REVIEW 3 minor 11 references
Estimating Individual Responses when Tomorrow Matters
T0 review · 0 major / 3 minor · reviewed 2026-05-24 · grok-4.3
Pith's one-line read A method based on average partial effects recovers how belief shifts about future income alter responses to tax changes.
desk verdict The paper gives a three-step estimator that folds panel data on subjective expectations into average partial effects so counterfactual policy impacts can reflect belief shifts, shown in an Italian tax-consumption application. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
Average partial effects estimated in three steps from panel data on subjective expectations, which recover counterfactual policy impacts when the paper's stated conditions hold.
What would settle it
Re-estimating the consumption response to the tax change while holding beliefs fixed and finding no material difference from the response that allows beliefs to update would falsify the claim that belief shifts matter.
Extended reading notes
Core claim
We propose an approach to estimate how individuals' expectations influence their responses to a counterfactual change. The approach relies on average partial effects, which recover counterfactual impacts under conditions that we specify. We propose a three-step estimation method that relies on panel data on subjective expectations. We illustrate our approach in a model of consumption and saving, focusing on the impact of an income tax that not only changes current income but also affects beliefs about future income. Applying our approach to Italian survey data, we find that individuals' beliefs matter for evaluating the impact of tax policies on consumption decisions.
Load-bearing premise
The conditions required for average partial effects to recover true counterfactual impacts are satisfied, and the survey data accurately measure the relevant shifts in beliefs.
Editorial extensions
If this is right
- Tax policy evaluations must incorporate belief adjustments about future income to avoid biased estimates of consumption effects.
- The three-step procedure separates the contribution of expectation changes from other channels in panel data.
- The stated conditions ensure average partial effects match model-implied counterfactuals in the consumption-saving setting.
- Belief shifts produce measurable differences in how income taxes affect current spending.
Reading between the lines
- The same average partial effects approach could be applied to other policies that simultaneously change current conditions and future expectations, such as pension reforms.
- Validation against administrative consumption records would test whether survey-based belief measures produce reliable counterfactual estimates.
- If measurement error in expectations is present, the estimated role of beliefs would be attenuated relative to the true effect.
- Extending the framework to dynamic labor supply decisions would require only the same panel structure on expectations.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript proposes an approach to estimate how individuals' expectations influence their responses to counterfactual changes. It relies on average partial effects that recover the counterfactual impacts under conditions the authors specify, and introduces a three-step estimation procedure that uses panel data on subjective expectations. The method is illustrated in a consumption-saving model where an income tax changes both current income and beliefs about future income; the approach is then applied to Italian survey data, yielding the finding that beliefs matter when evaluating tax policy impacts on consumption decisions.
Significance. If the stated conditions for the average partial effects hold and the three-step procedure is free of derivation gaps, the paper would supply a practical tool for incorporating expectation shifts into counterfactual policy analysis in dynamic settings. The Italian data application supplies a concrete empirical illustration of how beliefs can alter policy conclusions, which could be useful for researchers working with subjective-expectation panels.
minor comments (3)
- The abstract states that the average partial effects recover counterfactual impacts 'under conditions that we specify,' but does not list the key conditions; adding a one-sentence summary of those conditions would improve readability.
- The three-step estimator is described at a high level; a short appendix or subsection that walks through the exact mapping from the panel moments to the estimator would help readers verify implementation.
- The manuscript should clarify whether the Italian panel is balanced or unbalanced and how attrition or selection into the expectation questions is handled, as these details affect the credibility of the belief-shift measures.
Simulated Author's Rebuttal
We thank the referee for their positive summary of the paper and for recommending minor revision. No major comments were provided in the report.
Circularity Check
No significant circularity in derivation chain
full rationale
The paper proposes an estimation approach using average partial effects that recover counterfactual impacts under explicitly specified conditions, implemented via a three-step method on external panel data on subjective expectations. The central application to Italian survey data on tax policy and consumption is presented as an illustration rather than a tautological fit. No equations or claims reduce the target quantity to a fitted parameter by construction, and no load-bearing steps rely on self-citations or imported uniqueness theorems. The derivation remains self-contained against the stated assumptions and data, consistent with a standard empirical methods contribution.
Assumptions & free parameters
Cite this review
Pith. "Pith review of Estimating Individual Responses when Tomorrow Matters." pith.science (2026). https://pith.science/paper/W7AASCAE
@misc{pith2026231009105,
author = {Pith},
title = {Pith review of: Estimating Individual Responses when Tomorrow Matters},
year = {2026},
howpublished = {\url{https://pith.science/paper/W7AASCAE}},
note = {Machine review of arXiv:2310.09105}
}
read the original abstract
We propose an approach to estimate how individuals' expectations influence their responses to a counterfactual change. The approach relies on average partial effects, which recover counterfactual impacts under conditions that we specify. We propose a three-step estimation method that relies on panel data on subjective expectations. We illustrate our approach in a model of consumption and saving, focusing on the impact of an income tax that not only changes current income but also affects beliefs about future income. Applying our approach to Italian survey data, we find that individuals' beliefs matter for evaluating the impact of tax policies on consumption decisions.
