We estimate a panel error-correction version of an autoregressive distributed lag model to identify the long-term relationships between social expenditure and its determinants.
Next, we examine the long-run relationship between social expenditure and its determinants estimating a panel error-correction model (ECM) to find cointegration relationships between the I(1) and I 0) variables of the model.
The results from panel error correction model reveal that there is evidence of a bidirectional causality between output and exports and between output and imports in both the short and long-run.
In all panels, error bars indicate uncertainties related to fitting the images of the BECs.
In all panels, error bars are standard deviations from 10 random imaging locations in the same sample channel, and *** indicates p<0.001 by the Student's t-test.
Lower panel, quantification of the intensity for the band labeled 'p25' in the upper panel; error bars represent SEM.
The choice probabilities were simulated based on the panel error component coefficients using 1000 draws from the probability density functions estimated for the random error components.
Quantification of c-Myc-induced apoptosis was performed in three independent MEF lines that overexpressed MSCV or miR-92 (right panel, error bars represent SEM).
Additional file 4 shows that there is a negative correlation between the number of SNPs in a panel and the error associated to the estimates of ancestry.
We further account for unobserved heterogeneity and spatial dependence via the use of a panel data estimator with spatial error components.
