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Abstract

Purpose: Summarize the experience of using modern methods in the business plan with the application of economic and mathematical modeling.

Methodology: Theoretical and methodological basis of the study is the basic principles of economic theory, agricultural economics and scientific research of leading home and foreign scholars on the theory of planning.

Originality: This further justifies business planning processes in agriculture from the standpoint of raising economic protection of farmers. The methodology for assessing farm income for planned indicators through the application of fuzzy numbers method in business planning is improved.

Abstract

The gross capital formation (GCF), which helps to gradually increase GDP itself, is financed by domestic savings (DS) in both developed and developing countries. Therefore, forecasting GCF is the key subject to the economists’ decisions making. In this study, I use simple forecasting methods, namely dynamic relation model called “Autoregressive Distributed Lag Model (ARDL)”, and complex methods such as Adaptive Neuro Fuzzy Inference System (ANFIS) method and ARIMA-ANFIS method to determine which method provides better out-of-sample forecasting performance. In addition, the contribution of this study is to show how important to use domestic savings in forecasting GCF. On the other hand, ANFIS and hybrid ARIMA-ANFIS methods are comparatively new, and no GCF modeling using ANFIS and ARIMA-ANFIS was attempted until recently to the best of my knowledge. In addition, Autoregressive Integrated Moving Average (ARIMA) method and Vector Autoregressive (VAR) model serve as benchmarks, allowing for fair competing for the study.

Abstract

Background: Alongside the theoretical progress made in understanding the factors that influence firm growth, many methodological challenges are yet to be overcome. Authors point to the notion of interpretability of growth prediction models as an important prerequisite for further advancement of the field as well as enhancement of models’ practical values.

Objectives: The objective of this study is to demonstrate the application of factor analysis for the purpose of increasing overall interpretability of the logistic regression model. The comprehensive nature of the growth phenomenon implies propensity of input data to be mutually correlated. In such situations, growth prediction models can demonstrate adequate predictability and accuracy, but still lack the clarity and theoretical soundness in their structure.

Methods/Approach: The paper juxtaposes two prediction models: the first one is built using solely the logistic regression procedure, while the second one includes factor analysis prior to development of a logistic regression model.

Results: Factor analysis enables researchers to mitigate inconsistencies and misalignments with a theoretical background in growth prediction models.

Conclusions: Incorporating factor analysis as a step preceding the building of a regression model allows researchers to lessen model interpretability issues and create a model that is easier to understand, explain and apply in real-life business situations.

Abstract

Objective: The purpose of this article is to present a brief analysis of the Romanian higher education system from the perspective of basic indicators, as well as the use of Markovian techniques for studying the evolution of the schooling process.

Methodology: The descriptive statistical analysis was mainly used to visualize and synthesize the information extracted from the data on the Romanian higher education system. Markovian methods were used to study and predict the evolution of the schooling process.

Findings: The rapid dynamics of the number of students in Romania in the last two decades has been accompanied by a series of structural changes, of which the most important are: a) constantly increasing the degree of feminisation of student achievements and b) increasing the relative importance of economic studies, legal studies and other social sciences, while reducing the relative importance of technical sciences and of medical-pharmaceutical studies within university specialties. Also, the distribution of the graduates’ specializations correlated to a very small extent with the requirements of economic and social activity. It can be said that the development of tertiary education in Romania was stimulated mainly by the action of factors of social and cultural nature and only at second level by the demand for qualified personnel generated by the productive apparatus.

Value Added: This study highlights the current state of Romanian higher education. The fact that the evolution of tertiary education has been “explosive” over the past two decades makes some econometric methods, involving the use of stationary data or which have a high degree of complexity, more difficult to use. In this context, the use of Markovian modelling methods for studying and forecasting the evolution of the schooling process can contribute to improving access to and participation in higher education.

Recommendations: In the current conjucture, when trying to increase the insertion of graduates into the labour market, it is natural for decision-makers to use various estimation methods and techniques that allow them to correlate university study programs with the needs of the labour market and at the same time provide them with scientific support for their prognosis.

