• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.61-69
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• 2022

The study intends to investigate a short-run and a long-run causality among money, income, and prices in the Keynesian and Monetarists framework. This study emphasizes the importance of unrecorded money, which exists alongside legal monetary assets and plays a dual function in determining economic prosperity. The underground economy, which is a hidden component of aggregate economic activity, is determined using Tanzi's monetary approach (Tanzi, 1980). This research uses a time series of annual data from 1990 to 2019 for this purpose. The data is extracted from the World Bank database for the monetary and development indicators. The study keeping in view the trending nature in data follows a unit root testing followed by the Autoregressive Distributive Lag Model (ARDL) to assess the long and short-run dynamics of causality among the variables. In both the pricing and income equations, the study finds a significant level link among the variables; however, there is no evidence of the presence of a level association in the money equation. The short-run causal relationship provides evidence of bi-directional causation between the supply of money and national income. The outcome of this study advise that though the view point of both the Monetarist and Keynesian school holds in both short and long run, however, in Pakistan only the Monetarists' role of money supply and income holds in Pakistan. This evidence would be of precise interest to the policy-makers.

• The Journal of Society for e-Business Studies
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• v.11 no.1
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• pp.91-112
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• 2006

Unlike typical corporate investments, IT expenditures have direct impact on many aspects of a business, including those that are difficult to quantify. Therefore, financial indicators alone do not do justice to the full effect of an If investment. Proposed in this paper is a methodology to measure the return on IT investments, including non-financial impacts expressed in terms of monetary values. This methodology shows tangible cost as well as hidden cost by analyzing total cost of ownership. The methodology also produces ROI by performing cost benefit analysis including financial and non-financial factors. This paper suggests a more objective validation of If's impact on the business activities. It rationalizes investment priorities and provides a systematic approach to effective IT investment.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.241-249
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• 2020

The role of money in the modern economy highly determines the intensity and the development of the macroeconomy. The money supply is assumed to be as much as money demand, which reflects the economic character of a country and indicates the growth and development of macroeconomy. In Indonesia, the money supply (M1) is related to the economic dynamics in either the monetary market or the goods market. This research aims at analyzing factors that influence the money supply and to what extent the economic factors affect the money supply in Indonesia. The analysis method used in this research was Vector Autoregressive (VAR) with some variables, such as money supply (M1), interest rate, and Gross Domestic Product (GDP) from the 1st quarter of 2001 until the 1st quarter of 2013. The data collection method was in the form of data compilation from credible sources, such as Bank of Indonesia (BI), Central Bureau of Statistics (CBS), and International Financial Statistics (IFS). To obtain adequate analysis results, several tests were taken, such as unit-root test, Granger causality test, and optimal lag. VAR analysis formulates the correlation among independent variables, so it also sees the study of impulse response and matrix decomposition.

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.2
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• pp.13-20
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• 2015

Online or e-banking has been adopted as key banking innovation in Uganda adopted by all financial institutions in the country. This research explored the state of e-banking and its efficacy in Uganda banking industry. A correlation analysis approach was adopted for this research. In Uganda, the banking sector has been liberalized with telecommunications allowed to effect e-banking and ecommerce transactions. The study concentrated on the periods of years 2011/2012 and 2012/2013. Findings from this research revealed that BOU uses UNISS for real time gross settlement (RTGS). Since its adoption a +1 coefficient correlation was realized. With the use of mobile money, also a +1 coefficient correlation was achieved for the period under consideration. As regards the use of e-cheques, there was a drop reflected by -2.8 percent which could have been attributed to perception of the users, though there was a +1 coefficient correlation when considering e-cheque transactions and the monetary value. The use of EFT in Uganda generated a +1 coefficient correction considering the number of users and the monetary value involved. Bank of Uganda should work hard and make or go live with electronic banking supervision software which would aid them with their supervisory roles.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.273-279
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• 2011

Concerns over the environment have spawned a number of research studies in the construction industry, as the construction of built environments and large infrastructures involves diverse environmental impacts and loads of hazardous emissions. Many researchers have attempted to quantify these environmental loads, including greenhouse gases, carbon dioxide, nitrogen dioxide, and sulfur dioxide, to name a few. However, little research has been conducted regarding integrating the life-cycle assessment (LCA) of environmental loads with the current life-cycle cost analysis (LCCA) approach. This study aims to estimate the environmental loads as a monetary value using the European Climate Exchange (ECX) rate and, then, to integrate those impacts with the pure construction cost. Toward this end, this study suggests an integrated approach that takes into account the environmental effect on the evaluation of the life-cycle cost (LCC). The bill of quantity (BOQ) data of a real highway project are collected and analyzed for this purpose. As a result, considering the environmental loads in the pavement process, the total LCC increased 16% from the traditional LCC cost. This study suggests an integrated approach that will account the environmental effect on the LCC. Additionally, this study is expected to contribute to better decision-making, from the perspective of more sustainable development, for government as well as for contractors.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.283-289
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• 2007

Benefit-cost analysis is a useful tool for organizing information on the relative value of alternative public investments like national park preservation projects. When the value of all significant benefits and costs can be expressed in monetary terms, the net value (benefits minus costs) of the alternatives under consideration can be computed and used to identify the alternative that yields the greatest increase in public welfare. However, since goods and services of national parks are not commonly bought or sold in the marketplace, it can be difficult to express the outputs of a national park preservation project in monetary terms. In this case the dichotomous choice contingent valuation is employed to elicit the public benefit value. In this paper, a distribution-free approach, Turnbull empirical distribution model, is employed to analysis the benefit value of Woraksan National Park. The result is shown that annual use and preservation values of Woraksan National Park are estimated 6.5 and l37.4 billion won. Also, flow and stock values are estimated 143.9 and 3,021.7 billion won, respectively.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.143-149
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• 2020

Low inflation and sustainable growth have been the major macroeconomic goals being pursued by every developing country, Vietnam inclusive. The effect of inflation on economic growth has been intensively analyzed by a variety of studies, but the empirical evidence more often than not remains controversial and ambiguous. One common hypothesis of previous studies is that they have assumed that the effect of inflation on growth is symmetric. The main purpose of this study is to investigate the asymmetric effect of inflation and money supply on economic growth using the Nonlinear Autoregressive Distributed Lag approach introduced by Shin, Byungchul, and Greenwood-nimmo (2013) for Vietnam over the period 1990-2017. Empirical results provide evidence that the effects of inflation on economic growth are negative and asymmetric in the long run. The impact of money supply on growth is positive in both the short-run and long-run. Accordingly, the impact of the increase in the inflation rate is bigger than the decreasing in the long-run. This different impact is significant and high inflation will destruct economic activities. As a result, the study provides empirical evidence for the authorities to plan monetary policies and control the rate of inflation to achieve sustainable economic development in the long-run.