A growing body of literature explores how individuals perceive inequality, with a particular emphasis on how they conceptualize their own socio-economic standing, view social structures and broader inequality trends within their societies. Recent studies employ advanced methodologies, often survey-based, to capture these perceptions. The first stream in literature explores perceptions of national income inequality or national social structure, identifying the extent to which individuals recognize the disparities between social classes in their societies (Niehues, 2014; Hauser and Norton, 2017; Gimpelson and Treisman, 2018; Engelhardt and Wagener, 2018). The second stream in literature instead focuses on individuals' perceptions of their relative income rank within national income distribution and biases in how people locate themselves relative to others. To quantify individual rank perceptions researchers typically use tools such as income ladders or percentile scales, where respondents indicate their perceived rank on numeric continuum (Cruces et al., 2013; Engelhardt and Wagener, 2018; Bublitz, 2022; Fernández-Albertos and Kuo, 2018).

Regardless of the way of measurement and across diverse settings, studies consistently demonstrate significant biases in how individuals perceive their own position in the income distribution.¹ For example, Feichtmayer and Gründler (2021) report that approximately 40% of individuals in the OECD countries and around 37% worldwide believe that they are in the middle of the income distribution, even if objective measures contradict this perception. Feichtmayer and Gründler also find that among households in the lowest 30% of income distribution, 70% of households overestimate their relative standing. Similarly, Hoy and Mager (2021), in their comparative study of ten different countries, find that substantial proportions of respondents from the bottom two quintiles perceive themselves to be in the middle of the distribution, ranging from 37% in the United Kingdom to 63% in India Hoy and Mager, (2021), p. 316). Research from Sweden provides further insights into these patterns. Karadja et al. (2017) report that 68% of respondents underestimate their relative income position by more than 10 percentage points, in contrast to 6% who overestimate it. Results become more explicit when applying stricter criteria for accurate perceivers as those who correctly identify their income decile: 85.8% of respondents underestimate their position, while just 12.5% overestimate it. Also, findings of Cruces et al. (2013), analyzing data from Argentina, reveal that the most people misperceive their position in income distribution. They observe that 30% of respondents think that they are richer than they are and 55% think that they are poorer than in reality. Similarly, Fernández-Albertos and Kuo (2018), using data from Spain, report high level of misperceptions: Approximately 85% of respondents didn't manage to identify their place in income distribution correctly. Among them, over-estimators and under-estimators are nearly evenly divided, accounting for 40 and 45%, respectively. These findings together highlight the systematic nature of income rank misperceptions. Across diverse nations and methodological approaches, a clear majority of individuals, often exceeding tree-quarters, misperceive their income rank in one way or another.

Therefore, most researchers find the same pattern across different contexts when describing biases in perceptions of individual positions in income distribution. There is a center tendency of misperceptions Sattler-Bublitz et al., (2024), p. 29) or median bias (Hoy and Mager, 2021) when both rich and poor individuals view themselves as middle class. This aligns with frameworks of the “self-centered density function” (Knell and Stix, 2020, p. 2) or the “center bias” (Hvidberg et al., 2023, p. 3085). These studies reveal a positive correlation between perceived and objective income ranks; however, the most pronounced tendency is for individuals in the upper segment of the income distribution to underestimate their rank, whereas those in the lower segment often overestimate it.

Empirical evidence consistently show that erroneous beliefs are heterogeneous across population. For instance, Karadja et al. (2017) find that in Sweden several key sociodemographic characteristics improve the accuracy of relative income rank estimates, including years of education, cognitive abilities, self-reported media consumption and recent experience of upward mobility. However, the authors observe no significant correlation between the accuracy of perceptions and political orientation or the type of settlement (urban vs. rural). Further, adopting a broader perspective, Feichtmayer and Gründler (2021) examine misperceptions of social status across 97 countries and for 241,757 households. They find that older individuals, those with lower level of education and at the bottom of income distribution, have the tendency to overestimate their social status. In contrast to findings for Sweden, they find that being of left orientation is associated with less overestimation of social status. Busemeyer et al. (2024) explore the role of political attitudes and ideology for perceptions about individual relative income ranks using the data of the Konstanz Inequality Barometer (2020 and 2022). They argue that individuals tend to rely on their broader political beliefs when reflecting on their own position in income distribution and indeed find that in Germany politically conservative individuals underestimate their income rank, while those conservative in terms of economic ideology are more likely to overestimate it. Arin et al. (2024) conduct a comprehensive analysis of inequality perceptions in the United Kingdom and Germany, examining different dimensions: immigration, income inequality, and poverty. Their study reveals consistent overestimation of both poverty levels and share of those on top of the income distribution. They also find that gender, education, income, and political orientation are the significant determinants of misperceptions. For instance, women tended to overestimate the share of those under the poverty line, while men overestimate the income share of the richest. Although highly educated respondents showed more accurate perceptions of poverty levels, they are less precise about perceptions of income shares of those on top or bottom of income distribution.

