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We propose a new source of cross-sectional variation that may identify causal impacts of government spending on the economy. We use the fact that a large number of federal spending programs depend on local population levels. Every ten years, the Census provides a count of local populations. Since a different method is used to estimate non-Census year populations, this change in methodology leads to variation in the allocation of billions of dollars in federal spending. Our baseline results follow a treatment-effects framework where we estimate the effect of a Census Shock on federal spending, income, and employment growth by re-weighting the data based on an estimated propensity score that depends on lagged economic outcomes and observed economic shocks. Our estimates imply a local income multiplier of government spending between 1.7 and 2, and a cost per job of $30,000 per year. A complementary IV estimation strategy yields similar estimates. We also explore the potential for spillover effects across neighboring counties but we do not find evidence of sizable spillovers. Finally, we test for heterogeneous effects of government spending and find that federal spending has larger impacts in low-growth areas.

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China has experienced rapid economic growth over the past two decades and is on the brink of eradicating poverty. However, income inequality increased sharply from the early 1980s and rendered China among the most unequal countries in the world. This trend has started to reverse as China has experienced a modest decline in inequality since 2008. This paper identifies various drivers behind these trends – including structural changes such as urbanization and aging and, more recently, policy initiatives to combat it. It finds that policies will need to play an important role in curbing inequality in the future, as projected structural trends will put further strain on equity considerations. In particular, fiscal policy reforms have the potential to enhance inclusiveness and equity, both on the tax and expenditure side.

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