1 Summary

The Honduras HHS provides a useful view of change in management and collective action, economic conditions, and food security—three of the main household- and community-level dimensions that Rare’s Coastal Fisheries program monitors through the HHS. Across these pillars, several encouraging signals are visible in Honduras. Direct participation in fisheries management and pro-compliance behavior have strengthened; reported real household income has increased, including fishing-derived income among households that earn from artisanal fishing; and households report better food availability and stronger confidence in securing enough food in the future. At the same time, trust in local decision-makers and perceived financial sufficiency have weakened.

The strongest evidence comes from results that point in the same direction under both analytical approaches described below. When the two approaches differ, we place greater weight on the Matched-community results because they compare the same places over time.

2 Data coverage

The analysis uses 4,927 Honduras HHS responses covering 16 ABMs and 70 communities, collected between 2019 and 2025. Coverage varies across ABMs and survey generations: some ABMs have large repeated samples that support before–after analysis, while others contribute only a baseline or current snapshot.

Across the dataset, 36 communities appear in at least two survey generations. Of these, 27 have at least 10 HHS responses in each of two usable rounds. These repeated communities allow us to compare the same places over time and provide the basis for the Matched-community approach described below.

ggplot(
  coverage_plot_data,
  aes(
    x = factor(
      survey,
      levels = c(
        "2019-2022",
        "2022-2024",
        "2024-2026"
      )
    ),
    y = fct_reorder(
      abm,
      n_responses,
      .fun = max
    )
  )
) +
  geom_point(
    shape = 21,
    size = 9,
    fill = COL_POS,
    color = "black",
    stroke = 0.7
  ) +
  geom_text(
    aes(label = n_responses),
    color = "white",
    fontface = "bold",
    size = 3.1
  ) +
  scale_x_discrete(
    expand = expansion(add = 0.35)
  ) +
  labs(
    title = "HHS coverage across Honduras ABMs",
    subtitle = "Number of responses in each HHS survey generation",
    x = "HHS survey generation",
    y = NULL,
    caption = "Single isolated observations in Puerto Cortes (2022-2024) and San Francisco (Paisaje Marino; 2024-2026) are omitted from this coverage figure."
  )

3 Methodology

We use two complementary approaches to summarize before–after change in Honduras:

  1. The All ABMs approach includes every ABM with at least 50 valid responses for a given measure in both an earlier and later survey round. All communities surveyed within the ABM are used, change is calculated within each ABM, and every eligible ABM receives equal weight in the Honduras estimate. This makes the fullest use of the HHS data and describes how outcomes changed across the program sites as they were surveyed. Its main limitation is that the mix of communities within an ABM can change between rounds.

  2. The Matched-community approach compares only communities observed in at least two survey generations and requires at least 10 valid responses for the specific measure in both the earlier and later community-round. Each matched community receives equal weight. This is the more reliable geographic before–after comparison because the same places are observed at both points in time. Its trade-off is narrower coverage: it describes the repeatedly surveyed communities rather than the whole portfolio.

We interpret the two estimates together. A result is most convincing when both approaches point in the same direction; when they differ materially, we give more weight to the Matched-community estimate for interpreting change. Honduras-wide figures show 95% bootstrap confidence intervals, resampling ABMs for the All-ABM estimate and matched communities for the Matched-community estimate. These are repeated cross-sectional before–after comparisons, not causal estimates of Rare’s impact.

3.1 Income processing and cleaning

Some earlier HHS rounds recorded total monthly household income as categories rather than exact amounts. For the continuous-income analysis, those categories are represented by their midpoints: 1,250 HNL for 0–2,500; 3,750 for 2,500–5,000; 7,500 for 5,000–10,000; and 30,000 for 10,000–50,000.

To account for inflation and make income comparable across survey years, income is converted to constant 2024 Lempiras using Honduras annual-average CPI. Observations above the 99th percentile within each ABM and survey round are then removed before calculating means. Total income therefore represents average reported monthly household income from all activities in real 2024 HNL.

For artisanal-fishing income, the question is: among households earning income from artisanal fishing, how did fishing income change? Fishing-derived income is calculated for households reporting a positive artisanal-fishing income share as total real monthly household income multiplied by the reported percentage of income from artisanal fishing. A separate 99th-percentile filter is then applied to this derived measure.

