Research Design
The design of your study will
help you identify causality
Keeping all of this straight will help
you make stronger and more
interesting arguments about your
findings.
Time Dimension
• Cross-Sectional Studies
• Longitudinal Studies
– Trend-Repeated Cross-sectional
– Cohort-Event-based design
– Panel-Fixed sample
Nonspuriousness
• Random assignment
• Control Group
• Statistical controls
– Multivariate Regression
• Including control variables (which ones? – theory)
• Multiple Cases
– Most similar, or different case design
• Exploring alternative explanations
• Selecting a “hard” case
Crime and Support for Democracy
Kenneth E. Fernandez
Department of Political Science
University of Nevada, Las Vegas
Michele Kuenzi
Department of Political Science
University of Nevada, Las Vegas
Research Question
Does crime influence how citizens
evaluate democracies or influence their
level of support for democracy?
Why is this an Interesting Question?
• Scholars have noted that few studies, especially in
the field of political science, have examined crime
and its impact on society in a comparative manner
(Beirne 1997; Howard, et al. 2000).
• Current public opinion research suggests that the
issue of crime is of great concern to citizens
across the globe (Quann and Hung 2002)
• Many countries that have experienced recent
democratic reforms have also experienced
increasing crime rates (Bergman 2006).
What theories inform the study of
crime and democracy?
–Social Capital
–Rational Choice
–Modernization Theory
Crime is Often Ignored as a Factor in Democratization
– Much of the prior research on the development of
democracy focuses on economic conditions (Arat 1988;
Epstein et al. 2006; Lipset 1959; Przeworski et al.
2000).
– In fact, Kugler and Feng describe the recent application
of modernization theory as positing that “economic
development is a sufficient, rather than a necessary,
condition for democratic transitions” (1999, 140).
– We argue that crime and public disorder may pose even
greater challenges to the legitimacy and effectiveness of
democratic institutions
Social Capital Theories:
– Theory suggests that attitudes and feelings of
the masses regarding obligations within a
group, civic attachments, trust, and efficacy are
important determinants of democratic transition
and sustainability (Muller and Seligson 1994).
– Yet crime and violence is likely to reduce trust
and social capital (Lederman et al 2002).
Rational Choice:
– Citizens are treated as utility maximizing
consumers
– A political regime is expected to produce some
value or benefit to the consumer (Lane 1995).
– Regime support depends on how well citizens’
demands are met
– Thomas Hobbes argues that protection against
violence is the highest and most fundamental
human need and a citizen of the state has a
right to revoke its support and loyalty when the
state proves incapable of protecting its subjects.
The Paradox of Modernization theory:
– Modernization leads to increasing wealth,
leading to more literacy, education,
urbanization, leading to democratization
because citizens are less willing to put up with
oppressive, authoritarian behavior and more
willing to support democracy (Lipset 1959)
– But modernization may cause a breakdown in
traditional structures and values, an increase in
interaction, tension, and conflict. These social
changes then contribute to rising criminal
activity (Heiland and Shelley 1992).
Modernization Theory, Crime &
Democracy
– Consolidating both the political science and the
criminology/sociology literature on
modernization theory, we argue that socioeconomic conditions, as well as, crime and
public safety influence citizens’ support for
democracy.
Methodology: Macro or Micro Level
Analysis?
– Much of the research testing the modernization
theory uses a macrolevel approach utilizing the
nation-state at time t as the unit of analysis.
Aggregate national characteristics (i.e., per
capita GDP) are then used as predictors of
some measure of democracy.
– Yet Lipset (1959) posits that increases in wealth
and income leads to democratic transition
because it affects citizens’ values.
– We would like to examine this microlevel
statement.
Microlevel Analysis:
– An examination of citizen attitudes is
appropriate because the success of
democratic consolidation in these emerging
democracies is often linked to citizens’
support for democracy and perceptions of
government performance (Hiskey and Bowler
2005; Lagos 2001; Diamond 1999; Lipset
1959).
DATA:
• Afrobarometer (AB) and Latinbarometro (LB)
Survey Data
• The AB and LB together contain 33 countries (16
in Africa and 17 in Latin America).
Two Statistical Approaches
– Analysis of all countries pooled together (over
18,000 respondents in African and 13,000 in
Latin America
– Analysis of 4 cases
Case Selection:
– Initial Case - NIGERIA: Like many other
African countries, Nigeria experienced a
transition to democracy in the 1990s. We chose
Nigeria because crime is a very salient issue in
this country, and Nigeria has been well known
for mob justice or what has been called “jungle
justice”
– Most Different Systems Design: We
performed a cluster analysis to find a case in
the Afrobarometer data that was “most different”
to Nigeria in relation to three factors: crime,
democracy and per capita GDP.
