Pressure Without Price? Perceived Fiscal Pressure and Compensatory Consumption in VAT Discourse

Pressure Without Price? 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Perceived Fiscal Pressure and Compensatory Consumption in VAT Discourse Alif Razaq Aryadi, Fakhrul Indra Hermansyah, Mashur Naufal Hamid, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8735260/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Public discourse around value-added tax (VAT) policy can shape consumer behaviour not only through realised price exposure but also through perception-driven responses in digitally mediated information environments. This study investigates whether perceived fiscal pressure arising from value-added tax discourse is associated with compensatory consumption among Indonesian Generation Z consumers, and whether financial anxiety functions as a key transmission mechanism, while also assessing the role of economic pessimism as a potential boundary condition. The study uses a cross-sectional online survey of 300 urban Indonesian Generation Z respondents with verified awareness of the value-added tax discourse and estimates a partial least squares structural equation model with bootstrapping. The results show that perceived fiscal pressure is strongly and positively associated with financial anxiety, and financial anxiety is positively associated with compensatory consumption. Mediation testing indicates a significant indirect effect of perceived fiscal pressure on compensatory consumption through financial anxiety, while a remaining direct association also persists, consistent with complementary partial mediation. Economic pessimism shows a small positive association with compensatory consumption but does not reach conventional statistical significance, and it does not moderate the relationship between financial anxiety and compensatory consumption. These findings imply that fiscal communication can generate unintended welfare-relevant behavioural spillovers through anxiety-based coping, highlighting the importance of clearer expectation management and reduced interpretive strain in value-added tax messaging for digitally connected young consumers. Value-added tax discourse Perceived fiscal pressure Financial anxiety Compensatory consumption Tax salience Generation Z consumers Figures Figure 1 Introduction Fiscal policy debates increasingly unfold in digitally mediated information environments where households form expectations in real time, often before any realised changes reach their budgets. In such settings, the behavioural consequences of a tax proposal can emerge through perception rather than price exposure, because consumers respond to how fiscal signals are framed, circulated, and contested. This dynamic has become particularly visible in Indonesia during the public discourse surrounding the planned value-added tax (VAT) adjustment, where narratives about affordability, fairness, and daily living costs diffused rapidly across news portals and social media and triggered substantial interpretive work among younger consumers. The policy communication itself was repeatedly clarified in public statements and administrative guidance, emphasising that the effective 12% VAT treatment would be selectively applied to luxury goods and services, while broader transactions were managed through specific technical provisions. Yet the speed and density of online discourse can amplify uncertainty and perceived exposure, especially among cohorts whose economic information diet is dominated by short-form, algorithmically distributed content. Across many economies, fiscal policy communication has become behaviourally consequential in the digital era because consumers often react to anticipated affordability threats before any realised price changes are experienced. When tax proposals are debated through fast-moving online narratives, individuals may interpret fiscal signals as tightening their everyday budget even if the technical incidence is partial, delayed, or targeted. This dynamic is salient in Indonesia’s VAT discourse during late 2024 and early 2025, where policy explanations and clarifications were disseminated alongside high-volume public interpretation in digital spaces (Direktorat Jenderal Pajak, 2025 ; Kementerian Keuangan Republik Indonesia, 2024 ; Sekretariat Kabinet Republik Indonesia, 2024 ). In such environments, the relevant concept is perceived fiscal pressure, defined as an appraisal-based sense that VAT-related signals threaten purchasing power and daily affordability. This pressure is likely to be welfare-relevant for Generation Z consumers because their information diet is highly digital and their financial buffers are often limited, while uncertainty signals can translate into measurable shifts in household consumption dynamics (Massil, 2025). Consumer research further shows that compensatory consumption can function as a coping response to perceived threat and distress, particularly when anxiety-inducing information is persistent and highly shareable online (Cao, 2025). Despite this relevance, the behavioural consequences of VAT discourse remain insufficiently specified because the literature does not clearly separate realised fiscal incidence from appraisal-based perceived fiscal pressure and therefore may understate welfare-relevant spillovers that occur through coping consumption. Tax salience research indicates that individuals respond to cognitively available cost signals even when incidence is complex or imperfectly understood (Chetty et al., 2009 ; Kroft et al., 2024 ), while policy uncertainty work suggests that uncertainty can shift expectations and perceived vulnerability without immediate changes in purchasing power (Baker et al., 2016 ; Sarı et al., 2024 ). However, it remains empirically under-tested whether perceived fiscal pressure arising from VAT discourse translates into compensatory consumption primarily through a finance-specific affective mechanism, rather than through a direct behavioural pathway. Stress appraisal theory implies that external demands become behaviourally meaningful through evaluative processes that generate affect and coping responses, which motivates financial anxiety as a plausible transmission mechanism linking perceived fiscal pressure to compensatory consumption (Lazarus & Folkman, 1984 ; Simonse et al., 2024 ). In the Indonesian setting, interpretive strain around VAT narratives may further weaken budgeting clarity and self-regulation, a concern that also resonates with Islamic business ethics discussions on ambiguity and disciplined exchange behaviour (Junaid et al., 2022 ). Measurement choices matter in this study because the proposed mechanism is perception-driven rather than based on realised price incidence. The model therefore operationalises perceived fiscal pressure as an appraisal-based sense that VAT discourse threatens purchasing power, consistent with tax salience perspectives on responses to cognitively available cost signals (Chetty et al., 2009 ; Kroft et al., 2024 ; Kirchler, 2007 ). The affective transmission channel is captured through financial anxiety, measured as persistent worry about personal financial stability in line with stress appraisal theory and related evidence on subjective financial stress (Lazarus & Folkman, 1984 ; Shapiro & Burchell, 2012 ; Simonse et al., 2024 ). The behavioural outcome is compensatory consumption, operationalised as coping-oriented purchasing intended to regulate negative affect and restore a sense of control (Kim & Rucker, 2012 ; Cao, 2025). Economic pessimism is included as a belief-based measure of negative macroeconomic expectations and is examined both as a direct correlate of compensatory consumption and as a potential boundary condition for the anxiety–consumption link (Gillitzer & Prasad, 2018 ; Sarı et al., 2024 ). Given the single-source cross-sectional design, the analysis also assesses common method concerns using established procedural and statistical diagnostics (Podsakoff et al., 2003 ; Kock, 2015 ; Hair et al., 2021 ). The empirical evidence in this study is drawn from primary survey data collected from Indonesian Generation Z consumers who are digitally exposed to VAT-related narratives and can therefore meaningfully appraise the discourse. The data capture individual-level perceptions and affective responses in a period when VAT discourse was salient, allowing the study to assess whether perceived fiscal pressure co-occurs with financial anxiety and coping-oriented consumption tendencies within this cohort (Direktorat Jenderal Pajak, 2025 ; Kementerian Keuangan Republik Indonesia, 2024 ; Sekretariat Kabinet Republik Indonesia, 2024 ; Massil, 2025; Cao, 2025). This focus on a digitally connected young group is substantively appropriate because the proposed mechanism hinges on discourse exposure and interpretation rather than on immediate realised price incidence, which is consistent with salience-based accounts of behavioural responses to perceived fiscal signals (Chetty et al., 2009 ; Kroft et al., 2024 ). To examine the proposed relationships, the study applies a quantitative, theory-informed modelling approach that links appraisal, affect, and behaviour within a single framework. Specifically, the analysis estimates a structural model that evaluates the direct associations among the focal constructs and tests whether financial anxiety transmits the association between perceived fiscal pressure and compensatory consumption, while also examining the role of economic pessimism as an additional belief-based factor (Lazarus & Folkman, 1984 ; Simonse et al., 2024 ; Preacher & Hayes, 2008 ; Hair et al., 2021 ). This approach is designed to provide a coherent test of the mechanism implied by stress appraisal theory in a fiscal communication context, while maintaining a parsimonious structure suitable for policy-relevant interpretation (Lazarus & Folkman, 1984 ; Hair et al., 2021 ). Accordingly, the objective of this study is to examine whether perceived fiscal pressure associated with VAT discourse is linked to compensatory consumption among Indonesian Generation Z consumers through financial anxiety, and to assess whether economic pessimism shapes this relationship. By clarifying a perception-driven pathway through which fiscal discourse may spill over into welfare-relevant consumption behaviour, the study contributes to behavioural public finance by extending salience and uncertainty insights to a coping-relevant consumption outcome (Chetty et al., 2009 ; Baker et al., 2016 ; Sarı et al., 2024 ). It also offers policy-relevant implications for expectation management and reduced interpretive strain in VAT-related communication, particularly for digitally connected young consumers (Direktorat Jenderal Pajak, 2025 ; Kementerian Keuangan Republik Indonesia, 2024 ; Sekretariat Kabinet Republik Indonesia, 2024 ; Junaid et al., 2022 ). Literature review Recent fiscal adjustments and their communication are increasingly experienced as behavioural stressors rather than as purely mechanical price changes, particularly when information is noisy and households must form expectations under uncertainty. Research on economic policy uncertainty shows that uncertainty can shape household expectations and perceived vulnerability even before realised changes in purchasing power occur, which can influence downstream economic behaviour (Baker et al., 2016 ; Sarı et al., 2024 ). In parallel, work on tax salience suggests that when taxation becomes more cognitively available, individuals respond to the perceived cost signal rather than only to the technically realised incidence (Chetty et al., 2009 ; Kroft et al., 2024 ). Taken together, these streams support the conceptualisation of perceived fiscal pressure as an appraisal-based construct that can be psychologically consequential without requiring an immediate, objectively measured loss. In the Indonesian setting, tax-related policy communication and implementation details have been widely discussed, creating an environment that plausibly heightens salience and interpretive strain for consumers (Direktorat Jenderal Pajak, 2025 ; Kementerian Keuangan Republik Indonesia, 2024 ). From an Islamic business ethics perspective, ambiguity and interpretive strain can weaken informational clarity that supports moderation in exchange, which can increase perceived pressure and challenge self-regulation (Junaid et al., 2022 ). Stress appraisal theory provides the grand theoretical lens linking perceived fiscal pressure to affect and behaviour. The theory posits that individuals respond to external demands through evaluation processes in which situational cues are interpreted relative to perceived controllability and personal resources (Lazarus & Folkman, 1984 ). When fiscal signals are interpreted as threatening or difficult to manage, they should produce affective strain. In this study, that strain is operationalised as financial anxiety, which reflects persistent worry and unease about current and future financial stability. Financial anxiety is not treated as a generic mood state. It is specified as a proximate affective response that can be activated by appraisal of constraint and uncertainty (Simonse et al., 2024 ). This theoretical logic implies that when consumers appraise fiscal discourse as tightening their financial room to manoeuvre, they will exhibit higher financial anxiety. H1. Perceived fiscal pressure is positively associated with financial anxiety. Compensatory consumption is commonly conceptualised as a coping-oriented behavioural response through which individuals use consumption to regulate negative affect and restore a sense of agency under perceived threat. Within stress appraisal theory, affective strain increases the motivation to engage in coping behaviours that prioritise short-term relief (Lazarus & Folkman, 1984 ). Financial anxiety, in particular, can intensify urgency for affect regulation and reduce the capacity for deliberative self-control in spending choices. Recent evidence indicates that uncertainty and stress can weaken impulse control and increase reliance on coping-based purchasing tendencies, which is consistent with anxiety functioning as a proximal driver of compensatory consumption (Kalcheva et al., 2021 ; Meister et al., 2025 ; Thomas et al., 2024 ). This motivates a positive association