Browsing by Author "Cooray, TMJA"

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item: Thesis-Full-text
Analysing the significant factors which are affected to the selection of higher education opportunities in the private institutions
Waidyasekara, VT; Cooray, TMJA
Gaining higher education is vital for a person to find more lucrative careers pursuing a better professional and personal life growth. In the modern world today, private education institutes play an imperative and a competitive role by opening up many more opportunities for those who are seeking higher education aspirations. At such a turning point of a life, the determinants considered by the students when selecting higher education opportunities in the private institutions are worth to study. The study was carried out with the objectives of identifying the potential students for a particular programme of a private higher education institute in Sri Lanka and to identifying the salient factors which are considered by the students when selecting higher education opportunities in the private institutions. Due to the unavailability of the secondary data source, primary data was collected through a questionnaire survey and descriptive analysis has been carried out to check the relationship between the response variables and other explanatory variables. Due to the availability of colliniarity between explanatory variables and as those variables, factor analysis has been carried out. Hypothesis testing has been carried out for ordinal data using Kruskal Wallis test. As per the major findings, higher studies are more preferred by male students those who have done mathematics for their Advanced Level studies. The main sources, referred for gathering course information are friends and the websites. With reference to the education background and occupation of the respondents’ parents, the most have advanced level qualification, most fathers are government servants and businessmen and mothers are house wives. Parents are the main source of financial contributor for the higher studies of their children. Majority of the respondents live and have studied at Colombo and have gone to national schools. According to the factor analysis, Study Programme, Influence, Accommodation and Attitudes are the determinants considered by students those who are pursuing higher education. According to the Kruskal Wallis test Study Programme depends on gender, programme type (Degree, Advanced Diploma, Diploma, and Certificate) and programme area (Engineering, Medicine, Physical Science, Bio Science, Management and Arts). The Influence depends on programme type and programme area. Accommodation depends on gender, programme type, programme area and type of school. Attitudes depend on programme type, programme area, education of the mothers, district of the school and type of the school.
item: Thesis-Full-text
Analysis of the relationship between exchange rate, inflation rate and gold price of Sri Lanka:
Karunawardana, KMEM; Cooray, TMJA
Recent records show that the price of gold has been rising at a higher rate than in the past. This has been shown to be true for Sri Lankan gold prices as well. In this study an attempt has been made to develop a forecasting model for gold price and to examine the relationship between selected factors, that is the inflation rate, exchange rate and gold price. The data was mined from the World Gold Council and the Central Bank of Sri Lanka. The sample data of gold price were gathered from 2007 January to 2016 March in the currency of US dollars per troy ounce. It was converted into Sri Lankan rupees per 22 carat. Data until December 2015 were used to build the ARIMA model and the VEC model remainder was used to forecast the gold price and to check the accuracy of the model. Box-Jenkins, Auto Regressive Integrated Moving Average methodology (ARIMA) has been used to developed the model 𝐷[𝐿𝑛[𝐺𝑂𝐿𝐷 𝑃𝑅𝐼𝐶𝐸]]; with terms AR (3) and MA(3) and to forecast the future gold price. The MAPE value of fitted data in the appropriate model is 9.4%. To identify the relationship with gold price, inflation rate and exchange rate, quarter value data of all three factors were used. Two models were developed by based on the minimum AIC and the minimum SIC values. Firstly, the stationarity of the data is checked through the Augmented Dickey Fuller test and then the Johansen co-integration test and the Vector error correction model (VECM) are employed for analysis. The results of the Johansen co-integration test revealed that exchange and inflation rates are co-integrated with the gold price that led to run VECM. The VEC model developed for minimum AIC value provides evidence for the existence of long run and short run relationships between the gold prices, the exchange rate and the inflation rate and the model developed for minimum SIC value as well. The model developed based on minimum SIC value is rejected since the existence of serial correlation. The speed of adjustment to equilibrium is 12.1%, the model explains the gold price of the current quarter as 69.3% of the gold price of the previous quarter, and the exchange and inflation rates in the VEC model developed based on minimum AIC value. The MAPE value of fitted data from appropriate VEC model is 6.36%. When forecasting time period is increasing the percentage error in ARIMA model is higher than the percentage error increasing in appropriate VEC model. According to the mean absolute percentage error as forecasting accuracy measure the study concluded that the VEC model is more appropriate fitted model to forecast the gold price in Sri Lanka than the fitted ARIMA model.
