Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty

With the rapid expansion of mobile phone networks in developing countries, large-scale graph machine learning has gained sudden relevance in the study of global poverty. Recent applications range from humanitarian response and poverty estimation to urban planning and epidemic containment. Yet the vast majority of computational tools and algorithms used in these applications do not account for the multi-view nature of social networks: people are related in myriad ways, but most graph learning models treat relations as binary. In this paper, we develop a graph-based convolutional network for learning on multi-view networks. We show that this method outperforms state-of-the-art semi-supervised learning algorithms on three different prediction tasks using mobile phone datasets from three different developing countries. We also show that, while designed specifically for use in poverty research, the algorithm also outperforms existing benchmarks on a broader set of learning tasks on multi-view networks, including node labelling in citation networks

Manipulation-Proof Machine Learning

An increasing number of decisions are guided by machine learning algorithms. In many settings, from consumer credit to criminal justice, those decisions are made by applying an estimator to data on an individual's observed behavior. But when consequential decisions are encoded in rules, individuals may strategically alter their behavior to achieve desired outcomes. This paper develops a new class of estimator that is stable under manipulation, even when the decision rule is fully transparent. We explicitly model the costs of manipulating different behaviors, and identify decision rules that are stable in equilibrium. Through a large field experiment in Kenya, we show that decision rules estimated with our strategy-robust method outperform those based on standard supervised learning approaches

Spectral aerosol optical depth retrievals by ground-based fourier transform infrared spectrometry

Aerosol Optical Depth (AOD) and the Ångström Exponent (AE) have been calculated in the near infrared (NIR) and short-wave infrared (SWIR) spectral regions over a period of one year (May 2019–May 2020) at the high-mountain Izaña Observatory (IZO) from Fourier Transform Infrared (FTIR) solar spectra. The high-resolution FTIR measurements were carried out coincidentally with Cimel CE318-T photometric observations in the framework of the Aerosol Robotic Network (AERONET). A spectral FTIR AOD was generated using two different approaches: by means of the selection of seven narrow FTIR micro-windows (centred at 1020.90, 1238.25, 1558.25, 1636.00, 2133.40, 2192.00, and 2314.20 nm) with negligible atmospheric gaseous absorption, and by using the CE318-AERONET’s response function in the near-coincident bands (1020 nm and 1640 nm) to degrade the high-resolution FTIR spectra. The FTIR system was absolutely calibrated by means of a continuous Langley–Plot analysis over the 1-year period. An important temporal drift of the calibration constant was observed as a result of the environmental exposure of the FTIR’s external optical mirrors (linear degradation rate up to 1.75% month−1). The cross-validation of AERONET-FTIR databases documents an excellent agreement between both AOD products, with mean AOD differences below 0.004 and root-mean-squared errors below 0.006. A rather similar agreement was also found between AERONET and FTIR convolved bands, corroborating the suitability of low-resolution sunphotometers to retrieve high-quality AOD data in the NIR and SWIR domains. In addition, these results demonstrate that the methodology developed here is suitable to be applied to other FTIR spectrometers, such as portable and low-resolution FTIR instruments with a potentially higher spatial coverage. The spectral AOD dependence for the seven FTIR micro-windows have been also examined, observing a spectrally flat AOD behaviour for mineral dust particles (the typical atmospheric aerosols presented at IZO). A mean AE value of 0.53 ± 0.08 for pure mineral dust in the 1020–2314 nm spectral range was retrieved in this paper. A subsequent cross-validation with the MOPSMAP (Modeled optical properties of ensembles of aerosol particles) package has ensured the reliability of the FTIR dataset, with AE values between 0.36 to 0.60 for a typical mineral dust content at IZO of 100 cm$^{−3}$ and water-soluble particle (WASO) content ranging from 600 to 6000 cm$^{−3}$. The new database generated in this study is believed to be the first long-term time series (1-year) of aerosol properties generated consistently in the NIR and SWIR ranges from ground-based FTIR spectrometry. As a consequence, the results presented here provide a very promising tool for the validation and subsequent improvement of satellite aerosol products as well as enhance the sensitivity to large particles of the existing databases, required to improve the estimation of the aerosols’ radiative effect on climate

Subtropical trace gas profiles determined by ground-based FTIR spectroscopy at Izaña (28° N, 16° W): Five-year record, error analysis, and comparison with 3-D CTMs

