Panel data are often used in empirical work to account for additive fixed time and unit effects. More recently, the synthetic control estimator relaxes the assumption of additive fixed effects for case studies, using pre-treatment outcomes to create a weighted average of other units which best approximate the treated unit. The synthetic control estimator is currently limited to case studies in ...

Abstract. This paper proposes a penalized quantile regression estimator for panel data that explicitly considers individual heterogeneity associated with the covariates. We provide conditions under which the estimator is asymptotically Gaussian, and the harshness of the penalization can be determined by minimizing asymptotic mean squared error. We investigate finite sample and asymptotic perfor...

This paper tries to explore the asymptotic properties of maximum likelihood estimators for spatial dynamic panel data with fixed effects when both the number of time periods T and number of individuals n are large. When n is proportional to T or T is relatively large, the estimator is √ nT consistent and asymptotically normal; when n is relatively large, the estimator is consistent with the rat...

This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage ...

Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackw...

This paper studies the effects of land use consolidation on consumption growth of farm households in Rwanda. Data on 1 920 households, observed in two time periods, are used to estimate a first-differenced model using an instrumental variables estimator, which allow the analysis to account for selection bias and placement effects. Results show no significant effect of land use consolidation on ...

This work develops techniques for the sequential detection and location estimation of transient changes in the volatility (standard deviation) of time series data. In particular, we introduce a class of change detection algorithms based on the windowed volatility filter. The first method detects changes by employing a convex combination of two such filters with differing window sizes, such that...

Maddala and Wu (1999) proposed a simple panel unit test using a Fisher type test. We propose using Percival and Walden (2006) approximate maximum likelihood estimator of the fractional integration order with a Fisher type test to create a simple panel fractional integration order test. By combining the estimator and the test with a wavestrap method to obtain critical values, we allow for cross-...

For a random e ects regression model with unbalanced panel data, we demonstrate that the Generalized Least Squares (GLS) estimator can be expressed as a (matrix) weighted average of estimators which utilize the within individual and the between individual variation in the data set. We thus generalize a relationship familiar for balanced panel data. Speci c attention must be given to the interce...

We propose a jackknife for reducing the order of the bias of maximum likelihood estimates of nonlinear dynamic fixed effects panel models. In its simplest form, the half-panel jackknife, the estimator is just 2θ̂ − θ1/2, where θ̂ is the MLE from the full panel and θ1/2 is the average of the two half-panel MLEs, each using T/2 time periods and all N cross-sectional units. This estimator eliminates...