NYU Stern

Urgent Grants

Grant applications are typically reviewed twice a year. However, if a project would be unduly delayed by waiting for the next funding deadline, group coordinators may decide to review an application submitted between funding review dates.

The following grants have been awarded under an urgent review process.

Urgent Grants
Resulting Papers and Materials
  • Allan Collard-Wexler Abstract:
    his paper studies the role of technology and competition in industry-wide productivity growth. We rely on a unique producer-level dataset covering U.S. steel producers between 1963 and 2002 to measure the impact of a drastic new production technology, the minimill, on aggregate productivity. We find that minimills were on average 11% more productive than the old vertically integrated technology. Moving output from vertically integrated producers to minimills accounts for 27% of the productivity gains in this industry. While the new technology started out with a significant productivity premium by 2002 minimills and vertically integrated producers have similar efficiency. However virtually all of the catch-up is due to the exit of vertically integrated producers of bar products who competed in the same product segments as minimills. This additional selection and reallocation effect accounts for a further 40% of productivity gains over the period.

  • Matteo Maggiori
    • New Estimates of Currency Returns
    The dataset provides currency returns at monthly and quarterly horizon for 53 currencies for the period 1973-2010. The returns are decomposed into the exchange rate movement and the interest rate differential. The data are built from a variety of public and proprietary sources. The methodology used to build the data is discussed in detail to facilitate adaptations for various research needs. The quality of each data source, including those previously used in the literature, is reviewed in detail. The dataset improves the data currently available for research along three dimensions: the time span, the number of currencies covered and the quality of the time series.