4 Key HHS findings across three pillars

This brief focuses on management and collective action, economic conditions, and food security because these are the principal HHS-derived dimensions used by the program to understand community management capacity and household resilience. Each pillar first shows Honduras-wide change using both approaches and then shows the latest adequately sampled profile across ABMs. Detailed ABM results are moved to the Appendix.

4.1 Management and collective action

The management and collective action pillar combines measures of actual participation, pro-compliance behavior, confidence in collective management, legitimacy, and trust.

Measure Definition used in this brief
Management-meeting attendance Share of applicable households reporting that at least one household member attended a fisheries-management-body meeting in the last month. Responses indicating that no meeting was held or no management body exists are excluded.
Management leadership Share of applicable households reporting that at least one member holds a leadership position in the fisheries management body. Responses indicating no management body exists are excluded.
Encouraging compliance Share reporting that they encourage others inside or outside the community to comply with fishing regulations often or very often. Communities with no fishing regulations are excluded for this measure.
Community ability to manage the fishery (collective efficacy) Share who agree or strongly agree that their community has the ability to manage the fishery effectively and maximize food and profits.
Expected management benefits Share answering Yes when asked whether the fisheries-management / managed-access and reserve approach will benefit the community over the next five years. Unsure and No are treated as unfavorable; no management system is excluded.
Fair access rights Share who agree or strongly agree that access rights to the managed-access area have been distributed fairly to fishers.
Trust in local decision-makers Share who agree or strongly agree that local decision-makers / authorities can be trusted to make decisions that benefit the community over their own interests.

4.1.1 Honduras-wide change

management_summary <- binary_summary %>%
  filter(indicator %in% paste0("M", 1:7)) %>%
  arrange(indicator)

summary_change_plot(
  management_summary,
  title = "Management and collective action: Honduras-wide change"
)

The clearest positive signal is direct participation in fisheries management. Management-meeting attendance changes by +54.3 pp in the All-ABM analysis and +47.4 pp in the Matched-community analysis. Encouraging others to comply with fishing regulations also moves positively under both approaches (+10.0 pp and +8.6 pp).

The collective-efficacy measure asks specifically whether respondents believe their community can manage the fishery effectively and maximize food and profits. It changes by -4.3 pp across all eligible ABMs and +2.9 pp among matched communities.

Trust is the clearest counterpoint. The share agreeing that local decision-makers can be trusted to put community interests ahead of their own changes by -13.6 pp and -10.2 pp, respectively.

The management story is therefore stronger participation and pro-management behavior alongside weaker trust, rather than uniform improvement across every dimension.

4.1.2 Management-support norms remain high

The HHS also measures support for the principles and mechanisms of community fisheries management. The current-profile figure summarizes the latest adequately sampled ABM responses to statements on strong enforcement, the contribution of individual fishing behavior, willingness to change fishing behavior, community participation, catch recording, effectiveness of current regulations, fair access rights, and expected future benefits of the management approach.

latest_binary_profile_plot(
  latest_support_summary,
  title = "Support for community fisheries-management mechanisms remains high"
)

This latest-profile view is useful because a measure can remain substantively strong even if it does not increase from an already high baseline. It also shows an important distinction in the Honduras data: support for core management mechanisms remains strong even while trust in local decision-makers has weakened.

4.2 Economic conditions

The economic pillar combines a perceived adequacy measure with direct measures of reported income.

Measure Definition used in this brief
Financial sufficiency Share reporting that total household income covers household needs fairly easily, easily, or very easily. “With difficulty” and “with great difficulty” are unfavorable.
Real total monthly household income Mean reported household monthly income from all activities, including salaried and non-salaried labor, converted to constant 2024 HNL after midpoint imputation of historical income categories and outlier filtering.
Real artisanal-fishing income Among households reporting a positive artisanal-fishing income share, total real monthly household income multiplied by the reported percentage of income from artisanal fishing, with outlier filtering applied to the derived amount.

4.2.1 Honduras-wide change

financial_summary <- binary_summary %>%
  filter(indicator == "E1")

summary_change_plot(
  financial_summary,
  title = "Financial sufficiency: Honduras-wide change",
  subtitle = "Change in the share reporting that household income is sufficient to cover needs; 95% bootstrap intervals"
)

numeric_summary_plot(
  income_summary,
  title = "Reported real monthly income: Honduras-wide change"
)

Reported real total monthly household income changes by +17.4% under the All-ABM approach and +19.0% among matched communities.