In addition to individual-level determinants of misperceptions, contextual factors related to regional or cross-country differences such as regional- and country-level inequality and poverty rates also relate to income rank perceptions. Regional disparities in income distribution may amplify or mitigate biases, as individuals adjust their perceptions to localized norms and observable inequalities. Country differences also matter. Feichtmayer and Gründler (2021) document substantial cross-national differences in misperceptions. Interestingly, the respondents in higher developed countries such as Switzerland, the US, and Germany tend in general to overestimate their relative social standing, whereas individuals in Eastern Europe underestimate their own position. Arin et al. (2024) also find differences between the United Kingdom and Germany. The differences in all these instances could be due to various factors inherent to the countries such as history, economic growth and development, and the different institutions Gründler and Köllner, (2017).

The rise of globalization and inter-connectedness between countries, and advances in quality and availability of national-income data have made it necessary and possible to locate individuals on the global income scale. The integrated datasets containing the income data from most of countries worldwide now represent comprehensive global income database (Milanovic, 2016). These datasets allow for both cross-country comparisons and analyses of differences among residents of various nations. Thanks to those, objective income distribution worldwide and income inequality are increasingly being studied both within and across countries (e.g., Piketty, 2014; Hickel, 2017; Kanbur et al., 2022; Chancel and Piketty, 2021; Darvas, 2019; Milanovic, 2016).

The literature distinguishes between three main concepts of global inequality: unweighted international inequality or between country inequality, population-weighted international inequality, and global interpersonal inequality (Milanovic, 2006, 2013). Unweighted international inequality measures differences in per capita income across countries, calculated using GDP or average national income from household surveys without considering population size. Population-weighted international inequality incorporates also population sizes, providing an additional measure of inequality between countries. Global interpersonal inequality examines individual incomes worldwide by treating each person equally regardless of national affiliation. This latter approach conceptualizes the world as composed of individuals rather than nations and is of direct interest for the study of individual rank.

The global perspective is important as the place of individuals within national distribution and global distribution does not necessarily match. The individual position on global income rank is a result of both the individual position on national scale and the relative position of a country in a global context. Individuals from richer countries are naturally placed in the upper parts of the global distribution. However, over time, globalization has brought about the most profound redistribution and convergence of income ranks between the West, China, and other developing nations since the Industrial Revolution (Milanovic, 2024). Thus, the position of citizens of developed countries on the global scale has deteriorated over time, whereas the position of citizens of developing countries has improved (Milanovic, 2016).

Recent global processes and changes of global income distribution are often unknown to ordinary citizens across many countries regardless of the level of their development, making it difficult for ordinary people to understand their position globally. Indeed, the focus on the (perceived) interpersonal global income distribution results from the interest to explore whether people are aware of their position within the global income distribution. However, despite growing interest in measuring individual position in global income distribution, only few recent studies address individual perceptions of relative position in the global income distribution. Moreover, the analysis of (mis)perceptions of individual ranks in the global income distribution, defined as the discrepancy between perceived and actual income ranks is particularly rare in the literature (Fehr et al., 2022; Nair, 2018; Fehr et al., 2024). The examples of a global focus is research conducted by Fehr et al. (2022) in Germany and Nair (2018) in the United States, who examined how individuals form perceptions of their ranks in national and global income distributions, and how those perceptions causally relate to their national and global policy preferences. They find that almost half of the respondents underestimated their position in the global distribution. Similar to the studies on the national context Knell and Stix, (2020); Bublitz, (2022); Cruces et al., (2013), individuals tend to follow the scenario of center tendency (Sattler-Bublitz et al., 2024) or “middle-class” bias (Fehr et al., 2022). At the bottom of global income distributions individuals often overestimate their position in the global ranking, whereas those on the top tend to underestimate their position. Similarly, Sattler-Bublitz et al. (2024) explore how individuals in four European countries perceive their own income rank within the EU income distribution and observe the same tendency to lean toward the center. In contrast, some studies explore (mis)perceptions of between-country income inequality. For instance, Ziano et al. (2024) analyse how people estimate various indicators of economic development. Their findings suggest that Westerners tend to overestimate the wealth of developing and middle-income countries, underestimating the extent of global inequality. Therefore, despite the relatively limited number of studies in this area, all the previous studies about developed countries consistently reveal that individuals frequently misjudge their position within the global or supranational income distribution by mostly underestimating it together with the level of development and wealth of their own countries.