Cluster Analysis:
The Euclidean distance between two cases is
calculated by finding the square root of the sum
of the squared differences between the two
cases for each of the three variables (crime
rate; per capita GDP; level of democracy):
x
i
 x j    yi  y j   zi  z j 
2
2
2
MALAWI: Nigeria has a per capita GDP nearly 3
times that of Malawi, but Nigeria has a
substantially higher reported victimization rate
(Nigeria had the highest reported attacks of the 14
African cases and Malawi had the lowest). Both
countries were given a score of 4 for political rights
and civil liberties by Freedom House in 2005.
CHILE & NICARAGUA: Both Chile and Nicaragua
have modest crime rates compared to the rest of
Central and South America, but differ greatly on
GDP and level of democracy. Chile has a per
capita GDP almost 7 times higher than Nicaragua
and Chile has a score of 1 for both political rights
and civil liberties while Nicaragua scored a 3 for
both.
THE 4 CASES: The results seem to make intuitive
sense. There is substantial variation in GDP
across cases, they vary in crime rates from low to
moderate to high levels of victimization, and levels
of political freedom and civil liberties varied from
the highest (score of 1) to moderate/low (score of
4).
Operationalization
Dependent Variables: Attitudes toward Democracy
Support for Democracy
• Which of these three statements is closest to your
own opinion?
• A: Democracy is preferable to any other kind of
government.
• B: In some circumstances, a non-democratic
government can be preferable.
• C: For someone like me, it doesn’t matter what kind
of government we have.
• Recoded so that the value on this variable is 1 if the
response was A, and 0 otherwise.
• Satisfaction with Democracy
• Overall, how satisfied are you with the way
democracy works in __________.? Are you:
• 0=Tanzania/Nigeria is not a democracy,
1=Not at all satisfied, 2=Not very satisfied,
3=Fairly satisfied, 4=Very satisfied.
Chile and Nicaragua:
• In general, would you say that you are very
satisfied, fairly satisfied, not very satisfied or
not at all satisfied with the way democracy
works in (country)? 4=Very satisfied - 1=Not
at all satisfied
Independent Variables
• Experience with Crime
• Comparative assessments of safety from
crime and violence
• Crime Performance
Control Variables
• Demographic variables: gender, level of
poverty, age, education
• Other variables: political engagement,
identification with the party in power, and
subjective assessments of satisfaction with
life and the economy and government
service delivery
TABLE 7: ATTITUDES TOWARD DEMOCRACY II
Model 7
Model 8
Support
Support Democracy
Satisfaction with
Satisfaction with
Democracy
(Nicaragua)
Democracy
Democracy
(Chile)
(Chile)
(Nicaragua)
Est. Method
Logit
Logit
0.3019**
(0.1336)
0.3320***
(0.1180)
0.4495***
(0.1365)
0.3620***
(0.1107)
-0.0176
(0.1896)
-0.2076
(0.1929)
-0.0202
(0.1776)
0.1336
(0.1672)
0.4759***
(0.1216)
0.3663***
(0.1002)
0.0278
(0.1278)
0.0183
(0.0856)
-0.0327
(0.0568)
-0.0232
(0.0679)
0.0366
(0.0507)
0.0227
(0.0581)
0.0182
(0.0648)
-0.1179**
(0.0561)
0.2107***
(0.0662)
0.1414***
(0.0526)
0.4059***
(0.1296)
0.0094
(0.1179)
0.7059***
(0.1353)
0.4070***
(0.0937)
0.2248*
(0.1226)
-0.0108
(0.1104)
0.4065***
(0.1146)
0.2658***
(0.1028)
Education
0.0384
(0.0309)
-0.0092
(0.0234)
0.0484
(0.0305)
0.0066
(0.0195)
Poverty
0.1871
(0.1437)
-0.0438
(0.1099)
0.2208
(0.1464)
0.0152
(0.0908)
Female
0.0260
(0.1852)
-0.2137
(0.1839)
-0.0736
(0.1750)
-0.6451
(0.1668)
Age
0.0080
(0.0062)
0.0143**
(0.0065)
0.0149***
(0.0057)
0.0114*
(0.0064)
-4.1139***
(0.7574)
1000
0.0903
74.65
0.0000
-0.9637
(0.6937)
604
0.0538
32.55
0.0006
1018
0.1159
133.45
0.0000
640
0.0548
73.55
0.0000
War on Crime
Victim of Crime
Discuss Politics
TV-News
Service Delivery
Economy
Quality of Life
Cons
# obs
Pseudo R2
LR chi2
Prob > chi2
Ordered Logit
Ordered Logit
Results
Attitudes toward Democracy
Feeling Safe
• Nigerians who report feeling better off in
terms of safety from crime and violence are
significantly more likely to:
– Support democracy
– Be satisfied with the way democracy is working
Crime Victimization
• Nigerians and Malawians who report a
higher number of experiences with crime
victimization have significantly lower levels
of support for democracy.
