Welfare impact of climate change on capture fisheries in Vietnam

The regression results (Table 2) show that total vessel gears play a critical role in determining catch yield while the number of laborers is not significant. When sea surface temperature increases by 1˚C, the total catches fall 19.61%. If precipitation rises 1%, the output drops 0.44%. An additional typhoon in a year decreases the capture yield by 2.76%. The severity of storms also negatively influences output. When the maximum wind speed of typhoons increases by 1%, the yield reduces by 0.18%. The coefficient of SOI is positive, indicating that catch yield decreases when El Niño occurs and increases in the case of La Niña. However, the long-term impact of SOI is neglectable, as 1 point decrease in SOI leads to a merely 0.06% decrease in capture yield. IPCC [48] reports that the changing trend in the number of typhoons is not evident during the past decades. Vietnam’s climate change scenarios, developed by the Ministry of Natural Resources and Environment [77], indicate that there might be a decrease in frequency in the number of typhoons by the end of the 21st century under the RCP8.5. Under the RCP4.5, the typhoon frequency is not likely to change. Therefore, we will not consider the typhoon fre- quency and Southern Oscillation to pay attention to assess the impact of change in tempera- ture, rainfall and maximum wind speed of typhoons on capture fisheries in the long run. Table 3 summarizes the projected change in different scenarios compared to 2018. Changes in temperature and precipitation in early, mid and end periods of the 21st century, i.e., 2018-

2035, 2046-2065, and 2080-2099, are estimated based on the RCPs 4.5 and 8.5 for coastal prov- inces of Vietnam [76, 77]. Table 2. Long-run form of the production function. Variable Coefficient Standard Error ADF Statistic Number of lags in ARDL model LnCapacity 0.1453 �� 0.0567 -3.8608 �� I(0) 2 LnLabor -0.1180 0.0756 -2.6976 � I(1) 2 SST -0.1961 ��� 0.0516 -3.7521 ��� I(0) 3 LnRainfall -0.4372 �� 0.1421 -5.6733 ��� I(0) 3 Typhoon -0.0276 ��� 0.0063 -5.2423 ��� I(0) 3 LnWindmax -0.1806 � 0.0896 -5.4866 ��� I(0) 3 SOI 0.0623 ��� 0.0101 -4.5769 ��� I(0) 3 Number of observations after adjustment 40 Number of lags of dependent variable LnCatch 3 ADF statistic of dependent variable LnCatch, I(0) -4.0360 �� ADF statistic of residuals, I(0) -7.6431 ��� Adjusted R2 (Error Correction Model) 0.9588 CointEq(-1)� coefficient (Error Correction Model) -1.1449 ��� Durbin-Watson statistic 2.2006 F-bound test: F-Statistic (k = 7) 29.2657 ��� t-bound test: t-statistic -10.8023 ��� Breusch-Godfrey Serial Correlation LM Test: nR2 1.8385 NS Breusch-Pagan-Godfrey Heteroskedasticity Test: nR2 (df = 31) 36.5049 NS Jarque-Bera Statistic of residuals (normality test) 0.1278 NS Ramsey RESET test: t-statistic (df = 7) 0.9089 NS F-statistic df = (1,7) 0.8261 NS �p < 0.1 ��p < 0.05 ���p < 0.01 NS Non-significant All the statistics for model assessment show that the regression model is appropriate, and the results are statistically reliable. https://doi.org/10.1371/journal.pone.0264997.t002 PLOS ONE

Welfare impact of climate change on capture fisheries in Vietnam PLOS ONE | https://doi.org/10.1371/journal.pone.0264997 April 25, 2022 8 / 20