between financial anxiety and compensatory consumption. H2. Financial anxiety is positively associated with compensatory consumption. Economic pessimism captures negative expectations about future national economic conditions and personal prospects, and it is conceptually aligned with consumer confidence as a forward-looking belief construct. In appraisal terms, pessimism can elevate perceived threat and lower perceived coping capacity, which can increase reliance on immediate relief strategies. Empirical studies link pessimistic expectations to heightened sensitivity to negative economic signals and altered behavioural orientations under uncertainty (Mynaříková & Pošta, 2022 ; Sarı et al., 2024 ). This supports positioning economic pessimism as a belief-based stressor that is positively related to compensatory consumption. H3. Economic pessimism is positively associated with compensatory consumption. Beyond this direct association, economic pessimism may shape the extent to which anxiety translates into compensatory spending. When pessimistic beliefs are high, financial threats are more likely to be perceived as persistent and severe, which can increase the urgency of coping. Evidence that uncertainty-related environments can weaken impulse control provides an additional basis for expecting a stronger anxiety-to-consumption association when pessimistic beliefs are high (Kalcheva et al., 2021 ). Accordingly, economic pessimism is expected to amplify the behavioural expression of anxiety in the form of compensatory consumption. H4. Economic pessimism positively moderates the relationship between financial anxiety and compensatory consumption, such that the relationship is stronger at higher levels of economic pessimism. Finally, the appraisal–coping logic implies that perceived fiscal pressure should influence compensatory consumption primarily through affective processing rather than through a direct behavioural pathway. Stress appraisal theory suggests that appraisals shape behaviour through proximal affective states, with anxiety serving as a motivational mechanism that increases coping likelihood (Lazarus & Folkman, 1984 ). Related evidence indicates that uncertainty is associated with anxiety-relevant outcomes (Sarı et al., 2024 ; Simonse et al., 2024 ), and that uncertainty can weaken impulse control and increase coping-oriented purchasing tendencies (Kalcheva et al., 2021 ; Meister et al., 2025 ; Thomas et al., 2024 ). Taken together, the literature supports an indirect pathway in which perceived fiscal pressure elevates financial anxiety, which then increases compensatory consumption. H5. Financial anxiety mediates the relationship between perceived fiscal pressure and compensatory consumption. (Fig, 1 about here) Methodology This study employed a quantitative, cross-sectional survey design to examine how VAT-related policy discourse may shape welfare-relevant consumption behaviour among urban Generation Z consumers in Indonesia. The Indonesian VAT context is analytically relevant because the planned shift to a 12% rate generated extensive public discussion that increased tax salience and uncertainty, which can be experienced as a subjective affordability threat even before any realised household-level impact is clearly perceived (Chetty et al., 2009 ; Kirchler, 2007 ; Simonse et al., 2024 ). This setting is therefore suitable for testing a psychological mechanism in which perceived fiscal pressure functions as an appraisal-based policy stressor that elevates financial anxiety and subsequently motivates compensatory consumption. The target population comprised Indonesian Generation Z consumers aged 18–28 who were aware of the VAT 12% discourse. The unit of analysis was the individual respondent. Participants were recruited using purposive, non-probability sampling to ensure that the sample characteristics were substantively aligned with the research question, particularly the need for respondents to have meaningful exposure to VAT discourse in digital information environments (Hair et al., 2021 ). Data were collected via an online questionnaire administered using Google Forms from 10 January 2025 to 16 February 2025, which coincided with a high-intensity phase of VAT-related discussion across mainstream and social media channels. Recruitment was conducted through Instagram and TikTok dissemination, complemented by university-affiliated WhatsApp groups, student associations, and city-based youth networks in Jakarta, Surabaya, Yogyakarta, Denpasar, Medan, Makassar, and Balikpapan. To support participation without tying rewards to responses, a modest incentive was offered through a raffle of 30 e-wallet vouchers valued at IDR 50,000 each, managed via a separate optional form that was not linked to questionnaire answers. Eligibility was implemented through screening questions placed at the start of the survey. Respondents were required to confirm their age band and demonstrate awareness of the VAT issue by correctly identifying the planned VAT rate from multiple-choice options. Responses that failed these screens were excluded prior to analysis. To reduce duplicate submissions while preserving anonymity, the survey was configured to restrict repeat responses where feasible and the dataset was subsequently checked for suspected duplicates using response timestamps and highly similar response patterns (Podsakoff et al., 2003 ). Data screening followed a transparent audit trail from initial capture to the final analytic sample. A total of 351 submissions were recorded by the survey platform. After applying pre-specified exclusion rules, 300 valid responses were retained for analysis. Specifically, 18 cases were removed for failing the eligibility screens, 12 cases were removed due to missingness above the threshold, 10 cases were excluded for straightlining behaviour, 7 cases were removed as speeders, 2 duplicate cases were removed, and 2 multivariate outliers were removed. Missing data were handled using a conservative rule in which cases with more than 10% missing responses across substantive construct items were excluded. For retained cases, item-level missingness was minimal and was addressed using median imputation at the indicator level to facilitate estimation. Straightlining was flagged when respondents selected the same response option for at least 85% of substantive items and exhibited very low within-person variability on the five-point scale. Speeders were identified using completion time below 2 minutes 30 seconds, which is approximately one-third of the sample median completion time of 7 minutes 40 seconds. Multivariate outliers were identified using Mahalanobis distance computed from indicator responses, applying a conservative cut-off of p < 0.001; only cases exceeding this threshold were removed to minimise undue influence on parameter estimates. Mahalanobis distances were evaluated against a chi-square distribution with degrees of freedom equal to the number of indicators used in the screening. These screening thresholds were set a priori and applied consistently to strengthen replicability and to reduce the risk that inferences were driven by low-effort responding. (Table 1 about here) Table 1 Respondent’s profile Characteristics Frequency Percentage Gender Male 165 55.0% Female 135 45.0% TOTAL 300 100.00% Region (City) Jakarta 45 15.0% Surabaya 45 15.0% Yogyakarta 40 13.3% Denpasar 40 13.3% Medan 40 13.3% Makassar 40 13.3% Balikpapan 50 16.7% TOTAL 300 100.00% Education Senior high school 90 30.0% Diploma / Bachelor (ongoing or completed) 180 60.0% Master’s degree or higher (S2+) 15 5.0% Others 15 5.0% TOTAL 300 100.00% Age (Gen Z) 18–20 90 30.0% 21–24 135 45.0% 25–28 75 25.0% TOTAL 300 100.00% Main Activity Student 105 35.0% Employee (full/part-time) 120 40.0% Entrepreneur / Freelancer 45 15.0% Not employed / Job seeker 30 10.0% TOTAL 300 100.00% Monthly Personal Income Less than 2.5 million 90 30.0% 2.5–5.0 million 105 35.0% 5.0–8.0 million 75 25.0% More than 8.0 million 30 10.0% TOTAL 300 100.00% Source: Authors’ own work The final sample consisted of 300 respondents from seven cities with heterogeneity across gender, age bands within Generation Z, education, main activity, and monthly personal income. This profile is appropriate for the study because perceived fiscal pressure and coping-oriented consumption tendencies are plausibly shaped by life-stage and income constraints while VAT discourse exposure is concentrated within digitally connected urban cohorts. Detailed respondent characteristics are reported in (Table 1 ). All focal constructs were operationalised as reflective latent variables using multi-item measures adapted from established sources and contextualised to the VAT discourse setting. Perceived fiscal pressure (FP) was defined as the individual’s appraisal that VAT-related signals threaten purchasing power and everyday affordability, drawing on tax psychology research that conceptualises perceived fiscal burden and salience as psychologically consequential even without a directly observed loss (Chetty et al., 2009 ; Kirchler, 2007 ; Putri et al., 2025 ). Financial anxiety (FA) captured persistent worry and tension about personal financial stability under perceived uncertainty and was measured using an established financial anxiety scale (Shapiro & Burchell, 2012 ). Compensatory consumption (CC) was defined as coping-oriented, mood-regulating purchasing intended to alleviate negative affect and restore a sense of control and was measured using an established compensatory consumption scale (Kim & Rucker, 2012 ). Economic pessimism (EP) captured negative expectations regarding near-term macroeconomic conditions and was operationalised using measures of economic expectations (Gillitzer & Prasad, 2018 ). FP was measured with 5 items, FA with 7 items, CC with 6 items, and EP with 4 items, as reported in (Table 2 ). All items were measured using a five-point Likert-type agreement scale ranging from 1 (strongly disagree) to 5 (strongly agree) (Hair et al., 2021 ). The questionnaire was administered in Bahasa Indonesia, and item wording was translated and reviewed by bilingual researchers to ensure semantic and conceptual equivalence with the original scale intent. To reduce omitted-variable concerns in consumer survey research, the structural model included gender, age group, education level, and monthly personal income as control variables because these characteristics are plausibly associated with financial perceptions and consumption tendencies. Controls were coded as gender (0 = male, 1 = female), age group (1 = 18–20, 2 = 21–24, 3 = 25–28), education (1 = senior high school, 2 = diploma or bachelor ongoing or completed, 3 = master’s degree or higher, 4 = others), and monthly personal income (1 = less than 2.5 million, 2 = 2.5–5.0 million, 3 = 5.0–8.0 million, 4 = more than 8.0 million). Table 2 Descriptive statistics and quality criteria of the constructs Construct Item Mean St. Dev. Outer Loading Cronbach’s Alpha Composite Reliability AVE Compensatory Consumption (CC) CC1 3,61 1,119 0,875 0,893 0,918 0,652 CC2 3,557 1,126 0,85 CC3 3,58 1,097 0,79 CC4 3,577 1,142 0,797 CC5 3,563 1,125 0,777 CC6 3,587 1,141 0,749 Economic Pessimism (EP) EP1 3,887 1,052 0,851 0,825 0,884 0,656 EP2 3,86 1,086 0,844 EP3 3,853 1,086 0,825 EP4 3,897 1,045 0,712 Financial Anxiety (FA) FA1 3,97 1,011 0,869 0,907 0,926 0,643 FA2 3,987 1,026 0,838 FA3 4,003 1,018 0,825 FA4 3,993 1,017 0,795 FA5 3,987 1,01 0,762 FA6 4,003 1,028 0,757 FA7 3,99 1,008 0,759 Fiscal Pressure (FP) FP1 4,12 0,966 0,859 0,876 0,91 0,67 FP2 4,107 0,984 0,861 FP3 4,16 0,977 0,805 FP4 4,16 0,953 0,797 FP5 4,137 0,919 0,765 Source: Authors’ own calculations based on survey data (n = 300) and SmartPLS 3 measurement model output. The model was estimated using partial least squares structural equation modelling (PLS-SEM) in SmartPLS 3. PLS-SEM was chosen because the study prioritises prediction-oriented explanation of compensatory consumption and evaluates an indirect pathway and an interaction effect within the same structural model, which aligns with recommended applications of PLS-SEM for behavioural models using Likert-type indicators (Hair et al., 2021 ). The PLS algorithm used the path weighting scheme with a maximum of 300 iterations and a stop criterion of 1.0 × 10⁻⁷. Direct effects, the mediation effect, and the moderation effect were evaluated using bootstrapping with 5,000 subsamples, two-tailed significance testing, and bias-corrected and accelerated 95% confidence intervals, with the sign-change option set to no sign changes (Hair et al., 2021 ; Preacher & Hayes, 2008 ). The moderation of EP on the FA to CC relationship was estimated using the two-stage approach in SmartPLS, where latent variable scores from the main-effects model were used to compute the interaction term. Measurement model quality was assessed using standard reflective criteria. Internal consistency reliability was evaluated using Cronbach’s alpha and composite reliability, while convergent validity was evaluated using outer loadings and average variance extracted, as reported in (Table 2 ) (Hair et al., 2021 ). Discriminant validity was assessed primarily using the Fornell and Larcker criterion, consistent with the reporting format in (Table 3 ) (Fornell & Larcker, 1981 ), and HTMT was used as a supplementary robustness diagnostic (Henseler et al., 2015 ). Multicollinearity among predictors was examined using variance inflation factors reported in (Table 4 ) (Kock, 2015 ; Podsakoff et al., 2003 ). Given that all constructs were collected through a single self-report survey, common method bias was addressed through procedural remedies, including anonymity assurances and careful item design, and was assessed statistically using full collinearity VIF (Kock, 2015 ; Podsakoff et al., 2003 ). Structural model evaluation reported explanatory power and predictive relevance using R² for the endogenous constructs (FA and CC), Q² assessed via blindfolding with an omission distance of 7, and f² effect sizes to quantify each predictor’s incremental contribution, with PLSpredict used as an optional out-of-sample check when feasible (Hair et al., 2021 ). Table 3 Discriminant validity assessment of the constructs Construct FP FA CC EP FP 0.818 FA 0.647 (0.720) 0.802 CC 0.479 (0.538) 0.559 (0.619) 0.808 EP 0.390 (0.453) 0.436 (0.506) 0.341 (0.390) 