Tables 1 through 4 detail the statistical output of the bivariate regression model for Mexican and US cities. Tables 1 and 3 capture descriptive statistics describing the relationship between GDP per capita, homicides and drug arrests from 2000 to 2010. Tables 2 and 4 provide descriptive statistics detailing the relationship between unemployment rates, homicides and drug arrests during the same period. The author specifically chose to capture and record the Adjusted R Square correlation coefficient, which is a more conservative estimate of the relationship between the dependent and independent variables; the T-Statistic to compare the ratio of the Adjusted R Square and the Standard Error; the P-Value at a 95% confidence interval to determine if the output was produced by chance; and the Standard Error to capture the degree of statistical variance.
Mexican Descriptive Statistics – GDP Per Capita: The results of the regression analysis varied. When analyzing the relationship between municipal GDP per capita and homicides, the correlation coefficient ranged from -.13 to .68. In Ciudad Juarez and Nogales, there was a moderate to strong positive relationship between the independent and dependent variable comfortably within the 95% confidence interval. Monterrey represented a weak statistical relationship with a higher P-Value outside of the confidence interval. Albeit weak and not statistically significant, Nuevo Laredo was the only city to have a negative correlation between GDP per capita and homicides with a P-Value outside the confidence interval.
Table 1: Effects across sampled Mexican cities of GDP per capita and municipal homicides & drug arrests from 2000 - 2010.
| |
|
|
Adjusted R Square
|
T-Stat
|
P-Value (< .05)
|
Standard Error
|
|
Ciudad Juarez
|
|
|
|
|
| |
Homicides
|
0.544476694
|
3.428920563
|
0.008969112
|
0.201404296
|
| |
Drug Arrests
|
0.35986242
|
-2.344635039
|
0.051492456
|
0.196298428
|
|
Monterrey
|
|
|
|
|
| |
Homicides
|
0.141138748
|
1.62583031
|
0.138430435
|
0.956333002
|
| |
Drug Arrests
|
0.579699783
|
-3.469007567
|
0.010419856
|
0.340978899
|
|
Nogales
|
|
|
|
|
|
| |
Homicides
|
0.684643319
|
4.765514209
|
0.001021756
|
1.965061441
|
| |
Drug Arrests
|
0.661769322
|
4.080747074
|
0.00468527
|
1.070454034
|
|
Nuevo Laredo
|
|
|
|
|
| |
Homicides
|
-0.13123078
|
-0.433532507
|
0.67978108
|
8.767413742
|
| |
Drug Arrests
|
-0.030386475
|
0.890824017
|
0.407323506
|
0.669702762
|
Comparisons between GDP per capita and drug arrests was a little more consistent across the sampled cities. Monterrey and Nogales possessed a moderate to strong positive relationship between the independent and dependent variables with an acceptable level of statistical probability. Ciudad Juarez represented a weak to moderate positive statistical relationship with a P-Value just inside of the confidence interval. Again, Nuevo Laredo was the only city to have a negative correlation between GDP per capita and homicides with a P-Value well outside the confidence interval (See Table 1 for statistics).
Mexican Descriptive Statistics – Unemployment Rates: Like the relationship between GDP and drug indicators, the results of this regression analysis varied as well. When analyzing the relationship between municipal unemployment rates and homicides, the only city to have a moderate to strong positive relationship between the two variables was Ciudad Juarez. Monterrey, Nogales, and Nuevo Laredo all possessed relatively weak negative correlations outside of the confidence interval.
Table 2: Effects across sampled Mexican cities of unemployment rates and municipal homicides & drug arrests from 2000 - 2010.
