Related fields:
International Macroeconomics
Time Series Econometrics
This paper quantifies the importance of commodity import and export price shocks as a source of business cycles for 28 emerging and developing economies, and tests whether there exists a disconnect between theory and empirics on this question. Empirical findings using a SVAR model suggest that these shocks explain on average 26-30% of business-cycle fluctuations in the selected countries. However, according to theoretical predictions using a new RBC model featuring commodity importable and exportable sectors, these shocks can only explain on average 2-3% of business-cycle fluctuations. Finally, a comparative exercise suggests that at the country level, there is a weakly negative to zero correlation between the importance of these shocks predicted by the SVAR and RBC models. In conclusion, the predictions of the SVAR and RBC models are disconnected both on average and at the country level.
Related fields:
International Economics
Time Series Econometrics
R Programming
The estimation of impulse responses to shocks across multiple units (countries/regions/firms, etc.) is usually of interest in the international economics literature. One commonly faced challenge is that the limited time series dimension of the data undermines the precision of unit-specific impulse responses. Researchers often resort to panel regression estimation to exploit cross-sectional variation and shrink standard errors. However, the extensive homogeneity restrictions imposed by panel regressions can usually not be justified. This paper attempts to generalize, extend, and build an R package for a strategy described in Berg, Curtis, and Mark (2023) to shrink unit-specific impulse response standard errors in the context of local projection estimations.
This paper analyzes the potential repercussions of the Russia-Ukraine war on 44 African countries using a global vector autoregressive model. Focusing on the unexpected rise in global prices for food, oil, and fertilizers triggered by the war, we simulate the effects of these shocks on commodity terms of trade, consumer price inflation, real GDP, and the domestically deflated dollar exchange rate. Our findings suggest that most African countries will face a deterioration in commodity terms of trade, inflationary pressures, a decline in real GDP, and reduced domestic purchasing power of the U.S. dollar, with the effects potentially lasting beyond 3 years. The study reveals Africa’s vulnerability to global commodity price swings but also highlights the opportunity for the continent to reduce its dependence on imports and promote self-sufficiency in critical sectors.
Many low-income countries (LICs), especially in sub-Saharan Africa, are commodity dependent. Commodity terms-of-trade volatility poses a challenge for monetary policy in these countries, as it has important effects on domestic inflation, among other things. For LICs belonging to monetary unions, like WAEMU and CEMAC, the impossibility of resorting to exchange rate adjustments makes the monetary policy response to such shocks even more complicated. This project explores the optimal monetary policy in the presence of commodity terms-of-trade shocks in a monetary union, with application to WAEMU and CEMAC.