Stefan C Ciucu | The Bucharest Academy of Economic Studies (original) (raw)

Papers by Stefan C Ciucu

The first aim of this study is to identify possible natural disasters and catastrophes and to sum... more The first aim of this study is to identify possible natural disasters and catastrophes and to summarize the state of economic literature in the domain. Further are analyzed the methodologies used for estimating the economic impacts of disasters and catastrophes.
The second aim is to compare disasters and catastrophes from several transition countries (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania and Ukraine) in the 1900-2014 time period, underlining their negative impact on the economy.

In this paper we develop and analyze vector error correction models for Romania and Hungary in or... more In this paper we develop and analyze vector error correction models for Romania and Hungary in order to determine the relationships between GDP, government expenditure on education, number of enrolled persons in primary, secondary and tertiary education per 100.000 inhabitants. Using the software tool EViews several tests and methods described in the methodology are applied on the data. We underline the role of education (considered as human capital in economic development) in supporting economic growth and we point out the short and long run relationships between the variables.

The Republic of Moldova is listed by the International Monetary Fund (IMF) and by the World Bank ... more The Republic of Moldova is listed by the International Monetary Fund (IMF) and by the World Bank as a country with a transitional economy and studies of the evolution of the economy are of interest. Data has been gathered for a quantitative analysis of the economy using a multiple regression model (with the aid of computer software tools: Microsoft Excel with the Analysis ToolPak add-in and MathWorks - MATLAB), in order to determine if there is a significant importance of some major macroeconomic indicators to the GDP.
The indicators used in the study are GDP, exports of goods and services (% of GDP), inflation - GDP deflator (annual %), central government debt (% of GDP) and unemployment (% of total labor force).

The main objective of this paper is to present and analyze the evolution of the main contributors... more The main objective of this paper is to present and analyze the evolution of the main contributors to GDP in the transition countries: Republic of Macedonia, Republic of Moldova and to compare them with the main contributors to GDP in the developed country of Austria.
We will take a look at the Gross Domestic Product and its main contributors (agriculture, industry and services). Following the analysis of the statistical data, conclusions will be drawn regarding the situation of the economy in each country.
Computer software tool R is used in the study.

In transition countries affected by uncertainty, the educational system usually suffers from lack... more In transition countries affected by uncertainty, the educational system usually suffers from lack of funds from the government and it is affected by various reforms. It is important to see how education influences economic growth and how this growth can be improved by investing in education.
In this article, after a literature and econometric models review, the influence of primary, secondary and tertiary education over the GDP growth will be analyzed for Bulgaria, Czech Republic and the Netherlands, using regressions models, with the aid of computer software tool EViews. The models will be tested in order to obtain a good and reliable model.

This paper provides an overview over a way of integrating R with PHP scripting language in order ... more This paper provides an overview over a way of integrating R with PHP scripting language in order to analyze statistical data (time series).
We analyze the relationship between the foreign direct investments and GDP of the Republic of Moldova over 1992-2012 time period.

Under regimes like socialism, there was almost no unemployment, but transition countries have the... more Under regimes like socialism, there was almost no unemployment, but transition countries have the tendency of a high unemployment rate due to the lack of a consistent plan and uncertainly. Restructuring of the economy and reallocation of resources towards more efficient firms and sectors implies transitory unemployment.
This article presents the analysis of the relationship between unemployment and GDP, in two transitions countries, using a linear regression model estimated using MathWorks, Matlab Software R2011b.
Also, a forecast (using point prediction) is made of the GDP based on the number of people unemployed in Moldova.

Recent studies have shown the classification and prediction power of the Neural Networks. It has ... more Recent studies have shown the classification and prediction power of the Neural Networks. It has been demonstrated that a NN can approximate any continuous function. Neural networks have been successfully used for forecasting of financial data series. The classical methods used for time
series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and outputs. Neural Networks have the advantage that can approximate nonlinear functions. In this paper we compared the performances of different feed forward and recurrent neural networks and
training algorithms for predicting the exchange rate EUR/RON and USD/RON. We used data series with daily exchange rates starting from 2005 until 2013.

