Socioeconomic Effects of the Direct Procurement from Family Farming in the Brazilian School Feeding Program

Socioeconomic Effects of the Direct Procurement from Family Farming in the Brazilian School Feeding Program | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Socioeconomic Effects of the Direct Procurement from Family Farming in the Brazilian School Feeding Program Thais Diniz Oliveira, Paula Carvalho Pereda, Lilian Pellegrini Elias, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7717673/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Dec, 2025 Read the published version in Discover Sustainability → Version 1 posted 12 You are reading this latest preprint version Abstract In 2009, the Brazilian School Feeding Program (PNAE) became the first national initiative worldwide to mandate that at least 30% of federal resources - previously spent on public tenders – be directed toward the direct procurement of food from family farmers. In Brazil, these producers are more likely to adopt environmentally sustainable agricultural practices. This policy, therefore, aimed to both improve students’ diet quality and strengthen local food systems through support for family farmers. Despite its ambition, the nationwide socioeconomic effects of this procurement reform remain understudied. This paper aims to fill this gap by using an integrated economic modelling framework which combines a differences-in-differences and input-output model. With the differences-in-differences model we estimate the change in family and non-family farmer production value due to the modification in the PNAE procurement requirements. The input-output model was used to assess the effects on employment and gross domestic product (GDP), with a representation of family and non-family farming productive segments using information provided by the Brazilian Agricultural Census. Our findings indicate a positive socioeconomic effect of the program by improving employment and GDP. During the follow-up period, changes in PNAE food procurement policies generated a net increase of R$15 million in GDP and approximately 24 thousand new jobs nationally. Most of the jobs and positive economic results were greater for family farmers, whose income increased by R$ 39 million (or approximately US$ 8 million). Those gains can be attributed to the economic structure depicted in the estimated input-output, which identified livestock family production as a labour-intensive economic segment. Economic modelling suggests that PNAE has the potential to promote more equitable economic development. Addressing the identified compliance problems in several municipalities could enhance the estimated effects. Improved monitoring and provision of technical support to both local school feeding program managers and family farmers can enhance compliance and contribute to the promotion of healthier, more equitable and sustainable food systems. Figures Figure 1 Figure 2 Introduction Local food procurement and public food procurement from family farming have been linked to the promotion of healthier diets and more sustainable food systems ( 1 ), as well as driving potentially positive economic and social outcomes ( 2 ). In particular, school procurement from locally sourced and family-produced foods has demonstrated its contribution to promoting inclusive, biodiverse and sustainable production systems, to transform and shorten the supply chain, and promote nutritional quality menus, with increased inclusion of vegetables, fruits, and legumes and reduced ultra-processed food ( 3 – 8 ). In Brazil, family farming has been associated with agroecological practices, addressing not only productivity but also broader social and environmental outcomes ( 9 ). The economic and social benefits for family producers include generating local employment and strengthening local production ( 10 ). This is achieved by establishing an institutional market that bolsters family farming, rendering the market more predictable and stable for these farmers. A regular and predictable demand for farmers' products encourages investment in production, supports income growth, and facilitates their integration into markets ( 2 , 11 ). Our study examines the socioeconomic effects of direct food procurement from family farmers within the Brazilian School Feeding Program (PNAE). PNAE, a globally recognised and long-standing school feeding program dating back to 1955 ( 12 ), currently serves more than 40 million students (80% of all school-aged Brazilian population) in more than 150,000 public schools ( 13 ). The program aims to support students’ adequate growth, biopsychosocial development, learning, and academic performance by promoting healthy eating habits through food and nutrition education, while providing meals that meet their nutritional needs during the school day ( 14 ). To do that, we explore a change of the program’s rules. In 2009, Brazil became the first country to mandate at least 30% of federal funds received by local- and state governments for procuring foods for PNAE be used for direct purchases from family farmers and their organizations ( 15 ). This was achieved by eliminating a well-known barrier that prevented family farmers from accessing public procurement programs and replacing it with an innovative legal instrument that removed the requirement for public bidding, enabling direct procurement from family farmers ( 16 ). [1] These family farmers must comply with the Family Farming Law (Lei nº 11.326, 2006), which characterizes family farmers in the country as those engaged in family-run, small- to medium-scale and family-based agricultural practices whose income is derived from farming activities. This simplified procurement mechanism required suppliers to comply with pricing and food safety standards. Prices were based on the average price of the products in three local markets, including transportation costs. The policy instrument allows any family farmer to sell their products anywhere in the country while prioritizing the most socio-economically vulnerable family farmers as settlement groups, indigenous, quilombola (groups descended from escaped slaves in Brazil), women and other traditional communities, and producers of organic and agroecological food from the same municipality or state as the buyer ( 18 ). Family faming covers 3.9 million of the total 5 million agricultural establishments in Brazil ( 19 ). The effort to integrate family farming into PNAE has two origins. First, the heterogeneous group that constitutes family farming began to gain recognition in public policy during the 1990s. This was marked by the launch of the first credit policy tailored to family farmers, a significant shift from earlier public policies that exclusively targeted large agro-export-oriented farms designed to serve national macroeconomic interests ( 20 ). In the following decade, the Family Farming Act was enacted, accompanied by the creation of markets through public purchases. The second origin stems from the efforts of the Brazilian government under the Programa Fome Zero (Zero Hunger Program), which strengthened and expanded various food and nutrition security policies and included the Right to Healthy and Adequate Food in the country’s constitution. The Brazilian School Feeding Program became part of a set of policies aimed at promoting healthy and adequate diets to students and fighting hunger in rural and urban areas by strengthening family farming and productive inclusion. The National Council for Food and Nutrition Security, a key Brazilian democratic participation governing body, was key to bringing policymakers, academics, and advocates from public health, food and nutrition security, and rural development sectors together for the design and approval of the law ( 21 ). Currently, Brazilian family farming represents 77% of agricultural establishments and occupies 33%of the cultivated area ( 19 ). It plays a major role, especially in horticultural production, and is particularly significant across the country, with notable prominence in the southern, northern, and northeastern regions of Brazil ( 22 ). In 2022, R $ 1.6 billion (US $ 0.29 