International audienceWithin the framework of the NDSC (Network for the Detection of Stratospheric Change) ground-based FTIR solar absorption spectra have been routinely recorded at Izaña Observatory (28° N, 16° W) on Tenerife Island since March 1999. By analyzing the shape of the absorption lines, and their different temperature sensitivities, the vertical distribution of the absorbers can be retrieved. Unique time series of subtropical profiles of O3, HCl, HF, N2O, and CH4 are presented. The effects of both dynamical and chemical annually varying cycles can be seen in the retrieved profiles. These include enhanced upwelling and photochemistry in summer and a more disturbed atmosphere in winter, which are typical of the subtropical stratosphere. A detailed error analysis has been performed for each profile. The output from two different three-dimensional (3-D) chemical transport models (CTMs), which are forced by ECMWF analyses, are compared to the measured profiles. Both models agree well with the measurements in tracking abrupt variations in the atmospheric structure, e.g. due to tropical streamers, in particular for the lower stratosphere. Simulated and measured profiles also reflect similar dynamical and chemical annual cycles. However, the differences between their mixing ratios clearly exceed the error bars estimated for the measured profiles. Possible reasons for this are discussed

Quality assessment of ozone total column amounts as monitored by ground-based solar absorption spectrometry in the near infrared (> 3000 cm<sup>−1</sup>)

This study examines the possibility of ground-based remote-sensing ozone total column amounts (OTC) from spectral signatures at 3040 and 4030 cm−1. These spectral regions are routinely measured by the NDACC (Network for the Detection of Atmospheric Composition Change) ground-based FTIR (Fourier transform infraRed) experiments. In addition, they are potentially detectable by the TCCON (Total Carbon Column Observing Network) FTIR instruments. The ozone retrieval strategy presented here estimates the OTC from NDACC FTIR high-resolution spectra with a theoretical precision of about 2 and 5% in the 3040 and 4030 cm−1 regions, respectively. Empirically, these OTC products are validated by inter-comparison to FTIR OTC reference retrievals in the 1000 cm−1 spectral region (standard reference for NDACC ozone products), using an 8-year FTIR time series (2005–2012) taken at the subtropical ozone supersite of the Izaña Atmospheric Observatory (Tenerife, Spain). Associated with the weaker ozone signatures at the higher wave number regions, the 3040 and 4030 cm−1 retrievals show lower vertical sensitivity than the 1000 cm−1 retrievals. Nevertheless, we observe that the rather consistent variations are detected: the variances of the 3040 cm−1 and the 4030 cm−1 retrievals agree within 90 and 75%, respectively, with the variance of the 1000 cm−1 standard retrieval. Furthermore, all three retrievals show very similar annual cycles. However, we observe a large systematic difference of about 7% between the OTC obtained at 1000 and 3040 cm−1, indicating a significant inconsistency between the spectroscopic ozone parameters (HITRAN, 2012) of both regions. Between the 1000 cm and the 4030 cm−1 retrieval the systematic difference is only 2–3%. Finally, the long-term stability of the OTC retrievals has also been examined, observing that both near-infrared retrievals can monitor the long-term OTC evolution, consistent with the 1000 cm−1 reference data. These findings demonstrate that recording the solar absorption spectra in the 3000 cm−1 spectral region at high spectral resolution (about 0.005 cm−1) might be useful for TCCON sites. Hence, both NDACC and TCCON ground-based FTIR experiments might contribute to global ozone databases

Promises and Pitfalls of Mobile Money in Afghanistan: Evidence from a Randomized Control Trial

ABSTRACT Despite substantial interest in the potential for mobile money to positively impact the lives of the poor, little empirical evidence exists to substantiate these claims. In this paper, we present the results of a field experiment in Afghanistan that was designed to increase adoption of mobile money, and determine if such adoption led to measurable changes in the lives of the adopters. The specific intervention we evaluate is a mobile salary payment program, in which a random subset of individuals of a large firm were transitioned into receiving their regular salaries in mobile money rather than in cash. We separately analyze the impact of this transition on both the employer and the individual employees. For the employer, there were immediate and significant cost savings; in a dangerous physical environment, they were able to effectively shift the costs of managing their salary supply chain to the mobile phone operator. For individual employees, however, the results were more ambiguous. Individuals who were transitioned onto mobile salary payments were more likely to use mobile money, and there is evidence that these accounts were used to accumulate small balances that may be indicative of savings. However, we find little consistent evidence that mobile money had an immediate or significant impact on several key indicators of individual wealth or well-being. Taken together, these results suggest that while mobile salary payments may increase the efficiency and transparency of traditional systems, in the short run the benefits may be realized by those making the payments, rather than by those receiving them