Econometric Regression Research Articles

Corporate diversification and firm's financial performance: an empirical evidence from Indian IT sector

The aim of this research paper is to provide empirical evidence on the effect of geographic and segment diversification on the financial performance of the Indian IT sector. The study was done on 12 listed IT firms representing 93% market share on BSE/NSE. Standard econometric regression analysis on panel data was carried out to find the stated relationship. The results of the regression analysis revealed that international/geographic diversification impacted strongly on IT firms' profitability whereas product/segment diversification had no significant impact on the firms' profitability. This study also proves the existence of demand for Indian IT sector in other countries. These results could be useful in decision making for top managers of IT companies as they advocate the need for diversification (specialisation) and growth in size and also provide encouragement to small-scale Indian IT companies to undertake international diversification activities with confidence.

AN EMPIRICAL AND ECONOMIC ANALYSIS OF CASSAVA PRODUCTIVITY IN SELECTED AREAS OF SOUTHERN SIERRA LEONE

This study examined the productivity and economic analyses of the cassava production in three communities—Nyallay, Sammamie, and Sindeh sections in Bo districts, Southern Sierra Leone. The crop is processed into garri, fufu, akara, and other foods. Cassava can also be used to make flour, pellets, and chips for animal consumption, as well as biofuel and particle boards The data was gathered using a questionnaire and interview schedule that were both well organized. Descriptive statistics, financial techniques, and a multiple regression model were all employed in the data analysis. The main data came from a sample of 300 cassava growers from three regions. The collected data were evaluated using econometric regression analysis. The findings indicated that, the net farm income was Le 214,361 and the net return on investment was almost Le 258, 375. The findings of a regression analysis showed that the number of cassava cuttings, hired labor, farm size, farming experience, and age statistically substantially influenced the output of cassava in the research region. It is indicated that the availability of improved cassava cuttings in the area and farmers’ access to subsidized inputs like fertilizer. In the study it was suggested that farmers be prodded to invest in the cultivation of cassava because of its economic worth and profitability. Cassava growers should be encouraged to obtain instruction on correct agronomic practices and input usage, and inputs should be made available and at reasonable costs, especially improved types of cassava cuttings, this will increase productivity.

DISCOUNT RATE AS A MEASURE OF MONETARY POLICY FOR MARKET STABILIZATION - EXAMPLE OF THE NATIONAL BANK OF SERBIA

The increase in interest rate is related to the efforts of monetary authorities to neutralize inflationary pressures; while the rate reduction can be interpreted as an invitation to business sector to access more favorable lending conditions. The effectiveness of these changes largely depends on the development level of financial system, the role of the central bank as a creditor and current economic situation. In this research an econometric regression double-logarithmic model was applied, with the main goal of examining the relationship between discount rate and its influence on interest rates and money supply on the example of the National Bank of Serbia. The results show the correlation between the NBS discount rate and interest rates of commercial banks and the amount of money in circulation, indicating their influence on market stability.

Predicting Undergraduate RPA Training (URT) Student Performance

This project is in conjunction with the 558th Flying Training Squadron, the only Undergraduate Remotely Piloted Aircraft (RPA) Training (URT) squadron. The 558th is currently seeing a trainee failure rate of approximately 6%. The project team aims to predict student performance at URT using econometric regression strategies analyzing initial student data for selected trainees and identifying at-risk students early in the training timeline. The 558th seeks to enhance the performance of their trainees by identifying student trends indicative of success and failure prior to URT, enabling them to provide attention and resources to students in need. The team’s goal is to provide the 558th with information that will help them reduce the failure rate at URT without requiring additional funding. It was determined that GPA, PCSM, STEM, and Private Pilot’s License (PPL) status to be significant indicators of student success.

