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REVIEW 4 major objections 5 minor 4 references

Effect of Insecurity on Agricultural Output in Benue State, Nigeria

T0 review · 4 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read This paper claims that insecurity, measured by farmer-reported conflict experiences, lowers agricultural output in Benue State: a one percent rise in insecurity is associated with a 0.211 percent drop in crop output and a 0.311 percent…

desk verdict The paper's headline elasticity is a misinterpretation of standardized SEM coefficients; the survey work is real but the design cannot support the causal claim. read the letter →

arxiv 2506.01525 v1 pith:NV24EJ4S submitted 2025-06-02 econ.GN q-fin.EC

classification econ.GNq-fin.EC
keywords InsecurityAgriculturaloutputCropLivestockBenueStateFarmer-herderconflictStructuralequationmodellingFoodsecurity
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper sets out to show that insecurity—farmer-herder conflict, banditry, killing, displacement, and destruction—is a measurable drag on agricultural output in Benue State, Nigeria. It reports evidence from 400 farmers in eight conflict-prone local government areas, comparing their recalled annual monetary crop and livestock output before and during insecurity. The paired t-tests show large nominal declines, and the structural equation model estimates that a one percent increase in the insecurity factor is associated with a 0.211 percent decrease in crop output and a 0.311 percent decrease in livestock output. The paper's practical point is that security policy and agricultural policy in Benue are inseparable.

What carries the argument

The load-bearing construct is a latent variable named Insecurity, measured by six Likert-scaled indicators: massive killing, destruction of homes and farmlands, frequent attacks, rising fatalities and injuries, forced displacement, and damage to agricultural land and livestock. A structural equation model with two outcome equations—crop output and livestock output—regresses each on Insecurity plus controls for access to agricultural credit, fertilizer availability, farm size, and pest prevalence. The model allows correlated errors among selected indicators to improve fit. The key numerical output is the standardized regression coefficient from Insecurity to each output, from which the paper reads its elasticity-style conclusion.

What would settle it

Compare the same recalled outputs with an inflation-adjusted series or with official agricultural production statistics for Benue over the same period; if the real value of crop and livestock output did not fall, or fell equally in non-conflict local government areas, the paper's attribution to insecurity would be falsified.

Watch

Extended reading notes

Core claim

Using a latent variable built from six survey indicators of insecurity, the paper claims to estimate direct negative effects on both crop and livestock output. In the structural equation model, the standardized path from Insecurity to crop output is -0.211 (p=0.001) and to livestock output is -0.311 (p=0.000), with reported fit indices mostly in acceptable ranges. The paired-samples t-tests are offered as supporting evidence: mean annual crop value fell from N200,770.50 to N124,298.50, and livestock value from N371,354.75 to N82,219.75, with both differences statistically significant at the 5% level. The authors conclude that insecurity displaces farmers, disrupts farming and market access, lowers incomes, and worsens food insecurity, and they recommend stronger rural security, grazing reserves, and ranch-based livestock policy.

Load-bearing premise

The argument rests on farmers accurately recalling their pre-conflict annual output in naira and on the assumption that no other force—weather, prices, inflation, or state policy—moved output downward at the same time.

Editorial extensions

If this is right

  • If insecurity depresses output by the estimated amounts, reducing conflict in Benue's rural local government areas should be treated as a direct agricultural productivity intervention, not just a law-and-order matter.
  • Continued insecurity can be expected to erode the state's food supply, since the sampled local government areas are core food-producing areas and the estimated losses hit both main output categories.
  • Input-focused programs such as credit, fertilizer, and farm-size support are unlikely to fully restore output while the insecurity pathway remains active.
  • Under the paper's estimates, livestock output is more sensitive to insecurity than crop output, so policy responses aimed at protecting livestock may have the larger marginal payoff.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: the paper's coefficients are associations between a latent perception factor and self-reported output, not necessarily causal effects of conflict events; a randomized or quasi-experimental design would be needed to confirm the causal reading.
  • Editorial inference: because the before-during comparison uses nominal recalled income with no price adjustment, part of the reported decline in naira values could reflect Nigeria's inflation rather than real output loss; deflating by a local price index would test this.
  • Editorial inference: a testable extension would be to link the same survey responses to geolocated conflict-event data or satellite measures of vegetation and nighttime lights, which would validate the latent insecurity measure against an objective benchmark.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper uses a survey of 400 farmers in eight LGAs of Benue State, Nigeria, to examine the effect of insecurity on agricultural output. It uses a paired t-test comparing recalled pre-conflict and during-conflict monetary values of crop and livestock output, and a SEM with a latent 'Insecurity' factor measured by six Likert items, regressing crop and livestock output on this factor and covariates. The authors report statistically significant declines and interpret standardized SEM coefficients as elasticities: a one percent increase in insecurity decreases crop and livestock output by 0.211% and 0.311%, respectively.

