Inference in Continuous Systems with Mildly Explosive Regressors∗
نویسندگان
چکیده
New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressors, and is feasible to implement in practice. Simulations show that double asymptotics deliver a good approximation to the finite sample distribution, with both finite sample and asymptotic distributions showing sensitivity to initial conditions. The methods are implemented in the US real estate market for an empirical application, illustrating the usefulness of double asymptotics in practical work.
منابع مشابه
Limit Theory for Continuous Time Systems with Mildly Explosive Regressors∗
New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressor...
متن کاملIntegrated Time Series in Binary Choice Models
Though binary choice and multiple choice models have been a popular tool of microeconometrics for many years, there are macroeconomic time series that are connected with discrete decisions of authorities. Therefore it is very important to develop an appropriate tool for statistical inference for such macroeconomic time series. Macroeconomic continuous time series may be stationary as well as in...
متن کاملInference for high-dimensional sparse econometric models
This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression function is wellapproximated by a parsimonious, yet unknown set of regressors. The latter condition makes it possible to estimate the entire regressi...
متن کاملPartial Identification and Inference in Binary Choice and Duration Panel Data Models
Many semiparametric fixed effects panel data models, such as binary choice models and duration models, are known to be point identified when at least one regressor has full support on the real line. It is common in practice, however, to have only discrete or continuous, but possibly bounded, regressors. This paper addresses identification and inference for the identified set in such cases, when...
متن کاملModels as Approximations — A Conspiracy of Random Regressors and Model Misspecification Against Classical Inference in Regression
Abstract. More than thirty years ago Halbert White inaugurated a “modelrobust” form of statistical inference based on the “sandwich estimator” of standard error. This estimator is known to be “heteroskedasticityconsistent”, but it is less well-known to be “nonlinearity-consistent” as well. Nonlinearity raises fundamental issues because regressors are no longer ancillary, hence can’t be treated ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017