Well-Being and Geography: Modelling Differences in Regional Well-Being Profiles in Case of Spatial Dependence—Evidence from Turkey

The aim of this study is to provide a new quantitative perspective on the geography of well-being using an urban–rural typology and characteristic city size elements in order to detect where people are happier and to examine the determinants of well-being by considering spatial dependence effects. We use 81 NUTS 3 regions and the time period 2012–2019 to analyse the geography of well-being for Turkey with panel and spatial panel models. Our results show that living in an urban area, in general, makes people happy, but that density negatively affects well-being. In addition, city size matters for enhancing well-being. We also analyse the determinants of well-being by using several socio-economic well-being indicators. Next, the aspatial and spatial model results based on spatial econometric regressions show that education, health, employment, and income are all important for well-being, whereas indirect effects (spillovers) of these indicators also exist. Our results indicate that ignoring spatial effects causes a misinterpretation of the effects of critical determinants of well-being in geography.

Population Aging, Industrial Intelligence and Export Technology Complexity

The ageing of the population has become a serious test for all countries and regions, and industrial intelligence, as a new development model that integrates traditional industries with modern technology, will contribute to the deep integration of the industrial and innovation chains and thus to the enhancement of national core competitiveness. Based on the dual influence of population ageing and industrial intelligence, this paper uses the 2016 version of the World Input-Output Database (WIOD) data for 16 manufacturing industries in 43 countries from 2000 to 2014 to construct an econometric regression model to empirically test the relationship between population ageing, industrial intelligence and technological complexity of exports. The results of the study show, firstly, that population ageing plays a positive role in the technical complexity of exports. Secondly, the introduction of industrial intelligence mitigates the adverse effects of an ageing population through a complementary substitution mechanism on the one hand, and promotes industrial upgrading and transformation through the infiltration and expansion effects of industrial intelligence on the other, which in turn has a positive impact on the increase in technological sophistication of exports. In addition, the paper further divides the level of industry technology, the level of national development and the age structure of the ageing population, and explores the impact of industry intelligence in different dimensions. The results show that industrial intelligence can have a positive impact on export technological sophistication at the industry level, at the national level and in terms of ageing demographics. The research results provide a new way of thinking, through which countries around the world can formulate population policies and industrial policies and improve the complexity of export technology under the background of aging.

The Impact of Green Advertising Information Quality Perception on Consumers’ Response: An Empirical Analysis

Green advertising is one of the important tools for companies to carry out marketing activities, and it is especially important for green brand owners to improve the persuasive effect of green advertising. Existing studies focus on the effectiveness of green advertising from the level of message content and message expression, but there is little research to assess the advertising effectiveness of green advertising being “well said” from the perspective of message quality. This article constructs a theoretical framework based on the theory of communication persuasion to assess the effect of perceived message quality on the consumer’s green response to green advertising. Study 1 constructs an econometric regression model by crawling unstructured data, such as green ad review texts through Python, and verifies that consumers’ green responses (green purchase intention and green sharing intention) are mainly influenced by green ad information usefulness, information attractiveness and information truthfulness. Study 2 further tested the direct role of perceived green advertising information quality on the consumer’s green response by constructing structural equation models with situational experimental data, and verified the mediating role of green competence trust and green value trust in the process of perceived green advertising information quality influence on the consumer’s green response. These findings provide a new theoretical perspective on the effectiveness of green advertising, while providing practical guidance for green brand owners to develop green advertising strategies and assess green advertising quality.

Does the digital economy promote "innovation and entrepreneurship" in rural tourism in China?

