Pollution and Expenditures in a Penalized Vector Spatial Autoregressive Time Series Model with Data-Driven Networks

Abstract

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Machine Learning Guided Outlook of Global Food Insecurity Consistent with Macroeconomic Forecasts

“…. This is a measure of similarity between Z i and Z j for any nz > 0 (Andrée et al, 2019b;Andrée, 2020). This can be used to construct a matrix:…”

“…The exact approach is as follows. A Gaussian Kernel is used to calculate similarities between countries which can be expressed as an N × N contiguity matrix followingAndrée et al (2019b);Andrée (2020) based on a set of other covariates over which similarity is calculated.31 Missing country series are imputed by taking the average series of 4 countries that are most similar in terms of Child Mortality Rates, Life Expectancy, GDP ppp per capita, GDP, the share of Agriculture in GDP, and country coordinates. Whenever more than 5 observations are missing for a country, but some data is available, this 4-nearest neighbor average is indexed and used to extrapolate the observed data.…”