• There appears to be no relationship
between crime victimization and attitudes
toward democracy in the Chile and
Nicaragua countries.
Conclusion and Implications
• Perceptions of safety and government
performance in the area of crime
affect attitudes toward democracy.
• Crime victimization generally does not
appear related to satisfaction with
democracy.
Independent Sample T-test
Formula
t=
X1  X 2
s X1  X 2
 N1s1  N 2 s2
 
 N1  N 2  2
2
sx1  x2
2
 N1  N 2 


 N N 
 1 2 
Independent-samples t-tests
•
But what if you have more than two groups?
•
One suggestion: pairwise comparisons (t-tests)
Multiple independent-samples t-tests
# groups
2 groups
3 groups
4 groups
5 groups
...
10 groups
•
That’s a lot of tests!
# tests
= 1 t-test
= 3 t-tests
= 6 t-tests
= 10 t-tests
= 45 t-tests
Inflation of familywise error rate
• Familywise error rate – the probability of making
at least one Type I error (rejecting the Null
Hypothesis when the null is true)
• Every hypothesis test has a probability of making a
Type I error (a).
• For example, if two t-tests are each conducted
using a = .05, there is a .0975 probability of
committing at least one Type I error.
Inflation of familywise error rate
• The formula for familywise error rate:
1  1  a 
# groups
# tests
c
nominal alpha
familywise alpha
2 groups
1 t-test
.05
1  1  a   1  .95   .05
3 groups
3 t-tests
.05
1  1  a   1  .95   .14
4 groups
6 t-tests
.05
1  1  a   1  .95   .26
5 groups
10 t-tests
.05
1  1  a   1  .95   .40
45 t-tests
.05
1  1  a   1  .95   .90
c
c
c
c
1
3
6
10
...
10 groups
c
45
Analysis of Variance: Purpose
• Are there differences in the central
tendency (mean) of groups?
• Inferential: Could the observed differences
be due to chance?
Assumptions of ANOVA
•
Normality – scores should be normally distributed within
each group.
•
Homogeneity of variance – scores should have the same
variance within each group.
•
Independence of observations – observations are
randomly selected.
Logic of Analysis of Variance
• Null hypothesis (Ho): Population
means from different conditions are
equal
– m1 = m2 = m3 = m4
• Alternative hypothesis: H1
– Not all population means equal.
Lets visualize total amount of
variance in an experiment
Total Variance = Mean Square Total
Between Group Differences
(Mean Square Group)
Error Variance
(Individual Differences + Random Variance)
Mean Square Error
F ratio is a proportion of the MS group/MS Error.
The larger the group differences, the bigger the F
The larger the error variance, the smaller the F
Logic--cont.
• Create a measure of variability among
group means
– MSgroup
• Create a measure of variability within
groups
– MSerror
Example: Quiz Scores and
Attitudes on Statistics
Loves Statistics
Hates Statistics
Indifferent
9
4
8
7
7
4
6
5
5
11
6
6
12
3
7
•
•
Find the sum of squares between groups
SSbetween   N groupX
 Ntotal X
2
total
Find the sum of squares within groups
SS within   X
•
2
group
2
total
  N group X
2
group
Total sum of squares = sum of between
group and within group sums of squares.
SStotal   X
2
total
 Ntotal X
2
total
•
•
•
•
•
•
•
•
To find the mean squares: divide each
sum of squares by the degrees of
freedom (2 different dfs)
Degrees of freedom between groups =
k-1, where k = # of groups
Degrees of freedom within groups = n-k
MSbetween= SSbetween/dfbetween
MSwithin= SSwithin/dfwithin
F = MSbetween / MSwithin
Compare your F with the F in Table D