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Victor Musa, Bertrand Gilles Umba, Lewis Mambo, Jonas Kibala, Christian Kandolo, Josephine Mushiya, Yannick Luvezo, Jules Nsunda, Grégoire Lumbala, Yves Siasi, Serge Mfumukanda, Lubaki Ange, Kabata Olivier, Luc Shindano, Dyna Heng, Diego Rodriguez Guzman, and Barna Szabo
Euihyun Bae, Andrew Hodge, and Anke Weber
This paper studies how and why inflation expectations have changed since the emergence of Covid-19. Using micro-level data from the University of Michigan Survey of Consumers, we show that the distribution of consumer expectations at one-year and five-ten year horizons has widened since the surge of inflation during 2021, along with the mean. Persistently high and heterogeneous expectations of consumers with less education and lower income are mainly responsible. A simple model of adaptive learning is able to mimic the change in inflation expectations over time for different demographic groups. The inflation expectations of low income and female consumers are consistent with using less complex forecasting models and are more backward-looking. A medium-scale DSGE model with adaptive learning, estimated during 1965-2022, has a time-varying solution that produces lower forecast errors for inflation than a variant with rational expectations. The estimated model interprets the surge of inflation in 2021 mainly as the result of a price markup shock, which is more persistent and requires a larger and more persistent monetary policy response than under rational expectations.
International Monetary Fund. Monetary and Capital Markets Department
This Technical Assistance (TA) report analyzes expanding the nowcasting toolbox at the National Bank of Rwanda (NBR). The mission built on the progress made during the March 2022 mission, which focused on improving the nowcasting framework for the key domestic variables and building tools for analyzing new data releases and assessing the nowcasting systems. The TA should continue to focus on the developments of the nowcasting framework for inflation and gross domestic product (GDP). Specifically, the new consumer price index (CPI) and GDP Near-Term Forecast (NTF) tools should be used on a monthly basis as part of the forecasting process and Forecasting and Policy Analysis System work at the NBR. The new CPI NTF system now includes the monthly forecasts of ten subgroups of the core CPI inflation as well as two subgroups of food inflation, thus enabling the assessment of the key drivers of inflation as well as the nature of inflation shocks. It also allows for the ‘real time’ monitoring of monthly inflation outcomes relative to the forecast.