Specifically, Cawley, Han and Norton use a large US dataset comprised of immigrants from developing countries to examine the effect of Body Mass Index (hereafter BMI) and indicator variables for the clinical weight classifications for overweight and obese on several labor market outcomes2.
For the sake of simplicity, we drop the block index hereafter, but note that the results obtained do depend on the positions of blocks.
In the earlier case, the use of econometric method such as regression analysis is commonly employed to construct the Livelihood Vulnerability Index (hereafter referred to as LVI).
The maximal matching algorithm for maximizing the assortativity index (hereafter, referred to as the maximal assortative matching algorithm, MAM) prefers to include edges that have lower assortativity weight as part of the matching.
We assume the node weights as node degree and calculate the assortativity index (hereafter, shortly referred to as A.Index) of the network (considering the set of all edges) and the assortativity index of the maximal matching obtained with the MAM and MNM algorithms.
Second, we used the binomial skew index (hereafter B index; Nonacs 2000, 2003).
The tick value is calculated by multiplying the tick size (the minimum price movement for a unit of a security) by the contract size, where the contract size is the multiplication of the Standard & Poor's CNX Nifty Index Futures (hereafter "Nifty Futures" or "Nifty") price and its market lots.
We follow this approach and create an adverse selection index (ASY, hereafter) from five individual measures developed by market microstructure literature: the relative bid-ask spread, the illiquidity measure developed in Amihud (2002), the price impact introduced by Huang and Stoll (1996), the PIN, and the VPIN.
During pregnancy, maternal weight is a product of both prepregnancy body mass index (BMI), hereafter referred to as BMI, and gestational weight gain (GWG).
