rss_2.0Sciendo RSS Feed for Journal of Social and Economic Statisticshttps://sciendo.com/journal/JSEShttps://www.sciendo.comhttps://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/61a9142632fa2f51bbc1caa7/cover-image.jpghttps://sciendo.com/journal/JSES140216https://sciendo.com/article/10.2478/jses-2022-0004<abstract> <title style='display:none'>Abstract</title> <p>The insurance industry has an important role in the economy, being constantly focused on diversifying product portfolios and dispersing risks. Since the uncertainty, the asymmetric information, the current economic and social-political challenges affect the economic performance and competitiveness on the insurance market, it is necessary to focus on the evaluation of the technical efficiency of the players. One of the most complex analytical research tools with increased utility that can be applied to measure the efficiency is the Data Envelopment Analysis (DEA). Our work is designed to analyze the performance of a sample made up of the ten main players in the insurance industry in Romania. Assuming a predefined set of five inputs (total expenses, provisions, average number of employees, total placements and intangible assets) and one output (total income) selected from the firms’ balance sheets, we calculate the efficiency scores with the help of DEA techniques for each year from 2016 to 2020. Our results show that Allianz and City are the most efficient firms regardless of the model type VRS or CRS, while Groupama and Omniasig fail to operate at an optimal level in any of the analyzed periods.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00042023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0001<abstract> <title style='display:none'>Abstract</title> <p>Confronted with ageing and depopulation, Romania needs to identify the main factors that attract immigrant population. This paper tackles the matter of regional income disparities as a key factor for temporary immigration in Romania. The quantitative approach includes a spatial panel data analysis based on a dataset retrieved from the Romanian National Institute of Statistics and our data consists of 378 observations on 42 counties in Romania over a time span of nine years starting with the year 2012. Our findings suggest that temporary immigration in Romania is shaped by location, but does not follow the labour market characteristics. Higher salaries and job opportunities are not the main factors of attraction to temporary immigration and it does not seem to be influenced by regional disparities.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00012023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0002<abstract> <title style='display:none'>Abstract</title> <p>Romanian Agency for Quality Assurance in Higher Education evaluates, on demand or on its own initiative, the higher education providers and study programmes. This paper presents the results of a large-scale survey on the perception of the Romanian students in the field of Economic Sciences on the quality of the educational programs they follow. The themes covered are: the teaching resources, the educational process, the evaluation and communication, the teaching and learning, the infrastructure, the learning outcomes and the relevance for the labor market. Using a large sample of 8120 respondents, the results show that in general the perceptions are quite positive with scores between 8 and 9, on a range from 1 to 10. We identified differences between students by their seniority, by specific universities and their admission grades.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00022023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0003<abstract> <title style='display:none'>Abstract</title> <p>Sentiment analysis refers to the analysis of human opinions and sentiments that are expressed in written text, being also a part of the Natural Language Processing (NLP) tasks. Sentiment analysis can be applied in different domains, especially in the corporate marketing and sales, the healthcare system or the financial market analysis. In this paper we aim to highlight how data mining is able to extract the sentiment score from a financial platform that shows the major headlines regarding stocks, in order to highlight the publications’ positive or negative opinion over a stock. In order to gain the sentiment score we have scraped text data from the platform Finviz from which the polarity of the opinion may be extracted. We have also used Valence Aware Dictionary for Sentiment Reasoning (VADER), by running a Python script using the BeautifulSoup library. After that we have used Pandas (Python Data Analysis Library) to analyse and obtain a sentiment score on the article headlines. Results show that the script is able to generate the sentiment score for various selected stocks, while also showing graphical diagrams for the past and future trend of the stock, in terms of overall opinion on the stock performance.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00032023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0006<abstract> <title style='display:none'>Abstract</title> <p>This paper examines the reaction of the household indebtedness to various shocks in the economy between 2011Q1 and 2021Q4, using a Structural Vector Autoregressive model. The results of the econometric model indicate that average net wage was the driver of the loans granted by credit institutions to individuals’ variation after their own innovations at all time horizons. This result was achieved in the conditions that households’ resilience to shocks has improved significantly in the period 2011-2020 from lei 243 billion to lei 480 billion. The evolution of the economy starting from March 2020 was influenced by the emergence of the COVID-19 pandemic and the imposition of restrictions to prevent the spread of the disease. In this situation, between March 2020 and September 2021, the new standard mortgage loans recorded an average growth rate of 2.2 percent in nominal terms and 1.91 percent in real terms, standing above the pre-pandemic level (1.34 percent, respectively 1.17 percent). The low interest rates and general household income growth (the minimum wage in the economy increased 14 times between 2011 and 2021) were responsible for high household debt. The rise in household indebtedness growths its vulnerability to shocks in the economy, potentially having a negative impact mainly on the creditors’ balance sheet.