Abstract

Objective: The main purpose of this research is to analyze and reveal if the recent policy measures in higher education carried in European Union member countries have had a significant impact on the labour market integration of university graduates.

Methodology: We selected a set of indicators that were common in the 2015 and 2016 editions of Structural Indicators for Monitoring Education and Training Systems in Europe and could offer an image of intensity of higher education policies in relation with labour market at European level. We further used these measures to test for any significant effects of the policies on the integration of graduates in the labour market.

Findings: We found significant effects of various policy measures in high education in the European countries. We estimate a positive role for factors like monitoring of completion rates, requirements for the staff to have higher education, presence of educational guidelines, and recognition of formal and informal learning for entry in higher education.

Value Added: This is the first study to address the impact of high education policies carried in European countries on the integration of college graduates. The study is distinct through both the design of new measures of higher education policy in Europe as well through testing whether the intensity of policies carried for higher education has affected the employability of young graduates or not.

Recommendations: The results of this empirical research allow us to make some recommendations for improving the insertion of young graduates on European labour market.

Abstract

Considering the potential factors that might generate economic growth, a target for any economy, this paper identified some determinants of economic growth in the countries from Central and Eastern Europe (CEE countries) that are member states of the European Union. The foreign direct investment was the most important determinant of economic growth in most of the countries (Bulgaria, Slovenia, Estonia, Hungary, Romania, Poland, Latvia, Lithuania) in the period 2003-2016, according to Bayesian bridge regressions. The indicators related to the level and the quality of labour resources proved to be insignificant in explaining the economic growth in these countries. Moreover, in Croatia, Estonia, Latvia, Lithuania, and Poland, the government expenditure on education had a negative effect on economic growth.

Abstract

The insertion of graduates of higher education on the labor market is one of the problems faced by the Romanian labor market. Based on a VAR model in the panel, the number of unemployed with higher education in Romania is explained in correlation with variables related to the educational environment. As the number of graduates, the number of teaching staff and the number of faculties increase the unemployment rate among people with higher education also increases slightly, showing that they have not immediately integrated into the labor market. A shock (an innovation) in the series of unemployed numbers results in an increase in the number of unemployed and a long-term stabilization of the influence to positive values. A shock to the data series on the number of graduates, the number of faculties and teaching staff does not have an immediate effect on the number of unemployed with higher education.

Abstract

Croatian Industrial Confidence Indicator (ICI) is one of the measures of mangers’ sentiment about the economic situation in the Croatian manufacturing industry. Since 2005, the ICI has been calculated in accordance with the harmonised European Commission methodology as a simple average of three variables: order books, stocks of finished products and production expectation. It was empirically confirmed that the ICI could predict the direction of change in industrial production more than one month ahead. With the aim of raising the ICI forecasting power, this paper proposes a novel ICI with a different weighting scheme. The empirical analysis is based on monthly data for three standard ICI subcomponents and industrial production expressed as year-on-year growth rates. The data set covers the period from May 2008 to February 2019. Data sources were the European Commission and Eurostat. The newly defined ICI was constructed by using the nonlinear optimisation approach. The weights were determined by minimizing the root mean square error (RMSE) in a simple regression model and by maximizing the correlation coefficient between the ICI and industrial production for various time lags. The results reveal that the newly defined ICI performs better in adapting and following the industrial production growth rate as well as that the dominant component in the ICI is the production expectation.

Abstract

The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that according to data provided by EUROSTAT, the number of people looking for a job in Romania it is correlated with specific query terms using Google Trends. Search engine data is used to “predict the present” values of different economic indicators. The obtained results are compared with the classical method of developing the economic indicators, with official EUROSTAT employment data. In this paper, we demonstrate that the new methods to extract the economic indicators from web technologies are accurate.

Abstract

The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that according to data provided by EUROSTAT, the number of people looking for a job in Romania it is correlated with specific query terms using Google Trends. Search engine data is used to “predict the present” values of different economic indicators. The obtained results are compared with the classical method of developing the economic indicators, with official EUROSTAT employment data. In this paper, we demonstrate that the new methods to extract the economic indicators from web technologies are accurate.