Among households earning from artisanal fishing, real fishing-derived income changes by +48.6% and +37.8%, respectively.

These positive direct-income changes coexist with weaker financial sufficiency. The measures answer different questions: reported income measures how much households receive, while financial sufficiency asks whether that income is enough relative to household needs and costs.

4.2.2 Latest economic profile

To complement the change analysis, the latest profile shows the current level of financial sufficiency and the latest adequately sampled real-income estimates across ABMs.

latest_binary_profile_plot(
  latest_financial_summary,
  title = "Latest financial-sufficiency profile"
)

latest_numeric_profile_plot(
  latest_income_summary,
  title = "Latest reported real monthly income profile",
  subtitle = "Total household income and, separately, fishing income among households earning from artisanal fishing"
)

This current-status view helps avoid interpreting change without context: higher reported income does not necessarily imply that households currently feel financially secure.

4.3 Food security

Food security is assessed with three questions that capture recent availability, expected future access, and experienced worry.

Measure Definition used in this brief
Food availability Share rating the last year in terms of food availability as Good or Very good.
Confidence in future food procurement Share Confident or Very confident that the household will be able to procure enough food for the family during the next 12 months.
Food worry (IMEL Core) Share reporting that the statement “I worry about not having enough food for everyone in the household” was Never true during the previous 12 months.

4.3.1 Honduras-wide change

food_summary <- binary_summary %>%
  filter(indicator %in% c("F1", "F2", "F3")) %>%
  arrange(indicator)

summary_change_plot(
  food_summary,
  title = "Food security: Honduras-wide change"
)

The broader food-security picture is more encouraging than the Core food-worry item alone. Food availability changes by +9.7 pp across eligible ABMs and +13.8 pp among matched communities. Confidence in being able to procure enough food over the next 12 months changes by +10.3 pp and +28.9 pp, respectively.

The past-year food-worry measure does not necessarily move in the same direction, which is why the three questions are shown together rather than represented as a single ad hoc food-security index.

4.3.2 Latest food-security profile

latest_binary_profile_plot(
  latest_food_summary,
  title = "Latest food-security profile across adequately sampled ABMs"
)

The latest profile makes the current level of each food-security dimension visible alongside the before–after change. This is particularly important for the food-worry measure: relative stability can still coexist with a level of vulnerability that warrants continued attention.

5 Main takeaways and conclusion

Across the three pillars, the HHS points to several coherent positive changes rather than a single universally improving score.

Management and collective action: households report substantially stronger direct participation in fisheries management and more pro-compliance behavior, and support for core management mechanisms remains high. Trust in local decision-makers is the clearest concern.

Economic conditions: reported real total household income increases under both analytical approaches. Among households earning from artisanal fishing, real fishing-derived income also increases. These gains coexist with weaker perceived financial sufficiency, suggesting that income growth has not necessarily kept pace with household needs or perceived financial pressure.

Food security: households report stronger recent food availability and greater confidence in securing enough food in the coming year, including in the Matched-community comparison. The Core food-worry measure remains less positive, so the appropriate interpretation is one of encouraging food-resilience signals alongside continuing vulnerability.

Overall conclusion: The Honduras HHS shows a set of encouraging and mutually reinforcing before–after signals. The most compelling findings are those that persist when the same communities are compared over time: stronger engagement in fisheries management, improving reported real income, and positive movement in important food-security measures. These results do not establish causal impact, but they provide a credible picture of progress in several dimensions of community and household resilience while clearly identifying areas—especially trust and perceived financial sufficiency—where challenges remain.

6 Appendix

6.1 A. ABM-specific before–after changes

The Appendix retains the site-level detail so the main brief can stay focused on the Honduras-wide story. All ABM figures below are faceted by ABM, allowing the reader to see the set of changes within each site.

