Common use of Robustness Clause in Contracts

Robustness. Our results could be sensitive to the pre-disaster periods. We conduct a sensitivity analysis by extending the pre-disaster period to 12 quarters. Tables 7a to 9b show the sensitivity analysis for Thailand’s disasters, while Tables 10a and 10b show those results for the Philippine typhoons. As can be seen, the results are similar to those of the baseline. In the case of Thailand, we generally find a decline in total consumption. This decline stems from a reduction in expenditures on the service sector including transportation, hotels, and restaurants. In contrast, we generally observe increased household spending on food and non- alcoholic drinks, alcoholic beverages and tobacco products, clothing, and utilities. As seen from Table 7a, the total immediate expenditures declined by approximately 26 billion Thai baht after the Indian Ocean tsunami. Similar to our baseline results, we find housing- related expenses, including utilities and furniture, increased during this disaster. However, the estimates of the immediate expenditure declines in recreation, restaurants, and hotels are imprecise (Table 7b); yet we find the expenditure on transportation immediately dropped. Table 8a shows total consumption expenditure immediately dropped by approximately 70 billion Thai baht due to the 2011 Thailand floods. The results presented in Tables 8a and 8b resemble those of the baseline. Specifically, we find households immediately increased spending on both durable and non-durable goods. On the other hand, we find consumers immediately reduced their spending on transportation, restaurants, and hotels. Tables 9a and 9b show the results pertaining to the 2016-17 Thailand floods. We again find similar results to the baseline estimates. The total immediate consumption dropped approximately 31 billion Thai baht. Similar to aforementioned disasters in Thailand, households immediately increased spending on non-durable goods including food, beverages, tobacco, and clothing. Households also increased immediate spending on utilities. However, they reduced their spending on transportation, restaurants, and hotels. For the Philippines, the effects of the typhoons on consumption are usually small. Among the three typhoons, we still find that Typhoon Haiyan had the largest immediate effects on consumption expenditures; the total household spending immediately declined by approximately 40 billion pesos after Typhoon Haiyan. Although the magnitude of estimate shown in Table 10a is similar to that of the baseline, the estimate of total immediate household is imprecise. Similar to our bassline estimate, we do not find any significant changes in total consumption after Typhoon Meranti. Finally, we still do not find any regular patterns of change in consumption expenditures when we analyse components of consumption. 𝑇𝑖𝑑 15.43*** -0.09*** -0.01 -0.06*** -0.05*** 0.02** 0.03*** (0.38) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ - 25.87*** 0.26 0.34*** 0.30*** 0.38*** 0.05 0.00 (5.12) (0.19) (0.10) (0.06) (0.05) (0.04) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 4.30* 0.06 -0.05 0.07*** -0.14*** -0.03 -0.06*** (2.15) (0.10) (0.03) (0.02) (0.01) (0.02) (0.02) 𝑇𝑖𝑑 0.08** 0.04*** 0.07*** -0.09*** -0.01 0.06*** (0.03) (0.01) (0.02) (0.03) (0.01) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -0.51* 0.10 -0.07 -0.25 0.07* -0.39** (0.25) (0.08) (0.12) (0.31) (0.03) (0.17) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 -0.13** -0.02 0.004 0.28** -0.01 -0.05 (0.05) (0.02) (0.02) (0.09) (0.02) (0.06) 𝑇𝑖𝑑 17.39*** -0.22*** -0.07*** -0.06*** -0.05*** 0.06*** 0.09*** (0.92) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -70.08*** 0.89*** 0.29*** 0.39*** 0.86*** 0.12 0.09 (13.37) (0.23) (0.08) (0.05) (0.11) (0.13) (0.14) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 