This paper focuses on the impact of the “Digital Economy” on rural entrepreneurship. Unlike previous literature, the perspective of this paper focuses on a specific industry—tourism—and identifies a new mediating mechanism by which the “Digital Economy” affects rural tourism entrepreneurship—the promotion of innovation. The paper further clarifies the fact that the “Rural Digital Economy Index,” which is a dimension of the Digital Economy Indicator System, is the key to the mechanism of action. Theoretically, first, through a literature review, this paper provides a rationale for the “Digital Economy” to promote innovation behavior by reducing the cost of innovation. Second, using a product matching model, this paper argues that a rural tourism market characterized by innovation can stimulate more entrepreneurship. Empirically, using a sample of 150 counties in the Yangtze River Delta region of China, this paper argues that the higher the digitalization index of a county’s rural economy, the more national model villages and towns this county has (all of which include product innovation in the selection criteria) and more tourism entrepreneurial activities. Econometric methods such as endogeneity, spatial econometric regression, and sensitivity analysis proved the findings robust. Our recommendation is that the Chinese government could focus on improving the innovation environment for rural residents in the future, so that entrepreneurial activities will be spontaneously stimulated by market mechanisms.

Impacts from transportation measures in national appraisal guidelines: coverage and practices

Transportation appraisal has a potential important role in prioritization of transportation investment projects and other transportation measures. Appraisal practices vary much over countries and time, but these differences are not fully known. More knowledge on the variation in practices may contribute to smoother knowledge exchange between countries and more informed choices in the further development of each national practice. In this paper, we present both an updated mapping and a meta-analysis of impact coverage in national appraisal guidelines for transportation measures and spatial measures more generally. Our updated mapping of impact coverage covers 18 national and regional guideline sets and 44 sorts of impact. It shows rather similar overall impact coverage in the reviewed guide-lines for economic, social and environmental impacts. The most advanced appraisal practices are found in Northern and Western Europe and Oceania. We find that supplementary quantitative analyses are most common for economic impacts, while multi-criteria analyses are most common for environmental impacts. Our meta-analysis covers ours and 15 earlier impact mappings, jointly covering 42 countries and regions. In this examination, we show how impact cover-age in appraisal practices has improved over time, particularly for environmental, user and wider economic impacts. The meta-analysis also reveals that Western and Northern European and Oceanian countries and dependencies have had the widest impact coverage from 1998 to 2020, both in CB and overall. To examine what characterize countries with broad and narrow impact coverage, we have applied econometric regression models that are linear (i.e. linear least squares), quasi-linear (i.e. Tobit) and fractional response-based (i.e. fractional probit and fractional logit). In these regression analyses, we control for study-specific characteristics and clustering the standard errors on countries. Our results show that the CB impact coverage tends to increase with economic wealth, equality and population size in developed countries, while we find no such patterns for overall impact coverage.

The spatial panel econometric diagnosis of the influence of green finance on Chinese economic ecologization.

Green finance has the obvious impetus function to economic ecologization development. Through the test of the spatial agglomeration degree of China's green finance and ecological economic development index from 2001 to 2017 (30 provinces except for Hong Kong, Tibet, Taiwan, and Macao), this paper analyzes the spatial correlation of the green finance index and the ecological economic development index. It uses the spatial panel econometric regression analysis model to reveal the impact of Green Finance on China's economic ecology. Results show that (1) the development level of green finance and economic ecologization in China has improved to varying degrees in different periods. However, there are still noticeable regional differences between the eastern, central, western, and northeast regions; (2) green finance plays a positive role in promoting economic ecologization. Developing green finance in one province can promote its economic ecologization and positively impact on economic ecologization of surrounding provinces. (3) Economic ecologization also has a positive spillover effect. The improvement of the ecological economic level of a province can drive the improvement of the ecological economic level of other provinces. Therefore, improving green finance across the country has become a meaningful way to promote economic ecology and promote China's high-quality development.

