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Cited by 19Labor market dynamics and wage inequalityGender, Labor, and Family DynamicsLabour Market and Migration

The Gender Wage Gap in Peru: Drivers, Evolution, and Heterogeneities

Open access
Vaccaro, Giannina, Basurto, Maria Pia, Beltrán, Arlette, Montoya, Mariano·2022·Social Inclusion
DOI 10.17645/si.v10i1.4757
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Abstract

Despite the recent economic growth and gender equality improvement in educational attainment, important gender disparities remain in the Peruvian labour market. This article provides a comprehensive overview of the Peruvian gender wage gap evolution during 2007–2018 and identifies key elements that explain its patterns. First, the article shows that the raw wage gap showed an upward trend between 2007–2011, ranging from 6% to 12%, and remaining around that top bound ever since. Second, using Oaxaca‐Blinder decomposition we find that the unexplained wage gap has remained virtually unchanged at around 17% during the study period. Reductions in endowment differences between men and women coupled with a stagnant unexplained gap led to slightly larger raw wage gaps over time. Moreover, the stagnant unexplained gap suggests the presence of structural problems regarding social norms, gender stereotyping and potential discrimination that affects the wage gap. Third, we show that both at a national and regional level, gender wage gaps are larger within the lowest percentiles, and they mostly have a downward slope across the earnings distribution. Finally, after computing the raw and unexplained gap at the region‐year level, we show that smaller regional gender gaps are associated with (a) higher GDP, (b) lower levels of domestic physical violence against women, and (c) lower percentages of women as household heads.

AI snapshot

Written from the paper’s full text.

TL;DR

This paper documents Peru’s gender wage gap from 2007–2018, showing a raw gap that rose and then stabilized around 10% while the unexplained gap remained near 17%. It finds larger gaps among vulnerable groups and regions, and links smaller regional gaps to higher GDP, lower domestic physical violence, and lower percentages of women as household heads.

Key findings

  • The raw gender wage gap rose from 6%–12% in 2007–2011 and then stabilized around 10%; the unexplained gap remained virtually unchanged at around 17% over the period.
  • The explained gap was negative, ranging from -15% to -6%, indicating employed women had better observable working characteristics than employed men; education contributed -3 to -5 p.p., while occupation/industry contributed +3 to +5 p.p.
  • Heckman-adjusted raw gaps were larger, increasing from 7% to 22% between 2007 and 2018, compared with 6% to 12% without selection correction.
  • Unexplained gaps were higher in the private sector (17%) than the public sector (9%) and higher among informal workers (22%); quantile results show larger gaps at the lowest percentiles, with the unexplained gap at p10 falling from 0.39 in 2007 to 0.18 in 2018.
  • Regional unexplained gaps ranged from 12% in Lima to 27% in Centre Sierra; smaller regional gaps were associated with higher GDP, lower domestic physical violence, and lower percentages of women as household heads.

Methods

  • Uses individual-level Peruvian National Household Survey (ENAHO) data for 2007–2018, restricted to individuals aged 18–65, excluding unemployed, retired, and self-employed workers, trimming the first and last percentiles of wages; pooled sample of 250,000 observations.
  • Estimates Oaxaca-Blinder decompositions following Fortin (2008), Machado-Mata quantile decompositions with Chernozhukov et al. (2013) standard errors, and Heckman (1979) correction for selection into labour force participation.
  • Computes raw and unexplained gaps at region-year level and runs pooled regressions against regional aggregate variables; regional analysis uses 25 geopolitical regions grouped into 8 macro-regions.

Limitations

  • The paper states that self-employed workers—about 50% of the Peruvian labour force—were excluded because of heterogeneous self-employment types and selection concerns beyond the study’s scope.
  • The paper states that the regional analysis does not aim to identify causal effects and that the methodology does not provide a direct way to test drivers of reductions in the unexplained gap at lower quantiles.
  • Evident from the text: the exclusion of self-employed workers limits coverage of a large and likely more informal segment of the labour market, and the regional regressions are descriptive associations rather than causal estimates.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.17645/si.v10i1.4757

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

4 of 15 cited sources checked · 1 supported · 1 flagged · accuracy not yet measured

  • Findingcitation

    Once accounting for the working sector, there are no effects through occupation composition.