Significance. If the magnitude and causal interpretation were supported, the paper would provide useful policy evidence on a pressing issue. The data collection effort is notable, and the SEM fit indices are partially reported. However, the central quantitative claim is a misreading of standardized coefficients, and the measurement model includes an indicator that overlaps with the outcome, so the paper's headline results are not credible as stated. The qualitative finding of lower reported output during the conflict period is plausible but is not identified as a causal effect.

major comments (4)
  1. [Abstract and Results (Table 2)] The claim that 'a one percent increase in insecurity leads to a 0.211% and 0.311% decrease' is not supported by the analysis. Table 2 reports standardized SEM coefficients for CRP<---Insecurity (-0.211) and LVP<---Insecurity (-0.311). These are changes in SD units of the outcome per SD change in a latent variable whose scale is arbitrary (defined by fixing INS1 loading to 1). The model is not a log-log specification, and no percentage interpretation of the latent factor is given. The elasticity language should be removed or replaced by a statement about standardized associations.
  2. [Methodology, Equation 1 and INS items] The latent Insecurity factor includes INS6 ('Damage to agricultural lands and livestock caused by conflicts'), which directly overlaps with the outcome variables CRP and LVP (monetary value of crop and livestock output). This creates a mechanical association: respondents reporting damage to agricultural lands/livestock are likely the same as those reporting lower output. The SEM path from Insecurity to output is therefore partly a regression of output on an outcome-like indicator, undermining even the associational interpretation of the coefficient.
  3. [Methodology, paired t-test] The before-during comparison is based on retrospectively recalled annual monetary values of output, with no control group, no baseline records, and no adjustment for inflation, weather, prices, or other contemporaneous shocks. The statistically significant decline cannot be attributed to insecurity; it is consistent with many alternative explanations. The paper should acknowledge this identification limitation and avoid causal language.
  4. [Results and Discussion (text after Table 2)] The discussion contradicts the estimates in Table 2. The text states that 'only the effect of farm size on crop production is significant,' but Table 2 shows ACAC (P=0.002) and AVF (P=0.001) are also significant for CRP. For livestock, the text states all four predictors are positive and significant, but FSIZ (P=0.186) and PP (P=0.794) are not significant. These discrepancies need to be corrected.
minor comments (5)
  1. [Table 1] Table 1 presents means as N200,770.50 etc., but the table header says 'Annual Monetary Value' with categories; clarify the units and whether means are computed from category midpoints.
  2. [Abstract] In the abstract, 't tests' should be 't-tests' for consistency.
  3. [Figure 1] Figure 1 is referenced but not included in the text; provide the figure or remove the reference.
  4. [Results and Discussion (model fit)] The SEM fit discussion notes RFI=0.871 and TLI=0.879 are below acceptable thresholds; this should be acknowledged as a model fit concern, not merely 'could be improved.'
  5. [Literature Review] The literature review cites Saad (2024) as finding a positive correlation between insecurity and agricultural production; this is surprising and should be explained.

Circularity Check

1 steps flagged · score 6.0 of 10

The SEM effect is partly circular: the latent insecurity factor includes INS6 (damage to agricultural lands and livestock) and INS2 (destruction of farmlands), so the negative paths to crop and livestock output are partly mechanical.

