Search results for: macroeconomic indicators

Authors: Agim Kukelii, Gevorg Sargsyan

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This study, focusing on the base regional area (county level), estimates the effect of natural disaster damages on aggregate personal income, aggregate wages, wages per worker, aggregate employment, and aggregate income transfer. The study further estimates the dynamics of personal income, employment, and wages under natural disaster shocks. Southeast Texas, located at the center of Golf Coast, is hit by meteorological and hydrological caused natural disasters yearly. On average, there are more than four natural disasters per year that cane an estimated damage average of 2.2% of real personal income. The study uses the panel data method to estimate the average effect of natural disasters on the area’s economy (personal income, wages, employment, and income transfer). It also uses Panel Vector Autoregressive (PVAR) model to study the dynamics of macroeconomic variables under natural disaster shocks. The study finds that the average effect of natural disasters is positive for personal income and income transfer and is negative for wages and employment. The PVAR and the impulse response function estimates reveal that natural disaster shocks cause a decrease in personal income, employment, and wages. However, the economy’s variables bounce back after three years. The novelty of this study rests on several aspects. First, this is the first study to investigate the effects of natural disasters on macroeconomic variables at a regional level. Second, the study uses direct measures of natural disaster damages. Third, the study estimates that the time that the local economy takes to absorb the natural disaster damages shocks is three years. This is a relatively good reaction to the local economy, therefore, adding to the “resiliency” hypothesis. The study has several implications for policymakers, businesses, and households. First, this study serves to increase the awareness of local stakeholders that natural disaster damages do worsen, macroeconomic variables, such as personal income, employment, and wages beyond the immediate damages to residential and commercial properties, physical infrastructure, and discomfort in daily lives. Second, the study estimates that these effects linger on the economy on average for three years, which would require policymakers to factor in the time area need to be on focus.

Keywords: natural disaster damages, macroeconomics effects, PVAR, panel data

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Authors: Renata Silva-Mann, Sheila Valéria Álvares Carvalho, Robério Anastácio Ferreira, Laura Jane Gomes

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There is growing interest in defining indicators of sustainability, which are important for monitoring the conservation of native forests, particularly in areas of permanent protection. These indicators are references for assessing the state of the forest and the status of the depredated area and its ability to maintain species populations. The aim of the present study was to select genetic parameters as indicators of sustainability for Schinus terebinthifolius Raddi. Fragments located in riparian areas between the Sergipe and Alagoas States in Brazil. This species has been exploited for traditional communities, which represent 20% of the incoming. This study was carried out using the indicators suggested by the Organization for Economic Cooperation and Development, which were identified as Driving-Pressure-State-Impact-Response (DPSIR) factors. The genetic parameters were obtained in five populations located on the shores and islands of the São Francisco River, one of the most important rivers in Brazil. The framework for Schinus conservation suggests seventeen indicators of sustainability. In accordance with genetic parameters, the populations are isolated, and these genetic parameters can be used to monitor the sustainability of those populations in riparian area with the aim of defining strategies for forest restoration.

Keywords: alleles, molecular markers, genetic diversity, biodiversity

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Authors: Ahmad Haidar

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Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

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Authors: Alaa A. Al-Harthi, Abdulrahman S. Bageis, Bingunath Ingirige

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Poor levels of performance and low productivity were highlighted by many previous studies as a major cause of failure in the Saudi construction industry. This paper provides recommendations to address key external indicators that led to poor levels of performance and low productivity in Engineering and Technical Departments (ETDs) within the Saudi governmental agencies. The ETDs are client’s representative on behalf of the Saudi Ministries. This paper represents a part of an investigation which contained external and internal challenges that led to occurrence of the research problem. The paper is focusing on the external challenges which contain 14 indicators. These 14 external indicators had been examined carefully through comprehensive review of the literature then have been tested through quantitative and qualitative methods. 400 questionnaires were distributed to dozens of different bodies. The actual response rate was 47% completed responses. Four semi-structured interviews were conducted with senior practitioners from the Public Construction Sector. The finding showed that the 14 external indicators directly and/or indirectly influence the Public Construction Sector. It was noticed significantly that these indicators have prevented the ETDs from performing properly. It was also found that the 14 external indicators were constant with all kinds of Government Construction Projects in the Saudi context. Addressing the 14 external indicators requires to be planned over the long run which is responsible by relevant Saudi governmental authorities under the umbrella of the Saudi Council of Ministers. The study recommends that Project Management Office (PMO) should be considered in order to improve the performance of the ETDs.

