FACTORS AFFECTING MICRO AND SMALL ENTERPRISES’ ACCESS TO MICROFINANCE IN CROATIA

Micro, small and medium enterprises (MSMEs) are recognized worldwide as crucial element of boosting economic growth, reducing unemployment and poverty. In order to achieve growth, develop new products, create new jobs, they need to get finance. However, they are facing financing constraints, and persistent limitations to access to finance remain to be a major obstacle for them. Thus, financial inclusion is important for economic welfare and sustainable economic development. This study aims to identify the determinants of access to micro loans for micro and small enterprises (MSEs) by considering entrepreneur characteristics, firm characteristics, and perceived business obstacles. Data set of 173 MSEs from Croatia – the region Dalmatia, is available for the purpose of investigating and comparing characteristics of those that are financed and those that are not financed by micro loans. Besides, the paper also presents the logistic regression model which identifies set of characteristics which have significant relation with the MSE tendency to be financed by micro loans

VRIJEDNOST DIONIČKIH DRUŠTAVA I STRUKTURA KAPITALA: ISTRAŽIVANJE HRVATSKIH, SLOVENSKIH I ČEŠKIH DIONIČKIH DRUŠTAVA

This paper aims to explore the capital structure issue and corporate value and to investigate the effect of capital structure change on corporate value. Panel data regression was applied in the research. The empirical results show that all proxies of capital structure have a positive but not significant influence on the Sustainable Owners Value Added Ratio (SOVAR) as a performance proxy for joint-stock companies whose financial instruments are listed on the capital market in Croatia. The study indicates that the owners’ equity has a negative and significant influence on the value of joint-stock companies in Slovenia while the long-term debt has a positive and significant impact on the value of listed joint-stock companies in the Czech Republic. Future work is needed to extend the analysis across different countries in the European Union and a long time series of data. Although investments are the most significant determinants of corporate value, the results indicate that 29.53% variability of the corporate value is explained by the variables owners’ equity and long-term debt which represent capital structure. These results provide evidence that the capital structure decisions affect corporate value as well as capital structure is relevant for corporate value in the selected members of European Union.Cilj ovog istraživanja je istražiti međuzavisnost strukture kapitala i vrijednosti dioničkih društava te istražiti utjecaj promjena strukture kapitala na vrijednost dioničkih društava. Panel regresijska analiza je korištena za analizu podataka. Empirijski rezultati su pokazali da sve varijable strukture kapitala imaju pozitivan utjecaj, koji nije statistički značajan, na pokazatelj Sustainable Owners Value Added Ratio (SOVAR) kao mjeru performanse vrijednosti za dionička društva čiji su financijski instrumenti uvršteni na tržište kapitala u Republici Hrvatskoj. Nadalje, rezultati istraživanja pokazuju da glavnica ima negativan i statistički značajan utjecaj na vrijednost dioničkih društava u Sloveniji dok dugoročni dug ima pozitivan i statistički značajan utjecaj na vrijednost dioničkih društava u Češkoj Republici. Buduće istraživanje treba proširiti analizu na različite zemlje Europske unije i veće vremenske serije podataka. Iako su investicije najznačajnija determinanta vrijednosti poduzeća, rezultati istraživanja pokazuju da je 29.53% varijabilnosti vrijednosti dioničkih društava objašnjeno pomoću varijabli glavnica i dugoročni dug koje predstavljaju strukturu kapitala. Ovi rezultati dovode do zaključka da odluke o strukturi kapitala imaju utjecaja na vrijednost dioničkih društava u stvarnom svijetu te da je struktura kapitala relevantna za performansu vrijednosti dioničkih društava u odabranim članicama Europske unije

FINANCIAL DETERMINANTS OF SMEs GROWTH IN THE TIME OF ECONOMIC

The importance of high-growth enterprises in national economies has been widely substantiated by economic research in recent years. There are a small number of papers that investigate determinants of growth in the time of economic downturn. This paper is focused on finding financial ratios that are determinants of growth in small and medium-sized enterprises (SMEs) which operate in downturn economies. The assumption of this study is that the time of economic downturn sets new challenges to SMEs and that fact should be reflected in their financial statements as well as in the growth prediction model. Our hypotheses have been tested on the sample of 1492 SMEs from Croatia over the period 2008-2013 in the time of economic downturn. Using logistic regression, a growth prediction model has been developed and tested. Results have shown that in the time of economic downturn, growth potential of SMEs increases with the increase of liquidity, turnover and profitability and with the decrease of leverage

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods

SELECTING NEURAL NETWORK ARCHITECTURE FOR INVESTMENT PROFITABILITY PREDICTIONS

After production and operations, finance and investments are one of the most frequent areas of neural network applications in business. The lack of standardized paradigms that can determine the efficiency of certain NN architectures in a particular problem domain is still present. The selection of NN architecture needs to take into consideration the type of the problem, the nature of the data in the model, as well as some strategies based on result comparison. The paper describes previous research in that area and suggests a forward strategy for selecting best NN algorithm and structure. Since the strategy includes both parameter-based and variable-based testings, it can be used for selecting NN architectures as well as for extracting models. The backpropagation, radialbasis, modular, LVQ and probabilistic neural network algorithms were used on two independent sets: stock market and credit scoring data. The results show that neural networks give better accuracy comparing to multiple regression and logistic regression models. Since it is model-independant, the strategy can be used by researchers and professionals in other areas of application