  1. self definitional [Methodology (Equations 1–2, latent-variable indicators) and Results (Table 2)]
    "The latent variable "Insecurity" is measured by six indicators ... INS2: Massive destruction of homes and farmlands. ... INS6: Damage to agricultural lands and livestock caused by conflicts. ... LVP<---Insecurity -0.394 -0.311 ... CRP<---Insecurity -0.285 -0.211"

    The latent predictor Insecurity is defined partly by self-reported damage to farmlands (INS2) and to agricultural lands and livestock (INS6). These indicators are outcome-like: crop output is measured as the monetary value of crop outputs, and livestock output as the monetary value of livestock outputs, so destruction of farmlands and damage to livestock is the same construct as reduced agricultural output rather than an independent cause. The SEM then 'finds' negative standardized coefficients from Insecurity to CRP (-0.211) and LVP (-0.311). Part of that association is forced by construction, because the predictor contains items that already describe the outcome.

full rationale

The paper's central derivation is not fully self-contained: one load-bearing step reduces to its own input. The latent variable Insecurity is measured by six Likert indicators, and two of them (INS2, INS6) directly describe destruction of farmlands and damage to agricultural lands and livestock. Since the outcomes CRP and LVP are monetary values of crop and livestock output, regressing those outcomes on a factor partly composed of output-damage reports is partly a tautology. This is the main circular element; it affects the effect-size claims in Table 2 and the abstract. The before/during paired t-test is a genuine comparison and does not suffer from this same construct overlap, so the qualitative conclusion that output declined is not wholly circular. I do not treat the 'one percent increase' elasticity wording as circularity: it is a separate statistical misinterpretation of standardized coefficients, not a reduction to inputs. Self-citations (e.g., Ijirshar, Ker & Terlumun 2015) are used only as corroboration, not as load-bearing derivation, so they do not raise the score further. Overall: partial circularity in the SEM path due to outcome-like indicators in the predictor, score 6.

Assumptions & free parameters 4 free parameters · 5 assumptions · 1 invented entities

The paper's central claim rests on a latent-factor SEM and a recall-based t-test. The latent insecurity factor is built from six indicators collected in the same survey, two of which describe destruction of farmlands and damage to agricultural lands and livestock, creating overlap with the outcome. All coefficients are fitted to the survey data, and no external or longitudinal data are used.

free parameters (4)
  • Latent factor loadings INS1-INS6 = 0.984, 0.776, 0.987, 0.906, 0.969, 0.970 (standardized)
    Define the latent insecurity factor; these weights are fitted to the same survey data.
  • SEM path coefficient, Insecurity to CRP = -0.211
    Fitted standardized coefficient; presented as an elasticity despite not being one.
  • SEM path coefficient, Insecurity to LVP = -0.311
    Fitted standardized coefficient; presented as an elasticity despite not being one.
  • Error covariances e2-e4 and e5-e6 = estimated
    Added post hoc to improve model fit; no theoretical basis beyond shared variance.
assumptions (5)
  • domain assumption Farmers' recalled pre-insecurity output values are accurate and comparable to current values.
    No baseline data, no administrative records; the paired t-test depends on this.
  • ad hoc to paper The latent insecurity factor constructed from six Likert items has a meaningful continuous scale with percentage-like units.
    The standardized latent factor has arbitrary units; the elasticity interpretation requires a defined percentage scale.
  • domain assumption The eight purposively selected LGAs represent the farming population of Benue State, and the 440-person sample is representative.
    Purposive sampling from insecurity-prone areas only; there is no unaffected comparison group.
  • standard math Normality and homogeneity of variances hold for the paired t-test.
    Assumptions are asserted as checked, but test statistics for the checks are not shown.
  • domain assumption The SEM specification includes all relevant confounders.
    The model omits inflation, prices, weather, conflict duration, and government security responses; omitted variables could bias the path coefficients.
invented entities (1)
  • Latent 'Insecurity' factor
    purpose: To summarize six conflict-perception Likert indicators into a single predictor of crop and livestock output.
    The factor is defined entirely by the authors' six survey items; it has no external benchmark and no defined unit, and two indicators overlap with the outcome (destruction of farmland, damage to crops and livestock).