Keywords: construction projects' performance, low engineering productivity, public construction sector

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Authors: Amrutha Venugopal, Rabee Rustum

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In spite of huge investments and the vital role infrastructure plays in the economy of UAE, the country has not yet developed an assessment scheme to measure the sustainability of infrastructure projects/development. The aim of this study was to develop a sustainability rating system for infrastructure projects in UAE using weighted indicator scoring. The identification of the list of 66 indicators was done by content analysis. The sources of content analysis were from government guidelines, research literature and sustainability rating system for infrastructure projects namely BCA Greenmark for Infrastructure (Singapore), ISCA (Australia) and Envision (USA). These indicators were shortlisted based on their relevance in the UAE. A mixture of qualitative and quantitative research methods is utilized to find the weightage to be applied to the indicators and to find suggestive measures to improve infrastructure sustainability in this region. Interviews and surveys were conducted with a good mix of experts from the industry. The data collected from the interviews were collated to provide suggestive measures for improving infrastructure sustainability. The collected survey data were analyzed using statistical analysis techniques to find the indicator weighing. The indicators were shortlisted by 75% to minimize the effort and investment into the process. The weighing of the deleted indicators was distributed among the critical clusters identified by Pareto analysis. Finally a simple Microsoft Excel tool was developed as the rating tool by using the calculated weighing for the indicators.

Keywords: infrastructure, rating system, suggestive measures, sustainability, UAE

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Authors: Veruska C. Dutra, Afonso R. Aquino

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Since the 1980s, global tourism activity has consolidated worldwide to become an important economic contributor, and consequently, the sociocultural and environmental impacts are starting to become evidenced. This raises the need of discussing about actions for sustainable tourism that should be linked not only to the economy, but also to the environment and social aspects. The work that is going to be presented is part of a doctoral research project in Sciences undertaken at the Sao Paulo University, Brazil. It aims to analyze whether the monitoring of the tourism sector with a focus on sustainability is applicable or not, through those indicators, put in a case study in the Jalapão State Park (JSP) conservation unit, in the state of Tocantins, Brazil. This is a study of an interdisciplinary nature that had the deductive method as its guide. We concluded that the key points of the sustainable tourism, when analyzed with the focal point in environmental indicators, are an important evaluation and quantification tool of that activity in the study locus. It displayed itself as an adequate tool for monitoring, thus decoding, the main environmental impacts that occur in tourism regions and their intensity, which is made possible through analysis, and has the objective to trace ways to prevent and correct the presented impacts.

Keywords: indicators, tourism, sustainability, Jalapão

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Authors: Joana Margarida Bôto, Belmira Neto, Vera Miguéis, Manuela Meireles, Ada Rocha

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The Mediterranean diet has been recognized as a sustainable model of living with benefits for the environment and human health. However, a complete assessment of its sustainability, encompassing all dimensions and aspects, to our best knowledge, has not yet been realized. This systematic literature review aimed to fill this gap by identifying and describing the indicators used to assess the sustainability of the Mediterranean diet, looking at several dimensions, and presenting the results from their application. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines methodology was used, and searches were conducted in PubMed, Scopus, Web of Science, and GreenFile. There were identified thirty-two articles evaluating the sustainability of the Mediterranean diet. The environmental impact was quantified in twenty-five of these studies, the nutritional quality was evaluated in seven studies, and the daily cost of the diet was assessed in twelve studies. A total of thirty-three indicators were identified and separated by four dimensions of sustainability, specifically, the environmental dimension (ten indicators, namely carbon, water, and ecological footprint), the nutritional dimension (eight indicators, namely Health score and Nutrient Rich Food Index), the economic dimension (one indicator, the dietary cost), the sociocultural dimension (six indicators – with no results). Only eight of the studies used combined indicators. The Mediterranean diet was considered in all articles as a sustainable dietary pattern with a lower impact than Western diets. The carbon footprint ranged between 0.9 and 6.88 kg CO₂/d per capita, the water footprint between 600 and 5280 m³/d per capita, and the ecological footprint between 2.8 and 53.42 m²/d per capita. The nutritional quality was high, obtaining 122 points using the Health score and 12.95 to 90.6 points using the Nutrient Rich Food Index. The cost of the Mediterranean diet did not significantly differ from other diets and varied between 3.33 and 14.42€/d per capita. A diverse approach to evaluating the sustainability of the Mediterranean diet was found.