In addition to description of (mis)perceptions in global context, it is essential to understand the correlates of these (mis)perceptions. Yet, the study of individual correlates of perceptions of global inequality are limited, and most research simply argues that all individuals irrespective of their characteristics develop flawed perceptions of global income due to their reliance on their co-residents as their reference points. Nair (2018) claims that in advanced economies like the United States, reference groups are often limited to domestic peers, whose incomes tend to be higher at each percentile compared to the global distribution. As a result, individuals in such contexts systematically underestimate their global income rank while overestimating the global median income. Generally, misperceptions about income distribution are often more pronounced at the global level than in a national context, because individuals are more exposed to the information about domestic income than to the information about the global income. At the national level, people can make more accurate estimates about income distribution by observing their co-workers, neighbors, and social circles Nair, (2018), p. 5). Additionally, the media, political debates, and public reports often reinforce awareness about national income situation (Nair, 2018). By contrast, global income distribution receives far less attention in media and political discourse, particularly in developed countries where discussions of poverty in developing nations are limited. This imbalance further exacerbates biases when individuals assess their positions within global contexts (Nair, 2018).

To address our initial research questions, we utilize novel large-scale data collected through an online cross-sectional survey conducted in Italy in the months of November and December 2024 and in February and March 2025 (Kulic et al., 2025). The survey targeted individuals aged 18–70 and employing quotas to ensure representation of the Italian population across key socio-demographic variables, including gender, age, employment status, education level, and macro-region (North, Center, and South and Islands). The survey achieved a total sample size of 12,000 respondents, providing a robust foundation for in-depth analysis of income (mis)perceptions and their correlates across individual and contextual dimensions. The total sample after excluding cases with missing data on our core variables consists of 11,975 observations.

The research relies on questions assessing participants' perceived positions in national and global income distributions, socio-economic and demographic information, political orientation as well as the place of residence that was used as an indicator of geographical context.

This study uses two dependent variables capturing misperceptions of individual income ranking: one at the national level and the other one at global level. Misperceptions of individual position in the income distribution, either national or global, was derived from difference between respondent's subjective and objective income ranks expressed on a 0–100 percentile scale. Therefore, positive values indicate overestimation of one's income rank, while negative values indicate underestimation. Larger absolute values indicate greater misperception in one direction or another. The variable is continuous and ranges from −100 to 100.

As follows, the first dependent variable, Misperceptions of individual position in the national income distribution, is derived from the following continuous measures:

In a similar fashion, the second dependent variable Misperceptions of individual position in the global income distribution is a difference between:

Following previous research, the study includes a range of key sociodemographic variables, political orientation and contextual variables as possible correlates associated with income rank misperceptions both at national and global levels. Regression models incorporate the following independent variables: gender, age, education, employment status, migration background, urban–rural residence, and left–right political orientation.

Gender is coded as a binary variable (men and women). Age is grouped into six categories to reflect different life stages and capture possible cohort effect (18–24, 25–34, 35–44, 45–54, 55–64, and 65–70). The level of education is classified into three levels: Low-Up to elementary school, Medium-High school, and High-level-Bachelor degree and above. Employment status differentiates between employed, unemployed, inactive, and other. Migration background reflects the respondents' and their parents' country of birth and citizenship status. Respondents are classified into three groups: no migration background (if both the respondent and their parents are Italian), first generation (if respondent was born abroad), and second generation (if respondent was born in Italy but at least one of the parents is an immigrant). The type of settlement distinguished between rural and urban areas.⁶ Political orientation derives from self-placement on the left-right scale ranging from 1 (“far left”) to 10 (“far right”) and recoded into four categories: left (1–3), center (4–7), right (8–10), and missing (no response).