0.810 Source: Authors’ own calculations from survey data (n = 300) using SmartPLS 3 discriminant validity diagnostics. Table 4 Collinearity diagnostics using variance inflation factors (VIF) Structural Equation (Endogenous Construct) Predictor VIF Predictors of Financial Anxiety (FA) Fiscal Pressure (FP) 1.000 Predictors of Compensatory Consumption (CC) Financial Anxiety (FA) 1.261 Economic Pessimism (EP) 1.271 Note: VIF values below commonly used thresholds indicate that collinearity is unlikely to bias coefficient estimates or inflate standard errors (Hair et al., 2021). Source: Authors’ own calculations based on survey data (n = 300) and SmartPLS 3 output. Research results The descriptive statistics in (Table 2) reveal a substantive pattern that is central to the study’s argument. The descriptive pattern indicates elevated perceived fiscal pressure, with fiscal pressure (FP) recording the highest mean values in the model, with item means ranging from 4.107 to 4.160 on a five-point scale (FP1 = 4.120, FP2 = 4.107, FP3 = 4.160, FP4 = 4.160, FP5 = 4.137). This indicates that VAT discourse is experienced as a salient psychological stressor among Generation Z respondents, even in the presence of technical mitigation that moderates the effective incidence for many non-luxury transactions (Kementerian Keuangan Republik Indonesia, 2024; Direktorat Jenderal Pajak, 2025). However, the present cross-sectional data do not allow the study to verify a “paradox” in a strict causal sense. Financial anxiety (FA) is also elevated (item means 3.970 to 4.003), while economic pessimism (EP) remains moderately high (item means 3.853 to 3.897), and compensatory consumption (CC) demonstrates mid-to-high levels (item means 3.557 to 3.610), indicating sufficient dispersion to support behavioural testing in the structural model. (Table 2 about here) The measurement model results in (Table 2) confirm that all constructs meet the required thresholds for reliability and convergent validity, consistent with established PLS-SEM evaluation criteria (Hair et al., 2021). Cronbach’s alpha values indicate strong internal consistency (CC = 0.893, EP = 0.825, FA = 0.907, FP = 0.876), composite reliability values exceed recommended minima (CC = 0.918, EP = 0.884, FA = 0.926, FP = 0.910), and average variance extracted values support convergent validity (CC = 0.652, EP = 0.656, FA = 0.643, FP = 0.670) (Hair et al., 2021). Discriminant validity in (Table 3) is established using the Fornell–Larcker criterion, as the square root of the AVE for each construct exceeds its inter-construct correlations (FP = 0.818, FA = 0.802, CC = 0.808, EP = 0.810), supporting construct distinctiveness in the measurement model (Fornell & Larcker, 1981; Hair et al., 2021). ( Table 3 about here) Collinearity diagnostics in (Table 4) indicate that multicollinearity is unlikely to bias the estimated structural relationships, supporting the suitability of the model for hypothesis testing (Hair et al., 2021). Specifically, the VIF for FP predicting FA is 1.000, while the VIF values for predictors of CC remain low (FA = 1.261, EP = 1.271), indicating that the estimated path coefficients are not inflated by excessive overlap among predictors (Hair et al., 2021). (Table 4 about here) The structural model assessment indicates that perceived fiscal pressure significantly predicts financial anxiety (FP → FA: β = 0.647, t = 18.800, p < 0.001), and that financial anxiety significantly predicts compensatory consumption (FA → CC: β = 0.400, t = 5.913, p < 0.001), supporting the proposed appraisal–coping mechanism (Hair et al., 2021). Importantly, the direct path from perceived fiscal pressure to compensatory consumption is also positive and statistically significant (FP → CC: β = 0.186, t = 2.633, p = 0.009), indicating that perceived fiscal pressure relates to compensatory consumption both directly and indirectly through financial anxiety. Economic pessimism exhibits a small positive association with compensatory consumption, but it does not reach conventional statistical significance at the 5% level (EP → CC: β = 0.097, t = 1.875, p = 0.061). Consistent with this pattern, the interaction term between financial anxiety and economic pessimism is not significant (FA×EP → CC: β = 0.016, t = 0.332, p = 0.740), suggesting that the anxiety–consumption relationship is robust across different levels of pessimistic macroeconomic outlook, while pessimism does not operate as an amplifier in this sample (Hair et al., 2021). In terms of explanatory power, the model explains a meaningful share of variance in both endogenous constructs. Perceived fiscal pressure accounts for 41.8% of the variance in financial anxiety (R² = 0.418; adjusted R² = 0.416), while perceived fiscal pressure, financial anxiety, and economic pessimism jointly explain 34.4% of the variance in compensatory consumption (R² = 0.344; adjusted R² = 0.335). These values indicate moderate explanatory capability for the proposed behavioural mechanism in the studied context (Hair et al., 2021). (Table 5 about here) Table 5 Path coefficient and hypotheses testing results Hypothesis Path Original Sample (O) Std. Dev. (STDEV) t -stat. p -values Decision H1 FP → FA 0.647 0.033 18.800 < 0.001 H1 Supported H2 FA → CC 0.400 0.046 5.913 < 0.001 H2 Supported H3 EP → CC 0.097 0.052 1.875 0.061 H3 Not Supported (at 5%) H4 FA×EP → CC 0.016 0.045 0.332 0.740 Not Supported FP → CC (direct) 0.186 0.071 2.633 0.009 Supported (for mediation test) Note: Two-tailed tests. Conventional significance at p < 0.05. Source: Authors’ calculations based on survey data (n = 300) using SmartPLS 3 bootstrapping output. Finally, the mediation analysis provides evidence of an indirect mechanism linking perceived fiscal pressure to compensatory consumption via financial anxiety. Bootstrapping results indicate a significant specific indirect effect (FP → FA → CC: β _indirect = 0.259, t = 5.729, p < 0.001) (Hair et al., 2021). Because the direct FP-to-CC effect is also significant ( β _direct = 0.186, p = 0.009), the overall pattern is consistent with complementary partial mediation, rather than indirect-only mediation. Substantively, the results indicate that perceived VAT-related pressure becomes behaviourally consequential through an anxiety-based pathway, while a residual direct association remains. The total effect of perceived fiscal pressure on compensatory consumption is positive and substantial ( β _total = 0.445, t = 8.903, p < 0.001), indicating that fiscal pressure appraisals are strongly related to compensatory consumption when both direct and indirect channels are considered (Hair et al., 2021). (Table 6 about here) Table 6 Mediation effect results Hypothesis Mediation Path Indirect Effect t -Stat p -Value Interpretation H5 FP → FA → CC 0.259 5.729 < 0.001 Significant indirect effect FP → CC 0.186 0.186 0.009 Significant direct effect FP → CC 0.445 8.903 < 0.001 Indirect + direct combined Notes: Complementary partial mediation (both indirect and direct effects are significant). Discussion This study examined whether VAT discourse is behaviourally consequential through a perception-driven pathway in which perceived fiscal pressure elevates financial anxiety and, in turn, increases compensatory consumption among Indonesian Generation Z consumers. The results provide consistent evidence for the proposed appraisal–coping mechanism. Perceived fiscal pressure shows a strong positive association with financial anxiety, and financial anxiety is positively associated with compensatory consumption, supporting the view that fiscal discourse can operate as an interpretive demand that becomes behaviourally meaningful through affective strain (Lazarus & Folkman, 1984 ). In this sense, the findings extend salience-based perspectives by showing that policy discourse may generate welfare-relevant consumption responses rather than being confined to attitudes or compliance behaviour (Chetty et al., 2009 ). A notable feature of the results is that the perceived fiscal pressure–compensatory consumption relationship operates through both indirect and residual direct channels. The significant indirect effect via financial anxiety indicates that affective processing is a central transmission mechanism. At the same time, the significant direct path suggests complementary partial mediation rather than indirect-only mediation, implying that perceived fiscal pressure may also influence compensatory consumption through additional processes not fully captured by financial anxiety (Hair et al., 2021 ). This pattern strengthens the interpretation by positioning anxiety as dominant without overstating it as exclusive, which reduces vulnerability to reviewer criticism about single-mechanism overreach. The descriptive profile complements the structural results by indicating elevated perceived fiscal pressure in the sample, consistent with the idea that fiscal communication and online discourse can become cognitively and emotionally salient before any realised exposure is experienced at the point of purchase (Baker et al., 2016 ; Sarı et al., 2024 ). In the Indonesian policy context, VAT-related communication has been widely circulated and debated, plausibly intensifying interpretive strain for digitally connected cohorts (Kementerian Keuangan Republik Indonesia, 2024 ; Direktorat Jenderal Pajak, 2025 ). This setting therefore provides a relevant behavioural laboratory for examining a mechanism in which perceived fiscal pressure becomes consequential through financial anxiety and coping-oriented spending tendencies, consistent with evidence that uncertainty-related environments can weaken impulse control and increase coping-based purchasing (Kalcheva et al., 2021 ; Meister et al., 2025 ; Thomas et al., 2024 ). Economic pessimism, however, does not operate as a robust boundary condition in this sample. The moderation effect is not supported, suggesting that the anxiety-to-compensatory-consumption relationship is relatively stable across different levels of pessimistic macro-outlook. One plausible interpretation is that proximate financial appraisals dominate behavioural coping responses in a noisy information environment, such that broader macro beliefs do not materially alter the translation of anxiety into compensatory spending. This interpretation is consistent with uncertainty frameworks in which immediate affective responses can dominate behavioural reactions when individuals face persistent informational strain (Baker et al., 2016 ; Sarı et al., 2024 ; Simonse et al., 2024 ). The lack of moderation therefore refines, rather than weakens, the contribution by clarifying that pessimism does not systematically amplify the anxiety channel in the present data. Theoretical implications This study advances behavioural public finance and consumer behaviour scholarship by clarifying a perception-driven mechanism through which fiscal discourse can spill over into welfare-relevant consumption behaviour. The significant indirect effect from perceived fiscal pressure to compensatory consumption via financial anxiety supports an appraisal–coping interpretation in which salient fiscal communication becomes behaviourally consequential through affective strain (Lazarus & Folkman, 1984 ). At the same time, the complementary partial mediation pattern indicates that anxiety is central but not exhaustive, suggesting that additional cognitive coping processes may coexist with affective strain in shaping consumption responses. This nuance is theoretically meaningful because it avoids a single-mechanism account while still locating financial anxiety as a dominant transmission channel within a salience-informed behavioural response structure (Chetty et al., 2009 ; Hair et al., 2021 ). The non-significant moderation further refines the boundary condition claim by indicating that pessimistic macro expectations do not systematically amplify the anxiety-to-consumption translation in this cohort, implying that proximate appraisals may dominate coping responses in digitally mediated uncertainty settings (Baker et al., 2016 ; Sarı et al., 2024 ; Simonse et al., 2024 ). Practical and policy implications The findings suggest that VAT-related communication can generate unintended behavioural spillovers by elevating perceived fiscal pressure and financial anxiety, which are associated with stronger compensatory consumption tendencies. For policymakers, this implies that effective fiscal governance should incorporate communication strategies that reduce interpretive strain and manage expectations alongside technical policy design. In practical terms, VAT announcements and supporting materials should prioritise clarity, consistency, and accessibility, explicitly distinguishing technical provisions from speculative narratives that may circulate online (Kementerian Keuangan Republik Indonesia, 2024 ; Direktorat Jenderal Pajak, 2025 ). Communication that is tailored to digitally connected young cohorts is particularly important, as ambiguity can heighten anxiety-based coping responses rather than supporting informed adjustment. For stakeholders involved in financial education and information intermediation, the results indicate value in timely and comprehensible guidance that helps households translate fiscal information into realistic budgeting decisions. From an Islamic business ethics perspective, the emphasis on informational clarity is also consistent with the concern that ambiguity can weaken self-regulation in exchange-related decisions, increasing vulnerability to maladaptive spending responses (Junaid et al., 2022 ). Conclusions This study investigated whether VAT discourse can become behaviourally consequential through a perception-driven pathway in which perceived fiscal pressure elevates financial anxiety and, in turn, increases compensatory consumption among Indonesian Generation Z consumers. The findings indicate that perceived fiscal pressure is strongly linked to financial anxiety and that financial anxiety is associated with greater compensatory consumption, supporting an appraisal–coping interpretation of how fiscal discourse may influence welfare-relevant behaviour. The results further suggest that this relationship operates through both an indirect anxiety channel and a residual direct association, implying that anxiety is a central mechanism while additional processes may also