Keywords: Mediterranean diet, sustainability, environmental indicators, nutritional indicators

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Authors: Elena Tkachenko, Elena Rogova, Daria Koval

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The paper examines the ways of cash flows forecasting in the dynamic external environment. The so-called new reality in economy lowers the predictability of the companies’ performance indicators due to the lack of long-term steady trends in external conditions of development and fast changes in the markets. The traditional methods based on the trend analysis lead to a very high error of approximation. The macroeconomic situation for the last 10 years is defined by continuous consequences of financial crisis and arising of another one. In these conditions, the instruments of forecasting on the basis of fuzzy sets show good results. The fuzzy sets based models turn out to lower the error of approximation to acceptable level and to provide the companies with reliable cash flows estimation that helps to reach the financial stability. In the paper, the applicability of the model of cash flows forecasting based on fuzzy logic was analyzed.

Keywords: cash flow, industrial enterprise, forecasting, fuzzy sets

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Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

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The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: indicators, ISM, lean, social, sustainability

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Authors: Jonathan J. Burson

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With the rise of virtually costless, mobile-based trading platforms, stock market trading activity has increased significantly over the past decade, particularly for the millennial generation. This increased stock market attention, combined with the recent market turmoil due to the economic upset caused by COVID-19, make the topics of market-timing and forecasting particularly relevant. While the overall stock market saw an unprecedented, historically-long bull market from March 2009 to February 2020, the end of that bull market reignited a search by investors for a way to reduce risk and increase return. Similar searches for outperformance occurred in the early, and late 2000’s as the Dotcom bubble burst and the Great Recession led to years of negative returns for mean-variance, index investors. Extensive research has been conducted on fundamental analysis, technical analysis, macroeconomic indicators, microeconomic indicators, and other techniques—all using different methodologies and investment periods—in pursuit of higher returns with lower risk. The enormous variety of timeframes, data, and methodologies used by the diverse forecasting methods makes it difficult to compare the outcome of each method directly to other methods. This paper establishes a process to evaluate the market-timing methods in an apples-to-apples manner based on simplicity, performance, and feasibility. Preliminary findings show that certain technical analysis models provide a higher return with lower risk when compared to the buy-and-hold method and to other market-timing strategies. Furthermore, technical analysis models tend to be easier for individual investors both in terms of acquiring the data and in analyzing it, making technical analysis-based market-timing methods the preferred choice for retail investors.

Keywords: buy-and-hold, forecast, market-timing, probit, technical analysis

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: P. Mbecke

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Developmental social welfare implemented through developmental social work is being applauded internationally as an approach that facilitates social development theory and practice. However, twenty-two years into democracy, there are no tangible evidences that the much-desired developmental social welfare approach has assisted the post-apartheid macroeconomic policy frameworks in addressing poverty and inequality, thus, the derailment of the post-apartheid development approach in South Africa. Based on the implementation research theory, and the literature review technique, this paper recognizes social work as a principal role-player in social development. It recommends the redesign and implementation of an effective developmental social welfare approach with specific strategies, programs, activities and sufficient resources aligned to and appropriate in delivering on the promises of the government’s macroeconomic policy frameworks. Such approach should be implemented by skilled and dedicated developmental social workers in order to achieve transformation in South Africa.

