A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Two examples of welfare chauvinistic policy in Denmark:
(Jørgensen and Thomsen, 2016)
Direct: "Start Aid": Ca. 50% lower benefits to refugees & recent immigrants.
Indirect: "225 hour rule": Both partners in a union need to have worked 225+ hours in the past 12 months to qualify for benefits.
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Danes' public opinion on who should to get vaccinated first
Source: Schaeffer and Haderup Larsen (2022)
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Quality of written answers
from German welfare office administrators
Source: Hemker and Rink (2017)
Potential mechanisms
Research assistants call 200
Italian "Azienda Sanitaria Locale"
to ask for a general practitioner
Two students with
West-African accent
Two students with
native Italian accent
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Municipalities where far-right candidates ran
versus where they won
Source: Romarri (2020)
Note: Means with 90 and 95% CI.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Source: Romarri (2020)
Note: OLS with 90 and 95% CI fitted separately on each side of the margin of victory. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: OLS with 90 and 95% CI fitted separately on each side of the margin of victory. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
RD among callers with West-African accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 421# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 136 285# Eff. Number of Obs. 26 72# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 2.330 2.330# BW bias (b) 4.301 4.301# rho (h/b) 0.542 0.542# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.536 0.178 -3.012 0.003 [-0.885 , -0.187] # Bias-Corrected -0.616 0.178 -3.457 0.001 [-0.964 , -0.267] # Robust -0.616 0.196 -3.146 0.002 [-0.999 , -0.232] # =============================================================================
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
RD among callers with West-African accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 421# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 136 285# Eff. Number of Obs. 26 72# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 2.330 2.330# BW bias (b) 4.301 4.301# rho (h/b) 0.542 0.542# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.536 0.178 -3.012 0.003 [-0.885 , -0.187] # Bias-Corrected -0.616 0.178 -3.457 0.001 [-0.964 , -0.267] # Robust -0.616 0.196 -3.146 0.002 [-0.999 , -0.232] # =============================================================================
ΔRDD=−0.616−(−0.039)=−0.577
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Immigrant minorities face discrimination in access to basic healthcare.
At least those with a West-African accent.
Far-right mayors promote this type of discrimination.
Next step: 3 Mechanisms.
Immigrant minorities face discrimination in access to basic healthcare.
At least those with a West-African accent.
Far-right mayors promote this type of discrimination.
Next step: 3 Mechanisms.
Source: Romarri (2020)
For immigrant minorities
For immigrant minorities
For everyone
Thank you for your attention!
Calonico, S., M. D. Cattaneo, and R. Titiunik (2014). "Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs: Robust Nonparametric Confidence Intervals". In: Econometrica, pp. 2295-2326.
Farrar, J. and A. Ahuja (2021). Spike: The Virus vs. The People - the Inside Story. Profile Books.
Hemker, J. and A. Rink (2017). "Multiple Dimensions of Bureaucratic Discrimination: Evidence from German Welfare Offices". In: American Journal of Political Science, pp. 786-803.
Jørgensen, M. B. and T. L. Thomsen (2016). "Deservingness in the Danish context: Welfare chauvinism in times of crisis". In: Critical Social Policy, pp. 330-351.
Kitschelt, H. and A. J. McGann (1997). The radical right in Western Europe: A comparative analysis. Michigan: University of Michigan Press.
Romarri, A. (2020). Do Far-Right Mayors Increase the Probability of Hate Crimes? Evidence From Italy. SSRN Scholarly Paper ID 3506811. Rochester, NY: Social Science Research Network.
Schaeffer, M. and M. Haderup Larsen (2022). "Who Should Get Vaccinated First? Limits of Solidarity during the First Week of the Danish Vaccination Programme". In: European Sociological Review, p. jcac025.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 54 regions. Adjusted for gender of the caller and municipality fixed effects. n = 492 telephone calls (resp. 246 & 246) to 123 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 492 telephone calls (resp. 246 & 246) to 123 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 686 telephone calls (resp. 343 & 343) to 220 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 686 telephone calls (resp. 343 & 343) to 220 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals (capped at -2) based on 2,000 bootstrap samples stratified by Italian/West-African accent.
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
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A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Two examples of welfare chauvinistic policy in Denmark:
(Jørgensen and Thomsen, 2016)
Direct: "Start Aid": Ca. 50% lower benefits to refugees & recent immigrants.
Indirect: "225 hour rule": Both partners in a union need to have worked 225+ hours in the past 12 months to qualify for benefits.
