We address the cross-state indebtedness (DCL/RCL) variation connectedness using 89 bimonthly data from 2006b6 to 2021b4, based on indices proposed by Diebold and Yilmaz (2009, 2012, 2014). This framework enables us infer about direction, strength of bilateral spillovers for a large number simultaneously interacting variables in clear compact manner. are able identify most influential states eac...

In observational studies, investigators usually do not have the same control over the treatment assignment as they do with randomized controlled studies. As a result, the treatment and control groups may have a large difference on their observed covariates. These differences could lead to bias in estimating treatment effects. There are several propensity score based methods that could reduce th...

‡We gratefully acknowledge our indebtedness to Kevin Kelly and David Danks. We would also like to thank an anonymous reviewer for very detailed and helpful comments. have been concerned to show that certain procedural accounts of model confirmation are compromised by non-linear dynamics. We suggest that the issues raised are better approached by considering whether chaotic data analysis methods...

The Effect of Breastfeeding on Children’s Cognitive and Noncognitive Development This paper uses propensity score matching methods to investigate the relationship between breastfeeding and children’s cognitive and noncognitive development. We find that breastfeeding for four weeks is positively and statistically significantly associated with higher cognitive test scores, by around one tenth of ...

The aim is to assess the effect of imprisonment on rape myth acceptance. The research used a sample of male prisoners incarcerated for non-sexual crimes (n = 98) and a sample of males drawn from the general population (n = 160). Simple linear regression did not indicate a significant effect of incarceration on rape myth acceptance. After controlling for background covariates using propensity sc...

Observational studies draw inferences about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. Let r1(x) be the response when a unit with covariates x receives the treatment (z = 1), and r0(x) be the response when that unit does not receive the treatment (z = 0). Then one is int...

We are interested in estimating the average effect of a binary treatment on a scalar outcome. If assignment o the treatment is exogenous or unconfounded, that is, independent of the potential outcomes given covariates, biases associated with simple treatmentcontrol average comparisons can be removed by adjusting for differences in the covariates. Rosenbaum and Rubin (1983) show that adjusting s...