In this section, we use geographically disaggregated data on NPLs and bank pending portfolio from the Philippines’ central bank and other government authorities to estimate the effect of typhoon damage on the non-performing loans (NPL), the total loan portfolio, and the NPL ratio in the Philippine banking system (Figure 4). Our sample consists of a 7-year period between 2011-2018 period for 16 administrative regions in the country. We use the panel local projection model with correction for future biases and controlling for past regional economic growth. We find that for a 1 percentage point increase in the damage ratio, which is calculated as the typhoon damage over the regional GDP, leads to an increase of NPL by 0.72 percent in the year of the disaster and abates over subsequent years (see Figure 5a). The effect is only statistically significant in the typhoon year.

As NPLs only constitute the numerator of the NPL ratio, we repeat the exercise for the total loan portfolio size, we find that a 1 percentage point damage ratio increase leads to a significant drop in the overall loan portfolio size, up to three years into the future (see Figure 5b). Following a typhoon, the combined effect of bank lending contraction and an increase in defaulting loans leads to an overall increase of the NPL ratio. This evidence suggests that typhoons have a destabilizing effect on the Philippine banking system. Further, the peak estimate for the increase in the NPL ratio reaches around 2.3 percent, much larger than the estimates for our cross-country sample, suggesting that severe disasters may indeed have an outsized impact on banking sector resilience.

**Figure 5: Dis-aggregated impulse response functions**

<!-- Start of picture text --> (a) Non-performing loans 0.522%(b) Total loan portfolio (c) Non-performing loan ratio<br>0.00% 3.00%<br>1.00% 0.50% 2.50%<br>0.50% 1.00% 1.744% 1.593% 2.00%<br> 0.260% 1.50% +2.229% +2.272%<br> +0.718% 1.50% 2.259%<br>0.00% +0.502% 1.00%<br>2.00%<br>0.50% + 0.096% 0.50% +1.188% +1 .178%<br>2.50%<br>0.00%<br>Typhoon 1 year 2 years 3 years Typhoon 1 year 2 years 3 years Typhoon 1 year 2 years 3 years<br>year later later later year later later later year later later later<br><!-- End of picture text --> Source: Bangko Sentral ng Pilipinas, NDRRMC reports, Philippine Statistics Authority. The dashed lines represent the standard errors and the whiskers delineate the 95% confidence intervals.

# **7 Policy implications**

Our results show the importance of climate and environmental related natural disasters for the banking sector, and hence a role for financial sector policy makers to actively monitor, assess and mitigate climate-related risks. An important first step would be to collect information to track such risks, including filling any data gaps that may hinder a full understanding of such risks. Once information is in place, policy makers could consider a more detailed assessment of these risks, and specifically the various risk channels that may be at work behind the empirical results highlighted in this paper. For the banking sector, a stress testing exercise would be an important option for such in-depth assessments. This paper directly links the impacts of natural disasters to banking sector variables, and could provide inputs to parameters used in a stress test: for instance, the magnitude of the impact estimated could guide the selection of model parameters in a climate risk stress testing for a country’s banking sector.

16