6.1.1 A.1 Management and collective action by ABM

management_abm_effects <- abm_effects %>%
  filter(indicator %in% paste0("M", 1:7)) %>%
  arrange(indicator)

abm_effect_plot(
  management_abm_effects,
  title = "Management and collective-action changes by ABM",
  ncol = 2
)

6.1.2 A.2 Economic changes by ABM

financial_abm_effects <- abm_effects %>%
  filter(indicator == "E1")

abm_effect_plot(
  financial_abm_effects,
  title = "Financial-sufficiency change by ABM",
  ncol = 2
)

income_abm_faceted_plot(
  income_abm_period_combined,
  title = "Reported real monthly income before and after, by ABM"
)

6.1.3 A.3 Food security by ABM

food_abm_effects <- abm_effects %>%
  filter(indicator %in% c("F1", "F2", "F3")) %>%
  arrange(indicator)

abm_effect_plot(
  food_abm_effects,
  title = "Food-security changes by ABM",
  ncol = 2
)

6.2 B. Complete ABM-level before–after results

6.2.1 B.1 Percentage-point HHS measures

all_abm_changes %>%
  filter(
    indicator %in% c(
      paste0("M", 1:7),
      "E1",
      "F1",
      "F2",
      "F3"
    )
  ) %>%
  arrange(domain, indicator, abm) %>%
  transmute(
    Pillar = domain,
    Measure = indicator_label,
    ABM = abm,
    `Before survey` = before_survey,
    `After survey` = after_survey,
    `n before` = n_before,
    `n after` = n_after,
    Before = fmt_pct(before),
    After = fmt_pct(after),
    Change = fmt_pp(change)
  ) %>%
  knitr::kable(
    caption = "Complete ABM-level before–after results for percentage-based HHS measures"
  )
Complete ABM-level before–after results for percentage-based HHS measures
Pillar Measure ABM Before survey After survey n before n after Before After Change
Economic conditions Income sufficient to cover household needs Guanaja 2019-2022 2024-2026 221 148 61% 38% -22.8 pp
Economic conditions Income sufficient to cover household needs Iriona and Limon 2019-2022 2024-2026 282 291 81% 64% -17.3 pp
Economic conditions Income sufficient to cover household needs Omoa 2019-2022 2024-2026 273 329 52% 22% -30.1 pp
Economic conditions Income sufficient to cover household needs Puerto Cortes 2019-2022 2024-2026 284 302 30% 16% -14.0 pp
Economic conditions Income sufficient to cover household needs Santa Fe 2019-2022 2024-2026 284 291 63% 23% -40.4 pp
Economic conditions Income sufficient to cover household needs Santa Rosa de Aguan 2019-2022 2024-2026 236 292 32% 17% -14.7 pp
Economic conditions Income sufficient to cover household needs Trujillo 2019-2022 2024-2026 260 295 26% 20% -5.4 pp
Food security Food availability good/very good Guanaja 2019-2022 2024-2026 220 148 40% 22% -18.4 pp
Food security Food availability good/very good Iriona and Limon 2019-2022 2024-2026 284 291 26% 58% +31.3 pp
Food security Food availability good/very good Omoa 2019-2022 2024-2026 273 329 16% 38% +21.2 pp
Food security Food availability good/very good Puerto Cortes 2019-2022 2024-2026 280 302 14% 16% +1.6 pp
Food security Food availability good/very good Santa Fe 2019-2022 2024-2026 281 291 33% 54% +21.2 pp
Food security Food availability good/very good Santa Rosa de Aguan 2019-2022 2024-2026 230 292 15% 24% +8.8 pp
Food security Food availability good/very good Trujillo 2019-2022 2024-2026 270 295 17% 19% +1.9 pp
Food security Confident can procure enough food next 12 months Guanaja 2019-2022 2024-2026 223 148 49% 64% +14.6 pp
Food security Confident can procure enough food next 12 months Iriona and Limon 2019-2022 2024-2026 286 291 50% 94% +44.2 pp
Food security Confident can procure enough food next 12 months Omoa 2019-2022 2024-2026 275 329 54% 50% -4.0 pp
Food security Confident can procure enough food next 12 months Puerto Cortes 2019-2022 2024-2026 284 302 57% 44% -13.7 pp
Food security Confident can procure enough food next 12 months Santa Fe 2019-2022 2024-2026 283 291 68% 61% -6.7 pp
Food security Confident can procure enough food next 12 months Santa Rosa de Aguan 2019-2022 2024-2026 239 292 21% 30% +8.9 pp
Food security Confident can procure enough food next 12 months Trujillo 2019-2022 2024-2026 271 295 27% 56% +29.0 pp
Food security Never worried about enough food Guanaja 2019-2022 2024-2026 219 148 44% 17% -27.4 pp
Food security Never worried about enough food Iriona and Limon 2019-2022 2024-2026 281 291 33% 21% -11.4 pp
Food security Never worried about enough food Omoa 2019-2022 2024-2026 275 329 9% 16% +6.4 pp
Food security Never worried about enough food Puerto Cortes 2019-2022 2024-2026 284 302 7% 13% +5.5 pp
Food security Never worried about enough food Santa Fe 2019-2022 2024-2026 281 291 26% 16% -9.8 pp
Food security Never worried about enough food Santa Rosa de Aguan 2019-2022 2024-2026 239 292 9% 7% -2.3 pp
Food security Never worried about enough food Trujillo 2019-2022 2024-2026 270 295 10% 16% +5.9 pp
