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This paper builds a model-based dynamic monetary and fiscal conditions index (DMFCI) and uses it to examine the evolution of the joint stance of monetary and fiscal policies in the euro area (EA) and in its three largest member countries over the period 2007-2018. The index is based on the relative impacts of monetary and fiscal policy on demand using actual and simulated data from rich estimated models featuring also financial intermediaries and long-term government debt. The analysis highlights a short-lived fiscal expansion in the aftermath of the Global Financial Crisis, followed by a quick tightening, with monetary policy left to be the “only game in town” after 2013. Individual countries’ DMFCIs show that national policy stances did not always mirror the evolution of the aggregate stance at the EA level, due to heterogeneity in the fiscal stance.

Econometrics --- Financial Risk Management --- Macroeconomics --- Public Finance --- Fiscal Policy --- National Government Expenditures and Related Policies: General --- Computable and Other Applied General Equilibrium Models --- Financial Crises --- Public finance & taxation --- Econometrics & economic statistics --- Economic & financial crises & disasters --- Fiscal policy --- Fiscal stance --- Expenditure --- Dynamic stochastic general equilibrium models --- Financial crises --- Econometric analysis --- Expenditures, Public --- Econometric models --- Italy

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In recent years, New Keynesian dynamic stochastic general equilibrium (NK DSGE) models have become increasingly popular in the academic literature and in policy analysis. However, the success of these models in reproducing the dynamic behavior of an economy following structural shocks is still disputed. This paper attempts to shed light on this issue. We use a VAR with sign restrictions that are robust to model and parameter uncertainty to estimate the effects of monetary policy, preference, government spending, investment, price markup, technology, and labor supply shocks on macroeconomic variables in the United States and the euro area. In contrast to the NK DSGE models, the empirical results indicate that technology shocks have a positive effect on hours worked, and investment and preference shocks have a positive impact on consumption and investment, respectively. While the former is in line with the predictions of Real Business Cycle models, the latter indicates the relevance of accelerator effects, as described by earlier Keynesian models. We also show that NK DSGE models might overemphasize the contribution of cost-push shocks to business cycle fluctuations while, at the same time, underestimating the importance of other shocks such as changes to technology and investment adjustment costs.

Econometrics --- Labor --- Public Finance --- Computable and Other Applied General Equilibrium Models --- Demand and Supply of Labor: General --- National Government Expenditures and Related Policies: General --- Innovation --- Research and Development --- Technological Change --- Intellectual Property Rights: General --- Wages, Compensation, and Labor Costs: General --- Econometrics & economic statistics --- Labour --- income economics --- Public finance & taxation --- Technology --- general issues --- Dynamic stochastic general equilibrium models --- Labor supply --- Expenditure --- Real wages --- Econometric models --- Labor market --- Expenditures, Public --- Wages --- United States --- General issues --- Income economics

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In a SVAR model of the US, the response of the relative price of durables to a monetary contraction is either flat or mildly positive. It significantly falls only if narrowly defined as the ratio between new-house and nondurables prices. These findings are rationalized via the estimation of a two-sector New-Keynesian (NK) models. Durables prices are estimated to be as sticky as nondurables, leading to a flat relative price response to a monetary shock. Conversely, house prices are estimated to be almost flexible. Such results survive several robustness checks and a three-sector extension of the NK model. These findings have implications for building two-sector NK models with durable and nondurable goods, and for the conduct of monetary policy.

Monetary policy. --- Monetary management --- Economic policy --- Currency boards --- Money supply --- Econometrics --- Infrastructure --- Macroeconomics --- Real Estate --- Inflation --- Price Level --- Deflation --- Economic Development: Urban, Rural, Regional, and Transportation Analysis --- Housing --- Housing Supply and Markets --- Macroeconomics: Consumption --- Saving --- Wealth --- Computable and Other Applied General Equilibrium Models --- Monetary Policy --- Business Fluctuations --- Cycles --- Property & real estate --- Econometrics & economic statistics --- Sticky prices --- Housing prices --- Consumption --- Dynamic stochastic general equilibrium models --- Prices --- National accounts --- Saving and investment --- Economics --- Econometric models --- United States

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Dynamic factor models and dynamic stochastic general equilibrium (DSGE) models are widely used for empirical research in macroeconomics. The empirical factor literature argues that the co-movement of large panels of macroeconomic and financial data can be captured by relatively few common unobserved factors. Similarly, the dynamics in DSGE models are often governed by a handful of state variables and exogenous processes such as preference and/or technology shocks. Boivin and Giannoni(2006) combine a DSGE and a factor model into a data-rich DSGE model, in which DSGE states are factors and factor dynamics are subject to DSGE model implied restrictions. We compare a data-richDSGE model with a standard New Keynesian core to an empirical dynamic factor model by estimating both on a rich panel of U.S. macroeconomic and financial data compiled by Stock and Watson (2008).We find that the spaces spanned by the empirical factors and by the data-rich DSGE model states are very close. This proximity allows us to propagate monetary policy and technology innovations in an otherwise non-structural dynamic factor model to obtain predictions for many more series than just a handful of traditional macro variables, including measures of real activity, price indices, labor market indicators, interest rate spreads, money and credit stocks, and exchange rates.

Macroeconomics --- Equilibrium (Economics) --- Econometric models. --- Econometrics --- Inflation --- Investments: Stocks --- Bayesian Analysis: General --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Business Fluctuations --- Cycles --- Prices, Business Fluctuations, and Cycles: Forecasting and Simulation --- Computable and Other Applied General Equilibrium Models --- Classification Methods --- Cluster Analysis --- Principal Components --- Factor Models --- Price Level --- Deflation --- Pension Funds --- Non-bank Financial Institutions --- Financial Instruments --- Institutional Investors --- Macroeconomics: Consumption --- Saving --- Wealth --- Econometrics & economic statistics --- Investment & securities --- Dynamic stochastic general equilibrium models --- Factor models --- Stocks --- Consumption --- Econometric analysis --- Prices --- Financial institutions --- National accounts --- Econometric models --- Economics --- United States

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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.

Aggregate Factor Income Distribution --- Computable and Other Applied General Equilibrium Models --- Currency crises --- Deflation --- Dynamic stochastic general equilibrium models --- Econometric analysis --- Econometric models --- Econometrics & economic statistics --- Econometrics --- Economic & financial crises & disasters --- Economic Forecasting --- Economic forecasting --- Economic theory & philosophy --- Economic Theory --- Economic theory --- Economics of specific sectors --- Economics --- Economics: General --- Expectations --- Financial Institutions and Services: General --- Financial Instruments --- Forecasting and Other Model Applications --- Forecasting --- Income --- Inflation --- Informal sector --- Institutional Investors --- Macroeconomics --- Monetary Policy --- National accounts --- Non-bank Financial Institutions --- Pension Funds --- Price Level --- Prices --- Rational expectations --- Speculations