Maternal care receptivity--an innovative approach for the evaluation of MCH services

Despite rapid expansion in the maternal and child health and family planning services, there have been few attempts made to study the extent of utilisation of these services and their impact. The present study reports a simple method evolved in the quantification of utilisation of maternal care services (called maternal care receptivity - MCR), the relationship of factors such as age, parity, caste of the women and the distance of the health centre on the MCR and the impact of MCR on perinatal and neonatal mortalities. An inverse relationship was observed between MCR and perinatal and neonatal mortality rates and the two rates were three times less among babies born to mothers with high MCR scores compared to those with poor MCR scores.     

Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm's demand and cares about the short‐term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least‐cost separating equilibrium will result, in which a low‐quality firm chooses its optimal capacity and a high‐quality firm over‐invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low‐quality firms over‐invest and high‐quality firms under‐invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least‐cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used.     

Constant factor approximation for the weighted partial degree bounded edge packing problem

In the partial degree bounded edge packing problem (PDBEP), the input is an undirected graph \(G=(V,E)\) with capacity \(c_v\in {\mathbb {N}}\) on each vertex v. The objective is to find a feasible subgraph \(G'=(V,E')\) maximizing \(|E'|\), where \(G'\) is said to be feasible if for each \(e=\{u,v\}\in E'\), \(\deg _{G'}(u)\le c_u\) or \(\deg _{G'}(v)\le c_v\). In the weighted version of the problem, additionally each edge \(e\in E\) has a weight w(e) and we want to find a feasible subgraph \(G'=(V,E')\) maximizing \(\sum _{e\in E'} w(e)\). The problem is already NP-hard if \(c_v = 1\) for all \(v\in V\) (Zhang in: Proceedings of the joint international conference on frontiers in algorithmics and algorithmic aspects in information and management, FAW-AAIM 2012, Beijing, China, May 14–16, pp 359–367, 2012). In this paper, we introduce a generalization of the PDBEP problem. We let the edges have weights as well as demands, and we present the first constant-factor approximation algorithms for this problem. Our results imply the first constant-factor approximation algorithm for the weighted PDBEP problem, improving the result of Aurora et al. (FAW-AAIM 2013) who presented an \(O(\log n)\)-approximation for the weighted case. We also study the weighted PDBEP problem on hypergraphs and present a constant factor approximation if the maximum degree of the hypergraph is bounded above by a constant. We study a generalization of the weighted PDBEP problem with demands where each edge additionally specifies whether it requires at least one, or both its end-points to not exceed the capacity. The objective is to pick a maximum weight subset of edges. We give a constant factor approximation for this problem. We also present a PTAS for the weighted PDBEP problem with demands on H-minor free graphs, if the demands on the edges are bounded by polynomial. We show that the PDBEP problem is APX-hard even for bipartite graphs with \(c_v = 1, \; \forall v\in V\) and having degree at most 3.     

Special education disproportionality in the United States,Germany, Kenya,and India

Disproportionality in special education includes the underrepresentation and overrepresentation of children by gender, economic status, race, ethnicity, language, and culture. This article reviews literature on disproportionality in the United States, Germany, Kenya, and India. Societal views of disability, classism, racism, and inequitable assessment are among the factors that contribute to disproportionality. Preventative medicine, equitable access to resources, ethical and effective assessment procedures, and educational practices that are gender equitable and culturally responsive may reduce the problem of disproportionality.     

Does “buyer beware” work in migration? Contracting between brokers and migrants in Vietnam

This article is an attempt to open the lid a little of the “black box of migration” i.e. brokers. Analysing contracts between brokers and labour migrants, we identify four different forms of exploitation of migrants by brokers: expropriation of skill premium, risk shifting, over‐charging, and non‐refund of deposits. Opportunistic behaviour by brokers, as evidenced by such exploitation, is seen as a market failure that is explained by human attributes and transactional characteristics. Given the rigidities in the human attributes of the contracting parties and the nature of migration as a risky multi‐period transaction, proposals are made for non‐market interventions, which can lead to more equitable contracting.     

Gang Leader for a Day: A Response to the Critics

This essay provides a response to Clampet-Lundquist, Charles, and Young's comments on my book Gang Leader for a Day :     

LBI tests for the detection of compound normal distribution in control and treatment populations

Independent samples are drawn from control and treatment populations with normal and compound normal distributions respectively. We derive the locally best invariant (LBI) tests through Wijsman’s representation for the detection of mixture departures from the normal distribution. These tests may be viewed as tests for the equality of control and treatment populations. Further, they are optimally robust for the model considered by Durairajan and Raman (1994).     

Estimation of Error and Bias in Bayesian Monte Carlo Decision Analysis Using the Bootstrap

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.