Referencias bibliográficas Colombo, D., and Maathuis, M. H. (2014). Order-independent constraint-based causal structure learning. J. Mach. Learn. Res., 15(1), 3741-3782. David, F. (1949). The moments of the z and F distributions. Biometrika, 36, 394–403. Demiralp, S., and Hoover, K. D. (2003). Searching for the causal structure of a vector autoregression. Oxford Bulletin of Economics and statistics, 65, 745-767. Dumitrescu E.I and C. Hurlin (2012). Testing Granger Causality in Heterogeneous Panel Data Models. Economic Modelling, 29, 1450-1460. Eichler, M. (2007). Granger causality and path diagrams for multivariate time series. Journal of Econometrics, 137(2), 334-353. Eichler, M. (2012) Graphical modelling of multivariate time series. Probab. Theory Relat. Fields 153, 233–268. Emirmahmutoglu, F., and Kose, N. (2011). Testing for Granger causality in heterogeneous mixed panels. Economic Modelling, 28(3), 870-876. Granger, C.W.J., 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438. Hansen, H., and Rand, J. (2006). On the causal links between FDI and growth in developing countries. World Economy, 29(1), 21-41. Holtz-Eakin, D., Newey, W., and Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica: Journal of the econometric society, 1371-1395. Hurlin, C., and Venet, B. (2001). Granger causality tests in panel data models with fixed coefficients. Cahier de Recherche EURISCO, September, Université Paris IX Dauphine. Im, K. S., Pesaran, M. H., and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74. Malinsky, D., and Danks, D. (2018). Causal discovery algorithms: A practical guide. Philosophy Compass, 13(1), e12470 Onrubia, J., Pérez, J.J. and Sánchez-Fuentes, A.J. (2019) Public sector bureaucracies and economic growth. Revista de Economía Mundial, 51, 121-138. Nair‐Reichert, U., and Weinhold, D. (2001). Causality tests for cross‐country panels: a New look at FDI and economic growth in developing countries. Oxford bulletin of economics and statistics, 63(2), 153-171. Runge, J. (2018). Causal network reconstruction from time series: From theoretical assumptions to practical estimation. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(7), 075310. Spirtes, P., Glymour, C. and Scheines, R. (2000). Causation, Prediction, and Search, 2nd edn,MIT Press, Cambridge, MA.