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Danes' public opinion on who should to get vaccinated first
Source: Schaeffer and Haderup Larsen (2022)
A system of social protection for those who belong to the ethnically defined community
Kitschelt and McGann (1997)
Quality of written answers
from German welfare office administrators
Source: Hemker and Rink (2017)
Potential mechanisms
Research assistants call 200
Italian "Azienda Sanitaria Locale"
to ask for a general practitioner
Two students with
West-African accent
Two students with
native Italian accent
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Means with 90 and 95% CI. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Municipalities where far-right candidates ran
versus where they won
Source: Romarri (2020)
Note: Means with 90 and 95% CI.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Source: Romarri (2020)
Note: OLS with 90 and 95% CI fitted separately on each side of the margin of victory. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: OLS with 90 and 95% CI fitted separately on each side of the margin of victory. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
RD among callers with West-African accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 421# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 136 285# Eff. Number of Obs. 26 72# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 2.330 2.330# BW bias (b) 4.301 4.301# rho (h/b) 0.542 0.542# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.536 0.178 -3.012 0.003 [-0.885 , -0.187] # Bias-Corrected -0.616 0.178 -3.457 0.001 [-0.964 , -0.267] # Robust -0.616 0.196 -3.146 0.002 [-0.999 , -0.232] # =============================================================================
Bias-corrected non-parametric RD with optimized bandwidth (Calonico, Cattaneo, and Titiunik, 2014)
RD among callers with native Italian accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 391# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 116 275# Eff. Number of Obs. 32 88# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 3.035 3.035# BW bias (b) 6.032 6.032# rho (h/b) 0.503 0.503# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.026 0.021 -1.257 0.209 [-0.066 , 0.014] # Bias-Corrected -0.039 0.021 -1.892 0.058 [-0.079 , 0.001] # Robust -0.039 0.023 -1.669 0.095 [-0.085 , 0.007] # =============================================================================
RD among callers with West-African accent
# Sharp RD estimates using local polynomial regression.# # Number of Obs. 421# BW type mserd# Kernel Triangular# VCE method NN# # Number of Obs. 136 285# Eff. Number of Obs. 26 72# Order est. (p) 1 1# Order bias (q) 2 2# BW est. (h) 2.330 2.330# BW bias (b) 4.301 4.301# rho (h/b) 0.542 0.542# # =============================================================================# Method Coef. Std. Err. z P>|z| [ 95% C.I. ] # =============================================================================# Conventional -0.536 0.178 -3.012 0.003 [-0.885 , -0.187] # Bias-Corrected -0.616 0.178 -3.457 0.001 [-0.964 , -0.267] # Robust -0.616 0.196 -3.146 0.002 [-0.999 , -0.232] # =============================================================================
ΔRDD=−0.616−(−0.039)=−0.577
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 806 telephone calls (resp. 391 & 415) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent. n = 805 telephone calls (resp. 392 & 413) to 252 municipalities.
Immigrant minorities face discrimination in access to basic healthcare.
At least those with a West-African accent.
Far-right mayors promote this type of discrimination.
Next step: 3 Mechanisms.
Immigrant minorities face discrimination in access to basic healthcare.
At least those with a West-African accent.
Far-right mayors promote this type of discrimination.
Next step: 3 Mechanisms.
Source: Romarri (2020)
For immigrant minorities
For immigrant minorities
For everyone
Thank you for your attention!
Calonico, S., M. D. Cattaneo, and R. Titiunik (2014). "Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs: Robust Nonparametric Confidence Intervals". In: Econometrica, pp. 2295-2326.
Farrar, J. and A. Ahuja (2021). Spike: The Virus vs. The People - the Inside Story. Profile Books.
Hemker, J. and A. Rink (2017). "Multiple Dimensions of Bureaucratic Discrimination: Evidence from German Welfare Offices". In: American Journal of Political Science, pp. 786-803.
Jørgensen, M. B. and T. L. Thomsen (2016). "Deservingness in the Danish context: Welfare chauvinism in times of crisis". In: Critical Social Policy, pp. 330-351.
Kitschelt, H. and A. J. McGann (1997). The radical right in Western Europe: A comparative analysis. Michigan: University of Michigan Press.
Romarri, A. (2020). Do Far-Right Mayors Increase the Probability of Hate Crimes? Evidence From Italy. SSRN Scholarly Paper ID 3506811. Rochester, NY: Social Science Research Network.
Schaeffer, M. and M. Haderup Larsen (2022). "Who Should Get Vaccinated First? Limits of Solidarity during the First Week of the Danish Vaccination Programme". In: European Sociological Review, p. jcac025.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 812 telephone calls (resp. 391 & 421) to 257 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 54 regions. Adjusted for gender of the caller and municipality fixed effects. n = 492 telephone calls (resp. 246 & 246) to 123 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 492 telephone calls (resp. 246 & 246) to 123 municipalities.
Note: Point estimate with 90 and 95% CI based on OLS with standard errors clustered on the level of 72 regions. Adjusted for gender of the caller and municipality fixed effects. n = 686 telephone calls (resp. 343 & 343) to 220 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
n = 686 telephone calls (resp. 343 & 343) to 220 municipalities.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals based on 2,000 bootstrap samples stratified by Italian/West-African accent.
Note: ΔRDD estimates based on rdrobust() with 90 and 95% BCa confidence intervals (capped at -2) based on 2,000 bootstrap samples stratified by Italian/West-African accent.