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The main purpose of this paper is to investigate the sheepskin effects in the returns to education in the Sri Lankan labor market by ethnicity.

The study is based on the latest Sri Lankan Consumer Finance and Socio‐economic Survey. The study employs the quantile regression method for each conditional quantile wage group, rather than the mean regression analysis used in most labor market analysis. The quantile regression technique fits hyperplanes through out the conditional wage and is ideal for characterizing the entire wage distribution. The standard Mincerian wage equation was estimated for the full sample of male workers and separately for the two main ethnic groups in Sri Lanka.

The empirical findings are broadly encouraging. Quantile regression results suggest that average returns to education for both ethnic groups differs significantly from the returns at the two extreme ends of the wage distribution. In general, the returns to education are positive for both groups, but the returns are higher for Sinhalese workers than for Tamil. An increasing trend in returns to education is evident for both ethnic groups when moving up wage distribution. Sinhalese workers experience higher returns to education than for Tamil especially at the bottom of the wage distribution, but the difference becomes less at the upper part of the distribution. Estimated results with spline in years of education suggest that returns to secondary education are higher for Sinhalese workers, but the returns to tertiary education are greater for Tamil workers at the upper part of the wage distribution. Findings indicate that returns to experience are also higher for Sinhalese workers than for Tamil workers.

This is the first study that examines sheepskin effects in the returns to education by ethnicity in Sri Lanka in a Mincerian framework, employing quantile regression models.

The main purpose of this paper is to construct a poverty profile for Sri Lanka, and examine the micro‐level determinants and correlates of poverty.

The study is based on the latest Sri Lanka Integrated Survey commissioned by the World Bank. The unconditional poverty profile was constructed using three different poverty measures (poverty headcount, average poverty gap and squared poverty gap), nested in the Foster‐Greer‐Thorbecke index. The conditional poverty profile was constructed on the basis of a multivariate analysis of poverty correlates. Partial correlates of poverty are computed using two comparable methodologies. First, a logistic regression was estimated, with the probability of a household being in poverty as the dependent variable and a set of economic and demographic variables as correlates. Second, the quantile regression approach was utilized to examine the correlates of per capita consumption at different points on the distribution.

The empirical findings are broadly encouraging. The estimation results show that the education of the household head, being salary employed and being engaged in business have a significant positive effect on the standard of living. The probability of being poor increases with the household size, household head being female, living in a rural area, and being a casual wage earner. These findings indicate the importance of a set of policies which are super pro‐poor, namely increasing school enrolment and achievement, effective family planning programs to reduce the birth rate and dependency load within households, and granting priorities for specific cohorts (children‐, elderly‐, rural‐ and female‐headed households) in targeted interventions.

This is the first study that examines the probable determinants and correlates of Sri Lankan poverty in a multivariate framework employing both logit and quantile regressions.

The purpose of this paper is to decompose inequality in Sri Lanka by population subgroups and income sources.

The study is based on the latest Sri Lankan Household Income and Expenditure Survey. The study firstly sketches an inequality profile for Sri Lanka and then investigates the principle components of inequality by applying several decomposition techniques. Essentially a decomposable class of inequality measures were computed by considering households characteristics such as geographic location/sector, gender, education and type of employment. Inequality within and between population subgroups/sectors in the distribution of expenditure was done by employing the Theil's entropy index, mean logarithmic deviation, and the half the squared coefficient of variation. Concentration curves and indices were utilized to decompose inequality by expenditure components.

The empirical findings are broadly encouraging. Decomposition analysis results reveal that in all groups used, the between‐group inequality accounts only for a very small part of the overall inequality. Thus, reducing inequality between the household groups would have only limited effect on reducing the overall inequality. Results confirm the fact that inequality in Sri Lanka was driven by relatively higher levels of expenditure inequalities of those at the top of the expenditure distribution. Decomposition estimates of the Gini index by expenditure sources via Rao's method revealed that the distribution of non‐food expenditure was more asymmetric as compared to food expenditure. Findings in general point to the wisdom of considering the redistribution of economic resources within‐sectors and sub‐groups rather than between‐sectors and sub‐groups if the intention is to cost effectively reduce overall inequalities in Sri Lanka. However, in practice an optimal‐mix of within and between‐group policies would be required in addressing overall inequality.

This is the first study that analyzes the latest Sri Lankan Household Income and Expenditure Survey to decompose inequality by population subgroups and income sources.

Vertical alignment in high-rise building is a very important aspect. The architects are nowadays interested in improvising untypical complicated morphology in building designs which increase the difficulty in surveying for vertical alignments. Although the GNSS survey techniques are widely applied in constructions, there is a lack of data sources to explicitly expose their applicability in high-rise buildings and the challenges to be considered. This study has been oriented to find out the best suitable GPS survey technique for the vertical alignment in high-rise buildings and the practical challenges to be considered.

The findings have been attained by analyzing the reliable data gained through experts' comments through structured questionnaire survey, case studies and experiments on different GPS survey techniques.

The findings express that the GPS techniques can be used for vertical alignments in high-rise buildings except for direct setting out for which only RTK GPS can be used. There are some practical challenges to be considered in such GPS applications.

The findings encourage the research community to further focus on the GNSS survey applications in the constructions of high-rise buildings.

The research expresses applicability of easier and less time-consumed modern GNSS survey techniques instead of traditional survey methods for expediting building constructions.

The knowledge on such modern rapid survey techniques with accuracy, efficiency and reliability highly affects the process of infrastructure development.

The research presents a useful new knowledge on applying GNSS survey techniques for precise survey requirements in the construction industry and exposes the gateways for further researches and development.