Showing 1 - 5 of 5
Time series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a...
Persistent link: https://www.econbiz.de/10012467713
This paper introduces an instrumental variables estimator for the effect of a binary treatment on the quantiles of potential outcomes. The quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile regression as a special case when treatment status is...
Persistent link: https://www.econbiz.de/10012472370
Instrumental variables (IV) estimation of a demand equation using time series data is shown to produce a weighted … derivative estimation to models with endogenous regressors. The paper also shows how to compute the weights underlying IV …
Persistent link: https://www.econbiz.de/10012473812
From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the...
Persistent link: https://www.econbiz.de/10012456185
Using theories from the behavioral finance literature to predict that investors are attracted to industries with more salient outcomes and that therefore firms in such industries have higher valuations, we find that firms in industries that have high industry-level dispersion of profitability...
Persistent link: https://www.econbiz.de/10012457786