Analysis of the Effect of Simplified Profit Tax on SMEs at the Level of Factual Budgeted Revenues in Albania

Small and medium enterprises are very important part of Albanian Economy, they represent almost 99% of Albanian registered enterprises and generate more than 80% of jobs in the labour market. They also contribute 60-75% of Gross Domestic Product. SME-s are key elements of the Albanian economy. This study tries to investigate the effects of changes in fiscal policies to SMEs in Albania, which is also the reason why this topic is of interest to many researchers. If we compare Albania’s number of SMEs with other countries that stand for the same level of economic development, they are almost at the same level. Moreover, turnover and the number of employees have increased for SMEs, while revenues collected from this tax have decreased. The study tends to explain how the simplified corporate profit tax rate affects budget revenues, its impact and the changes over the years. We use secondary data to analyze periods from the year 2000 to the year 2019. Also, to analyze if the simplified profit tax is important or statistically significant and it has an effect on the budget revenues, we use an econometric regression model. In a conclusion, this study will also show the government measures during the post-Covid-19 period taken for SMEs. Besides conclusions, we give our recommendations based on our econometric model analysis.

Narrative entrepreneurship: bringing (his)story back to entrepreneurship

Narrative entrepreneurship is the study of the spread and dynamics of popular narratives and stories focusing on the role and impact of entrepreneurs (stories of human interest and emotions), and how these change through time, to understand variation and heterogeneity in entrepreneurial activities across time and space. The term ‘narrative’ refers to a simple story or expressed explanation of events that many people want to bring up in conversation or on the news or social media because it can be used to stimulate the concerns or emotions of others and/or because it appears to advance self-interest. The field of entrepreneurship should be expanded to include serious quantitative study of changing popular narratives (theory development, experiments and econometric regressions). Narrative entrepreneurship is not only a product of reverse causality, from the outcomes to the narrative, but also from the narrative to the outcome (as we know from other fields such as marketing, philanthropy or education). The goal of this paper is to distil what we know, and should know, about narratives and stories to consider reasons to expect that stories and narratives might be thought of as important in the field of entrepreneurship and to stimulate future research to apply the concept of narrative into the field of entrepreneurship for both theory building and empirical analysis.

The impact of informal communication on the quality and productivity of digital collaborative work.

Working via databases has become an integral and necessary part of work in businesses. The availability of knowledge and information from any location contributes to better networking and more transparency in companies and enables collaborative work regardless of the location. In the wake of the COVID-19 pandemic in 2020/21, physical distancing and digital work have become imperative for a greater number of people. This, in turn, can severely restrict both formal and informal means of communication, which can lead to rising cognitive job demands and decreasing productivity at work. Against this background, the question of whether and to what extent digital databases are able to guarantee effective task fulfilment without parallel communication has acquired new relevance. The relationship between informal communication via four communication channels and a) the efficiency of work via databases and b) their necessity for the quality of work are investigated. Employee surveys are evaluated in the form of cross-sectional data from three medium-sized German companies using econometric regression analyses. A clear relationship is revealed between informal communication and the effectiveness of work via databases as well as their necessity for work quality. The level of this relationship, however, varies depending on the type and purpose of informal communication. This article highlights the necessity of informal communication for digital collaborative work and hence has significant implications for business practice.

The Spatial Network Structure of Tourism Efficiency and Its Influencing Factors in China: A Social Network Analysis

Although tourism has gradually become a popular form of leisure and entertainment in China, the quality of China’s tourism development remains unclear. Through the panel data of 30 provinces in China, an SBM-DEA model and a social network analysis are used to explore the quality of tourism development, and a spatial econometric regression is used to identify the relevant factors affecting tourism efficiency. The study found that the level of tourism efficiency in Southwest China is high and stable. The northwest region has a low level of tourism efficiency, but a slow growth trend. The rest of the regions show fluctuating trends of tourism efficiencies. The spatial correlation network of provincial tourism efficiency is gradually complicated. Regarding influencing factors, the number of patents granted, traffic levels, financial development, and government macro-control all have positive effects on tourism efficiency. The study uncovered some useful management insights and implications for the travel industry.