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Cite this review

Pith. "Pith review of Effect of Insecurity on Agricultural Output in Benue State, Nigeria." pith.science (2026). https://pith.science/paper/NV24EJ4S

@misc{pith2026250601525,
  author       = {Pith},
  title        = {Pith review of: Effect of Insecurity on Agricultural Output in Benue State, Nigeria},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NV24EJ4S}},
  note         = {Machine review of arXiv:2506.01525}
}
read the original abstract

This study examined the effect of insecurity on agricultural output in Benue state. A descriptive survey design was employed, and 400 respondents were purposively selected from insecurity-prone local government areas, namely, Guma LGA, Agatu LGA, Gwer LGA, Gwer-West LGA, Katsina-Ala LGA, Logo LGA, Ukum LGA and Kwande LGA. The data were collected through the administration of a questionnaire and were analysed using t tests and structural equation modelling (SEM). The t-test was used to compare farmers' incomes before and after the insecurity in the study area to assess if the differences were statistically significant, while Structural Equation Modelling analysed the complex relationships among multiple variables, employing regression and factor analysis to model both direct and indirect effects. The results revealed that the monetary value of crop and livestock output decreased during periods of insecurity. Furthermore, the study showed that insecurity has an adverse effect on crop and livestock output. This means that a one percent increase in insecurity leads to a 0.211% and 0.311% decrease in crop and livestock output respectively. The study concluded that insecurity reduced agricultural output in Benue state. Based on the findings, it was recommended that the government deploy more security personnel, establish community policing initiatives, and employ modern surveillance technologies to deter criminal activities in insecure areas. Additionally, for places experiencing farmer-herder conflict, the government should provide grazing reserves for herdsmen and further strengthen the state law on open grazing prohibition and the establishment of ranch law.

Figures

Figures reproduced from arXiv: 2506.01525 by the authors.

Figure 1
Figure 1. SEM Model for Estimating the Effect of Insecurity on Agricultural Output. In the confirmatory analysis of the latent variable Insecurity (INS), additional covariance relationships were introduced to improve the model's fit and enhance its explanatory power. Specifically, covariance was allowed between the error terms e2 and e4, as well as between e5 and e6. These covariances reflect correlations between the measurem… view at source ↗

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Reference graph

Works this paper leans on

4 extracted references · 4 canonical work pages

  1. [1]

    The Effect of Land Conflict on Rice Production in Agatu Local Government Area of Benue State

    Abah, D., O. C. Ochoche, and J. I. Stephen. "The Effect of Land Conflict on Rice Production in Agatu Local Government Area of Benue State." International Journal of Agricultural Economics, Management and Development, 2022, 218–33. Abubakar, A. A. "The Effects of Insecurity on Agricultural Output in Nigeria." In Proceedings of the 1st International Confere...

  2. [2015]

    Herdsmen Attacks and Agricultural Productivity in Benue and Nasarawa States of Nigeria

    Musa, M. J., H. Salami, and A. F. Umoru. "Herdsmen Attacks and Agricultural Productivity in Benue and Nasarawa States of Nigeria." Al-Hikmah University Central Journal 3, no. 1 (2022): 13–24. Nomor, D. T., and F. I. Ikyoyer. "The Impact of the Herdsmen -Crop Farmers Conflict on the Productivity of Yam Farmers in Logo Local Government Area of Benue State."...

  3. [2017]

    The Effects of Insecurity on Agricultural Productivity in Nigeria

    Eneji, M. A., B . Babangario, and G. E. Agri. "The Effects of Insecurity on Agricultural Productivity in Nigeria." Sumerians Journal of Management and Marketing 2, no. 6 (2020): 59–69. Ewetan, O. O., and E. Urhie. "Insecurity and Socio -economic Development in Nigeria." Journal of Sustainable Development Studies 5, no. 1 (2014): 40–63. Food and Agricultur...

  4. [2021]

    Socio -economic Effects of Farmers -Fulani Herdsmen’s Conflict on Farmers Output in Benue, Niger ia

    https://doi.org/10.4060/cb4474en. Ijirshar, V. U., G. Ker, and T. C. Yange. "Socio -economic Effects of Farmers -Fulani Herdsmen’s Conflict on Farmers Output in Benue, Niger ia." In Proceedings of an International Academic Conference of the International Multidisciplinary Research and Academic Society, edited by F. S. Bakpo and F. E. Ugbeda. Obudu, Cross ...

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Reviewed August 7, 2026 · model on record in the stance chip above.