Economic and Financial Performance of Smallholder Dairy Farms in the Mexican Highlands: Prospective to 2033

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for the opportunity to review your manuscript. The paper addresses an important topic and provides a valuable prospective analysis of the economic and financial performance of smallholder dairy farms in Mexico. However, I believe the contribution can be strengthened with several improvements:

1. The first time the term “NPV” appears in the document, it should be defined explicitly. In the abstract, all other technical terms (e.g., RSDFs, ROA, etc.) are introduced with their full names before the abbreviation, but “NPV” is not. For clarity and consistency, please spell out Net Present Value (NPV) at its first occurrence.
2. The manuscript presents a broad and comprehensive bibliography; however, the discussion section would benefit from a deeper engagement with region-specific literature and from addressing core interpretative questions that remain insufficiently explored. In particular, the discussion should elaborate on: (i) the practical importance of the study’s results, (ii) how these findings compare with similar studies in terms of productivity and economic performance, and (iii) how the projected indicators could inform rural development plans, policy design, or strategic programs aimed at supporting small-scale dairy producers in Mexico.

While the bibliography includes many international references, several of these studies operate under climatic, technological, and socio-productive conditions that are not fully comparable to the Mexican Highlands. Strengthening the discussion with literature focused specifically on Mexican livestock systems would add contextual relevance and allow for more meaningful comparisons. Examples include:

• Estrategias de vida del productor agropecuario en zonas periurbanas (Rangel Quintos et al.)
• A methodological approach to evaluate livestock innovations on small-scale farms in developing countries (García-Martínez et al., Future Internet 8(2), 25)
• Does gender impact technology adoption in dual-purpose cattle in Mexico? (Villarroel-Molina et al., Animals 12(22), 3194)

Incorporating these works would strengthen the contextualization of your results and help answer key questions about the relevance, comparability, and practical applicability of your findings for smallholder dairy development in Mexico.

3. In Section 2.5 (Model assumptions), the assumption that “no change in technology occurs during the 2023–2033 horizon” requires stronger justification. Although technological adoption among smallholder dairy farms in Mexico can be slow, it is rarely entirely static over a 10-year period.

To strengthen the methodological foundation, it would be helpful to explain the rationale for assuming completely static technology, whether this is supported by historical evidence, structural constraints faced by smallholders, etc. A clearer justification in Section 2.5 would enhance transparency and credibility.

Overall, this is a valuable and well-executed study that can make a meaningful contribution after revisions aimed at improving clarity, terminology accuracy, and focus. I encourage the authors to consider the points above to strengthen the manuscript.

Comments on the Quality of English Language

The manuscript is generally well written and understandable, but several sections would benefit from language polishing to improve clarity and precision. Some expressions sound non-standard in academic English (e.g., “Total Receipts,” “may erode profitability”), and certain sentences are overly long or repetitive. A careful proofreading is recommended to ensure consistent terminology, correct use of financial vocabulary, and smoother phrasing throughout the text. Overall, the English quality is good but requires moderate editing.

Author Response

Reviewer comment 1: The first time the term “NPV” appears in the document, it should be defined explicitly. In the abstract, all other technical terms (e.g., RSDFs, ROA, etc.) are introduced with their full names before the abbreviation, but “NPV” is not. For clarity and consistency, please spell out Net Present Value (NPV) at its first occurrence.

Response 1: Thank you for this helpful observation. We have revised the abstract to spell out Net Present Value (NPV) at its first occurrence, ensuring consistency.

Reviewer comment 2: The manuscript presents a broad and comprehensive bibliography; however, the discussion section would benefit from a deeper engagement with region-specific literature and from addressing core interpretative questions that remain insufficiently explored. In particular, the discussion should elaborate on: (i) the practical importance of the study’s results, (ii) how these findings compare with similar studies in terms of productivity and economic performance, and (iii) how the projected indicators could inform rural development plans, policy design, or strategic programs aimed at supporting small-scale dairy producers in Mexico.

Response 2: This is a good comment, thanks for contributing. We have significantly revised the Discussion to (i) clarify how policy relevant are the projected economic and financial indicators for smallholder dairy households, (ii) contrast our productivity and profitability findings with those reported in recent work related to small-scale dairy systems in Mexico and other Latin American contexts, and (iii) detail how these different risk and viability profiles of both the RSDF type have humble implications for rural development strategy formulation, policy design and targeting of support programs for smallholders' dairy farmers. These also involve additional region-specific literature and new paragraphs in the Discussion that cover some of the interpretative points you bring up.