In this paper we make a new presentation of the Weibull distribution. We will make some add-ons f... more In this paper we make a new presentation of the Weibull distribution. We will make some add-ons for the Statistics Toolbox in MATLAB with our functions for the form with scale and displacement of the distribution. Finally we will use these new functions on applications of the Weibull distribution.

“Traditional” websites are a very good method of disseminating information for students in online... more “Traditional” websites are a very good method of disseminating information for students in online environment. We might thing that with this new trend, people prefer to get information on a social network website, but actually for complex information the “traditional” websites are better.
Facebook social network is very used in Romania, mostly by young people. It is a common saying around here: if you do not have a Facebook account, then you do not exist. The Facebook account of the University was created in may, 2012.
Since then it has been a powerful tool for disseminating information, but mostly for photos, short messages, links and videos.
YouTube and Twitter are not that used by students for finding information about their University, but during one year, I’ve recorded growth in number of followers.
In this paper I compare these four online methods of disseminating information for students (may 2012-may 2013 period of time).

A significant problem in higher education is the poor results of students after admission. Many s... more A significant problem in higher education is the poor results of students after admission. Many students leave universities from a variety of reasons: poor background knowledge in the field of study, very low grades and the incapacity of passing an examination, lack of financial resources. Predicting students' results is an important problem for the management of the universities who want to avoid the phenomenon of early school leaving. We used a neural network to predict the students' results measured by the grade point average in the first year of study. For this purpose we used a sample of 1000 students from "Nicolae Titulescu" University of Bucharest from the last three graduates' generations, 800 being used for training the network and 200 for testing the network. The neural network was a multilayer perceptron (MLP) with one input layer, two hidden layers and one output layer and it was trained using a version of the resilient backpropagation algorithm. The input data were the students profile at the time of enrolling at the university including information about the student age, the GPA at high school graduation, the gap between high school graduation and higher education enrolling. After training the network we obtained MSE of about 1.7%. The ability to predict students' results is of great help for the university management in order to take early action to avoid the phenomenon of leaving education.

The first aim of this study is to identify possible natural disasters and catastrophes and to sum... more The first aim of this study is to identify possible natural disasters and catastrophes and to summarize the state of economic literature in the domain. Further are analyzed the methodologies used for estimating the economic impacts of disasters and catastrophes.
The second aim is to compare disasters and catastrophes from several transition countries (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania and Ukraine) in the 1900-2014 time period, underlining their negative impact on the economy.

In this paper we develop and analyze vector error correction models for Romania and Hungary in or... more In this paper we develop and analyze vector error correction models for Romania and Hungary in order to determine the relationships between GDP, government expenditure on education, number of enrolled persons in primary, secondary and tertiary education per 100.000 inhabitants. Using the software tool EViews several tests and methods described in the methodology are applied on the data. We underline the role of education (considered as human capital in economic development) in supporting economic growth and we point out the short and long run relationships between the variables.

The Republic of Moldova is listed by the International Monetary Fund (IMF) and by the World Bank ... more The Republic of Moldova is listed by the International Monetary Fund (IMF) and by the World Bank as a country with a transitional economy and studies of the evolution of the economy are of interest. Data has been gathered for a quantitative analysis of the economy using a multiple regression model (with the aid of computer software tools: Microsoft Excel with the Analysis ToolPak add-in and MathWorks - MATLAB), in order to determine if there is a significant importance of some major macroeconomic indicators to the GDP.
The indicators used in the study are GDP, exports of goods and services (% of GDP), inflation - GDP deflator (annual %), central government debt (% of GDP) and unemployment (% of total labor force).

The main objective of this paper is to present and analyze the evolution of the main contributors... more The main objective of this paper is to present and analyze the evolution of the main contributors to GDP in the transition countries: Republic of Macedonia, Republic of Moldova and to compare them with the main contributors to GDP in the developed country of Austria.
We will take a look at the Gross Domestic Product and its main contributors (agriculture, industry and services). Following the analysis of the statistical data, conclusions will be drawn regarding the situation of the economy in each country.
Computer software tool R is used in the study.

