Abstract
Administrative data is key to many government functions; but generating and maintaining it is costly and challenging in low-income countries. We study an overhaul of public assistance in Pakistan that created a national database of household assets and used the data to means-test cash transfers, eliminating discretion in their allocation. We use difference-in-differences and regression discontinuity approaches to quantify the effect of this reform. Favoritism and transfers to wealthy households dropped; we estimate that the welfare benefits of the reform were seven times as large as its costs. The reform improved public perceptions of social assistance and helped create a robust institution that survived political transitions.
| Original language | English |
|---|---|
| Article number | 104535 |
| Journal | Journal of Public Economics |
| Volume | 206 |
| DOIs | |
| Publication status | Published - 2022 |
Bibliographical note
Funding Information:This study was approved by Oxford Central University Research Committee. Analysis was pre-registered with the EGAP registry (20130921AA). We are grateful for guidance from Marcel Fafchamps. We appreciate feedback from Madiha Afzal, Sami Bazzi, Kathleen Beegle, Erlend Berg, Alan de Brauw, Mike Callen, Azam Chaudhry, Ali Cheema, Jacobus Cilliers, Michael Clemens, Julie Berry Cullen, Clement de Chaisemartin, Pascaline Dupas, Erica Field, James Fenske, Haris Gazdar, Jenny Guardado, Naved Hamid, Clement Imbert, Herbert Kitschelt, Chris Ksoll, Julien Labonne, Clare Leaver, Steve Lyon, Nicolas Martin, Kaivan Munshi, Matthew Nelson, Ijaz Nabi, Matthew Notowidigdo, Ben Olken, Simon Quinn, Jake Shapiro, Bilal Siddiqi, Maximo Torero, Milan Vaishnav, Xiao Yu Wang, Xiaoxue Zhao, and Laura Zimmerman, and participants in seminars at Duke, Oxford, CGD, IFPRI, LUMS, AIMS, the World Bank, and the CSAE, RECODE, DIAL, MWIEDC, and AEA conferences; we appreciate extremely useful constructive feedback from Sandip Sukhtankhar and three anonymous reviewers. We thank Julien Labonne for advising on and carrying out the data split and “testing” estimations, and Naveed Akbar, Saleem Baloch, Ali Cheema, Shujaat Farooq, Haris Gazdar, Ijaz Nabi, Cem Mete, Muhammad Tahir Noor, Sarah Saeed, Khurram Shahzad, and Khaleel Tetlay for help in understanding the program context. We thank Misha Saleem, Amber Nasir, and Abbas Raza for research assistance, and CSAE Oxford, Naved Hamid and the Center for Research on Economics and Business at the Lahore School of Economics, and Shamim Rafique, Sajid Rasul and colleagues at the Punjab Bureau of Statistics for institutional support for the project and data collection. We gratefully acknowledge funding from the British Academy and the Lahore School of Economics.
Funding Information:
This study was approved by Oxford Central University Research Committee. Analysis was pre-registered with the EGAP registry (20130921AA). We are grateful for guidance from Marcel Fafchamps. We appreciate feedback from Madiha Afzal, Sami Bazzi, Kathleen Beegle, Erlend Berg, Alan de Brauw, Mike Callen, Azam Chaudhry, Ali Cheema, Jacobus Cilliers, Michael Clemens, Julie Berry Cullen, Clement de Chaisemartin, Pascaline Dupas, Erica Field, James Fenske, Haris Gazdar, Jenny Guardado, Naved Hamid, Clement Imbert, Herbert Kitschelt, Chris Ksoll, Julien Labonne, Clare Leaver, Steve Lyon, Nicolas Martin, Kaivan Munshi, Matthew Nelson, Ijaz Nabi, Matthew Notowidigdo, Ben Olken, Simon Quinn, Jake Shapiro, Bilal Siddiqi, Maximo Torero, Milan Vaishnav, Xiao Yu Wang, Xiaoxue Zhao, and Laura Zimmerman, and participants in seminars at Duke, Oxford, CGD, IFPRI, LUMS, AIMS, the World Bank, and the CSAE, RECODE, DIAL, MWIEDC, and AEA conferences; we appreciate extremely useful constructive feedback from Sandip Sukhtankhar and three anonymous reviewers. We thank Julien Labonne for advising on and carrying out the data split and “testing” estimations, and Naveed Akbar, Saleem Baloch, Ali Cheema, Shujaat Farooq, Haris Gazdar, Ijaz Nabi, Cem Mete, Muhammad Tahir Noor, Sarah Saeed, Khurram Shahzad, and Khaleel Tetlay for help in understanding the program context. We thank Misha Saleem, Amber Nasir, and Abbas Raza for research assistance, and CSAE Oxford, Naved Hamid and the Center for Research on Economics and Business at the Lahore School of Economics, and Shamim Rafique, Sajid Rasul and colleagues at the Punjab Bureau of Statistics for institutional support for the project and data collection. We gratefully acknowledge funding from the British Academy and the Lahore School of Economics.
Publisher Copyright:
© 2021 Elsevier B.V.
Keywords
- Targeting
- Cash transfers
- Favoritism
- Administrative data