This article aims to show the potential contribution of high-yielding rice varieties to achieve sustainable intensification in paddy farming, by focusing on a developing country. A comparative life cycle assessment of traditional vs. high-yielding varieties is carried out by comparing the area-based and yield-based results. Primary data are collected through a farm survey (49 farms in the Mazandaran province, Iran; spring 2018). The results highlight that high-yielding varieties can reduce the yield-scaled impacts. However, area-scaled impacts are subject to increase for most impact categories. Statistically significant trade-offs involve global warming potential (+13% per ha and −28% per t in high-yielding varieties) and fossil resource depletion (+15% per ha and −26% per t in high-yielding varieties). Pesticide management is the most alarming practice. High-yielding varieties increase pesticide consumption and related toxicity impacts both per t and per ha. This study is a new contribution to the literature by improving and broadening the mainstream productivity perspective of current life cycle assessment research about crop varieties. The lessons learnt from this study suggest that the trade-offs between yield-scaled and area-scaled impacts should be carefully considered by decision-makers and policymakers, especially in developing countries that, like Iran, are affected by the overexploitation of natural resources. Targeted policy and the development of farmer education and advisory services are needed to create the enabling conditions for farm management changes, including conscious use of production inputs while avoiding heuristics.

Abstract This study classifies local self-government units (local communities) in the Federation of Bosnia and Herzegovina (FBIH) according to socio-economic characteristics by applying the following multivariate methods: principal component analysis (PCA), regression and cluster analysis. The selection of variables was based on literature and adjusted by FBIH specifics, covering the four hypothetical dimensions of regional differentiation: macroeconomic, demographic, infrastructural and socio-cultural indicators. PCA has identified five components: the productivity component, demographic component, component of economic activity potential, spatial component and employment component. Further analysis showed that all identified factors are significant predictors of local communities’ development, measured by the development index. The cluster analysis resulted with four clusters in the FBIH with significant differences in development level. Considering that FBIH municipalities are administrative units of local government and that the classification is based on socio-economic dimensions, identified clusters correspond to the NUTS principles.

Comparing portfolio performance is complex due to the fact that each model is dominant in its own risk space. Since there is no single dominant performance measure, the research problem is how to incorporate several different measures into a performance evaluation model that allows portfolios to be ranked. In this regard, the objective of this study was to develop a new comprehensive method for comparing portfolio performance based on multiple-criteria decision-making (MCDM). This paper proposes an integrated approach for stock market decision making that combines the Analytic Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), which allow hierarchical evaluation of a finite number of alternatives according to different criteria. This hybrid approach is especially advantageous, utilizing the strengths of both individual methods. AHP enables the decomposition of a complex problem into its constituent parts and the determination of weights for criteria, while the PROMETHEE method allows the investor to determine the preference function, complete ranking, and analysis of the robustness of the results. For the MCDM model in this study, different dimensions of performance measures are considered criteria: return measures, risk measures, stability measures, and predictability measures. The methodology has been applied in comparing real portfolios selected on the basis of different risk measures. For this purpose, weekly return data were used for a sample of stocks that are components of the STOXX Europe 600 Index for the period 2000–2020. In addition, a sensitivity analysis is performed to investigate the strength of the results of this method. It suggests that the simultaneous consideration of different performance measures and the investor’s attitude towards the importance of these measures are notably important in the portfolio efficiency estimation process.

Abstract This paper analyses the inefficiency of social services targeting in the Federation of Bosnia and Herzegovina (FB&H). Using official statistics microdata of the Household Budget Survey 2015, three models of social minimum in FB&H were constructed: extreme and general poverty, and the model with multidimensional poverty aspects. The analysis of features of poor household categories showed that the most vulnerable residents of FB&H are not beneficiaries of permanent financial assistance. The reason for such an inefficient targeting was recognized in the Federal Law on Principles of Social Care, Care for the War-Disabled Civilians and Care for Families with Children that stipulates that only persons and families that (cumulatively): are incapable for work, have insufficient income, and there are no family members who are legally obligated to support them. The results indicated a high inconsistency in the legal criteria for qualification, and also in the amounts of permanent social assistance among cantons. The Proxy Means Test (PMT) Model is offered as one of the possible solutions for the improvement of social services targeting in FB&H. Given the importance of efficiency of targeting in social services, the research results could be useful, for both, vulnerable segments of the society and federal and cantonal ministries of labour and social affairs, in the process of targeting the households qualified for social support programmes.

Abstract The paper provides an overview of the trend in the concentration of the total assets of banks in Croatia for the period from 2007 to 2016 with the aim of analysing and presenting the changes that occurred in the system. Also, the paper shows the theoretical framework of the indicators used in the research as well as the comparison of their obtained values. The data used to calculate the total assets concentration are taken from the Croatian National Bank. The concentration indices used in the study include the entropy measure, the Theil entropy, the Gini coefficient, the Pietra index, the Atkinson index and the coefficient of variation. The results indicate a very slight decrease in concentration over the past several years, while the coefficient of variation points to the heterogeneity of the system, as well as to inequalities among the banks, which are most evident in the size of banks assets.

Abstract Unlike the standard unidimensional poverty indices, based mostly on monetary poverty measures, multidimensional poverty indices may include numerous non-monetary poverty indicators. This study utilized fuzzy and Alkire – Foster (AF) and fuzzy methodology to assess the poverty level in Bosnia and Herzegovina (B&H) and to compare the results with official poverty assessments. In addition to consumption as a monetary measure, we constructed AF and fuzzy indices by including numerous non-monetary measures that indicate housing quality, possession of durable goods and the household structure. AF multidimensional indices for B&H are calculated based on data from Household Budget Surveys (2004, 2007 and 2011) and fuzzy poverty indices are calculated based on data from HBS 2011. This research has found the differences in the values, direction and dynamics between unidimensional and multidimensional approaches to poverty measurement. Authors state that it is not sufficient to base the creation of more efficient social policies and poverty reduction strategies exclusively on unidimensional indices that address just one dimension of poverty.

Abstract This paper presents linear and goal programming optimization models for determining and analyzing the food basket in Bosnia and Herzegovina (BiH) in terms of adequate nutritional needs according to World Health Organization (WHO) standards and World Bank (WB) recommendations. A linear programming (LP) model and goal linear programming model (GLP) are adequate since price and nutrient contents are linearly related to food weight. The LP model provides information about the minimal value and the structure of the food basket for an average person in BiH based on nutrient needs. GLP models are designed to give us information on minimal deviations from nutrient needs if the budget is fixed. Based on these results, poverty analysis can be performed. The data used for the models consisted of 158 food items from the general consumption of the population of BiH according to COICOP classifications, with average prices in 2015 for these products.