Inflationary Household Uncertainty Shocks

Layer 1: Overview

Research question and motivation: Macro-uncertainty is widely believed to depress activity, but existing measures are tied to financial markets, professional forecasters, or economic policy, while a key transmission channel runs through households’ propensity to consume, save, and work. Direct, macro-usable measures of household uncertainty are scarce. Ambrocio asks whether household uncertainty shocks behave like the negative demand shocks documented for the US (Leduc and Liu, 2016), and finds they do not in Europe.

Data and measurement: The paper builds a novel household uncertainty index (HUN) from the European Commission’s harmonized consumer survey, defined as the average fraction of “Don’t know” responses across the four forward-looking questions used to construct the pre-2019 Consumer Confidence Indicator (general economic situation, unemployment, household financial position, likelihood to save). The survey is monthly, covers all EU member states (and candidates), averaging over 40,000 households per month, conducted in the first two to three weeks of each month. HUN is constructed for January 2002 to December 2019. On average 3-6% of Euro area households respond “Don’t know” per round; at the national level the range runs from 2 to over 10 percent (e.g. Spain, France, Italy). HUN is standardized so 100 = mean and 10 points = one standard deviation. The Euro area HUN peaks around EU enlargement, the Global Financial Crisis, the European Sovereign Debt Crisis, and Brexit.

Empirical strategy: Following Leduc and Liu (2016), the author estimates monthly VARs with an uncertainty measure, unemployment, inflation, and the short rate, three lags, Bayesian estimation with Minnesota priors (ECB BEAR toolbox). Shocks are identified recursively with uncertainty ordered first, justified by the early-month survey timing and household inattention.

Main findings (with magnitudes/signs/scope): (1) For the Euro area, household uncertainty shocks are inflationary, with a delayed rise in unemployment only after about 20 months. By contrast, financial (Eurostoxx-50 implied volatility, IVOL) uncertainty shocks resemble negative demand shocks (raise unemployment, lower inflation), and policy (Baker-Bloom-Davis EPU) shocks have ambiguous inflation effects. (2) FEVDs: household or financial uncertainty shocks each account for about 20% of inflation forecast-error variance at roughly a 4-year horizon (policy uncertainty substantially less); household shocks account for about 10% of unemployment variation, financial and policy 20-30%. (3) Counterfactuals zeroing out the monetary-policy response to uncertainty: cumulated 48-month inflation IRF for HUN moves from 2.02 (baseline) to 1.66 (still inflationary); EPU from -0.79 to 0.68 (becomes inflationary); IVOL from -2.66 to -1.33 (less deflationary) - indicating monetary policy responds to financial/policy but not household uncertainty. (4) Cross-country (17 Euro-area countries excluding Ireland and Malta plus 8 non-Euro-area), cumulated 48-month inflation responses range from nearly 6% deflation (Lithuania) to over 12% inflation (Bulgaria); deflationary in Austria, Finland, Portugal, inflationary in Italy, Spain, Sweden. The cross-country inflation response correlates positively and significantly with average markups (De Loecker and Eeckhout, 2020; 13 countries, 2002-2016), regression slope ~1.86, robust to labor-market, institutional, and economic-structure controls.

Mechanism and implications: Results support a pricing-bias (precautionary pricing) channel: under nominal rigidities and monopolistic competition, firms raise prices when uncertainty rises because under-pricing is more costly than over-pricing. A calibrated New Keynesian model (Rotemberg pricing, third-order perturbation) matching country markups reproduces the deflationary-to-inflationary range for supply-side uncertainty; varying price rigidity and the monetary-policy response to uncertainty can jointly generate inflationary household and deflationary financial uncertainty shocks. Supply-side (productivity-volatility) uncertainty matches the data features better than demand-side uncertainty.

Layer 2: Deep Dive

What is the identification strategy and what are the main threats to it?

Recursive (Cholesky) identification in monthly VARs with the uncertainty measure ordered first, justified because the consumer survey is conducted in the first two weeks of the month (so contemporaneous monthly movements in other variables plausibly cannot affect HUN) and because households are inattentive and under-react to news. The main drawback is the assumption that the uncertainty measure is not contemporaneously affected by other shocks. The author argues monthly data mitigates this (Carriero et al., 2021, find limited contemporaneous feedback to uncertainty at this frequency) and shows results are robust to ordering uncertainty last and to the Carriero et al. (2021) time-varying-volatility identification (which allows uncertainty to respond contemporaneously). He also notes the recursive scheme can be read as a proxy-SVAR with the first variable as instrument, yielding more conservative (attenuated) impulse responses than a proxy SVAR.

