Breakthrough Elections, Segregation and White Flight

class: center, middle, inverse, title-slide

.title[
# Breakthrough Elections, Segregation and White Flight
]
.author[
### Daniel Tabak, Marcelino Guerra, and Ethan Dee
]
.author[
### University of Illinois at Urbana-Champaign
]
.date[
### February, 2023
]

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# Motivation

<br/>
* Places and Neighborhoods significantly impact adult outcomes in the US

* Racial Segregation and its persistence can, therefore, work as
a mechanism to reinforce racial disparities in outcomes

* Simply moving to more diverse and opportunity-rich locations might not be enough to overcome such challenges since
there’s much evidence of endogenous sorting due to migrant inflow

* **This paper** aims to estimate if local minority representation (black mayors) can work as a tool to

- Decrease Segregation

- Improve opportunity for the minority population (future work)

---

# Related Literature

<br/>

* Place effects and migration 
  - [Ludwig *et al*., 2013; Chetty *et al*., 2016]

- [Chetty and Hendren, 2018; Derenoncourt, 2022]

* Local representation and opportunity

- [Dippel, 2022; Brollo and Troiano, 2016] 
  
  - [Sylvera, 2022; Logan, 2020; Nye *et al*., 2015]

* White Flight and Segregation

- [Card *et al*., 2008; Boustan, 2010]

---
# Data and Context I

<br/>

**Census data 1970-2010 - NHGIS**

1. Tract level Individual demographic (population, race, gender, age, education, population below pov. line, labor force
participation, unemployment rate)

2. Tract level housing information(housing units, vacancy status, renter occupied, Median Value)

**Election Data - Warshaw *et al*., 2022**

1. All close Mayor elections from 1980-2010 Winner, Loser, Year, City (margins up to 10.5%)

2. Identify all interracial elections- first breakthrough black mayor of a city denotes treatment.

---
# Data and Context II

.pull-left2[

* Match tracts to cities where the centroid of the tract is
located within a place's boundaries

* Boundaries of places consistent with 2020 definition

* Tracts are matched over time using 6 digits id

]

.pull-right2[
<iframe src="maps/sacramento.html"  style="width: 1200px; height: 500px; border: 5px" alt="">

]

---
# Data and Context III

.pull-left[

* We Identify 40 breakthrough elections where a black mayor wins by a close margin

* We Identify 20 additional interracial elections where the black candidate loses by a close margin.

* Create two geographic dissimilarity measures at the city level for first-level analysis (Cutler et al., 1999)
  
   1. Dissimilarity Index 
   `\(DI=\frac{1}{2}\sum^{N}_{i=1}\Big|\frac{\text{Pop Black}_{i}}{\text{Pop Black}_{total}} - \frac{\text{Pop Non Black}_{i}}{\text{Pop Non Black}_{total}} \Big|\)`
   
   2. Isolation Index 
   `\(II= \frac{\sum_{i=1}^N \left( \frac{Pop\ Black_i}{Pop\ Black_{total}}\times \frac{Pop\ Black_i}{Pop_i} \right) - \frac{Pop\ Black_{total}}{Pop_{total}}}{1-\frac{Pop\ Black_{total}}{Pop_{total}}}\)`

]

.pull-right[

]
---
name: empirical-st
# Empirical Strategy

.pull-left[

**Three different specifications**

1. Difference-in-differences with full sample 
  * 40 treated cities and 3,690 control cities  
  * [Full sample characteristics](#census-table2)

2. Difference-in-differences with restricted sample
  * Restricted sample is formed by cities that had close elections with a black candidate as runner-up 
  * [Restricted sample characteristics](#census-table2)

3. Callaway and Sant'Anna (2021) doubly-robust matching strategy with full sample

]

.pull-right[

Since there is considerable treatment timing variation (table below), we apply Callaway and Sant'Anna (2021) using city-level information in the propensity score step

<table class="table table" style="width: auto !important; margin-left: auto; margin-right: auto; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:right;"> Year </th>
   <th style="text-align:right;"> Number of Treated Cities </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 1980 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 1990 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 2000 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
</tbody>
</table>

]

---
name: results-full
# Results - Full Sample

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="2"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> Dissimilarity Index </b> </td>
      <td style="text-align:center;"> <b> Isolation Index </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;">  0.054***</td>
   <td style="text-align:center;"> -0.034   </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (0.020) </td>
   <td style="text-align:center;"> (0.023) </td>

