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The purpose of this paper is to devise a simple but practical model to assist decision makers in evaluating the tariff stability of concession schemes.

To develop such a model necessitates the identification of parameters that could contribute to an increase or decline in investment return. With that a Monte‐Carlo‐based simulation model is devised to determine the probability that the tariff regime remains unchanged even when the identified risks do occur at the operational stage. Sensitivity analysis is performed to identify the most influential factors to investment return and tariff stability.

The results of the scenario indicate that the internal rate of return could be profoundly influenced by the risk factors which reaffirm the needs for a more comprehensive model for tariff stability evaluation.

Through the simulation model, a tariff stability indicator is derived and when integrated with the results of sensitivity analysis this could generate a weighted indicator for alternative tariff regimes for use in decision support systems.

With the aid of simulation techniques, decision makers can predict the impact of a range of possible market conditions and/or levels of demand on the investment return and hence the stability of the tariff regime.

The model could be extended to other types of public‐private partnerships schemes upon suitable adjustment

This study seeks to examine the effect of pricing as a marketing instrument to stimulate word‐of‐mouth (WOM) by comparing the influence of two pricing strategies (i.e. a low‐complexity vs a network‐effects tariff) on the referral behaviour.

Using customer data from a German mobile network operator (including information on customer characteristics, referral behaviour, and service usage), the authors develop a logit model.

Surprisingly, the results indicate that it is the low‐complexity tariff that increases the likelihood of referrals and leads to an overall higher referral activity. Despite the lower referral activity, however, the network‐effects tariff generates higher revenues.

The results show that companies can use pricing schemes to influence referral behaviour and strongly indicate the need of further research on manageable tools to stimulate word‐of‐mouth marketing.

The findings show not only that pricing has an impact on customers' referral behaviour but also that it is the low‐complexity tariffs that trigger referrals. Furthermore, the results underline the importance of considering the monetary value of referrals.

In contrast with many previously conducted studies on customer referrals, the paper explicitly analyses the impact of pricing on referral behaviour and empirically shows that firms are able to actively manage WOM among customers.

This study aims to price the risk contribution of general Takaful at the level of tariff cells, considering a spatial dependency framework.

Three different models, including a generalized linear model, a generalized linear mixed model (GLMM) and a spatial generalized linear mixed model (SGLMM), according to the actuarial modeling of general Takaful, are used to price pure risk contribution (PRC).

The results reveal that the SGLMM yields more accurate predictions of the PRC compared to the other models, emphasizing the significance of spatial modeling in this context. Following the estimation of the PRC, the gross contribution according to the mechanism of Takaful models is calculated considering the spatial model.

Considering the similarities between Takaful and insurance, this study addresses the pricing of general Takaful within different Takaful models through a spatial dependency framework, such that the practical implications of the study are applicable for running Takaful's business in both Islamic and non-Islamic countries.

Most studies consider only the social or practical view of Takaful. This study contributes to the broader knowledge and understanding of Takaful by presenting a conceptual understanding of Takaful and then investigates the practical application of pricing risk contribution using innovative modeling of claim frequency and severity at the level of tariff cells.

The European Union (EU) has notified its revised Generalized System of Preference (GSP) on 31 October, 2012 which will come into effect from 1 January, 2014. The EU is also in the process of, or contemplating, to sign Free Trade Agreements (FTAs) with many developing countries. Recently, EU has officially announced initiation of FTA negotiations with USA. Such preferential tariff arrangements could lead to significant erosion of preferences enjoyed currently by the Least Developed Countries (LDCs). In this backdrop, the main objective of the present study is to investigate the economic impacts originating from preference erosion in the EU market which could potentially affect LDCs in general, Bangladesh in particular. In this context, a dynamic computable general equilibrium (CGE) analysis has been developed by using the Global Trade Analysis Project (GTAP) model and database to explore the aggregate impact of the preferential erosion as well as sectoral implications for which different partial equilibrium analyses were used. The analysis evince that if the EU eliminates all tariffs for Pakistan, India and Vietnam, Bangladesh's real GDP could decrease by 0.27 percent whilst welfare loss could be to the tune of US$ 54 million. Total exports to the EU will be reduced by 0.18 percent; consequently, Bangladesh’s terms of trade and exports of textiles and clothing could be fall by about 1 percent. The product level disaggregated analysis using RCA and unit price of major items also indicate that a number of products including textiles and clothing will be confronted with formidable market access difficulties in the EU.

A recurrent concern of researchers who measure the cost of protection is that welfare estimates based on models with highly aggregated sectors of the economy in question will understate the true cost of protection if the tariff system is not uniform. Uses the 1988 tariff schedule of the US and a detailed 1988 social accounting matrix of the US to construct a number of aggregation schemes to calculate the extent to which tariff means and variances change under different aggregations. Then uses a computable general equilibrium model to compare the cost of tariff protection between two of the aggregation schemes.

Electricity consumption around the world and in India is continuously increasing over the years. Presently, there is a huge diversity in electricity tariffs across states in India. This paper aims to focus on development of new tariff design method using K-means clustering and gap statistic.

Numbers of tariff plans are selected using gap-statistic for K-means clustering and regression analysis is used to deduce new tariffs from existing tariffs. The study has been carried on nearly 27,000 residential consumers from Sangli city, Maharashtra State, India.