| |
|
|
Adjusted R Square
|
T-Stat
|
P-Value (< .05)
|
Standard Error
|
|
Ciudad Juarez
|
|
|
|
|
| |
Homicides
|
0.629461281
|
4.241194756
|
0.002170463
|
0.000407756
|
| |
Drug Arrests
|
0.161580691
|
-1.594291371
|
0.154900041
|
0.000503877
|
|
Monterrey
|
|
|
|
|
| |
Homicides
|
-0.102671624
|
0.262455809
|
0.798878843
|
0.001747341
|
| |
Drug Arrests
|
-0.011692969
|
-0.952647581
|
0.372497005
|
0.00060256
|
|
Nogales
|
|
|
|
|
|
| |
Homicides
|
-0.050294589
|
0.721899068
|
0.488686839
|
0.007018901
|
| |
Drug Arrests
|
0.255086742
|
-1.933780095
|
0.094395555
|
0.003449755
|
|
Nuevo Laredo
|
|
|
|
|
| |
Homicides
|
-0.047665658
|
0.738261384
|
0.479163163
|
0.008965468
|
| |
Drug Arrests
|
0.612666802
|
3.695138966
|
0.007704203
|
0.000288154
|
When analyzing the relationship between unemployment rates and drug arrests in the sampled cities, the correlation coefficient ranged from -.01 to .61. In general, the relationship between the independent and dependent variables was weak and not statistically significant. However, Nuevo Laredo did possess a moderate to strong positive correlation well within the confidence interval (See Table 2 for statistics).
US Descriptive Statistics – GDP Per Capita: The correlation between GDP per capita and homicides within the sampled US cities was not statistically significant. Tucson had a weak positive relationship outside of the 95% confidence interval. El Paso and Laredo both had very weak negative relationships outside of the confidence interval. Phoenix was the only city to have a weak to moderate positive correlation with an acceptable P-Value. The relationship between GDP per capita and drug arrests was a little more promising. While Tucson, El Paso and Laredo possessed statistically insignificant correlations with high P-Values, Phoenix did have a moderate positive correlation within the confidence interval (See Table 3 for statistics).
Table 3: Effects across sampled US cities of GDP per capita and municipal homicides & drug arrests from 2000 - 2010.
| |
|
|
|
|
|
|
| |
|
|
Adjusted R Square
|
T-Stat
|
P-Value (< .05)
|
Standard Error
|
|
Phoenix
|
|
|
|
|
|
| |
Homicides
|
0.380319137
|
2.671579822
|
0.025556215
|
12.97783895
|
| |
Drug Arrests
|
0.437617519
|
2.963358355
|
0.015872699
|
0.929542853
|
|
Tucson
|
|
|
|
|
|
| |
Homicides
|
0.07757121
|
1.35681437
|
0.207891911
|
46.9854012
|
| |
Drug Arrests
|
-0.034829979
|
0.766905574
|
0.814507936
|
0.436375048
|
|
El Paso
|
|
|
|
|
|
| |
Homicides
|
-0.099513979
|
0.308103175
|
0.765015353
|
36.13363105
|
| |
Drug Arrests
|
0.093131692
|
-1.423713237
|
0.188260502
|
0.254950273
|
|
Laredo
|
|
|
|
|
|
| |
Homicides
|
-0.101800105
|
0.275783417
|
0.788942071
|
26.22775372
|
| |
Drug Arrests
|
0.22336426
|
-1.968768449
|
0.080501433
|
1.365757051
|
US Descriptive Statistics – Unemployment Rates: The results of this regression analysis varied for US cities as well. In regards to unemployment and aggregate homicide statistics, Phoenix and El Paso both possessed a weak to moderate positive correlation with a low probability that the results were influenced by a third variable. On the other hand, Tucson and Laredo had very weak correlation coefficients with a P-Value outside of the confidence interval. With correlation coefficients ranging from -.02 to -.10 with P-Values as high as -.85, the relationship between unemployment and drug arrests was not found to be statistically significant across the four sampled cities (See Table 4 for statistics).
Table 4: Effects across sampled US cities of unemployment rates and municipal homicides & drug arrests from 2000 - 2010.