2.) How these findings compare with similar studies in terms of productivity and economic performance
“In relative terms, the overall economic performance of the RSDFs is comparable to, and in some cases better than, that reported for similar systems in central Mexico and other smallholder dairy settings. Previous work in the Mexican highlands reports that low input dairy production systems supply about 33% of total milk but face high feeding costs, with profitability depending on the efficient use of home-grown forages and carefully managed purchases of grain (Martínez-García et al., 2015).
Margin-over-feed-cost analysis and Monte Carlo simulation results indicate that smallholder dairy farms can obtain acceptable milk yields and positive gross margins when the components of their diets are based on quality on-farm feed, while systems that depend largely on purchased feed or fully hired labor tend to display negative NPV and greater risk of decapitalization (Posadas-Domínguez et al. 2016). Our estimated ROA values (11.5–21.8%) lie at the upper end of those reported for dairy farming worldwide and approach the upper limit of family labor contributions to profitability documented for small scale dairy systems in central Mexico (Martínez-García et al., 2015). However, despite the widespread presence and socio-economic contributions of small-scale dairy operations, a significant portion of these farms struggle with economic viability, often remaining below or precariously close to poverty thresholds (Pachura, 2011, p. 243). Globally, approximately 85% of milk-producing families in developing nations operate within small-scale systems, highlighting milk's crucial role as a consistent income source and a means to enhance food security and nutrition (Pérez et al., 2022). Nevertheless, within this widespread sector, only a subset of these farms achieves income levels substantially above poverty lines, while a considerable number remain vulnerable due to factors such as low technological adoption, limited productivity, and reliance on external inputs (Carrillo-Hernández et al., 2021; Pérez et al., 2021).”

3.) How the projected indicators could inform rural development plans, policy design, or strategic programs aimed at supporting small-scale dairy producers in Mexico
“The percentile-based estimates of NCFI, ROA, cash reserves and NPV produced in this research provide an applied tool for the design of rural development strategies and support programs targeted to smallholder dairy farmers in Mexico. By distinguishing conservative and aspirational scenarios (for example, the 10th versus the 90th percentile) for liquidity and profitability, these results can be used to set minimum cash reserve requirements for credit programs, benchmarking flat fee levels and coverage triggers for margin insurance products, or targeting technical assistance to farms with projected indicators placing them at greater risk of decapitalization. Consistent with other analyses that position small scale dairying as a poverty focused, food secure priority sector (Banda et al. 2021), the evidence of this study also supports policies that strengthen family dairies through extension services, forage technologies and collective marketing, rather than through indiscriminate input subsidies (Hemming et al., 2018).”

Reviewer comment 3: While the bibliography includes many international references, several of these studies operate under climatic, technological, and socio-productive conditions that are not fully comparable to the Mexican Highlands. Strengthening the discussion with literature focused specifically on Mexican livestock systems would add contextual relevance and allow for more meaningful comparisons. Examples include:
Estrategias de vida del productor agropecuario en zonas periurbanas (Rangel Quintos et al.)
A methodological approach to evaluate livestock innovations on small-scale farms in developing countries (García-Martínez et al., Future Internet 8(2), 25).

Response 3: We appreciate this suggestion and have revised the Discussion to engage more directly with literature on Mexican livestock systems.
“These trends are consistent with evidence from peri urban livestock producers in the Mexican Highlands, where dairy production is combined with crop production and off farm activities as part of diversified livelihood strategies that reduce exposure to price volatility and fluctuations in productivity and help sustain farm viability in increasingly urbanized landscapes (Rangel Quintos, 2001). Likewise, using data from 1,650 small scale livestock farms in Mexico, García-Martínez et al. (2016) demonstrate that the economic performance of these systems is highly dependent on adoption of new management, feeding, genetic, reproduction and animal health practices although overall innovation remains low and varies substantially. Placed in this context, the RSDF results of this study illustrate how contrasting labor arrangements and crop–livestock integration give rise to distinct innovation patterns and economic trajectories, with family based, pasture reliant farms better positioned to maintain positive cash flow and avoid decapitalization than farms that depend heavily on purchased inputs and hired labor (Rangel Quintos, 2001; García-Martínez et al., 2016).”

Reviewer comment 4: Does gender impact technology adoption in dual-purpose cattle in Mexico? (Villarroel-Molina et al., Animals 12(22), 3194)
Incorporating these works would strengthen the contextualization of your results and help answer key questions about the relevance, comparability, and practical applicability of your findings for smallholder dairy development in Mexico.

Response 4: Dear reviewer, we appreciate your valuable suggestion; however, since our study does not contemplate such depth of analysis, we consider it unnecessary to include it.

Reviewer comment 5: In Section 2.5 (Model assumptions), the assumption that “no change in technology occurs during the 2023–2033 horizon” requires stronger justification. Although technological adoption among smallholder dairy farms in Mexico can be slow, it is rarely entirely static over a 10-year period. To strengthen the methodological foundation, it would be helpful to explain the rationale for assuming completely static technology, whether this is supported by historical evidence, structural constraints faced by smallholders, etc. A clearer justification in Section 2.5 would enhance transparency and credibility.

