On the heterogeneous consequences of civil war

Abstract

We show how the occurrence of a civil war has heterogeneous effects on the level of GDP, using case-study, synthetic control and large-N panel-data approaches. We first discuss the relation between these methods and then provide lower and upper estimates of the economic effect of civil war. Although, on average, the incidence of internal conflicts has a negative effect on the GDP level, it is very often insignificant. More importantly, however, both methods display a wide variety of individual separate effects, and in a large number of countries civil war has either no effect or a positive and significant impact on the prospect for economic growth.

The economic and environmental effects of the Beijing-Tianjin-Hebei Collaborative Development Strategy— taking Hebei Province as an example

“…The PDA is particularly suitable for the macroeconometric context (Bai et al 2014;Bove et al 2016;Wan et al 2018), and it has been applied to estimate the macroeconomic effects of China's entry to the WTO (Ching et al 2011), the policy initiatives launched by Japan's Prime Minister Shinzo Abe in his first quarter in the office (Hayashi 2014), China's 2008 economic stimulus package (Ouyang and Peng 2015), China's high-speed rail projects (Ke et al 2017), and China's Clean Air Action (Li et al 2019b).…”

Synthetic Control Estimator: A Tool for Comparative Case Studies in Economic History

“…The Synthetic Control Method has gained significant momentum in the scholarly literature and has been applied in several different settings in a wide range of applications in economics and political science. These applications include evaluating the impact of: terrorism, civil wars and political risk (Abadie and Gardeazabal 2003, Bove et. al.…”

What has New Zealand gained from The FTA with China?: Two counterfactual analyses†

“…Since its introduction, the SCM has seen a range of applications in economics, political science, and international relations. 10 In the words of Athey and Imbens 10 Examples of such applications include openness and trade liberalization policies (Nannicini and Billmeier, 2011;Billmeier and Nannicini, 2013;Ritzel and Kohler, 2017), impact of trade agreements (Hosny, 2012;Hannan, 2016Hannan, , 2017Aytuğ et al, 2017), impact of joining a currency union (Saia, 2017;Puzzello and Gomis-Porqueras, 2018), economic regimes/political stability (Matta et al, 2019;Jales et al, 2018;Grier and Maynard, 2016;Meyersson, 2017), natural disasters (Coffman and Noy, 2012;Cavallo et al, 2013;Mideksa, 2013;Barone and Mocetti, 2014;Mohan, 2017), terrorism, civil wars, crime, and political risks (Montalvo, 2011;Pinotti, 2015;Singhal and Nilakantan, 2016;Bilgel and Karahasan, 2017;Bove et al, 2017;Costalli et al, 2017;Bove and Elia, 2018), health economics (Bilgel and Galle, 2015;Kreif et al, 2016), economic sanctions (Gharehgozli, 2017), migration (Powell et al, 2017), and natural resource discoveries (Smith, 2015). (2017, p. 9), the synthetic control approach is "arguably the most important innovation in the policy evaluation literature in the last 15 years.…”