# The Effect of Rainfall on Economic Growth in Thailand: A Blessing for Poor Provinces
## 4 Results and Discussion
### Economic Sector Results
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **(1)** & **(2)** & **(3)** & **(4)** \\ \hline
**Panel A. Dependent variable is growth in agriculture value added** & & & & \\ Precipitation (100 mm/year) & \(-\)0.0316 ** & \(-\)0.0581 *** & \(-\)0.0584 *** & \(-\)0.0586 *** \\  & (0.0109) & (0.0131) & (0.0133) & (0.0133) \\ Precipitation interact with \(\ldots\) & & & & \\ Poor province dummy & & & & \\  & & & & \\  & & & & \\ Temperature (Celsius) & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multicolumn{4}{l}{**Panel B. Dependent variable is growth in industrial value added**} & & \\ Precipitation (100 mm/year) & 0.0212 & 0.00975 & 0.0134 & 0.0132 \\  & (0.0130) & (0.0157) & (0.0159) & (0.0159) \\ Precipitation interact with \(\ldots\) & & & & \\ Poor province dummy & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \multicolumn{4}{l}{Poor province dummy} & & 0.0325 & 0.0262 & 0.0262 \\  & & (0.0250) & (0.0258) & (0.0258) \\ Temperature (Celsius) & & & & 0.0196 & 0.0193 \\  & & & & (0.0148) & (0.0148) \\ Temperature interact with \(\ldots\) & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ Population growth & & & & \\  & & & & \\ Constant & \(-\)0.105 *** & \(-\)0.126 *** & \(-\)0.369 & \(-\)0.0821 \\  & (0.0314) & (0.0354) & (0.2284) & (0.2210) \\ Observations & 1596 & 1596 & 1596 & 1596 \\ Log likelihood & 1090.343 & 1091.191 & 1092.098 & 1092.187 \\ \hline \multicolumn{4}{l}{**Panel C. Dependent variable is growth in service value added**} & & \\ Precipitation (100 mm/year) & \(-\)0.0132 * & \(-\)0.0173 * & \(-\)0.0166 * & \(-\)0.0169 * \\  & (0.0057) & (0.0069) & (0.0070) & (0.0070) \\ Precipitation interact with \(\ldots\) & & & & \\ Poor province dummy & & 0.0119 & 0.0107 & 0.0107 \\  & (0.0110) & (0.0114) & (0.0113) \\ Temperature (Celsius) & & & 0.00444 & 0.00365 \\  & & & (0.0065) & (0.0065) \\ Temperature interact with \(\ldots\) & & & & \\ Poor province dummy & & & \(-\)0.00259 & \(-\)0.00163 \\  & & & (0.0064) & (0.0064) \\ Population growth & & & & \\  & & & & \\  & & & & \\ Constant & 0.0546 *** & 0.0462 ** & \(-\)0.0546 & 0.0168 \\  & (0.0151) & (0.0170) & (0.1007) & (0.0971) \\ Observations & 1596 & 1596 & 1596 & 1596 \\ Log likelihood & 2335.928 & 2336.511 & 2336.795 & 2341.986 \\ \hline \hline \end{tabular} Notes: 1. Standard errors in parentheses; 2. Time and provincial fixed effects were included (coefficient not reported); 3. * Significant at 10%, ** Significant at 5%, *** Significant at 1%; 4. Industry classifications (refer to Table 4).  
\end{table} 
Table 3: Economic sector panel results. Sample: 76 provinces (1995–2015); Estimation method: FGLS. Other agricultural products come from the South, which receives the highest volume of rainfall and is a large area covering 14 provinces. A potential explanation for why rainfall has a negative impact on the agricultural sector is that heavy rain events during the growing season may ruin agricultural products. During the rainy season, Thailand has also suffered from floods every year from 1986 to 2015 (The National Statistical Office of Thailand 2018). Very heavy rainfall can result in flooding, which can destroy agricultural products. Additionally, precipitation has a major role in the Thai agricultural sector since approximately 10,000 ha of the country's 13,100 ha of farming area is located away from irrigated areas (Bank of Thailand 2006). This means that 80% of the country's farmland is dependent on rainfall making Thai crop yields particularly sensitive to rainfall. The present research also studied farming1 and fishing as agricultural subsectors, with both found to be negatively affected by precipitation although this was not significant for fishing (refer to Table 4). However, Thailand's northern and northeastern regions benefit from such precipitation.