</tr>

<tr>
   <td style="text-align:left;" > <b>Fixed-Effects:</b>  </td>
   <td style="text-align:center;" > City and Census Year </td>
   <td style="text-align:center;" > City and Census Year </td>

</tr>
    <tr>
   <td style="text-align:center;" colspan="3">  </td>
  </tr>
  
  <tr>
  
   <td style="text-align:left;"> <b>Mean of Outcome</b> </td>
   <td style="text-align:center;" > 0.248 </td>
   <td style="text-align:center;" > 0.056 </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 12,184 </td>
   <td style="text-align:center;"> 12,184 </td>

</tr>
   <tfoot><tr><td colspan="5"> Regression weighted by population.  To make the balanced panel we only keep cities with observations in all periods. From the design, standard errors are robust and clustered at the city level. Results
change little when we keep all cities in the sample (but with unbalanced panel we cannot
accurately weight by population in the start of the panel).  </td></tr></tfoot>
    <tfoot><tr><td colspan="5"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1 </td></tr></tfoot>
</tbody>
</table>

[Changes in pop shares.](#pop-results-full)
---
name: results-rest
# Results - Restricted Sample

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="2"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> Dissimilarity Index </b> </td>
      <td style="text-align:center;"> <b> Isolation Index </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;">  0.028**</td>
   <td style="text-align:center;"> 0.013   </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (0.012) </td>
   <td style="text-align:center;"> (0.013) </td>

</tr>

<tr>
   <td style="text-align:left;" > <b>Fixed-Effects:</b>  </td>
   <td style="text-align:center;" > City and Census Year </td>
   <td style="text-align:center;" > City and Census Year </td>

</tr>
    <tr>
   <td style="text-align:center;" colspan="3">  </td>
  </tr>
  
  <tr>
  
   <td style="text-align:left;"> <b>Mean of Outcome</b> </td>
   <td style="text-align:center;" > 0.572 </td>
   <td style="text-align:center;" > 0.366 </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 280 </td>
   <td style="text-align:center;"> 280 </td>

[Changes in pop shares.](#pop-results-rest)

---
name: results-cs
# Results - Callaway and Sant'Anna (2021)

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="2"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> Dissimilarity Index </b> </td>
      <td style="text-align:center;"> <b> Isolation Index </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;">  0.0605***</td>
   <td style="text-align:center;"> -0.0126***  </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (0.0024) </td>
   <td style="text-align:center;"> (0.0015) </td>

</tr>

<tr>
   <td style="text-align:left;" > <b>Fixed-Effects:</b>  </td>
   <td style="text-align:center;" > City and Census Year </td>
   <td style="text-align:center;" > City and Census Year </td>

</tr>
    <tr>
   <td style="text-align:center;" colspan="3">  </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 97,200 </td>
   <td style="text-align:center;"> 97,200 </td>

</tr>
   <tfoot><tr><td colspan="5"> This specification follows the Callaway and Sant’Anna(2021) matching strategy. We use
the Matching version with a doubly robust strategy using all information nfrom the summary
tables as inputs to select cities that are more similar to the ones in the treatment groups. We
additionally use information on the population and housing growth between 1970 and 1980. </td></tr></tfoot>
    <tfoot><tr><td colspan="5"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1 </td></tr></tfoot>
</tbody>
</table>

[Changes in pop shares.](#pop-results-cs)

---
# Future Directions

<br/>

* Deep dive on the mechanisms behind the RDI and II dynamics

* Add measures of economic activity and housing prices
  * Median home value
  * Local Government expenditure
  
* Explore place effects data from Chetty and Hendren (2018)

---
class: inverse, middle, center

# Appendix

---
name: census-table1
# Full Sample City Characteristics (1980 Census)

<font size="3.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;" colspan="4"> <b> Mean equality: Treated vs All other cities </b> </td>
   </tr>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:center;"> All other cities </th>
   <th style="text-align:center;"> Cities with breakthrough elections </th>
<th style="text-align:center;"> F-test </th>
  </tr>
 </thead>
<tbody>

<tr>
   <td style="text-align:left;"> Population </td>
   <td style="text-align:center;"> 46,373.958  </td>
   <td style="text-align:center;"> 330,064.3  </td>
  <td style="text-align:center;"> 18.6*** </td>
  
  </tr>
  <tr>
   <td style="text-align:left;">  Dissimilarity Index  </td>
   <td style="text-align:center;"> 0.25 </td>
   <td style="text-align:center;"> 0.66 </td>
   <td style="text-align:center;"> 95.44*** </td>
 