    “Interestingly, as suggested by Neumark and Vaccaro (2020), once we account for the working sector, there are no effects through occupation composition.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Neumark and Vaccaro (2020) source

      In “OLS Wage Equation Estimates” (page unavailable), the paper reports that detailed occupation controls alone reduce the estimated wage gap at labor-market entry from about 8.5% to a small, statistically insignificant 1.3%. Adding industry controls then brings it to zero. It does not find that occupation composition has no effect once working sector is accounted for; its reported comparison points to an important role for occupation controls. (LLM, conf=0.82)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
  • Premisecitation

    The public sector usually has more accountability measures and transparency labour rules that allow them to implement equal opportunity and anti-discrimination policies.

    “Studies argue that this situation occurs because the public sector usually has more accountability measures and transparency labour rules that allow them to implement equal opportunity and anti-discrimination policies (Antón & Muñoz de Bustillo, 2015).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Antón & Muñoz de Bustillo, 2015 source

      The Econometric analysis section says the public sector is usually a pioneer in measures promoting gender equality and non-discriminatory practices. It also suggests that more rigid pay-setting procedures leave less room for unexplained wage differences. But the cited passages do not identify greater accountability or transparent labour rules as the reason those measures can be implemented. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
  • Findingown data

    In Peru, the unexplained gender wage gap remained virtually unchanged at around 17% during 2007-2018.

    “Second, using Oaxaca-Blinder decomposition we find that the unexplained wage gap has remained virtually unchanged at around 17% during the study period.”
    • Also stated in: § 1. Introduction · plain
      “On the other hand, the unexplained wage gap (also called”
    • Also stated in: § 4.1. Aggregate Results · plain
      “During this period, the unexplained wage gap was steady at around 17%, with only a minor decrease between 2010 and 2012.”
    Quote in the paperSubstantial claim
  • Findingown data

    The Andean regions (mainly Southern and Centre Sierra) average a gender wage gap of over 20% during both periods.

    “The Andean regions (mainly Southern and Centre Sierra) average a gender wage gap of over 20% during both periods.”
    Quote in the paperNot a substantial claim
  • Findingcitation

    The unexplained wage gap is persistently higher in the private than in the public sector (17% vs. 9%, respectively, for the whole period).

    “Third, the unexplained wage gap is persistently higher in the private than in the public sector (17% vs. 9%, respectively, for the whole period).”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 15
  • May combine two claims. 28
  • The quote only partly states this claim. 2

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Ñopo (2009) found an unexplained gender wage gap of 28% for the period between 1986 and 2000.

    “For example, Ñopo (2009) found an unexplained gender wage gap of 28% for the period between 1986 and 2000.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Ñopo (2009) source

  • May combine two claims.

    Premisenone given

    Ñopo (2009) was the most recent study about the evolution of the Peruvian gender wage gap and comprised a period between 1980 and 2000.

    “To the best of our knowledge, Ñopo (2009) was the most recent study about the evolution of the Peruvian gender wage gap and comprised a period between 1980 and 2000.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Ñopo (2009) source

      The Summary says Ñopo analyzes the evolution of Peru’s gender wage gap, but specifies 1986–2000, not 1980–2000. The claim that it was the most recent study is the citing authors’ own qualification, not a finding attributed to Ñopo. (LLM, conf=0.90)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    There is a considerable degree of heterogeneity across macroregions with the highest raw gaps surpassing 20%.

    “First, there is a considerable degree of heterogeneity across macroregions with the highest raw gaps surpassing 20%.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Occupations and industries explain the observed gender gap (between +3 p.p. and +5 p.p.), confirming that men are consistently allocated to more profitable industries than women.

    “Conversely, we find that, as shown in the literature, occupations and industries explain the observed gender gap (between +3 p.p. and +5 p.p.), confirming that men are consistently allocated to more profitable industries than women.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Besides more women working in the informal sector, the unexplained gender wage gap against female workers is also more pronounced (22%).

    “Fourth, besides more women working in the informal sector, the unexplained gender wage gap against female workers is also more pronounced (22%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Education and tenure contribute negatively to the unexplained component, attenuating the overall gap.

    “While the unexplained gender wage gap is always positive and statistically significant, both education and tenure contribute negatively to the unexplained component, attenuating the overall gap.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The unexplained gender wage gap is always positive and statistically significant.

    “While the unexplained gender wage gap is always positive and statistically significant, both education and tenure contribute negatively to the unexplained component, attenuating the overall gap.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Southern Sierra and Centre Sierra have the highest gender physical violence rate and the highest unexplained gender wage gaps.

    “Southern Sierra and the Centre Sierra are the regions with the highest gender physical violence rate, as well as the highest unexplained gaps.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    After correcting for participation decision, the raw wage gap increased from 7% to 22% between 2007 and 2018, compared to 6% to 12% without correction, almost doubling its size.

