Abstract
This chapter investigates whether predictions of future economic growth can be improved by using standard measures of broadband infrastructure. The investigation is carried out by comparing the predictive accuracy of dynamic panel models of economic growth estimated with and without measures of broadband infrastructure. The more powerful versions of the Diebold–Mariano–West (DMW) and Morgan–Granger–Newbold (MGN) test are employed for predictive accuracy comparison. It is evident that measures of broadband infrastructure can improve predictions of GDP growth after controlling for standard growth determinants.
In memory of late Gary Madden. The majority of the paper is published as a conferences paper at the 20th ITS Biennial Conference, Rio de Janeiro, 2014, where Gary Madden presented the paper.
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Notes
- 1.
Equation (5.1) is a simplified version of the model estimated by Madden et al. (2016). The model in that study allows the coefficients to vary by income group. This additional source of endogeneity raises new issues for the present prediction problem which have yet to be addressed in the literature. The purpose of the present paper is to assess the predictive content of broadband infrastructure using a standard dynamic panel data model. Hence, (5.1) suffices for the present paper.
- 2.
Chile, Estonia, Israel and Slovenia are not included as they have only joined the OECD in 2010, and this does not cover our period from 2008 to 2012.
- 3.
Under these assumptions, \(\text{cov} (x_{is} ,u_{i} + \varepsilon_{it} )\) depends only on s, while \(\text{cov} (Y_{is} ,u_{i} + \varepsilon_{it} )\) and \(\text{cov} (y_{is} ,u_{i} + \varepsilon_{it} )\) depend only on s and t − s.
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Mayer, W., Madden, G., Dang, X. (2020). Predictive Accuracy Tests for Prediction of Economic Growth Based on Broadband Infrastructure. In: Alleman, J., Rappoport, P., Hamoudia, M. (eds) Applied Economics in the Digital Era. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-40601-1_5
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