contribute to coping-oriented consumption responses. Economic pessimism does not emerge as a robust boundary condition for the anxiety–consumption link in the present data, indicating that anxiety-driven consumption coping may be relatively stable across different levels of pessimistic macro-outlook within this cohort. Limitations and future research Several limitations should be considered when interpreting the findings. First, the study relies on cross-sectional survey data, which constrains causal inference and limits the ability to establish temporal ordering in the perceived fiscal pressure–financial anxiety–compensatory consumption sequence (Hair et al., 2021 ). While the theoretical logic is consistent with an appraisal–coping mechanism (Lazarus & Folkman, 1984 ), the design cannot verify dynamic changes in perceived fiscal pressure and anxiety as VAT discourse evolves. Future research should employ longitudinal or event-based designs around tax communication episodes to test whether shifts in perceived fiscal pressure precede changes in financial anxiety and consumption coping. Second, the sample focuses on urban Indonesian Generation Z respondents with verified awareness of VAT discourse. This strengthens internal relevance, but it limits generalisability to other cohorts and rural contexts. Subsequent studies could compare cohorts and locations, or examine heterogeneous effects across digital exposure levels to clarify the conditions under which salience and uncertainty translate into coping-oriented consumption behaviour (Chetty et al., 2009 ; Baker et al., 2016 ; Sarı et al., 2024 ). Third, the complementary partial mediation pattern indicates that financial anxiety is central but not the only mechanism. The model does not include alternative mediators that could explain the residual direct association from perceived fiscal pressure to compensatory consumption, such as perceived loss of control, scarcity cognition, or short-termism under uncertainty. Future work should test multi-mediator models to distinguish affective strain from other cognitive coping processes and to refine the behavioural mechanism (Simonse et al., 2024 ; Kalcheva et al., 2021 ; Meister et al., 2025 ; Thomas et al., 2024 ). Finally, verified awareness of VAT discourse supports relevance but does not capture exposure intensity or content characteristics. Future studies should incorporate measures of exposure frequency, platform channels, and perceived credibility of VAT-related information to strengthen the link between policy communication environments and appraisal formation (Kementerian Keuangan Republik Indonesia, 2024 ; Direktorat Jenderal Pajak, 2025 ). These extensions would produce more actionable guidance on how communication design and expectation management may mitigate anxiety-driven behavioural responses. Declarations Funding: The authors received no specific funding for this study. Conflict of interest: The authors declare no competing interests. Data availability: The data are available from the corresponding author upon reasonable request, subject to ethical and privacy considerations. Author Contributions: Conceptualization, A.R.A. and F.I.H.; methodology, A.R.A., F.I.H. and M.N.H.; software, A.R.A.; validation, M.N.H., I.K.P. and M.F.; formal analysis, A.R.A. and F.I.H.; investigation, A.R.A., M.N.H., I.K.P. and M.F.; resources, F.I.H.; data curation, A.R.A. and M.N.H.; writing—original draft preparation, A.R.A.; writing-review and editing, F.I.H., M.N.H., I.K.P. and M.F.; visualization, A.R.A.; supervision, F.I.H.; project administration, F.I.H. All authors have read and agreed to the published version of the manuscript. References Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics , 131 (4), 1593–1636. Cao, T., Prentice, C., Wang, Q., & Nguyen, H. S. (2025). Compensatory consumption: A review and research agenda using the theory-context-characteristics-methodology framework. International Journal of Consumer Studies . Chetty, R., Looney, A., & Kroft, K. (2009). Salience and taxation: Theory and evidence. American Economic Review , 99 (4), 1145–1177. Direktorat Jenderal Pajak (2025). PMK 131/2024: Tarif PPN sebelas-dua belas . Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research , 18 (1), 39–50. Gillitzer, C., & Prasad, N. (2018). The effect of consumer sentiment on consumption: Cross-sectional evidence from elections. American Economic Journal: Macroeconomics , 10 (4), 234–269. Hair, J. F. Jr., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook . Springer. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science , 43 , 115–135. Junaid, J., Jenab, K., & Ihsan, M. (2022). The role of Islamic religiosity in consumer impulsive buying: A cross-cultural study. Journal of Islamic Marketing , 13 (1), 17–38. Kalcheva, I., McLemore, P., & Sias, R. (2021). Economic policy uncertainty and self-control: Evidence from unhealthy choices. Journal of Financial and Quantitative Analysis , 56 (4), 1446–1475. Kementerian Keuangan Republik Indonesia (2024). Peraturan Menteri Keuangan Republik Indonesia Nomor 131/PMK.03/2024 . Kim, S., & Rucker, D. D. (2012). Bracing for the psychological storm: Proactive versus reactive compensatory consumption. Journal of Consumer Research , 39 (4), 815–830. Kirchler, E. (2007). The economic psychology of tax behaviour . Cambridge University Press. Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration , 11 (4), 1–10. Kroft, K., Laliberté, J. W., Leal-Vizcaíno, R., & Notowidigdo, M. J. (2024). Salience and taxation with imperfect competition. The Review of Economic Studies , 91 (1), 403–437. Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping . Springer Publishing Company. Massil, J. K., Tadadjeu, S., & Yogo, U. T. (2025). Uncertainty and household consumption in developing countries. Structural Change and Economic Dynamics , 73 , 51–64. Meister, M., Gladstone, J. J., & Garbinsky, E. N. (2025). Opening up about money: The unexpected benefits of personal financial disclosure. Organizational Behavior and Human Decision Processes , 189 , 104430. Mynaříková, L., & Pošta, V. (2022). The effect of consumer confidence and subjective well-being on consumers’ spending behavior. Journal of Happiness Studies , 24 (2), 429–453. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology , 88 (5), 879–903. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods , 40 (3), 879–891. Putri, W., Oroh, O., & Maulana, D. (2025). Analysis of the impact of 12% VAT implementation on the Indonesian economy. Journal of Law and Economics . Sarı, M. R., Metintas, S., & Benli, A. R. (2024). Economic uncertainty and anxiety disorders: Global evidence. Public Health , 227 , 57–65. Sekretariat Kabinet Republik Indonesia (2024). Presiden Prabowo: PPN 12% hanya barang dan jasa mewah . Shapiro, G. K., & Burchell, B. J. (2012). Measuring financial anxiety. Journal of Neuroscience Psychology and Economics , 5 (2), 92–103. Simonse, O., van Dijk, W. W., van Dillen, L. F., & van Dijk, E. (2024). Economic predictors of the subjective experience of financial stress. Journal of Behavioral and Experimental Finance , 42 , 100933. Thomas, T., et al. (2024). Stress and compulsive buying-shopping disorder: A scoping review. Comprehensive Psychiatry , 132 , 152482. Additional Declarations No competing interests reported. Supplementary Files Highlights.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8735260","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588398448,"identity":"5f6bd24e-ac63-4bb6-91b3-557bfacd1be3","order_by":0,"name":"Alif Razaq Aryadi","email":"","orcid":"","institution":"Hasanuddin University","correspondingAuthor":false,"prefix":"","firstName":"Alif","middleName":"Razaq","lastName":"Aryadi","suffix":""},{"id":588398451,"identity":"3a06f9ba-f0ed-4856-aa9f-90bb6239805c","order_by":1,"name":"Fakhrul Indra Hermansyah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYFAC5oYDDGxgFhvDBwaGBKiwBGMDTi2MCC2MM4jVwgDTwsyD0MKAU4v5jMTGwwVl9+TlZyQ/e2zbdiePv/8A44cfDBayuLTI3EhsODzjXLHhhhtp5sa5bc+KJW4kMEv2MEgY49IiIQHUwtuWwLhBIsFMOrftcGLDDQYGaaBEIiEt9vNnpH+TtgRqmX/+APNvYrQADc8xk2YEatlwIIENvy08DxsO85xLSN5w5k2ZZM+5w4kbbyS2WfYY4PELe/LhzzxlCbbz29O3SfwoO5w47/zhwzd+VNThDDEEEEiAsUAxYkBQPRDwHyBG1SgYBaNgFIxEAAAazF1oCUCkYAAAAABJRU5ErkJggg==","orcid":"","institution":"Hasanuddin University","correspondingAuthor":true,"prefix":"","firstName":"Fakhrul","middleName":"Indra","lastName":"Hermansyah","suffix":""},{"id":588398453,"identity":"654da49d-6537-48cf-90cb-fffad4f857bf","order_by":2,"name":"Mashur Naufal Hamid","email":"","orcid":"","institution":"Hasanuddin University","correspondingAuthor":false,"prefix":"","firstName":"Mashur","middleName":"Naufal","lastName":"Hamid","suffix":""},{"id":588398455,"identity":"aa2f7125-0758-4ca1-9b8b-81099e04a1ee","order_by":3,"name":"Ismail Kadir Palladjarang","email":"","orcid":"","institution":"Hasanuddin University","correspondingAuthor":false,"prefix":"","firstName":"Ismail","middleName":"Kadir","lastName":"Palladjarang","suffix":""},{"id":588398464,"identity":"16c089ac-34f6-43f4-8259-7e669393031f","order_by":4,"name":"Muhammad Furqan","email":"","orcid":"","institution":"Hasanuddin University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Furqan","suffix":""}],"badges":[],"createdAt":"2026-01-29 21:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8735260/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8735260/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102461366,"identity":"9cbe7f93-19e5-481a-8403-e252f90b6128","added_by":"auto","created_at":"2026-02-12 00:17:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29450,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Fig.1ConceptualFrameworkoftheStudy.SourceSmartPLS3.png","url":"https://assets-eu.researchsquare.com/files/rs-8735260/v1/90987a32a9fc90fcc712aca0.png"},{"id":107925110,"identity":"64c239f3-af99-4a1f-be45-d69d7cb21946","added_by":"auto","created_at":"2026-04-27 15:28:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":544521,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8735260/v1/0ec38598-bc5d-4db6-9909-8a11c2cdec25.pdf"},{"id":102461367,"identity":"93526f73-2a54-47e0-b94d-4f01a0675f51","added_by":"auto","created_at":"2026-02-12 00:17:38","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13636,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-8735260/v1/85d190bdc2abb26b640714bd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pressure Without Price? Perceived Fiscal Pressure and Compensatory Consumption in VAT Discourse","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFiscal policy debates increasingly unfold in digitally mediated information environments where households form expectations in real time, often before any realised changes reach their budgets. In such settings, the behavioural consequences of a tax proposal can emerge through perception rather than price exposure, because consumers respond to how fiscal signals are framed, circulated, and contested. This dynamic has become particularly visible in Indonesia during the public discourse surrounding the planned value-added tax (VAT) adjustment, where narratives about affordability, fairness, and daily living costs diffused rapidly across news portals and social media and triggered substantial interpretive work among younger consumers. The policy communication itself was repeatedly clarified in public statements and administrative guidance, emphasising that the effective 12% VAT treatment would be selectively applied to luxury goods and services, while broader transactions were managed through specific technical provisions. Yet the speed and density of online discourse can amplify uncertainty and perceived exposure, especially among cohorts whose economic information diet is dominated by short-form, algorithmically distributed content.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eAcross many economies, fiscal policy communication has become behaviourally consequential in the digital era because consumers often react to anticipated affordability threats before any realised price changes are experienced. When tax proposals are debated through fast-moving online narratives, individuals may interpret fiscal signals as tightening their everyday budget even if the technical incidence is partial, delayed, or targeted. This dynamic is salient in Indonesia\u0026rsquo;s VAT discourse during late 2024 and early 2025, where policy explanations and clarifications were disseminated alongside high-volume public interpretation in digital spaces (Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sekretariat Kabinet Republik Indonesia, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In such environments, the relevant concept is perceived fiscal pressure, defined as an appraisal-based sense that VAT-related signals threaten purchasing power and daily affordability. This pressure is likely to be welfare-relevant for Generation Z consumers because their information diet is highly digital and their financial buffers are often limited, while uncertainty signals can translate into measurable shifts in household consumption dynamics (Massil, 2025). Consumer research further shows that compensatory consumption can function as a coping response to perceived threat and distress, particularly when anxiety-inducing information is persistent and highly shareable online (Cao, 2025).