billion) was spent on direct procurement from family farming ( 23 ), making up 45% of the federal transfers for Brazil’s school feeding program - exceeding the legal obligation. Local- and state- governments might also allocate their own resources to match food procurement needs, although in a much smaller magnitude. This strategy/policy helps family farmers access formal markets, stimulates local economies, and improves school meal quality with fresh and minimally processed foods provided by family farmers ( 24 , 25 ). The existing literature shows the influence of the Brazilian school feeding program on purchases from family farmers ( 24 , 26 ) and local development ( 27 ), on the food supply and/or demand across different municipalities ( 28 , 29 ) and states ( 24 , 25 ) as well as on the promotion of better diet quality ( 3 , 30 , 31 ), lower occurrence of obesity among adolescents ( 32 ), and protection against the consumption of sugary beverages ( 4 ). Nonetheless, the existing literature on PNAE has yet to undertake a nationwide quantitative evaluation of the ramifications of mandating direct procurement from family farmers for school feeding in Brazil on the food supply chain, particularly the family farming segment using a comprehensive socio-economic and nationwide perspective. While ( 24 ) conducted a closely related assessment using an input-output framework, the analysis was limited to a specific Brazilian state. This paper contributes to the available literature on PNAE by adding an economic dimension to analyse the impacts. By exploring the extent to which the Brazilian program can affect the domestic economy, this study highlights the sectoral interdependencies between family farming segments and other economic activities. The novelty of this study lies in its capacity to furnish an impact analysis that distinguishes between family and non-family production segments. The literature suggests that partially reallocating food procurement resources toward direct purchases from family farms can enhance local economic dynamism, income and employment, albeit with potential trade-offs from reducing purchases from non-family farmers. Balancing these trade-offs is critical for assessing the affordability of these policies and their potential for continuation or scale-up. This distinction is essential for informing the design of targeted policies and understanding the role of school feeding procurement in promoting planet-friendlier and more equitable agriculture practices. The study contributes as a proof of concept, providing empirical evidence that structured food procurement policies can generate measurable socioeconomic benefits. As international organizations increasingly recognize the role of public procurement in transforming food systems, this study offers timely and globally relevant insights. It advances broader discussion on how targeted institutional demand can support inclusive rural development, economic resilience, and sustainable food systems. Methods Analytical and conceptual framework We developed an empirical strategy that combines an econometric and an Input-Output (IO) model, as described in Fig. 1 . The econometric model examines how mandatory procurement from family farmers influenced their production and demand using data from the Brazilian Agricultural Censuses (before and after the change in PNAE’s mandatory procurement) and public schools’ food procurement. The results are then integrated into the IO model, which estimates the broader economic effects, including GDP, employment, income, and taxes, by capturing the interdependencies among various sectors of the Brazilian economy and considering the trade-off from replacing demand for non-family farmers by family farmers. The socioeconomic impacts encompass income and employment conditions that collectively shape livelihoods and well-being. In the context of school purchases, it extends beyond direct transactions, stimulating broader economic activity through a chain of supplementary acquisitions. School suppliers, for instance, procure inputs from other sectors to meet the food demands of schools, creating ripple effects across the economy according to sectoral interdependencies. In this analysis, the mechanisms behind socioeconomic impacts of the PNAE local procurement policy arise from key structural differences between family farms and non-family farms, which influence economic outcomes such as employment, income, GDP, and taxes. Family farming segments are more labour-intensive, meaning a shift in procurement toward family farming potentially increases demand for labour, thereby boosting employment. Additionally, family farmers are more likely to spend their income locally, also potentially creating stronger multiplier effects (e.g., additional rounds of spending) in rural economies by stimulating demand for goods and services, which contributes to higher local income and GDP. This contrasts with non-family farming segments, which are often more capital-intensive and generate less localized economic activity. These causal pathways, which include changes in labour demand, localized spending, and tax contributions, are captured through the input-output impact analysis and help explain the broader socioeconomic effects of the policy. Econometric model For the first part of the analysis, we use a panel dataset covering the years 2006 and 2017, which represent the pre-and post-implementation periods of the PNAE’s 2009 family farming-based rule. The dataset includes information on agricultural production value and pricing obtained from the two Brazilian Agricultural Censuses of the period, categorised by municipality and sector (agriculture; livestock; forestry, fishery, and aquaculture; among others) and further stratified by family and non-family farming. Since all Brazilian municipalities are equally exposed to the PNAE rules and required to comply with the food procurement from the family farming component, the panel dataset also incorporates national food procurement data provided by FNDE by municipality to understand which municipalities complied or not with the change in PNAE rules. The specifics of food procurement from family (and non-family) farmers - including data on expenditures - have been publicly accessible through the Accountability Management System (SiGPC) ( 33 ) since 2013. We use the 2017 PNAE procurement data to align with the year of the agriculture census. Schools procure a wide variety of foods and beverages, including fruits, vegetables, cereals, milk, meat, and ready-to-eat items. Table 1 highlights the top 20 most purchased food categories in 2017. More information about the data for the econometric exercise is provided in Supplementary Appendix S.1. Table 1 Main products purchased by schools, SIGPC 2017 Product Proportion of the School Purchases Meat 11.9% Milk 10.1% Chicken 7.7% Banana 4.6% Salty snacks 4.4% Rice 4.2% Bread 3.7% Fruit Pulp 3.6% Beans 2.7% Fruit Juice - ultraprocessed 2.0% Pasta 1.8% Sugar 1.8% Apple 1.7% Potato 1.5% Eggs 1.4% Jerky meat 1.4% Orange 1.4% Tomato 1.3% Cocoa powder 1.2% Dairy beverage 1.2% Others 30.4% Notes: Over 300 product categories are purchased, each classified individually or grouped under the “Others” category based on their proportional significance to total school purchases. The panel allows for the identification of municipalities that adhere to the PNAE rules governing food purchases from family farming in 2017. Compliant municipalities are those whose expenditures comprised 30% or more of family farming products that year. We compare these compliant municipalities with non-compliant ones, the latter serving as control groups, using a differences-in-differences (DiD) method. The goal is to understand the impacts on the production value of agriculture, livestock and forestry from family farmers among compliers. We expect that the compliers have purchased more agricultural, livestock and forestry products from family farmers (a positive effect) and less from non-family farmers (a negative effect). To mitigate potential sample selection bias related to PNAE rule-compliant municipalities, we include a set of fixed effects (Fes) – municipal, year - and covariates – average prices as well as local market conditions that affected prices (see more details on the relevance of the controls in Supplementary Appendix S.1). However, as with any DiD approach, our analysis relies on key assumptions, particularly the parallel trends assumption and no anticipation of the policy. Due to data limitations, we observe only one pre-treatment period, which prevents us from formally assessing the feasibility of the parallel trends assumption—that is, whether compliant and non-compliant municipalities exhibited similar trends in agricultural production prior to the policy. This limitation should be considered when interpreting the results, as unobserved differences in pre-treatment trends could potentially bias our estimates. Despite this constraint, we take steps to strengthen the credibility of our findings by including robustness analysis in the supplementary material. In other words, our identification strategy assumes that differences in agricultural purchases between compliant and non-compliant municipalities remain constant over time. However, it is possible that compliant municipalities made additional efforts to increase purchases from family farmers after the reform, potentially creating spillover effects that prompted non-compliant municipalities to partially adjust their behaviour as well. These dynamics could introduce a conservative bias, causing an underestimation of the true impact of compliance. Therefore, our results should be interpreted as a lower-bound estimate of the policy's effects. The econometric regression below describes the estimation for agricultural, livestock and forest products and distinguishes the production value into family and non-family producers: $$\:\text{ln}\left(valu{e}_{imst}\right)={\alpha\:}_{0}+\beta\:Complie{r}_{m}.Pos{t}_{t}+\gamma\:ln\:\left(pric{e}_{imst}\right)+{\lambda\:}_{m}+{\theta\:}_{t}+{u}_{imst}$$ 1 Where \(\:ln\left(value\right)\) is the log of the production value of product i , in municipality m , allocated in sector s (agriculture, livestock or fishing/forestry), and in time t (the years 2006 and 2017). Ln(price) is the logarithm of the price with the same dimensions. α 0 is the constant, λ m is a county-fixed effect, θ t is a time-fixed effect, and u imsjt is the econometric error term. Finally, \(\:{\beta\:}_{}\:\) is the parameter that measures the effects of our variable of interest ( \(\:Complier.Post\) ) that captures the effect of the PNAE program in 2017. We run the regression for all products and production value by municipality separated by family farmers and non-family farmers. The regressions were weighted by the 2006 baseline production value, enabling our results to be interpreted as national averages. Specifically, the key coefficient in our model represents the weighted average impact of policy compliance across products within the same sector, with weights determined by the contribution of each product to the sector's total production value. Table 2 shows the percentage change of production value observed in family production of agriculture, livestock, and forestry products following the implementation of the PNAE rule for family farming purchases. Family farmers in compliant municipalities experience positive effects, particularly in the agricultural and livestock sectors. The average increase in family farming production value in compliant municipalities is 9·8% for agricultural products and 4·5% for cattle products. The findings suggest a positive effect of PNAE in promoting productive agricultural and livestock activities in family farming. The effect for fishing and forestry is, on the other hand, negative, although very small in absolute terms, as this sector represents only 1·6% of total PNAE expenditures. Table 2 Impacts of complying with the rules of PNAE in 2017 on family farming production ( 1 ) ( 2 ) ( 3 ) Agriculture Livestock Forestry/ Fishery Effect on PNAE rule 0·098*** 0·045*** -0·019*** (0·001) (0·002) (0·006) N 3,727,322 677,436 148,847 Notes : Clustered standard errors by municipality in parentheses. P-values: * p < 0·1, ** p < 0·05, *** p < 0·01. To compute the changes in final demand for both family farmers and non-family farmers that will be used in the IO model, we use the average effect estimated in Table 2 . We assume that the increase in production value from family farmers results in a corresponding decrease in production value from non-family farming products. This assumption is based on the fixed PNAE expenditures per student, implying that any increase in purchases from family farmers directly reduces purchases from non-family farmers. This assumption simplifies the analysis by treating the PNAE budget as a zero-sum game, where gains for family farmers result in losses for non-family farmers. While this approach provides a clear-cut way to estimate the impact, it does not fully capture the dynamics of agricultural markets. However, our analysis indicates that the PNAE program’s procurement volume represents a relatively small share of the overall food market – approximately 0.02% of the total food market and 0.3% of the family farmer’s food market. This suggests that the rule change is unlikely to have a significant impact on broader price and market dynamics. If the PNAE program represented a larger portion of the market, changes in the program could potentially influence prices. The changes in total purchases (in Brazilian reais, R $ ) were used to design the shock in the IO impact analysis during the second part of the analytical framework, better explained in the next section. Input-output model We estimate a national IO matrix disaggregated into family and non-family farming agriculture production and perform an impact analysis to quantify the effects of PNAE on the main macroeconomic variables. The IO matrix depicts the functioning of an economic system considering the interrelationships among sectors to produce goods and services. The IO model is designed to show how changes in consumer demand impact the overall economy based on several assumptions, including that each sector produces using inputs in fixed proportions and with constant returns to scale. It also assumes fixed technical coefficients and output prices, and linear relationships between sectors. The fixed price assumption is considered reasonable for this study, as it focuses on isolating the immediate direct and indirect economic effects of PNAE, where price volatility is not the central focus and price adjustments may be limited. The primary interest lies in the sectoral economic linkages and labour demand induced by changes in PNAE procurement. This section describes the procedures and data employed in the disaggregation process and introduces the IO model for the impact analysis. Disaggregation of family and non-family production The most recent public and official version of the Brazilian IO matrix, provided by the Brazilian Institute of Geography and Statistics (IBGE), is from 2015. It includes 68 sectors and 128 products. However, it does not differentiate between family and non-family agricultural production, which is necessary to assess the direct effects of the policy. This paper advances methodologically by breaking down the agricultural sectors into family and non-family segments, using data from the 2017 Brazilian Agricultural Census ( 19 ), the primary source for this type of information. To match with the year of the agricultural census, we opted to use the IO matrix of 2017 estimated by the Regional and Urban Economics Lab – NEREUS ( 34 ) based on official economic data. The agricultural sectors of the Brazilian Agriculture Census are explicitly represented in the national IO matrix, which facilitates the pairing of information between them. We maintain the original sectoral structure of the agriculture sectors in the IO matrix and create a separate family and non-family farming segment for each of these economic activities in the estimated IO matrix: a) non-family farming agriculture, b) family farming agriculture, c) non-family farming livestock, d) family farming livestock, e) non-family farming forest/fishery