25.13*** -0.34*** -0.06*** -0.18*** -0.16*** -0.15** -0.18*** (4.66) (0.08) (0.02) (0.01) (0.02) (0.05) (0.04) 𝑇𝑖𝑑 0.15*** 0.00 0.09*** 0.15*** -0.01*** -0.04 (0.03) (0.02) (0.01) (0.03) (0.00) (0.03) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -2.25*** 0.20* -0.12 -0.58*** 0.04 0.51** (0.28) (0.11) (0.10) (0.17) (0.02) (0.23) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 0.98*** -0.10*** -0.01 -0.02 -0.04*** 0.09 (0.09) (0.02) (0.03) (0.04) (0.01) (0.08) 𝑇𝑖𝑑 16.72*** -0.11*** -0.04*** -0.04*** -0.00 -0.03*** -0.01 (0.62) (0.02) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -30.98** 0.36*** -0.05 0.14*** 0.08 0.08 0.16 (11.82) (0.11) (0.06) (0.04) (0.11) (0.09) (0.12) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 9.36 -0.08* -0.00 -0.02 -0.04 -0.01 -0.05 (5.49) (0.04) (0.02) (0.02) (0.05) (0.03) (0.04) 𝑇𝑖𝑑 0.03* -0.02* 0.12** 0.06 -0.00 0.02 (0.02) (0.01) (0.05) (0.04) (0.00) (0.03) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -0.19 0.18** 0.04 -0.45* -0.02 0.15 (0.21) (0.06) (0.20) (0.22) (0.02) (0.17) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 0.12* 0.001 -0.12** 0.36*** -0.00 -0.08* (0.05) (0.02) (0.05) (0.09) (0.01) (0.03) 𝑇𝑖𝑑 15.26** * 0.05 -0.01* -0.01 -0.07*** -0.01 0.02* (1.82) (0.04) (0.00) (0.01) (0.02) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž 𝑖𝑑 -19.21 -0.59** -0.02 -0.10* 0.05 -0.20 -0.00 (15.07) (0.26) (0.04) (0.06) (0.18) (0.12) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž βˆ— 𝑇𝑖𝑑 𝑖𝑑 12.88** 0.09 -0.01 0.03 0.24** 0.00 -0.02 (4.69) (0.12) (0.02) (0.02) (0.09) (0.03) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 - 39.76** * -0.71*** 0.12** -0.01 -0.41 0.06 0.07 (13.40) (0.26) (0.05) (0.05) (0.30) (0.09) (0.06) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 βˆ— 𝑇𝑖𝑑 -7.47* -0.17 0.02 -0.05** -0.19** -0.03 0.02 (4.21) (0.11) (0.02) (0.02) (0.09) (0.03) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 2.37 0.32** -0.01 0.02 -0.07 -0.05 0.03 (7.02) (0.14) (0.03) (0.07) (0.14) (0.10) (0.04) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 βˆ— 𝑇𝑖𝑑 1.37 -0.05* -0.03*** 0.02 0.06** 0.05*** -0.02** (1.29) (0.03) (0.00) (0.01) (0.03) (0.02) (0.01) 𝑇𝑖𝑑 -0.02 -0.01 0.01 0.01** -0.02** 0.06 (0.03) (0.01) (0.01) (0.01) (0.01) (0.04) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž 𝑖𝑑 0.18 0.11 -0.04 0.09 0.09 0.42** (0.22) (0.14) (0.07) (0.07) (0.07) (0.19) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž βˆ— 𝑇𝑖𝑑 𝑖𝑑 -0.08 0.04 0.02 -0.08*** -0.04 -0.18* (0.10) (0.05) (0.03) (0.01) (0.03) (0.09) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 0.53** -0.20 -0.13* 0.20*** 0.23*** 0.24 (0.24) (0.14) (0.07) (0.05) (0.07) (0.29) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 βˆ— 𝑇𝑖𝑑 0.18** -0.03 -0.00 0.09*** 0.04 0.12* (0.09) (0.05) (0.03) (0.02) (0.03) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 0.05 -0.20* -0.21*** 0.02 0.00 0.09 (0.16) (0.12) (0.06) (0.06) (0.05) (0.16) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 βˆ— 𝑇𝑖𝑑 -0.14*** -0.00 -0.02*** -0.00 0.05*** 0.09*** (0.02) (0.01) (0.01) (0.01) (0.01) (0.03)

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Sources: Research Paper

Robustness. Our results could be sensitive to the pre-disaster periods. We conduct a sensitivity analysis by extending the pre-disaster period to 12 quarters. Tables 7a to 9b show the sensitivity analysis for Thailand’s disasters, while Tables 10a and 10b show those results for the Philippine typhoons. As can be seen, the results are similar to those of the baseline. In the case of Thailand, we generally find a decline in total consumption. This decline stems from a reduction in expenditures on the service sector including transportation, hotels, and restaurants. In contrast, we generally observe increased household spending on food and non- alcoholic drinks, alcoholic beverages and tobacco