Management & collective action Household attended management meeting (last month) Iriona and Limon 2019-2022 2024-2026 161 97 9% 49% +40.8 pp
Management & collective action Household attended management meeting (last month) Santa Fe 2019-2022 2024-2026 283 79 13% 84% +70.1 pp
Management & collective action Household attended management meeting (last month) Santa Rosa de Aguan 2019-2022 2024-2026 201 77 3% 83% +79.6 pp
Management & collective action Household attended management meeting (last month) Trujillo 2019-2022 2024-2026 270 68 31% 57% +26.6 pp
Management & collective action Household holds management leadership role Iriona and Limon 2019-2022 2024-2026 105 96 5% 17% +11.9 pp
Management & collective action Household holds management leadership role Santa Fe 2019-2022 2024-2026 284 81 5% 22% +17.3 pp
Management & collective action Household holds management leadership role Santa Rosa de Aguan 2019-2022 2024-2026 194 74 1% 82% +81.9 pp
Management & collective action Household holds management leadership role Trujillo 2019-2022 2024-2026 268 68 20% 12% -8.0 pp
Management & collective action Often encourages compliance with regulations Iriona and Limon 2019-2022 2024-2026 101 97 10% 37% +27.2 pp
Management & collective action Often encourages compliance with regulations Omoa 2019-2022 2024-2026 272 299 44% 53% +8.7 pp
Management & collective action Often encourages compliance with regulations Puerto Cortes 2019-2022 2024-2026 282 279 36% 33% -2.8 pp
Management & collective action Often encourages compliance with regulations Santa Fe 2019-2022 2024-2026 279 81 11% 52% +41.1 pp
Management & collective action Often encourages compliance with regulations Santa Rosa de Aguan 2019-2022 2024-2026 144 79 48% 16% -31.5 pp
Management & collective action Often encourages compliance with regulations Trujillo 2019-2022 2024-2026 244 69 19% 36% +17.4 pp
Management & collective action Community ability to manage fishery (collective efficacy) Guanaja 2019-2022 2024-2026 205 148 38% 5% -32.2 pp
Management & collective action Community ability to manage fishery (collective efficacy) Iriona and Limon 2019-2022 2024-2026 182 291 52% 41% -10.8 pp
Management & collective action Community ability to manage fishery (collective efficacy) Omoa 2019-2022 2024-2026 275 329 48% 55% +7.7 pp
Management & collective action Community ability to manage fishery (collective efficacy) Puerto Cortes 2019-2022 2024-2026 283 302 33% 25% -8.0 pp
Management & collective action Community ability to manage fishery (collective efficacy) Santa Fe 2019-2022 2024-2026 284 291 73% 42% -30.6 pp
Management & collective action Community ability to manage fishery (collective efficacy) Santa Rosa de Aguan 2019-2022 2024-2026 239 292 4% 35% +30.8 pp
Management & collective action Community ability to manage fishery (collective efficacy) Trujillo 2019-2022 2024-2026 270 295 29% 42% +13.1 pp
Management & collective action Expects management approach to benefit community Iriona and Limon 2019-2022 2024-2026 91 94 89% 90% +1.4 pp
Management & collective action Expects management approach to benefit community Santa Fe 2019-2022 2024-2026 283 81 96% 98% +1.4 pp
Management & collective action Expects management approach to benefit community Trujillo 2019-2022 2024-2026 266 65 39% 77% +38.2 pp
Management & collective action Access rights perceived as fair Iriona and Limon 2019-2022 2024-2026 92 79 82% 49% -32.2 pp
Management & collective action Access rights perceived as fair Omoa 2019-2022 2024-2026 169 291 85% 69% -15.5 pp
Management & collective action Access rights perceived as fair Puerto Cortes 2019-2022 2024-2026 145 279 88% 34% -53.5 pp
Management & collective action Access rights perceived as fair Santa Fe 2019-2022 2024-2026 141 81 81% 89% +8.0 pp
Management & collective action Access rights perceived as fair Santa Rosa de Aguan 2019-2022 2024-2026 187 97 6% 70% +63.7 pp
Management & collective action Access rights perceived as fair Trujillo 2019-2022 2024-2026 250 73 30% 74% +44.4 pp
Management & collective action Trust in local decision-makers Guanaja 2019-2022 2024-2026 226 148 31% 1% -29.6 pp
Management & collective action Trust in local decision-makers Iriona and Limon 2019-2022 2024-2026 286 291 69% 46% -23.5 pp
Management & collective action Trust in local decision-makers Omoa 2019-2022 2024-2026 275 329 73% 38% -35.2 pp
Management & collective action Trust in local decision-makers Puerto Cortes 2019-2022 2024-2026 284 302 83% 19% -64.6 pp
Management & collective action Trust in local decision-makers Santa Fe 2019-2022 2024-2026 284 291 30% 66% +36.0 pp
Management & collective action Trust in local decision-makers Santa Rosa de Aguan 2019-2022 2024-2026 239 292 11% 32% +20.9 pp
Management & collective action Trust in local decision-makers Trujillo 2019-2022 2024-2026 271 295 30% 31% +0.6 pp