item: Conference-Extended-Abstract
Anlysis and forecasting of multiple seasonal time series models
(2007) Cooray, TMJA
Time series may contain multiple seasonal cycles of different lengths. There are several notable features in Figure 1, reference to the hourly electricity demand in Sri Lanka, data are given in the Table lFirst, we observe that the daily cycles are not all the same, although it may reasonably be claimed that the cycles for Monday through Sunday are similar. A second feature of the data is that the underlying levels of the daily cycles may change from one week to the next, yet be highly correlated with the levels for the days immediately preceding. Thus, an effective time series model must be sufficiently flexible to capture these principal features without imposing too heavy computational or inferential burdens. The goal of this paper is to introduce a new procedure that uses innovation ARIMA models to forecast time series with multiple seasonal patterns.
item: Thesis-Abstract
Application of MTO concept for existing ERP system
(2014-08-13) Wanasinghe, WMCP; Cooray, TMJA; Peiris, TSG
Companies, organizations and government agencies are all seeking to improve their customer value, efficiency and effectiveness, while there are many approaches to improving performance. It is the combination of management perspective, appropriate improvement methodology and visibility on production orders & order status in production and the ability to analyze relevant measures of performance that will yield best results. lr\ Relay's economy, having a good marketing strategy is not enough to meet organizational goals. So organizations are struggling to implement operational strategies, streamline operations, and deliver more value to their customers. MTO (make to order) strategy in ERP (Enterprises Resources Planning) was a decision of Textured Jersey board (reference Textured Jersey Board minutes September 2009) considering continues improvement. This research is discussed the existing approaches and MTO applications that are implemented in SAP ERP system. Also we were considered systems where some products are make-to-stock while another product line is make-to-order. We are also presented the rich and effective strategies for which a variety of cost and performance measures can be evaluated efficiently by analytical methods. This is also examined an approach to improving operational performance by calculating the "post order costing, improve order tractability & forecasting while addressing the relevant configurations in the SAP (ERP Software name) system on MTO strategy and aims to provide the MTO solution map based on the existing production processes at Textured Jersey. Further, the project is addressed the existing business 'pain points' (Annexure A) based on the complete Make-to-Order (MTO) process and evaluate how the SAP - MTO help organizations to measure, monitor, and manage business performance while addressing Key performance indicators (KPls) such as sales order projection profitability, on time delivery of the sales orders, total sales and profitability per sales order etc.
item: Thesis-Full-text
Application of queuing theory to enhance the operational efficiency of the bank
(2016-09-17) Hettiarachchi, AT; Cooray, TMJA
This study reviews the applications of queuing theory to the field of banking queue management problems. This review proposes a system of classification of queues in the banking sectors, which examined with the assistance of queuing models. The areas described in the literature are the common problems encountered in the queue management strategies in the banking industry. The goal is to identify the best effective method to reduce customer-waiting time at the bank to the maximum possible standard while improving the efficiency of the bank. Customer satisfaction is a concern to service industries as customers expect to get their service promptly. For a service industry like a bank, there is a need for efficient bank Teller scheduling system that takes into account recognizing various customers’ expectations. This study concentered on the single channel waiting line systems with poison arrivals and exponential service times in Bank of Ceylon, City office, Bank of Ceylon Kuliyapitiya and Bank of Ceylon Bingiriya. All above branches have separate queues for the separate counters. (Many lines)They use rule of thumb to open/close counters at the branches based on their experience.Consequent to our findings and calculations we have proved that having one line and many counters (One line) is effective than having many lines. Further, with respect to open/close of counters we have suggested queue probability tool. Queue probability is one of significant factor to determine to set up number of counters effectively.