What are the main mechanisms and how are they distinguished empirically?

The central mechanism is the pricing bias (precautionary pricing) channel under nominal rigidities and monopolistic competition: firms set higher prices when uncertain because ending up with too-low a price (selling more at thin margins) is costlier than too-high a price. This is distinguished from the standard precautionary-savings/negative-demand interpretation. Empirically: (i) household uncertainty is inflationary while financial uncertainty is deflationary; (ii) the cross-country inflation response correlates positively and significantly with average markups - the key comparative-static predicted by theory (elasticity of substitution governs markups); (iii) counterfactual VARs show monetary policy response, not the measure itself, drives part of the sign difference. The NK model then confirms only supply-side (not demand-side) uncertainty generates the observed positive markup-inflation relationship.

What heterogeneity is documented?

Large cross-country heterogeneity: cumulated 48-month inflation responses range from nearly 6% deflation (Lithuania) to over 12% inflation (Bulgaria); deflationary in Austria, Finland, Portugal and inflationary in Italy, Spain, Sweden. Splitting into core / periphery / non-Euro-area shows little difference in average response; geographically, Southern European responses are marginally higher than Northern. The cross-country variation is well explained by average markups: a regression of the cumulated inflation IRF on markups yields a positive slope (~1.86, significant) and country-group dummies are insignificant once markups are controlled for.

What robustness checks are run?

(1) Ordering uncertainty last - results virtually unchanged. (2) Carriero et al. (2021) time-varying-volatility identification - household uncertainty still inflationary. (3) Adding consumer sentiment (CSI) to the VAR - sentiment acts like a positive demand shock (lower unemployment, higher inflation), HUN remains inflationary, so results are not driven by first-moment sentiment. (4) A VAR with all three uncertainty measures (IVOL, EPU, HUN) - HUN still inflationary; policy uncertainty becomes inflationary in this setup. (5) Replacing the short rate with the Wu-Xia (2016) shadow rate to capture unconventional policy - results hold. (6) Adding linear trends and month-specific (seasonal) intercepts - results hold. (7) Alternative HUN built only from the two macro questions (HUN-Macro) and common-factor versions (HUN-F10, HUN-F16) - still inflationary. (8) Household belief dispersion (DIS) shocks instead of HUN are mildly deflationary, distinguishing uncertainty from disagreement. (9) Markup regressions remain significant controlling for labor-market, institutional-quality, and economic-structure variables.

How does this paper relate to and differ from closely related prior work?

It directly contrasts with Leduc and Liu (2016), who use the Michigan Consumer Survey and find US household uncertainty shocks resemble negative demand shocks (higher unemployment, lower inflation); here European household uncertainty shocks are inflationary. The inflationary result aligns with Mumtaz et al. (2018) (US state-level) and Mumtaz and Theodoridis (2015) (US shocks on the UK), while Carriero et al. (2018) find no significant price effect for the US. It builds on the pricing-bias literature (Born and Pfeifer, 2014, 2021; Fernandez-Villaverde et al., 2015; Bianchi et al., 2018) and on multi-source-uncertainty models. Relative to Bianchi et al. (2018), who find supply-side uncertainty deflationary and demand-side neutral under low price rigidity, this paper’s baseline (price duration over 3 quarters, calibrated shock volatilities) yields both demand- and supply-side uncertainty inflationary; their result is recoverable under low rigidity. The HUN measure newly exploits an under-explored source (households) with long time and broad country coverage.

What are the policy implications and their scope conditions?

The monetary-policy response to uncertainty matters for whether an uncertainty shock is inflationary or deflationary: counterfactuals show that when policy does not respond to household uncertainty it stays inflationary, while financial and policy uncertainty (to which policy does respond) shift toward inflation when that response is removed. In the model, very small monetary-response coefficients to uncertainty are sufficient to flip the sign (a_vb=0.0002 yields near-zero, 0.0004 yields about -1.1% deflation, against a 1.37% baseline). Scope conditions: results are specific to Europe / the Euro area’s common monetary policy; the counterfactual is subject to the Lucas critique (assumes the policy change is small enough not to alter agents’ behavior); and the paper explicitly does NOT evaluate whether monetary policy should respond - optimal policy is left for future research, noting that raising rates under uncertainty aggravates the output decline.

