The aim of this paper is to identify the basic characteristics of organic production in the agricultural sector of Bosnia and Herzegovina in terms of determining the scope, trends and flows in the selected time period. In terms of competitiveness, special emphasis is placed on the position of Bosnia and Herzegovina in the region. That is, a comparative review with the countries of the region according to the available indicators of organic production within the data of the Research Institute for Organic Production (FiBL). The analysis is focused on the changes of relevant indicators for Bosnia and Herzegovina and the countries of the region in the period from 2010 to 2020. The analysis was made using methods of dynamic analysis (index numbers, average annual rate of change, trend) and comparison methods. The results of the research can be a starting point for policy makers in support of the development of the agricultural sector.

Abstract The paper explores the possibilities of creating an econometric model for making short-term forecasts of the Gross Domestic Product of Bosnia and Herzegovina (GDP of B&H). Its aim is to determine the most representative and most efficient model for forecasting the quarterly GDP of B&H. This is the first paper that simultaneously compares ARIMA models, bridge models and factor models in three different time periods. All variables are available for the period of 2006q1-2016q4. The final choice of the model for forecasting the quarterly GDP of B&H was selected on the basis of a comparative analysis of the predictive efficiency of the analysed models. Based on the obtained results, the most efficient model for forecasting quarterly GDP of B&H is the bridge model, which includes four variables as regressor: Retail sale of other goods, Total loans, Manufacturing and Manufacture of food products.

The aim of this paper is to identify the basic characteristics of foreign trade of Bosnia and Herzegovina in terms of determining the volume, trends, geographic orientation, production structure and level of concentration of export-import flows in the selected time period, with emphasis on its trade with major partners, such as the EU and CEFTA. A special emphasis has been placed on exports as a driver of growth and development of the domestic economy. In order for the economy of Bosnia and Herzegovina to grow, creating jobs and increasing economic welfare of its citizens, it must focus on international trade, particularly the increase in the volume and value of exports. To say that the export is a requirement for survival may sound dramatic, but there can be no doubt that our country needs to improve its trading result. This reflects the importance of foreign trade. The focus of the analysis is placed on the dynamics and structure of the total exchange of B&H in the period from 2004 to 2018. Analysis was done using the appropriate method of dynamic analysis (index methods, average annual growth rate). The main results indicate not so positive trends for international trade of Bosnia and Herzegovina.

Abstract In the most developed countries the first estimations of Gross Domestic Product (GDP) are available 30 days after the end of the reference quarter. In this paper, possibilities of creating an econometric model for making short-term forecasts of GDP in B&H have been explored. The database consists of more than 100 daily, monthly and quarterly time series for the period 2006q1-2016q4. The aim of this study was to estimate and validate different factor models. Due to the length limit of the series, the factor analysis included 12 time series which had a correlation coefficient with a quarterly GDP at the absolute value greater than 0.8. The principal component analysis (PCA) and the orthogonal varimax rotation of the initial solution were applied. Three principal components are extracted from the set of the series, thus together accounting for 73.34% of the total variability of the given set of series. The final choice of the model for forecasting quarterly B&H GDP was selected based on a comparative analysis of the predictive efficiency of the analysed models for the in-sample period and for the out-of-sample period. The unbiasedness and efficiency of individual forecasts were tested using the Mincer-Zarnowitz regression, while a comparison of the accuracy of forecast of two models was tested by the Diebold-Mariano test. We have examined the justification of a combination of two forecasts using the Granger-Ramanathan regression. A factor model involving three factors has shown to be the most efficient factor model for forecasting quarterly B&H GDP.

Abstract This special issue of Business Systems Research is highlights recent advances and trends in post-transition countries, taking into account statistical modelling approach. Nine papers that have been selected for this special issue present improvements and new techniques (methodology) in statistical modelling and their use in various aspects of development in post-transition countries

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.

In this article, we propose a new methodology for solving the vendor selection and the supply quotas determination problem. The proposed methodology combines the Analytic Hierarchy Process (AHP) for determining the coefficients of the objective functions and a new multiple objective programming method based on the cooperative game theory for vendor selection and supply quotas determination. The proposed methodology is tested on the problem of flour purchase by a company that manufactures bakery products. For vendor selection and supply quotas determination we use three complex criteria: (1) purchasing costs, (2) product quality, and (3) vendor reliability.