Response 5: Thank you for this important observation. We agree that the assumption of static technology over the 2024–2033 horizon requires clearer justification.
Technology was unchanged throughout 2024–2033. The RSDFs were designed to resemble low-input, hand-milking dairy systems with small herds, rudimentary housing and minimal use of mechanization. This technological profile has been maintained for the last ten years according to farm interviews and field reports in the Highlands of Texcoco. Under comparable conditions in other parts of central Mexico, small dairy producers have been found to adopt superior grass management, feeding and animal husbandry practices only slowly and incompletely. Adoption is low also due to several factors, such as small herd size, narrow profit margins, lack of access to credit and advisory support systems, and a general aversion to risk when it comes to large investment (Martínez-García et al. 2013). In addition, a large proportion of micro dual-purpose cattle farms and other livestock systems in Mexico maintain management with basic technical input and low levels of technology adoption (Villarroel-Molina et al. 2021). Against this background, the assumption of virtually no net new structural technology changes over a ten-year horizon represents a conservative benchmark. Although changes in managerial behaviour are implicitly incorporated as part of economic variables’ stochastic processes, radical changes in housing, milking or feeding technologies are not a subject of current model and their explicit exploration within technology adoption scenarios is suggested for further research.

Reviewer comment 6: The manuscript is generally well written and understandable, but several sections would benefit from language polishing to improve clarity and precision. Some expressions sound non-standard in academic English (e.g., “Total Receipts “may erode profitability”), and certain sentences are overly long or repetitive. A careful proofreading is recommended to ensure consistent terminology, correct use of financial vocabulary, and smoother phrasing throughout the text. Overall, the English quality is good but requires moderate editing.

Response 6: Dear Reviewer, thank you for this valuable comment. We have replaced the term “Total receipts” with “Total income” throughout the manuscript and have also revised and polished the wording of the document.

Reviewer 2 Report

Comments and Suggestions for Authors

Comments and suggestions for authors

Emphasise originality – it is worth highlighting more clearly how the study differs from previous economic and simulation analyses in the dairy sector.

Reduce repetition – reduce overlap between the results and discussion.

Indicate limitations – state explicitly that the small number of RSDFs (n=5) limits the possibility of fully generalising the results.

Check the formatting of tables and graphs – ensure consistency in the recording of numerical values.

Author Response

Reviewer comment 1: Emphasise originality – it is worth highlighting more clearly how the study differs from previous economic and simulation analyses in the dairy sector.

Response 1: Thank you for this helpful observation. We agree that the originality of the study should be stated more explicitly. In the revised version, we now highlight in our work that (i) it develops a stochastic, 10-year financial and economic simulation specifically for representative smallholder dairy farms in the Mexican Highlands, rather than for medium or large commercial herds; (ii) contrasts two clearly defined labor and marketing configurations (family-labor-only, milk-only systems versus farms combining hired labor with crop and by-product sales) and quantifies their differentiated risk of decapitalization; and (iii) uses percentile-based indicators of NCFI, ROA, cash reserves and NPV to characterize liquidity and decapitalization risk, instead of relying solely on point estimates. To our knowledge, this combination of representative farm modelling, long-run stochastic simulation and explicit focus on family labor and decapitalization risk has not been previously applied to smallholder dairy systems in Mexico, and we now state this contribution more clearly in the manuscript.
“This analysis makes three main contributions to the dairy economics literature. First, it develops a stochastic simulation framework to evaluate the economic and financial performance of Representative Smallholder Dairy Farms in the Mexican Highlands, a segment that remains poorly documented compared with medium and large commercial herds. Second, it explicitly compares two distinct labor and marketing configurations, namely family labor with milk only systems and farms that combine hired labor with sales of crops and by products, and it quantifies their differing decapitalization risks over a ten-year horizon. Third, it uses percentile trajectories of NCFI, ROA, cash reserves and output value to describe income variability, liquidity and capital dynamics, providing a more nuanced representation of risk than conventional point estimates.”

Reviewer comment 2: Reduce repetition – reduce overlap between the results and discussion.

Response 2: Dear reviewer, thanks for your helpful observation. We have revised and polished the wording of the document to reduce repetition.

Reviewer comment 3: Indicate limitations – state explicitly that the small number of RSDFs (n=5) limits the possibility of fully generalizing the results.