item: Conference-Full-text
An approach of state space modelling for indirect tire pressure monitoring
(2005) Cooray, TMJA
In this paper, dynamical vehicle models and Time dependent State Space model have successfully been used to detect tire pressure losses(non observabilty). When the pressure is decreased in a tire, the corresponding wheel radius is reduced and the angular velocity increases. The basic idea behind this paper, is to indirectly estimate the wheel radius via secondary existing sensors. Two dynamical vehicle models, in which the relative wheel radius is included as model parameters, are formed. With these models any combination of pressure loss in the tires can be detected
item: Thesis-Abstract
An Approach to investigate the relationship between share prices and macroeconomic variables
(2014-12-12) Jayasundara, AN; Cooray, TMJA
With the development of the economy in Sri Lanka and low interest rate for savings influencing people to invest their money in other profitable areas. Therefore stock market is one of the good opportunities that can open the door for local investors as well as foreign investors to invest their money. This study examines the causal long run relationships among stock prices and macroeconomic variables and forecasting stock prices in an emerging stock market, the Colombo Stock Exchange (CSE). Data is used on four macroeconomic variables obtained by web site of Central Bank of Sri Lanka and the All Share Price Index (ASI) of the CSE obtained from Data Library CD published by the Colombo Stock Exchange for the period January 2003 to December, 2010. Johansen’s co-integration test, Granger Causality Test and econometrics techniques with regression analysis were used in the empirical analysis and indicate that there are long-run causal relationships among stock prices and macroeconomic variables where as Money Supply (M1) and Interest rate in Sri Lanka. These results indicate that stock prices can be predicted from certain macroeconomic variables. The above results have implications for investors, both domestic and international.
item: Thesis-Abstract
Business process re-engineering in a logistic operation
Dissanayake, CS; Cooray, TMJA
The development of the industrial age has seen a remarkable growth which has led to competition not of products but of the supply chains. A related problem such organisations face is the difficulty in identifying the most appropriate way of managing the operation in a cost effective and efficient for the organisation as a whole. The better way to solve such kinds of problems, is the use of Operations Research (OR) techniques. The purpose of this project is to use statistical techniques to solve operational problems and further optimise the model. Here an operational environment is used to apply this learning with the intension of gaining benefits in terms of cost savings and service improvement. \ Here two operating models (model A and model B) were studied in detail study, its pros and cons as well as problems that may arise were identified. Since the model needed to be cost effective, the main cost elements were identified and their impacts were quantified base on the past information and finally forecast figures were estimated. Based on all the key parameters, the final impacts ofthe models were derived along with the optimum inventory model and the feasibility ofthe model is also evaluated. Finally, the outcomes were evaluated for all the cost elements using the actual data of the two models and the best model has been concluded to be Model B since it is cost effective by 6.5% and also service oriented. At this point, deviations of cost due to inefficiencies in the operation were also identified where the main cause is due to poor inventory management. Therefore, could conclude that proper inventory management is essential in order to optimise model B and for it to be feasible. The inefficiencies were proposed to be solved as future projects. The difficulties faced during the study and limitations are also been discussed. provided such as identifying a better location to relocate an optimum distribution network Finally, recommendations the Regional DC (Distribution Centre) and to develop are to reduce the distribution cost
item: Thesis-Full-text
Casual relationship between construction activities & GDP growth in Sri Lanka
(2015-08-26) Athukorala, R; Cooray, TMJA
The construction industry plays a vital role in the socio economic development and national fiscals in any country. Usually it provides a considerable share towards the Gross Domestic Product (GDP) and Gross National Product (GNP) of the economy. Further it helps to bring lot of development goals for any country such as providing infrastructure, technology, machinery, engineering services and employment opportunities. Construction industry is a highly booming sub sector in Sri Lankan economy. The sector alone has contributed 6.6% in 2009 to 8.7% in 2013 towards the overall GDP. Therefore it has indicted a significant impact to the economy of the country. This study helps to understand mathematical relationships between construction industry and economy in an investor perspective and economic policy development standpoint. Also it helps to evaluate the structures of government policies, their effectiveness as well as direct and indirect impact of social wellbeing in the country. This study focuses on the causality relationship between the developments of construction activities and the GDP Growth in Sri Lanka. It describes as a country how construction activities have been responded to the trend of national economy and vice versa. Empirical data of economic indicators and construction index were used to determine the Granger Causality Test for the period of 1990 to 2013. Therefore, it checked the associations between national economic statistics and construction activates in Sri Lanka specially to identify unidirectional and bidirectional relationships among the variables as well as short term and long term relationships. The research reveals the Balance of Trade (BOT) has a relationship between previous year Gross Domestic Products (GDP) and a year before. Also it reveals that All Construction Cost Index (ACINDEX) has an impact on last three year GDP figures, Construction sector Gross Domestic Product (CGDP) figures and BOT. Therefore it can confirm a strong relationship between construction activities and economic growth in Sri Lanka.
