t indicates the processes that entered the system in the same department and period t, and PriorP j , t refers accumulated processes by the system until t in j department.

  10. When calculating the total crime rate directly from 100,000 people in the population over the whole territory, and not as an average among political and administrative units, it is possible to identify a slight reduction between 2000 and 2011. Indeed, in that scenario the crime rate fell from 26.73 to 26.43 However, this reduction is relatively insignificant considering the length of the period.

  11. The scales of the maps are identical, and the quintiles represent the joint distribution of the 50 data points per crime committed in both 2000 and 2011.

  12. The political-administrative units with a value in iop below 0.5 increased from 12 in 2000 to 17 in 2011. However, the change was positive in 13 units, among which Risaralda, Cauca, Norte de Santander, Santander, Atlántico and Chocó stand out. The situation was different in departments such as Guajira, Valle del Cauca, Meta, Magdalena, Huila and Cesar, where the indicator deteriorated.

  13. The index of judicial efficiency was below 0.57 in 60% of the political-administrative units that were studied in 2011, whereas in 2000, only one of the units was below that level. Also, the indicator was worse in 2011 than in 2000 in all units except Caldas and the Atlantic departments. The worst judicial performance departments were Huila, Meta and Cesar.

  14. As mentioned above, in this paper we take into account only crimes affecting democratic and public security (as were called by the policing strategy implemented during the period 2002–2010), but not those “white collar crimes” related to other criminal actions such as corruption and fraud. Therefore, even though the impact informal institutions may have in reducing crime is recognized, this is not the approach taken into account in this analysis.

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Author information

Authors and Affiliations

  1. Department of Economics, School of Economics and Finance, Universidad EAFIT, Carrera 49 # 7 sur 50, Medellín-, Colombia

    Catalina Gómez, Hermilson Velásquez, Andrés Julián Rendón & Santiago Bohórquez

Authors
  1. Catalina Gómez
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  2. Hermilson Velásquez
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  3. Andrés Julián Rendón
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  4. Santiago Bohórquez
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Corresponding author

Correspondence to Catalina Gómez.

Appendix 1: Statistical tests

Appendix 1: Statistical tests

The results of statistical tests that validate the robustness of the model are presented in the table. Among these are unit root tests and the Sargan and Hansen tests to eliminate possible endogeneity problems.

Test

Characteristic

Statistical value

P value

Conclusion

Pesaran-Shin

Unit Root

-21.086

0.018

Some panels are stationary

AR(1)

Autocorrelation

-2.41

0.016

First lag correlation

AR(2)

Autocorrelation

-1.39

0.166

No second lag correlation

AR(3)

Autocorrelation

1.18

0.237

No third lag correlation

Sargan

Instrument validation

216.47

0.347

Instruments are valid

Hansen

Instrument validation

18.7

1

Instruments are valid

Hansen in levels.

Instrument validation in levels

-4.36

1

At levels, the instruments are valid

Hansen subgroup

Instrument validation in levels

14.56

0.951

The main instruments are valid

The Arellano-Bond test considering three laps ensures no autocorrelation between errors and lagged exogenous variables.

The Sargan and Hansen tests help ensure the validity of the instruments used in the estimated individual and overall models.

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Gómez, C., Velásquez, H., Rendón, A.J. et al. Crime in Colombia: more law enforcement or more justice?. Crime Law Soc Change 68, 233–249 (2017). https://doi.org/10.1007/s10611-017-9682-6

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  • DOI: https://doi.org/10.1007/s10611-017-9682-6

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