In this paper, I have used a novel dataset of loan-level transactions covering lending by official
creditors to developing country governments to estimate government spending multipliers. My
identification strategy exploits the substantial lags that occur between loan commitment and the
eventual full disbursement of the loan, a process which typically takes several years. The key identifying
assumption is that loan approvals, and the decision to embark on the associated spending plans, do not
anticipate future shocks to growth. Given this assumption, fluctuations in disbursements that are
attributable to fluctuations in past loan approval decisions are plausibly exogenous to contemporaneous
shocks, and can be used as an instrument for fluctuations in government spending. Deploying this
strategy in a large sample of developing countries, I find reasonably precise estimates of the
government spending multiplier that are in the vicinity of 0.4. These results survive a range of
robustness checks designed to address concerns about data quality and potential violations of the
exclusion restriction. I find some evidence of heterogeneity in estimated multipliers that is consistent
with the implications of basic theories. However, these differences typically are not statistically