  </tr>
  
  <tr>
   <td style="text-align:left;"> Isolation Index </td>
   <td style="text-align:center;"> 0.056 </td>
   <td style="text-align:center;"> 0.44  </td>
   <td style="text-align:center;"> 290.05*** </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> Share of whites </td>
   <td style="text-align:center;"> 89.46  </td>
   <td style="text-align:center;"> 65.52 </td>
   <td style="text-align:center;"> 86.06*** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Share of blacks</td>
   <td style="text-align:center;"> 7.05 </td>
   <td style="text-align:center;"> 29.60 </td>
   <td style="text-align:center;"> 93.66*** </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Share of poverty </td>
   <td style="text-align:center;"> 8.52 </td>
   <td style="text-align:center;"> 16.58 </td>
   <td style="text-align:center;">60.35***  </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Unemployment rate </td>
   <td style="text-align:center;"> 5.97 </td>
   <td style="text-align:center;"> 8.44  </td>
   <td style="text-align:center;">22.75***  </td>

</tr>
  
  <tr>
   <td style="text-align:left;"> Housing vacancy rate </td>
   <td style="text-align:center;"> 5.51 </td>
   <td style="text-align:center;"> 6.91  </td>
   <td style="text-align:center;"> 2.671 </td>

</tr>
    <tr>
   <td style="text-align:left;"> Share of renter-occupied </td>
   <td style="text-align:center;"> 30.42  </td>
   <td style="text-align:center;"> 46.87 </td>
   <td style="text-align:center;"> 38.56***  </td>

</tr>
  
   <tr>
   <td style="text-align:left;"> Labor force participation </td>
   <td style="text-align:center;"> 0.631 </td>
   <td style="text-align:center;"> 0.613  </td>
   <td style="text-align:center;"> 2.035  </td>

</tr>

<tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 3,690 </td>
   <td style="text-align:center;"> 40 </td>
   <td style="text-align:left;">  </td>

</tr>
    <tfoot><tr><td colspan="4"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1. </td></tr></tfoot>
</tbody>
</table>

[Back to empirical strategy.](#empirical-st)

---
name: census-table2
# Restricted Sample City Characteristics (1980 Census)

<font size="3.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;" colspan="4"> <b> Mean equality: Treated vs Restricted cities </b> </td>
   </tr>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:center;"> Black Runner-up Elections </th>
   <th style="text-align:center;"> Cities with breakthrough elections </th>
<th style="text-align:center;"> F-test </th>
  </tr>
 </thead>
<tbody>

<tr>
   <td style="text-align:left;"> Population </td>
   <td style="text-align:center;"> 112,366.75  </td>
   <td style="text-align:center;"> 330,064.3  </td>
  <td style="text-align:center;"> 1.126 </td>
  
  </tr>
  <tr>
   <td style="text-align:left;">  Dissimilarity Index  </td>
   <td style="text-align:center;"> 0.57 </td>
   <td style="text-align:center;"> 0.66 </td>
   <td style="text-align:center;"> 3.57* </td>
 
  </tr>
  
  <tr>
   <td style="text-align:left;"> Isolation Index </td>
   <td style="text-align:center;"> 0.37 </td>
   <td style="text-align:center;"> 0.44  </td>
   <td style="text-align:center;"> 1.64 </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> Share of whites </td>
   <td style="text-align:center;"> 62.48  </td>
   <td style="text-align:center;"> 65.52 </td>
   <td style="text-align:center;"> 0.32 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Share of blacks</td>
   <td style="text-align:center;"> 31.17</td>
   <td style="text-align:center;"> 29.60 </td>
   <td style="text-align:center;"> 0.08 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Share of poverty </td>
   <td style="text-align:center;"> 15.39 </td>
   <td style="text-align:center;"> 16.58 </td>
   <td style="text-align:center;"> 0.75  </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Unemployment rate </td>
   <td style="text-align:center;"> 7.17 </td>
   <td style="text-align:center;"> 8.43  </td>
   <td style="text-align:center;"> 3.06*  </td>

</tr>
  
  <tr>
   <td style="text-align:left;"> Housing vacancy rate </td>
   <td style="text-align:center;"> 5.99 </td>
   <td style="text-align:center;"> 6.91  </td>
   <td style="text-align:center;"> 0.97 </td>