Keywords: apartheid, developmental social welfare, developmental social work, inequality, poverty alleviation, social development, South Africa

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Authors: J. Fajardo, J. Guerra, E. Gonzales

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This paper will outline a study of Brazil's industrial base of defense (IDB), through a bibliographic research method, combined with an analysis of macroeconomic data from several available public data platforms. This paper begins with a brief study about Brazilian national industry, including analyzes of productivity, income, outcome and jobs. Next, the research presents a study on the defense industry in Brazil, presenting the main national companies that operate in the aeronautical, army and naval branches. After knowing the main points of the Brazilian defense industry, data on the productivity of the defense industry of the main countries and competing companies of the Brazilian industry were analyzed, in order to summarize big cases in Brazil with a comparative analysis. Concerned the methodology, were used bibliographic research and the exploration of historical data series, in order to analyze information, to get trends and to make comparisons along the time. The research is finished with the main trends for the development of the Brazilian defense industry, comparing the current situation with the point of view of several countries.

Keywords: economics of defence, industry, trends, market

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Authors: Khalid Obaed Mahmod, Mesut Cevik

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The term smart city has appeared recently and was accompanied by many definitions and concepts, but as a simplified and clear definition, it can be said that the smart city is a geographical location that has gained efficiency and flexibility in providing public services to citizens through its use of technological and communication technologies, and this is what distinguishes it from other cities. Smart cities connect the various components of the city through the main and sub-networks in addition to a set of applications and thus be able to collect data that is the basis for providing technological solutions to manage resources and provide services. The basis of the work of the smart city is the use of artificial intelligence and the technology of the Internet of Things. The work presents the concept of smart cities, the pillars, standards, and evaluation indicators on which smart cities depend, and the reasons that prompted the world to move towards its establishment. It also provides a simplified hypothetical way to measure the ideal smart city model by defining some indicators and key pillars, simulating them with logic circuits, and testing them to determine if the city can be considered an ideal smart city or not.

Keywords: factors, indicators, logic gates, pillars, smart city

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Authors: A. Bouabid, B. Bielenberg, S. Ainane, N. Pasha

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In this paper, a team of faculty members of the Petroleum Institute in Abu Dhabi, UAE representing six different courses across General Engineering (ENGR), Communication (COMM), and Design (STPS) worked together to establish a clear developmental progression of learning outcomes and performance indicators for targeted knowledge, areas of competency, and skills for the first three semesters of the Bachelor of Sciences in Engineering curriculum. The sequences of courses studied in this project were ENGR/COMM, COMM/STPS, and ENGR/STPS. For each course’s nine areas of knowledge, competency, and skills, the research team reviewed the existing learning outcomes and related performance indicators with a focus on identifying linkages across disciplines as well as within the courses of a discipline. The team reviewed existing performance indicators for developmental progression from semester to semester for same discipline related courses (vertical alignment) and for different discipline courses within the same semester (horizontal alignment). The results of this work have led to recommendations for modifications of the initial indicators when incoherence was identified, and/or for new indicators based on best practices (identified through literature searches) when gaps were identified. It also led to recommendations for modifications of the level of emphasis within each course to ensure developmental progression. The exercise has led to a revised Sequence Performance Indicator Mapping for the knowledge, skills, and competencies across the six core courses.

Keywords: curriculum alignment, horizontal and vertical progression, performance indicators, skill level

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Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

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Authors: Veruska C. Dutra, Lucio F.M. Adorno, Mary L. G. S. Senna

