Estimating short and long-term residential demand for electricity: New evidence from Sri Lanka

This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, -0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country.

Demand for electricity: evidence of cointegration and causality from Sri Lanka

This study examines the cointegration and causality relationship between the demand for residential electricity and real income, average real electricity prices, real kerosene prices and real gas prices using annual data for the period, 1960-2007 in Sri Lanka. Error correction (EC) techniques and the Granger-causality (GC) approaches are employed. The long run income elasticity of demand, price elasticity of demand and kerosene price were estimated to be 0.78, -0.62, and 0.14 respectively. The short run elasticities for the same variables were 0.32, -0.16 and 0.10 respectively. The GC results detect bi-directional causality between electricity consumption and real income as well as electricity prices and its consumption. This suggests that these variables are determined jointly. Furthermore, one-way causality running from kerosene price to electricity demand was also found.Electricity demand, causality, cointegration analysis

Why do policy decision-makers opt for command and control environmental regulation? An economic analysis with special reference to Sri Lanka

This chapter examines why policy decision-makers opt for command and control environmental regulation despite the availability of a plethora of market-based instruments which are more efficient and cost-effective. Interestingly, Sri Lanka has adopted a wholly command and control system, during both the pre and post liberalisation economic policies. This chapter first examines the merits and demerits of command and control and market-based approaches and then looks at Sri Lanka’s extensive environmental regulatory framework. The chapter then examines the likely reasons as to why the country has gone down the path of inflexible regulatory measures and has become entrenched in them. The various hypotheses are discussed and empirical evidence is provided. The chapter also discusses the consequences of an environmentally slack economy and policy implications stemming from adopting a wholly regulatory approach. The chapter concludes with a discussion of the main results.Command and control vs market-based instruments, Environmental and health effects, Economic analysis, Policy implications

The Iron-Type Nitrile Hydratase Activator Protein Is A GTPase

The Fe-type nitrile hydratase activator protein from Rhodococcus equi TG328-2 (ReNHase TG328-2) was successfully expressed and purified. Sequence analysis and homology modeling suggest that it is a G3E P-loop guanosine triphosphatase (GTPase) within the COG0523 subfamily. Kinetic studies revealed that the Fe-type activator protein is capable of hydrolyzing GTP to GDP with a kcat value of 1.2 × 10−3 s−1 and a Km value of 40 μM in the presence of 5 mM MgCl2 in 50 mM 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid at a pH of 8.0. The addition of divalent metal ions, such as Co(II), which binds to the ReNHase TG328-2 activator protein with a Kd of 2.9 μM, accelerated the rate of GTP hydrolysis, suggesting that GTP hydrolysis is potentially connected to the proposed metal chaperone function of the ReNHase TG328-2 activator protein. Circular dichroism data reveal a significant conformational change upon the addition of GTP, which may be linked to the interconnectivity of the cofactor binding sites, resulting in an activator protein that can be recognized and can bind to the NHase α-subunit. A combination of these data establishes, for the first time, that the ReNHase TG328-2 activator protein falls into the COG0523 subfamily of G3E P-loop GTPases, many of which play a role in metal homeostasis processes

The Alpha-Activator Complex, Cellular Maturation, and Catalytic Mechanism of Iron-Type Nitrile Hydratase

In industry, chemicals are typically synthesized through catalytically accelerated chemical processes. The use of biocatalysts is an increasingly important trend in achieving environmentally friendly chemical production processes. Nitrile Hydratases (NHases) are well-known biocatalysts that are used by several manufacturers such as Mitsubishi Rayon Corporation and Lonza for the conversion of acrylonitrile to acrylamide and 3-cyanopyridine to nicotinamide, respectively. Amides, in general, are used in polymer preparation, adhesive manufacturing, and the paper industry. Refrigeration is needed in the enzymatic hydration process on the industrial scale to maintain a low reaction temperature to stabilize the NHase enzyme. The use of whole cells instead of purified enzyme is one way to overcome this stability issue. However, the permeability of nitriles across the bacterial plasma membrane and cell wall is an important issue in order to get nitrile substrates into the cell and amide products excreted. The presence of unwanted enzymes in whole cells that can interfere with NHase activity, raw material, or product inhibition are also important considerations. Despite these issues, NHase shows great promise as a biocatalyst and, as a more detailed understanding of their catalytic mechanism and biological assembly processes emerge, improved biocatalyst designs that are more efficient, stable, and selective will advance their industrial use. The goal of the dissertation is to: study the formation of Fe-Type α(ɛ) protein complex, investigate the cellular maturation of Fe-Type nitrile hydratase, and discover intermediates along the catalytic cycle of NHases in-order to gain additional insight into the bio-assembly and catalytic mechanism of NHase enzymes