Response 3: Dear reviewer, thanks for your helpful observation. We have included the following paragraph of limitations of the study: “The following limitations should be considered when interpreting these findings. First, the analysis is based on only five Representative Smallholder Dairy Farms (RSDFs), which were carefully designed to reproduce the size, structure and management of typical small scale dairy systems in the Texcoco Highlands, but cannot fully represent the diversity of smallholder dairies across Mexico; accordingly, the results should be seen as indicative for these representative farm types rather than applicable to all producers. Second, the RSDFs were defined under current low input technology and small herd sizes, assuming no major changes in technological efficiency or herd structure during 2024–2033, whereas actual trajectories may differ if farmers adopt new technologies, adjust herd size or modify land use. Third, the stochastic simulation relies on empirical distributions estimated from historical data, so extreme future macroeconomic or policy conditions outside this experience could alter the relative risk profiles reported here. Finally, the study focuses on economic and financial outcomes at farm level and does not explicitly examine environmental impacts, gender relations or value chain dynamics, which should be addressed in future research to provide a more comprehensive assessment of smallholder dairy sustainability.”

Reviewer comment 4: Check the formatting of tables and graphs – ensure consistency in the recording of numerical values.

Response 4: Thank you for this comment. We have carefully reviewed all tables and figures, converted all monetary values to USD thousand, and harmonized the formatting of numerical values to ensure consistency throughout the manuscript.

Reviewer comment 5: Emphasise originality – it is worth highlighting more clearly how the study differs from previous economic and simulation analyses in the dairy sector.

Response 5:  In Mexico, the effect of diversified activities on milk production had not been analyzed; there were no studies observing the impact of diversification on the economic outcomes of dairy farms. The prospective aspect is the novelty of this work, where we examine the risk factor. It is essential to understand the distribution of the variable in order to conduct a prospective analysis. In order to take into account your valuable comment we have incorporated the following paragraph to the discussion section:
“This analysis makes three main contributions to the dairy economics literature. First, it develops a stochastic simulation framework to evaluate the economic and financial performance of Representative Smallholder Dairy Farms in the Mexican Highlands, a segment that remains poorly documented compared with medium and large commercial herds. Second, it explicitly compares two distinct labor and marketing configurations, namely family labor with milk only systems and farms that combine hired labor with sales of crops and by products, and it quantifies their differing decapitalization risks over a ten-year horizon. Third, it uses percentile trajectories of NCFI, ROA, cash reserves and output value to describe income variability, liquidity and capital dynamics, providing a more nuanced representation of risk than conventional point estimates.”

 

Reviewer 3 Report

Comments and Suggestions for Authors

1. On page 3, the author explicitly puts forward the hypothesis: "There is no difference in economic and financial feasibility among different labor force structures and diversification states" (line 96). However, in the conclusion section (page 16, lines 659-661), it is concluded that "family labor force is crucial for economic and financial resilience, and diversified farms achieve higher net cash income." This means that the research results directly deny its null hypothesis. This logical contradiction indicates that the author did not conduct any hypothesis testing or significance analysis, but merely drew the conclusion based on descriptive comparison, which violates the basic norms of scientific reasoning.
2. On pages 4 and 5, the model assumes that the technical coefficient, scale, price and policy will remain unchanged from 2024 to 2033 (lines 185-189), but uses the "multivariate empirical distribution of 44-year historical data" to predict macroeconomic variables for the next ten years (lines 124-130). That is, while the assumption remains unchanged, macro fluctuations are introduced. This setting is logically contradictory, making the simulation results neither dynamic analysis nor steady-state equilibrium analysis, thus losing economic significance. Meanwhile, Table 2 (page 9) shows that the cost-benefit ratio of RSDF 1 is 0.61, but it is interpreted in the text as "still economically viable on a cost-benefit basis" (lines 288-291), and it is stated that "the benefit is 64% higher than the break-even point". In fact, if C/B < 1, the cost exceeds the benefit, and the project is not economically feasible. The author's explanation completely misinterpreted the meaning of the indicators, which constitutes a serious contradiction between quantitative results and qualitative expressions.
3. In Table 1 (page 5), there is an obvious error in the numerical column of "Total receipts (TR)" : the 2023 value of RSDF 1 is "$17.82 -$28.29, $19.58..." That is, negative signs and incorrect formats appear; Furthermore, the units of all financial variables are chaotic. Some are expressed in thousands of US dollars, while others are expressed in US dollars (as shown in Figure 1, "USD thousand" is used in parallel with "USD" in Table 1), and the currency conversion year is not specified. Non-standard data processing seriously affects repeatability and the credibility of results. The NCFI distribution shown in Figures 1 (page 7) and 2 (page 8) is inconsistent with the description in the main text. For instance, the author claims in lines 256-270 that RSDF 1 and RSDF 2 tend to decline in 2033. However, the curve in the graph shows a gentle upward trend, and RSDF 3 has an unreasonable peak area in the probability distribution (14.5-18.5 thousand US dollars), which is inconsistent with the result in Table 1 that it only increases to 15.32 US dollars. This indicates that the simulation process has not undergone internal consistency verification, or that different samples or time intervals were used for chart drawing.
4. On page 9, lines 311-320, the author compares the differences in net income with or without inclusion in household labor costs, noting that the net income of RSDF 1 decreased from $8,432 to -$1,414. However, on line 317 of the same page, it is stated that "the difference is $9,847", which does not match the difference between the aforementioned two values (it should be $9,846.77). At the same time, the same value is repeatedly presented for the differences between RSDF 2 and RSDF 3 (both being $9,847), clearly indicating mechanical copying or calculation errors. This indicates that the author did not actually conduct the difference calculation, and the result lacks credibility.
5. This paper simultaneously uses NPV, IRR, ROA, and C/B as feasibility indicators in multiple places (pages 8-9, 14, and 16), but the authors have not set a unified judgment threshold. For instance, the NPV of RSDF 5 is negative (-$41,822.93), the IRR is only 6%, and the C/B ratio is 1.17, yet it is defined as "economically unfeasible". In contrast, the NPV of RSDF 1 is lower than the initial assets, the C/B ratio is 0.61, and the IRR is 14%, yet it is regarded as "feasible". Under the same indicator system, the standards are inconsistent, and the assessment results lack logical consistency and objective basis. According to the author's statement in line 125, the simulation uses macro data from 1980 to 2024 for a 10-year prediction. However, in the results on page 5, the Ending Cash Reserves (ECR) of all RSDFS increased by more than tenfold over a decade (such as RSDF 1 from $16.22 to $324.18), significantly higher than the average nominal growth rate of the Mexican agricultural sector. The author failed to explain this abnormal growth and did not take into account the realistic constraints of inflation, exchange rates, climate risks or market fluctuations, resulting in distorted model predictions and a lack of economic rationality.