    “On the one hand, the raw wage gap increased from 7% to 22% between 2007 and 2018 in comparison to 6% to 12% when we do not correct for self-selection, almost doubling its size.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Andean territories show the largest gender wage gaps at the lowest percentiles, at around 50%, but almost 0% at the highest percentiles.

    “On the one hand, Andean territories show the largest gender wage gaps at the lowest percentiles, at around 50% (but interestingly, almost 0% at the highest percentiles).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The unexplained gap in Peru is heterogeneous across regions: it ranges from 12% in Lima to 27% in Centre Sierra, and it is always positive.

    “As in the case of the raw gap, the unexplained gap in Peru is heterogeneous across regions: It ranges from 12% in Lima to 27% in Centre Sierra, and it is always positive.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Education explains between 3 to 5 negative percentage points of the explained component, pointing towards a better education endowment in working women.

    “We find that for every reported year, education explains between 3 to 5 (negative) percentage points of the explained component, pointing towards a better education endowment in working women.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Among macro-regions, Centre Sierra has the lowest GDP per capita and the largest unexplained gender wage gap component.

    “the one with the lowest GDP per capita, Centre Sierra, is actually the one with the largest unexplained component.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The Forest region had negative raw gaps during 2007-2010 and close to zero during 2011-2018.

    “Remarkable examples are the Forest region with negative raw gaps during 2007-2010 and close to zero during 2011-2018.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    Among macro-regions, Lima has the highest GDP per capita and the smallest unexplained gender wage gap.

    “the region with the highest GDP per capita, Lima, is the one with the smallest unexplained gap”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Smaller regional gender gaps in Peru are associated with higher GDP and lower levels of domestic physical violence against women.

    “we show that smaller regional gender gaps are associated with (a) higher GDP, (b) lower levels of domestic physical violence against women”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In Peru, the raw gender wage gap showed an upward trend between 2007 and 2011, ranging from 6% to 12%, and remained around that upper bound thereafter.

    “First, the article shows that the raw wage gap showed an upward trend between 2007-2011, ranging from 6% to 12%, and remaining around that top bound ever since.”
    • Also stated in: § 1. Introduction · plain
      “We find that the raw wage gap showed an upward trend between 2007-2011, ranging from 6% to 12%, and remaining around that top bound ever since.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Both at a national and regional level in Peru, gender wage gaps are larger within the lowest percentiles, and they mostly have a downward slope across the earnings distribution.

    “Third, we show that both at a national and regional level, gender wage gaps are larger within the lowest percentiles, and they mostly have a downward slope across the earnings distribution.”
    • Also stated in: § 4.3. Quantile Decomposition Results · plain
      “In line with previous research (Carrillo et al., 2014;Del Pozo Segura, 2017;Ñopo, 2009), we find that both gender wage gaps are considerably larger at the lowest percentiles for the evaluated period.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Education contributes to reducing the observable gender wage gap through both the unexplained and explained components.

    “education in the unexplained and explained component contributes to reducing the observable gap of working men and women.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The Peruvian unexplained gender wage gap has remained stable during the last 13 years at around 17%, with only minor reductions at the lowest end of the wage distribution.

    “the Peruvian unexplained gap has remained stable during the last 13 years at around 17%, with only minor reductions at the lowest end of the wage distribution.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data

    Unexplained gender wage gaps are always positive.

    “always-positive unexplained gaps”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The negative sign of the explained gender wage gap can be interpreted as the attenuation effect that control variables have on the raw wage gap, pointing towards employed women having better working characteristics than employed men.

    “The negative sign of this gap can be interpreted as the attenuation effect that control variables included in the decomposition have on the raw wage gap, therefore, pointing towards employed women having better working characteristics than employed men.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Women's empowerment and economic development have a strong and potentially bi-directional relationship.

    “Duflo (2012), who explains a strong and potentially bi-directional relationship between women's empowerment and economic development.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Duflo (2012) source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The lower unexplained wage gap for the older group may reflect differences in children's ages, with younger children demanding more care.

    “The only age group that consistently has a lower unexplained wage gap is the older group (43 and older), this result may be a reflection of differences in children's ages among the first two groups in comparison to the latter being that younger children (especially under five) demand more care.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Peru ranks 128 out of 153 countries in wage equality for similar work, being one of the most unequal countries in the region.

    “However, in terms of wage equality for similar work, Peru ranks 128 out of 153 countries, being one of the most unequal countries in the region (WEF, 2020, p. 285).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites WEF, 2020, p. 285

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    These factors could explain why working men have more years of education and work experience in some particular regions.