COMPARING FINANCIAL DISTRESS PREDICTION MODELS BEFORE AND DURING RECESSION

The purpose of this paper is to design three separate financial distress prediction models that will track the changes in a relative importance of financial ratios throughout three consecutive years. The models were based on the financial data from 2000 privately-owned small and medium-sized enterprises in Croatia from 2006 to 2009, and developed by means of logistic regression. Macroeconomic conditions as well as market dynamic have been changed over the mentioned period. Financial ratios that were less important in one period become more important in the next period. Composition of model starting in 2006 has been changed in the next years. It tells us what financial ratios are more important during the time of economic downturn. Besides, it helps us to understand behavior of small and medium-sized enterprises in the period of prerecession and in the period of recession

ANALYSIS OF IMPACT OF ENTREPRENEURS’ CHARACTERISTICS TO THE NUMBER OF EMPLOYEES IN CROATIAN COMPANIES

Rad autorica jedan je model istraživanja utjecaja na broj uposlenih u hrvatskim poduzećima. Uzorak na kojem je provedeno istraživanje činilo je 200 poduzeća u Hrvatskoj. Analizirani su utjecaji konkurencije, proizvodne tehnologije i usluga na tržištu, iskustva i obrazovanje poduzetnika i novog i kupljenog poduzeća na implementaciju strategije poduzeća i utjecaji kvantitativnih i kvalitativnih metoda implementacije strategije poduzeća, hijerarhijske strukture, prihoda poduzeća i iskustva, obrazovanja i spola poduzetnika na broj uposlenih u hrvatskim poduzećima.The paper represents a research model of impact to the number of employees in companies owned by Croatian entrepreneurs.The research was carried out on a sample of 200 companies in Croatia. Analyzed were impacts of competitiveness, productive technology and services at market, experiences and education of entrepreneurs, of new and bought company to implementation of strategy of companies, and impacts of quantitative methods of strategy implementation of companies, hierarchy structure, company revenue, experience, education and sex of entrepreneurs to the number of employees in companies of Croatian entrepreneurs. The model of structural equations is used for analysis of mentioned impacts

The impact of liquidity on the capital structure: a case study of Croatian firms

Background: Previous studies have shown that in some countries, liquid assets increased leverage while in other countries liquid firms were more frequently financed by their own capital and therefore were less leveraged. Objectives: The aim of this paper is to investigate the impact of liquidity on the capital structure of Croatian firms. Methods/Approach: Pearson correlation coefficient is applied to the test on the relationship between liquidity ratios and debt ratios, the share of retained earnings to capital and liquidity ratios and the relationship between the structure of current assets and leverage. Results: A survey has been conducted on a sample of 1058 Croatian firms. There are statistically significant correlations between liquidity ratios and leverage ratios. Also, there are statistically significant correlations between leverage ratios and the structure of current assets. The relationship between liquidity ratios and the short-term leverage is stronger than between liquidity ratios and the long-term leverage. Conclusions: The more liquid assets firms have, the less they are leveraged. Longterm leveraged firms are more liquid. Increasing inventory levels leads to an increase in leverage. Furthermore, increasing the cash in current assets leads to a reduction in the short-term and the longterm leverage

COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS

Despite increased interest in the entrepreneurial intentions and career choices of young adults, reliable prediction models are yet to be developed. Two nonparametric methods were used in this paper to model entrepreneurial intentions: principal component analysis (PCA) and artificial neural networks (ANNs). PCA was used to perform feature extraction in the first stage of modelling, while artificial neural networks were used to classify students according to their entrepreneurial intentions in the second stage. Four modelling strategies were tested in order to find the most efficient model. Dataset was collected in an international survey on entrepreneurship self-efficacy and identity. Variables describe students’ demographics, education, attitudes, social and cultural norms, self-efficacy and other characteristics. The research reveals benefits from the combination of the PCA and ANNs in modeling entrepreneurial intentions, and provides some ideas for further research

UTJECAJ STRUKTURE KAPITALA I TEORIJE HIJERARHIJE FINANCIJSKIH IZBORA NA LIKVIDNOST DIONIČKIH DRUŠTAVA

Dionička društva susreću se sa sličnim problemima kako financirati investicijske projekte koji su potrebni za njihovu ekspanziju i rast. Cilj je empirijskog istraživanja proučiti utjecaj strukture kapitala na likvidnost dioničkih društava, čiji su financijski instrumenti uvršteni na tržište kapitala, i primjenu teorije hijerarhije financijskih izbora. Empirijsko istraživanje provodi se na uzorku hrvatskih, slovenskih i čeških dioničkih društava, a u istraživanju koriste se panel višestruka linearna regresija i analiza korelacije. Rezultati istraživanja pokazali su da udio zadržane dobiti u ukupnom kapitalu i obvezama ima pozitivan i statistički značajan utjecaj na likvidnost dioničkih društava u Republici Sloveniji i Češkoj Republici. Također, utvrđeno je da dionička društva u Republici Hrvatskoj i Republici Sloveniji primjenjuju teoriju hijerarhije financijskih izbora jer preferiraju interno financiranje, odnosno financiranje iz zadržane dobiti u odnosu na eksterno financiranje. Odabirom komponenti strukture kapitala, povećanjem udjela zadržane dobiti u ukupnom kapitalu i obvezama te primjenom teorije hijerarhije financijskih izbora dionička društva mogu utjecati na održavanje i unapređenje njihove likvidnosti