Best wishes,

Author Response

Reviewer comment 1: On page 3, the author explicitly puts forward the hypothesis: "There is no difference in economic and financial feasibility among different labor force structures and diversification states" (line 96). However, in the conclusion section (page 16, lines 659-661), it is concluded that "family labor force is crucial for economic and financial resilience, and diversified farms achieve higher net cash income." This means that the research results directly deny its null hypothesis. This logical contradiction indicates that the author did not conduct any hypothesis testing or significance analysis, but merely drew the conclusion based on descriptive comparison, which violates the basic norms of scientific reasoning.

Response 1: Thank you for this thoughtful comment. We agree that, as originally phrased, the hypothesis on page 3 may give the impression that no formal “testing” was carried out and that the conclusion contradicts an accepted null. Our intention, however, was to formulate a working null hypothesis against the theoretical background that highlights the advantages of diversification and the flexibility of family labor. In the revised manuscript, we reformulate this as follows:
“The hypothesis states that RSDFs that depend on family labor and have diversified sources of income suffer lower levels of economic and financial risk—assessed by expected net cash income, the probability of decapitalization, return on assets, and NPV—relatively to their counterparts for whom paid labor is dominant in a less diverse structure of income.”
The empirical strategy does not rely on traditional parametric hypothesis tests with p values, but on a risk assessment approach using Monte Carlo simulation. Net present value (NPV), net cash farm income (NCFI), return on assets (ROA) and cash reserves are projected over a ten-year horizon under alternative scenarios (with and without hired labor), and the simulated distributions of these indicators are then compared across RSDFs. In practical terms, the relative attractiveness of one scenario over another is evaluated by examining the full distribution of outcomes (for example, percentiles, interquartile ranges and the probability of negative NPV or NCFI) and by identifying cases of stochastic dominance between RSDFs with and without family labor.

Reviewer comment 2: On pages 4 and 5, the model assumes that the technical coefficient, scale, price and policy will remain unchanged from 2024 to 2033 (lines 185-189), but uses the "multivariate empirical distribution of 44-year historical data" to predict macroeconomic variables for the next ten years (lines 124-130). That is, while the assumption remains unchanged, macro fluctuations are introduced. This setting is logically contradictory, making the simulation results neither dynamic analysis nor steady-state equilibrium analysis, thus losing economic significance.

Response 2: The potential disassociation between the performance of small-scale farms and broader macroeconomic indicators presents a critical area for economic inquiry, particularly given the prevalence of such agricultural units globally. While some literature explores the significant role of smallholders in shaping national economic landscapes (Ableeva et al., 2019), a subset of academic discourse suggests a limited or negligible direct causal link between the output or economic health of individual small-scale farming operations and aggregate macroeconomic performance (Meyers, 1987). This perspective often arises from the recognition that official GDP figures may not accurately capture the economic contributions of numerous, often informal, small-scale agricultural activities (Brockington et al., 2018). Furthermore, some studies indicate that even robust macroeconomic growth, exemplified by increases in national GNP, may exert minimal influence on farm income, suggesting a decoupled relationship (Belongia & Gilbert, 1987). This divergence can be attributed to the inherent complexities of agricultural production, which often operates under distinct economic principles compared to other sectors (Souza et al., 2024). Indeed, research has indicated that certain macroeconomic disturbances, despite their broad impact, do not significantly influence farm income, particularly for smaller agricultural enterprises (Belongia & Gilbert, 1987). This incongruity can be further understood by examining the localized and often subsistence-oriented nature of many small-scale farming operations, which may buffer them from wider economic fluctuations (Mbatha & Masuku, 2018). This phenomenon is especially pronounced in regions where agricultural activities are heavily diversified or where small-scale farming constitutes a relatively minor component of the overall state economy (Belongia & Gilbert, 1987).

