Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches

In recent years, neural networks have received an increasing amount of intention among macroeconomic forecasters because of their potential to detect and reproduce linear and nonlinear relationship among a set of variables. This study provides an introduction to neural networks and its establishment to standard econometric techniques. An empirical results in forecasting macroeconomic variables to GDP growth in Malaysia was initially introduced. For both the in-sample and the out-of-sample periods, the forecasting accuracy of the neural network is found to be superior to a well established linear regression model, with the error reduction ranging 8 per cent to 57 per cent. A throughout review of the literature suggests that neural networks are generally more accurate than linear models for out-of-sample forecasting of economic output and various financial variables such as stock prices. However, the literature should still be considered inconclusive due to the relatively small number of reliable studies on the macroeconomic forecasting. The full potential of neural networks can probably be exploited by using them in conjunction with linear regression models. Hence, neural networks should be viewed as an additional tool to be included in the toolbox of macroeconomic forecasters

Predicting GDP growth in Malaysia using knowledge-based economy indicators : a comparison between neural network and econometric approaches

In recent years, neural network techniques have been increasingly used for a wide variety of applications where statistical methods had been traditionally employed. Neural network techniques, for example, have been applied to problems like chemical process control, seismic signals interpretation, machines diagnostic, target marketing, economic forecasting, financial modelling, market share prediction, stock market prediction, and risk management. In contrast, traditional econometric approaches have continued to be used for prediction models in almost all the above areas. This paper proposes the extension of neural network techniques to include prediction models because of two obvious advantages. First, it does not require any assumptions about underlying population distribution; second, it is especially useful in cases where inputs are highly correlated or are missing, or where the systems are nonlinear. This paper presents a comparative case study between neural network and econometric approaches to predict GDP growth in Malaysia using knowledge based economy indicators based on time series data collected from 1995?2000. The findings indicate that the neural network technique has an increased potential to predict GDP growth based on knowledge based economy indicators compared to the traditional econometric approach

Experience in the Rapid Progress of Plantation Development Malaysia : Opportunities and Challenges of Platation Development in New Normal

Materi ini disampaikan pada webinar yang diselenggarakan oleh Pascasarjana Universitas Medan Area dengan Tema "The Future Strategies Of Estate Crops In The New Normal ". Adapun pembicara pada webinar ini adalah Dr. Antarjo Dikin, Prof. John McCarthy, Dr. Shri Dewi, Dr. Mulia Panusunan Nasution, Prof. Phuong Ho Ngoc, dan Dr. Mohd Zukime B. Mat Junoh - This material was presented in a webinar organized by the Graduate University of Medan Area with the theme "The Future Strategies Of Estate Crops In The New Normal ". The speakers at this webinar are Dr. Antarjo Dikin, Prof. John McCarthy, Dr. Shri Dewi, Dr. Mulia Panusunan Nasution, Prof. Phuong Ho Ngoc, and Dr. Mohd Zukime B. Mat Junoh

Loan Growth, Bank Solvency and Firm Value: A Comparative Study of Nigerian and Malaysian Commercial Banks

The study explore the issues relating to credit growth, non-performing credit and bank solvency in the banking industry, recognizing that existing studies are largely sketchy in emerging and developing markets. Panel data estimation technique is employed in the study based on data extracted from 26 commercial banks in Nigeria and Malaysia over the period 2009 to 2017 making up to 234 observations. The results reveal that the NPLs for all banks is only explained by loan growth and inflation, NPLs for Nigerian banks is only explained by loan growth, leverage, efficiency, size and inflations while NPLs for Malaysian banks is only explained by leverage, efficiency, size, GDP and inflation. The bank solvency for all banks is only explained by NPLs, loan growth and leverage. The solvency for Nigerian banks is explained by NPLs, leverage and GDP while loan growth, size and inflation explained bank solvency for Malaysian banks. Firm value for all banks is explained by solvency, NPLs, leverage, efficiency, size and GDP, the value of firm for Nigerian banks is only explained by solvency, loan growth, leverage, efficiency and size. The firm value for Malaysian banks is only explained by solvency, loan growth, leverage, efficiency, size, GDP and inflation. It is observed that bank solvency play an important role in the firm value of commercial banks in the period of study. Hence, this paper contributes to the understanding of the dynamic role of abnormal loan growth and how it can enhance the volume of non-performing credit and suggest that further study can explore the interaction between abnormal loan growth and non-performing loans