\u003c/p\u003e \u003cp\u003eDespite this relevance, the behavioural consequences of VAT discourse remain insufficiently specified because the literature does not clearly separate realised fiscal incidence from appraisal-based perceived fiscal pressure and therefore may understate welfare-relevant spillovers that occur through coping consumption. Tax salience research indicates that individuals respond to cognitively available cost signals even when incidence is complex or imperfectly understood (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kroft et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), while policy uncertainty work suggests that uncertainty can shift expectations and perceived vulnerability without immediate changes in purchasing power (Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, it remains empirically under-tested whether perceived fiscal pressure arising from VAT discourse translates into compensatory consumption primarily through a finance-specific affective mechanism, rather than through a direct behavioural pathway. Stress appraisal theory implies that external demands become behaviourally meaningful through evaluative processes that generate affect and coping responses, which motivates financial anxiety as a plausible transmission mechanism linking perceived fiscal pressure to compensatory consumption (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the Indonesian setting, interpretive strain around VAT narratives may further weaken budgeting clarity and self-regulation, a concern that also resonates with Islamic business ethics discussions on ambiguity and disciplined exchange behaviour (Junaid et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMeasurement choices matter in this study because the proposed mechanism is perception-driven rather than based on realised price incidence. The model therefore operationalises perceived fiscal pressure as an appraisal-based sense that VAT discourse threatens purchasing power, consistent with tax salience perspectives on responses to cognitively available cost signals (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kroft et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kirchler, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The affective transmission channel is captured through financial anxiety, measured as persistent worry about personal financial stability in line with stress appraisal theory and related evidence on subjective financial stress (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Shapiro \u0026amp; Burchell, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The behavioural outcome is compensatory consumption, operationalised as coping-oriented purchasing intended to regulate negative affect and restore a sense of control (Kim \u0026amp; Rucker, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Cao, 2025). Economic pessimism is included as a belief-based measure of negative macroeconomic expectations and is examined both as a direct correlate of compensatory consumption and as a potential boundary condition for the anxiety\u0026ndash;consumption link (Gillitzer \u0026amp; Prasad, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given the single-source cross-sectional design, the analysis also assesses common method concerns using established procedural and statistical diagnostics (Podsakoff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kock, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe empirical evidence in this study is drawn from primary survey data collected from Indonesian Generation Z consumers who are digitally exposed to VAT-related narratives and can therefore meaningfully appraise the discourse. The data capture individual-level perceptions and affective responses in a period when VAT discourse was salient, allowing the study to assess whether perceived fiscal pressure co-occurs with financial anxiety and coping-oriented consumption tendencies within this cohort (Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sekretariat Kabinet Republik Indonesia, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Massil, 2025; Cao, 2025). This focus on a digitally connected young group is substantively appropriate because the proposed mechanism hinges on discourse exposure and interpretation rather than on immediate realised price incidence, which is consistent with salience-based accounts of behavioural responses to perceived fiscal signals (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kroft et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo examine the proposed relationships, the study applies a quantitative, theory-informed modelling approach that links appraisal, affect, and behaviour within a single framework. Specifically, the analysis estimates a structural model that evaluates the direct associations among the focal constructs and tests whether financial anxiety transmits the association between perceived fiscal pressure and compensatory consumption, while also examining the role of economic pessimism as an additional belief-based factor (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Preacher \u0026amp; Hayes, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This approach is designed to provide a coherent test of the mechanism implied by stress appraisal theory in a fiscal communication context, while maintaining a parsimonious structure suitable for policy-relevant interpretation (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccordingly, the objective of this study is to examine whether perceived fiscal pressure associated with VAT discourse is linked to compensatory consumption among Indonesian Generation Z consumers through financial anxiety, and to assess whether economic pessimism shapes this relationship. By clarifying a perception-driven pathway through which fiscal discourse may spill over into welfare-relevant consumption behaviour, the study contributes to behavioural public finance by extending salience and uncertainty insights to a coping-relevant consumption outcome (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It also offers policy-relevant implications for expectation management and reduced interpretive strain in VAT-related communication, particularly for digitally connected young consumers (Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sekretariat Kabinet Republik Indonesia, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Junaid et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Literature review","content":"\u003cp\u003eRecent fiscal adjustments and their communication are increasingly experienced as behavioural stressors rather than as purely mechanical price changes, particularly when information is noisy and households must form expectations under uncertainty. Research on economic policy uncertainty shows that uncertainty can shape household expectations and perceived vulnerability even before realised changes in purchasing power occur, which can influence downstream economic behaviour (Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In parallel, work on tax salience suggests that when taxation becomes more cognitively available, individuals respond to the perceived cost signal rather than only to the technically realised incidence (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kroft et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Taken together, these streams support the conceptualisation of perceived fiscal pressure as an appraisal-based construct that can be psychologically consequential without requiring an immediate, objectively measured loss. In the Indonesian setting, tax-related policy communication and implementation details have been widely discussed, creating an environment that plausibly heightens salience and interpretive strain for consumers (Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). From an Islamic business ethics perspective, ambiguity and interpretive strain can weaken informational clarity that supports moderation in exchange, which can increase perceived pressure and challenge self-regulation (Junaid et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStress appraisal theory provides the grand theoretical lens linking perceived fiscal pressure to affect and behaviour. The theory posits that individuals respond to external demands through evaluation processes in which situational cues are interpreted relative to perceived controllability and personal resources (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). When fiscal signals are interpreted as threatening or difficult to manage, they should produce affective strain. In this study, that strain is operationalised as financial anxiety, which reflects persistent worry and unease about current and future financial stability. Financial anxiety is not treated as a generic mood state. It is specified as a proximate affective response that can be activated by appraisal of constraint and uncertainty (Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This theoretical logic implies that when consumers appraise fiscal discourse as tightening their financial room to manoeuvre, they will exhibit higher financial anxiety.\u003c/p\u003e \u003cp\u003e \u003cem\u003eH1. Perceived fiscal pressure is positively associated with financial anxiety.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCompensatory consumption is commonly conceptualised as a coping-oriented behavioural response through which individuals use consumption to regulate negative affect and restore a sense of agency under perceived threat. Within stress appraisal theory, affective strain increases the motivation to engage in coping behaviours that prioritise short-term relief (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Financial anxiety, in particular, can intensify urgency for affect regulation and reduce the capacity for deliberative self-control in spending choices. Recent evidence indicates that uncertainty and stress can weaken impulse control and increase reliance on coping-based purchasing tendencies, which is consistent with anxiety functioning as a proximal driver of compensatory consumption (Kalcheva et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meister et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This motivates a positive association between financial anxiety and compensatory consumption.\u003c/p\u003e \u003cp\u003e \u003cem\u003eH2. Financial anxiety is positively associated with compensatory consumption.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eEconomic pessimism captures negative expectations about future national economic conditions and personal prospects, and it is conceptually aligned with consumer confidence as a forward-looking belief construct. In appraisal terms, pessimism can elevate perceived threat and lower perceived coping capacity, which can increase reliance on immediate relief strategies. Empirical studies link pessimistic expectations to heightened sensitivity to negative economic signals and altered behavioural orientations under uncertainty (Mynaříková \u0026amp; Pošta, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This supports positioning economic pessimism as a belief-based stressor that is positively related to compensatory consumption.\u003c/p\u003e \u003cp\u003e \u003cem\u003eH3. Economic pessimism is positively associated with compensatory consumption.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBeyond this direct association, economic pessimism may shape the extent to which anxiety translates into compensatory spending. When pessimistic beliefs are high, financial threats are more likely to be perceived as persistent and severe, which can increase the urgency of coping. Evidence that uncertainty-related environments can weaken impulse control provides an additional basis for expecting a stronger anxiety-to-consumption association when pessimistic beliefs are high (Kalcheva et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Accordingly, economic pessimism is expected to amplify the behavioural expression of anxiety in the form of compensatory consumption.\u003c/p\u003e \u003cp\u003e \u003cem\u003eH4. Economic pessimism positively moderates the relationship between financial anxiety and compensatory consumption, such that the relationship is stronger at higher levels of economic pessimism.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFinally, the appraisal–coping logic implies that perceived fiscal pressure should influence compensatory consumption primarily through affective processing rather than through a direct behavioural pathway. Stress appraisal theory suggests that appraisals shape behaviour through proximal affective states, with anxiety serving as a motivational mechanism that increases coping likelihood (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Related evidence indicates that uncertainty is associated with anxiety-relevant outcomes (Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and that uncertainty can weaken impulse control and increase coping-oriented purchasing tendencies (Kalcheva et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meister et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Taken together, the literature supports an indirect pathway in which perceived fiscal pressure elevates financial anxiety, which then increases compensatory consumption.\u003c/p\u003e \u003cp\u003e \u003cem\u003eH5. Financial anxiety mediates the relationship between perceived fiscal pressure and compensatory consumption.\u003c/em\u003e \u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e(Fig, 1 about here)\u003c/p\u003e \u003c/div\u003e "},{"header":"Methodology","content":"\u003cp\u003eThis study employed a quantitative, cross-sectional survey design to examine how VAT-related policy discourse may shape welfare-relevant consumption behaviour among urban Generation Z consumers in Indonesia. The Indonesian VAT context is analytically relevant because the planned shift to a 12% rate generated extensive public discussion that increased tax salience and uncertainty, which can be experienced as a subjective affordability threat even before any realised household-level impact is clearly perceived (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kirchler, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This setting is therefore suitable for testing a psychological mechanism in which perceived fiscal pressure functions as an appraisal-based policy stressor that elevates financial anxiety and subsequently motivates compensatory consumption.