6.2.2 B.2 Income measures

bind_rows(
  total_income_all_units,
  fishing_income_all_units
) %>%
  arrange(metric, abm) %>%
  transmute(
    Measure = metric,
    ABM = abm,
    `Before survey` = before_survey,
    `After survey` = after_survey,
    `n before` = n_before,
    `n after` = n_after,
    Before = fmt_hnl(before),
    After = fmt_hnl(after),
    Change = fmt_change_pct(pct_change)
  ) %>%
  knitr::kable(
    caption = "Complete ABM-level before–after results for real income measures"
  )
Complete ABM-level before–after results for real income measures
Measure ABM Before survey After survey n before n after Before After Change
Real artisanal-fishing income Iriona and Limon 2019-2022 2024-2026 199 92 HNL 1,815 HNL 1,895 +4.4%
Real artisanal-fishing income Omoa 2019-2022 2024-2026 163 292 HNL 3,603 HNL 4,959 +37.6%
Real artisanal-fishing income Puerto Cortes 2019-2022 2024-2026 142 273 HNL 2,938 HNL 4,720 +60.7%
Real artisanal-fishing income Santa Fe 2019-2022 2024-2026 134 72 HNL 2,091 HNL 3,949 +88.9%
Real artisanal-fishing income Santa Rosa de Aguan 2019-2022 2024-2026 219 124 HNL 2,481 HNL 3,713 +49.7%
Real artisanal-fishing income Trujillo 2019-2022 2024-2026 233 72 HNL 3,777 HNL 5,583 +47.8%
Real total monthly household income Guanaja 2019-2022 2024-2026 219 146 HNL 12,574 HNL 9,796 -22.1%
Real total monthly household income Iriona and Limon 2019-2022 2024-2026 282 288 HNL 4,813 HNL 6,098 +26.7%
Real total monthly household income Omoa 2019-2022 2024-2026 275 325 HNL 7,022 HNL 7,819 +11.3%
Real total monthly household income Puerto Cortes 2019-2022 2024-2026 282 298 HNL 6,486 HNL 6,428 -0.9%
Real total monthly household income Santa Fe 2019-2022 2024-2026 282 288 HNL 5,796 HNL 9,774 +68.7%
Real total monthly household income Santa Rosa de Aguan 2019-2022 2024-2026 239 289 HNL 4,030 HNL 7,974 +97.8%
Real total monthly household income Trujillo 2019-2022 2024-2026 265 292 HNL 8,137 HNL 9,461 +16.3% 
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