Bright Investments: Measuring the Impact of Transport Infrastructure Using Luminosity Data in Haiti

Abstract

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The Impact of Ethiopia'S Road Investment Program on Economic Development and Land Use: Evidence from Satellite Data

“…Faber (2014) finds that highways connecting major metropolitan areas caused a reduction in GDP growth in peripheral counties also connected to the new highways. In addition, Mitnik et al (2018) find that poor communities do not benefit from road improvements, but they also find that the richest communities do not benefit either; namely, gains are concentrated in communities in the middle of a ranking according to unsatisfied basic needs.…”

“…Second, we contribute to the broad literature on the effects of transportation infrastructure. 3 Our analysis is related to that of Mitnik et al (2018), who use nighttime lights as an outcome with a two-way fixed effects approach and find that road rehabilitation in Haiti from 2004 to 2013 leads to increases of 6-26% in luminosity (corresponding to 0.5-2.1% increases in GDP). Similarly, BenYishay et al (2018) evaluate road upgrades in the West Bank using panel data and find a 0.341 increase in absolute luminosity;…”

“…The interpretation is equivalent to that of logarithms. The transformation is defined at zero and provides a way to use a transformation that is suited for cases where there are a large number of zeros (Mitnik et al, 2018).…”

What Works to Improve Lives?: What Works for Transport, Water and Sanitation, and Urban Development

“…These new data types have also made it possible to design evaluations ex-post (Yañez-Pagans et al 2019). For example, satellite data provide opportunities to proxy for economic activity, as seen in the evaluation of road rehabilitation programs in Haiti discussed above (Mitnik, Sanchez, and Yañez-Pagans 2018). The use of cellphone-generated data has also…”

Measuring industrial lumber production using nighttime lights: A focus study on lumber mills in British Columbia, Canada

“…The increased spatial resolution of VIIRS has been shown to allow detection of variable illumination levels based on industrial production [24], and transportation infrastructure [25,26], and employee populations [27] This highlights the potential for NTL to track "boom and bust" cyclical industries, such as forestry which is highly susceptible to international trade regimes and market conditions. Given that NTL has been utilized to detect production trends in other volatile natural resource-based industries including mining, fishing, and oil and gas [28] it has the potential to be applied to forestry production as well.…”