and f) family farming forest/fishery. For this analysis, the Brazilian IO matrix exhibits a total of 29 sectors. A detailed description of the sectoral resolution and breakdown approach is given in Supplementary Appendix S.2. This Brazilian IO matrix for family farming is a novelty of this study. It can support future investigations on family farming, especially because the economic literature still underexploits the inter-dependence relations of family production in Brazil. Part of this is attributed to the limited availability of detailed statistical information on the flows of goods and other factors specific to family-related production. Input-output impact analysis Input-output impact analysis is a valuable tool for understanding how the economy and its sectors respond to policy-driven or behaviour-driven changes, providing insights into the effectiveness and consequences of the interventions. This analysis involves comparing the input-output matrix results both before (ex-ante) and after (ex-post) the changes occur. The basic IO model, its applications and terminologies are provided in ( 35 ) while the technical description of the model is available in Supplementary Appendix S.2. This economic impact study estimates the effects of using PNAE resources to purchase food directly from family farming. Direct impacts are linked to the additional monetary flow to family production segments whereas indirect impacts are due to intersectoral transactions flowing from the PNAE incentives. Here we consider type 1 multipliers, which incorporate direct and indirect effects to express the total effect on the economy in terms of output, employment, income, GDP, and taxes of a unit increase in final demand for each sector. The employment multiplier is a measure of the number of jobs created by the sector to carry out the increased production activity. In 2017, the FNDE transferred R $ 3·8 billion to PNAE food procurement, and the municipalities complemented those resources with R $ 591 million. Therefore, R $ 4·47 billion is the total value of the shock applied to the final demand in the IO model, and more specifically, to the agriculture segments of family and non-family production. Although the analysis assumes a fixed total PNAE funding, local variations in municipal co-financing may amplify or mitigate its impacts in specific regions. These variations could influence the geographical distribution of benefits without altering the total federal funding or the overall interpretation of the national-level impacts of PNAE. The simulation scenario is designed based on the share of food purchases in 2017 grouped by food category and classified according to the sectors of the IO matrix. Using the SiGPC data ( 33 ), we attributed the portion of FNDE resources to each of the sectors under scrutiny and adjusted the values using the results from the econometric evaluation to reflect the food procurement from family farming demand that complies with the 30% requirement of food procurement from family farming. This reflects the primary focus on family farming procurement rather than on wholesalers and other distributors, which is controlled for in the econometric segment and consequently, in the shock. The final distribution of the shock and corresponding values are presented in Table 2 . Table 3 The distribution of shock across family and non-family segments (in R $ million) Sectors Non-family farming Family farming Agriculture -387 387 Livestock − 19 19 Forest/fishery 2 -2 Total Notes : Estimated using the coefficients from Table 1 . Values were calculated based on the total expenditures of PNAE in 2017 (R$ 4·47 billion) and the participation of agriculture, livestock, and forest/fishery in those expenses using SIGPC data. Results The macroeconomic effects of PNAE´s direct procurement mandate from family farming Figure 2 a shows the macroeconomic and sectoral impacts of the abovementioned shifts in economic activity for all sectors and family farmers in agriculture and livestock. The macroeconomic effect refers to the net national effect or the aggregate economic impact of the policy on the Brazilian economy as whole. It captures the overall balance of gains and losses across all sectors. These results should be interpreted as the change in million R $ relative to the input-output baseline (before PNAE). The economic impacts of PNAE depend upon its productive structure and the total amount of resources FNDE transfers to PNAE each year. This is captured in our results. From a nationwide perspective, there is a positive net impact of PNAE on national GDP. This effect is small in magnitude, R $ 15 million (a total GDP increase of 0·0003%, or an increase of 0·004% of the PNAE GDP from the baseline). Previous school-feeding assessments have found similar positive impacts on GDP for different contexts and countries ( 38 ). The total net income and tax results are negative but relatively minor, while national output decreases by R $ 28 million. This decline stems from sectoral characteristics and interdependencies, whereby a reduction in non-family farming demand reduces production and subsequently input purchases from other sectors, causing the observed decrease. Although these results may not have substantial implications for the broader context of the Brazilian economy, their socioeconomic effects demonstrate the importance of family farming-oriented policies to potentially address existing and emerging social issues in rural areas. (a) Macroeconomic and sectoral effects of family farming procurement under PNAE, in R $ million The net gain is the strongest in family farming segments, especially agriculture, but while benefiting family farming production, PNAE’s success in buying directly from family farming shifts production and slightly shrinks non-family/conventional agriculture. This outcome brings the program closer to attaining the objective of procuring food from family farming operations, which is to serve as a to be an instrument to support local and smallholder farmers and to help integrate them into markets ( 11 ). This is observed in the sectoral results of Fig. 2 b, which reveals gains in output resulting from the reservation rule of PNAE for purchases from family production segments of R $ 390 million (an increase of 0·61%). In Brazil, 67% of all workers involved in agricultural activities are family farmers, occupying 77% of the rural establishments registered. Family production agriculture benefits economically the most from the policy, with an increase of 0·65% in income. Figure 2 shows that when giving access to family farmers, the program provides an opportunity to improve living conditions in terms of employment. It displays the sectoral effects on employment expressed in absolute terms (or man-equivalent-year). Overall, the change in the PNAE rule implies a net effect of approximately 24 thousand direct and indirect jobs at national level. These are mostly concentrated in family farming agriculture, with the creation of 27,243 job opportunities. Non-family farming, agriculture and livestock segments lose approximately 3 thousand jobs due to the substitution effects. Both family and non-family livestock segments play a key role in the PNAE value chain, being responsible for 11·8% and 18·5% of the total employment effect, respectively. This decomposition highlights ‘winners and losers’ resulting from the policy, where winners are those experiencing increases due to the higher demand for their goods and services, while losers refer to sectors facing declines as resources are reallocated or demand shifts within the economy. Other sectors absorb the effects differently. In addition to the economic relationships between producers (family and non-family farmers) and the consumer (schools, in the case of school feeding), there are additional, often stronger, linkages between these producers and other sectors of the economy. These indirect impacts are due to intersectoral transactions flowing from the changes in school purchases from family and non-family farmers to the linked sectors. They account for 0·63% of the total increase in the number of jobs, reflecting the varying