Gaussian process modeling of nonstationary crop yield distributions with applications to crop insurance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wenbin Wu ◽  
Ximing Wu ◽  
Yu Yvette Zhang ◽  
David Leatham
Keyword(s):  
Gaussian Process ◽  
Crop Yield ◽  
Bayesian Model Averaging ◽  
Crop Yields ◽  
Crop Insurance ◽  
Model Averaging ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Content Type ◽  
Stage Estimation

PurposeThe purpose of this paper is to bring out the development of a flexible model for nonstationary crop yield distributions and its applications to decision-making in crop insurance.Design/methodology/approachThe authors design a nonparametric Bayesian approach based on Gaussian process regressions to model crop yields over time. Further flexibility is obtained via Bayesian model averaging that results in mixed Gaussian processes.FindingsSimulation results on crop insurance premium rates show that the proposed method compares favorably with conventional estimators, especially when the underlying distributions are nonstationary.Originality/valueUnlike conventional two-stage estimation, the proposed method models nonstationary crop yields in a single stage. The authors further adopt a decision theoretic framework in its empirical application and demonstrate that insurance companies can use the proposed method to effectively identify profitable policies under symmetric or asymmetric loss functions.

Diversifying systemic risk in agriculture

2016 ◽  
Vol 76 (4) ◽  
pp. 512-531 ◽  
Author(s):  
Xiaoguang Feng ◽  
Dermot Hayes
Keyword(s):  
Crop Yield ◽  
Systemic Risk ◽  
Crop Insurance ◽  
Tail Dependence ◽  
Model Potential ◽  
High Dimensional ◽  
Computationally Efficient ◽  
Content Type ◽  
Insurance Portfolio ◽  
Systemic Nature

Purpose Portfolio risk in crop insurance due to the systemic nature of crop yield losses has inhibited the development of private crop insurance markets. Government subsidy or reinsurance has therefore been used to support crop insurance programs. The purpose of this paper is to investigate the possibility of converting systemic crop yield risk into “poolable” risk. Specifically, this study examines whether it is possible to remove the co-movement as well as tail dependence of crop yield variables by enlarging the risk pool across different crops and countries. Design/methodology/approach Hierarchical Kendall copula (HKC) models are used to model potential non-linear correlations of the high-dimensional crop yield variables. A Bayesian estimation approach is applied to account for estimation risk in the copula parameters. A synthetic insurance portfolio is used to evaluate the systemic risk and diversification effect. Findings The results indicate that the systemic nature – both positive correlation and lower tail dependence – of crop yield risks can be eliminated by combining crop insurance policies across crops and countries. Originality/value The study applies the HKC in the context of agricultural risks. Compared to other advanced copulas, the HKC achieves both flexibility and parsimony. The flexibility of the HKC makes it appropriate to precisely represent various correlation structures of crop yield risks while the parsimony makes it computationally efficient in modeling high-dimensional correlation structure.

scholarly journals Prediction Model for Antimalarial Activities of Hemozoin Inhibitors by Using Physicochemical Properties

2018 ◽  
Vol 62 (5) ◽  
Author(s):  
Farhana Mosaddeque ◽  
Shusaku Mizukami ◽  
Mohamed Gomaa Kamel ◽  
Awet Alem Teklemichael ◽  
Truong Van Dat ◽  
...  
Keyword(s):  
Physicochemical Properties ◽  
Distribution Coefficient ◽  
High Throughput Screening ◽  
Bayesian Model Averaging ◽  
Prediction Models ◽  
Antimalarial Activity ◽  
Model Averaging ◽  
Content Type ◽  
D Values

ABSTRACT The rapid spread of strains of malaria parasites that are resistant to several drugs has threatened global malaria control. Hence, the aim of this study was to predict the antimalarial activity of chemical compounds that possess anti-hemozoin-formation activity as a new means of antimalarial drug discovery. After the initial in vitro anti-hemozoin-formation high-throughput screening (HTS) of 9,600 compounds, a total of 224 hit compounds were identified as hemozoin inhibitors. These 224 compounds were tested for in vitro erythrocytic antimalarial activity at 10 μM by using chloroquine-mefloquine-sensitive Plasmodium falciparum strain 3D7A. Two independent experiments were conducted. The physicochemical properties of the active compounds were extracted from the ChemSpider and SciFinder databases. We analyzed the extracted data by using Bayesian model averaging (BMA). Our findings revealed that lower numbers of S atoms; lower distribution coefficient (log D) values at pH 3, 4, and 5; and higher predicted distribution coefficient (ACD log D) values at pH 7.4 had significant associations with antimalarial activity among compounds that possess anti-hemozoin-formation activity. The BMA model revealed an accuracy of 91.23%. We report new prediction models containing physicochemical properties that shed light on effective chemical groups for synthetic antimalarial compounds and help with in silico screening for novel antimalarial drugs.