The Debt-Equity Ratio Choice: Risk Sharing Instruments, A Viable Alternative

Evidence has been documented in the literature that the interest based debt financing system is experiencing continuous discomfort. The outcome of the 2008 global financial crisis has further create fresh vigor to the assertion. Also, these authors have submitted that debt and leveraging are the two major causes of financial instability in the present system. This paper claims that the existence of the interest-based debt regime is becoming less acceptable, as excessive debt can affect the whole economic system, even in a developed country like United States. From an economic viewpoint, therefore, by banning interest rate-based contracts and decreeing exchange contracts, Islamic financeinspires risk sharing and prohibits risk transfer, risk shedding, and risk shifting. The paper proposes risk sharing based Islamic financing as a suitable alternative to the interest based debt financing. This study concludes that risk-sharing finance has several benefits, especially its potential to minimize, if not circumvent, the debt prompted financial crises that have beset the world..Keywords :  Debt-Equity Ratio; Risk Sharing Instruments; Islamic Financ

Predicting the GDP of the new economy based on the human capital using neural network approach

Human capital has become important because knowledge is a critical ingredient for gaining competitive advantages, particularly in the New Economy era.It has been described as becoming the preeminent resource for creating economic wealth. To date, several studies have been conducted to determine the relationship between human capital and company performance.The relationship between human capital and economic growth has been explored.However, past literature reveals that artificial intelligence techniques have not been utilized in understanding the effect of human capital on economic growth.Artificial intelligence techniques such as neural networks have been successfully applied to business and financial problems.To this end, the neural networks approach was used to determine the impact of human capital on the New Economy.This paper discusses the results of the exploratory study for predicting demand for human capital. Data from 1971 to 1996 was collected for this study.The variables used for the prediction were based on Canadian’s Human Capital Measurement as suggested by Laroche and Merrette (2000).The exploratory study indicated that neural network is a potential approach for predicting the GDP based on human capital. In conjunction with neural network approach, statistical methods were also used to explain the relationships between variables in the study

Liquidity risk underlying debt financing and economic condition: A Panel data analysis of Islamic Bank in Malaysia

The objective of this paper is to analyze the determinants of Islamic bank liquidity risk in Malaysia with special focus on debt financing. Based on this objective, this study utilized unbalanced panel dataset of 17 Islamic banks in Malaysia over the period 1998-2012.The method use is this study is panel data regression analysis. The results show that the level of capital is significant with the liquidity risk.For debt financing variable, the results signify that the higher volatility of debt financing modes will cause some liquidity risk.For macroeconomic condition, the result shows that impact of inflation rate could decrease the nominal value deposits in Islamic bank and finally the relationship of liquidity risk and Islamic bank deposit rate is negative.The implication of this study is that when the Islamic banks consider on their liquidity risk management, the have to look upon the behaviour of debt financing, inflation rate and Islamic bank deposit rate

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Human resource development (HRD): Technology and ICT adoption in industrial sector, Malaysia

The roles of information and communication technology (ICT) in boosting productivity and in promoting human resource development cannot be underestimated. Small and medium enterprises, in particular, have to grapple with the technological innovations that challenge operations, efficiency, and productivity vis-à-vis human resource capabilities.As in many countries, Malaysia has adopted ICT in various sectors such as manufacturing, banking, finance, and telecommunication, to name a few.These sectors utilize knowledge workers that have technological and ICT skills for competitive advantage.In line with the 9th Malaysia Plan (2006-2010), it was reported that investment from the technology and ICT sector are expected to be the main driver for the manufacturing sector’s overall growth, which in turn, could contribute to greater export and create more employment opportunities.This research assessed the development of human resources based on the application of ICT in the industrial sector in Malaysia.This was a field study in the form of a survey research using a random sample of organizations representing the industrial and government sectors in Malaysia. A total of 706 firms were selected in which questionnaires were sent and 120 usable returns were received representing a 17% response.The distribution of the sample suggests a high concentration of the ICT industry and high technology industry in the central and northern regions of Malaysia.Results of the study showed a moderate number of employees using IT were present in the organizations with more than half of the sample reported having employees with IT skills.There was also a low degree of technology and IT adoption among the sample with only half invested in technology and/or IT. Finally, the findings indicated that ICT adoption had a strong significant impact on the company’s productivity and quality of services