labour intensity across different economic activities. PNAE’s regulatory framework connects family farming and institutional markets, whereby the federal budget is allocated to the acquisition of food for school feeding. The government tax losses from the increase in the purchases of family and decrease in non-family products is R $ 3·8 million in tax collection annually. Non-family production is more consolidated and dominated by larger producers, which contribute significantly to government tax revenues through higher utilization of labour, inputs, and greater overall revenue generation. From a socioeconomic perspective, and given the evidence provided, this total accumulated loss in tax collection represents an annual cost from the government side of R $ 160 per job created in the economy. This is of paramount importance for promoting healthier and more sustainable food systems, as well as generating jobs. Most importantly, to address food insecurity within and outside the school environment while reducing poverty. As argued in ( 39 ), more financial and political incentives are, hence, necessary and they could help develop shorter and closer production chains to schools but also enhance local development dynamization. The role of family and non-family farming in the economy Family farming is seen as a key element in building sustainable and healthy food systems but has also been identified as socially vulnerable. They are characterised by low incomes, and proportionally higher food insecurity and nutrition than urban areas, leading to a constant risk of rural-urban migration. Among our findings, family and non-family production accounted for 5·3% of the Brazilian GDP in 2017, of which 21·7% is family-farming-led. However, in an input-output analysis conducted in 1996 ( 36 ), family farming comprised approximately one-third of the Brazilian agribusiness landscape, indicating the sector has been shrinking. In the agriculture sector, family farmers have usually lower incomes than farmers from non-family agriculture. According to the 2017 Census, the annual income of almost 44% of family farmers varies between US $ 1250 and US $ 12500 whereas for 42% the income remains below US $ 1250 per year. This reflects the small scale of farms as well as the lack of physical and human capital, which is a determinant factor in low-income levels and high poverty rates ( 37 ). A growing output and GDP effect have the potential to help address these issues. More importantly, they drive the creation of employment opportunities for family and non-family segments. The multipliers presented in Table 3 are outputs derived from the input-output model. Comparing these multipliers, the increase in the PNAE demand would lead to a larger multiplying GDP effect on agriculture and livestock family segments than non-family ones. A similar multiplier effect is observed for the income of livestock and forest and fishery sectors, where there is a larger effect on the family over non-family sectors. In contrast, family agriculture producers experience a lower income multiplier effect than non-family. Despite not specifying the mechanisms driving the employment impacts, the input-output analysis provides a general estimate of demand for additional labour across sectors and segments. Table 4 Input-output type 1 multipliers Sectors Output Employment Income GDP Tax Agriculture (non-family) 1.68 1.64 2.35 1.47 2.06 Agriculture (family farmers) 1.62 1.08 2.28 1.52 1.81 Livestock (non-family) 1.82 1.43 1.88 1.65 1.99 Livestock (family farmers) 1.77 1.08 1.89 1.66 1.89 Forestry/Fishery (non-family) 1.36 1.38 1.95 1.23 1.79 Forestry/Fishery (family farmers) 1.35 1.04 2.11 1.23 1.76 Extractive Sector 1.86 7.59 2.72 2.08 1.81 Machinery and Equipment 2.05 4.28 2.29 2.92 1.92 Food Beverages Industry 2.31 5.96 3.10 3.93 2.23 Other Manufacturing 2.04 2.62 2.43 2.65 1.77 Elec. Gas 1.95 7.61 3.17 2.06 1.73 Water.Waste 1.57 1.56 1.39 1.42 1.85 Consumer Prod 1.88 1.48 1.90 1.80 2.03 Commerce 1.55 1.27 1.40 1.46 1.86 Transportation 1.85 1.69 1.72 1.83 1.93 Accom. And Food services 1.82 1.38 1.68 1.74 1.56 Info. Communication 1.64 2.55 1.70 1.67 1.58 Finance 1.45 2.65 1.48 1.40 1.55 Real Estate 1.12 1.88 3.02 1.07 1.55 Scient. Technical 1.58 1.53 1.57 1.52 1.83 Administrative Services 1.42 1.19 1.20 1.30 1.70 Government Services 1.38 1.51 1.16 1.29 1.62 Public Education 1.22 1.18 1.07 1.14 1.73 Private Education 1.40 1.16 1.16 1.31 1.74 Public Health 1.46 1.42 1.18 1.33 1.70 Private Health 1.60 1.48 1.48 1.53 1.66 Arts and Culture 1.61 1.16 1.39 1.63 1.72 Other Services 1.67 1.23 1.58 1.65 1.69 Domestic Services 1.00 1.00 1.00 1.00 1.00 Discussion Mandating that a fraction of the Brazilian school food procurement national funding be used to source directly from family farmers - prioritizing the most socio-economically vulnerable and those with the most sustainable food systems ( 16 ) -, extends the impacts of the program beyond providing healthy meals to students. In fact, we found a multiplying effect of the program´s direct food procurement from family farmers on GDP. For every R $ 1.00 increase in demand for family farming and family livestock products for the PNAE, Brazilian GDP grow by R $ 1.52 (agriculture) and R $ 1.66 (livestock), respectively. This approach can impact employment and income levels within this segment. Such policies potentially foster sustainable food systems ( 40 ) by integrating nutrition, food and agriculture through the strengthening of local food production and processing ( 41 ). This integration is achieved by engaging local, small and medium-sized food enterprises, women, youth and/or other vulnerable groups, including settlement, indigenous, quilombola and other traditional communities, while simultaneously promoting healthy and sustainable diets ( 42 ). Hence, this dynamic also potentially reduces barriers to market participation and contributes to more inclusive food systems. Our findings on the socioeconomic impacts of PNAE highlight the importance of food procurement from family farming policies in supporting local communities, and the need to strengthen regulatory policies to promote healthier and more sustainable food systems in Brazil. PNAE generates positive primary and secondary benefits, including increased income, job creation, potentially contributing to improved livelihoods for family farmers. It also supports the preservation of food landscapes and local cultural practices, and the promotion of environmentally friendly, sustainable production systems. A third of the food used in the preparation of school meals is required to be sourced from these sustainable family farming practices ( 7 ). The shift in the food procurement regulations enacted in 2009 produced a net national effect of R $ 15 million increase in GDP and the creation of approximately 24 thousand jobs. However, this was accompanied by an annual tax loss of R $ 160 (approximately US $ 32) per job created, which can be attributed to changes in the sectoral composition of food supply to schools and the demand for intermediate inputs. As the policy shift favoured more labour-intensive family farming sectors over higher-taxed non-family farming sectors, the overall tax revenue generated by the economy decreased. Most of the jobs and positive economic results are more pronounced for family farming producers, whose income increases by R $ 39 million (or approximately US $ 8 million) and observed a creation of 27,243 jobs. The number of jobs created is relatively small compared to the total number of people employed in family farming, but this increase is significant given the trend of declining employment in family farming over recent decades. This highlights the importance of policy interventions in reversing negative employment trends and boosting economic activity within this sector. Of the 15 million people employed in the Brazilian agriculture sector, 10 million are engaged in family farming. In 2017, family farmers contributed an annual production value of R $ 106.5 billion or US $ 17,2 billion ( 19 ). Family agriculture producers are the most economically affected by the policy, resulting in a 0.65% increase in