item: Thesis-Abstract
CEnhanced camshift kalman filter for object tracking
(2015-11-27) Fernando, WSP; Cooray, TMJA
In this thesis an enhanced Cam-shift Kalman object tracking algorithm for video surveillance and object tracking was developed. And this new algorithm was based on a modified Cam-shift tracking algorithm and the Kalman filter. This modified Cam-Shift algorithm solves a major drawback in the classical Cam-Shift algorithm such that the search area for the next frame was optimized, so that the time taken to track the object was minimized. The classical Cam-Shift algorithm for tracking performs well under perfectly maintained conditions such as light condition and without partial occlusions that constitute a good tracking method. However, under different environment conditions and with occlusions the algorithm fails. To test the performance of the enhanced Cam-Shift algorithm color of the object was selected as the feature for identifying the object, and was compared with the performance of the classical Cam-Shift algorithm. Also mean-shift algorithm was also incorporated for the comparison. In order to enhance the performance and accuracy under cluttered environment, the presence of noise and occlusions Kalman filter was combined. When the object disappears from the scene partially or fully the algorithm is capable of tracking the object. The experimental results verifies the ability of the enhanced Cam-shift Kalman object tracking algorithm in comparison to the classical Cam-Shift, which can locate the target object more effectively.
item: Thesis-Abstract
Comparing the applicability of box-jenkins arima methodology and arch/garch methodology among real data sets
(2014-08-19) Ferdinandis, MGSMA; Cooray, TMJA; Malhardeen, MZM
The main objective of this research is to compare the applicability of Box-Jenkins ARIMA methodology and ARCH/GARCH methodology among two real data sets. This study addresses the question of how to analyze time series data, identify structures, explain behaviours, model the identified structures and using the insight gained, to analyze and forecast values for the specific time series. For the purpose of this study the time series data included, the total kurakkan yield obtained from the Census department of Sri Lanka and the Money series obtained from the International Financial Statistics data source of Central bank of Sri Lanka. Each of the time series has its own characteristics and different methodologies were needed to require a deeper understanding of the time series data. The analysis of time series constitutes an important area of statistics. The kurakkan yield data set consisted of a few missing values. Three different approaches namely deterministic, stochastic and state space method were used to estimate these missing values. Out of the three approaches the state space method gave the best estimates. Once the missing values were fitted The complete series was used to analyze and then forecast values. To build the models and perform the analysis a statistical software called "Minitab" and the software package called "E-views" was used. The best model obtained was a seasonal ARIMA model with 2 non-seasonal AR terms and 2 non-seasonal MA terms with one seasonal differencing. The model was used to forecast values and the accuracy measure MAPE was 1.65% for the ARIMA model fitted, which.was the minimum value of MAPE for all the en-bloc methods mentioned above. The errors of this model were independent and identically distributed and followed a normal distribution. The main difference between the two time series data sets used for this study is that the money series obtained is a high-volatile data series which includes heteroscedasticity. For this data series the ARIMA methodology cannot be used since the data will not become stationary to fit a model. Therefore the ARCH/GARCH methodology was used to deal with the money data series. To build models for this series the software package called "E-views" has been used. Different ARCH models and GARCH models were fitted to this data set and the parameters were chosen so that the kurtosis value was closer to three. The best model was, a logarithmic transformation of the money series with one GARCH term and no ARCH terms. This model yielded a kurtosis value of 3.09. The main model for this data set did not include any AR or MA terms. However a very large number of data points are required to model the series with AR and MA terms in the main model. iii
item: Thesis-Abstract
Computerized inventory control applications in operational research techniques
(5/12/2011) Dassanayake, A; Cooray, TMJA; Gamini, DDA
Operational Research (OR) is the use of advanced analytical techniques to improve decision making. OR is sense to make the best use of available resources. OR consistently delivers significant value strategic to tactical, top-line to bottom-line to the organizations and executives who use it. Organizations worldwide in business. the military, health care, and the public sector are realizing powerful benefits from Operational Research//Basically, OR models contained hard mathematical calculations such as matrices. differentiations, integrations, calculus, Lagrangian multipliers with very complex formulas. To find solutions for selected OR model, needed to memorized the final formulas or needed to have a good OR, Mathematical and Statistical theory background in order to derive final formulas. However, to achieve the final solutions, wants to passed lots of calculations and also it might take more time. It has to be carefully worked with numerical calculations to reached accurate answers in short time period, for handle the final decision. Therefore, to find accuracy solutions for selected OR model in short time period without having any theoretical background, it is important to have software.//There is a few number of Computerized Operational Research Applications are available; Such as Windows based TORA, Excel Spreadsheet templates, LINGO,QM and AMPL applications. By considering, OR models, there were no options to solve Inventory Control and Replacement & Maintenance models by using a software. Studying, Inventory Control and Replacement & Maintenance techniques and identified the requirements in each model//Designed software based on structured system analysis design method. To implemented, Microsoft Visual C++ 6.0 is a textual language used to create the required system. Test the models to verify the accuracy for each possibility with actual expected answer and computerized answer//The main advantage of this software is, user doesn't need to worry about the mathematical and statistical calculations and can be saved time and energy.