    “Altogether, these factors could be behind working men having more years of education and work experience for some particular regions.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Women in greater vulnerability conditions (less educated and informal) have higher unexplained wage gaps than other groups, reflecting a greater disparity in terms of wage gap.

    “In summary, we show that women in greater vulnerability conditions (less educated and informal) have higher unexplained wage gaps than other groups, reflecting a greater disparity in terms of wage gap.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    For each year, individuals lying in the first or last percentile of the wage distribution were trimmed to avoid conclusions being distorted by outliers.

    “Finally, for each year, we trim individuals lying in the first or last percentile of the wage distribution to avoid conclusions being distorted by outliers.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Heterogeneous regional contexts for men and women could involve differences in access to education, early labour market engagement, and participation in well-remunerated sectors.

    “These could be, for example, in terms of access to education (in all levels), the ability to engage in the labour market at an early age, and the possibility to participate in well-remunerated sectors.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Geographic conditions may be more relevant than individual characteristics at predicting gender violence.

    “recent evidence suggests that geographic conditions may be more relevant than individual characteristics at predicting gender violence (Hernández et al., 2018).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hernández et al., 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    These regions could have stronger structural inequalities in other domains.

    “suggesting these could be regions with stronger structural inequalities in other domains.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Larger gaps are found within the poorest quantiles, independently of the geographic and cultural conditions.

    “This finding is in line with our aggregate results, pointing out a consistent outcome: Larger gaps are found within the poorest quantiles, independently of the geographic and cultural conditions.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The study uses the Chernozhukov et al. (2013) extension to compute asymptotic standard errors.

    “In addition, we use the Chernozhukov et al. (2013) extension to compute asymptotic standard errors.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Chernozhukov et al. (2013)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    The endowment difference between men and women in Peru reduced during 2007-2018, and women in the Peruvian labour market are now more similar to men in terms of human capital and socio-demographic characteristics.

    “This suggests that the endowment difference between men and women (i.e., in terms of education, experience, tenure, and other controls used in the regression) reduced during this period, and therefore women in the Peruvian labour market are now more similar to men in terms of human capital and socio-demographic characteristics.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The regional aggregate regression method does not identify causal effects; it aims to shed light on associations that could help comprehend regional differences.

    “The method of estimation does not intend to identify causal effects, but instead to shed some light on interesting associations that could help to better comprehend regional differences.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    According to the theory of exposure, increasing individual employment reduces domestic violence by reducing the time partners spend together.

    “According to the theory of exposure, incrementing individual employment will reduce domestic violence by reducing the time partners spend together”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Aizer, 2010; Zhang & Breunig, 2021

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    The study statistically tests whether overall regional gender gaps have changed significantly between the two periods of analysis.

    “Following a similar procedure to Piazzalunga and Di Tommaso (2019), we statistically test whether overall regional gender gaps have changed significantly between the two periods of analysis.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Piazzalunga and Di Tommaso (2019)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Regions where women struggle more to support their families may be those where women are forced into less favourable jobs and sectors, facing larger wage gaps.

    “this last result may suggest that those regions where women struggle more greatly to support their families are those where women may be forced to allocate in less favourable jobs and sectors (due to time constraints for example), facing larger wage gaps.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The backlash effect posits a positive relationship between gender physical violence and labour outcomes.

    “the backlash effect posits a positive relationship between gender physical violence and labour outcomes”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hornung et al., 1981; Macmillan & Gartner, 1999

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    According to household bargaining theory, an increase in a woman's relative wage raises her power position and lowers the levels of violence in the household.

    “according to household bargaining theory, an increase in a woman's relative wage raises her power position and lowers the levels of violence in the household”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Aizer, 2010; Zhang & Breunig, 2021

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims. The quote only partly states this claim.

    Interpretationreasoning

    Higher unexplained gaps for the poorest lead to a pervasive cycle of human capital losses for women, reinforcing wage and participation gaps.

    “This leads to a pervasive cycle of human capital losses for women, which reinforces wage and participation gaps.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Peru is one of the countries with the highest gender inequality in the region, mainly in economic independence and labour participation.

    “Peru is still one of the countries with the highest gender inequality in the region, mainly in terms of economic independence and labour participation (WEF, 2020).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites WEF, 2020

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

42 of 42

  • The paper relies on this without support.

    The exclusion of self-employed workers does not substantially bias the estimated gender wage gaps for the Peruvian labour market.

    “The sample of the study is restricted to individuals between 18 and 65 years of age and it excludes those who are unemployed, retired, and self-employed.”
    “Therefore, from an estimation point of view, including these types of workers would require us to model selection into selfemployment that is beyond the scope of this article.”

