{"id":"fe3b75a4-b4a2-4872-8b42-50f56fc970f4","arxiv_id":"2506.07476","paper_version":1,"verdict":"REJECT","confidence":"HIGH","novelty_score":4.0,"correctness_risk":"high","formal_verification":"none","parameter_count":3,"one_line_summary":"For twelve U.S. durable goods firms, panel quantile and VAR-MIDAS estimates are claimed to show that Tobin's Q falls with policy uncertainty, recession risk, and inflation expectations and rises with consumer confidence, but the paper's own tables and text contradict each other on key signs.","lead":"This paper claims that economic policy uncertainty, recession risk, and inflation expectations lower Tobin's Q for twelve U.S. durable goods firms, while consumer confidence raises it. The evidence is presented through panel quantile regressions and a mixed-frequency panel VAR, but the reported signs and test statistics are internally inconsistent.","discovery_kind":"extension","skeptic_critique":{"model":"deepseek-v4-flash","headline":"Table 3 does not support the abstract's claim that consumer confidence raises Q in most quantiles: net lagged effects are negative at the 25th and 50th quantiles and positive only at the 75th.","rationale":"I read the paper as trying to establish that macro uncertainty measures are priced into durable-goods firms' Tobin's Q in a quantile-dependent way, with the abstract making four specific sign claims. The most load-bearing condition for that claim is that the reported estimates actually exhibit the claimed signs. They do not for consumer confidence, and the accompanying text contradicts itself. This is a stronger objection than the stationarity concern because it is verifiable directly from Table 3 and requires no assumptions about cross-sectional dependence, cointegration, or estimator validity. The reader's verdict of REJECT is therefore correct, but my reason differs: the reader's weakest-assumption is the LLC cross-sectional independence issue, while I would emphasize the internal sign inconsistency. Other concerns, such as implausibly small p-values, enormous Wald statistics, and the exclusion of EPU from the final PVM, reinforce the rejection but are not needed to establish it.","tokens_in":22903,"tokens_out":2413,"duration_ms":29881,"concrete_test":"Sum the three lagged consumer-confidence coefficients (consconf t-1, t-2, t-3) in Table 3 for the 25th, 50th, and 75th quantiles. If the net effect is positive at fewer than two quantiles, the abstract's \"positively to consumer confidence in most quantiles\" is false. As an additional check, re-estimate the panel quantile regression using the described Compustat and FRED data and verify whether any quantile shows a positive net consumer-confidence coefficient; the reported p-values on the order of 1e-7 and Wald statistics on the order of 1e10 make mechanical error a plausible explanation worth ruling out.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim requires that Q reacts negatively to EPU, recession risk, and inflation expectations, but positively to consumer confidence in most quantiles. The paper's own Table 3 fails this requirement for consumer confidence. Summing the three lagged consconf coefficients gives: q25 = +0.0043 - 0.0277 - 0.0025 = -0.0259; q50 = -0.0036 + 0.00013 + 0.0025 = -0.00097; q75 = +0.000277 - 0.00666 + 0.00895 = +0.00257. Thus the net association is negative at the 25th and 50th quantiles and positive only at the 75th, so the phrase \"positively to consumer confidence in most quantiles\" is not supported by the reported estimates. The text compounds the problem by stating that \"in all quantiles reported in Table 3, the coefficient of the lagged consumer confidence index is unexpectedly negative and significant,\" which contradicts both the table and the abstract. Because one of the four uncertainty channels named in the headline finding has the wrong sign under the paper's own numbers, the central conclusion as stated is unsupported. The stationarity and cross-sectional dependence issues identified by the reader are real, but this sign inconsistency is more load-bearing because it does not depend on any re-estimation or alternative assumption; it is a direct internal failure of the evidence relative to the claim.","agreement_with_reader":"partial"},"referee_report":{"model":"deepseek-v4-flash","summary":"This paper studies how economic policy uncertainty, recession risk, inflation expectations, and consumer confidence affect Tobin's Q for twelve U.S. consumer durable goods firms, using panel quantile regression (PQR) and a panel VAR-MIDAS (PVM) model on mixed-frequency data from 1985 to 2022. The abstract claims that Q reacts negatively to EPU, recession risk, inflation expectations, current ratio, and debt-to-asset ratio, positively to consumer confidence in most quantiles, and that Granger causality tests confirm these uncertainty indicators are significant predictors. The manuscript also derives managerial hedging implications from the results.","tokens_in":23188,"tokens_out":8097,"duration_ms":78209,"significance":"The topic is relevant and the paper assembles a reasonable dataset, combining Compustat firm-level data with widely used public uncertainty indices. However, the central claims are not supported by the paper's own reported estimates. The consumer-confidence effect in Table 3 is negative in most quantiles once all lags are summed, contradicting the abstract and the text; the impulse responses from the PVM conflict with the PQR results; and the PVM as described omits EPU and recession risk, so several headline