income. Through a substitution effect, where food procurement from non-family agriculture farmers reduces to accommodate the increase in purchases from family farmers, the new mandate implies modest losses for non-family farmers. This segment has historically benefited from substantial governmental support, which has reinforced its significant contribution to the Brazilian economy. Our results show that giving access to family farmers over other suppliers does not cause significant economic harm. Moreover, the social, environmental, and cultural benefits—while not accounted for in this analysis—are important factors that warrant further exploration in future studies. These benefits emphasize the value of strengthening family farming procurement programs. More importantly, it has important implications for rethinking the global food system. The growth in employment, incomes and GDP offsets the losses identified, such as tax reductions. Since the 1980s, the modernisation of agriculture, the food industry, and retail sectors has reshaped the landscape of food production and consumption. These transformations have been the major drivers of poor health and environmental degradation, particularly through changes in food systems and dietary patterns associated to reduced biodiversity ( 43 ). Food systems have become increasingly concentrated in distribution, commercialisation, and retail, especially within the food industry and supermarket chains, with production decisions shaped by the economic logic of these sectors ( 44 ). In this context, reallocating resources towards family farmers has the potential to challenge and shift this entrenched dynamic, which has been consolidated over the past four decades. Despite the recent advances of PNAE, and its fragrant potential, that have led to both economic and social benefits, these remain limited, in part because not all local and state governments reach the 30% minimum mandated threshold of direct procurement of locally sourced and family-produced food. If all Brazilian municipalities complied with the rule, the impacts on jobs and total GDP would be higher. Access to all food procurement data by municipality facilitates monitoring and enforcement, potentially lowering costs for policymakers, yet the extent of these potential cost reductions remains to be quantifiable. This investigation brings evidence that should encourage future research and dialogue into the opportunities available to align the socioeconomic and health impacts of the school feeding program within a broader research agenda on healthy diets from sustainable food systems. By doing so and overcoming socioeconomic limitations, especially via investments that increase the sector’s dynamism, school meals can help achieve multiple SDGs. These dimensions, including sustainability-related outcomes, should be explored in future studies. Acknowledging the limitations of the IO model, future research could build upon our findings by employing a Computable General Equilibrium (CGE) approach using the estimated IO matrix to capture price dynamics, factor substitutions, and more nuanced behavioural responses from both the socioeconomic and environmental perspectives. This would provide a more comprehensive analysis of the economic impacts of PNAE, an aspect beyond the scope of this study. Several limitations of this paper, such as simplifying assumptions about production value shifts between family and non-family farmers, the focus on municipal-level data, and the inability to test the parallel trends assumption, could be addressed in future research. Specifically, the assumption that an increase in production value for family farmers corresponds to a decrease for non-family farmers oversimplifies the complexities of agricultural markets, overlooking price differences between farm types. Additionally, while the focus on municipal-level data assumes that the effects of PNAE compliance are primarily local, we note that approximately 88.8% of municipalities in Brazil can be supplied by local family farmers. Finally, although the empirical approach provides valuable insights, the inability to test the parallel trends assumption presents a limitation. The multifaceted feature of PNAE lays the foundation for a healthier and more resilient future. In this study, we advance in finding that well-designed school feeding programs can contribute to economic development more equitably. Declarations Funding This work was supported by Bloomberg Philanthropies, through a partnership between the University of North Carolina at Chapel Hill and the Center for Epidemiological Studies in Nutrition and Health (NUPENS) at the University of São Paulo. Data sharing The input-output matrix for family farming generated for the study is available as SI. Both the econometric and input-output models are summarised in the Supplementary Appendix, including mathematical descriptions and other relevant information. Additional data is available on request to TDO and PCP. Ethical approval This manuscript does not involve human or animal participants. It is our original work and has not been published elsewhere in any form or language. Contributors TDO developed the input-output model, conducted the analysis, interpreted the results, and developed the figures. PCP developed the econometric model, conducted the analysis and interpreted the results. TDO, PCP and LPE wrote the manuscript and collected the data. PCP, LPE and ACD were involved in conceptualization. ACD was responsible for the funding acquisition. All authors commented on the manuscript draft and had final responsibility for the decision to submit for publication. Declaration of interests We declare no competing interests. Consent to Participate Not applicable. Consent for Publication Not applicable. Clinical Trial Number Not applicable. Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work the authors used ChatGPT in order to review grammar, cohesion and clarity of the text. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the publication. References Gaitán-Cremaschi D, Klerkx L, Aguilar-Gallegos N, Duncan J, Pizzolón A, Dogliotti S, et al. Public food procurement from family farming: A food system and social network perspective. Food Policy. 2022 Aug;111:102325. Kelly S, Swensson LFJ. Leveraging institutional food procurement for linking small farmers to markets. FAO; 2017. (FAO Agricultural Development Economics Technical Studies). Boklis-Berer M, Rauber F, Azeredo CM, Levy RB, Louzada ML da C. 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Global Food Security. 2020 Jun;25:100366. Willett W, Rockström J, Loken B, Springmann M, Lang T, Vermeulen S, et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. The Lancet. 2019 Feb;393(10170):447–92. Reardon T, Timmer CP. Chapter 55 Transformation of Markets for Agricultural Output in Developing Countries Since 1950: How Has Thinking Changed? In: Handbook of Agricultural Economics [Internet]. Elsevier; 2007 [cited 2024 Dec 19]. p. 2807–55. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1574007206030556 Footnotes These family farmers must comply with the Family Farming Law (Lei nº 11.326, 2006), which characterizes family farmers in the country as those engaged in family-run, small- to medium-scale and family-based agricultural practices whose income is derived from farming activities Additional Declarations No competing interests reported. Supplementary Files Supplementaryappendix1JUN2025submmitted.docx Cite Share Download PDF Status: Published Journal Publication published 14 Dec, 2025 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 30 Oct, 2025 Reviews received at journal 28 Oct, 2025 Reviewers agreed at journal 25 Oct, 2025 Reviewers agreed at journal 25 Oct, 2025 Reviews received at journal 24 Oct, 2025 Reviews received at journal 15 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 02 Oct, 2025 Reviewers invited by journal 30 Sep, 2025 Editor assigned by journal 30 Sep, 2025 Submission checks completed at journal 30 Sep, 2025 First submitted to journal 26 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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2","display":"","copyAsset":false,"role":"figure","size":67298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKey results from economic modelling. (a) exhibits the effects on key economic variables and by type of family production, i.e., agriculture and livestock. (b) highlights the sectoral decomposition of employment effects, indicating a reallocation of jobs.