Incorporating aleatory and epistemic uncertainties in the modelling of construction duration

2020 ◽  
Vol 27 (9) ◽  
pp. 2199-2219
Author(s):  
Hassan Adaviriku Ahmadu ◽  
Ahmed Doko Ibrahim ◽  
Yahaya Makarfi Ibrahim ◽  
Kulomri Jipato Adogbo
Keyword(s):  
Construction Projects ◽  
Bayesian Model Averaging ◽  
Predictive Accuracy ◽  
Tertiary Education ◽  
Model Averaging ◽  
Building Construction ◽  
Percentage Error ◽  
Content Type ◽  
The Impact ◽  
Matlab Programming

PurposeThis study aims to develop a model which incorporates the impact of both aleatory and epistemic uncertainties into construction duration predictions, in a manner that is consistent with the nature/quality of information available about various factors which bring about uncertainties.Design/methodology/approachData relating to 178 completed Tertiary Education Trust Fund (TETfund) building construction projects were obtained from construction firms via questionnaire survey. Using 90% of the data, the model was developed in the form of a hybrid-based algorithm implemented through a suitable user-friendly graphical user interface (GUI) using MATLAB programming language. Bayesian model averaging, Monte Carlo simulation and fuzzy logic were the statistical methods used for the algorithm development, prior to its GUI implementation in MATLAB. Using the remaining 10% data, the model's predictive accuracy was assessed via the independent samples t-test and the mean absolute percentage error (MAPE).FindingsThe developed model's predictions were found not statistically different from those of actual duration estimates in the 10% test data, with a MAPE of just 2%. This suggests that the model's ability to incorporate both aleatory and epistemic uncertainties improves accuracy of duration predictions made using it.Research limitations/implicationsThe model was developed using a particular type of building projects (TETfund building construction projects), and so its use is limited to projects with characteristics similar to those used for its development.Practical implicationsThe developed model's predictions are expected to serve as a useful basis for consultancy firms and contractor organisations to make more realistic schedules and benchmark measures of construction period, thereby facilitating effective planning and successful execution of construction projects.Originality/valueThe study presented a model which permits combined manipulation of aleatory and epistemic uncertainties, hence ensuring a more realistic incorporation of uncertainty into construction duration predictions.

Determinants of corruption in developing countries: case of Tunisia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Azzouz Zouaoui ◽  
Mounira Ben Arab ◽  
Ahmad Mohammed Alamri
Keyword(s):  
Developing Countries ◽  
Unemployment Rate ◽  
Bayesian Model Averaging ◽  
Estimation Method ◽  
Model Averaging ◽  
Public Expenditures ◽  
Annual Data ◽  
Content Type ◽  
Determinants Of Corruption ◽  
The Government

Purpose This paper aims to investigate the economic, political or sociocultural determinants of corruption in Tunisia. Design/methodology/approach To better understand the main determinants of corruption in Tunisia. This study uses The Bayesian Model Averaging (BMA) model, which allows us to include a large number of explanatory variables and for a shorter period. Findings The results show that economic freedom is the most important variable of corruption in Tunisia. In second place comes the subsidies granted by the government, which is one of the best shelters of corruption in Tunisia through their use for purposes different from those already allocated to them. Third, this paper finds the high unemployment rate, which, in turn, is getting worse even nowadays. The other three factors considered as causal but of lesser importance are public expenditures, the human development index (HDI) and education. Education, the HDI and the unemployment rate are all socio-economic factors that promote corruption. Originality/value The realization of this study will lead to triple net contributions. The first is to introduce explicitly and simultaneously political, social and economic determinants of corruption in developing countries. Second, unlike previous studies based on the simple and generalized regression model, the present research uses another novel and highly developed estimation method. More precisely, this study uses the BMA model, on the set of annual data for a period of 1998–2018. The third contribution of this research resides in the choice of the sample.

scholarly journals Seasonal variation and its impacts in rice-growing regions of the Mekong Delta

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Van Hong Nguyen ◽  
Hoang Phan Hai Yen
Keyword(s):  
Seasonal Variation ◽  
Crop Yield ◽  
Crop Yields ◽  
Rice Variety ◽  
Mekong Delta ◽  
Production Costs ◽  
Weather Factors ◽  
Content Type ◽  
Weather Factor ◽  
Food And Agriculture