conclusions cannot be drawn from the reported exercises. These are internal failures of evidence rather than mere disagreements with prior literature, so the findings as stated cannot be accepted.","major_comments":[{"comment":"The claim that Q 'reacts ... positively to consumer confidence in most quantiles' is contradicted by Table 3. Summing the three lagged consconf coefficients gives -0.0259 at the 25th quantile, -0.00097 at the 50th quantile, and +0.00257 at the 75th quantile, so only the 75th quantile is positive. Furthermore, the text at the end of the consumer-confidence discussion states that 'in all quantiles reported in Table 3, the coefficient of the lagged consumer confidence index is unexpectedly negative and significant,' which is inconsistent both with the table entries (e.g., +0.0043 for the first lag at q25) and with the abstract. The headline finding is therefore unsupported by the paper's own estimates.","section":"Abstract; Section V; Table 3"},{"comment":"The debt-to-asset coefficient changes sign across quantiles: +0.422 at q25, -0.2925 at q50, and -1.2255 at q75. The text in Section V states that 'variables qr, da, and oiad show a positive association with Q,' which is false for da at the median and upper quantile. Conversely, the impulse-response text claims that positive DA shocks lower Q, which matches only the q50/q75 PQR results. Similarly, Table 3 reports negative cr coefficients at all quantiles, while the impulse-response text says that 'one standard deviation positive shock to cr ... triggers positive reactions in q.' The two empirical methodologies thus contradict each other on the signs of key firm-level variables, so the paper's assertion that the PVM results 'bolster' the PQR findings is not credible.","section":"Table 3; Figure 1"},{"comment":"The paper states that EPU, recessionary risk, and consumer confidence were removed from the PVM because they were 'weakly correlated causing singularity in the matrix of the variables.' Weak correlation does not cause singularity, and the reported impulse responses in Figure 1 contain no EPU or recession-risk panels. Nevertheless, the Summary and Conclusions attribute to the PVM the finding that Q 'reacts negatively to economic policy uncertainty (EPU), recessionary risks, and inflationary expectations, while being positively associated with consumer confidence.' The PVM as estimated cannot support the EPU and recession-risk conclusions, so these claims are not backed by the reported exercise.","section":"Panel VAR-MIDAS section; Figure 1; Conclusions"},{"comment":"The Wald statistics are reported only as 4.9e+07, 1.4e+07, 5.9e+08, and 3.2e+10, without degrees of freedom, sample size, or a derivation of the panel quantile Granger test. These values are implausibly large for any standard test, and the tests are computed from the same three-lag PQR specification used in Table 3, so they do not constitute an independent validation. The abstract's claim that 'Granger causality tests confirm that the uncertainty indicators ... are significant predictors' is not supported by the information provided in the manuscript.","section":"Table 4; Granger causality discussion"},{"comment":"The LLC unit root test used to justify first-differencing of DA, OIAD, and Q assumes cross-sectional independence. The twelve firms are all in the durable goods industry and are likely exposed to common macro shocks, so this assumption is implausible. If cross-sectional dependence or cointegration is present, the first-differencing scheme and the subsequent PQR and Granger tests may be spurious. The paper should report cross-sectionally augmented or panel cointegration methods, or at least provide a justification for the LLC assumption beyond a footnote.","section":"Table 2; Methodology"},{"comment":"The reported mean acceptance rate is 0.002 (0.2%) for all quantiles, which is far below the typical 0.2-0.5 range for random-walk Metropolis samplers. This suggests very poor mixing, yet every coefficient is reported as statistically significant at 0.01% or less. The reliability of the PQR estimates is therefore questionable and should be checked with alternative samplers, longer chains, or different tuning parameters before any conclusions are drawn.","section":"Table 3; MCMC diagnostics"}],"minor_comments":[{"comment":"The notation in equation (4) is garbled, with subscripts and matrices not properly defined, and the PVM model description is not self-contained; it should be rewritten for reproducibility.","section":"Section IV (Methodology)"},{"comment":"The sample period is given as Q1/1980-Q4/2022 in the text but Q1/1985-Q4/2022 in Table 2 and the conclusions; please reconcile these statements.","section":"Data section; Table 2; Conclusions"},{"comment":"There are numerous typographical errors, including 'Mote Carlo' for Monte Carlo, 'Coversly' for Conversely, 'urns elastic' for becomes elastic, and 'fir value' for firm value; a thorough proofreading is needed.","section":"Throughout"},{"comment":"The sentence 'The demand for petroleum products such as gasoline and natural gas is inelastic in the short-run...' appears in a discussion of consumer durables and seems out of place; it should be removed or rephrased to relate to durable goods.","section":"Section V"},{"comment":"Several references are incomplete or inconsistent (e.g., Baker et al. 2014 and 2016 share the same title; the Chauvet (2008) citation does not match the reference list); the citation style should be harmonized.","section":"References"},{"comment":"The statement that 'Data for the research are available upon request' should specify whether the underlying Compustat data are subject to WRDS licensing restrictions.","section":"Declarations"}],"recommendation":"reject","confidential_remarks":"The paper appears to be a version of a published article (Journal of Theoretical Accounting Research, 2025) and is heavily self-referential, citing the authors' own prior work for the methodology. The reviewer may wish to verify the novelty relative to those prior publications and whether the journal's scope covers this type of applied panel-quantile study. The internal contradictions noted in the major comments stand on their own and are sufficient to reject the manuscript in its current form."