What does the New Keynesian model add and how is it calibrated?

A basic NK model with habit-forming risk-averse households, monopolistically competitive firms with Rotemberg price-adjustment costs, productivity (supply-side) and preference (demand-side) stochastic-volatility shocks, and a Taylor rule that can respond to uncertainty. The elasticity of substitution is calibrated to match average markups (baseline Euro area, eta=3.13; range Portugal-to-Italy 1.84-8.82 markups); baseline price stickiness matches a Calvo price duration of just over 3 quarters; shock-volatility variances are calibrated to match the VAR cumulated inflation IRF. Solved by third-order perturbation; IRFs are generalized impulse responses at the stochastic steady state (500-quarter burn-in). Findings: markup variation generates a wide deflationary-to-inflationary range for supply-side uncertainty (matching Italy high / Finland low) but not for demand-side; inflation responses are hump-shaped in price rigidity, with low rigidity giving deflationary supply / inflationary demand shocks and high rigidity reversing this; supply-side uncertainty better matches the markup-inflation correlation, suggesting HUN proxies uncertainty about productive capacity rather than relative consumption desires.

What are the notable caveats and limitations the author flags?

(i) The Rotemberg-vs-Calvo choice is not innocuous: Oh (2020) shows Rotemberg costs make uncertainty shocks more deflationary, so a Calvo model would likely be even more inflationary. (ii) The counterfactual monetary-policy exercise is subject to the Lucas critique. (iii) The empirical link between price rigidity and inflationary responses across countries is not tested - left for future research. (iv) The model has simple financial and labor markets; labor-market frictions known to matter for uncertainty transmission are abstracted from. (v) Some country HUN indices (Cyprus, Lithuania, Slovakia) may have unaddressed structural breaks. (vi) Cross-country markup regressions have only 13 observations, creating degrees-of-freedom limits in the slope-interaction specifications. (vii) HUN correlates positively (about 0.49) with the new European Commission uncertainty index and shows no detected structural break from the 2019/2021 survey-question change.

Key Concepts

Household uncertainty index (HUN): A survey-based measure equal to the average fraction of respondents answering ‘Don’t know’ across the four forward-looking questions (general economic situation, unemployment, household finances, likelihood to save) of the European Commission harmonized consumer survey; interpreted as households’ uncertainty about the economy, and argued to proxy supply-side (productive-capacity) uncertainty.

Pricing bias (precautionary pricing) mechanism: The transmission channel whereby firms in monopolistically competitive markets with nominal rigidities raise prices under higher uncertainty, because ending up with a too-low price (large volume, thin margins) is more costly than a too-high price; this makes uncertainty shocks inflationary, amplified by stronger nominal rigidities and higher markups.

Inflationary vs. deflationary uncertainty shock: In this paper, household uncertainty shocks raise inflation (inflationary) whereas financial (IVOL) uncertainty shocks lower it like negative demand shocks (deflationary); the sign depends on the relative strength of the pricing-bias channel versus precautionary savings and on whether monetary policy responds to that source of uncertainty.

Counterfactual monetary-policy IRF: Impulse responses computed by zeroing out the direct (contemporaneous and lagged) response of the policy-rate equation to uncertainty in an estimated recursive VAR (Bachmann-Sims, Kilian-Lewis), isolating how much of the inflation response is attributable to the systematic monetary-policy reaction to that uncertainty source.

Supply-side vs. demand-side uncertainty: In the NK model, demand-side uncertainty is a shock to the volatility of preference shocks and supply-side uncertainty a shock to the volatility of productivity shocks; only supply-side uncertainty reproduces the empirical positive markup-inflation correlation, leading the author to interpret HUN as closer to supply-side uncertainty.

Disagreement (DIS) vs. uncertainty: DIS is the average cross-household dispersion of survey views (a measure of disagreement/polarization), distinct from HUN (frequency of ‘Don’t know’); the two are negatively correlated, and DIS shocks are mildly deflationary, paralleling Born et al. (2020a)’s distinction between belief dispersion and forecast-error uncertainty.