The analysis includes indicators for 20 Italian regions and four macro-areas: North-West, North-East, Center, and South and Islands. These contextual variables are analytically relevant due to Italy's persistent territorial disparities in economic development between less developed Southern regions and more developed regions from the North and the Center (D'Adamo et al., 2021, 2025).

This section examines the relationship between individuals' perceived positions in the national income distribution and their objective positions, with a focus on systematic patters of misperceptions across income groups. Figure 2 categorizes respondents by income deciles and compares their subjective and objective income ranks within the Italian income distribution.

The divergence between objective and subjective positions highlights the systematic misperceptions across income groups. There is a strong tendency for individuals to regress toward the mean, with those in lower income deciles overestimating their relative position and those in higher deciles underestimating it. For instance, the average perceived percentile in the 1st income decile is 46, whereas in the 10th income decile, it is 57. Despite the significant disparity in actual income levels between these deciles, the perceived difference amounts to just 11 percentage points. This pattern underscores a pronounced bias: the further individuals are from the middle of the income distribution, the more pronounced their misperception of their position. In contrast, individuals in the middle of the distribution exhibit the smallest gap between their objective and subjective positions, indicating a closer alignment between perception and reality.

This pattern reflects and confirms for Italy the well-documented phenomenon of the bias to the median or center bias where individuals across income groups tend to cluster their self-assessments around the middle of the income distribution. Such findings align with previously mentioned literature, which documents “center bias” (Hvidberg et al., 2023), “median bias” (Hoy and Mager, 2021), and “middle-class bias” (Evans and Kelley, 2004; Fehr et al., 2022).

Table 2 provides further clarifications and reveals insights into income rank misperceptions defined as difference between perceived and actual income rank in national distribution (see also Supplementary Figure A1). Interestingly, a majority of respondents (53%) with different degree underestimate their position in the income distribution, believing they are ranked lower than they actually are. In contrast, 46% overestimate their income rank, positioning themselves higher than their objective place. A small fraction, 1%, or 141 individuals out of 11,975, managed to exactly align their perceived and actual ranks (Table 2). These results confirm the previous findings for Spain and Argentina where both groups of over- and under-estimators are well populated (Cruces et al., 2013; Fernández-Albertos and Kuo, 2018), but not for Sweden where the majority underestimate their income rank in national income distribution (Karadja et al., 2017).

The extent of deviation among a substantial portion of the population highlights the widespread nature of income rank misperceptions and raises questions about the factors driving these biases. These findings have critical implications for understanding public attitudes toward income inequality and the potential mismatch between subjective experiences and objective realities.

Regional disparities also reveal systematic differences in income rank misperceptions (Figure 3). Here, we can see the same pattern and clear North–South divide: residents of more affluent Northern regions tend to underestimate their relative income rank in national distribution while residents of the poorer Southern regions overestimate their income ranks. For instance, in the economically prosperous regions of Lombardy, Veneto, and Emilia-Romagna, the objective income ranks are relatively high, on average 57–58th income percentiles, yet average perceived positions are between the 48th and 49th percentiles. Conversely, in less affluent regions such as Calabria, Basilicata, and Sicily, where average objective income ranks are 39 percentiles, individuals' perceived income positions surpass their objective ranks by over 10 percentile points. In Calabria and Sicily, the average perceived income rank is 49, and in Basilicata 52. In other words, in less prosperous regions there is an overestimation of own position, in comparison to prosperous regions where the underestimation is visible.

As for general tendency across income deciles, for Italian regions we can observe a central tendency bias: individuals across regions tend to perceive themselves closer to the middle of the income distribution regardless of average income ranks in their regions.

In the same way as for national income distribution, respondents tend to place themselves near the middle of the global income distribution, regardless of their actual income levels (Figure 4). Similar to the national income distribution, this pattern reflects a central tendency bias, where individuals gravitate toward the median. Similar to the findings above, this trend is more pronounced for the extreme deciles: individuals in the lowest global income deciles tend to overestimate their position, while those in the highest deciles underestimate it.

For example, those Italians who are in the 1st global income decile perceive themselves to be at the 51st percentile globally, while in reality, they are on average positioned around the 6th percentile. Conversely, individuals in the top 10th global decile (the richest) believe that they are at the 65th percentile, though their actual position is closer to the 96th percentile. Respondents that are in the 5th and 6th global deciles are the only groups that come close to accurately identifying their global standing: they perceive themselves to be at the 51st and 52nd percentiles, while their objective positions are around the 46th and 56th percentiles, respectively. The finding aligns with results from previous studies in Germany (Fehr et al., 2022) and the United States (Nair, 2018), which also identified a middle-class bias in global income perceptions.