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"This one is not ready for referees. The authors take an established toolkit (PQR and VAR-MIDAS) that they have used in at least five earlier papers, apply it to twelve U.S. durable goods firms, and claim that uncertainty measures predict Tobin's Q. The sector is a legitimate extension and the question is sensible, but the evidence as reported does not support the headline claim.\n\nWhat is genuinely useful: the data work covers a long panel (1985–2022) and the paper tries to bring monthly uncertainty measures into a quarterly firm-value model via MIDAS. The literature review is adequate, though heavily self-referencing. The managerial implications are boilerplate but not harmful.\n\nThe problems are load-bearing. The abstract states that Q reacts negatively to EPU, recession risk, and inflation expectations, and positively to consumer confidence in most quantiles. Table 3 shows the opposite for consumer confidence: summing the three lagged coefficients gives -0.026 at the 25th quantile, -0.001 at the 50th, and +0.003 at the 75th. So only the top quantile is positive. The text then says the lagged consumer confidence coefficient is 'unexpectedly negative and significant' in all quantiles—which contradicts both the table and the abstract. The impulse response text says a positive shock to the current ratio raises Q, while Table 3 and the abstract say CR is negative. The debt-to-asset coefficient flips sign from positive at the 25th quantile to negative at the median and 75th. Granger causality statistics are impossibly large (chi-squared values in the millions to billions), which suggests a computational or reporting error. The robustness PVM drops EPU and recession risk entirely because of collinearity, so the central negative-EPU claim is not actually corroborated by the VAR-MIDAS.\n\nThe stationarity concern the reader raised is real but secondary: the LLC test assumes cross-sectional independence, and twelve same-industry firms surely share macro shocks. But the sign inconsistencies alone sink the paper. There are no replication materials, and 'data available upon request' is not enough for a quantitative paper.\n\nWho is this for? Anyone studying sector-level uncertainty and firm value might find the sample interesting, but the current manuscript cannot be used as evidence. It needs a careful re-estimation and a consistent narrative. I would not send this to referees in its present form; it would waste their time. A desk reject with an invitation to resubmit after fixing the internal contradictions and providing code/data would be appropriate.","headline":"The durable-goods extension is sensible, but the paper's own Table 3 contradicts its abstract on consumer confidence and the Granger statistics are implausible.","tokens_in":23748,"tokens_out":3128,"would_cite":false,"duration_ms":35697,"reading_group":"no","serious_thinker":"no","would_accept_peer_review":false},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"Macro uncertainty is priced into durable goods makers' market value: policy uncertainty, recession risk, and inflation expectations lower Tobin's Q, while consumer confidence raises it.","keywords":["Tobin's Q","economic policy uncertainty","panel quantile regression","VAR-MIDAS","consumer confidence","inflation expectations","recession risk","durable goods"],"falsifier":"Re-estimate equation (5) allowing the twelve firms to share common business-cycle shocks, using an estimator that does not assume cross-sectional independence; if the negative coefficients on EPU, recession risk, and inflation expectations and the positive coefficient on consumer confidence survive, the claim is confirmed, and if they disappear the reported result is an artifact of the independence assumption.","tokens_in":22708,"feed_emoji":"📉","tokens_out":10651,"duration_ms":113571,"temperature":0.7,"pith_summary":"This paper asks whether macroeconomic uncertainty is priced into the market values of U.S. consumer durable goods producers. Using Tobin's Q for twelve firms from 1985 to 2022, the authors claim that economic policy uncertainty, recession risk, and inflation expectations lower firm value, while consumer confidence raises it, across most quantiles of the Q distribution. If the claim holds, standard uncertainty indicators become usable leading signals for the market value of this sector, not just descriptions of the macro environment.","feed_headline":"Policy uncertainty drags down durable-goods firm value","feed_subtitle":"Twelve durable goods firms' Q falls with policy risk and inflation expectations, but rises with consumer confidence.","key_machinery":"The machinery is a three-part econometric sequence. Tobin's Q, market value of assets over replacement cost, is the dependent variable. Panel quantile