</tr>
    <tr>
   <td style="text-align:left;"> Share of renter-occupied </td>
   <td style="text-align:center;"> 46.03  </td>
   <td style="text-align:center;"> 46.87 </td>
   <td style="text-align:center;"> 0.05  </td>

</tr>
  
   <tr>
   <td style="text-align:left;"> Labor force participation </td>
   <td style="text-align:center;"> 0.615 </td>
   <td style="text-align:center;"> 0.613  </td>
   <td style="text-align:center;"> 0.01  </td>

</tr>

<tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 20 </td>
   <td style="text-align:center;"> 40 </td>
   <td style="text-align:left;">  </td>

</tr>
    <tfoot><tr><td colspan="4"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1. </td></tr></tfoot>
</tbody>
</table>

[Back to empirical strategy.](#empirical-st)

---
name: pop-results-full
# Changes in population shares - Full Sample

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="3"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> White share </b> </td>
      <td style="text-align:center;"> <b> Black share </b> </td>
      <td style="text-align:center;"> <b> Other Minority share </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;">  -4.159***</td>
   <td style="text-align:center;"> 1.342  </td>
   <td style="text-align:center;"> 3.641*  </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (0.952) </td>
   <td style="text-align:center;"> (1.569) </td>
    <td style="text-align:center;"> (2.211) </td>

</tr>

<tr>
   <td style="text-align:left;" > <b>Fixed-Effects:</b>  </td>
   <td style="text-align:center;" > City and Census Year </td>
   <td style="text-align:center;" > City and Census Year </td>
   <td style="text-align:center;" > City and Census Year </td>

</tr>
    <tr>
   <td style="text-align:center;" colspan="4">  </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 70,895 </td>
   <td style="text-align:center;"> 70,895  </td>
    <td style="text-align:center;"> 70,895  </td>

</tr>
    <tfoot><tr><td colspan="5"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1 </td></tr></tfoot>
</tbody>
</table>

[Back to results - full sample.](#results-full)

---
name: pop-results-rest
# Changes in population shares - Restricted Sample

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="3"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> White share </b> </td>
      <td style="text-align:center;"> <b> Black share </b> </td>
      <td style="text-align:center;"> <b> Other Minority share </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;"> -1.221</td>
   <td style="text-align:center;"> -2.721  </td>
   <td style="text-align:center;"> 3.942**  </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (1.693) </td>
   <td style="text-align:center;"> (1.806) </td>
    <td style="text-align:center;"> (1.574) </td>

</tr>

</tr>
    <tr>
   <td style="text-align:center;" colspan="4">  </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 21,050 </td>
   <td style="text-align:center;"> 21,050  </td>
    <td style="text-align:center;"> 21,050  </td>

</tr>
    <tfoot><tr><td colspan="4"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1 </td></tr></tfoot>
</tbody>
</table>

[Back to results - restricted sample.](#results-rest)

---
name: pop-results-cs
# Changes in population shares - CS

<font size="4.5" face="Helvetica" >
<table style="table-layout: fixed;">
 <thead>
   <tr>
   <td style="text-align:center;"> <b>  </b> </td>
   <td style="text-align:center;" colspan="3"> <b> Dependent variable: </b> </td>
   </tr>
   
   <tr>
      <td style="text-align:left;"> <b>  </b> </td>
   <td style="text-align:center;"> <b> White share </b> </td>
      <td style="text-align:center;"> <b> Black share </b> </td>
      <td style="text-align:center;"> <b> Other Minority share </b> </td>
   </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> <b>Treated x Post </b> </td>
   <td style="text-align:center;"> -3.522***</td>
   <td style="text-align:center;"> 1.358***  </td>
   <td style="text-align:center;"> 2.164***  </td>

</tr>
  
  <tr>
   <td style="text-align:left;">           </td>
   <td style="text-align:center;"> (0.199) </td>
   <td style="text-align:center;"> (0.159) </td>
    <td style="text-align:center;"> (0.127) </td>

</tr>

</tr>
    <tr>
   <td style="text-align:center;" colspan="4">  </td>
  </tr>
  
  <tr>
   <td style="text-align:left;"> <b>Observations</b> </td>
   <td style="text-align:center;"> 97,200 </td>
   <td style="text-align:center;"> 97,200  </td>
    <td style="text-align:center;"> 97,200  </td>

</tr>
    <tfoot><tr><td colspan="4"> <b>Note:</b> ***: 0.01, **: 0.05, *: 0.1 </td></tr></tfoot>
</tbody>
</table>

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