Morphmetric Analysis of Randenigala Reservoir catchment using GIS

Morphometric techniques play a major role in addressing the quantitative description of the geometry of thedrainage basins and its network. This helps in characterizing the drainage network, comparing thecharacteristics and examining the effect of lithology, rock structure and rainfall. The study focuses onanalysis of morphometric features of Randenigala reservoir catchment based on available digital data usingGIS.River Mahaweli was dammed closer to MinepeAnicut to build Randenigala reservoir with the elevation of160 m to 240 m (7 8 to 7 14N and 80 48 to 80 49 E). The capacity is 861 MCM and catchmentcomprise of 448 km2 in the Kandy and Nuwara-Eliya districts. The elevation of the catchment ranges from240 m to 2500 m. Method of Horton and Strahler (1945) was used to rank the stream segments. The streamnumbers were entered into the table and other analyses based on the mathematical formulas. The resultsindicated that the catchment area was 448.9 km2, perimeter 111.24 km, mean slope 36.8, axial length 30.5km, basin width 14.72 km, form factor 0.48, compactness factor 1.48, circulatory ratio 0.46, elongation ratio0.78, orders of stream network indicated, 1315 of first orders, 314 of 2nd, 72 of 3rd, 15 of 4th, 3 of 5th, 1 of 6thand one seventh order stream. The stream frequency and drainage density were 3.83 (no. of streams /km2)and 2.43 (km/km2). Bifurcation ratio was 3.65 and length of overland flow was 0.21 km. These findings areuseful in determining the effect of catchment characteristics such as size, shape, slope of the catchment anddistribution of stream network.KEYWORDS: Morphometric features, GIS, Catchment characteristic

Employee Satisfaction of Academics in Sri Lanka: A Logistic Regression Approach

This study has mainly focused on the use of multinomial logistic regression in predicting employee satisfaction of the academics in Sri Lankan universities A questionnaire was used to gather data from acdemics and it is prepared to collect demographic data and eight main factors Demographic factors were analyzed with multinomial logistic regression and it resulted in three elements namely sector salary and gender Before examining the main factors in the questionnaire a reliability analysis was done Factors were analyzed with multinomial logistic regression and resulted in different models and the best model out of all is presented in this paper By comparing the models with R-squared values goodness-of-fit statistics and residuals the best model was obtained This study revealed thatfitting of the abilities and knowledge with the job ability to use the full potential in work superior behavior and freedom are significant factors in predicting employee satisfaction of academics in Sri Lankan universitie

Forecasting Population Changes and Service Requirements in the Regions: A Study of Two Regional Councils in Queensland, Australia

Forecasting population growth to meet the service needs of a growing population is a vexed issue. The task of providing essential services becomes even more difficult when future population growth forecasts are unavailable or unreliable. The aim of this paper is to identify the main methods used in population forecasting and thereby select an approach to demonstrate that such forecasting can be undertaken with certainly and transparency, barring exogenous events. We then use the population forecasts to plan for service needs that arise from changes in population in the future. Interestingly, although there are techniques available to forecast such future population changes and much of this forecasting occurs, such work remains somewhat clouded in mystery. We strive to rectify this situation by applying an approach that is verifiable, transparent, and easy to comprehend. For this purpose we select two regional councils in Queensland, Australia. The experience derived from forecasting shows that forecasts for service needs of larger populations are more easily and accurately derived than for smaller populations. Hence, there is some evidence, at least from a service provision point of view, to justify the benefits of council/municipality amalgamation in recent times in Australia and elsewhere. The methodology used in this paper for population forecasting and the provision of service needs based on such forecasts will be of particular interest to policy decision-makers and planners.Regional Population forecasting, service provision, Box-Jenkins model