Volume 75, Issue 1

The HWWI Commodity Price Index, which aims at reflecting price developments of raw materials imported by highly industrialized countries, dates back to the 1950s. This paper explains the calculation of the index at the example of its latest revision, which became effective on 1st September 2023. While the index and its subindices are still calculated for OECD and European Momentary Union countries at four different frequencies (annual, monthly, quarterly and daily) for two different currencies (USD, EUR), it now additionally includes index values for several weighting periods (long-term: 2012–2021, pre-crisis: 2017–2019 and crisis years: 2020–2021), for individual countries and for different perspectives (daily revised, real-time and historical time series). The paper also provides detailed information on the employed methodology and the input data (commodities, import data, prices) used to calculate the weights and the index values. Although the revision is not without effect on the resulting index values, especially throughout the crises periods, the correlation between the initial and the revised index remains very high.

This paper uses an augmented gravity model framework to investigate the historical impact of infectious diseases on international tourism and develops an out-of-sample prediction model. Using bilateral tourism flows among 38,184 pairs of countries during the period 1995–2017, I compare the forecasting performance of alternative specifications and estimation methods. These computations confirm the statistical and economic significance of infectious-disease episodes in forecasting international tourism flows. Including infectious diseases in the model brings a significant improvement in forecast accuracy relative to the standard gravity model. The magnitude of these effects, however, is likely to be much greater in the case of COVID-19, which is a highly contagious virus that has spread fast throughout populations across the world.

Japan and Germany are both facing a rapidly aging population and have similar social insurance-based long-term care systems. However, there are significant differences in utilization and costs. This paper presents a microeconomic decision model validated by regression analysis, Blinder-Oaxaca decomposition, and Data Envelopment Analysis to contrast the utilization patterns in the Japanese and German long-term care sectors. The design of the welfare programs for low-income families has been identified as one of the main reasons. In Germany, the welfare system leads to a demand curve for nursing home care that is comparable to that of an inferior good which makes external long-term care in nursing homes the more attractive, the poorer the respective households are. In addition, the resulting inelastic demand of the population groups in need of social benefits seem to reduces competition among Germany’s long-term care providers, which is associated with a loss of efficiency in how they use production factors. In Japan, this negative outcome is avoided by a comfort segmentation in the nursing home market.

This paper uses firm level data from the World Bank Enterprise surveys conducted in 2019 and from the COVID-19 follow-up surveys conducted in 2020 in eight European countries to investigate the link between exporting before the pandemic and firm survival until 2020. The estimated effect of exports is positive and statistically significant ceteris paribus after controlling for various firm characteristics that are known to be related to firm survival. Furthermore, the size of this estimated effect can be considered to be large on average. Exporting helped firms to survive.