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Since it recognized the importance of planning sustainable tourism, which has been discussed effective methods of monitoring tourist. In this sense, the indicators, can transmit a set of information about complex processes, events or trends, showing up as an important monitoring tool and aid in the environmental assessment, helping to identify the progress of it and to chart future actions, contributing, so for decision making. The World Tourism Organization - WTO recognizes the importance of indicators to appraise the tourism activity in the point of view of sustainability, launching in 1995 eleven Keys Indicators of Sustainable Tourism to assist in the monitoring of tourist destinations. So we propose a case study to examine the applicability or otherwise of a monitoring methodology and aid in the understanding of tourism sustainability, analyzing the effectiveness of local indicators on the approach defined by the WTO. The study was applied to the Lagoa da Confusão City, in the state of Tocantins - North Brazil. The case study was carried out in 2006/2007, with the guiding deductive method. The indicators were measured by specific methodologies adapted to the study site, so that could generate quantitative results which could be analyzed at the proposed scale WTO (0 to 10 points). Applied indicators: Attractive Protection – AP (level of a natural and cultural attractive protection), Sociocultural Impact–SI (level of socio-cultural impacts), Waste Management - WM (level of management of solid waste generated), Planning Process-PP (trip planning level) Tourist Satisfaction-TS (satisfaction of the tourist experience), Community Satisfaction-CS (satisfaction of the local community with the development of local tourism) and Tourism Contribution to the Local Economy-TCLE (tourist level of contribution to the local economy). The city of Lagoa da Confusão was presented as an important object of study for the methodology in question, as offered condition to analyze the indicators and the complexities that arose during the research. The data collected can help discussions on the sustainability of tourism in the destination. The indicators TS, CS, WM , PP and AP appeared as satisfactory as allowed the measurement "translating" the reality under study, unlike TCLE and the SI indicators that were not seen as reliable and clear and should be reviewed and discussed for an adaptation and replication of the same. The application and study of various indicators of sustainable tourism, give better able to analyze the local tourism situation than monitor only one of the indicators, it does not demonstrate all collected data, which could result in a superficial analysis of the tourist destination.

Keywords: indicators, Lagoa da Confusão, Tocantins, Brazil, monitoring, sustainability

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Authors: Vijay Kumar, Ron Bird

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The study investigates the effect of bank-specific, industry-specific and macroeconomic variables on the profitability of conventional and Islamic banks. Our sample comprises 1,781 bank-year observations of 205 banks from four countries in the Asian region for the period 2004-2014. Our results suggest that credit quality, cost management and bank size are the keys factors that contribute positively to bank profitability in Asia. The banks with high non-performing loans and high cost-to-income ratio are more likely to be exposed to losses. The impacts of the bank-specific variables are stronger than are the industry-specific and macroeconomic variables. We find that Malaysian banks are the least profitable compared to the banks in Bangladesh, Indonesia and Pakistan. There is strong evidence to suggest that conventional banks are more profitable than Islamic banks. Our results suggest that the impact of capital adequacy ratio and bank size and loan to deposit ratio vary across Islamic and conventional banks and across different subsamples.

Keywords: capital adequacy ratio, Islamic banks, non-performing loan ratio, ownership

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Authors: Tzay-An Shiau, Kuan-Lin Ho

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This study developed sustainability and quality of life indicators for urban passenger transportation by using Social Construction of Technology (SCOT). The initial indicators were proposed by referring to literatures and were summarized by using impact-based framework. Subsequently, the stakeholders were defined according to their interest, power and then classified into scientific, operational, policy making, policy monitoring and nonprofessional frames. The scientific frame consisted of nine scholars in transportation field. Ten representatives from Taipei Rapid Transit Corporation (TRTC), Taiwan Railways Administration (TRA) and bus operators were grouped into the operational frame. The policy making frame comprised of ten representatives from Department of Transportation, Taipei City Government (DOT, TCG), Department of Railways and Highways, Ministry of Transportation and Communication (DORH, MOTC), Directorate General of Highways, Ministry of Transportation and Communication (DGOH, MOTC) and Institute of Transportation, Ministry of Transportation and Communication (IOT, MOTC). The policy monitoring frame consisted of 15 representatives from Taipei City Councilor, legislator and reporter. The nonprofessional frame comprised of 72 Taipei citizens. The stakeholders were asked to evaluate the relative importance of indicators using Delphi survey method. Social construction of 14 transport sustainability indicators and 12 transport quality of life indicators were obtained.