regression estimates covariate effects at the 25th, 50th, and 75th percentiles of Q, capturing distribution-dependent responses rather than a single average effect. The panel VAR-MIDAS model is a panel vector autoregression that keeps quarterly firm-level data and monthly uncertainty data at their own frequencies and traces impulse responses. Granger causality tests on the lagged uncertainty terms complete the link from uncertainty to subsequent Q.","core_discovery":"The paper's central claim is that Tobin's Q for twelve U.S. consumer durable goods producers moves systematically with macro uncertainty. In panel quantile regressions estimated at the 25th, 50th, and 75th percentiles of Q, economic policy uncertainty, recession risk, and inflation expectations enter with negative coefficients, and consumer confidence with positive coefficients, at most quantiles; the effects are strongest among high-Q firms. The panel VAR-MIDAS impulse responses show Q falling after positive inflation-expectation shocks and rising after consumer-confidence shocks, and Granger causality tests show the uncertainty indicators predict changes in Q. Among the firm-level controls, the quick ratio and operating income after depreciation move Q up, while the current ratio and debt-to-asset ratio move it down in most quantiles.","pith_inferences":["Our inference: the negative effect of the current ratio on Q suggests investors may read high liquidity as idle cash or caution, a mechanism the paper does not develop; it could be tested by interacting liquidity with investment opportunity.","Our inference: because the twelve firms share macro shocks, the cleanest way to separate pricing of uncertainty from common cyclicality would be to compare durable goods producers against a less cyclically exposed industry in the same quarters.","Our inference: if the Granger-causal channel is real, then a simple testable strategy is to track EPU and consumer confidence as leading indicators for the market values of this sector, and to check whether valuation changes precede changes in cash flows."],"forward_implications":["Lagged values of EPU, recession risk, and inflation expectations are predictors of future changes in durable goods firm value, not just contemporaneous correlates.","Firms in the upper tail of the Q distribution absorb the largest valuation hit from uncertainty, so high-valued producers have the most to gain from hedging.","Consumer confidence and firm value move together, so a falling sentiment index is an early warning that durable goods valuations will soften.","Markets treat expected inflation as a risk to durable goods makers' value rather than a stimulus to buy now, which matters for pricing and capital budgeting in the sector."],"supporting_citations":[{"why":"Supplies the monthly economic policy uncertainty index that is the main uncertainty regressor.","marker":"Baker et al. (2016)"},{"why":"Introduces regression quantiles, the estimation concept behind the panel quantile regressions.","marker":"Koenker and Bassett (1978)"},{"why":"Extends quantile regression to longitudinal data, the basis of the panel quantile specification.","marker":"Koenker (2004)"},{"why":"Develops the mixed-frequency MIDAS approach that the panel VAR-MIDAS model relies on.","marker":"Ghysels et al. (2004 and 2016)"},{"why":"Provides the smoothed U.S. recession probability series used as recession risk.","marker":"Chauvet and Piger (2008)"},{"why":"Earlier panel evidence that economic policy uncertainty lowers Tobin's Q, which this study extends to durable goods.","marker":"García-Gómez et al. (2022)"}],"fun_headline_variants":["Policy uncertainty drags durable-goods firm value","Durable-goods Q slides on policy risk, climbs on confidence","Uncertainty shocks cut durable goods makers' Tobin's Q","Consumer confidence buoys durable-goods firms, policy fears sink"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The load-bearing premise is that the unit-root and first-differencing steps are valid, which requires the twelve firms' shocks to be independent even though they share the same durable goods industry and the same macroeconomy.","fun_headline_variants_meta":{"raw":{"variants":["Policy uncertainty drags durable-goods firm value","Durable-goods Q slides on policy risk, climbs on confidence","Uncertainty shocks cut durable goods makers' Tobin's Q","Consumer confidence buoys durable-goods firms, policy fears sink"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000217,"raw_usage":{"total_tokens":1388,"prompt_tokens":850,"completion_tokens":538,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":466,"completion_tokens_details":{"reasoning_tokens":468}},"tokens_in":466,"tokens_out":538,"duration_ms":6507,"temperature":1.0,"reasoning_tokens":468,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-07T05:33:39.254992+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Re-estimate equation (5) allowing the twelve firms to share common business-cycle shocks, using an estimator that does not assume cross-sectional independence; if the negative coefficients on EPU, recession risk, and inflation expectations and the positive coefficient on consumer confidence survive, the claim is confirmed, and if they disappear the reported result is an artifact of the independence assumption.","supporting_citations":[{"cited_title":"Measuring Economic Policy Uncertainty,","cited_arxiv_id":null,"evidence_quote":"Supplies the monthly economic policy uncertainty index that is the main uncertainty regressor."}],"review_version":1}