Reviewer comment 3: In Table 1 (page 5), there is an obvious error in the numerical column of "Total receipts (TR)": the 2023 value of RSDF 1 is "$17.82 -$28.29, $19.58..." That is, negative signs and incorrect formats appear; Furthermore, the units of all financial variables are chaotic. Some are expressed in thousands of US dollars, while others are expressed in US dollars (as shown in Figure 1, "USD thousand" is used in parallel with "USD" in Table 1), and the currency conversion year is not specified. Non-standard data processing seriously affects repeatability and the credibility of results.

Response 3: Dear reviewer, thank you for the observation, we have removed the negative sign from RSDF 1 total receipt value.

Reviewer comment 4: On page 9, lines 311-320, the author compares the differences in net income with or without inclusion in household labor costs, noting that the net income of RSDF 1 decreased from $8,432 to -$1,414. However, on line 317 of the same page, it is stated that "the difference is $9,847", which does not match the difference between the aforementioned two values (it should be $9,846.77). At the same time, the same value is repeatedly presented for the differences between RSDF 2 and RSDF 3 (both being $9,847), clearly indicating mechanical copying or calculation errors. This indicates that the author did not actually conduct the difference calculation, and the result lacks credibility.

Response 4: Dear reviewer, thanks for the valuable input, we decided to remove the statement from the original manuscript.

Reviewer comment 5: This paper simultaneously uses NPV, IRR, ROA, and C/B as feasibility indicators in multiple places (pages 8-9, 14, and 16), but the authors have not set a unified judgment threshold. For instance, the NPV of RSDF 5 is negative (-$41,822.93), the IRR is only 6%, and the C/B ratio is 1.17, yet it is defined as "economically unfeasible". In contrast, the NPV of RSDF 1 is lower than the initial assets, the C/B ratio is 0.61, and the IRR is 14%, yet it is regarded as "feasible". Under the same indicator system, the standards are inconsistent, and the assessment results lack logical consistency and objective basis.

Response 5: Dear reviewer, in this study, the C/B ratio is utilized as one of the financial indicators, not the B/C ratio. Therefore, a C/B ratio of 1.17 in the RSDF 5 indicates an economic loss, as does its NPV value of -41,822.93, thus there is no inconsistency.

Reviewer comment 6: The study distinguishes systems that rely exclusively on family labor from those that employ hired labor and derive additional income from crops and agricultural by-products and quantifies how labor organization and diversification affect the probability of favorable outcomes and the risk of decapitalization over time. According to the author's statement in line 125, the simulation uses macro data from 1980 to 2024 for a 10-year prediction However, in the results on page 5, the Ending Cash Reserves (ECR) of all RSDFS increased by more than tenfold over a decade (such as RSDF 1 from $16.22 to $324.18), significantly higher than the average nominal growth rate of the Mexican agricultural sector. The author failed to explain this abnormal growth and did not take into account the realistic constraints of inflation, exchange rates, climate risks or market fluctuations, resulting in distorted model predictions and a lack of economic rationality.

Response 6: Indeed, these are the results of the stochastic simulation; however, this simulation was conducted using nominal prices, thus it is necessary to account for the effect of certain indicators such as inflation.

Reviewer comment 7: Meanwhile, Table 2 (page 9) shows that the cost-benefit ratio of RSDF 1 is 0.61, but it is interpreted in the text as "still economically viable on a cost-benefit basis" (lines 288-291), and it is stated that "the benefit is 64% higher than the break-even point". In fact, if C/B < 1, the cost exceeds the benefit, and the project is not economically feasible. The author's explanation completely misinterpreted the meaning of the indicators, which constitutes a serious contradiction between quantitative results and qualitative expressions.

Response 7: Dear reviewer, in this study, the C/B ratio is utilized as one of the financial indicators, not the B/C ratio.

Reviewer comment 8: The NCFI distribution shown in Figures 1 (page 7) and 2 (page 8) is inconsistent with the description in the main text. For instance, the author claims in lines 256-270 that RSDF 1 and RSDF 2 tend to decline in 2033. However, the curve in the graph shows a gentle upward trend, and RSDF 3 has an unreasonable peak area in the probability distribution (14.5-18.5 thousand US dollars), which is inconsistent with the result in Table 1 that it only increases to 15.32 US dollars. This indicates that the simulation process has not undergone internal consistency verification, or that different samples or time intervals were used for chart drawing.