item: Thesis-Full-text
Daily profit maximization using linear programming techniques: Sapugaskanda
(2015-08-26) Rajapaksha, RKMM; Cooray, TMJA
The petroleum industry plays one of the most significant role in the energy market in Sri Lanka. The actual use of this source is limited by economical, technological and political reasons. Crude oil refining is an extremely complex and dynamic activity since the refinery itself works to maximize its profitability under the frame work of the organization. To model the LP Problem to the Crude Oil Refinery station in Sapugaskanda, Sri Lanka, the primary data was collected. The data was modeled and the Linear Programming (LP) method was used to get the optimum solution. The refinery produces 12 major petroleum products together with 24 intermediate streams. The commonly used and most profitable products are Gasoline, SBP and Diesel. For above 36 streams, the flow rates in Metric Ton (MT) per day were considered as decision variables. To maximize the profit, the product values were considered as positive and the raw material costs and operating costs were considered as negative. The TORA software was used to generate the optimum solution. The optimum result obtained showed a notable profit compared to the existing situation in the Oil Refinery Station, Sapugaskanda. The operational difficulties, assumptions, suggestions and further recommendations were discussed.
item: Thesis-Abstract
Design models for the peak values of daily, day and night, load forecasting for the power system in Sri Lanka
(3/29/2011) Cooray, TMJA; Priyanka, BAS
Today, most of the countries use forecasting techniques to predict their future demand in electricity. But at present there is no such technique used in Sri Lanka except for the market forecast report which is prepared by the Resource Management Associates Pvt. Ltd. regarding the load forecasting. A country like Sri Lanka can not always depend on hydro-power. If we have an idea of the future demand we can plan and take necessary action. In this thesis, I try to identify the best model for forecasting day and night peak values of electricity demand in Sri Lanka, for week-days as well as week-ends. Here I use more popular time-series techniques such as Double Exponential Smoothing and ARIMA Modeling. I carried out the research by using two year data of the peak values of electricity demand in day and night of Sri Lanka. With the use of MINITAB package for double exponential smoothing, I tried all possible models and selected the best. After testing the adequacy of the fitted model. I could forecast for last three periods. Secondly, using Box-Jenkins ARIMA techniques, 1 tried all possible models and selected the best. Here also check the model adequacy and forecast the last three values using the selected model. Finally comparing both techniques, I selected the best model for a particular day- day time and night time
item: Thesis-Full-text
Develop a stochastic inventory control model: a case study in rubber manufacturing industry
Wasala, WAB; Cooray, TMJA
The purpose of this research to develop a system for the evaluating and defining of inventory management parameters ofwidely using Purchasing models in polymer rubber manufacturing industry. This paper investigates the application of inventory models in determining stock control in a polymer rubber manufacturing organization. Developing of common data entering and analyzing software like MS excel to perform the task was particularly interested by the research. The paperstarts with an overview ofmain types of purchasing models and also provides a user friendly system for the managing ofthe stock parameters of those models. It shows that there are many opportunities for using descriptive, predictive and prescriptive approaches in all areas of purchasing models by using commonly used software to apply real life situation in practical industrial level. The models were selected by focusing on the actual function from a purely operational and execution perspective in the organizational level for a strategic decision making. Introduced system was featured for easy and user friendly integration of computer aided inventory management which focused in the area ofInventory control and generates the stock management parameters easily. It can be concluded that future researches needs to explore the purchasing models evaluation systems related to enterprise resources planning in practical level which can be applied in a real life situation of an organization. It also can be acknowledged that while using empirical results to inform and improve models has advantages, but there are also drawbacks, which relate to the value, the practical relevance and the generalizability ofthe modelling plus software based approaches.
