Publications

by members of

Department of Public Policy
Central European University
Wien, Austria

These are publications listed in RePEc written by members of the above institution who are registered with the RePEc Author Service. Thus this compiles the works all those currently affiliated with this institution, not those affilated at the time of publication. List of registered members. Register yourself. Citation analysis. Find also a compilation of publications from alumni here.

This page is updated in the first days of each month.

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| Working papers | Journal articles | Books | Chapters |

Working papers

2023

1. Anand Murugesan & Jean-Robert Tyran, 2023. "The Puzzling Practice of Paying “Cash for Votes”," CESifo Working Paper Series 10504, CESifo.

2020

1. Vikram Dayal & Anand Murugesan, 2020. "Demystifying causal inference: ingredients of a recipe," IEG Working Papers 393, Institute of Economic Growth.

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Journal articles

2022

1. Vikram Dayal & Anand Murugesan & Tauhidur Rahman, 2022. "Drain on your health: Sanitation externalities from dirty drains in India," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2251-2273, November.
2. Das, Sanghamitra & Dayal, Vikram & Murugesan, Anand & Rajarathnam, Uma, 2022. "Air pollution trade-offs in developing countries: an empirical model of health effects in Goa, India," Environment and Development Economics, Cambridge University Press, vol. 27(2), pages 145-166, April.
3. Centofanti, Tiziana & Murugesan, Anand, 2022. "Leader and citizens participation for the environment: Experimental evidence from Eastern Europe," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 100(C).

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Books

2023

1. Vikram Dayal & Anand Murugesan, 2023. "Demystifying Causal Inference," Springer Books, Springer, number 978-981-99-3905-3, September.

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Chapters

2023

1. Vikram Dayal & Anand Murugesan, 2023. "John Snow and Causal Inference," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 1-17, Springer.
2. Vikram Dayal & Anand Murugesan, 2023. "Panel Data and Fixed Effects," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 193-226, Springer.
3. Vikram Dayal & Anand Murugesan, 2023. "Difference-in-Differences," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 227-253, Springer.
4. Vikram Dayal & Anand Murugesan, 2023. "Integrating and Generalizing Causal Estimates," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 255-294, Springer.
5. Vikram Dayal & Anand Murugesan, 2023. "RStudio and R," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 19-31, Springer.
6. Vikram Dayal & Anand Murugesan, 2023. "Regression and Simulation," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 33-54, Springer.
7. Vikram Dayal & Anand Murugesan, 2023. "Potential Outcomes," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 55-64, Springer.
8. Vikram Dayal & Anand Murugesan, 2023. "Causal Graphs," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 65-80, Springer.
9. Vikram Dayal & Anand Murugesan, 2023. "Experiments," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 81-108, Springer.
10. Vikram Dayal & Anand Murugesan, 2023. "Matching," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 109-134, Springer.
11. Vikram Dayal & Anand Murugesan, 2023. "Instrumental Variables," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 135-168, Springer.
12. Vikram Dayal & Anand Murugesan, 2023. "Regression Discontinuity Design," Springer Books, in: Demystifying Causal Inference, chapter 0, pages 169-192, Springer.

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