The Propagation of Monetary Policy Shocks in a Heterogeneous Production Economy

Pastén, Ernesto; Schoenle, Raphael; Weber, Michael

doi:10.2139/ssrn.3338705

Cited by 4 publications

(24 citation statements)

References 23 publications

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“…Second, there is substantial evidence pointing towards the necessity of addressing industry-specific reactions to monetary surprises, confirming the empirical and theoretical findings by Ehrmann and Fratzscher (2004), Chen (2007) or Pasten et al (2019).…”

Section: Introductionsupporting

confidence: 65%

“…Considering hypothetical responses to a surprise 25 basis points interest rate hike, this implies that a number of industries shows stock market return declines exceeding 0.75 percent. These findings provide further strong empirical evidence for the necessity of considering heterogeneous coefficients and a sophisticated econometric approach; they can be explained partly by the theoretical channels provided in Ehrmann and Fratzscher (2004) and Pasten et al (2019).…”

Section: Nested Specifications and Benchmarkssupporting

confidence: 52%

“…In the following, we discuss our findings for the full model featuring time-varying network dependence and cross-sectional heterogeneities. Given the importance of industry-specific idiosyncrasies identified in previous contributions (Ehrmann and Fratzscher, 2004;Gorodnichenko and Weber, 2016;Pasten et al, 2019) and suggested by Tab. 1, we begin by discussing our findings for the heterogeneous regression coefficients.…”

Section: Nested Specifications and Benchmarksmentioning

confidence: 93%

“…, N , with two extreme cases: either one decides to pool information over the cross-section, restricting θ i to be equal for all units, or one introduces truly observation specific parameters. The first restriction, especially in the empirical application of this paper considering the established literature (Ehrmann and Fratzscher, 2004;Gorodnichenko and Weber, 2016;Pasten et al, 2019), is likely to be overly restrictive and may mask important structural dynamics. The second variant, however, implies estimating a large number of parameters and may thus result in imprecise estimates and overfitting issues.…”

Section: Sparse Finite Mixtures To Pool Coefficientsmentioning

confidence: 99%

“…This is particularly important considering that industries and sectors differ substantially in size and use vastly different production inputs. In a theoretical framework, Pasten et al (2019) show that heterogeneities in price rigidities are an important determinant how policy interventions are transmitted to the real economy, suggesting a pronounced role for industry-specific responses of stock market returns to surprise monetary policy shocks.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy

Hauzenberger¹,

Pfarrhofer²

2019

Preprint

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Understanding disaggregate channels in the transmission of monetary policy is of crucial importance for effectively implementing policy measures. We extend the empirical econometric literature on the role of production networks in the propagation of shocks along two dimensions. First, we set forth a Bayesian network panel state-space model that assumes time variation in the network dependence parameter. The framework is applied to a study of the network effects of Federal Reserve (Fed) monetary policy announcements on US stock market returns on the industry level using high-frequency data. Second, we account for cross-sectional heterogeneity and cluster impacts of monetary policy shocks to industries via a sparse finite Gaussian mixture model. The results suggest substantial heterogeneities in the responses of industries to surprise monetary policy shocks in line with the recent literature. Moreover, we find that the impact of policy surprises on stock returns differes strongly over time. This time-variation stems mainly from changes in the strength network effects, with magnitudes of the effects during periods coinciding with recessions being almost twice as large than in expansionary phases.

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Section: Introductionsupporting

confidence: 65%

Section: Nested Specifications and Benchmarkssupporting

confidence: 52%

Section: Nested Specifications and Benchmarksmentioning

confidence: 93%

Section: Sparse Finite Mixtures To Pool Coefficientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy

Hauzenberger¹,

Pfarrhofer²

2019

Preprint

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Optimal Monetary Policy in Production Networks

La’O

Tahbaz-Salehi

2020

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This paper studies the optimal conduct of monetary policy in a multi-sector economy in which firms buy and sell intermediate goods over a production network. We first provide a necessary and sufficient condition for the monetary policy's ability to implement flexible-price equilibria in the presence of nominal rigidities and show that, generically, no monetary policy can implement the first-best allocation. We then characterize the constrained-efficient policy in terms of the economy's production network and the extent and nature of nominal rigidities. Our characterization result yields general principles for the optimal conduct of monetary policy in the presence of input output linkages: it establishes that optimal policy stabilizes a price index with higher weights assigned to larger, stickier, and more upstream industries, as well as industries with less sticky upstream suppliers but stickier downstream customers. In a calibrated version of the model, we find that implementing the optimal policy can result in quantitatively meaningful welfare gains.

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Networks, Phillips Curves, and Monetary Policy

Rubbo

2023

ECTA

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This paper revisits the New Keynesian framework, theoretically and quantitatively, in an economy with multiple sectors and input‐output linkages. Analytical expressions for the Phillips curve and welfare, derived as a function of primitives, show that the slope of all sectoral and aggregate Phillips curves is decreasing in intermediate input shares, while productivity fluctuations endogenously generate an inflation‐output tradeoff—except when inflation is measured according to the novel divine coincidence index. Consistent with the theory, the divine coincidence index provides a better fit in Phillips curve regressions than consumer prices. Monetary policy can no longer achieve the first‐best, resulting in a welfare loss of 2.9% of per‐period GDP under the constrained‐optimal policy, which increases to 3.8% when targeting consumer inflation. The constrained‐optimal policy must tolerate relative price distortions across firms and sectors in order to stabilize the output gap, and it can be implemented via a Taylor rule that targets the divine coincidence index.

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The Propagation of Monetary Policy Shocks in a Heterogeneous Production Economy

Cited by 4 publications

References 23 publications

Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy

Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy

Optimal Monetary Policy in Production Networks

Networks, Phillips Curves, and Monetary Policy

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