We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the remaining...

The concept of revealed comparative advantage (RCA) stands as a major pillar in empirical trade literature. Yet there is no absolute preference among the suggested RCA measures. Given that these are volume-based indices, results of any relevant empirical analysis would be heavily influenced by...

We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the remaining...

[Update: Within four weeks of the original publication of this research report, Risk Magazine reported in its 28th February 2012 issue story titled 'Goodbye VaR? Basel to Consider Other Risk Metrics': "A review of trading book capital rules, due to be launched in March by the Basel Committee on...

The spatial granularity of poverty statistics can have a significant impact on the efficiency of targeting resources meant to improve the living conditions of the poor. However, achieving granularity typically requires increasing the sample sizes of surveys on household income and expenditure or...

Existing measures of core inflation ignore a part of ‘should be’ the core inflation. Exclusion based measures ‘exclude’ a part of persistent inflation inherently existing in the excluded part whereas filter based measures ‘filter-out’ the cyclical part also rather than the irregular...

This paper states that market sentiments are central to any financial data analysis. A vivid distinction is made between studying financial data in terms of the concept of volatility and in rapport to analysing financial data in terms of market sentiments. The former is an existing approach that...

Poverty statistics are conventionally compiled using data from household income and expenditure survey or living standards survey. This study examines an alternative approach in estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial...

The spatial granularity of poverty statistics can have a significant impact on the efficiency of targeting resources meant to improve the living conditions of the poor. However, achieving granularity typically requires increasing the sample sizes of surveys on household income and expenditure or...

We propose two indexes to measure the agglomeration forces acting within and between different regions. Unlike the existing measures of agglomeration, our model-based indexes allow for simultaneous treatment of both aspects. Local plant diffusion in a given industry is modelled as a spatial...