Features of Inter-enterprise Knowledge Recombination in China’s Heavily Polluting Industry

In recent years, knowledge recombination has become a hot topic in green innovation adoption (GIA) research. However, previous studies have mainly discussed the knowledge recombination within a single enterprise but ignored inter-enterprise knowledge recombination (Inter-KR). In this paper, a theoretical framework of Inter-KR is developed, and the three features of Inter-KR are discussed, which are elements, characteristics, and performances. Natural language process, patent analysis, and econometric regression are used to analysze the above three features. Firm-level data from patents, annual suvery, and sweage discharge of Chinese textile enterprises between 1998 and 2013 are matched and analyzed. The empirical results indicate that enterprises can effectively improve their environmental performance by participating in Inter-KR, and the characteristic of comprehensiveness of Inter-KR has a significant promoting effect on GIA. In summary, the Inter-KR trigger more green innovation in both R&D and the manufacturing process of enterprises, and the construction of relevant framework is an effective way to further explore the knowledge recombination of enterprises, which has guiding significance for future GIA research. Our findings provide several new insights for research on knowledge recombination, the literature on collaboration innovation, and green innovation adoption research.

Spatial Econometric Models: A Bayesian Approach

In this paper we propose Bayesian methods to fit econometric regression models, including those where the variability is assumed to follow a regression structure. We formulate the main functions of the statistical R-package BSPADATA, developed according to the proposed methods to obtain posteriori parameter inferences. After that, we include results of simulated studies to illustrate the use of this package and the performance of the proposed methods. Finally, we provide studies to illustrate the applications of the models and compare our results with that obtained by maximum likelihood.

Drivers of foreign direct investment: new evidence from West African regions

PurposeThis paper aims to empirically investigate the factors attracting foreign direct investment (FDI) inflows into emerging economies.Design/methodology/approachThis study uses secondary data from the World Bank and the Global State of Democracy Indices of 16 West African countries (WACs) over the period from 1989 to 2018. Fixed- and random-effects econometric regression models are used to assess the nexus between 12 macroeconomic indicators (including political risk and cultural factors) and FDI inflows into WACs.FindingsThe critical drivers of FDI inflows into WACs are the richness of natural resources, market size or gross domestic product (GDP), imports and exports of goods and services, trade openness and the currency's strength as measured by the exchange rate. The result also reveals that French-speaking countries attract more FDI than other English-speaking countries. The previously cited determinants of FDI, such as infrastructural development, inflation, tax and political stability, are insignificant in determining FDI inflows into WACs.Originality/valueThis study uncovers the critical drivers explaining the FDI inflows into WACs, where FDI accounts for 39% of external finance. The study's contribution is that Francophone WACs attract more FDI than Anglophone WACs. The most important drivers of FDI are abundant natural resources, GDP, imports, exports, trade openness and exchange rate.

Assessing the combining role of public-private investment as a green finance and renewable energy in carbon neutrality target

All governments have lately placed a high priority on achieving carbon neutrality. Environmental sustainability may be achieved via the evaluation of novel approaches. We are looking at the impact of China's public-private energy and efficiency partnerships on the country's carbon dioxide emissions from 1990Q1 to 2019Q4. Furthermore, we include sustainability initiatives, sustainable sources, green finance, and financial progress into our model to better understand carbon dioxide emissions. Econometric regression techniques, such as dynamic ordinary least squares (DOLS) and FMOLS, are used in this work. The research also showed that financial inclusion positively impacts the goal of green finance attainment. According to the findings, China's economic growth and public-private collaboration positively impact carbon emissions. Emissions of carbon dioxide gases, on the other hand, are negatively influenced by improvements in energy efficiency, renewable energy, and technical innovation. Public-private partnerships in energy production must be more efficient to reduce carbon emissions. Chinese policymakers must guarantee a successful and prompt changeover to renewable energy sources via environmental, technological adaptation, and efficient use of all renewable resources.