| |
|
|
Adjusted R Square
|
T-Stat
|
P-Value (< .05)
|
Standard Error
|
|
Phoenix
|
|
|
|
|
|
| |
Homicides
|
0.50914101
|
-3.372306262
|
0.008226809
|
1.581220162
|
| |
Drug Arrests
|
-0.026934339
|
2.287100805
|
-0.858906818
|
0.412682922
|
|
Tucson
|
|
|
|
|
|
| |
Homicides
|
0.056170372
|
1.946327032
|
-1.262985565
|
0.238332688
|
| |
Drug Arrests
|
-0.103320966
|
2.104359558
|
0.252082732
|
0.806639447
|
|
El Paso
|
|
|
|
|
|
| |
Homicides
|
0.371013407
|
0.956498609
|
0.02751535
|
2.626516717
|
| |
Drug Arrests
|
-0.062416638
|
1.243114352
|
0.642264118
|
0.536716579
|
|
Laredo
|
|
|
|
|
|
| |
Homicides
|
-0.10942067
|
1.363668125
|
0.117104385
|
0.909348985
|
| |
Drug Arrests
|
-0.103900739
|
1.360271424
|
-0.242457204
|
0.813860846
|
Analysis: Though the data points to a weak or nonexistent relationship between selected economic indicators, homicides and drug arrests in both Mexico and the United States, a few moderate to strong correlations were identified that warrant further analysis. In Mexico, the regression model found a positive relationship between GDP per capita, municipal homicides and drug arrests in both Ciudad Juarez and Nogales. The data seemingly disproves H1, which predicted a decrease in homicides and drug arrests as GDP per capita increased in the sampled cities. However, it is worth noting that both Ciudad Juarez and Nogales recorded a precipitous increase in homicides starting in 2008. Despite steady year-to-year increases in GDP per capita in Ciudad Juarez and Nogales from 2000 to 2010, murders held steady or decreased from 2000 to 2007 (see Tables 6 & 7 for data). This dramatic increase in homicides closely coincides with Mexican President Felipe Calderon’s deployment of troops to Northern Mexican states as part of “Operation Michoacana,” coined after both the Mexican state and the organized crime family. Both residents and human rights groups have directly attributed the increase in violence to confrontations between government troops and cartel enforcers, who routinely engage in running gun battles throughout the urban centers of cities like Juarez and Nogales (Wilkinson, 2009). When the data sets are analyzed excluding the 2008, 2009 and 2010 statistics, the results were drastically different for Ciudad Juarez. The Adjusted R Square was -.073 with a P-Value slightly outside of the 95% confidence interval as opposed to .544 cited in Table 1. Unfortunately, excluding the outlier statistics still does not explain the relationship between GDP per capita and homicides in Nogales; the Adjusted R Square is still .585 and slightly outside of the confidence interval.Continued on Next Page »
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Appendix
Table 5: Arrests for drug-related offenses by municipality in Mexico from 2000 – 2010.
| |
|
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Ciudad Juarez
|
3029
|
2727
|
2717
|
2886
|
2587
|
2851
|
2824
|
2595
|
936
|
*
|
*
|
|
Monterrey
|
2226
|
2525
|
2713
|
2642
|
2109
|
1709
|
1448
|
1529
|
1438
|
*
|
*
|
|
Nogales
|
|
610
|
625
|
447
|
460
|
608
|
592
|
615
|
743
|
862
|
*
|
*
|
|
Nuevo Laredo
|
491
|
437
|
314
|
310
|
1190
|
1458
|
1305
|
1398
|
1381
|
*
|
*
|
Statistics gathered from the Instituto Nacional de Estadística y Geografía (INEGI) at www.inegi.org.mx. Per the INEGI, drug arrests are listed under the blanket arrest “en material de narcoticos,” which includes a large number of different drugs offenses, including but not limited to illicit drug consumption, possession with intent to distribute narcotics, and drug smuggling activities. * = Statistics unavailable for the listed year.
Table 6: Municipal homicides of sampled Mexican cities from 2000 – 2010.
| |
|
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Ciudad Juarez
|
385
|
371
|
399
|
318
|
338
|
320
|
315
|
401
|
1372
|
2000
|
2545
|
|
Monterrey
|
497
|
568
|
533
|
524
|
510
|
619
|
658
|
784
|
732
|
704
|
1287
|
|
Nogales
|
|
31
|
52
|
32
|
42
|
43
|
60
|
58
|
78
|
138
|
174
|
226
|
|
Nuevo Laredo
|
115
|
71
|
79*
|
106
|
97*
|
154*
|
199
|
116
|
119
|
119
|
155
|
Municipal statistics gathered from the Instituto Nacional de Estadística y Geografía (INEGI) at www.inegi.org.mx. State-level statistics were gathered from the Transborder Institute at http://justiceinmexico.org/data-portal/2480-2/. For the missing years, a percent representation was derived by dividing the municipal homicides by state level homicides. The percentages were averaged together to calculate an average percent representation. The average percent was multiplied by state level statistics for the years where data is unavailable to generate a predictive statistic. * = Homicide statistics were unavailable for the listed year.
