Follow us
Publications Commentary Research People Events News Resources and Videos About IFS
Home Publications Estimation with Mixed Data Frequencies: A Bias-Correction Approach

Estimation with Mixed Data Frequencies: A Bias-Correction Approach

Anisha Ghosh and Oliver Linton
Cemmap Working Paper CWP65/19

We propose a solution to the measurement error problem that plagues the estimation of the relation between the expected return of the stock market and its conditional variance due to the latency of these conditional moments. We use intra-period returns to construct a nonparametric proxy for the latent conditional variance in the first step which is subsequently used as an input in the second step to estimate the parameters characterizing the risk-return tradeoff via a GMM approach. We propose a bias-correction to the standard GMM estimator derived under a double asymptotic framework, wherein the number of intra-period returns, N, as well as the number of low frequency time periods, T , simultaneously go to infinity. Simulation exercises show that the bias-correction is particularly relevant for small values of N which is the case in empirically realistic scenarios. The methodology lends itself to additional applications, such as the empirical evaluation of factor models, wherein the factor betas may be estimated using intra-period returns and the unexplained returns or alphas subsequently recovered at lower frequencies.

More on this topic

Cemmap Working Paper CWP4/20
This article provides a selective review on the recent literature on econometric models of network formation.
Cemmap Working Paper CWP3/20
This paper introduces measures for how each moment contributes to the precision of parameter estimates in GMM settings.
Cemmap Working Paper CWP1/20
We study the incidental parameter problem in "three-way" Poisson Pseudo-Maximum Likelihood "PPML" gravity models recently recommended for identifying the effects of trade policies.
Cemmap Working Paper CWP2/20
We propose an optimal-transport-based matching method to nonparametrically estimate linear models with independent latent variables.
Journal article | Macroeconomic Dynamics
Consumption Euler equations are important tools in empirical macroeconomics. When estimated on micro data, they are typically linearized, so standard IV or GMM methods can be employed to deal with the measurement error that is endemic to survey data. However, linearization, in turn, may induce ...