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00062023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0007<abstract> <title style='display:none'>Abstract</title> <p>The article provides the impact of different averages (feature importance) within the admission exam for the national military high schools using and testing three supervised machine learning algorithms: logistic regression, K-Nearest Neighbors, and random forest. For this purpose, I have used the list with the results of candidates compounded by 430 rows, an unclassified document posted on the national military high school website, with details about: the final admission grade, the general grade for graduating of the secondary school, the general grade obtained at the national assessment, the mark obtained at admission test from Romanian language and mathematics items, etc. From the machine learning perspective, I have built a Jupyter notebook, a Python code using the specialized ML libraries (numpy, pandas, matplotlib, sklearn). In conclusion, the logistic regression algorithm identified the ‘feature importance’ (how each variable contributes to the predicted model) for admission in the national military high school: the mark obtained at admission test from Romanian language and Mathematics items - 4.821834, the general average obtained at the national assessment - 0.584434, the general average for graduating of the secondary school - 0.285446, etc. These are the expected results based on the admission methodology for the national military high schools.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00072023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0008<abstract> <title style='display:none'>Abstract</title> <p>This study aims to investigate the potential existence of a cointegration relationship between Romania’s gross domestic product (GDP), credit interest rates charged by financial institutions, and the benchmark interest rate set by the National Bank of Romania (NBR). The identification of a long-term relationship between these variables is considered to be of significant importance as it may provide a deeper understanding of the interactions between interest rates and GDP dynamics in Romania. To achieve this objective, we employed a robust econometric methodology, utilizing well-established and widely-used techniques for capturing long-term statistical relationships. Careful consideration was given to the manipulation of macroeconomic data in order to ensure the validity and reliability of the analysis. The results of our analysis reveal that there is no statistically significant evidence of a long-term relationship between GDP, credit interest rates, and the benchmark rate set by the NBR. This finding suggests that the interaction between interest rates and GDP in Romania is complex and may be influenced by other variables. Further research should focus on these other factors in order to gain a more comprehensive understanding of the relationship between GDP, credit interest rates and benchmark rate set by NBR.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00082023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2022-0005<abstract> <title style='display:none'>Abstract</title> <p>The circular economy has increasingly attracted the attention of regulators as a result of the emergence of the challenges associated with climate change and the need to increase the lifetime of goods in order to reduce waste and high consumption of resources. Therefore, the paper aims to identify the current state of the circular economy in Romania by analyzing waste recovery in territorial profile. Also, another objective of the work is to identify the gaps in the territorial profile of the recovery rate of collected waste. To achieve the goals of the research, appropriate statistical methods were used in this study, such as: the Jenks algorithm and the Gini Coefficient. The main results of research suggest there are a lot of gaps in territorial profile from recycling rate perspective and a low concern about circular economy in Romania.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2022-00052023-02-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0005<abstract> <title style='display:none'>Abstract</title> <p>Accounting conservatism is necessary for more reliability and verifiability in financial reports. Studies have reported mixed results concerning the comparative level of conservatism across countries, especially the celebrated comparison between the common law and code law countries. Therefore, this study is an attempt to reinvestigate accounting conservatism in French and UK companies, using 110 French companies and 105 UK companies during the period 2011-2019. Accounting conservatism was measured depending on the asymmetric accruals-to-cash flows because it does not rely on market information and its fluctuations. The results document a greater level of conservatism in UK companies compared to French companies, which confirms the findings of several previous studies concluding that companies in common law countries are more conservative than those from code law countries. The results of this study have many implications for different parties affecting the financial information environment, especially auditors who must continuously monitor conservatism practices in financial reports to maintain an adequate level.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00052022-05-22T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0006<abstract> <title style='display:none'>Abstract</title> <p>The expansion of annual capital budget over the years without a corresponding increase in the volume and quality of infrastructural development in Nigeria has been attributed to those factors assumed to have great impact on the economic performance of the country. This study examined the effect of selected economic factors on the size of construction sector expenditure in Nigeria using economic data from 1981-2020. It employed econometrics statistics. The result revealed that there was a long-run co-integration among the variables with ARDL bound estimate values of F-stat. (7.40) and t-stat. (-6.56) respectively. These are higher than both the lower and upper bound critical values at 1%, 2.5%, 5% and 10% respectively. The result further revealed that exchange rate, oil prices, population, trade openness, foreign direct investment, unemployment rate, public debt and real GDP were important determinants of the size of construction sector expenditure in Nigeria. It also revealed that construction output, inflation rate, government revenue and taxation had trivial determinants due to issues relating to policy, management and execution of capital budget. The study suggested that government should make and implement apposite policies, and be diligent in allocation and management of public fund to ensure a sustainable economy through infrastructural development.