Representative Bureaucracy & Economic Prosperity Nikko Brady, Ariam Ford & Tremayne Youmans │UA 702 Final Project
Our Project Our Interest: To assess the impact of an existing racially or ethnically representative municipal leadership team on the economic and social prosperity of a city and its residents. The Impetus and Relevance: ◦ In Detroit in the 1970s, there was political unrest surrounding the concerns of marginalized Black citizens who disapproved of their social, political and economic exclusion. ◦ Since that time, Detroit has seen a dramatic increase in Black leadership. However it remains unstudied whether or not the onset of representative bureaucracy has any positive effects or significant influence on the economic trajectory of the city and its residents. ◦ This idea led us to explore the general concept of representative bureaucracy in relation to the economic prosperity of a city. ◦ Representative bureaucracy is a prominent idea in the fields of education, public policy, and corporate management. Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Research Question: What is the relationship between having leadership that racially/ethnically represents the majority population of a city AND that city’s economic prosperity?
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Sample & Size 50 Capital Cities of the United States
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Variables Dependent Variable ◦ Economic Prosperity
Independent Variables ◦ Representative Bureaucracy ◦ Educational Attainment ◦ Industry Breakdown ◦ Immigration ◦ Presence of Arts Organizations ◦ Health Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Concept Economic Prosperity
Operationalized Variable Unemployment Rate (unemployment)
Representative Bureaucracy
Whether or not the Mayor was of same culture/race as the majority culture/race in the population (repbureac)
Educational Attainment
% of population over 25 with less than a High School Diploma (edlowest) % of business establishments in professional, scientific and technical services (totalwhitecollar) % Foreign Born (foreignborn) Ratio of arts establishments to every 5000 people (artspop) Ratio of health care establishments to every (health)
Industry Breakdown
Immigration Presence of Arts Organizations Health
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Hypotheses Dependent Variable: Economic Prosperity ─────────
Racially Representative Government (-) Educational Attainment (+) Industry Breakdown(+) Immigration(-) Presence of Arts Organizations(+) Presence of Health Facilities(+) Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Data Collection ◦ Census 2000 ◦ Economic Census 2002
◦ Mayors
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Descriptive Statistics N
Minimum
Maximum
Mean
Std. Deviation
Unemployment Rate (%)
50
1.70
9.10
4.21
1.62
Mayor same race/culture as majority population?
50
1.00
2.00
1.18
.39
50
4.85
39.16
17.24
7.10
% of industry establishments in information, proffesional, educational, or health care
47
11.73
26.38
18.45
3.65
% Foreign Born
50
.30
25.80
8.07
6.83
Ratio of arts establishments to every 5000 people
50
.94
8.60
2.75
1.65
Ratio of healthcare establishments to every 1000 people
50
2.06
8.94
4.23
1.59
Valid N (listwise)
47
Percent of population over 25 with less than a HS diploma
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Unemployment Rate
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Mayor's Race
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Educational Attainment
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Industry Type
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Immigration
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram Arts Establishments
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Histogram
Healthcare Establishments
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Scatter Plots
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
ANOVA
◦ Variables ◦ Grouping Variable: Unemployment Rate Categories ◦ Low Unemployment = 1.7-3.3% ◦ Medium Unemployment= 3.4%-4.4% ◦ High Unemployment=4.5%-9.1% ◦ Test Variables ◦ Repbureac ◦ Edlowest ◦ Totalwhitecollar ◦ Foreignborn ◦ Artspop ◦ Test/Technique ◦ ANOVA to determine if there is a significant difference between unemployment rate categories in terms of each independent variable ◦ Hypotheses ◦ H0: µ1= µ2= µ3 ◦ H1: at least one of the population means is different in terms of the various test variables ◦ Sampling Distribution: F-distribution ◦ α =0.05 ◦ F(critical)=3.6 ◦ F(obtained) > F(critical) = reject null
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
ANOVA Variable
F
Sig.
