An economic reappraisal of the Melamchi water supply project - Kathmandu,Nepal

This paper examines whether the benefits of the Melamchi water supply project in Nepal are likely to exceed its costs, assuming that high-quality municipal water services can be delivered to households and firms in the urbanized part of the Kathmandu Valley. Monte Carlo simulations are used to explore the sensitivity of the net present value and economic internal rate of return calculations to a wide range of assumptions and input parameters. We find that extreme assumptions are not required to generate large differences in economic feasibility; quite plausible differences in the values of some key parameters can lead to large differences in the economic attractiveness of the project. The results reveal that the three most important influences on net present value and economic internal rate of return are: (i) the discount rate and discounting procedure; (ii) the magnitude of monthly benefits for households connected to the new water system; and (iii) the annual growth rate in monthly benefits of connected households after the project comes on line. Our contribution lies in illustrating, with an actual case study in a developing country, the degree to which cost-benefit calculations of large infrastructure projects are influenced by key economic modeling assumptions and input parameters.JEL Classification: H42, H43, H54, Q25, Q56 Correspondence to: Dale WhittingtonWe would especially like to thank Keiichi Tamaki (ADB) and Ian Hill (Acres International) for their guidance and assistance with this project. We would also like to thank the following individuals for their help during our mission to Kathmandu in May, 2003: Richard W. A. Vokes, Kathie M. Julian, Raj Kumar Malla, Madan Shankar Shrestha, Suman Prasad Sharma and Noor Kumar Tamrakar.     

Forecasting technology diffusion: a new generalisation of the logistic model

The present research proposes a new generalisation of the logistic model aiming at technology diffusion forecasting. Regarding criticisms and failures reported in the literature to apply logistic function for long-term forecasting, in our work we focused on short-term accuracy of forecast. To formulate the model, based on mathematical approximation, at first the differential equation governing the diffusion process is found and then by solving the derived differential equation, the forecast function is obtained. In all steps, mathematical tools from numerical analysis are used. We compared the New Generalized Logistic Model with eight of the most renowned models in the literature. The model led to more accurate fits and forecasts than those obtained from other models we applied for comparison.     

A new energy model to capture the behavior of energy price processes

Owing to the vague fluctuation of energy prices from time to time, a new energy model, which considers both the mean-reverting behavior and the long memory property, is proposed in this paper. Since the problem of estimating parameters, in discrete time for this model, plays a central role in forecast inference, the problem of estimating the unknown parameters has been dealt with for the fractional Ornstein–Uhlenbeck process observed discretely. The asymptotic properties of these estimates are also provided. The numerical simulation results confirm the theoretical analysis and show that our method is effective. To show how to apply our approach in realistic contexts, an empirical study of energy in China, namely Daqing crude oil, is presented. The empirical results seem reasonable when compared to the real data.     

Pseudolikelihood estimation of the stochastic frontier model

Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it has been applied using maximum likelihood (ML) estimation. An alternative approach, pseudolikelihood (PL) estimation, which decouples estimation of the error component structure and the production frontier, has been adopted in both the non-parametric and panel data settings. To date, no formal comparison has yet to be conducted comparing these methods in a standard, parametric cross-sectional framework. We produce a comparison of these two competing methods using Monte Carlo simulations. Our results indicate that PL estimation enjoys almost identical performance to ML estimation across a range of scenarios and performance metrics, and for certain metrics, outperforms ML estimation when the distribution of inefficiency is incorrectly specified.     

A fuzzy multiple criteria comparison of technology forecasting methods for predicting the new materials development

New materials have been recognized as key drivers for corporate profitability and growth in today's fast changing environments. To predict correctly the development of the new materials becomes a critical issue. However, little has been done in discussing the selection of technology forecasting methods for the new materials development. Accordingly, this study adopted the fuzzy AHP method to obtain professional's opinions on this issue. The efforts result in seven evaluation criteria with one, the “data validity” having the highest weight, followed by “method adaptability” and “technology predictability”. Delphi method and case study method are the two most applicable technology forecasting methods for predicting the new materials development.     

A technology replacement model with variable market potential — An empirical study of CRT and LCD TV

The rapidly changing economic environment and increasingly fierce competition indicate that companies must innovate in both their products and marketing strategies if they are to continue to flourish. Specifically, the ability to accurately predict the demand for products is crucial when firms decide to allocate their resources, especially in the fast moving high technology industries, where there is very high investment in R&D and production facilities. This study establishes a forecast model for technology replacement based on the diffusion model with population growth used for the variable market potential. The proposed model is then applied to investigate the CRT and LCD TV market.The results suggest that the new model is more accurate than the constant market potential model in fitting and forecasting performance. Consumers who purchase a TV for the first time are likely more attracted to LCD TV rather than CRT TV. As for those individuals who already own a CRT TV, the attraction is not strong enough to encourage them to replace their current CRT TV with a new LCD TV. Moreover, it is noted that the falling price of LCD TV is an essential factor in encouraging purchases.     

