Sentence examples for dynamic panel modelling from inspiring English sources

In situations where time effect was considerable, the use of dynamic panel modelling was required because the inclusion of lagged dependent variable as a regressor might result in an autocorrelation problem and lead to biased estimates of fixed effects model.

Evidence of the causality links that have prevailed in 13 advanced economies over the 1980 2004 period has been obtained through dynamic panel models.

Hence, a limitation of fixed effects model that may arise due to the inclusion of lagged variable (lagged income) was checked using dynamic panel model as shown in Eq. (6).

To control for persistence, we consider a dynamic panel model of the type4: m it = ρ m it − 1 + γAi d it + X it β + δ i + τ t + ε it with i = 1 … n and t = 1 … T (2).

Based on the empirical results from the fixed effect model and dynamic panel data model, increasing the UTII could generally mitigate the air pollution, but the long-run and short-run effects are significantly different.

A further advantage of this econometric specification which uses panel data and not cross-sectional data is that individual heterogeneity and state dependence can be considered in a dynamic panel data model, which is not possible in a model for cross-sectional data.

We have applied several GMM specifications for dynamic panel data models.

In the empirical section we performed a Dynamic Panel Data model.

Table 2 reports the results of the specifications presented in (6) as the dynamic panel data model.

We therefore also consider a dynamic panel data model using the system GMM methodology developed by Blundell and Bond (1998).3.3

Therefore, for a given norm and a given destination we estimate the following dynamic panel data model: Δ I it = α + ρ I it - 1 + θ m it - 1 + γ N it - 1 + δ H it - 1 + ϵ it (1).