Means
.056
Low unemployment ≈ Yes Medium unemployment ≈ Yes High unemployment ≈ Yes
.000
Low unemployment = 13.13% Medium unemployment = 15.51% High unemployment = 22.99%
.543
Low unemployment = 0.18% Medium unemployment = 0.18% High unemployment = 0.19%
.062
Low unemployment = 4.92% Medium unemployment = 9.69% High unemployment = 9.69%
1.08
Low unemployment ≈ 3 Medium unemployment ≈ 3 High unemployment ≈ 2
.081
Low unemployment ≈ 5 Medium unemployment ≈ 4 High unemployment ≈ 4
Mayor same race/culture as majority population? 3.061 % Population over 25 with less than HS diploma 13.393 % of industry establishments in information, professional, educational or health care
.619
% Foreign born 2.959 Ratio of arts establishments to every 5000 people 2.338 Ratio of health care establishments for every 1000 people 2.658
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Correlation Matrix
Pearson Correlation
% Unemployment
repbureac
edlowest
totalwhitecollar
foreignborn
artspop
health
.236
.600
.257
.154
-.282
-.251
.099
.000
.081
.287
.047
.078
50
50
47
50
50
50
Sig. (2-tailed)
N
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Hypothesized Multivariate Regression Model
Unemployment = a + b1repbureac + b2edlowest + b3totalwhitecollar+ b4foreignborn+ b5artspop+ b6health
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Multivariate Regression Model Unstandardized Coefficients Constant repbureac
B .130 .060
Std. Error 1.461 .508
edlowest totalwhitecollar foreignborn
.150 12.103 -.057
.033 5.394 .032
artspop health
-.071 -.025
.148 .147
Standardized Coefficients
Sig.
Beta
.015 .655 .272 -.244 -.066 -.024
.929 .906 .000 .030 .083 .633 .864
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Multivariate Regression Model: Ordinary Least Squares Equation unemployment= .130 + 0.060(repbureac)+ 0.150(edlowest)+ 12.103(totalwhitecollar) - 0.057(foreignborn)- 0.071(artspop) - 0.025(health)
R.
R Square
Adjusted R Square
Std. Error of the Estimate
.680
.463
.382
1.27611
Sum of Squares
df
Mean Square
F
Sig.
Regression
56.142
6
9.357
5.746
.000
Residual
65.138
40
1.628
Total
121.280
46
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac Unstandardized Coefficients
Standardized Coefficients
Sig.
B
Std. Error
Beta
Constant
.200
1.321
edlowest
.151
.031
.659
.000
totalwhitecollar
12.077
5.325
.271
.029
foreignborn
-.058
.032
-.244
.078
artspop
-.072
.146
-.067
.623
health
-.027
.144
-.026
.853
.880
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac Unemployment = .200 + 0.151(edlowest)+ 12.077(totalwhitecollar) - 0.058(foreignborn)- 0.072(artspop) - 0.027(health)
R.
R Square
Adjusted R Square
Std. Error of the Estimate
.680
.463
.397
1.26067
Sum of Squares
df
Mean Square
F
Sig.
Regression
56.119
5
11.224
7.062
.000
Residual
65.161
41
1.589
Total
121.280
46
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac and health Unstandardized Coefficients
Standardized Coefficients
Sig.
B
Std. Error
Beta
Constant
.093
1.177
edlowest
.152
.031
.663
.000
totalwhitecollar
12.085
5.263
.271
.027
foreignborn
-.056
.031
-.240
.076
artspop
-.084
.130
-.078
.523
.937
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac and health Unemployment = .093 + 0.152(edlowest)+ 12.085(totalwhitecollar) - 0.056(foreignborn)- 0.084(artspop) R.
R Square
Adjusted R Square
Std. Error of the Estimate
.680
.462
.411
1.24611
Sum of Squares
df
Mean Square
F
Sig.
Regression
56.063
4
14.016
9.026
.000
Residual
65.217
42
1.553
Total
121.280
46
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac, health and artspop Unstandardized Coefficients
Standardized Coefficients
Sig.
B
Std. Error
Beta
Constant
-.251
1.041
edlowest
.158
.029
.693
.000
totalwhitecollar
12.196
5.224
.274
.024
foreignborn
-.058
.031
-.247
.064
.810
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Backwards Selection Model: Remove repburac, health and artspop Unemployment = -.251 + 0.158(edlowest)+ 12.196(totalwhitecollar) - 0.058(foreignborn) R.
R Square
Adjusted R Square
Std. Error of the Estimate
.676
.457
.419
1.23760
Sum of Squares
df
Mean Square
F
Sig.
Regression
55.419
3
18.473
12.061
.000
Residual
65.861
43
1.532
Total
121.280
46
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Conclusions & Takeaways ◦ Representative bureaucracy is not significantly related to unemployment rates for the cities in this sample
◦ % Population over 25 years old with less than a high school diploma has the most variation among cities, but is the most significant predictor of unemployment
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Limitations ◦ Small sample size ◦ Year 2000 data ◦ Longitudinal element missing ◦ Single indicator of economic prosperity taken into account ◦ Difficult to ascertain or assume the personal perspectives of Black leaders and representatives Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions
Questions?
Introduction │ Variables │ Hypotheses │Data │ Univariate │ Bivariate │ Multivariate │ Conclusions