Formula
City 2000 / State 2000 + City 2001 / State 2001 + City 2003 / State 2003 + City 2006 / State 2006 + City 2007 / State 2007 + City 2008 / State 2008 + City 2009 / State 2009 + City 2010 / State 2010 = Average Percent Representation (APR)
APR x State Homicides = Number of Homicides for No Year Data
Table 7: Gross Domestic Product (GDP) per capita of sampled Mexican cities from 2000 – 2010.
| |
|
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Ciudad Juarez
|
1330
|
1294
|
1434
|
1560
|
1656
|
1796
|
2250
|
2174
|
2507
|
2782
|
715*
|
|
Monterrey
|
1541
|
1704
|
2118
|
2207
|
3356
|
2955
|
3476
|
3078
|
3516
|
3253
|
3272
|
|
Nogales
|
|
1464
|
1455
|
1562
|
1706
|
1864
|
1712
|
1963
|
2820
|
3376
|
2916
|
3077
|
|
Nuevo Laredo
|
***
|
4524
|
3656
|
4460
|
5349
|
3514
|
4177
|
5096
|
6248
|
8832
|
6581
|
Statistics gathered from the Instituto Nacional de Estadística y Geografía (INEGI) at www.inegi.org.mx. GDP is measured in Mexican pesos. * = Based on partial-year data; *** = Data unavailable for that year.
Table 8: Unemployment rates of sampled Mexican cities from 2000 – 2010.
| |
|
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Ciudad Juarez
|
1.7
|
2.6
|
4.2
|
3.8
|
1.8
|
2.1
|
2.7
|
2.6
|
4.2
|
7.2
|
5.4
|
|
Monterrey
|
2.9
|
2.9
|
4.4
|
4.3
|
5.7
|
4.7
|
4.7
|
4.5
|
4.3
|
7.2
|
4.3
|
|
Nogales
|
|
2.7
|
3.9
|
6.7
|
5.8
|
5.4
|
3.4
|
2.9
|
2.9
|
4
|
5.6
|
5.6
|
|
Nuevo Laredo
|
2.7
|
3.1
|
3.6
|
3.2
|
4.7
|
4.1
|
4
|
4.1
|
4.5
|
6.4
|
4.8
|
Statistics gathered from the Instituto Nacional de Estadística y Geografía (INEGI) at www.inegi.org.mx. This data represents the statistical average over a twelve month reporting period.
Table 9: Annual drug arrest totals of sampled US cities from 2000 – 2010.
| |
|
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Phoenix
|
Sale & Distribution
|
2,100
|
2,053
|
2,421
|
2,623
|
1,929
|
1,218
|
1,678
|
1,399
|
1,258
|
1,281
|
1,242
|
| |
Possession
|
3,736
|
3,453
|
3,268
|
3,615
|
5,147
|
5,763
|
5,053
|
5,546
|
5,113
|
5,266
|
4,467
|
| |
Total
|
|
5,836
|
5,506
|
5,689
|
6,238
|
7,076
|
6,981
|
6,731
|
6,945
|
6,371
|
6,547
|
5,709
|
| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Tucson
|
Sale & Distribution
|
576
|
648
|
678
|
674
|
803
|
826
|
708
|
853
|
869
|
973
|
753
|
| |
Possession
|
5,597
|
5,599
|
5,730
|
6,132
|
6,555
|
7,018
|
6,365
|
5,970
|
5,681
|
6,474
|
5,774
|
| |
Total
|
|
6,173
|
6,247
|
6,408
|
6,806
|
7,358
|
7,844
|
7,073
|
6,823
|
6,550
|
7,447
|
6,527
|
| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
El Paso
|
Sale & Distribution
|
149
|
74
|
17
|
94
|
28
|
109
|
183
|
109
|
180
|
195
|
263
|
| |
Possession
|
3,355
|
3,862
|
3,398
|
3,516
|
3,364
|
2,930
|
2,685
|
3,902
|
4,561
|
4,473
|
4,028
|
| |
Total
|
|
3,504
|
3,936
|
3,415
|
3,610
|
3,392
|
3,039
|
2,868
|
4,011
|
4,741
|
4,668
|
4,291
|
| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Laredo
|
Sale & Distribution
|
*
|
4
|
2
|
*
|
*
|
*
|
*
|
*
|
3
|
12
|
13
|
| |
Possession
|
797
|
769
|
742
|
752
|
871
|
833
|
1,002
|
1,031
|
864
|
1,029
|
928
|
| |
Total
|
|
797
|
773
|
744
|
752
|
871
|
833
|
1,002
|
1,031
|
867
|
1,041
|
941
|
Data obtained from the Bureau of Justice Statistics. Statistics gathered through the Arrest Analysis Tool found at http://bjs.ojp.usdoj.gov/index.cfm?ty=datool&surl=/arrests/index.cfm#. This data represents total arrest tallies recorded by major municipal police departments in each city. Statistics are voluntarily provided by each department annually. The statistics have been subdivided into two categories: arrests for the sale or manufacturing of illicit substances and arrests for the possession substances for personal use. Drug violation totals in each of the four cities have been captured. * = Denotes a lack of available statistics in that given year.
