motives for weighting when estimating causal effects: (1) to achieve precise estimates by correcting for heteroskedasticity …

heteroskedasticity. The technique uses approximating parametric models for the projection of right hand side variables onto the … instrument space, and for conditional heteroskedasticity and serial correlation of the disturbance. Use of parametric models …

heteroskedasticity in their movements. In particular, we estimate a structural-form GARCH' model that includes the short-term interest …

response of equity prices to interest rate changes. This paper uses an identification technique based on the heteroskedasticity …

heteroskedasticity of the structural shocks. I show that if the heteroskedasticity can be described as a two-regime process, then the …

model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset … size-ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This … pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns …

paper applies the identification through heteroskedasticity methodology to estimate the effect of openness on growth while …