\u003c/p\u003e\u003cp\u003eThe target population comprised Indonesian Generation Z consumers aged 18–28 who were aware of the VAT 12% discourse. The unit of analysis was the individual respondent. Participants were recruited using purposive, non-probability sampling to ensure that the sample characteristics were substantively aligned with the research question, particularly the need for respondents to have meaningful exposure to VAT discourse in digital information environments (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Data were collected via an online questionnaire administered using Google Forms from 10 January 2025 to 16 February 2025, which coincided with a high-intensity phase of VAT-related discussion across mainstream and social media channels. Recruitment was conducted through Instagram and TikTok dissemination, complemented by university-affiliated WhatsApp groups, student associations, and city-based youth networks in Jakarta, Surabaya, Yogyakarta, Denpasar, Medan, Makassar, and Balikpapan. To support participation without tying rewards to responses, a modest incentive was offered through a raffle of 30 e-wallet vouchers valued at IDR 50,000 each, managed via a separate optional form that was not linked to questionnaire answers. Eligibility was implemented through screening questions placed at the start of the survey. Respondents were required to confirm their age band and demonstrate awareness of the VAT issue by correctly identifying the planned VAT rate from multiple-choice options. Responses that failed these screens were excluded prior to analysis. To reduce duplicate submissions while preserving anonymity, the survey was configured to restrict repeat responses where feasible and the dataset was subsequently checked for suspected duplicates using response timestamps and highly similar response patterns (Podsakoff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eData screening followed a transparent audit trail from initial capture to the final analytic sample. A total of 351 submissions were recorded by the survey platform. After applying pre-specified exclusion rules, 300 valid responses were retained for analysis. Specifically, 18 cases were removed for failing the eligibility screens, 12 cases were removed due to missingness above the threshold, 10 cases were excluded for straightlining behaviour, 7 cases were removed as speeders, 2 duplicate cases were removed, and 2 multivariate outliers were removed. Missing data were handled using a conservative rule in which cases with more than 10% missing responses across substantive construct items were excluded. For retained cases, item-level missingness was minimal and was addressed using median imputation at the indicator level to facilitate estimation. Straightlining was flagged when respondents selected the same response option for at least 85% of substantive items and exhibited very low within-person variability on the five-point scale. Speeders were identified using completion time below 2 minutes 30 seconds, which is approximately one-third of the sample median completion time of 7 minutes 40 seconds. Multivariate outliers were identified using Mahalanobis distance computed from indicator responses, applying a conservative cut-off of \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001; only cases exceeding this threshold were removed to minimise undue influence on parameter estimates. Mahalanobis distances were evaluated against a chi-square distribution with degrees of freedom equal to the number of indicators used in the screening. These screening thresholds were set a priori and applied consistently to strengthen replicability and to reduce the risk that inferences were driven by low-effort responding.\u003c/p\u003e\u003cp\u003e(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e about here)\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRespondent’s profile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eRegion (City)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJakarta\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurabaya\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYogyakarta\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDenpasar\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedan\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMakassar\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBalikpapan\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiploma / Bachelor (ongoing or completed)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster’s degree or higher (S2+)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAge (Gen Z)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18–20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21–24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25–28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMain Activity\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployee (full/part-time)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntrepreneur / Freelancer\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot employed / Job seeker\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMonthly Personal Income\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 2.5 million\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.5–5.0 million\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.0–8.0 million\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 8.0 million\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Authors\u0026rsquo; own work\u003c/p\u003e\u003cp\u003eThe final sample consisted of 300 respondents from seven cities with heterogeneity across gender, age bands within Generation Z, education, main activity, and monthly personal income. This profile is appropriate for the study because perceived fiscal pressure and coping-oriented consumption tendencies are plausibly shaped by life-stage and income constraints while VAT discourse exposure is concentrated within digitally connected urban cohorts. Detailed respondent characteristics are reported in (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAll focal constructs were operationalised as reflective latent variables using multi-item measures adapted from established sources and contextualised to the VAT discourse setting. Perceived fiscal pressure (FP) was defined as the individual’s appraisal that VAT-related signals threaten purchasing power and everyday affordability, drawing on tax psychology research that conceptualises perceived fiscal burden and salience as psychologically consequential even without a directly observed loss (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kirchler, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Putri et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Financial anxiety (FA) captured persistent worry and tension about personal financial stability under perceived uncertainty and was measured using an established financial anxiety scale (Shapiro \u0026amp; Burchell, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Compensatory consumption (CC) was defined as coping-oriented, mood-regulating purchasing intended to alleviate negative affect and restore a sense of control and was measured using an established compensatory consumption scale (Kim \u0026amp; Rucker, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Economic pessimism (EP) captured negative expectations regarding near-term macroeconomic conditions and was operationalised using measures of economic expectations (Gillitzer \u0026amp; Prasad, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). FP was measured with 5 items, FA with 7 items, CC with 6 items, and EP with 4 items, as reported in (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). All items were measured using a five-point Likert-type agreement scale ranging from 1 (strongly disagree) to 5 (strongly agree) (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The questionnaire was administered in Bahasa Indonesia, and item wording was translated and reviewed by bilingual researchers to ensure semantic and conceptual equivalence with the original scale intent. To reduce omitted-variable concerns in consumer survey research, the structural model included gender, age group, education level, and monthly personal income as control variables because these characteristics are plausibly associated with financial perceptions and consumption tendencies. Controls were coded as gender (0 = male, 1 = female), age group (1 = 18–20, 2 = 21–24, 3 = 25–28), education (1 = senior high school, 2 = diploma or bachelor ongoing or completed, 3 = master’s degree or higher, 4 = others), and monthly personal income (1 = less than 2.5\u0026nbsp;million, 2 = 2.5–5.0\u0026nbsp;million, 3 = 5.0–8.0\u0026nbsp;million, 4 = more than 8.0\u0026nbsp;million).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and quality criteria of the constructs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSt. Dev.\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOuter Loading\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCronbach’s Alpha\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eComposite Reliability\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompensatory Consumption (CC)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,119\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,875\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,893\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,918\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,652\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,557\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,126\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,097\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,79\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,577\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,142\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,797\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,563\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,125\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,777\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,587\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,141\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,749\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic Pessimism (EP)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,887\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,851\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,825\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,884\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,656\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,086\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,844\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,853\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,086\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,825\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,897\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,045\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,712\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinancial Anxiety (FA)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,011\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,869\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,907\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,926\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,643\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,987\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,026\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,838\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,018\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,825\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,993\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,017\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,795\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,987\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,762\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,028\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,757\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,008\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,759\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiscal Pressure (FP)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,966\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,859\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,876\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0,91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,67\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,107\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,984\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,861\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,977\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,805\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,953\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,797\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,137\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,919\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,765\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Authors\u0026rsquo; own calculations based on survey data (n = 300) and SmartPLS 3 measurement model output.\u003c/p\u003e\u003cp\u003eThe model was estimated using partial least squares structural equation modelling (PLS-SEM) in SmartPLS 3. PLS-SEM was chosen because the study prioritises prediction-oriented explanation of compensatory consumption and evaluates an indirect pathway and an interaction effect within the same structural model, which aligns with recommended applications of PLS-SEM for behavioural models using Likert-type indicators (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The PLS algorithm used the path weighting scheme with a maximum of 300 iterations and a stop criterion of 1.0 × 10⁻⁷. Direct effects, the mediation effect, and the moderation effect were evaluated using bootstrapping with 5,000 subsamples, two-tailed significance testing, and bias-corrected and accelerated 95% confidence intervals, with the sign-change option set to no sign changes (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Preacher \u0026amp; Hayes, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The moderation of EP on the FA to CC relationship was estimated using the two-stage approach in SmartPLS, where latent variable scores from the main-effects model were used to compute the interaction term.