Sigitas Vaitkevičius, V. Aleknevičienė, L. Girdžiūtė, A. Miceikienė
{"title":"Integrated Risk Assessment: Case Study of Lithuanian Family Farms","authors":"Sigitas Vaitkevičius, V. Aleknevičienė, L. Girdžiūtė, A. Miceikienė","doi":"10.5755/j01.ee.30.4.23502","DOIUrl":null,"url":null,"abstract":"This study is designed to develop the tool for risk assessment under the integrated approach. Analyzing risk several problems are encountered: the first one arises at the farm level – assessment of risk in the whole-farm context rather than in a partial context, i.e. an integrated risk assessment tool is necessary. The second problem is related to the dynamic aspect when determining how the risk changes over time and what the main drivers of these changes are. All these problems are solved in the presented research, creating an integrated risk assessment index (IRAI) and testing it in Lithuanian family farms. This index assesses four types of risk: economic, financial, production, and political. The research methodology is developed to make sure that the data collected on the IRAI behavior is as diverse as possible. A model of IRAI variation by farm size illustrating risk evolution at the Lithuanian farms and, at the same time, enabling visual diversification of the dependence of integrated risk on farm size is developed. Hierarchical cluster analysis is applied for identification of the integrated risk evolution models. Assessment of the interaction between the IRAIand output and input using nonparametric Kruskal-Wallis testis used to find out whether the type of integrated risk is based on differential logic. IRAI was tested using official statistical data of 1300 family farms collected in 2004–2013 for institutional purposes. The testing revealed that the designed IRAI allows identifying types of farms by their risk evolvement profiles and the key risk (s) acting on the farm in the historical period. Four meaningful clusters representing the changing pattern of the risk are identified during the testing of IRAI: increasing risk farms; reducing risk farms; relatively constant risk farms; varying risk farms. IRAI can be applied both for macro analysis (at a national, EU or other levels) and microanalysis (at the level of a single farm).","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2019-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inzinerine Ekonomika-Engineering Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.5755/j01.ee.30.4.23502","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1
Abstract
This study is designed to develop the tool for risk assessment under the integrated approach. Analyzing risk several problems are encountered: the first one arises at the farm level – assessment of risk in the whole-farm context rather than in a partial context, i.e. an integrated risk assessment tool is necessary. The second problem is related to the dynamic aspect when determining how the risk changes over time and what the main drivers of these changes are. All these problems are solved in the presented research, creating an integrated risk assessment index (IRAI) and testing it in Lithuanian family farms. This index assesses four types of risk: economic, financial, production, and political. The research methodology is developed to make sure that the data collected on the IRAI behavior is as diverse as possible. A model of IRAI variation by farm size illustrating risk evolution at the Lithuanian farms and, at the same time, enabling visual diversification of the dependence of integrated risk on farm size is developed. Hierarchical cluster analysis is applied for identification of the integrated risk evolution models. Assessment of the interaction between the IRAIand output and input using nonparametric Kruskal-Wallis testis used to find out whether the type of integrated risk is based on differential logic. IRAI was tested using official statistical data of 1300 family farms collected in 2004–2013 for institutional purposes. The testing revealed that the designed IRAI allows identifying types of farms by their risk evolvement profiles and the key risk (s) acting on the farm in the historical period. Four meaningful clusters representing the changing pattern of the risk are identified during the testing of IRAI: increasing risk farms; reducing risk farms; relatively constant risk farms; varying risk farms. IRAI can be applied both for macro analysis (at a national, EU or other levels) and microanalysis (at the level of a single farm).