In transition countries affected by uncertainty, the educational system usually suffers from lack... more In transition countries affected by uncertainty, the educational system usually suffers from lack of funds from the government and it is affected by various reforms. It is important to see how education influences economic growth and how this growth can be improved by investing in education.
In this article, after a literature and econometric models review, the influence of primary, secondary and tertiary education over the GDP growth will be analyzed for Bulgaria, Czech Republic and the Netherlands, using regressions models, with the aid of computer software tool EViews. The models will be tested in order to obtain a good and reliable model.

This paper provides an overview over a way of integrating R with PHP scripting language in order ... more This paper provides an overview over a way of integrating R with PHP scripting language in order to analyze statistical data (time series).
We analyze the relationship between the foreign direct investments and GDP of the Republic of Moldova over 1992-2012 time period.

Under regimes like socialism, there was almost no unemployment, but transition countries have the... more Under regimes like socialism, there was almost no unemployment, but transition countries have the tendency of a high unemployment rate due to the lack of a consistent plan and uncertainly. Restructuring of the economy and reallocation of resources towards more efficient firms and sectors implies transitory unemployment.
This article presents the analysis of the relationship between unemployment and GDP, in two transitions countries, using a linear regression model estimated using MathWorks, Matlab Software R2011b.
Also, a forecast (using point prediction) is made of the GDP based on the number of people unemployed in Moldova.

Recent studies have shown the classification and prediction power of the Neural Networks. It has ... more Recent studies have shown the classification and prediction power of the Neural Networks. It has been demonstrated that a NN can approximate any continuous function. Neural networks have been successfully used for forecasting of financial data series. The classical methods used for time
series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and outputs. Neural Networks have the advantage that can approximate nonlinear functions. In this paper we compared the performances of different feed forward and recurrent neural networks and
training algorithms for predicting the exchange rate EUR/RON and USD/RON. We used data series with daily exchange rates starting from 2005 until 2013.

In this paper we make a new presentation of the Weibull distribution. We will make some add-ons f... more In this paper we make a new presentation of the Weibull distribution. We will make some add-ons for the Statistics Toolbox in MATLAB with our functions for the form with scale and displacement of the distribution. Finally we will use these new functions on applications of the Weibull distribution.

“Traditional” websites are a very good method of disseminating information for students in online... more “Traditional” websites are a very good method of disseminating information for students in online environment. We might thing that with this new trend, people prefer to get information on a social network website, but actually for complex information the “traditional” websites are better.
Facebook social network is very used in Romania, mostly by young people. It is a common saying around here: if you do not have a Facebook account, then you do not exist. The Facebook account of the University was created in may, 2012.
Since then it has been a powerful tool for disseminating information, but mostly for photos, short messages, links and videos.
YouTube and Twitter are not that used by students for finding information about their University, but during one year, I’ve recorded growth in number of followers.
In this paper I compare these four online methods of disseminating information for students (may 2012-may 2013 period of time).

A significant problem in higher education is the poor results of students after admission. Many s... more A significant problem in higher education is the poor results of students after admission. Many students leave universities from a variety of reasons: poor background knowledge in the field of study, very low grades and the incapacity of passing an examination, lack of financial resources. Predicting students' results is an important problem for the management of the universities who want to avoid the phenomenon of early school leaving. We used a neural network to predict the students' results measured by the grade point average in the first year of study. For this purpose we used a sample of 1000 students from "Nicolae Titulescu" University of Bucharest from the last three graduates' generations, 800 being used for training the network and 200 for testing the network. The neural network was a multilayer perceptron (MLP) with one input layer, two hidden layers and one output layer and it was trained using a version of the resilient backpropagation algorithm. The input data were the students profile at the time of enrolling at the university including information about the student age, the GPA at high school graduation, the gap between high school graduation and higher education enrolling. After training the network we obtained MSE of about 1.7%. The ability to predict students' results is of great help for the university management in order to take early action to avoid the phenomenon of leaving education.