Basic Regression

The primary aim of this paper is to measure how the potential damage induced by typhoons affects local economic activity as measured by TFP following the approach to the measurement of TFP by De Loecker (2007). Our key estimation equation is

57 According to the NOAA scale, 1 corresponds to “No real damage to building structure. Damage primarily to unanchored mobile homes, shrubbery, and trees. Also, some coastal road flooding and minor pier damage”, scale 3 refers to “Some structural damage to small residences and utility buildings with a minor amount of curtain wall failures. Mobile homes are destroyed. Flooding near the coast destroys smaller structures larger structure damaged by floating debris. Terrain continuously lower than 5 feet ASL may be flooded inland 8 miles or more.”

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where TFP is the TFP calculated based on the full sample of CASIF data including the firms located in the whole of China and then merged for each observations using each unique firm ID and is the error term.⁵⁸ Wage is the deflated wage value, labour is number of employees for each observations and output is represented by production sales.⁵⁹ The variable allows for unobserved individual observation time invariant effects that might be correlated with both typhoon destruction and economic activity.

More precisely, whilst actual typhoon incidence can be considered to be an exogenous shock it can be shown that some areas of China are more prone to typhoons than others (southern coastal China is more prone that northern coastal China) and hence economic agents will know this in turn may invest move heavily in typhoon damage prevention or choose to locate elsewhere which will lead to less economic activity being recorded in those areas. To control for this possibility we use a fixed effects estimator. We also include time dummies that will take account of anytime varying common changes in economic factors (such as aggregate disaster mitigation investment set at the central government level). Finally, captures the wind speed and implies the potential power and destruction of typhoons once a typhoon that makes landfall and is either 119 km/hr or 178km/hr. Table 4.4 provides a summary of our key estimators in the regressions which in this case are V_178 and V_119 and represent the wind speeds at Saffir-Simpson scale 1 and 3 respectively. The annual average temperature is between and while total annual rain fall is between 26mm to 3,858mm. The number of observations with wages less than 1 thousand RMB (deflated) less than 10 employees or with less than 100,000 RMB production sales (deflated) is only 3, 118 and 120

58 The TFP value cannot be calculated by using only sample of enterprises located in the coastal regions due to collinearity and therefore we use the cleaned full sample of CASIF to estimate TFP of each observation and merge the TFP values for each of the firms for each year in our coastal region sample.

59 All deflated values are in 2000 prices.

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respectively.

Tables 4.5. 4.6, 4.7, 4.8, 4.9 and 4.10 present our regression results using wind speeds (below 119km/hr and below 178km/hr) to examine the impact of typhoon damage on our main economic indicators based on equations (5) to (9). We also include the lagged value of wind speed to estimate if a typhoon that damaged a firm still impacts the economy in the following one or two years’ time.

[Table 4.5 about here]

[Table 4.6 about here]

[Table 4.7 about here]

[Table 4.8 about here]

[Table 4.9 about here]

[Table 4.10 about here]

The results in table 4.5 show that typhoons have a negative and significant impact on TFP. However, there is no evidence to show that typhoons also significantly negatively impact TFP in the following two years. Typhoons at scale 1 also show a significant and negative impact on the deflated export value in the current year and export quickly recovers in the following year. In Table 4.8 we find similar results for the correlation between output value and typhoon strikes although we also find a positive impact on output in the following year (column 9) suggesting that production activity recovers quickly. The impact on wages is similar with a current year negative effect but positive one year later but negative again two years later. The negative and significant impact of typhoon on wage in the current year implies the typhoon damage lead social welfare losses. When we look at employment we found an insignificant effect for the current year.

In general, we find that typhoons at scale 1 wind speed have a negative impact on economic activity. In order to recover quickly from the disaster, employers may hire more labour in the year the typhoon hits to help with reconstruction of buildings to fulfil

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delayed orders. But as production recovers to pre-typhoon standard, the excess labour would no longer need. Finally, the typhoon damages appear to lead to a reduction in wages in the year of the typhoon and recover in the following year. The correlation again turns significantly negative which is consistence with the correlation between typhoon and number of workers. The reduction in wages may result is workers resigning. In Tables 4.8, 4.9 and 4.10 we repeat the regressions for the higher scale 3 typhoons.

Reassuringly we find generally higher coefficients although the general level of significance is broadly similar. Typhoons at scale 3 have less strong but significant impacts on export as its less happened frequency and shorter time. However, it has longer impacts until the third year that typhoons occurred and a positive and significant impact reflect the exporting has to take longer to repair international trade relations.

Other main difference is that employment is consistently positive in the year of the typhoon. In summary, the weaker typhoon still has a significant impact in the current year but stronger typhoons appear to demonstrate a longer and stronger negative impact on economic activity and fluctuations in wage and employee numbers.