We leverage the small open economy Switzerland as a testing ground for basic premises of macroeconomic models of endogenous information acquisition, using tailored surveys of firms and households. First, we show that firms perceive a greater exposure to exchange rate movements than households, which is reflected in higher levels of information acquisition and less dispersed beliefs about past and future exchange rate realizations. Similarly, within the two samples, acquisition of exchange rate information strongly increases in various proxies for stake size. Second, households who perceive higher costs of acquiring or processing information acquire less information. Finally, an exogenous increase in the perceived uncertainty of the exchange rate increases firms' demand for a report about exchange rate developments, but not households'. Our findings inform the modeling of information frictions in macroeconomics.

This paper documents daily compound indicators on physical mobility and sales activity in Switzerland during the Corona crisis. We report several insights from these indicators: The Swiss population substantially reduced its activities already before the shops closed and before the authorities introduced containment policies in mid-March 2020. Activity started to gradually recover from the beginning of April onwards, again substantially before the first phase of the shutdown easing started at the end of April. Low physical mobility during the second half of March and during April likely contributed to the quick fall in new COVID-19 infections since mid-March. The sharp drop in economic activity in consumer-related services during March and April and the gradual recovery in these sectors since May correlates strongly with the reduction and subsequent gradual resurgence of mobility. In addition, while activity within Switzerland was back to normal levels by late June, activity of Swiss residents outside of Switzerland was still below normal.

We argue that membership in International Organizations (IOs) is an important determinant of FDI inflows. To the extent that membership restricts a country from pursuing policies that are harmful to investors, it can signal low political risk. Using data over the 1971-2005 period, we find that membership in IOs does indeed increase inflows of FDI. Controlling for the endogeneity of membership, we find this effect to be substantively important and robust to the method of estimation.

Most macroeconomic series failed to capture the sharp fluctuations during the COVID-19 pandemic. Also, it proved difficult to extract business cycle information from alternative high-frequency data. We present a Bayesian mixed-frequency dynamic factor model with stochastic volatility for measuring GDP growth at high-frequency intervals. Its novelty is an additional state-space block, in which the sparse observations in the mixed-frequency data are augmented to a balanced panel with observed and estimated latent information. The dynamic factor is then estimated conditional on the augmented data. Our model exploits the information in rich datasets well, tracking GDP timely and accurately during volatile periods.

Abstract: Background: Early in the COVID-19 pandemic, it became apparent that members of marginalized populations and immigrants were also at risk of being hospitalized and dying more frequently from COVID-19. To examine how the pandemic affected underserved and marginalized populations, we analyzed data on changes in the number of deaths among people with and without Swiss citizenship during the first and second SARS-CoV-2 waves. Method: We analyzed the annual number of deaths from the Swiss Federal Statistical Office from 2015 to 2020, and weekly data from January 2020 to May 2021 on deaths of permanent residents with and without Swiss citizenship, and we differentiated the data through subdivision into age groups. Results: People without Swiss citizenship show a higher increase in the number of deaths in 2020 than those who were Swiss citizens. The increase in deaths compared to the previous year was almost twice as high for people without Swiss citizenship (21.8%) as for those with it (11.4%). The breakdown by age group indicates that among people between the ages of 64 and 75, those without Swiss citizenship exhibited an increase in mortality (21.6%) that was four times higher than that for people with Swiss citizenship (4.7%). Conclusion: This study confirms that a highly specialized health care system, as is found in Switzerland, does not sufficiently guarantee that all parts of the population will be equally protected in a health crisis such as COVID-19

GDP forecasters face tough choices over which leading indicators to follow and which forecasting models to use. To help resolve these issues, we examine a range of monthly indicators to forecast quarterly GDP growth in a major emerging economy, Russia. Numerous useful indicators are identified and forecast pooling of three model classes (bridge models, MIDAS models and unrestricted mixed-frequency models) are shown to outperform simple benchmark models. We further separately examine forecast accuracy of each of the three model classes. Our results show that differences in performance of model classes are generally small, but for the period covering the Great Recession unrestricted mixed-frequency models and MIDAS models clearly outperform bridge models. Notably, the sets of top-performing indicators differ for our two subsample observation periods (2008Q1-2011Q4 and 2012Q1-2016Q4). The best indicators in the first period are traditional real-sector variables, while those in the second period consist largely of monetary, banking sector and financial market variables. This finding supports the notion that highly volatile periods of recession and subsequent recovery are driven by forces other than those that prevail in more normal times. The results further suggest that the driving forces of the Russian economy have changed since the global financial crisis.