This paper joins discussions on normalized regression and decomposition equations in devising a simple and general algorithm for obtaining the normalized regression and applying it to the Oaxaca decomposition. This resolves the invariance problem in the detailed Oaxaca decomposition. An...

We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant...

Social scientists are often interested in assessing relative changes between two groups over time, for example, the convergence of black-white wages from 1940 to 1990. In such situations, we need a control group for both treatment groups to remove biases resulting from time trends and unobserved...

We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant...

Social scientists are often interested in assessing relative changes between two groups over time, for example, the convergence of black-white wages from 1940 to 1990. In such situations, we need a control group for both treatment groups to remove biases resulting from time trends and unobserved...

Authors often add covariates to a base model sequentially either to test a particular coefficient's “robustness” or to account for the “effects” on this coefficient of adding covariates. This is problematic, due to sequence-sensitivity when added covariates are intercorrelated. Using the...

This paper joins discussions on normalized regression and decomposition equations in devising a simple and general algorithm for obtaining the normalized regression and applying it to the Oaxaca decomposition. This resolves the invariance problem in the detailed Oaxaca decomposition. An...

We propose a simple methodology for decomposing differences in the first moment into characteristics and coefficients effects. This methodology provides a way to apply the Blinder-Oaxaca decomposition to a non-linear function for both aggregate and detailed decompositions

Volatility is the feature in the India fiber market. By using the granger’s causality test, the study inferred that there was a unidirectional causality between WPI values of jute and cotton and WPI values of silk and cotton at an all India level. By carrying out the co-integration test the...