Purpose In recent years, agricultural activities in the Mekong Delta have frequently faced the potential risks of drought, saline intrusion and unusually heavy rainfall because of climate change, leading to a decline in crop yield. Therefore, this study aimed to establish rice planting seasons in An Giang, an upper-located province in the Mekong Delta. Design/methodology/approach The impacts of seasonal variation on the key rice seasons were simulated using the Food and Agriculture Organization-crop model for the OM6976 rice variety grown in the study area. For the simulation, the model combined crop, soil, weather and crop management data. Findings The results show that seasonal variation because of changes in weather factors leads to alternation in crop yields across the study area. Specifically, the spring and summer rice planting seasons are advanced by one to two weeks compared with the baseline, and crop yield increased by 5.9% and 4.2%, respectively. Additionally, planting for the autumn–winter rice season on 3 August increased crop yield by up to 8.1%. Originality/value In general, rice planting seasons that account for weather factor changes effectively reduce production costs and optimise production.

Does a meaningful relationship exist between copper prices and economic growth in Zambia?

2019 ◽  
Vol 10 (1) ◽  
pp. 72-84 ◽  
Author(s):  
Sydney Chikalipah
Keyword(s):  
Economic Growth ◽  
Causal Relationship ◽  
Bayesian Model Averaging ◽  
Empirical Studies ◽  
Model Averaging ◽  
Policy Implications ◽  
Metal Exchange ◽  
Data Set ◽  
Content Type ◽  
Heritage Foundation

PurposeThe purpose of this paper is to examine the causal relationship between the copper price dynamics and economic growth in Zambia over the period from 1995 to 2015.Design/methodology/approachThe study uses a data set assembled from five difference sources: the heritage foundation; the London metal exchange index; the Penn World Tables version 9.0; the total economy database; and the World Bank Development Indicators. The paper employs the Bayesian Model Averaging (BMA) approach as the estimation technique.FindingsThe estimates demonstrate that there exists a positive and significant relationship between movements in copper prices and economic growth in Zambia. The study draws policy implications from these findings.Research limitations/implicationsThis study is limited to the period from 1995 to 2015, this is due to lack of data on the country’s institutional indicators, trade openness and the real exchange rate.Practical implicationsThere have been calls to diversify the economy of Zambia due to the recurring chaotic events, which are often induced by over-dependence on copper exports. Thus, the study findings will be useful to academia, policy makers and stakeholders with vested interest in the economy of Zambia.Originality/valueTo the best of the author’s knowledge, this is the first empirical study to investigate the causal relationship that exists between copper prices and economic growth in Zambia. The existing empirical studies in the domain have devoted their attention on establishing the relationship between commodity price movements and exchange rates in Zambia.

Risk‐efficient portfolio crop choice with amended water and irrigation policies in northern Germany

2013 ◽  
Vol 73 (2) ◽  
pp. 373-388 ◽  
Author(s):  
Matthias Buchholz ◽  
Oliver Musshoff
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Future Research ◽  
Programming Approach ◽  
Northern Germany ◽  
Gross Margin ◽  
Economic Implications ◽  
Content Type ◽  
Crop Choice ◽  
Irrigation Intensity

PurposeIncreasing environmental concerns have placed the need for an enhanced water resources management on the policy agenda. In this context, a restrictive regulation of water withdrawals for irrigation has gained in importance. The purpose of this paper is to investigate how a reduction in water quotas and increased water prices affect risk‐efficient crop choices and the related economic implications for northern German farmers.Design/methodology/approachThe authors apply a whole‐farm risk programming approach to a typical arable farm in northern Germany. By using irrigation field trials, production activities with varying irrigation intensities and inherently incorporated crop yield uncertainty are defined.FindingsIn contrast to increased water prices, a reduction in water quotas leads to higher water savings and lower economic disadvantages for farmers. Due to an adjusted portfolio crop choice, as well as irrigation intensity, the reduction in the expected total gross margin is partially offset.Research limitations/implicationsThis example ensures volumetric water monitoring at the farm level which, however, remains a major pitfall in many other countries. From a methodological perspective, the crop yield distribution choice might affect the findings. Likewise, the consideration of downside risk in an irrigation context appears to be interesting for future research.Originality/valueThis is the first paper to compare the implications of differentiated water quotas and water pricing schemes suggested by the European Water Framework Directive, while taking risk‐efficient crop portfolio considerations into account. This approach facilitates water reallocation not only between crops, but also in terms of the crop‐specific irrigation intensity. Crop yields are based on a unique panel of micro data rather than expert opinions or simulations.

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