Fernanda Brollo, Emine Hanedar, and Mr. Sébastien Walker
This paper assesses the additional spending required to make substantial progress towards achieving the SDGs in Pakistan. We focus on critical areas of human (education and health) and physical (electricity, roads, and water and sanitation) capital. For each sector, we document the progress to date, assess where Pakistan stands relative to its peers, highlight key challenges, and estimate the additional spending required to make substantial progress. The estimates for the additional spending are derived using the IMF SDG costing methodology. We find that to achieve the SDGs in these sectors would require additional annual spending of about 16 percent of GDP in 2030 from the public and private sectors combined.
This paper is the first attempt to directly explore the long-run nonlinear relationship between the
shadow economy and level of development. Using a dataset of 158 countries over the period from
1996 to 2015, our results reveal a robust U-shaped relationship between the shadow economy size
and GDP per capita. Our results imply that the shadow economy tends to increase when economic
development surpasses a given threshold or at least does not disappear. Our findings suggest that
special attention should be given to the country’s level of development when designing policies to
tackle issues related to the shadow economy.
We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian model averaging (BMA). We find that the posterior probability is distributed among many models, suggesting the superiority of BMA over any single model. Out-of-sample predictive results support that claim. In contrast with Levine and Renelt (1992), our results broadly support the more “optimistic” conclusion of Sala-i-Martin (1997b), namely, that some variables are important regressors for explaining cross-country growth patterns. However, the variables we identify as most useful for growth regression differ substantially from Sala-i-Martin’s results.