Chaotic Features of Decomposed Time Series from Tidal River Water Level

This study assessed the characteristics of water-level time series of a tidal river by decomposing it into tide, wave, rainfall-runoff, and noise components. Especially, the analysis for chaotic behavior of each component was done by estimating the correlation dimension with phase-space reconstruction of time series and by using a close returns plot (CRP). Among the time series, the tide component showed chaotic characteristics to have a correlation dimension of 1.3. It was found out that the water level has stochastic characteristics showing the increasing trend of the correlation exponent in the embedding dimension. Other components also showed the stochastic characteristics. Then, the CRP was used to examine the characteristics of each component. The tide component showed the chaotic characteristics in its CRP. The CRP of water level showed an aperiodic characteristic which slightly strayed away from its periodicity, and this might be related to the tide component. This study showed that a low water level is mainly affected by a chaotic tide component through entropy information. Even though the water level did not show chaotic characteristics in the correlation dimension, it showed stochastic chaos characteristics in the CRP. Other components showed stochastic characteristics in the CRP. It was confirmed that the water level showed chaotic characteristics when it was not affected by rainfall and stochastic characteristics deviating from the bounded trajectory when water level rises due to rainfall. Therefore, we have shown that the water level related to the chaotic tide component can also have chaotic properties because water level is influenced by chaotic tide and rainfall shock, thus it showed stochastic chaos characteristics.

Coping with negative shocks and the role of the farm input subsidy programme in rural Malawi

This study uses household panel data from Malawi's 2010/11 and 2012/13 Integrated Household Panel Survey to investigate the mitigating role of its Farm Input Subsidy Programme (FISP) against the deleterious impacts of negative rainfall shock on households’ welfare in rural Malawi. The study finds that the FISP has a cushioning role on the negative impact of rainfall shocks. The use of a farm input subsidy scheme enables rural households to substantially increase their food consumption and overall food security, despite the increasing threat of climate change. The results of this study highlight the importance of agricultural policy, such as the FISP, in rural households’ mitigation of weather risk.

Impact of climate change on food yield in Senegal: FAVAR approach

The main objective of this research is to evaluate the impact of climate change on food crop yields in Senegal using the Factor Augmented Vector Auto Regression (FAVAR) approach. The estimation method used is principal components analysis. We identified two major shocks representative of climate change. The first is an increase of temperature (thermal shock) and the second is a decrease in the quantity of precipitation (rainfall shock). The data covers the period 1970-2014 and each of the shocks is carried out over the prior year. The impact of each shock is observed along a time horizon of 10 years. The results show a positive impact of the thermal shock on the yields of rice, maize and millet, with a much greater impact on rice and maize yield. Rising temperatures are, however, detrimental to sorghum. A decline in rainfall has a negative impact on the yields of all cereals, which is in line with expectations.

Do Public Fund Windfalls Increase Corruption? Evidence From a Natural Disaster

We show that unexpected financial windfalls increase corruption in local government. Our analysis uses a new data set on flood-related transfers, and the associated spending infringements, which the Bulgarian central government distributed to municipalities following torrential rains in 2004 and 2005. Using information from the publicly available audit reports, we are able to build a unique objective index of corruption. We also exploit the quasi-random nature of the rainfall shock (conditional on controls for ground flood risk) to isolate exogenous variation in the amount of funds received by each municipality. Our results imply that a 10% increase in the per capita amount of disbursed funds leads to a 9.8% increase in corruption. We also present suggestive evidence that more corrupt mayors anticipated punishment by voters and dropped out of the next election race. Our results highlight the governance pitfalls of nontax transfers, such as disaster relief or assistance from international organizations, even in moderately strong democracies.