This paper brings the aid effectiveness debate to the sub-national level. We hypothesize the nonrobust
results regarding the effects of aid on development in the previous literature to arise due to
the effects of aid being insufficiently large to measurably affect aggregate outcomes. Using geocoded
data for World Bank aid to a maximum of 2,221 first-level administrative regions (ADM1)
and 54,167 second-level administrative regions (ADM2) in 130 countries over the 2000-2011
period, we test whether aid affects development, measured as nighttime light growth. Our
preferred identification strategy exploits variation arising from interacting a variable that indicates
whether or not a country has passed the threshold for receiving IDA's concessional aid with a
recipient region's probability to receive aid, in a sample of 478 ADM1 regions and almost 8,400
ADM2 regions from 21 countries. Controlling for the levels of the interacted variables, the
interaction provides a powerful and excludable instrument. Overall, we find significant
correlations between aid and growth in ADM2 regions, but no causal effects.
Mark Agerton, Peter Hartley, Kenneth Medlock III, and Ted Temzelides
Technological progress in the exploration and production of oil and gas during the 2000s has led to a boom in upstream investment and has increased the domestic supply of fossil fuels. It is unknown, however, how many jobs this boom has created. We use time-series methods at the national level and dynamic panel methods at the state-level to understand how the increase in exploration and production activity has impacted employment. We find robust statistical support for the hypothesis that changes in drilling for oil and gas as captured by rig-counts do in fact, have an economically meaningful and positive impact on employment. The strongest impact is contemporaneous, though months later in the year also experience statistically and economically meaningful growth. Once dynamic effects are accounted for, we estimate that an additional rig-count results in the creation of 37 jobs immediately and 224 jobs in the long run, though our robustness checks suggest that these multipliers could be bigger.
We propose a coherent unified approach to the study of the linkages among economic growth, financial structure, and inequality, bringing together disparate theoretical and empirical literature. That is, we show how to conduct model-based quantitative research on transitional paths. With analytical and numerical methods, we calibrate and make tractable a prototype canonical model and take it to an application, namely, Thailand 1976-1996, an emerging economy in a phase of economic expansion with uneven financial deepening and increasing inequality. We broadly replicate the actual data, test the model formally, and identify anomalies.