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7717673/v1/e16581f95a321d94c5a5524b.png"},{"id":98243531,"identity":"32dc6bac-89ed-4837-b94b-978310158030","added_by":"auto","created_at":"2025-12-15 16:08:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1073737,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7717673/v1/3dce8cb7-9e94-41af-be0e-c2f285766a7d.pdf"},{"id":93428753,"identity":"5db8b125-ec3d-4e65-abfb-f13cebbf3599","added_by":"auto","created_at":"2025-10-13 17:25:10","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":65237,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryappendix1JUN2025submmitted.docx","url":"https://assets-eu.researchsquare.com/files/rs-7717673/v1/e19d3457bf8de6a043caf48e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Socioeconomic Effects of the Direct Procurement from Family Farming in the Brazilian School Feeding Program","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLocal food procurement and public food procurement from family farming have been linked to the promotion of healthier diets and more sustainable food systems (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), as well as driving potentially positive economic and social outcomes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In particular, school procurement from locally sourced and family-produced foods has demonstrated its contribution to promoting inclusive, biodiverse and sustainable production systems, to transform and shorten the supply chain, and promote nutritional quality menus, with increased inclusion of vegetables, fruits, and legumes and reduced ultra-processed food (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In Brazil, family farming has been associated with agroecological practices, addressing not only productivity but also broader social and environmental outcomes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The economic and social benefits for family producers include generating local employment and strengthening local production (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). This is achieved by establishing an institutional market that bolsters family farming, rendering the market more predictable and stable for these farmers. A regular and predictable demand for farmers' products encourages investment in production, supports income growth, and facilitates their integration into markets (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur study examines the socioeconomic effects of direct food procurement from family farmers within the Brazilian School Feeding Program (PNAE). PNAE, a globally recognised and long-standing school feeding program dating back to 1955 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), currently serves more than 40\u0026nbsp;million students (80% of all school-aged Brazilian population) in more than 150,000 public schools (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The program aims to support students\u0026rsquo; adequate growth, biopsychosocial development, learning, and academic performance by promoting healthy eating habits through food and nutrition education, while providing meals that meet their nutritional needs during the school day (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo do that, we explore a change of the program\u0026rsquo;s rules. In 2009, Brazil became the first country to mandate at least 30% of federal funds received by local- and state governments for procuring foods for PNAE be used for direct purchases from family farmers and their organizations (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This was achieved by eliminating a well-known barrier that prevented family farmers from accessing public procurement programs and replacing it with an innovative legal instrument that removed the requirement for public bidding, enabling direct procurement from family farmers (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003csup\u003e[1]\u003c/sup\u003e These family farmers must comply with the Family Farming Law (Lei n\u0026ordm; 11.326, 2006), which characterizes family farmers in the country as those engaged in family-run, small- to medium-scale and family-based agricultural practices whose income is derived from farming activities. This simplified procurement mechanism required suppliers to comply with pricing and food safety standards. Prices were based on the average price of the products in three local markets, including transportation costs. The policy instrument allows any family farmer to sell their products anywhere in the country while prioritizing the most socio-economically vulnerable family farmers as settlement groups, indigenous, quilombola (groups descended from escaped slaves in Brazil), women and other traditional communities, and producers of organic and agroecological food from the same municipality or state as the buyer (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Family faming covers 3.9\u0026nbsp;million of the total 5\u0026nbsp;million agricultural establishments in Brazil (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe effort to integrate family farming into PNAE has two origins. First, the heterogeneous group that constitutes family farming began to gain recognition in public policy during the 1990s. This was marked by the launch of the first credit policy tailored to family farmers, a significant shift from earlier public policies that exclusively targeted large agro-export-oriented farms designed to serve national macroeconomic interests (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In the following decade, the Family Farming Act was enacted, accompanied by the creation of markets through public purchases. The second origin stems from the efforts of the Brazilian government under the \u003cem\u003ePrograma Fome Zero\u003c/em\u003e (Zero Hunger Program), which strengthened and expanded various food and nutrition security policies and included the Right to Healthy and Adequate Food in the country\u0026rsquo;s constitution. The Brazilian School Feeding Program became part of a set of policies aimed at promoting healthy and adequate diets to students and fighting hunger in rural and urban areas by strengthening family farming and productive inclusion. The National Council for Food and Nutrition Security, a key Brazilian democratic participation governing body, was key to bringing policymakers, academics, and advocates from public health, food and nutrition security, and rural development sectors together for the design and approval of the law (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Currently, Brazilian family farming represents 77% of agricultural establishments and occupies 33%of the cultivated area (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). It plays a major role, especially in horticultural production, and is particularly significant across the country, with notable prominence in the southern, northern, and northeastern regions of Brazil (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn 2022, R\u003cspan\u003e$\u003c/span\u003e 1.6\u0026nbsp;billion (US\u003cspan\u003e$\u003c/span\u003e 0.29\u0026nbsp;billion) was spent on direct procurement from family farming (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), making up 45% of the federal transfers for Brazil\u0026rsquo;s school feeding program - exceeding the legal obligation. Local- and state- governments might also allocate their own resources to match food procurement needs, although in a much smaller magnitude. This strategy/policy helps family farmers access formal markets, stimulates local economies, and improves school meal quality with fresh and minimally processed foods provided by family farmers (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The existing literature shows the influence of the Brazilian school feeding program on purchases from family farmers (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and local development (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), on the food supply and/or demand across different municipalities (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and states (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) as well as on the promotion of better diet quality (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), lower occurrence of obesity among adolescents (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and protection against the consumption of sugary beverages (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Nonetheless, the existing literature on PNAE has yet to undertake a nationwide quantitative evaluation of the ramifications of mandating direct procurement from family farmers for school feeding in Brazil on the food supply chain, particularly the family farming segment using a comprehensive socio-economic and nationwide perspective. While (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) conducted a closely related assessment using an input-output framework, the analysis was limited to a specific Brazilian state.