This paper addresses a general problem with the use of surveys as source of information about the state of an economy: Answers to surveys are highly dependent on information that is publicly available, while only additional information that is not already publicly known has the potential to improve a professional forecast. We propose a simple procedure to disentangle the private information of agents from knowledge that is already publicly known for surveys that ask for general as well as for private prospects. Our results reveal the potential of our proposed technique for the usage of European Commissions‘ consumer surveys for economic forecasting for Germany.

This paper studies whether and how banks‘ technology adoption affects the bank lending channel of monetary policy transmission. We construct a new measurement of bank-level technology adoption, which can tell whether the technology is related to the bank‘s lending business and which specific technology is adopted. We find that lending-related technology adoption significantly strengthens the transmission of the bank lending channel, meanwhile, adopting technologies that are not related to lending activities significantly mitigates that. By technology categories, the adoption of cloud computing technology displays the largest impact on strengthening the bank lending channel. Moreover, higher exposure to BigTech competition is significantly associated with a weaker reaction to monetary policy shocks.

By focusing on the episodes of substantial capital account liberalisation and adopting a new methodology, this paper provides new evidence on the dilemma and global financial cycle theory. I first identify the capital account liberalisation episodes for 95 countries from 1970 to 2016, and then employ an augmented inverse propensity score weighted (AIPW) estimator to calculate the average treatment effect (ATE) of opening capital account on the interest rate comovements with the core country. Results show that opening capital account causes a country to lose its monetary policy independence, and a floating exchange rate regime cannot shield this effect. Moreover, the impact is stronger when liberalising outward and banking flows.

We investigate U.S. monetary and fiscal policy interactions in a regime-switching model of monetary and fiscal policy rules where policy mixes are determined by a latent bivariate autoregressive process consisting of monetary and fiscal policy regime factors, each determining a respective policy regime. Both policy regime factors receive feedback from past policy disturbances, and interact contemporaneously and dynamically to determine policy regimes. We find strong feedback and dynamic interaction between monetary and fiscal authorities. The most salient features of these interactions are that past monetary policy disturbance strongly influences both monetary and fiscal policy regimes, and that monetary authority responds to past fiscal policy regime. We also find substantial evidence that the U.S. monetary and fiscal authorities have been interacting: central bank responds less aggressively to inflation when fiscal authority puts less attention on debt stabilisation, and vice versa.

Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.