Research

Hubrich, Kirstin and Frauke Skudelny (2017), ‘Forecast combination for euro area inflation - A cure in times of crisis?’, Journal of Forecasting, 36: 515 - 540

We investigate whether forecast combination does help improving forecast accuracy of inflation models in times of crises and investigate performance based weighting can outperform the simple average. Overall, we find that, first, forecast combination helps hedge against bad forecast performance and, second, that performance-based weighting tends to outperform simple averaging.

We use novel disaggregate sectoral‐regional euro‐area data to investigate the sources of price changes, introducing a new method to extract factors from overlapping data blocks that allows for estimation of aggregate, sectoral, country‐specific and regional components of price changes. Our sectoral component explains much less variation in disaggregate inflation rates and exhibits much less volatility and more persistence than previous findings for the US indicate. Country‐ and region‐specific factors play an important role, emphasizing heterogeneity of inflation dynamics along both sectoral and geographical dimensions. Our results are incompatible with basic sticky‐information or Calvo‐type price‐setting models, but require multi‐sector, multi‐country models.

Hubrich, Kirstin and Simone Manganelli (2014), Discussion of 'Central Bank Macroeconomic Forecasting during the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiences' by L. Alessi, E. Ghysels, L. Onorante, R. Peach, S. Potter, Journal of Business and Economic Statistics, Vol. 32, Issue 4: 506-509

Granziera, Elenora, Kirstin Hubrich and Roger Moon (2014), ‘A predictability test for a small number of nested models’, Journal of Econometrics, 182(1): 174-185, 2014

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.

Hubrich, Kirstin and Timo Teräsvirta (2013), ‘Thresholds and smooth transitions in vector autoregressive models’, Advances in Econometrics “VAR Models in Macroeconomics, Financial Econometrics, and Forecasting”, Vol. 31: 273-326, 2013 (link to CREATES Working Paper Version)

This survey focuses on two families of nonlinear vector time series models, the family of Vector Threshold Regression models and that of Vector Smooth Transition Regression models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary Vector Threshold Regression and Vector Smooth Transition Regression models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.

Working Papers

Kirstin Hubrich and Dan Waggoner (2022), ‘The transmission of financial shocks and the leverage of financial institutions: An endogenous regime switching framework’ , Finance and Economics Discussion Series, Federal Reserve Board

We conduct a novel empirical analysis of the role of leverage of financial institutions for the transmission of financial shocks to the macroeconomy. For that purpose we develop an endogenous regime-switching structural vector autoregressive model with time-varying transition probabilities that depend on the state of the economy. We propose new identification techniques for regime switching models. Recently developed theoretical models emphasize the role of bank balance sheets for the build-up of financial instabilities and the amplification of financial shocks. We build a market-based measure of leverage of financial institutions employing institution-level data and find empirical evidence that real effects of financial shocks are amplified by the leverage of financial institutions in the financial-constraint regime. We also find evidence of heterogeneity in how financial institutions, including depository financial institutions, global systemically important banks and selected nonbank financial institutions, affect the transmission of shocks to the macroeconomy. Our results confirm the leverage ratio as a useful indicator from a policy perspective.

Fulton, Chad and Kirstin Hubrich (2021), ‘Forecasting US inflation in real time’, Finance and Economics Discussion Series 2021-014. Washington: Board of Governors of the Federal Reserve System

We perform a real-time forecasting exercise for US inflation, investigating whether and how additional information--additional macroeconomic variables, expert judgment, or forecast combination--can improve forecast accuracy and robustness. In our analysis we consider the pre-pandemic period including the Global Financial Crisis and the following expansion--the longest on record--featuring unemployment that fell to a rate not seen for nearly sixty years. Distinguishing features of our study include the use of published Federal Reserve Board staff forecasts contained in Tealbooks and a focus on forecasting performance before, during, and after the Global Financial Crisis, with relevance also for the current crisis and beyond. We find that while simple models remain hard to beat, the additional information that we consider can improve forecasts, especially in the post-crisis period. Our results show that (1) forecast combination approaches improve forecast accuracy over simpler models and robustify against bad forecasts, a particularly relevant feature in the current environment; (2) aggregating forecasts of inflation components can improve performance compared to forecasting the aggregate directly; (3) judgmental forecasts, which likely incorporate larger and more timely datasets, provide improved forecasts at short horizons

Holm-Hadulla, Federic and Kirstin Hubrich (2017), ‘Macroeconomic implications of oil price fluctuations: a regime-switching framework for the euro area’, Finance and Economics Discussion Series 2017-063, May 2017, Washington: Board of Governors of the Federal Reserve System;

'Macroeconomic implications of oil price fluctuations: a regime-switching framework for the euro area,' Working Paper Series 2119, December 2017, European Central Bank.

We investigate whether the response of the macro-economy to oil price shocks undergoes episodic changes. Employing a regime-switching vector autoregressive model we identify two regimes that are characterized by qualitatively different patterns in economic activity and inflation following oil price shocks in the euro area. In the normal regime, oil price shocks trigger only limited and short-lived adjustments in these variables. In the adverse regime, by contrast, oil price shocks are followed by sizeable and sustained macroeconomic fluctuations, with inflation and economic activity moving in the same direction as the oil price. The responses of inflation expectations and wage growth point to second-round effects as a potential driver of the dynamics characterising the adverse regime. The systematic response of monetary policy works against such second-round effects in the adverse regime but is insufficient to fully offset them. The model also delivers (conditional) probabilities for being (staying) in either regime, which may help interpret oil price fluctuations – and inform deliberations on the adequate policy response – in real-time.

Philipp Hartmann, Philipp, Kirstin Hubrich, Manfred Kremer and Robert J. Tetltow (2014), 'Melting down: Systemic financial instability and the macroeconomy'

We investigate the role of systemic financial instability in an empirical macrofinancial model for the euro area, employing a richly specified Markov-Switching Vector Autoregression model to capture the dynamic relationships between a set of core macroeconomic variables and a novel indicator of systemic financial stress. We find that at times of widespread financial instability the macroeconomy functions fundamentally differently from tranquil times. Not only the variances of the shocks, but also the parameters that capture the transmission of shocks change regime, especially around times of high systemic stress in the financial system. In particular, financial shocks are larger and their e¤ects on real activity propagate much more strongly during high systemic-stress regimes than during tranquil times. We find an economically important role of lending in the propagation of financial stress to the macroeconomy. We also show that prospects for detecting high systemic stress episodes appear promising, although we argue that more research is required. We conclude that macroprudential policy makers are well advised to take these non-linearities into account.

‘Forecasting inflation with gradual regime shifts and exogenous information’ (with Timo Teräsvirta, Aarhus University and Stockholm School of Economics, and Andrés Gonzáles, Central Bank of Columbia), CREATES Research Paper 2009-3, ECB Working Paper No. 1363, July 2011

We propose a new method for medium-term forecasting using exogenous information. We suggest a penalised likelihood estimation procedure to combine the model-based forecast and exogenous information about the quantity to be forecast. We show analytically and with simulations how the penalised likelihood procedure can be used for forecasting. We find that our method improves the forecast accuracy of the point forecast for euro area inflation compared to that of a number of relevant benchmark models when we incorporate the central bank's quantitative aim of price stability and its credibility as important exogenous information. We also provide and discuss density forecasts.

‘Forecasting economic aggregates by disaggregates’ (with David Hendry, Oxford University), EABCN/CEPR Discussion Paper No. 5485, 2006; ECB Working Paper No. 589, February 2006