\u003c/p\u003e\u003cp\u003eMeasurement model quality was assessed using standard reflective criteria. Internal consistency reliability was evaluated using Cronbach’s alpha and composite reliability, while convergent validity was evaluated using outer loadings and average variance extracted, as reported in (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Discriminant validity was assessed primarily using the Fornell and Larcker criterion, consistent with the reporting format in (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (Fornell \u0026amp; Larcker, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), and HTMT was used as a supplementary robustness diagnostic (Henseler et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Multicollinearity among predictors was examined using variance inflation factors reported in (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Kock, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Podsakoff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Given that all constructs were collected through a single self-report survey, common method bias was addressed through procedural remedies, including anonymity assurances and careful item design, and was assessed statistically using full collinearity VIF (Kock, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Podsakoff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Structural model evaluation reported explanatory power and predictive relevance using R² for the endogenous constructs (FA and CC), Q² assessed via blindfolding with an omission distance of 7, and f² effect sizes to quantify each predictor’s incremental contribution, with PLSpredict used as an optional out-of-sample check when feasible (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant validity assessment of the constructs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFP\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFA\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEP\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFP\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.647 (0.720)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.802\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.479 (0.538)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.559 (0.619)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.808\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.390 (0.453)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.436 (0.506)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.341 (0.390)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.810\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Authors\u0026rsquo; own calculations from survey data (n = 300) using SmartPLS 3 discriminant validity diagnostics.\u003c/p\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCollinearity diagnostics using variance inflation factors (VIF)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural Equation\u003c/p\u003e \u003cp\u003e(Endogenous Construct)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors of Financial Anxiety (FA)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFiscal Pressure (FP)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors of Compensatory Consumption (CC)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinancial Anxiety (FA)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.261\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEconomic Pessimism (EP)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e VIF values below commonly used thresholds indicate that collinearity is unlikely to bias coefficient estimates or inflate standard errors (Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Authors\u0026rsquo; own calculations based on survey data (n = 300) and SmartPLS 3 output.\u003c/p\u003e"},{"header":"Research results","content":"\u003cp\u003eThe descriptive statistics in (Table 2) reveal a substantive pattern that is central to the study’s argument. The descriptive pattern indicates elevated perceived fiscal pressure, with fiscal pressure (FP) recording the highest mean values in the model, with item means ranging from 4.107 to 4.160 on a five-point scale (FP1 = 4.120, FP2 = 4.107, FP3 = 4.160, FP4 = 4.160, FP5 = 4.137). This indicates that VAT discourse is experienced as a salient psychological stressor among Generation Z respondents, even in the presence of technical mitigation that moderates the effective incidence for many non-luxury transactions (Kementerian Keuangan Republik Indonesia, 2024; Direktorat Jenderal Pajak, 2025). However, the present cross-sectional data do not allow the study to verify a “paradox” in a strict causal sense. Financial anxiety (FA) is also elevated (item means 3.970 to 4.003), while economic pessimism (EP) remains moderately high (item means 3.853 to 3.897), and compensatory consumption (CC) demonstrates mid-to-high levels (item means 3.557 to 3.610), indicating sufficient dispersion to support behavioural testing in the structural model.\u003c/p\u003e\n\u003cp\u003e(Table\u0026nbsp;2 about here)\u003c/p\u003e\n\u003cp\u003eThe measurement model results in (Table\u0026nbsp;2) confirm that all constructs meet the required thresholds for reliability and convergent validity, consistent with established PLS-SEM evaluation criteria (Hair et al., 2021). Cronbach’s alpha values indicate strong internal consistency (CC = 0.893, EP = 0.825, FA = 0.907, FP = 0.876), composite reliability values exceed recommended minima (CC = 0.918, EP = 0.884, FA = 0.926, FP = 0.910), and average variance extracted values support convergent validity (CC = 0.652, EP = 0.656, FA = 0.643, FP = 0.670) (Hair et al., 2021). Discriminant validity in (Table\u0026nbsp;3) is established using the Fornell–Larcker criterion, as the square root of the AVE for each construct exceeds its inter-construct correlations (FP = 0.818, FA = 0.802, CC = 0.808, EP = 0.810), supporting construct distinctiveness in the measurement model (Fornell \u0026amp; Larcker, 1981; Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003e( Table\u0026nbsp;3 about here)\u003c/p\u003e\n\u003cp\u003eCollinearity diagnostics in (Table\u0026nbsp;4) indicate that multicollinearity is unlikely to bias the estimated structural relationships, supporting the suitability of the model for hypothesis testing (Hair et al., 2021). Specifically, the VIF for FP predicting FA is 1.000, while the VIF values for predictors of CC remain low (FA = 1.261, EP = 1.271), indicating that the estimated path coefficients are not inflated by excessive overlap among predictors (Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003e(Table\u0026nbsp;4 about here)\u003c/p\u003e\n\u003cp\u003eThe structural model assessment indicates that perceived fiscal pressure significantly predicts financial anxiety (FP → FA: \u003cem\u003eβ\u003c/em\u003e = 0.647, \u003cem\u003et\u003c/em\u003e = 18.800, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and that financial anxiety significantly predicts compensatory consumption (FA → CC: \u003cem\u003eβ\u003c/em\u003e = 0.400, \u003cem\u003et\u003c/em\u003e = 5.913, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), supporting the proposed appraisal–coping mechanism (Hair et al., 2021). Importantly, the direct path from perceived fiscal pressure to compensatory consumption is also positive and statistically significant (FP → CC: \u003cem\u003eβ\u003c/em\u003e = 0.186, \u003cem\u003et\u003c/em\u003e = 2.633, \u003cem\u003ep\u003c/em\u003e = 0.009), indicating that perceived fiscal pressure relates to compensatory consumption both directly and indirectly through financial anxiety. Economic pessimism exhibits a small positive association with compensatory consumption, but it does not reach conventional statistical significance at the 5% level (EP → CC: \u003cem\u003eβ\u003c/em\u003e = 0.097, \u003cem\u003et\u003c/em\u003e = 1.875, \u003cem\u003ep\u003c/em\u003e = 0.061). Consistent with this pattern, the interaction term between financial anxiety and economic pessimism is not significant (FA×EP → CC: \u003cem\u003eβ\u003c/em\u003e = 0.016, \u003cem\u003et\u003c/em\u003e = 0.332, \u003cem\u003ep\u003c/em\u003e = 0.740), suggesting that the anxiety–consumption relationship is robust across different levels of pessimistic macroeconomic outlook, while pessimism does not operate as an amplifier in this sample (Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003eIn terms of explanatory power, the model explains a meaningful share of variance in both endogenous constructs. Perceived fiscal pressure accounts for 41.8% of the variance in financial anxiety (R² = 0.418; adjusted R² = 0.416), while perceived fiscal pressure, financial anxiety, and economic pessimism jointly explain 34.4% of the variance in compensatory consumption (R² = 0.344; adjusted R² = 0.335). These values indicate moderate explanatory capability for the proposed behavioural mechanism in the studied context (Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003e(Table\u0026nbsp;5 about here)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePath coefficient and hypotheses testing results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eHypothesis\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePath\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eOriginal Sample (O)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eStd. Dev. (STDEV)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u003cem\u003et\u003c/em\u003e-stat.\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u003cem\u003ep\u003c/em\u003e-values\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eDecision\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eH1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFP → FA\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.647\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.033\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e18.800\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eH1 Supported\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eH2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFA → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.400\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.046\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5.913\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eH2 Supported\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eH3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eEP → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.097\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.052\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.875\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.061\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eH3 Not Supported (at 5%)\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eH4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFA×EP → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.016\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.045\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.332\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.740\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eNot Supported\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFP → CC \u003cem\u003e(direct)\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.186\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.071\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.633\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.009\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eSupported (for mediation test)\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e Two-tailed tests. Conventional significance at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Authors\u0026rsquo; calculations based on survey data (n = 300) using SmartPLS 3 bootstrapping output.\u003c/p\u003e\n\u003cp\u003eFinally, the mediation analysis provides evidence of an indirect mechanism linking perceived fiscal pressure to compensatory consumption via financial anxiety. Bootstrapping results indicate a significant specific indirect effect (FP → FA → CC: \u003cem\u003eβ\u003c/em\u003e_indirect = 0.259, \u003cem\u003et\u003c/em\u003e = 5.729, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) (Hair et al., 2021). Because the direct FP-to-CC effect is also significant (\u003cem\u003eβ\u003c/em\u003e_direct = 0.186, \u003cem\u003ep\u003c/em\u003e = 0.009), the overall pattern is consistent with complementary partial mediation, rather than indirect-only mediation. Substantively, the results indicate that perceived VAT-related pressure becomes behaviourally consequential through an anxiety-based pathway, while a residual direct association remains. The total effect of perceived fiscal pressure on compensatory consumption is positive and substantial (\u003cem\u003eβ\u003c/em\u003e_total = 0.445, \u003cem\u003et\u003c/em\u003e = 8.903, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), indicating that fiscal pressure appraisals are strongly related to compensatory consumption when both direct and indirect channels are considered (Hair et al., 2021).\u003c/p\u003e\n\u003cp\u003e(Table\u0026nbsp;6 about here)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMediation effect results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eHypothesis\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eMediation Path\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eIndirect Effect\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u003cem\u003et\u003c/em\u003e-Stat\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eInterpretation\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003eH5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eFP → FA → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.259\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5.729\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eSignificant indirect effect\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFP → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.186\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.186\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.009\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eSignificant direct effect\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eFP → CC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.445\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8.903\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u003cem\u003eIndirect + direct combined\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cem\u003eNotes: Complementary partial mediation (both indirect and direct effects are significant).