Illuminating Africa?

November 2023

Tanner Regan (George Washington University)
Giorgio Chiovelli (Universidad de Montevideo)
Stelios Michalopoulos (Brown University, CEPR and NBER)
Elias Papaioannou (London Business School, CEPR)

IIEP working paper 2023-11

Abstract: Satellite images of nighttime lights are commonly used to proxy local economic conditions. Despite their popularity, there are concerns about how accurately they capture local development in low-income settings and different scales. We compile a yearly series of comparable nighttime lights for Africa from 1992 to 2020, considering key factors that affect accuracy and comparability over time: sensor quality, top coding, blooming, and, importantly, variations in satellite systems (DMPS and VIIRS) using an ensemble, machine learning, approach. The harmonized luminosity series outperforms the unadjusted series as a stronger predictor of local development, particularly over time and at higher spatial resolutions.

JEL Codes: O1, R1, E01, I32

Keywords: Night Lights, Economic Development, Measurement, Africa

The Role of Social Connections in the Racial Segregation of US Cities

July 2023

Tanner Regan (George Washington University)
Andreas Diemer
(Stockholm University (SOFI))
Cheng Keat Tang
(Nanyang Tech. University)

IIEP working paper 2023-05

Abstract: We study the extent of segregation in the social space of urban America. We measure segregation as the (lack of) actual personal connections between groups as opposed to conventional measures based on own neighbourhood composition. We distinguish social segregation from geographical definitions of segregation, and build and compare city-level indices of each. Conditional on residential segregation, cities with more institutions that foster social cohesion (churches and community associations) are less socially segregated. Looking at within-city variation across neighbourhoods, growing up more socially exposed to non-white neighbourhoods is related to various adulthood outcomes (jailed, income rank, married, and non-migrant) for black individuals. Social exposure to non-white neighbourhoods is always related to worsening adulthood outcomes in neighbourhoods that are majority non-white. Our results suggest that social connections, beyond residential location or other spatial relationships, are important for understanding the effective segregation of race in America.

JEL Codes: R23, J15

Key Words: Residential and Social Segregation, Networks, Social connectedness

Public Disclosure and Tax Compliance: Evidence from Uganda

June 2023

Tanner Regan (George Washington University)
Priya Manwaring
(University of Oxford)

IIEP working paper 2023-04

Abstract: Public disclosure of tax behavior is a promising policy tool for raising tax compliance in low-income countries with limited capacity for alternative enforcement mechanisms. Through a field experiment involving over 65,000 taxpayers in Kampala, we study effects of reporting delinquents and recognizing compliers and provide evidence on the social determinants of tax compliance. The threat of publicly disclosing delinquency raises compliance, but subsequently disseminating delinquent behavior lowers compliance of others. Public recognition backfires, lowering compliance both for those promised recognition and for those who receive information about compliant taxpayers. These results are consistent with a model of tax evasion with privacy costs to tax eligibility status and limited shame of delinquency. Disseminating tax behavior reduces compliance by lowering compliance beliefs as measured in survey data. Overall, public disclosure policies in this context are limited at raising revenue and enforcement reminder nudges more effective.

JEL Codes: O18, H30, H26

Key Words: property tax, tax morale, public disclosure, shaming

Ask a local: Improving the public pricing of land titles in urban Tanzania

June 2022

Tanner Regan (George Washington University)
Martina Manara (London School of Economics)

IIEP working paper 2022-07

Abstract: Information on willingness-to-pay is key for public pricing and allocation of services but not easily collected. Studying land titles in Dar-es-Salaam, we ask whether local leaders know and will reveal plot owners’ willingness-to-pay. We randomly assign leaders to predict under different settings then elicit owners’ actual willingness-to-pay. Demand is substantial, but below exorbitant fees. Leaders can predict the aggregate demand curve and distinguish variation across owners. Predictions worsen when used to target subsidies, but adding cash incentives mitigates this. We demonstrate that leader-elicited information can improve the public pricing of title deeds, raising uptake while maintaining public funds.

JEL Codes: O17; H40; R21; D80

Key Words: property rights; willingness-to-pay; public pricing; local publicly provided goods