Political risk, like all other risks, has an adverse effect on any economy. Even though other forms of risk, such as economic risk and financial risk have been studied quite extensively, political risk has not received much attention owing primarily to lack of data. The current paper attempts to study a negative and significant relationship between political risk and Foreign Direct Investment (FDI), accounting for 94 countries over a span of 24 years from 1986-2009. It was found that most of the political risk indicators have a negative relationship with FDI for the world as a whole and also, the high-income countries but the relationship was the strongest for the upper middle-income countries.

Segara Anakan, Cilacap District is an area that embodies the largest mangrove forest in Indonesia, namely 8,576.06 ha in 2016. The observation and mapping of vegetation index surrounding the forest are done by utilizing remote sensing to acquire satellite images. Plants have adequate reflectance to Near Infrared (NIR) lights. Normalized Vegetation Index (NDVI) is classified to have high accuracy in mapping mangrove in an area. The concept of NDVI is considerably simple, namely by observing the best NIR light reflected by the chlorophyll and red light radiation absorbed by green plants. Algorithm or equation used is (NIR - RED)/(NIR + RED). The results from the algorithm will then be used to derive index value ranging from -1 to 1. This index value will be employed as a parameter to indicate whether the mangroves are healthy or not. This study is done in 2020 incorporating data from 2017 to 2020 that are relevant to Segara Anakan, Cilacap District and implementing NDVI method to analyze the mangroves’ health. Results from the satellite images show that mangroves in Segara Anakan are experiencing a negative trend regarding their health from year to year. The result in 2017 shows a majority of 0.9 index with pixel vegetation frequency of 17,500 which drastically declined in 2020 to only 7,000 with majorities of 0,2;0,6;0,8 which is caused by deforestation and natural causes inhibiting the sowing and growth of mangroves.

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For this paper we conducted a regional analysis (RA) of annual peak flows using linear combination of order statistics, i.e., linear-moments (LM) and trimmed linear moments (TLM). Design flood estimates are calculated and compared at different return periods, which are useful for water resources management, including hydrological structures and basin management. The main objective of our study was to compare regional design flood estimates for untrimmed and trimmed samples. LM is the special case of TLM, when we have no trimming from either side. First, regional flood frequency analysis is performed for LM and then for TLM. After initial screening of the annual peak flow series, a discordancy measure was used to diagnose the discordant sites. No site was found to be discordant. For homogeneity of the region, the homogeneity measure "H" was employed using simulation study based on Kappa distribution, and found that the nine sites on the Indus Basin included in the study constitute a single homogeneous region. In this study we used TLM with trimming values (γ, 0), where γ = 1, 2, 3, 4. In order to determine the most appropriate probability distribution for regional quantile estimates, different probability distributions are used, namely: generalized extreme value (GEV), generalized pareto (GPA), generalized logistic (GLO), Pearson type three (PE3), and generalized normal (GNO). L-moments ratio diagram and Z-test as goodness of fit are engaged to identify the most suitable probability distribution. A comparison revealed that GNO is the best distribution for first three cases as (0, 0), (1, 0), and (2, 0), while for the last two cases of (3, 0) and (4, 0) the most appropriate choice is GEV. A simulation study was also carried out to evaluate the performance and robustness of the best fit probability distribution using relative bias (RB) and relative root mean square error (RRMSE).