Sticky Prices or Sticky Wages? An Equivalence Result
Florin Bilbiie, Mathias Trabandt
Review of Economics and Statistics,
forthcoming
Abstract
We show an equivalence result in the standard representative agent New Keynesian model after demand, wage markup and correlated price markup and TFP shocks: assuming sticky prices and flexible wages yields identical allocations for GDP, consumption, labor, inflation and interest rates to the opposite case- flexible prices and sticky wages. This equivalence result arises if the price and wage Phillips curves' slopes are identical and generalizes to any pair of price and wage Phillips curve slopes such that their sum and product are identical. Nevertheless, the cyclical implications for profits and wages are substantially different. We discuss how the equivalence breaks when these factor-distributional implications matter for aggregate allocations, e.g. in New Keynesian models with heterogeneous agents, endogenous firm entry, and non-constant returns to scale in production. Lastly, we point to an econometric identification problem raised by our equivalence result and discuss possible solutions thereof.
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Assumption Errors and Forecast Accuracy: A Partial Linear Instrumental Variable and Double Machine Learning Approach
Katja Heinisch, Fabio Scaramella, Christoph Schult
IWH Discussion Papers,
No. 6,
2025
Abstract
Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.
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Green Transition
Green Transition Research and Policy Advice for Structural Change in the German Economy Dossier, 18.06.2024 Green Transition The green transition is a key topic of our time. In a…
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Understanding Post-Covid Inflation Dynamics
Martín Harding, Jesper Lindé, Mathias Trabandt
Journal of Monetary Economics,
November
2023
Abstract
We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the post-COVID period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroskedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is elevated.
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Financial Stability
Financial Systems: The Anatomy of the Market Economy How the financial system is constructed, how it works, how to keep it fit and what good a bit of chocolate can do. Dossier In…
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Household Indebtedness, Financial Frictions and the Transmission of Monetary Policy to Consumption: Evidence from China
Michael Funke, Xiang Li, Doudou Zhong
Emerging Markets Review,
June
2023
Abstract
This paper studies the impact of household indebtedness on the transmission of monetary policy to consumption using the Chinese household-level survey data. We employ a panel smooth transition regression model to investigate the non-linear role of indebtedness. We find that housing-related indebtedness weakens the monetary policy transmission, and this effect is non-linear as there is a much larger counteraction of consumption in response to monetary policy shocks when household indebtedness increases from a low level rather than from a high level. Moreover, the weakened monetary policy transmission from indebtedness is stronger in urban households than in rural households. This can be explained by the investment good characteristic of real estate in China.
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Trust, Politics and Post-IPO Performance: SOEs vs. the Private Sector
Bill Francis, Iftekhar Hasan, Xian Sun, Mingming Zhou
Economic and Political Studies,
No. 3,
2022
Abstract
This paper empirically investigates the role of social trust in the long-term performance of the initial public offerings (IPOs) in China, controlling for the formal institutional environment. We find that privately owned or smaller IPO firms experience significantly better post-IPO performance when they are incorporated in regions with more social trust. The state-owned and bigger IPO firms, on the other hand, experience better long-term post-IPO performance when they are incorporated in regions with stronger formal institutions (e.g. court enforcement and contract holding). Political pluralism turns out to benefit all IPOs in the long term. In addition, our evidence shows that stronger social trust substitutes for the quality of court enforcement but complements the role of contract holding. These results are robust after controlling for alternative definitions of ownership, outliers, non-linear effects of institutions, and the potential endogeneity of institutions in the model.
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Understanding Post-Covid Inflation Dynamics
Martín Harding, Jesper Lindé, Mathias Trabandt
Abstract
We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the Post-Covid period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroscedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is high.
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Resolving the Missing Deflation Puzzle
Martín Harding, Jesper Lindé, Mathias Trabandt
Journal of Monetary Economics,
March
2022
Abstract
A resolution of the missing deflation puzzle is proposed. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.
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Optimizing Policymakers’ Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Macroeconomic Dynamics,
No. 1,
2021
Abstract
Recurring financial instabilities have led policymakers to rely on early-warning models to signal financial vulnerabilities. These models rely on ex-post optimization of signaling thresholds on crisis probabilities accounting for preferences between forecast errors, but come with the crucial drawback of unstable thresholds in recursive estimations. We propose two alternatives for threshold setting with similar or better out-of-sample performance: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide real-world and simulation evidence that this simplification results in stable thresholds, while keeping or improving on out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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