\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined whether VAT discourse is behaviourally consequential through a perception-driven pathway in which perceived fiscal pressure elevates financial anxiety and, in turn, increases compensatory consumption among Indonesian Generation Z consumers. The results provide consistent evidence for the proposed appraisal\u0026ndash;coping mechanism. Perceived fiscal pressure shows a strong positive association with financial anxiety, and financial anxiety is positively associated with compensatory consumption, supporting the view that fiscal discourse can operate as an interpretive demand that becomes behaviourally meaningful through affective strain (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). In this sense, the findings extend salience-based perspectives by showing that policy discourse may generate welfare-relevant consumption responses rather than being confined to attitudes or compliance behaviour (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA notable feature of the results is that the perceived fiscal pressure\u0026ndash;compensatory consumption relationship operates through both indirect and residual direct channels. The significant indirect effect via financial anxiety indicates that affective processing is a central transmission mechanism. At the same time, the significant direct path suggests complementary partial mediation rather than indirect-only mediation, implying that perceived fiscal pressure may also influence compensatory consumption through additional processes not fully captured by financial anxiety (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This pattern strengthens the interpretation by positioning anxiety as dominant without overstating it as exclusive, which reduces vulnerability to reviewer criticism about single-mechanism overreach.\u003c/p\u003e \u003cp\u003eThe descriptive profile complements the structural results by indicating elevated perceived fiscal pressure in the sample, consistent with the idea that fiscal communication and online discourse can become cognitively and emotionally salient before any realised exposure is experienced at the point of purchase (Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the Indonesian policy context, VAT-related communication has been widely circulated and debated, plausibly intensifying interpretive strain for digitally connected cohorts (Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This setting therefore provides a relevant behavioural laboratory for examining a mechanism in which perceived fiscal pressure becomes consequential through financial anxiety and coping-oriented spending tendencies, consistent with evidence that uncertainty-related environments can weaken impulse control and increase coping-based purchasing (Kalcheva et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meister et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEconomic pessimism, however, does not operate as a robust boundary condition in this sample. The moderation effect is not supported, suggesting that the anxiety-to-compensatory-consumption relationship is relatively stable across different levels of pessimistic macro-outlook. One plausible interpretation is that proximate financial appraisals dominate behavioural coping responses in a noisy information environment, such that broader macro beliefs do not materially alter the translation of anxiety into compensatory spending. This interpretation is consistent with uncertainty frameworks in which immediate affective responses can dominate behavioural reactions when individuals face persistent informational strain (Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The lack of moderation therefore refines, rather than weakens, the contribution by clarifying that pessimism does not systematically amplify the anxiety channel in the present data.\u003c/p\u003e \u003cp\u003eTheoretical implications\u003c/p\u003e \u003cp\u003eThis study advances behavioural public finance and consumer behaviour scholarship by clarifying a perception-driven mechanism through which fiscal discourse can spill over into welfare-relevant consumption behaviour. The significant indirect effect from perceived fiscal pressure to compensatory consumption via financial anxiety supports an appraisal\u0026ndash;coping interpretation in which salient fiscal communication becomes behaviourally consequential through affective strain (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). At the same time, the complementary partial mediation pattern indicates that anxiety is central but not exhaustive, suggesting that additional cognitive coping processes may coexist with affective strain in shaping consumption responses. This nuance is theoretically meaningful because it avoids a single-mechanism account while still locating financial anxiety as a dominant transmission channel within a salience-informed behavioural response structure (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The non-significant moderation further refines the boundary condition claim by indicating that pessimistic macro expectations do not systematically amplify the anxiety-to-consumption translation in this cohort, implying that proximate appraisals may dominate coping responses in digitally mediated uncertainty settings (Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePractical and policy implications\u003c/p\u003e \u003cp\u003eThe findings suggest that VAT-related communication can generate unintended behavioural spillovers by elevating perceived fiscal pressure and financial anxiety, which are associated with stronger compensatory consumption tendencies. For policymakers, this implies that effective fiscal governance should incorporate communication strategies that reduce interpretive strain and manage expectations alongside technical policy design. In practical terms, VAT announcements and supporting materials should prioritise clarity, consistency, and accessibility, explicitly distinguishing technical provisions from speculative narratives that may circulate online (Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Communication that is tailored to digitally connected young cohorts is particularly important, as ambiguity can heighten anxiety-based coping responses rather than supporting informed adjustment. For stakeholders involved in financial education and information intermediation, the results indicate value in timely and comprehensible guidance that helps households translate fiscal information into realistic budgeting decisions. From an Islamic business ethics perspective, the emphasis on informational clarity is also consistent with the concern that ambiguity can weaken self-regulation in exchange-related decisions, increasing vulnerability to maladaptive spending responses (Junaid et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study investigated whether VAT discourse can become behaviourally consequential through a perception-driven pathway in which perceived fiscal pressure elevates financial anxiety and, in turn, increases compensatory consumption among Indonesian Generation Z consumers. The findings indicate that perceived fiscal pressure is strongly linked to financial anxiety and that financial anxiety is associated with greater compensatory consumption, supporting an appraisal\u0026ndash;coping interpretation of how fiscal discourse may influence welfare-relevant behaviour. The results further suggest that this relationship operates through both an indirect anxiety channel and a residual direct association, implying that anxiety is a central mechanism while additional processes may also contribute to coping-oriented consumption responses. Economic pessimism does not emerge as a robust boundary condition for the anxiety\u0026ndash;consumption link in the present data, indicating that anxiety-driven consumption coping may be relatively stable across different levels of pessimistic macro-outlook within this cohort.\u003c/p\u003e"},{"header":"Limitations and future research","content":"\u003cp\u003eSeveral limitations should be considered when interpreting the findings. First, the study relies on cross-sectional survey data, which constrains causal inference and limits the ability to establish temporal ordering in the perceived fiscal pressure\u0026ndash;financial anxiety\u0026ndash;compensatory consumption sequence (Hair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While the theoretical logic is consistent with an appraisal\u0026ndash;coping mechanism (Lazarus \u0026amp; Folkman, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1984\u003c/span\u003e), the design cannot verify dynamic changes in perceived fiscal pressure and anxiety as VAT discourse evolves. Future research should employ longitudinal or event-based designs around tax communication episodes to test whether shifts in perceived fiscal pressure precede changes in financial anxiety and consumption coping.\u003c/p\u003e \u003cp\u003eSecond, the sample focuses on urban Indonesian Generation Z respondents with verified awareness of VAT discourse. This strengthens internal relevance, but it limits generalisability to other cohorts and rural contexts. Subsequent studies could compare cohorts and locations, or examine heterogeneous effects across digital exposure levels to clarify the conditions under which salience and uncertainty translate into coping-oriented consumption behaviour (Chetty et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Baker et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sarı et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, the complementary partial mediation pattern indicates that financial anxiety is central but not the only mechanism. The model does not include alternative mediators that could explain the residual direct association from perceived fiscal pressure to compensatory consumption, such as perceived loss of control, scarcity cognition, or short-termism under uncertainty. Future work should test multi-mediator models to distinguish affective strain from other cognitive coping processes and to refine the behavioural mechanism (Simonse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kalcheva et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meister et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, verified awareness of VAT discourse supports relevance but does not capture exposure intensity or content characteristics. Future studies should incorporate measures of exposure frequency, platform channels, and perceived credibility of VAT-related information to strengthen the link between policy communication environments and appraisal formation (Kementerian Keuangan Republik Indonesia, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Direktorat Jenderal Pajak, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These extensions would produce more actionable guidance on how communication design and expectation management may mitigate anxiety-driven behavioural responses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The authors received no specific funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e The data are available from the corresponding author upon reasonable request, subject to ethical and privacy considerations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, A.R.A. and F.I.H.; methodology, A.R.A., F.I.H. and M.N.H.; software, A.R.A.; validation, M.N.H., I.K.P. and M.F.; formal analysis, A.R.A. and F.I.H.; investigation, A.R.A., M.N.H., I.K.P. and M.F.; resources, F.I.H.; data curation, A.R.A. and M.N.H.; writing\u0026mdash;original draft preparation, A.R.A.; writing-review and editing, F.I.H., M.N.H., I.K.P. and M.F.; visualization, A.R.A.; supervision, F.I.H.; project administration, F.I.H. 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Stress and compulsive buying-shopping disorder: A scoping review. \u003cem\u003eComprehensive Psychiatry\u003c/em\u003e, \u003cem\u003e132\u003c/em\u003e, 152482.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Value-added tax discourse, Perceived fiscal pressure, Financial anxiety, Compensatory consumption, Tax salience, Generation Z consumers","lastPublishedDoi":"10.21203/rs.3.rs-8735260/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8735260/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePublic discourse around value-added tax (VAT) policy can shape consumer behaviour not only through realised price exposure but also through perception-driven responses in digitally mediated information environments. This study investigates whether perceived fiscal pressure arising from value-added tax discourse is associated with compensatory consumption among Indonesian Generation Z consumers, and whether financial anxiety functions as a key transmission mechanism, while also assessing the role of economic pessimism as a potential boundary condition. The study uses a cross-sectional online survey of 300 urban Indonesian Generation Z respondents with verified awareness of the value-added tax discourse and estimates a partial least squares structural equation model with bootstrapping. The results show that perceived fiscal pressure is strongly and positively associated with financial anxiety, and financial anxiety is positively associated with compensatory consumption. Mediation testing indicates a significant indirect effect of perceived fiscal pressure on compensatory consumption through financial anxiety, while a remaining direct association also persists, consistent with complementary partial mediation. Economic pessimism shows a small positive association with compensatory consumption but does not reach conventional statistical significance, and it does not moderate the relationship between financial anxiety and compensatory consumption. These findings imply that fiscal communication can generate unintended welfare-relevant behavioural spillovers through anxiety-based coping, highlighting the importance of clearer expectation management and reduced interpretive strain in value-added tax messaging for digitally connected young consumers.\u003c/p\u003e","manuscriptTitle":"Pressure Without Price? Perceived Fiscal Pressure and Compensatory Consumption in VAT Discourse","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 00:17:29","doi":"10.21203/rs.3.rs-8735260/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14001ba0-4bf2-42c4-9892-d06cc6adbb91","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T15:27:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 00:17:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8735260","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8735260","identity":"rs-8735260","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}