This paper studies the impact of immigration on the US macroeconomy. I identify structural vector autoregressions (SVARs) with time-varying parameters (TVPs) and stochastic volatility (SV) using a novel set of restrictions. The TVP-SV-SVARs are estimated on a quarterly sample including average labor productivity (ALP), hours worked, immigration, consumption, and term spread from 1953 to 2017. An immigration supply shock increases domestic ALP and hours worked over the business cycle horizons. Movements in immigration are explained by its own shock and to a lesser extent by the productivity and news shocks. IRFs driven by these shocks vary over the sample, especially around changes in immigration policy such as the Immigration Act of 1990. In contrast, the forecast error variance decompositions exhibit little change over the sample. Immigration plays an important role in the US macroeconomy.

In this paper, we identify the technology shock at business cycle frequencies to improve the performance of structural vector autoregression models in small samples. To this end, we propose a new identification method based on the spectral decomposition of the variance, which targets the contributions of the shock in theoretical models. Results from a Monte-Carlo assessment show that the proposed method can deliver a precise estimate of the response of hours in small samples. We illustrate the application of our methodology using US data and a standard Real Business Cycle model. We find a positive response of hours in the short run following a non-significant, near-zero impact. This result is robust to a large set of credible parameterizations of the theoretical model.

We study the main shocks driving current account (CA) fluctuations for the G6 economies, using a standard two-good intertemporal model. We build a structural vector autoregression model including the world real interest rate, net output (NO), the real exchange rate, and the CA and identify four structural shocks. Our results suggest four main conclusions: (i) there is substantial support for the two-good intertemporal model with time-varying interest rate, since both external supply and preference shocks account for an important proportion of CA fluctuations; (ii) temporary domestic shocks account for a large proportion of CA fluctuations, albeit smaller than in previous studies; (iii) our results alleviate the puzzle in the literature that a shock that explains little about NO changes can explain a large proportion of CA changes; (iv) the nature of the shock matters to shape the relationship between the CA and the real exchange rate.

Using a structural vector autoregressive (SVAR) model, this paper provides deeper insight into unemployment dynamics in Germany. We identify a technology shock and two policy shocks that play a central role in business cycle research. Accordingly, we enrich the discussion on the sources of unemployment dynamics by considering demand-side impulses. The worker reallocation process varies substantially with the identified shocks. The job-finding rate plays a larger role after a technology shock and a monetary policy shock, whereas the separation rate appears to be the dominant margin after a fiscal policy shock. Technology shocks turn out to be relatively important for variations in the transition rates. Regarding policy shocks, our results point toward fiscal interventions as a promising instrument but with several limitations.

This paper provides long-run evidence on the dynamic effects of supply and demand shocks on commodity prices. I assemble and analyze a new data set of price and production levels of copper, lead, tin, and zinc from 1840 to 2014. Using a novel approach to identification, I show that price fluctuations are primarily driven by demand, rather than supply shocks. Demand shocks affect the price for up to 15 years, whereas the effect of mineral supply shocks persists for up to 5 years. Price surges caused by rapid industrialization are a recurrent phenomenon throughout history. Mineral commodity prices return to their declining or stable trends in the long run.