  • The paper relies on this without support.

    The observable characteristics included in the Oaxaca-Blinder and Machado-Mata decompositions capture the relevant differences in human capital, sociodemographic characteristics, and occupation, so that the unexplained component reflects differential returns rather than omitted variables.

    “Here, w t g is the log hourly wage and X t g constitutes a vector of observable characteristics (listed in Table 1).This vector also includes the occupation and industry dummies.”
    “This suggests that unexplained wage differentials operate mainly through non-observable characteristics, such as cultural practices in the firm, personal skills, and potentially gender discrimination.”

  • The paper relies on this without support.

    The ENAHO survey data are representative and accurate for the Peruvian working-age population over 2007-2018.

    “ENAHO is a representative annual national and regional survey, conducted by the National Institute of Statistics (INEI).”

  • The paper relies on this without support.

    Seven out of ten women in Peru have experienced some type of violence by their current or prior partners.

    “seven out of ten women have experienced some type of violence by their current or prior partners”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • El factor no observable persiste como uno de los mayores responsables de la brecha de ingresos desfavorable a las mujeres.

    “Sin embargo, como muestran Vaccaro et al. (2022), el documento encuentra que el factor no observable persiste como uno de los mayores responsables de la brecha de ingresos desfavorable a las mujeres.”

    From Changes in Peru's Gender Earning Gap: An Analysis from 1997 to 2021 (2023) · cites this paper as Vaccaro et al. (2022)

  • Pese a avances en acumulación de capital humano, prevalecen barreras laborales para las mujeres en el ingreso y desempeño dentro del mercado laboral.

    “Pese a estos avances en acumulación de capital humano, prevalecen barreras laborales para las mujeres en el ingreso y desempeño dentro del mercado laboral.”

    From Evolución de la brecha salarial de género en el Perú (2024) · cites this paper as Vaccaro et al. (2022)

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Opposite findings for women household heads

    Major

    The abstract says smaller regional wage gaps are associated with fewer women household heads, while the introduction and conclusion say they are associated with more women household heads.

  • Centre Sierra is not the lowest-GDP region in Table 7

    Minor

    The claimed lowest GDP per capita is Centre Sierra, at 879.61 USD in Table 7. Northern Sierra is lower, at 873.95 USD.

  • Negative early regional raw gap attributed to the wrong region

    Minor

    The text attributes a negative 2007-2010 raw gap to the Forest region. Table 6 reports a positive 0.05 for Forest; the negative value, −0.12, belongs to Northern Sierra.

  • Informal work is more prevalent among women in the reported sample

    Minor

    The text says informal work is more prevalent among men, but Table 2 reports higher female shares in both displayed years: 0.46 versus 0.40 in 2007 and 0.45 versus 0.42 in 2018.

4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Boraz, F., & Robano, C. (2010). Brecha salarial en Uruguay [Gender wage gap in Uruguay]. Revista de Análisis Económico, 25(1), 49–77.

Cited by

Sorted by citations

Related

Authors
Vaccaro, G., Basurto, M. P., Beltrán, A., & Montoya, M.
Affiliations
  • FORS – Swiss Centre of Expertise in the Social Sciences (CH)
  • University of the Pacific (PE)
ORCID
Venue
Social Inclusion
Publisher
Cogitatio
Published
2022-01-25
Volume
10
Issue
1
Pages
19-34
ISSN
2183-2803 (ISSN-L)
DOI
10.17645/si.v10i1.4757
OpenAlex
W4210520669
Semantic Scholar
8bee3af6e6f3332c5b76bb1daa517be54f1bd5f5
Cited by
17
References
27
Citations by year
2025: 2 · 2024: 4 · 2023: 8 · 2022: 2 · 2013: 1
FWCI
3.16
Type
journal article
Language
en
Open access
Licence
Locations
  • Social Inclusion (publishedVersion, cc-by)
  • Social Inclusion (Cogitatio Press) (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Social Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences) (submittedVersion, cc-by)
  • IRIS (submittedVersion)
  • SERVAL (Université de Lausanne) (submittedVersion)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
  • Social Sciences › Gender Studies › Gender, Labor, and Family Dynamics
  • Social Sciences › Gender Studies › Labour Market and Migration
Keywords
gender pay gap, Peru, unexplained wage gap, Oaxaca-Blinder decomposition, gender discrimination, gender norms, gender stereotyping, wage distribution, regional wage differentials, domestic violence against women

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-19.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-19.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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