The distribution of misperceptions of global income ranks shows almost the same pattern as for misperceptions of income ranks in national income distribution. About 54% of respondents underestimate their global income rank, 44% overestimate it, and 1.5% are accurate in their estimates (Table 3, Supplementary Figure A2).

Center tendency bias for regions can also be observed for perceptions of individual ranks on a global scale. Similar to the findings about perceptions of individual ranks within national context, Figure 5 displays the perceived and objective income ranks of respondents in global income distribution by their regions of residence. In line with center tendency rule, individuals living in more affluent Northern and Central regions generally tend to underestimate their global objective position, while those residing in poor Southern regions tend to overestimate their global objective position. The only exception in the Northern regions is Aosta Valley, while in the Southern regions, the exceptions are Abruzzo and Molise. For instance, in the more developed regions such Lombardy, the mean objective rank in global income distribution is the 60th percentile whereas the perceived global income rank is at 54th percentile. Similarly, in Piedmont, the objective mean for global rank is 59th percentile in comparison to subjective mean global rank of 53rd percentile; this applies also to Liguria where the objective rank is 58th percentile vs. the subjective rank of 53rd percentile. On the contrary, in the Southern region of Sicily, the mean objective income rank is 49th percentile in comparison to the subjective income rank of 52nd percentile. In Calabria, another Southern region of Italy, the mean objective global rank is 49th percentile in comparison to 53rd percentile as subjective rank. This confirms the general finding that those who are poorer either as individuals or living in poorer regions tend to overestimate their position toward the mean, whereas those who are richer individually and living in richer regions, tend to underestimate their position toward the mean.

This section investigates which social groups are more prone to misperceive their income ranks both in national and global context, and explores how these misperceptions vary across sociodemographic and contextual divides. The current analysis consists of a series of regression models to examine the correlates of income rank misperceptions within country and within world in greater detail. Since our dependent variables, misperceptions of income rank, either in national or global income distribution, can take both positive and negative values, the interpretation of raw regression coefficients is not always intuitive. While the coefficients show the direction and relative magnitude of group differences compared to the reference category, they don't reveal whether a given group's estimates values are closer to zero (that means more accurate perceptions) or further from it (indicating larger misperceptions). To enhance interpretability, the regression coefficients (reported in Table 4) are complemented with predictive margins (Figures 6, 7, Supplementary Tables A1, A2) that translate estimated results into predicted values of misperceptions for each group, holding other variables constant. This approach allows us to directly observe and compare the degree of misperception across multiple categories.

Table 4 shows how demographic, socioeconomic characteristics, and political orientation along with geographical characteristics correlate with misperception of income ranks in national and global income distributions. The table indicates significant differences in misperceptions across groups. Figure 6 translates the coefficients in predictive margins for national income distribution. The x-axis represents the percentage point deviation in income rank perception with zero indicating accurate perception, while the y-axis lists various individual and contextual characteristics. Given that the dependent variable ranges from −100 to 100%, the estimates can be interpreted directly in terms of percentage point difference: positive values indicate an overestimation relative to the objective position, whereas negative values indicate an underestimation of objective income ranks.

The results show a statistically significant gender differences in misperceptions at national level: men are more likely to underestimate their position compared to women (b = 3.60, p < 0.01), who tend to accurately perceive their income rank. Age is important for misperceptions: The younger people are more optimistic about their income ranks. Young adults (18–24 years old) tend to overestimate their income rank by 9 percentage points. As people age, they become more realistic about their position in income distribution. Those who are 25–34 years old demonstrate less overestimation (4 percentage points) then members of the youngest group. Middle-aged people from 35 to 44 and 45 to 54 years old are rather accurate in the estimates of their own position in income distribution (−2 and −1 percentage points). In contrast, older cohorts tend to underestimate their income rank. This underestimation intensifies with age. Those who are from 55 to 64 years old think that their position is 3 percentage points lower than it is, and those who are over 65 think that they are 14 percentage points lower in income distribution compared to the real position.

