WORKING PAPERS
Speaking of Inflation: The Influence of FED Speeches on Expectations (with V. H. Larsen, G. Meggiorini and L. Melosi) submitted NB wp FT coverage
We examine how speeches by Federal Open Market Committee (FOMC) members, including regional Fed presidents, shape private sector expectations. Speeches that signal rising inflationary pressures prompt both households and professional forecasters to raise their inflation expectations, consistent with Delphic effects. Only professional forecasters respond to Odyssean communications statements about the Fed’s intended policy response - leaving Delphic effects as the dominant channel for households. These household responses are driven by speeches from regional presidents, likely due to greater visibility in regional media coverage. A general equilibrium model, featuring agents who differ in their ability to interpret Odyssean signals, explains this heterogeneity.
Five Facts About Inflation Expectations: Evidence from Four Different Groups of Agents (with L. Reiche, N. Maffei-Faccioli, M. Weber and T. Fastbø) NB blog
We investigate how education shapes households' macroeconomic beliefs by surveying Dutch households on their perceptions and forecasts of inflation, unemployment, mortgage rates, and stock prices. Our findings unveil significant differences between highly-educated and less-educated households. Highly educated respondents form beliefs consistent with a monetary policy trade-off between inflation and unemployment, whereas less-educated households adopt a "supply-side" perspective. When exposed to vignette-based scenarios simulating monetary policy shocks, highly educated individuals adjust their beliefs and consumption-saving decisions in line with intertemporal substitution and textbook economic models. In contrast, less-educated respondents often retain pre-existing beliefs or revise them using non-standard mental models. Moreover, highly educated households primarily rely on formal education and newspapers for economic information, while less-educated households are more influenced by social media. These findings point to the need to model education-related heterogeneity and communicate policy targets and decisions in a simplified manner to reach different socio-economic groups.
Households' Macroeconomic Beliefs: The Role of Education (with J. Piccolo, A. Russo and E. Castelnuovo)
We investigate how education shapes households' macroeconomic beliefs by surveying Dutch households on their perceptions and forecasts of inflation, unemployment, mortgage rates, and stock prices. Our findings unveil significant differences between highly-educated and less-educated households. Highly educated respondents form beliefs consistent with a monetary policy trade-off between inflation and unemployment, whereas less-educated households adopt a "supply-side" perspective. When exposed to vignette-based scenarios simulating monetary policy shocks, highly educated individuals adjust their beliefs and consumption-saving decisions in line with intertemporal substitution and textbook economic models. In contrast, less-educated respondents often retain pre-existing beliefs or revise them using non-standard mental models. Moreover, highly educated households primarily rely on formal education and newspapers for economic information, while less-educated households are more influenced by social media. These findings point to the need to model education-related heterogeneity and communicate policy targets and decisions in a simplified manner to reach different socio-economic groups.
WORK IN PROGRESS
Cross-Check of Economic Forecasts (with F. Bowe and P. Ulvedal)
When People Don't Believe the Inflation Target (with S. Ahn and T. Fastbø)
PUBLISHED PAPERS
Nowcasting Norwegian Household Consumption with Debit Card Transaction Data (with Knut Are Aastveit, Tuva M. Fastbø, Kenneth S. Paulsen and Kjersti N. Torstensen) - Journal of Applied Econometrics, (2024)
We use a novel data set covering all domestic debit card transactions in physical terminals by Norwegian households, to nowcast quarterly Norwegian household consumption. These card payments data are free of sampling errors and are available weekly without delays, providing a valuable early indicator of household spending. To account for mixed-frequency data, we estimate various mixed-data sampling (MIDAS) regressions using predictors sampled at monthly and weekly frequency. We evaluate both point and density forecasting performance over the sample 2011Q4-2020Q1. Our results show that MIDAS regressions with debit card transactions data improve both point and density forecast accuracy over competitive standard benchmark models that use alternative high-frequency predictors. Finally, we illustrate the benefits of using the card payments data by obtaining a timely and relatively accurate nowcast of the first quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic. NB wp
The Bias of the ECB Inflation Projections: a State Dependent Analysis, (with P. Jalasjoki and M. Paloviita) Journal of Forecasting, (2024)
We test for state-dependent bias in the European Central Bank’s inflation projections. We show that the ECB tends to underpredict when the observed inflation rate at the time of forecasting is higher than an estimated threshold of 1.8%. The bias is most pronounced at intermediate forecasting horizons. This suggests that inflation is projected to revert towards the target too quickly. These results cannot be fully explained by the persistence embedded in the forecasting models nor by errors in the exogenous assumptions on interest rates, exchange rates or oil prices. The state-dependent bias may be consistent with the aim of managing inflation expectations, as published forecasts play a central role in the ECB’s monetary policy communication strategy. NB wp
Bonds Currencies and Expectational Errors (with M. Sihvonen) - Journal of Economic Dynamics and Control, (2024) vol. 158
We propose a model in which sticky expectations concerning short-term interest rates generate joint predictability patterns in bond and currency markets. Using our calibrated model, we quantify the effect of this channel and find that it largely explains why short rates and yield spreads predict bond and currency returns. The model also creates the downward sloping term structure of carry trade returns documented by Lustig et al. (2019), difficult to replicate in a rational expectations framework. Consistent with the model, we find that variables that predict bond and currency returns also predict survey-based expectational errors concerning interest and FX rates. The model explains why monetary policy induces drift patterns in bond and currency markets and predicts that long-term rates are a better gauge of market's short rate expectations than previously thought.
