Cross-border mobility responses to COVID-19 in Europe: new evidence from facebook data

Table 4 MAE comparison of the different models with and without day/corridor dummies

	Linear	KNN	G-Boost	MLP	Linear	KNN	G-Boost	MLP
	Panel A: No dummies				Panel B: Day dummies
avg MAE	0.201	0.019	0.042	0.057	0.179	0.181	0.056	0.059
std MAE	(0.005)	(0.001)	(0.001)	(0.003)	(0.004)	(0.005)	(0.001)	(0.003)
avg RMSE	0.287	0.043	0.064	0.089	0.259	0.269	0.084	0.090
std RMSE	(0.009)	(0.005)	(0.002)	(0.008)	(0.008)	(0.008)	(0.002)	(0.004)
	Panel C: Corridor dummies				Panel D: Corridor & Day dummies
avg MAE	0.156	0.018	0.037	0.048	0.134	0.020	0.049	0.038
std MAE	(0.006)	(0.001)	(0.001)	(0.004)	(0.005)	(0.001)	(0.001)	(0.003)
avg RMSE	0.231	0.043	0.059	0.086	0.203	0.047	0.077	0.064
std RMSE	(0.010)	(0.005)	(0.002)	(0.009)	(0.009)	(0.005)	(0.002)	(0.005)

Notes: The table compares the performances of the 4 different approaches with and without the day- and corridor-specific dummies. All models are estimated with directional priors. Errors are computed from a 10-fold cross-validation on the whole data set

ISSN: 1744-8603