Where do Remittances Go in Household Consumption? Empirical Evidence from Sri Lanka-Wide Micro-data

Private internal and international remittances are a major source of household money in Sri Lanka, yet their impact on household welfare has long been a research gap. Based on the Migration and Development Theory, this article examines how private remittances affect household expenditure behaviour, using nationally representative microdata and applying quasi-experimental methods. Private remittances have significantly increased household per-capita expenditure and initiated positive behavioural changes via increased allocations for basic needs, human and physical capital investment. Compared with internal remittances, the impact of international remittance shows a strong potential for reducing poverty incidence and improving people's well-being: households in richer/richest expenditure quartiles and urban households invest in education, which supports the country's long-standing record of education. Rural households demonstrate favourable changes in spending behaviour with receiving private remittances. From a public policy standpoint, government favours migration so that remittances are more likely to flow. A proper remittance-transfer mechanism to encourage smooth remittance is thus required.     

Exploring gillnet catch efficiency of sardines in the coastal waters of Sri Lanka by means of three statistical techniques: a comparison of linear and nonlinear modelling techniques

The present investigation was undertaken to study the gillnet catch efficiency of sardines in the coastal waters of Sri Lanka using commercial catch and effort data. Commercial catch and effort data of small mesh gillnet fishery were collected in five fisheries districts during the period May 1999–August 2002. Gillnet catch efficiency of sardines was investigated by developing catch rates predictive models using data on commercial fisheries and environmental variables. Three statistical techniques [multiple linear regression, generalized additive model and regression tree model (RTM)] were employed to predict the catch rates of trenched sardine Amblygaster sirm (key target species of small mesh gillnet fishery) and other sardines (Sardinella longiceps, S. gibbosa, S. albella and S. sindensis). The data collection programme was conducted for another six months and the models were tested on new data. RTMs were found to be the strongest in terms of reliability and accuracy of the predictions. The two operational characteristics used here for model formulation (i.e. depth of fishing and number of gillnet pieces used per fishing operation) were more useful as predictor variables than the environmental variables. The study revealed a rapid tendency of increasing the catch rates of A. sirm with increased sea depth up to around 32 m.     

Optimized Sampling Strategies for Identifying Modes in Length-frequency Distributions

An approach to evaluate sampling strategies to detect modes in length-distributions is presented. Distributions based on various numbers of samples (S) and sample sizes (n) were simulated from the original cod and capelin data in Icelandic waters, incorporating within sample correlations. A peak was discerned if the difference between any simulated and original distribution did not exceed a pre-specified Δ, given a probability. This was achieved with numerous combinations of S and n, and the optimal choice will depend on the sampling costs. Variance-equivalence curves also illustrate the difference between demanding precision of mean lengths versus precision of length distributions.