State Dependence of Monetary Policy Across Business, Credit and Interest Rate Cycles (with Sami Alpanda and Sarah Zubairy) - European Economic Review, (2021) vol. 140
We study how phases of the business, credit and interest rate cycles affect the transmission of monetary policy using state-dependent local projection methods and data from 18 advanced economies. We find that the impact of monetary policy shocks on output and other macroeconomic and financial variables is weaker during periods of economic downturns, high household debt, and high interest rates. We then build a small-scale theoretical model to rationalize these facts. The model points to the presence of collateral and debt-service constraints on household borrowing and refinancing as potential drivers of state dependence of monetary policy with respect to the business, credit, and interest rate cycles. Our findings bear significant implications for the transmission of monetary policy and highlight potentially important features to be considered in models used to inform monetary policy decisions.
Predicting Relative Forecasting Performance: an Empirical Investigation (with Tatevik Sekhposyan) - International Journal of Forecasting (2019) vol. 35, 1636-1657
The relative performance of forecasting models is known to be unstable over time. However, it is not well understood why the forecasting performance of economic models change. We propose to address this question by evaluating the predictive ability of a wide range of economic variables for key U.S. macroeconomic aggregates: output growth and inflation. We take a conditional view on this issue, identifying situations where particular kind of models perform better than simple benchmarks. We, therefore, test whether the relative forecasting performance of models depend on the state of the business cycle, financial conditions, uncertainty or measures of past relative performance. We then investigate whether the conditioning variables help us predict the more accurate forecasting model for a specific future date. In particular, we analyze whether using the conditional performance as a model selection or model averaging criteria can improve the accuracy of the predictions. The proposed strategies deliver sizable improvements especially when the relative performance is predicted using financial variables.
Inference for VARs Identified with Sign Restrictions (with H. Roger Moon and Frank Schorfheide) - Quantitative Economics (2018) vol. 9, 1087-1121
There is a fast growing literature that set-identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variables to a particular structural shock (sign-restricted SVARs). Most methods that have been used to construct error bands for impulse responses of sign-restricted SVARs are justified only from a Bayesian perspective. This paper demonstrates how to formulate the inference problem for sign-restricted SVARs within a moment-inequality framework. In particular, it develops methods of constructing error bands for impulse response functions of sign-restricted SVARs that are valid from a frequentist perspective. The paper also provides a comparison of frequentist and Bayesian error bands in the context of an empirical application - the former can be substantially wider than the latter.
Monetary Policy, Private Debt and Financial Stability Risks (with Greg H. Bauer) - International Journal of Central Banking (2017) vol.13, 337-373
Can monetary policy be used to promote financial stability? We answer this question by estimating the impact of a monetary policy shock on the private sector leverage and the likelihood of a financial crisis. Impulse responses obtained from a panel VAR of eighteen advanced countries suggest that the debt-to-GDP ratio rises in the short run following an unexpected tightening in monetary policy. As a consequence, the likelihood of a financial crisis increases, as estimated from a panel logit regression. However, in the long run output recovers and higher borrowing costs discourage new lending, leading to a deleveraging of the private sector. A lower debt-to-GDP ratio in turn reduces the likelihood of a financial crisis. These results suggest that monetary policy can achieve a less risky financial system in the long run but could fuel financial instability in the short run. We also find that the ultimate effects of a monetary policy tightening on the probability of a financial crisis depend on the leverage of the private sector: the higher the initial value of the debt-to-GDP ratio, the more beneficial the monetary policy intervention in the long run, but the more destabilizing in the short run.
House Price Dynamics: Fundamentals and Expectations (with Sharon Kozicki) - Journal of Economic Dynamics and Control (2015) vol.60, 152-165
We investigate whether expectations that are not fully rational have the potential to explain the evolution of house prices and the price-to-rent ratio in the United States. First, a stylized asset-pricing model solved under rational expectations is used to derive a fundamental value for house prices and the price-rent ratio. Although the model can explain the sample average of the price-rent ratio, it does not generate the volatility and persistence observed in the data. Then, we consider a rational bubble solution, an extrapolative expectations solution and a near rational bubble solution. In this last solution, agents extrapolate the future from the latest realization and the degree of extrapolation is stronger in good times than in bad times, generating waves of over-optimism. We show that under this solution the model not only is able to match key moments of the data but can also replicate the run up in the U.S. house prices observed over the 2000-2006 period and the subsequent sharp downturn.
A Predictability Test for a Small Number of Nested Models (with Kirstin Hubrich and H. Roger Moon) - Journal of Econometrics (2014) vol.182, 174-185
We introduce quasi-likelihood ratio tests for one sided multivariate hypotheses to evaluate the null that a parsimonious model performs equally well as a small number of models which nest the benchmark. The limiting distributions of the test statistics are non-standard. For critical values we consider: (i) bootstrapping and (ii) simulations assuming normality of the mean square prediction error difference. The proposed tests have good size and power properties compared with existing equal and superior predictive ability tests for multiple model comparison. We apply our tests to study the predictive ability of a Phillips curve type for the US core inflation.