Unlike standard unidimensional poverty indices, based mostly on monetary poverty measure such as income or consumption, multidimensional poverty indices can include numerous nonmonetary poverty indicators. In addition to multidimensional poverty indices obtained by generalization of standard unidimensional poverty indices (Foster – Greer – Thorbecke’s indices), many authors (Ambrosio, Deutsch and Silber (2011) ; Betti, Chelli and Lemmi (2005) ; Alkire and Santos (2013)) emphasize the importance and advantages of Alkire – Foster (AF) and fuzzy multidimensional indices. This study utilized fuzzy and AF methodology to investigate poverty level in Bosnia and Herzegovina. In addition to consumption as monetary measure, we constructed AF and fuzzy indices by including the numerous nonmonetary measures that indicates dwelling quality, possession (of durable goods) and household structure (size, education and vulnerability). The usage of fuzzy sets in poverty analysis is inspired by fuzzy sets theory and motivated by artifi cial classifi cation in poor and non-poor population units. Instead of this classifi cation, fuzzy indices are based on poverty membership function that refl ects level of poverty. These indices allow the usage of all types of poverty indicators: binary, categorical and continuous. Two main approaches in determining fuzzy poverty indices are used: Totally Fuzzy (TF) and Totally Fuzzy and Relative approach (TFR). Some authors (Chelli and Lemmi (1995)) emphasize that TFR approach is less arbitrary due to defi ning poverty membership functions without predefi ned limits in the cases of categorical and continuous variables, which are required in TF approach. AF method for construction of multidimensional poverty indices uses overlapping or multiple deprivations by included poverty measures. The unit will be considered as poor if the weighted sum of its deprivations is higher than predefi ned poverty threshold. After identifi cation of poor units, information on the proportion of deprivations have to be aggregated for all units. The most commonly used and also the simplest index within the class of Alkire – Foster indices is the adjusted headcount index M0, which is the product of multidimensional headcount index and the average proportion of deprivation for the poor units (intensity of poverty). Adjusted headcount index indicates incidence and intensity of poverty. Next index, M1 indicates incidence, intensity and depth of poverty, while M2 indicates incidence, intensity and depth of poverty and also inequality in distribution of selected poverty measures within population of poor units. AF poverty indices are important because they allow decomposition by subgroups and comparisons of poverty over time. Considering these characteristics of AF poverty indices, United Nations adopted this methodology for determination global Multidimensional Poverty Index, in 2010. Fuzzy and AF multidimensional indices for Bosnia and Herzegovina are calculated based on data from Household Budget Surveys (2004, 2007 and 2011). Their advantage comparing to unidimensional poverty indices is inclusion of relevant nonmonetary poverty indicators, such as education, possession of durable goods, dwelling characteristics, household participation in the labor force etc. For certain cases, their values signifi cantly deviate from the values of corresponding unidimensional indices. Unidimensional indices indicate deterioration of poverty in 2007 comparing to 2004 and 2011 while AF adjusted headcount index indicates the permanent improvement of poverty level in B&H and its parts. Also, determined fuzzy index indicates that Brcko District suff ers from highest poverty level comparing to Federation of Bosna and Herzegovina and Republika Srpska in 2011, while unidimensional indices have the opposite direction. Authors state that, creation of more effi cient social policies and poverty reduction strategies is not suffi cient to base exclusively on unidimensional indices that address just one dimension of poverty.

There are over 50 financial ratios available for industry ratio analysis and some are more important than the others for different industries. Very often we have a situation that a performance seem to be excellent according to one ratio, but poor to another ratio. Therefore, we need to identify the smaller set of ratios to be used for industry financial analysis. The objective of this paper is to examine the use of multivariate statistical methods in financial ratios analysis in order to reduce the number of ratios and to select optimal ones as a base for construction of a synthetic general index. Empirical research covers BiH companies from the construction industry for the period from 2003 to 2012. The study shows that multivariate methods may be a useful tool for analysing the relation between financial ratios, as for reduction of the number of ratios required for assessing industry financial performance.

Abstract This research is designed to examine the relationship between the capital structure and profitability of non-financial firms in Bosnia and Herzegovina during the ten years period, from 2003-2012. The goal is to prove the existence of the relationship between the firm’s capital structure choice and its profitability. The analysis is extended by including the debt structure and differentiating between the types of debt such as the long-term and the short-term ones. Canonical correlation and multiple regression analysis are used. The results of the multivariate canonical correlation analysis provide support to a hypothesis that the capital structure and profitability have statistically significant relationships. Furthermore, the findings provide support that firms develop different patterns of profitability depending on the capital structure choice. We found that an increasing proportion of short-term debt and long-term debt in the overall liability of the firm reduces its profitability.

This research is designed to examine the relationship between the capital structure and profitability of non-financial firms in Bosnia and Herzegovina during the period of ten years, from 2003-2012. The goal is to prove the existence of the relationship between the firm's capital structure choice and its profitability. The analysis is extended by including the debt structure and differentiating between the types of debt such as the long-term and the short-term ones. The results of the multivariate canonical correlation analysis provide support to a hypothesis that the capital structure and profitability have statistically significant relationships. Furthermore, the findings provide support that firms develop different patterns of profitability depending on the capital structure choice. We found that an increasing proportion of short-term debt and long-term debt in the overall liability of the firm reduces its profitability.

The article investigates the relationship between unemployment rate and development indicators: (1) the GDP per capita in Purchasing Power Parities (PPP in current international $); and (2) the Internet penetration rate, defined as the percentage of Internet users per 100 people. For 34 countries in 2013, only two simple linear regression models based on natural logarithms of data and the Ordinary Least Squares (OLS) estimator appeared to be useful. The simple linear regression "Model 1" shows a negative correlation between the main variable under study ln(Y_UemRate) and the regressor ln(X_GDPpc), explaining nearly half of the total variation. The simple linear regression "Model 2" shows a negative correlation between ln(Y_UemRate) and ln(X_IntUse), explaining 27 % of the total sum of squares. Regarding clustering of 34 countries based on three variables, the Ward linkage and squared Euclidean distances gave an interesting four-cluster solution. The South-East European (SEE), and especially to the Western Balkan's countries (WBC) are focused. These countries, spread in three clusters, are not homogeneous. Bosnia and Herzegovina and R. Macedonia are with Spain and Greece, all having difficult economic situation. Albania, Montenegro and Serbia are with Bulgaria, Romania and Turkey, all being the SEEC. Croatia is with more developed Italy, Cyprus and Poland, and with less developed Portugal. Central European Slovenia, joined more developed countries of that area, but the most developed European countries comprised a cluster of their own.