The suitability of technology forecasting/foresight methods for decision systems and strategy: A Japanese view

This paper evaluates technology forecasting and foresight (TF/F) methods in relation to users' decision systems for science and technology (S&T) strategies. As TF/F is an aid to decisions for attaining S&T goals, we examine the serviceability or suitability and acceptability of the methods and outcomes of TF/F for decision systems and S&T strategies. The focus is on extrapolation and Delphi methods because they are so widely used in technology forecasting (TFC). Based on the complaint analysis of TFC that revealed inaccuracy as the most serious obstacle to its acceptance, this paper especially analyses the meaning of accuracy. Learning from the experiences of TFC, the suitability of technology foresight (TFS) to cognitive structures in users' decisions is discussed. Finally, some lessons from TFC are presented for TFS.     

Decomposition of new venture growth into firm age,survey period and vintage effects

Firm data are accumulated on a yearly basis. In view of the linear relationship of firm age?+?foundation year?=?survey year, the fluctuations of firm data classified by age and period cannot be decomposed into age, period and cohort (foundation year) effects. Three decomposition methods are briefly reviewed and applied to Japanese data on new ventures founded since 1995. Regarding sales and employment growth, the age effect is the largest with a downward trend, and the cohort effect is negligible. Regarding labour productivity, the age effect indicates upward movements, and the cohort effect is negligible. The reason of the negligible cohort effect is discussed.     

Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management

Significant second-moment transmission effects and obvious time-varying patterns of correlation coefficients among major equity and currency markets in the US, Japan and the UK are found to exist. Such observations inspire the time-varying setting of dynamic conditional correlation coefficients in MGARCH models. On the other hand, the multivariate Student-t distribution is suitable for analysing the visible leptokurtosis that is common in financial markets. Both are important for international portfolio risk management. Thus, a comparison on the hedging efficiency of hypothetical portfolios consisting of stock and currency future positions is conducted in order to justify the multivariate Student-t distribution based on the DCC-MGARCH model.     

A global economic model to assess the cost-effectiveness of new treatments for advanced breast cancer in Canada

Objective Considering the increasing number of treatment options for metastatic breast cancer (MBC), it is important to develop high-quality methods to assess the cost-effectiveness of new anti-cancer drugs. This study aims to develop a global economic model that could be used as a benchmark for the economic evaluation of new therapies for MBC.

Methods The Global Pharmacoeconomics of Metastatic Breast Cancer (GPMBC) model is a Markov model that was constructed to estimate the incremental cost per quality-adjusted life years (QALY) of new treatments for MBC from a Canadian healthcare system perspective over a lifetime horizon. Specific parameters included in the model are cost of drug treatment, survival outcomes, and incidence of treatment-related adverse events (AEs). Global parameters are patient characteristics, health states utilities, disutilities, and costs associated with treatment-related AEs, as well as costs associated with drug administration, medical follow-up, and end-of-life care. The GPMBC model was tested and validated in a specific context, by assessing the cost-effectiveness of lapatinib plus letrozole compared with other widely used first-line therapies for post-menopausal women with hormone receptor-positive (HR+) and epidermal growth factor receptor 2-positive (HER2+) MBC.

Results When tested, the GPMBC model led to incremental cost-utility ratios of CA$131 811 per QALY, CA$56 211 per QALY, and CA$102 477 per QALY for the comparison of lapatinib plus letrozole vs letrozole alone, trastuzumab plus anastrozole, and anastrozole alone, respectively. Results of the model testing were quite similar to those obtained by Delea et al., who also assessed the cost-effectiveness of lapatinib in combination with letrozole in HR+/HER2?+?MBC in Canada, thus suggesting that the GPMBC model can replicate results of well-conducted economic evaluations.

Conclusions The GPMBC model can be very valuable as it allows a quick and valid assessment of the cost-effectiveness of any new treatments for MBC in a Canadian context.     

Quantificational analysis and simulation of Technical Barriers to Trade with two country model

The Technical Barriers to Trade （TBT） is an important problem faced to the export of China. Based on the number differences of TBT notifications between countries, we propose the concept and computational method of the technical barrier coefficient. By means of price-production and price-demand functions, a trade model with a developed country and a developing country is designed. The available trade policies such as technical barriers, tariffs and export subsidies are simulated and analyzed. According to the simulation results, several trade strategies to come over technical barriers are suggested. These suggestions were provided to several export enterprises for their export strategy design.     

Prediction of acute and chronic complications by a new computer simulation model for type 1 and type 2 diabetes: the Diabetes Mel l it us Model (DMM)

Summary

An epidemiological simulation model for patients with type 1 and type 2 diabetes (the Diabetes Mellitus Model (DMM)) was developed based on published clinical and observational data and expert estimations, for prediction of short- and long-term outcomes in defined patient cohorts. A computer program was developed with an interface for definition of patient cohorts and for results display. Patient cohorts can be user-defined by gender, age, duration and type of diabetes, glycosylated haemoglobin, blood pressure, albumin excretion and therapy. Based on risk

equations and current risk variable levels, the DMM simulates complications over 10 years (hypoglycaemia; retinopathy; blindness; microalbuminuria and macroalbuminuria; end-stage renal disease; neuropathy; amputation; diabetic foot syndrome; myocardial infarction; stroke; angina pectoris; heart failure; and death). The DMM is suitable for simulation of complications and for estimation of clinical implications of various diabetes care strategies, and may be particularly valuable in lieu of long-term clinical trial data.