products, clothing, and utilities. As seen from Table 7a, the total immediate expenditures declined by approximately 26 billion Thai baht after the Indian Ocean tsunami. Similar to our baseline results, we find housing- related expenses, including utilities and furniture, increased during this disaster. However, the estimates of the immediate expenditure declines in recreation, restaurants, and hotels are imprecise (Table 7b); yet we find the expenditure on transportation immediately dropped. Table 8a shows total consumption expenditure immediately dropped by approximately 70 billion Thai baht due to the 2011 Thailand floods. The results presented in Tables 8a and 8b resemble those of the baseline. Specifically, we find households immediately increased spending on both durable and non-durable goods. On the other hand, we find consumers immediately reduced their spending on transportation, restaurants, and hotels. Tables 9a and 9b show the results pertaining to the 2016-17 Thailand floods. We again find similar results to the baseline estimates. The total immediate consumption dropped approximately 31 billion Thai baht. Similar to aforementioned disasters in Thailand, households immediately increased spending on non-durable goods including food, beverages, tobacco, and clothing. Households also increased immediate spending on utilities. However, they reduced their spending on transportation, restaurants, and hotels. For the Philippines, the effects of the typhoons on consumption are usually small. Among the three typhoons, we still find that Typhoon Haiyan had the largest immediate effects on consumption expenditures; the total household spending immediately declined by approximately 40 billion pesos after Typhoon Haiyan. Although the magnitude of estimate shown in Table 10a is similar to that of the baseline, the estimate of total immediate household is imprecise. Similar to our bassline estimate, we do not find any significant changes in total consumption after Typhoon Meranti. Finally, we still do not find any regular patterns of change in consumption expenditures when we analyse components of consumption. (1) (2) (3) (4) (5) (6) (7) Table 7b. 𝑇𝑖𝑑 152004 Indian Ocean Earthquake and Tsunami (Continued) Transport Communication Recreation Restaurants & hotels Education Miscellaneous (8) (9) (10) (11) (12) (13) Table 8a. 2011 Floods: Sensitivity Analysis Alcohol beverages (1) (2) (3) (4) (5) (6) (7) & tobacco Table 8b. 2011 Floods: Sensitivity Analysis (Continued) Table 9a. Late 2016-Early 2017 Floods: Sensitivity Analysis (1) (2) (3) (4) (5) (6) (7) Clothing Utilities Furniture Health Notes: β–‡β–‡β–‡β–‡β–‡-β–‡β–‡β–‡β–‡ standard errors are in parentheses. We set one lag as the maximum lag order of autocorrelation. *, **, .43*** -0denote statistical significance at 10, 5, and 1 percent levels, respectively. Each consumption component is expressed as a percentage of total consumption expenditure. Total Food & Alcohol Clothing Utilities Furniture Health non- and alcoholic beverages tobacco (1) (2) (3) (4) (5) (6) (7) Table 10a. Effects of Typhoons on the Philippines’ Consumption: Sensitivity Analysis Table 10 b. Effects of Typhoons on the Philippines’ Consumption: Sensitivity Analysis (Continued) Notes: β–‡β–‡β–‡β–‡β–‡-β–‡β–‡β–‡β–‡ standard errors are in parentheses. We set one lag as the maximum lag order of autocorrelation. *, **, .09*** -0.01 -0.06*** -0.05*** 0.02** 0.03*** (0.38) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ - 25.87*** 0.26 0.34*** 0.30*** 0.38*** 0.05 0.00 (5.12) (0.19) (0.10) (0.06) (0.05) (0.04) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 4.30* 0.06 -0.05 0.07*** -0.14*** -0.03 -0.06*** (2.15) (0.10) (0.03) (0.02) (0.01) (0.02) (0.02) 𝑇𝑖𝑑 0.08** 0.04*** 0.07*** -0.09*** -0.01 0.06*** (0.03) (0.01) (0.02) (0.03) (0.01) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -0.51* 0.10 -0.07 -0.25 0.07* -0.39** (0.25) (0.08) (0.12) (0.31) (0.03) (0.17) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 -0.13** -0.02 0.004 0.28** -0.01 -0.05 (0.05) (0.02) (0.02) (0.09) (0.02) (0.06) 𝑇𝑖𝑑 17.39*** -0.22*** -0.07*** -0.06*** -0.05*** 0.06*** 0.09*** (0.92) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -70.08*** 0.89*** 0.29*** 0.39*** 0.86*** 0.12 0.09 (13.37) (0.23) (0.08) (0.05) (0.11) (0.13) (0.14) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 25.13*** -0.34*** -0.06*** -0.18*** -0.16*** -0.15** -0.18*** (4.66) (0.08) (0.02) (0.01) (0.02) (0.05) (0.04) 𝑇𝑖𝑑 0.15*** 0.00 0.09*** 0.15*** -0.01*** -0.04 (0.03) (0.02) (0.01) (0.03) (0.00) (0.03) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -2.25*** 0.20* -0.12 -0.58*** 0.04 0.51** (0.28) (0.11) (0.10) (0.17) (0.02) (0.23) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 0.98*** -0.10*** -0.01 -0.02 -0.04*** 0.09 (0.09) (0.02) (0.03) (0.04) (0.01) (0.08) 𝑇𝑖𝑑 16.72*** -0.11*** -0.04*** -0.04*** -0.00 -0.03*** -0.01 (0.62) (0.02) (0.01) (0.01) (0.01) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -30.98** 0.36*** -0.05 0.14*** 0.08 0.08 0.16 (11.82) (0.11) (0.06) (0.04) (0.11) (0.09) (0.12) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 9.36 -0.08* -0.00 -0.02 -0.04 -0.01 -0.05 (5.49) (0.04) (0.02) (0.02) (0.05) (0.03) (0.04) 𝑇𝑖𝑑 0.03* -0.02* 0.12** 0.06 -0.00 0.02 (0.02) (0.01) (0.05) (0.04) (0.00) (0.03) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ -0.19 0.18** 0.04 -0.45* -0.02 0.15 (0.21) (0.06) (0.20) (0.22) (0.02) (0.17) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘–π‘‘ βˆ— 𝑇𝑖𝑑 0.12* 0.001 -0.12** 0.36*** -0.00 -0.08* (0.05) (0.02) (0.05) (0.09) (0.01) (0.03) 𝑇𝑖𝑑 15.26** * 0.05 -0.01* -0.01 -0.07*** -0.01 0.02* (1.82) (0.04) (0.00) (0.01) (0.02) (0.01) (0.01) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž 𝑖𝑑 -19.21 -0.59** -0.02 -0.10* 0.05 -0.20 -0.00 (15.07) (0.26) (0.04) (0.06) (0.18) (0.12) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž βˆ— 𝑇𝑖𝑑 𝑖𝑑 12.88** 0.09 -0.01 0.03 0.24** 0.00 -0.02 (4.69) (0.12) (0.02) (0.02) (0.09) (0.03) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 - 39.76** * -0.71*** 0.12** -0.01 -0.41 0.06 0.07 (13.40) (0.26) (0.05) (0.05) (0.30) (0.09) (0.06) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 βˆ— 𝑇𝑖𝑑 -7.47* -0.17 0.02 -0.05** -0.19** -0.03 0.02 (4.21) (0.11) (0.02) (0.02) (0.09) (0.03) (0.02) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 2.37 0.32** -0.01 0.02 -0.07 -0.05 0.03 (7.02) (0.14) (0.03) (0.07) (0.14) (0.10) (0.04) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 βˆ— 𝑇𝑖𝑑 1.37 -0.05* -0.03*** 0.02 0.06** 0.05*** -0.02** (1.29) (0.03) (0.00) (0.01) (0.03) (0.02) (0.01) 𝑇𝑖𝑑 -0.02 -0.01 0.01 0.01** -0.02** 0.06 (0.03) (0.01) (0.01) (0.01) (0.01) (0.04) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž 𝑖𝑑 0.18 0.11 -0.04 0.09 0.09 0.42** (0.22) (0.14) (0.07) (0.07) (0.07) (0.19) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ΅π‘œπ‘β„Žπ‘Ž βˆ— 𝑇𝑖𝑑 𝑖𝑑 -0.08 0.04 0.02 -0.08*** -0.04 -0.18* (0.10) (0.05) (0.03) (0.01) (0.03) (0.09) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 0.53** -0.20 -0.13* 0.20*** 0.23*** 0.24 (0.24) (0.14) (0.07) (0.05) (0.07) (0.29) οΏ½denote statistical significance at 10, 5, and 1 percent levels, respectively. Each consumption component is expressed as a percentage of total consumption expenditure.οΏ½π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ»π‘Žπ‘–π‘¦π‘Žπ‘› 𝑖𝑑 βˆ— 𝑇𝑖𝑑 0.18** -0.03 -0.00 0.09*** 0.04 0.12* (0.09) (0.05) (0.03) (0.02) (0.03) (0.07) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 0.05 -0.20* -0.21*** 0.02 0.00 0.09 (0.16) (0.12) (0.06) (0.06) (0.05) (0.16) π·π‘–π‘ π‘Žπ‘ π‘‘π‘’π‘Ÿπ‘€π‘’π‘Ÿπ‘Žπ‘›π‘‘π‘– 𝑖𝑑 βˆ— 𝑇𝑖𝑑 -0.14*** -0.00 -0.02*** -0.00 0.05*** 0.09*** (0.02) (0.01) (0.01) (0.01) (0.01) (0.03)

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