Table 10: Municipal homicides of sampled US cities from 2000 – 2010.
| |
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Phoenix
|
|
152
|
209
|
177
|
241
|
202
|
220
|
235
|
212
|
167
|
122
|
116
|
|
Tucson
|
|
60
|
42
|
47
|
47
|
55
|
55
|
51
|
49
|
65
|
35
|
51
|
|
El Paso (SD)
|
5
|
4
|
3
|
0
|
6
|
4
|
8
|
3
|
2
|
4
|
2
|
|
El Paso (PD)
|
20
|
20
|
14
|
21
|
11
|
14
|
13
|
17
|
17
|
12
|
5
|
|
El Paso (Total)
|
25
|
24
|
17
|
21
|
17
|
18
|
21
|
20
|
19
|
16
|
7
|
|
Laredo
|
|
10
|
8
|
7
|
29
|
15
|
18
|
22
|
10
|
10
|
17
|
9
|
Data obtained from the Federal Bureau of Investigation, Uniform Crime Report. Statistics gathered through the UCR Table Building tool found at http://www.ucrdatatool.gov/. This data represents homicide totals recorded by major municipal police departments in each city. Statistics are voluntarily provided by each department annually. * = Individual homicide statistics are collected and distributed to the FBI by the El Paso County Sheriff's Department and the El Paso City Police Department. Statistics are listed separately (SD for Sheriff's Department and PD for the City Police Department) and together (SD and PD added to represent the total number of homicides).
Table 11: Gross Domestic Product (GDP) per capita of sampled US cities from 2000 – 2010.
| |
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Phoenix
|
|
41050
|
41107
|
41264
|
42494
|
43006
|
44658
|
46290
|
46112
|
44499
|
40182
|
40375
|
|
Tucson
|
|
29240
|
29222
|
28326
|
29508
|
29589
|
30605
|
31365
|
31975
|
31442
|
28870
|
28387
|
|
El Paso
|
|
29500
|
29535
|
30272
|
30062
|
29846
|
30029
|
30854
|
30505
|
30323
|
28984
|
29759
|
|
Laredo
|
|
22050
|
22119
|
22559
|
22558
|
22266
|
22521
|
22295
|
22188
|
22920
|
20991
|
21440
|
Data obtained from the US Department of Commerce, Bureau of Economic Analysis. Statistics gathered through the BEA's Interactive Data Service tool at http://www.bea.gov/itable/. This data represents the statistical average over a twelve month reporting period. GDP is measured in US dollars.
Table 12: Unemployment rates of sampled US cities from 2000 – 2010.
| |
|
2000
|
2001
|
2002
|
2003
|
2004
|
2005
|
2006
|
2007
|
2008
|
2009
|
2010
|
|
Phoenix
|
|
3.3
|
4.2
|
5.6
|
5.2
|
4.5
|
4.1
|
3.6
|
3.2
|
5.3
|
9.3
|
9.8
|
|
Tucson
|
|
3.7
|
4.3
|
5.7
|
5.3
|
4.6
|
4.5
|
3.9
|
3.6
|
5.6
|
9
|
9.4
|
|
El Paso
|
|
6.8
|
7.3
|
8.2
|
8.8
|
7.6
|
7
|
6.7
|
5.9
|
6.3
|
8.8
|
9.8
|
|
Laredo
|
|
6.1
|
6.6
|
7.3
|
7.4
|
6.7
|
6
|
5.4
|
4.7
|
5.4
|
8.4
|
8.9
|
Data obtained from the US Department of Labor, Bureau of Labor Statistics. Statistics gathered through the BLS Tools application at http://data.bls.gov/cgi-bin/surveymost?la. This data represents the statistical average over a twelve month reporting period.