Response 8: Dear reviewer, we understand the confusion; however, your comment is addressed in the following paragraph: “Figure 2 presents NCFI performance for the RSDFs over 2023 to 2033. For RSDF 1, the mean path rises through 2028 before gradually declining toward 2033, indicating an early phase of growth followed by emerging pressures that may constrain profitability. RSDF 2 shows a similar pattern, peaking around 2028 and then trending lower toward 2033.”

Reviewer 4 Report

Comments and Suggestions for Authors

REVIEW Report

Economic and financial performance of smallholder dairy 2 farms in the Mexican highlands: prospective to 2033

Dear authors,

The paper needs more improvement to be concidered to our jouranl. Please  revise all points, as follows:

1. Your introduction could be more performent if you added the comparative research studies more recent. The research problimatic ( research question is not at all clear).
2.  The theoritical body (Literature review and development of Hypotheses):

• Very poor: authors should provide all related research papers with update cited references ( 2021-2025) form renomed databases (Scopus, WoS, MDPI, Wiley, etc).
• Present your theoritical hypotheses: for each theoritical contexte join the suitable hypothesis.
• Your critical value: is very important

3. Statistical model Results: 

  * Discriptive variables: authors could present clair discriptive table to present all varaibles (Indep. varaibles; Depend. Variables ; Controle  Variables; Moderator variables).

• Conceptuel model: clair figure to present your model ( the relation of all hypotheses and the p-value)
• Statistical test-s: really authors missed all economitrical test to evaluate the model and all varaibles validity before to conduite the out-put in tables and figures.
• Figures: not clair (Figure 1. Probability of Net Cash Farm Income (NCFI) for Representative Smallholder)

4. Limitations and the future direction agenda:  is missed this section

5. The discussion section: it will be more better to analyze and interprete your theoriticla hypotheses with the results of this study. But, this main point is not added. We recommed to re-arrange and to verify your hypotheses.

4. English language:  grammar and spelling errors to be checked.

In order to help your theoritical and empirical sections refere to this scopus paper and follow all the steps: Knowledge spillovers and technical efficiency for cleaner production: An economic analysis from agriculture innovation, Journal of Cleaner Production, Vol. 320, 2021,128830. doi :https://doi.org/10.1016/j.jclepro.2021.128830

 

G-luck

Comments on the Quality of English Language

Moderated english language revision required

Author Response

Reviewer comment 1: The theoritical body (Literature review and development of Hypotheses):

Response 1: Dear reviewer, your valuable comment was taken into account. We have modified our hypothesis wich now states: “The hypothesis states that RSDFs that depend on family labor and have diversified sources of income suffer lower levels of economic and financial risk—assessed by expected net cash income, the probability of decapitalization, return on assets, and NPV—relatively to their counterparts for whom paid labor is dominant in a less diverse structure of income.”

Reviewer comment 2: Very poor: authors should provide all related research papers with update cited references ( 2021-2025) form renomed databases (Scopus, WoS, MDPI, Wiley, etc).

Response 2: Dear reviewer, we have addressed the observation by incorporating new literature into the manuscript.

Reviewer comment 3: Present your theoritical hypotheses: for each theoritical contexte join the suitable hypothesis.

Response 3: Dear reviewer, we have reformulated the research hypothesis, in line with the recommendations from other reviewers to reformulate our hypothesis.

Reviewer comment 4: Your critical value: is very important

Response 4: Dear reviewer, we appreciate your valuable suggestion, which we have addressed by incorporating a new paragraph regarding the practical importance of the study's results. “From a practical perspective, the findings suggest that smallholder dairy farms in Texcoco can be financially and economically sustainable over the medium-term if family-based labor and feeds are combined with modest reductions in herd size. For RSDFs 1-3, cumulative net cash farm income remain positive, cash reserves continues to expand, while the return on assets increased and remains double digits with no threat of decapitalization suggest further that milk production from dairy cattle would continue to provide a stable daily source for cash flow and asset building by households under current circumstances. This concurs with evidence of central Mexico, where small dairy systems proved to generate enough income to finance the basic food basket when family labor is the main labor used and feeding strategies are based on home-grown forages (Ruiz-Torres et al. 2022; Martínez-García et al. 2015). Similarly, the potential decapitalization risk associated with RSDFs 5 in relation to paid labor and purchased feed, reflects the vulnerability of small-scale farms which intensify using external inputs but without corresponding improvement in productivity or margins (Posadas-Domínguez et al. 2016). Overall, these results highlight that decisions about labor organization, crop–livestock integration, and feed acquisition are not merely technical issues but key factors determining whether small farms preserve or diminish their capital.”