Keywords: sustainability, quality of life, Social Construction of Technology (SCOT), stakeholder

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Authors: S. Karklina, I. Erins

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The main problem is that there is a very low innovation performance in Latvia. Since Latvia is a Member State of European Union, it also shall have to fulfill the set targets and to improve innovative results. Universities are one of the main performers to provide innovative capacity of country. University, industry and government need to cooperate for getting best results. The intellectual property is one of the indicators to determine innovation level in the country or organization and patents are one of the characteristics of intellectual property. The objective of the article is to determine indicators characterizing innovative environment in Latvia and influence of the development of universities on them. The methods that will be used in the article to achieve the objectives are quantitative and qualitative analysis of the literature, statistical data analysis, and graphical analysis methods.

Keywords: HEI, innovations, Latvia, patents

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Levente Varga, Dávid Deritei, Mária Ercsey-Ravasz, Răzvan Florian, Zsolt I. Lázár, István Papp, Ferenc Járai-Szabó

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One of the major shortcomings of widely used scientometric indicators is that different disciplines cannot be compared with each other. The issue of cross-disciplinary normalization has been long discussed, but even the classification of publications into scientific domains poses problems. Structural properties of citation networks offer new possibilities, however, the large size and constant growth of these networks asks for precaution. Here we present a new tool that in order to perform cross-field normalization of scientometric indicators of individual publications relays on the structural properties of citation networks. Due to the large size of the networks, a systematic procedure for identifying scientific domains based on a local community detection algorithm is proposed. The algorithm is tested with different benchmark and real-world networks. Then, by the use of this algorithm, the mechanism of the scientometric indicator normalization process is shown for a few indicators like the citation number, P-index and a local version of the PageRank indicator. The fat-tail trend of the article indicator distribution enables us to successfully perform the indicator normalization process.

Keywords: citation networks, cross-field normalization, local cluster detection, scientometric indicators

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Authors: Maha Rashid Al-Azib, Almuzn Qasem Alqathradi, Amal Munir Alshahrani, Bilqis Mohammed Assiri, Ali Almuflih

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The Occupational Safety and Health Management System in one of the largest Saudi companies has been experiencing in the last 10 years extensive direct and indirect expenses due to lack of proactive leading indicators and safety leadership effective procedures. And since there are no studies that are associated with this department of safety in the company, this research has been conducted. In this study we used a mixed method approach containing a literature review and experts input, then a qualitative questionnaire provided by Institute for Work and Health related to determining the company’s occupational safety and health management system level out from three levels (Compliance - Improvement - Continuous Learning) and the output regarding the company’s level was in Continuous Learning. After that Deming cycle was employed to create a set of proactive leading indicators and analyzed using the SMART method to make sure of its effectiveness and suitability to the company. The objective of this research is to provide a set of proactive indicators to contribute in making an efficient occupational safety and health management system that has less accidents which results in less expenses. Therefore, we provided the company with a prototype of an APP, designed and empowered with our final results to contribute in supporting decisions making processes.

Keywords: proactive leading indicators, OSH MS, safety leadership, accidents reduction

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Authors: Alain Villemeur

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The relationships between the profit share in income on the one hand and the growth rates of output and employment on the other hand have been studied for 17 advanced economies since 1961. The vast majority (98%) of annual values for the profit share fall between 20% and 40%, with an average value of 33.9%. For the 17 advanced economies, Gross Domestic Product and productivity growth rates tend to fall as the profit share in income rises. For the employment growth rates, the relationships are complex; nevertheless, over long periods (1961-2000), it appears that the more job-creating economies are Australia, Canada, and the United States; they have experienced a profit share close to 1/3. This raises a number of questions, not least the value of 1/3 for the profit share and its role in macroeconomic fundamentals. To explain these facts, an endogenous growth model is developed. This growth and distribution model reconciles the great ideas of Kaldor (economic growth as a chain reaction), of Keynes (effective demand and marginal efficiency of capital) and of Ricardo (importance of the wage-profit distribution) in an economy facing creative destruction. A production function is obtained, depending mainly on the growth of employment, the rate of net investment and the profit share in income. In theory, we show the existence of incentives: an incentive for job creation when the profit share is less than 1/3 and another incentive for job destruction in the opposite case. Thus, increasing the profit share can boost the employment growth rate until it reaches the value of 1/3; otherwise lowers the employment growth rate. Three key findings can be drawn from these considerations. The first reveals that the best GDP and productivity growth rates are obtained with a profit share of less than 1/3. The second is that maximum job growth is associated with a 1/3 profit share, given the existence of incentives to create more jobs when the profit share is less than 1/3 or to destroy more jobs otherwise. The third is the decline in performance (GDP growth rate and productivity growth rate) when the profit share increases. In conclusion, increasing the profit share in income weakens GDP growth or productivity growth as a long-term trend, contrary to the trickle-down hypothesis. The employment growth rate is maximum for a profit share in income of 1/3. All these lessons suggest macroeconomic policies considering the profit share in income.

