This paper describes and applies econometric strategies for estimating regression models of economic share data outcomes where the shares may take boundary values (zero and one) with nontrivial probability. The main focus of the paper is on the conditional mean structures of such data. The paper...

Ultra-high frequency data are complete transactions data which inherently arrive at random times. Marked point processes provide a theoretical framework for analysis of such data sets. The ACD model developed by Engle and Russell (1995) is then applied to IBM transactions data to develop...

We propose leave-out estimators of quadratic forms designed for the study of linear models with unrestricted heteroscedasticity. Applications include analysis of variance and tests of linear restrictions in models with many regressors. An approximation algorithm is provided that enables accurate...

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent...

In this paper we provide econometric tools for the evaluation of intertemporal asset pricing models using specification-error and volatility bounds. We formulate analog estimators of these bounds, give conditions for consistency and derive the limiting distribution of these estimators. The...

This paper considers models for unobservables in duration models. It demonstrates how cross-section and time-series variation in regressors facilitates identification of single-spell, competing risks and multiple spell duration models. We also demonstrate the limited value of traditional...

Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners,...

We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to the policy variable of interest. We provide sufficient conditions to identify the causal effect of the policy by exploiting covariates related to the policy only through the...