Educational attainment is another strong correlate of misperceptions. Individuals with lower level of education overestimate their income rank by 5.68 percentage points, while those with medium (b = −10.06, p < 0.01; predictive margins is −4.40) and high levels of education (b = −16.13, p < 0.01; predictive margins is −10.44) show a tendency to underestimation. This pattern partially reflects previous findings about median bias of people located in lower- and upper-income deciles. Education in this context can be considered more as an indicator of a position in social hierarchy then as a source of unbiased information about individual positions in income distribution. This approach provides us with the reasoning why highly educated people underestimate their income rank by 10 percentage points. Differences also emerge by employment status: the unemployed significantly overestimate their rank by 7.49 percentage points, employed on the contrary generally underestimate their rank by 4.84 percentage points.

Regarding migration background, natives underestimate their position in income distribution, while immigrants, overestimate their position. Specifically, first-generation migrants show the highest levels of overestimation (7 percentage points), followed by second-generation migrants (4 percentage points), and natives slightly underrate their position by on average 2 percentage points. Overall, there is a clear pattern: low-resource individuals overestimate their position, while high-resource individuals underestimate their position in the income distribution. There is a difference in misperceptions between individuals living in urban and rural areas. Respondents in urban areas show slightly larger level of under-estimation of their income position (1.43 percentage points), in comparison to residents of rural areas that tend to be rather accurate.

Regional disparities are pronounced and align with broader economic divides in Italy. In this context, we can also identify evidence of the median bias: residents of more prosperous northern regions, for example Veneto, Friuli Venezia Giulia, and Lombardy, tend to underestimate their position in national income distribution, while residents of Southern regions, such as Campania, Basilicata, and Sicily, exhibit significant overestimation of their income rank. These findings are consistent with Italy's well-documented North–South divide in economic opportunities and income levels. The observed overestimation in the South may stem from a combination of lower exposure to national benchmarks and a greater reliance on local comparisons.

The following analysis contributes to the previous literature by systematic examination of the correlates of misperceptions of global income position. The same modeling strategy is applied as for misperceptions at the national level: misperceptions at global level are regressed on socio-demographic variables and 20 Italian regions (Table 4). Figure 7 presents the predictive margins with 95% confidence intervals derived from the OLS regression analyzing the misperception of income position in the global income distribution (Table 4). As before, misperception is defined here as difference between an individual's subjective and objective income percentile position in global income distribution; hence, lower values indicate greater underestimation, while higher values suggest overestimation.

The results show that both men and women tend to underestimate their position: the average underestimation is 3 percentage points yet with no significant difference across two groups. Younger adults, particularly those under 24, tend to overestimate their relative income position by 5 percentage points. In contrast, older age groups tend to underestimate their income rank on the global scale: older adults (65–70) show the most salient underestimation by 10 percentage points, whereas the other age groups are closer to accurate perceptions: they underestimate their position by 2-4 percentage points. Hence, the older the individuals are, the more they tend to underestimate their income percentile position on the global scale. Regarding education, highly and medium educated individuals tend to underestimate their position in global distribution (for 6 and 5 percentage points, respectively) while low educated show no bias in estimates. Unemployed respondents tend to overestimate their position by three points, while employed tend to underestimate their position by six points. Migration background also associates with individual misperceptions. First-generation migrants overestimate their income position by four points, while those without a migration background show a tendency to underestimate it by 3.5 percentage points. The second-generation migrants are relatively accurate in their estimates. Regarding political orientation, respondents having left political view perceive their income rank on global scale almost correctly (−1 percentage points), while those who positioned themselves at the center or right show a larger underestimation of between 3 and 4 percentage points. Those who preferred not to disclose their political orientation similarly underestimate their position, by approximately 2.7 percentage points. Respondents living in urban areas tend to underestimate their global income position by approximately 3 percentage points while those residing in rural contexts show no bias. Regarding the contextual correlates, residents of Northern and Central Italy (e.g., Lombardy, Emilia-Romagna, Tuscany) tend to underestimate their position, whereas individuals from Southern regions (e.g., Calabria, Sicily, Campania) tend to overestimate it. In Lombardy, Piedmont, and Liguria, as the three richest Italian regions (D'Adamo et al., 2021, 2025), the underestimation is approximately from 5 to 7 percentage points. Differently, in Southern regions there is an overestimation of global position, the largest of which in Basilicata (7 percentage points), followed by Calabria and Campagna (approximately at 4 percentage points). However, among the Southern regions, there are three exceptions: respondents from Sardinia, Abruzzo, and Molise underestimate their position by 2, 4, and 8 percentage points respectively. The results overall show significant similarity to previous findings about misperceptions of income ranks in national income distribution.