Reference graph
Works this paper leans on
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[1]
College attrition and the dynamics of information revelation,
Arcidiacono, P., E. Aucejo, A. Maurel, and T. Ransom (2016): “College attrition and the dynamics of information revelation,” Discussion paper, National Bureau of Economic Research. Arcidiacono, P., V. J. Hotz, A. Maurel, and T. Romano (2020): “Ex ante returns and occupational choice,” Journal of Political Economy , 128(12), 4475–4522. Arellano, M., and S....
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[2]
Home price expectations and behaviour: Evidence from a randomized information experiment,
Armona, L., A. Fuster, and B. Zafar(2019): “Home price expectations and behaviour: Evidence from a randomized information experiment,” The Review of Economic Studies , 86(4), 1371–1410. Attanasio, O., F. Cunha, and P. Jervis (2019): “Subjective parental beliefs. their measurement and role,” Working Paper 26516, National Bureau of Economic Research. Attana...
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[3]
Note that, in this case, beliefs πit depend on past actions yi,t´1, so (6) does not hold. B Structural and semi-structural counterfactuals In this section of the appendix we present the details of the calibration that we used to produce Table 1, and report additional output from the simulation. B.1 Model The model closely follows Kaplan and Violante (2010...
work page 2010
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[4]
The interest rate is r “ 0.03, and β “ 1{p1 ` rq
Discount factor and interest rate. The interest rate is r “ 0.03, and β “ 1{p1 ` rq. Income process. We use the deterministic age profileκt from Kaplan and Violante (2010). For the stochastic components of the income process, we set σ2 η1 “ 0.15, σ2 v “ 0.01, and σ2 ε “ 0.05. Initial wealth and borrowing limit. Households’ initial assets are set to 0 and ...
work page 2010
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[5]
Pre-tax benefits are equal to 90% of average past earnings up to a given bend point, 32% from this first bend point to a second bend point, and 15% beyond that. The two bend points are set at, respectively, 0.18 and 1.10 times cross-sectional average gross earnings. Benefits are then scaled proportionately so that a worker earning average labor between ag...
work page 2010
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[6]
0” if certain of earning more than X, “100
We see that, under rational expectations (left panel), the contemporanous effect of the tax is higher for the young than for older households, while the dynamic impact is lower. This reflects the fact that households start their working life without assets, and that they cannot borrow. The semi- structural average partial effects reproduce the structural ...
work page 1989
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[7]
Instead of assuming that respondents report exact, normal-based probabilities, we follow Arellano, Bonhomme, De Vera, Hospido, and Wei (2022) and assume that, when answering the survey expectations questions, individuals sample M draws from their underlying N pµg, σ2 gq distribution, and use those draws to provide their answers ppj. Given that, in the sur...
work page 2022
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[8]
We report the results for different values of M
In Figure G3 we report the bias-corrected estimatorpβ BC for two of the regression parameters: the coefficient of the mean income beliefs, and the coefficient of current log income. We report the results for different values of M. The figure shows that the results are fairly robust to this form of measurement error, with pβ BC and pβ OLS being close to ea...
work page 2010
Show all 11 references
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[9]
10 9Specifically, rλ “ λK τ, for K the average gross income in the population
In the regressivity counterfactual, we set τ 1 “ 0.142, the progressivity parameter of the tax system in France according to Holter, Krueger, and Stepanchuk (2019), and set λ1 such that the tax change is revenue neutral. 10 9Specifically, rλ “ λK τ, for K the average gross inc...
2019
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[10]
Results by age. 53 Table G2: Descriptive statistics on income expectations questions 1989–1991 Cross-sectional sample Panel sample Obs P25 Mean P75 Obs P25 Mean P75 Income growth ą 25% 5,486 0 0.79 0 1,096 0 0.63 0 Income growth 20´ 25% 5,486 0 0.85 0 1,096 0 1.18 0 Income gro...
1989
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[11]
Standard errors are based on 1,000 bootstrap replications
In the bottom panel we report estimates based on the double/debiased Lasso, for a dictionary including interactions and power of the covariates up to the third order. Standard errors are based on 1,000 bootstrap replications. 60 Figure G1: Policy rules by type of expectations ...
1989
Reviewed May 24, 2026 · model on record in the stance chip above.
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