# _2.2. Modeling the economic impacts of floods_

The risks from flooding are confounded by the high degree of uncertainty about the scale and location of future floods. There is further uncertainty about the economic impact of these floods. This uncertainty is not well reflected in standard modeling approaches, which typically adopt assumptions about perfect knowledge.

In this section we attempt to quantify potential losses of production from flooding. A set of eight possible scenarios is assessed, each one based on the likelihood of the flood occurring. Using the probabilistic risk assessment approach outlined in the World Bank Group’s (2023) Cambodia Country Climate and Development Report (CCDR), we consider both low-frequency, high-impact events and high-frequency, lower-impact events to capture a realistic range of outcomes, including those that may arise under projected climate conditions. The data taken from the floods analysis are: i) the potential losses of production from manufacturing and services sectors; and ii) the expected duration of the loss of production.

The loss of production in manufacturing sectors was disaggregated further, using the split of impacts in the 2011 Thailand floods. This disaggregation is important for informing analysis of possible bottlenecks in production supply chains (see below). Although the pattern of impacts across sectors in Cambodia is likely to be different to that in Thailand, the aim of the exercise is to give a sense of the scale of the heterogeneity of the impacts and how these could in turn affect complex supply chains.

The total loss of production is estimated as being equal to the total duration of the flood (defined as time the business is inundated with water) plus the time to rebuild production capacity. Rebuilding is assumed to be a gradual process that starts immediately once flood drainage has been completed. We draw on Hallegatte (2014) and use the same approach as Tanoue and others (2020) in assuming a linear trajectory of recovery. The time to full recovery is assumed to be ten times the duration of the flood itself, which compares to an estimate of 11.5 times for Thailand (ibid). Given that rebuilding is expected to be faster in more advanced economies, our assumption for total duration of lost production may therefore understate the true value. Because production recovers linearly during the rebuilding period, with companies resuming production when ready, the average recovery time is half the value of ten. If the duration of the floods is expressed in days, the total loss of annual production is therefore: These losses in themselves could be substantial. However, there may also be two types of indirect economic impacts. First, supply shortages may prevent companies from producing, even if their own facilities are undamaged. Second, a loss of income may lead to further losses of production across the economy due to demand deficiency.

Both types of effect are typically missing from standard equilibrium-based analysis. Computable General Equilibrium (CGE) models usually assume that the economy can immediately adjust to its new conditions and find a new optimal position. In this way supply shortages are restricted to where they cause least economic damage. Losses of demand are similarly largely absent because market clearing mechanisms ensure that supply and demand can match exactly. In