"The Great Depression of the 1930s and the Great Credit Crisis of the 2000s had similar causes but elicited strikingly different policy responses. While it remains too early to assess the effectiveness of current policy, it is possible to analyse monetary and fiscal responses in the 1930s as a natural experiment or counterfactual capable of shedding light on the impact of current policies. We employ vector autoregressions, instrumental variables, and qualitative evidence for 27 countries in the period 1925-39. The results suggest that monetary and fiscal stimulus was effective -- that where it did not make a difference it was not tried. They shed light on the debate over fiscal multipliers in episodes of financial crisis. They are consistent with multipliers at the higher end of those estimated in the recent literature, and with the argument that the impact of fiscal stimulus will be greater when banking systems are dysfunctional and monetary policy is constrained by the zero bound." Copyright (c) CEPR, CES, MSH, 2010.

The Great Depression of the 1930s and the Great Credit Crisis of the 2000s had similar causes but elicited strikingly different policy responses. It may still be too early to assess the effectiveness of current policy responses, but it is possible to analyze monetary and fiscal policies in the 1930s as a "natural experiment" or "counterfactual" capable of shedding light on the impact of recent policies. We employ vector autoregressions, instrumental variables, and qualitative evidence for a panel of 27 countries in the period 1925-1939. The results suggest that monetary and fiscal stimulus was effective -that where it did not make a difference it was not tried. The results also shed light on the debate over fiscal multipliers in episodes of financial crisis. They are consistent with multipliers at the higher end of those estimated in the recent literature, consistent with the idea that the impact of fiscal stimulus will be greater when banking system are dysfunctional and monetary policy is constrained by the zero bound.

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This paper uses a newly constructed, comprehensive dataset to investigate the diffusion of containerization. The data show that country adoption is exceptionally fast while firm usage increases more slowly. To guide my empirical investigation, I build a multi-country trade model with endogenous adoption of a new transportation technology that is consistent with these facts. I then test empirically the predictions of the model and find that: (1) usage of containerization increases with firms' fixed costs and the size and average income of the container network; and (2) adoption depends on expected future usage, adoption costs, and trade with the United States, the first and largest user of containerization.