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00062022-05-22T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0004<abstract> <title style='display:none'>Abstract</title> <p>Immigration in Romania is a scarcely studied topic, mainly because the impact of this phenomenon is low. Romania is primarily known due to its history of emigration. This paper is a preliminary analysis of the way both temporary and permanent Romanian immigration changed at the NUTS 3 level during the 2015 migration crisis and due to COVID-19 pandemics. Internal migration was also included as the analysis was based on a component of the MASST model on in-migration, but with respect to NUTS3 level migration. The results obtained were statistically significant for the temporary migration and permanent migration. The refugees’ crisis had a direct influence on permanent migrants, while the COVID-19 pandemic left its mark on temporary migration, leading to an increase in the number of temporary migrants.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00042022-05-22T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0001<abstract> <title style='display:none'>Abstract</title> <p>The purpose of this paper is to explore the impact of effective teaching methods on learning outcomes in elementary schools in rural India. Particularly, this paper studies an innovative learning enhancement program called “Parrho Punjab” launched in 2007 in the Indian state of Punjab. Using cross-sectional data, the effect of the “Parrho Punjab” program on third to fifth grade children’s learning levels in basic mathematics is evaluated. This study develops combined research designs of propensity score matching technique and the difference-in-differences (DID) method. In a first step, propensity score matching technique is applied to create a synthetic control group that is as similar as possible to the treatment group in terms of pre- “Parrho Punjab” characteristics. The difference-in-differences approach is then used to estimate the effect of the program on third to fifth grade children’s learning outcomes in basic mathematics. The results indicate a positive and significant effect of the program on children’s learning outcomes in basic mathematics, underscoring the importance of effective pedagogy in enhancing learning outcomes. Combining propensity score matching with the difference-in-differences approach, this study addresses the problem of unmeasured confounding. The DID approach will produce misleading conclusions in the presence of bias due to unmeasured confounders. To the best of my knowledge, previous studies using a DID method for examining the impact of effective teaching strategies on student learning outcomes in India have not made such attempts to address the problem of confounding bias.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00012021-12-02T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0002<abstract> <title style='display:none'>Abstract</title> <p>Migration has for a long time been a significant source of revenue for a huge number of persons in the Republic of Niger. In order to improve their families living condition, a great number of young people in Niger follow the migration path. In 2019, a total of 293 million U.S. dollars has been sent by migrants to their family members in Niger (World Bank, 2019), that is 3% of Niger GDP. The study used various time series econometric techniques including unit root test, Engle-Granger cointegration test, vector equilibrium correction method and some diagnostic tests on the residuals to inspect the connection between remittances and economic growth in Niger. The empirical results showed that there is the existence of a long run relationship between remittances and economic growth in Niger. The error correction term’s coefficient shows that about 51.62% of the discrepancy between long run and short run is corrected with a yearly data suggesting an acceptable rate of adjustment to equilibrium. Also, in the short run ceteris paribus a 10% increase in the remittances would lead to 2.03% increase in Niger Gross Domestic Product.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00022021-12-02T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2021-0003<abstract> <title style='display:none'>Abstract</title> <p>Since the smartphone market is an oligopoly market structure, consumer purchase intention is usually driven by brand preference. This research analyses the customer-to-customer market of second-hand smartphones, pointing out how the brand factor affects the consumers’ purchasing behaviour. It is found that the recovery value and life cycle of Apple smartphones are higher and longer than those of other brands. Moreover, the recovery value of other brand smartphones is significantly driven by the debut date of the Apple smartphones, implicitly forming a consumption cycle. In addition, through machine learning models, the predictability for the recovery value is able to reach 93.55%.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2021-00032021-12-02T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2020-0009<abstract><title style='display:none'>Abstract</title><p>In the present study, generalized classes of estimators for estimating population mean, ratio and product of two population means using rank of auxiliary character in presence of non-response are proposed. The bias and mean square error of proposed classes of estimators are obtained and their performances examined. Specific conditions under which the members of proposed classes of estimators attain minimum mean square error are obtained. Comparative study of the proposed classes of estimators with the relevant estimators is carried out. An empirical study is given to justify the efficiency of the proposed classes of estimators.