item: Thesis-Full-text
Developing the existing queuing system for the banking sector using queuing simulations
(2016-01-16) De SIlva, WMH; Cooray, TMJA
Waiting lines occur in many business operations as well as in everyday life. Most service systems, such as fast food restaurants, Banks, gasoline stations, and technical support telephone hotlines involve customer waiting. In these systems customers arrive at random times and service times are rarely predictable. The important issue in designing such systems involves the tradeoff between customer waiting time and system cost, usually determined by number of servers. The analysis of waiting lines, called queuing theory, applies to any situations which customers arrive to the system wait and receive service. The People’s Bank is one of the important governmental banks that plays an important role in the Sri Lankan economy. The customers dealing with servers of general transaction section of Peoples Bank in metropolitan areas suffer and complain from the long times they spend in the bank to acquire their needed service. This happens especially in specific days in each week. This problem was the main motive to perform this study. However, more queuing problems in the bank’s branch have been discovered through the study. The main objectives of the study are to investigate the services delivery system at the people’s Bank in metropolitan areas, and to propose a more efficient system. Analytical methods and simulation methods are used to analyze the queuing systems. Simulation analysis has been used to model the existing queuing system and to enhance the system by using computer simulations of Arena 12.0 statistical software. As the conclusion of this project new working schedule for counters in different days of weeks are presented and find out how arrangement of queues should change.
item: Conference-Full-text
Development of an Algorithm to find the Optimum Dredging Region for Short Term Scheduling
(2014-07-11) Fernando, JMMP; Cooray, TMJA; Dissanayake, DMDOK
This research focuses on the short-term scheduling of the vertical slicing method applied dredge mine sites. An algorithm was developed to outline the region to mine, when the block model, optimum pit limit, topography limit and the market demand are given. The algorithm is based on the concepts. of dynamic programming and zero-one integer programming to avoid repetitive solutions and memorize the previous stage outcome for the next stage process. It utilizes 3D matrix to store previous and next stage solutions with three integers representation for "possible future mining", "already mined" and "never mine" conditions. The algorithm is used on 2D resource block model, which is obtained by pre-processing optimized 3D block model to 2D plan-view block model. The developed algorithm was faster and required less data storage over the conventional method due to exclusion of repetitive solutions in the processing.
item: Conference-Full-text
Development of an algorithm to find the optimum dredging region for short term scheduling
(Department of Earth Resources Engineering, 2013-06) Fernando, JMMP; Cooray, TMJA; Dissanayake, DMDOK; Hemalal, PVA
This research focuses on the short-term scheduling of the vertical slicing method applied dredge mine sites. An algorithm was developed to outline the region to mine, when the block model, optimum pit limit, topography limit and the market demand are given. The algorithm is based on the concepts, of dynamic programming and zero-one integer programming to avoid repetitive solutions and memorize the previous stage outcome for the next stage process. It utilizes 3D matrix to store previous and next stage solutions with three integers representation for "possible future mining", "already mined" and "never mine" conditions. The algorithm is used on 2D resource block model, which is obtained by pre-processing optimized 3D block model to 2D plan-view block model. The developed algorithm was faster and required less data storage over the conventional method due to exclusion of repetitive solutions in the processing.
