I am a PhD candidate at Harvard University Government Department, expecting to receive the degree in summer 2021. During the 2020-2021 academic year, I am a Pre-Doctoral Research Fellow at Harvard Kennedy School’s Middle East Initiative.
My dissertation project explores the reasons behind the weak electoral appeal of secular-modernist parties in the Middle East after the popular uprisings of 2011-2013 and why they could not form a credible alternative to Islamist parties. I undertake a close case analysis of two large secular parties in the region, Cumhuriyet Halk Partisi (Republican People’s Party) in Turkey and Nidaa Tounes (Call of Tunisia), and exploit the subnational variation to test various hypotheses. I find that, unlike many conventional expectations, valence deficit and inability of secular parties to signal good governance credentials are among the main causes of secular disadvantage. The valence deficit stems from negative political selection and problems in organizational cohesion, i.e. inability of social networks within the party organization to cooperate effectively.
The data for this project comes from pre-election interviews, candidate and household surveys and post-election interviews in both countries. Data collection efforts were supported by Democracy International, Belfer Center for Science and International Affairs, Weatherhead Center for International Affairs, Institute for Quantitative Social Science and Center for Middle Eastern Studies at Harvard University.
My other current projects explore how parties and charities engage in and affect the quality of primary healthcare in Lebanon, the role of international organizations in poverty reduction programs for refugees, and why citizens support executive aggrandizement reforms in Turkey.
Here is an up-to-date CV.
Please feel free to contact me for inquiries related to my work at firstname.lastname@example.org.
“Targeting humanitarian aid using administrative data: model design and validation” (with O. Altindag, S.D. O’Connell, Z. Balcioglu, P. Cadoni, M. Jerneck, A. K. Foong), Journal of Development Economics, Vol. 148, January 2021.
Most of the unconditional cash transfers for the poor depends on a short-form proxy-means test, which requires a survey of the entire target population. Such an approach is logistically challenging in the context of a refugee crisis. We instead develop an econometric prediction model that relies on administrative data held by international agencies to target over $380 million annually in unconditional cash transfers to Syrian refugees in Lebanon. Standard metrics of prediction accuracy suggest targeting using administrative data is comparable to more conventional approaches. The results are robust to a blind validation test performed on a random sample collected after the model derivation.