These tariff plans are proposed with two objectives: first, possibility to shift consumer’s from existing to lower tariff plan for saving electricity and, second, to increase revenue by increasing tariff charges using Pay-by-Use policy.

The study can be performed on hourly or daily data using automatic meter reading and to introduce Time of Use or demand based tariff.

The proposed study focuses on use of data mining techniques for tariff planning based on consumer’s electricity usage pattern. It will be helpful to detect abnormalities in consumption pattern as well as forecasting electricity usage.

Consumers will be able to decide own monthly electricity consumption and related tariff leading to electricity savings, as well as high electricity consumption consumers have to pay more tariff charges for extra electricity usage.

To remove the disparity in various tariff plans across states and country, proposed method will help to provide a platform for designing uniform tariff for entire country based on consumer’s electricity consumption data.

The purpose of this paper is to investigate the potential economic effects of the proposed Bangladesh-India free trade agreement (FTA).

The authors have used the computable general equilibrium (CGE) analysis of Global Trade Analysis Project (GTAP) database. The analysis highlights the possible costs and benefits of the two nations within three different scenarios. Under Scenario I all bilateral import tariffs between Bangladesh and India are removed; Scenario II represents the setting where Bangladesh cuts its all tariffs by 75 and in Scenario III Bangladesh cuts tariffs by 50 percent. India cuts all their tariffs by 100 percent in all three scenarios.

The findings indicate that India may gain more in terms of welfare and real GDP via the improved terms of trade while Bangladesh is going to have welfare loss, but if Bangladesh is able to make a preferential FTA like Scenario III with India its welfare, real GDP and exports will be increased substantially.

This paper is the first-ever attempt to estimate the effect of the proposed Bangladesh-India FTA using CGE analysis of GTAP database version 7.

Corn, which has the highest domestic production, planting area and consumption, is the top cereal in relation to demand and supply in China. However, the comparative advantage of China in corn has continuously deteriorated in recent years and based on the recent situation and possible supply and demand trends, it is widely accepted that a corn self-sufficiency rate of 95% is difficult to achieve. Under current import-restriction policies, corn may stand at the crossroads of reforms to solve its predicted insufficient supply. In this study, the authors analyse the necessity of relaxing trade restrictions on corn in China and explore the effects of trade restrictions by reducing tariffs and expanding tariff-rate quotas on corn and related industries and the welfare change caused by possible relaxations.

The authors construct a computable general equilibrium (CGE) model and design nine scenarios for the analysis.

The results show that relaxations of import restrictions are probable methods to meet the aim of sufficient corn supply during shortages. They are simulated to reduce corn's domestic production and price, increase import and import prices and lead to a decline in self-sufficiency but benefit the production of corn-related industries of corn. The results also imply that expanding the quota is a better method for releasing trade restrictions in China.

The comparative advantage of China in corn deteriorated with an increase in prices. Based on the current situation and possible trends of supply and demand, the referenced goal of achieving 95% corn self-sufficiency appears difficult, implying that reliance on imports is probably imminent and vital. This study provides simulation results in future scenarios and offers policy implications for China's corn trade policies.

The purpose of this paper is to assess the impact of India’s trade liberalization during the late 1990s and 2000s on productivity of manufacturing firms and verify whether the productivity-enhancing impact of reductions in input tariffs was greater than that of output tariff cuts, as found in some earlier studies.

Firm-level (company-level) data drawn from Prowess database are used for the estimation of total factor productivity (TFP) at the firm level, done by using the Levinsohn–Petrin methodology. Econometric models are estimated to explain firm-level TFP. The explanatory variables used are output and input tariff rates and quantitative restrictions on imports at the industry level and firm characteristics such as firm size, export intensity and import intensity. Firm-level panel data for 2002-2010 or for a longer period 1998-2010 are used for the estimation of econometric models. Model estimation is done by applying the fixed-effects model and IV-2SLS, 3SLS estimators and EC2SLS estimators.

Trade liberalization had a significant positive effect on the productivity of Indian manufacturing firms. The lowering of output tariff had a greater beneficial impact on TFP of Indian manufacturing firms than the lowering of tariff on intermediate inputs.

Good deal of care has been taken in the measurement of output and inputs for the purpose of TFP measurement. Two alternative frameworks, gross output and value added, are used. This helps in making a better estimate of the impact of trade liberalization on TFP.

The purpose of this paper is to assess the degree of tariff escalation in Taiwan's agriculture-related commodities and the economy-wide impact of tariff harmonization.

A computable general equilibrium model of the Taiwan economy is applied to simulate for the economy-wide impact of three alternative proposals that reduce tariff rates as well as the degree of tariff escalation in agriculture-related products.

The paper shows that reduction in tariff wedge helps increase social welfare of Taiwan at the expense of some agricultural sectors. Based on the pair-wise comparisons of the three tariff reduction proposals, the scenario where the upstream products have the least reduction would have agricultural sectors fare better than in the other scenarios where more negative impact on output and employment would occur to agricultural sectors.

The paper assesses quantitatively the economy-wide impact of reducing tariff wedges between unprocessed and processed products, which is rarely seen in the literature using a detailed computable general equilibrium model.