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2020-00092020-12-31T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2020-0011<abstract><title style='display:none'>Abstract</title><p>In this research work, rotating savings and credit association (ROSCA) effect on the growth of micro, small and medium enterprises (MSMEs) and identification of a factor supporting the continuity of ROSCAs is studied. A well-designed questionnaire with a reliability value of 0.957 was distributed to 400 entrepreneurs in Wukari through snowball sampling technique. After validity check, 368 valid questionnaires were used for the research. Firstly, a paired t-test was applied to know if entrepreneurs achieve significant positive growth in their business before and after 5 years of joining ROSCAs. At 5% level of significance, entrepreneurs achieved significant positive growth in their businesses 5 years and above of joining ROSCAs. Secondly, a one sample proportion Z-score test was used to identify the major factor responsible for ROSCAs continuity. At 5% significance level, flexibility was identified as the major factor responsible for ROSCAs. It was concluded based on the results obtained that ROSCAs has a significant positive effect on the growth of MSMEs and ROSCAs continuity towards MSMEs growth is due to its flexibility factor in terms of operations, disbursement, seeking loans and interest rate.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2020-00112020-12-31T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2020-0012<abstract><title style='display:none'>Abstract</title><p>Collaborative consumption is currently an exciting topic of interest for many debates and controversies being perceived as a fast-growing social phenomenon. Considering the contemporary development processes via sharing economy, there is an interest to prove that the segment of young consumers practices changed from traditional buying and owning behaviour to collaborative consumption stratagems. Thus, the central objective of the present study is to explore the potential young consumer behaviour adjustments and to discuss the motivations behind those changes by considering the emergence of collaborative consumption.</p><p>The primary hypothesis of the present article states that intrinsic and extrinsic motivations influence teenager’s attitudes and behavioural intentions regarding participation in collaborative consumption.</p><p>Regarding the methodology, the author’s performed confirmatory factor analysis and structural equation modelling. The objective was to determine if previously exposed motivational factors influence positively the young consumer’s behavioural intention and their attitude towards a supposed adherence to collaborative consumption schemes.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2020-00122020-12-31T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2020-0010<abstract><title style='display:none'>Abstract</title><p>Identifying the macro-economic determinants of poverty is a key concern for developing poverty reduction policies. Since young people and young migrants in particular are more exposed to poverty, establishing the factors that trigger poverty among these social categories has even more relevance. A preliminary analysis shows that significant differences exist between at-risk-of poverty or social exclusion rate of young migrants and young nationals across European countries. For a more thorough study of the reasons behind these differences in poverty rates between young migrants and young nationals, two panel data regression models are estimated on a cross-section of 23 countries over the period 2010 – 2018 (one model for young migrants, the other for young nationals). Results confirm the main theories in the specialty literature: unemployment and inequality (measured by the Gini index) are the main triggers of poverty or social exclusion both for young nationals and young migrants. However, the income is significant for reducing poverty only for young nationals, but not for the young migrants. This result reinforces the necessity of better integration policies for young migrants in richer Member States.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2020-00102020-12-31T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2019-0005<abstract><title style='display:none'>Abstract</title><p>We investigate the regional dynamic of nosocomial infections in Romanian hospitals, and find potential predictors. Our data covers 13 years, and refer to the incidence of nosocomial infections for each of the 42 Romanian administrative units every year. A preliminary cluster analysis reveals that there is heterogeneity across counties both in terms of average, and variability of nosocomial infections incidence. The heterogeneity can be explained to an important degree by the local level of healthcare infrastructure, urbanization rate and economic development. Supporting programs and clear standards for quality assurance must accompany the investment in health infrastructure, and the development of new out – care units should be prioritized</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2019-00052020-12-17T00:00:00.000+00:00https://sciendo.com/article/10.2478/jses-2019-0008<abstract><title style='display:none'>Abstract</title><p>This study attempts to analyze the impact of climate change on crop production using household consumption survey collected by the national institute of statistics and data imported from the department of statistics of ministry of agriculture and rural development. The main research question is: what is the relationship between climate change and crop production? Methodologically, used is made of instrumental variable and control function models to compute for the data. We realized that to a lesser extent climate change has an effect on agricultural production and more of a fishing phenomenon. In terms of policy, mainstreaming climate change adaptation into national development strategy and budgets could promote proactive engagement on the formulation and implementation of climate change adaptation strategy; this is a wise step towards increasing crop production and malnutrition reduction.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jses-2019-00082020-12-17T00:00:00.000+00:00en-us-1