References
- Cai, T., and P. Hall. 2006. Prediction in functional linear regression. The Annals of Statistics 34 (5):2159–79. https://www.jstor.org/stable/25463504. doi:https://doi.org/10.1214/009053606000000830.
- Case, A. C. 1991. Spatial patterns in household demand. Econometrica 59 (4):953–65. doi:https://doi.org/10.2307/2938168.
- Case, A. C., H. S. Rosen, and J. R. Hines. 1993. Budget spillovers and fiscal policy interdependence: Evidence from the states. Journal of Public Economics 52 (3):285–307. doi:https://doi.org/10.1016/0047-2727(93)90036-S.
- Dou, B., M. L. Parrella, and Q. Yao. 2016. Generalized yule-walker estimation for spatio-temporal models with unknown diagonal coefficients. Journal of Econometrics 194 (2):369–82. doi:https://doi.org/10.1016/j.jeconom.2016.05.014.
- Egozcue, J. J., and V. Pawlowsky-Glahn. 2005. Group parts and their balances in compositional data analysis. Mathematical Geology 37 (7):795–828. doi:https://doi.org/10.1007/s11004-005-7381-9.
- Frédéric, F., and V. Philippe. 2006. Nonparametric functional data analysis: Theory and practice. New York: Springer.
- Filzmoser, P., K. Hron, and C. Reimann. 2009. Principal component analysis for compositional data with outliers. Environmetrics 20 (6):621–32. doi:https://doi.org/10.1002/env.966.
- Gao, Z., Y. Ma, H. Wang, and Q. Yao. 2019. Banded spatio-temporal autoregressions. Journal of Econometrics 208 (1):211–230.
- Hall, P., and J. L. Horowitz. 2007. Methodology and convergence rates for functional linear regression. The Annals of Statistics 35 (1):70–91. doi:https://doi.org/10.1214/009053606000000957.
- Hron, K., P. Filzmoser, and K. Thompson. 2012. Linear regression with compositional explanatory variables. Journal of Applied Statistics 39 (5):1115–28. doi:https://doi.org/10.1080/02664763.2011.644268.
- Jenish, N., and I. R. Prucha. 2009. Central limit theorems and uniform laws of large numbers for arrays of random fields. Journal of Econometrics 150 (1):86–98. ISSN 0304-4076. http://www.sciencedirect.com/science/article/pii/S0304407609000475. doi:https://doi.org/10.1016/j.jeconom.2009.02.009.
- Kelejian, H. H., and I. R. Prucha. 1999. A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40 (2):509–33. doi:https://doi.org/10.1111/1468-2354.00027.
- Lee, L.-F. 2004. Asymptotic distributions of quasi-maximum likelihood estimators for spatial autoregressive models. Econometrica 72 (6):1899–925. doi:https://doi.org/10.1111/j.1468-0262.2004.00558.x.
- Lee, L-F. 2007. Gmm and 2sls estimation of mixed regressive, spatial autoregressive models. Journal of Econometrics 137 (2):489–514. ISSN 0304-4076. http://www.sciencedirect.com/science/article/pii/S0304407606000662. doi:https://doi.org/10.1016/j.jeconom.2005.10.004.
- Lesage, J., and R. K. Pace. 2009. Introduction to spatial econometrics. Florida: Chapman and Hall/CRC.
- Olubusoye, O. E., G. O. Korter, and A. A. Salisu. 2016. Modelling road traffic crashes using spatial autoregressive model with additional endogenous variable. Statistics in Transition New 17 (4):659–70.
- Ord, K. 1975. Estimation methods for models of spatial interaction. Journal of the American Statistical Association 70 (349):120–6. doi:https://doi.org/10.1080/01621459.1975.10480272.
- Pawlowsky-Glahn, V., J. J. Egozcue, and R. Tolosana-Delgado. 2015. Modelling and analysis of compositional data. London: John Wiley & Sons, Ltd. doi:https://doi.org/10.1002/9781119003144.
- Qu, X., and L-F Lee. 2015. Estimating a spatial autoregressive model with an endogenous spatial weight matrix. Journal of Econometrics 184 (2):209–32. ISSN 0304-4076. http://www.sciencedirect.com/science/article/pii/S0304407614001870. doi:https://doi.org/10.1016/j.jeconom.2014.08.008.
- Ramsay, J. O., and B. W. Silverman. 2002. Applied functional data analysis: Methods and case studies. New York: Springer.
- Ramsay, J. O., and B. W. Silverman. 2005. Functional data analysis. New York: Springer.
- Su, L., and S. Jin. 2010. Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models. Journal of Econometrics 157 (1):18–33. doi:https://doi.org/10.1016/j.jeconom.2009.10.033.
- Sun, Y., and E. Malikov. 2018. Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects. Journal of Econometrics 203 (2):359–78. ISSN 0304-4076. http://www.sciencedirect.com/science/article/pii/S0304407618300010. doi:https://doi.org/10.1016/j.jeconom.2017.12.006.
- Topa, G. 2001. Social interactions, local spillovers and unemployment. The Review of Economic Studies 68 (2):261–95. doi:https://doi.org/10.1111/1467-937X.00169.
- Wang, H., L. Shangguan, J. Wu, and R. Guan. 2013. Multiple linear regression modeling for compositional data. Neurocomputing 122:490–500. ISSN 0925-2312. http://www.sciencedirect.com/science/article/pii/S0925231213005808. doi:https://doi.org/10.1016/j.neucom.2013.05.025.