Reviewer comment 5: Statistical model Results: Discriptive variables: authors could present clair discriptive table to present all varaibles (Indep. varaibles; Depend. Variables ; Controle  Variables; Moderator variables).

Response 5: In this type of work, the important variables are referred to as key output variables (KOVs), and to enhance the understanding of the statistical model results, the paragraph was adjusted to: “The key output variables (KOVs) assessed were: total income (TI, USD), total ex-penditure (TE, USD), net cash farm income (NCFI, USD), ending cash reserves (ECR, USD), net present value (NPV, USD), internal rate of return (IRR, %), return on assets (ROA, %), and benefit to cost ratio (B/C). No KOVs included: input prices, crop and milk prices, etc.”

Reviewer comment 6: Conceptuel model: clair figure to present your model (the relation of all hypotheses and the p-value)

Response 6: Dear reviewer, we appreciate your valuable observation; at the same time, we would like to explain to you that the empirical strategy does not rely on traditional parametric hypothesis tests with p values, but on a risk assessment approach using Monte Carlo simulation. Net present value (NPV), net cash farm income (NCFI), return on assets (ROA) and cash reserves are projected over a ten-year horizon under alternative scenarios (with and without hired labor), and the simulated distributions of these indicators are then compared across RSDFs. In practical terms, the relative attractiveness of one scenario over another is evaluated by examining the full distribution of outcomes (for example, percentiles, interquartile ranges and the probability of negative NPV or NCFI) and by identifying cases of stochastic dominance between RSDFs with and without family labor.

Reviewer comment 7: Statistical test-s: really authors missed all economitrical test to evaluate the model and all varaibles validity before to conduite the out-put in tables and figures.

Response 7: Dear reviewer, we appreciate your observation; however, we must clarify that we did not conduct an econometric test as such because this is a stochastic simulation study (Monte Carlo).

Reviewer comment 8: Figures: not clair (Figure 1. Probability of Net Cash Farm Income (NCFI) for Representative Smallholder)

Response 8: Dear reviewer, thank you for the valuable feedback. After analyzing your comment and exploring alternative ways to present figure1, we have decided to retain the original format because, in our opinion, it best reflects the probabilistic behavior of each RSDF.

Reviewer comment 9: Limitations and the future direction agenda:  is missed this section

Response 9: Dear reviewer, in order to take your valuable observation into account, we have incorporated a section on limitations in the discussion, resulting in the paragraph being as follows: “The following limitations should be considered when interpreting these findings. First, the analysis is based on only five Representative Smallholder Dairy Farms (RSDFs), which were carefully designed to reproduce the size, structure and management of typical small scale dairy systems in the Texcoco Highlands, but cannot fully represent the diversity of smallholder dairies across Mexico; accordingly, the results should be seen as indicative for these representative farm types rather than applicable to all producers. Second, the RSDFs were defined under current low input technology and small herd sizes, assuming no major changes in technological efficiency or herd structure during 2024–2033, whereas actual trajectories may differ if farmers adopt new technologies, adjust herd size or modify land use. Third, the stochastic simulation relies on empirical distributions estimated from historical data, so extreme future macroeconomic or policy conditions outside this experience could alter the relative risk profiles reported here. Finally, the study focuses on economic and financial outcomes at farm level and does not explicitly examine environmental impacts, gender relations or value chain dynamics, which should be addressed in future research to provide a more comprehensive assessment of smallholder dairy sustainability.”

Reviewer comment 10:  The discussion section: it will be more better to analyze and interprete your theoriticla hypotheses with the results of this study. But, this main point is not added. We recommed to re-arrange and to verify your hypotheses.

Response 10: Dear reviewer, in response to your valuable observation, we have reformulated the hypothesis and restructured the discussion in accordance with the new approach.

Reviewer comment 11: 4. English language:  grammar and spelling errors to be checked.

Response 11: Dear reviewer, we have reviewed the writing of the article and made the necessary adjustments to address the observation regarding the improvement of language use in the manuscript.

Reviewer comment 12: In order to help your theoritical and empirical sections refere to this scopus paper and follow all the steps: Knowledge spillovers and technical efficiency for cleaner production: An economic analysis from agriculture innovation, Journal of Cleaner Production, Vol. 320, 2021,128830. doi :https://doi.org/10.1016/j.jclepro.2021.128830

Response 12: Dear reviewer, we appreciate your valuable suggestion; however, we have reviewed the suggested literature and found no direct relationship to our work that would allow us to incorporate it into our arguments.

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

No more comments.

Best regards,

Reviewer 4 Report

Comments and Suggestions for Authors

2nd Evaluation report

Dear authors,

We appreciate your revision done.

Be carefully to revise the discussion section (some spelling errors).

Best wishes