Keywords: advanced countries, GDP growth, employment growth, profit share, economic policies

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

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Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

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Authors: Wesam Rababa, Jamal Al-Qawasmi

Abstract:

The global climate is negatively impacted by CO2 emissions, which are mostly produced by buildings. Several green building rating systems (GBRS) have been proposed to impose low-carbon criteria in order to address this problem. The Green Globes certification is one such system that evaluates a building's sustainability level by assessing different categories of environmental impact and emerging concepts aimed at reducing environmental harm. Therefore, assessment tools at the national level are crucial in the developing world, where specific local conditions require a more precise evaluation. This study analyzed eight sustainable building assessment systems from different regions of the world, comparing a comprehensive list of CO2-related indicators with a various assessment system for conducting coverage analysis. The results show that GBRS includes both direct and indirect indicators in this regard. It reveals deep variation between examined practices, and a lack of consensus not only on the type and the optimal number of indicators used in a system, but also on the depth and breadth of coverage of various sustainable building SB attributes. Generally, the results show that most of the examined systems reflect a low comprehensive coverage, the highest of which is found in materials category. On the other hand, the most of the examined systems reveal a very low representative coverage.

Keywords: Assessment tools, CO2-related indicators, Comparative study, Green Building Rating Systems

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

Abstract:

Risk premium of emerging markets are moving altogether depending on the momentum and shifts in the global risk appetite. However, the magnitudes of these changes in the risk premium of emerging market economies might vary. In this paper, we focus on how global risk factor affects credit default swaps (CDS) premiums of emerging markets using principal component analysis (PCA) and rolling regressions. PCA results indicate that the first common component accounts for almost 76% of common variation in CDS premiums of emerging markets. Additionally, the explanatory power of the first factor seems to be high over sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are employed to identify the macroeconomic factors driving the heterogeneity across emerging markets. There are two main macroeconomic variables that affect the sensitivity; government debt to GDP and international reserves to GDP. The countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: emerging markets, principal component analysis, credit default swaps, sovereign risk

Procedia PDF Downloads 348

Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

Abstract:

Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

Procedia PDF Downloads 110

Authors: Davod Ahmadigheidari

Abstract:

The main objective of this study was to explore prevalence of anthropometric indicators as well the factors associated with the anthropometric indications in Mali. Data on 2015, downloaded from the website of Unicef, were analyzed. A total of 16,467 women (ages 15-49 years) and 16,467 children (ages 0-59 months) were selected for the sample. Different statistical analyses, such as descriptive, crosstabs and binary logistic regression form the basis of this study. Child anthropometric indicators (i.e., wasting, stunting, underweight and BMI for age) were used as the dependent variables. SPSS Syntax from WHO was used to create anthropometric indicators. Different factors, such as child’s sex, child’s age groups, child’s diseases symptoms (i.e., diarrhea, cough and fever), maternal education, household wealth index and area of residence were used as independent variables. Results showed more than forty percent of Malian households were in nutritional crises (stunting (42%) and underweight (34%). Findings from logistic regression analyses indicated that low score of wealth index, low maternal education and experience of diarrhea in last two weeks increase the probability of child malnutrition.

Keywords: Mali, wasting, stunting, underweight, BMI for age and wealth index

Procedia PDF Downloads 127