Forecasting annual electric power consumption using a random parameters model with heterogeneity in means and variances

This paper develops heterogeneity-based econometric models that forecast the yearly consumption of electricity. Unlike previous research, this paper departs from classical econometric regression models and explicitly accounts for unobserved heterogeneity and corresponding interactions. More specifically, three modeling approaches are applied: a random parameter linear regression model (RPLRM), a correlated random parameter linear model (C-RPLRM), and a random parameter linear model with heterogeneity in means and variances (RP-HMV). In addition, a grey model is estimated based on historical consumption data. The estimation results clearly demonstrate that the random parameter methodology is statistically superior to the classical multiple linear regression model. Moreover, based on the test results reported in this paper, as well as the forecasting accuracy measures, the RP-HMV model is shown to be statistically outstanding, with a very low forecasting error (MAPE of 0.04%) compared to the other models, including the grey model. Our estimation results show that two variables, namely the average electricity price and contribution of renewable energy to the national and distribution grids, produced statistically significant random parameters with heterogeneous variances and means. Moreover, the results show that factors including the number of households on the distribution grid, average electric power price, and availability of all-season air conditioners with hot and cold inverter characteristics significantly influenced the electricity consumption. These empirical results reveal that random-parameters models with heterogeneity in their means and variances can provide a detailed analysis of the predictor variables shaping the annual electricity consumption, and they highlight the importance of including unobserved heterogeneity and related interactions in econometric models.

The effects of CSR disclosure on asymmetric information and RoI of publicly listed companies in SRI-Kehati index in Indonesia

PurposeThis study aims to investigate the influence of corporate social responsibility (CSR) disclosure on asymmetric information and return on investment (RoI) in Indonesia. The research specifically assesses the effects of CSR disclosure along with other independent variables such as total assets, return on equity, capital expenditures, net profit margin and sales growth on asymmetric information and RoI.Design/methodology/approachThe study applied a panel econometric regression model to examine and test the effects of CSR disclosure and financial indicators on asymmetric information and RoI. A total of 275 samples were garnered from private and state-owned publicly listed companies selected in the SRI-Kehati index as sustainable firms in Indonesia from 2009 to 2019. Those listed companies in the SRI-Kehati index have market recognition and are able to maintain sustainability practices in their business doings. Asymmetric information was calculated by measuring the spread of market share prices. CSR disclosure was measured with global reporting initiative standards. Other variables did not require calculation.FindingsThis study discerns the significant influence of CSR disclosure on asymmetric information and RoI on the listed firms of the SRI-Kehati Index in Indonesia. To articulate, the more transparent CSR disclosure is, the asymmetric information should be lower. Besides that, more comprehensive CSR disclosure is associated with a better corporate return of investment. In scrutinizing the control variables, this research validates the significant influence of corporate assets and sales revenue on both dependent variables.Research limitations/implicationsThis research has some limitations that require further research. First, the research was conducted in Indonesia. However, other Southeast Asian markets may have their own uniqueness. Therefore, further research is needed in other specific Southeast Asian countries. Second, the sampling bounds on the corporation which gained sustainable recognition in SRI-Kehati Index. Future studies can extend more observation by comparing SRI-Kehati index to firms, which are not listed in the index.Practical implicationsThis study recommends better capital market monitoring and evaluation to improve the quality of the firms’ reports in both business and social aspects. By investing more in philanthropic and social activities, firms can signal the market credibility to their various external stakeholders on their market adjustment to changing external business environment.Social implicationsAs for society, robust CSR disclosures will facilitate investors’ understanding of the conditions before making an investment in public listed companies. At the same time, companies issuing the disclosures are expected by society to perform responsibly, as illuminated in the report. As a result, the CSR disclosures will create a virtuous cycle of sustainability between the company and the society.Originality/valueFirst, this research reinforces the global corporate governance concern to urge more corporate disclosures on firm performance in an Indonesian context. Second, this study fills the research gap on the association of CSR disclosure to asymmetric information in Indonesian literature. Third, the findings underpin the integration of social responsibility on the firms’ core business decision-makings to warrant business credibility to all firms’ stakeholders in Indonesia.