item: Thesis-Abstract
Econometric analysis of value added tax with Colombo consumer price index in Sri Lanka
(2014-08-14) Kodikara, PT; Cooray, TMJA
Value Added Tax is one of the major type of tax currently practiced in Sri Lanka. This study focuses on the determinants of the Value Added Tax (VAT) and Colombo Consumer Price Index (CCPI) and its future forecasts, which could be used as a guidance of monetary policy decisions. The data used for the study are the VAT data obtained from the Department of Inland Revenue and CCPI data obtained from the Central Bank of Sri Lanka for the period of January 2004 to December 2010. It includes monthly data point in each index. VAT is a tax on domestic consumption of goods and services. The goods imported into Sri Lanka and goods and services supplied within the territorial limits of Sri Lanka are the subject matter of this tax. It is a multi stage tax levied on the incremental value at every stage in the production and distribution chain of goods and services. The tax is borne by the final or the ultimate consumer of goods or services. Therefore, VAT revenue directly affects the price of the goods and services. Inflation is simply the percentage change of CCPI which is the official price index in the country. It measures the changes through time in the price level of consumer goods and services purchased by households in Sri Lanka. This study is significant, because there is no previous analysis about VAT with CCPI in Sri Lanka. Value added Tax is one of the major type of tax currently used to collect taxes in Sri Lanka. V A T is a general consumption tax assessed on the value added to goods and services. Therefore, it is very important to study about effect of goods and services prices to VAT revenue. Inflation is simply the percentage change of CCPI. Thus the intention is to the existing forecasting method change of VAT revenue in Sri Lanka by using CCPI. Forecasting was performed using the time series techniques and Econometrics approaches. This study is to find the relationship between VAT and CCPI and fit a suitable model to forecast monthly V A T Revenue in Sri Lanka, which would be used as a guidance of monetary policy decisions. Time series analysis was used to analysis the VAT data. CCPI data and econometrics modeling approach considers the impact of CCPI factor in forecasting VAT for the future. Then Ganger Causality test were applied to find the direction of causality between V A T and CCPI. Causality between VAT to CCPI. Further co-integration test was used to identify linear combination of the integrated series and best define the long run equilibrium relationships between the variables. Since both VAT and CCPI series are non stationary order one, Therefore, Vector Error Correction Model (VECM) was formulated, and it was proved that the changes of price level of CCPI were strongly affected by the VAT. Therefore, in order to assess the significant interrelationship VECM (Vector Error Correction Model) is used to forecast V A T less than 5% Mean Absolute Percentage Error (MAPE). It was found through this study that the CCPI is an influential factor on V A T revenue in Sri Lanka. The developed VEC model can be used to predict V A T revenue with less than 5% MAPE.
item: Thesis-Abstract
Effectiveness of recursive estimation of time series analysis and forecasting
(6/21/2011) Cooray, TMJA; Indralingam, M
This study is about practical forecasting and analysis of time series, to investigate the effectiveness of recursive estimation of time series analysis and forecasting performance for real data sets. It addresses the question of how to analyze time series data, identify structure, explain observed behavior, modeling those structure and how to use insight gained from the analysis to make informed forecasts. For the purpose of the study total production of paddy and total demand of electricity in Sri Lanka were used. Those values were obtained from the Annual Bulletin, published. by the Central Bank of Sri Lanka. The thesis is organised into two parts. The first part is a course of methods and theory. Time series modelling concepts are described with 'abstract' definitions related to actual time series to give empirical meaning and facilitate understanding. Formal algorithms are developed and methods are applied to analyze data. Two detailed case studies are presented, illustrating the practicalities that arise in time series analysis forecasting. The second part is a course of applied time series analysis and forecasting. It shows how to build the models and perform the analyses shownin the first part using the our own software called "Space" and another downdable software called the "BATS" application program The first few chapters are concerned with sing theoretical aspects of en-bloc time series models such as the seasonal decomposition method exponential smoothing method, Winter's seasonal method, and the ARIMA methodology to describe the' behaviour of the data series. Even though fairly general, these model do not account for the uncertainties due to the specific choice of trend / seasonal! level. The main drawbacks in this study are its lack of accessing model uncertainties, when choosing the recursive estimation of time series models based on the Kalman filter. Therefore we used an approach -that incorporates all uncertainties involved in the time series modelling simultaneously. Dynamic state space models provided an excellent basis for constructing and forecasting models for a number of reasons. In particular recursive estimation of time series based on the use of discounting techniques proved to be extremely useful in practice. Many practitioners have a natural feel for the discounting concept, and furthermore when one discounting factor has been specified, the standard technique may be utilised. in addition to that the Kalman filter based on state space form and Bayesian models can be used to analyse the incomplete data set using EM algorithms. The last two chapters were devoted for empirical evaluation of data series in order to investigate the effectiveness of recursive estimation of time series. According to the forecast performance of recursive time series models are much more accurate than the en-bloc models. This means that the mean percentage error (MAP E) recursive estimation oftime series model is relatively small (nearly 0.5%) so that this method gives higher degrees of accuracy. The recursive estimation of time series models can play an important role of time series modelling. However, these procedures are based on the predictor-corrector type algorithms. Hence without identifying the appropriate structure the variation of parameters could be implemented in contrast to "en-bloc" procedure s which could be used only after assuming the specific type of parameter variation