alongside the rebuilding of physical capital which will unavoidably be a key component of the agenda. Further, attention also needs to be paid to other factors contributing to total factor productivity (TFP), including institutions and market efficiency.

However, the prospects for mobilizing meaningful multi‐year financing for reconstruction and development and for achieving a critical mass of voluntary repatriation of refugees would hinge on the nature of the ultimate political settlement of the conflict. A lopsided political settlement may deter refugees, with strong lingering uncertainty about security and economic prospects, to return. Some of the main impediments hindering repatriation include the dispossession of refugees’ homes and mandatory military conscription for men of age. Therefore, and despite the “invitation” for refugees to return home and the refugee camps being set up within Syria, it is not surprising that only a few thousands returned in 2017, mostly motivated by push factors in the recipient countries. Indeed, this very limited response did not mark the opening of the flood gates for massive repatriation in the following years (POMEPS 2018).

Moreover, the volume of the funding required for reconstruction has been estimated at USD 250 billion by the United Nations to as high as USD1 trillion (POMEPS 2018), by far more than could be provided by Syrian allies. Thus, a genuine reconstruction plan for Syria would best be served by robust support from the wider international community, who have indicated a preference for a more robust political settlement (ERF 2019). The international community can provide some reconstruction aid that would support and encourage the return of refugees, infrastructure investment, and policy reform. This includes aid for geographically dispersed economic reconstruction (rebuilding infrastructure, access to health and education, etc.) and institutional reform (including security, property rights, and access to justice) that benefit various segments of the population fairly (Yahya 2017). Djankov and Reynal‐Querol (2010) find that both per capita income and civil war are jointly determined by country‐specific phenomena, such as colonial history. Consequently, policies are needed to rectify structural problems that make countries more prone to conflict.

Subscribing to the context discussed above, this paper uses the World Bank Long‐Term Growth Model ‐ Public Capital Extension (LTGM‐PC) by Devadas and Pennings (2019) ‐ see Appendix 1 for details ‐ to simulate a counterfactual of no conflict scenario (in Section 2), to estimate the impact of conflict (in Section 3), and to assess the potential post‐conflict growth for Syria (in Section 4). The after‐war projections are carried out for three political settlement scenarios: a baseline (Sochi‐plus, mainly operated by Iran, Russia, and Turkey, with some involvement from the United Nations) moderate scenario; a high (robust political settlement, brokered by the United Nations) scenario; and a pessimistic (de facto balance of power) scenario. The LTGM‐PC builds on the Solow‐Swan growth model, and is evolved from another World Bank tool, the Long‐Term Growth Model (LTGM) (Loayza and Pennings 2018; Hevia and Loayza 2012). The LTGM‐PC splits the accumulation of aggregate capital into public and private portions, while retaining other features of the LTGM including other growth drivers (demographics and the labor force, human capital, and total factor productivity). We run all our simulations using the LTGM‐PC Excel‐based toolkit.

Our paper complements earlier modeling work by World Bank (2017b) in four ways. One, it provides a straightforward and transparent analysis of how GDP evolves based on projections for the growth drivers. World Bank (2017b) uses a dynamic general equilibrium model to simulate the effects of the conflict through three channels – physical capital destruction, casualties, and economic disorganization; with the last calculated as a residual based on estimated GDP losses. Two, data‐wise, we use estimates of physical damage across all types of capital whereas World Bank (2017b) determines destruction in their simulations based on physical damage assessments in the housing 3