\u003c/p\u003e\u003cp\u003eThis paper contributes to the available literature on PNAE by adding an economic dimension to analyse the impacts. By exploring the extent to which the Brazilian program can affect the domestic economy, this study highlights the sectoral interdependencies between family farming segments and other economic activities. The novelty of this study lies in its capacity to furnish an impact analysis that distinguishes between family and non-family production segments. The literature suggests that partially reallocating food procurement resources toward direct purchases from family farms can enhance local economic dynamism, income and employment, albeit with potential trade-offs from reducing purchases from non-family farmers. Balancing these trade-offs is critical for assessing the affordability of these policies and their potential for continuation or scale-up. This distinction is essential for informing the design of targeted policies and understanding the role of school feeding procurement in promoting planet-friendlier and more equitable agriculture practices. The study contributes as a proof of concept, providing empirical evidence that structured food procurement policies can generate measurable socioeconomic benefits. As international organizations increasingly recognize the role of public procurement in transforming food systems, this study offers timely and globally relevant insights. It advances broader discussion on how targeted institutional demand can support inclusive rural development, economic resilience, and sustainable food systems.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eAnalytical and conceptual framework\u003c/h2\u003e\u003cp\u003eWe developed an empirical strategy that combines an econometric and an Input-Output (IO) model, as described in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The econometric model examines how mandatory procurement from family farmers influenced their production and demand using data from the Brazilian Agricultural Censuses (before and after the change in PNAE\u0026rsquo;s mandatory procurement) and public schools\u0026rsquo; food procurement. The results are then integrated into the IO model, which estimates the broader economic effects, including GDP, employment, income, and taxes, by capturing the interdependencies among various sectors of the Brazilian economy and considering the trade-off from replacing demand for non-family farmers by family farmers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe socioeconomic impacts encompass income and employment conditions that collectively shape livelihoods and well-being. In the context of school purchases, it extends beyond direct transactions, stimulating broader economic activity through a chain of supplementary acquisitions. School suppliers, for instance, procure inputs from other sectors to meet the food demands of schools, creating ripple effects across the economy according to sectoral interdependencies. In this analysis, the mechanisms behind socioeconomic impacts of the PNAE local procurement policy arise from key structural differences between family farms and non-family farms, which influence economic outcomes such as employment, income, GDP, and taxes. Family farming segments are more labour-intensive, meaning a shift in procurement toward family farming potentially increases demand for labour, thereby boosting employment. Additionally, family farmers are more likely to spend their income locally, also potentially creating stronger multiplier effects (e.g., additional rounds of spending) in rural economies by stimulating demand for goods and services, which contributes to higher local income and GDP. This contrasts with non-family farming segments, which are often more capital-intensive and generate less localized economic activity. These causal pathways, which include changes in labour demand, localized spending, and tax contributions, are captured through the input-output impact analysis and help explain the broader socioeconomic effects of the policy.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEconometric model\u003c/h3\u003e\n\u003cp\u003eFor the first part of the analysis, we use a panel dataset covering the years 2006 and 2017, which represent the pre-and post-implementation periods of the PNAE\u0026rsquo;s 2009 family farming-based rule. The dataset includes information on agricultural production value and pricing obtained from the two Brazilian Agricultural Censuses of the period, categorised by municipality and sector (agriculture; livestock; forestry, fishery, and aquaculture; among others) and further stratified by family and non-family farming.\u003c/p\u003e\u003cp\u003eSince all Brazilian municipalities are equally exposed to the PNAE rules and required to comply with the food procurement from the family farming component, the panel dataset also incorporates national food procurement data provided by FNDE by municipality to understand which municipalities complied or not with the change in PNAE rules. The specifics of food procurement from family (and non-family) farmers - including data on expenditures - have been publicly accessible through the Accountability Management System (SiGPC) (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) since 2013. We use the 2017 PNAE procurement data to align with the year of the agriculture census. Schools procure a wide variety of foods and beverages, including fruits, vegetables, cereals, milk, meat, and ready-to-eat items. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e highlights the top 20 most purchased food categories in 2017. More information about the data for the econometric exercise is provided in Supplementary Appendix S.1.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMain products purchased by schools, SIGPC 2017\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProduct\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProportion of the School Purchases\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMilk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChicken\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBanana\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalty snacks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBread\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit Pulp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeans\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit Juice - ultraprocessed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePasta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSugar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eApple\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePotato\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEggs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJerky meat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTomato\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCocoa powder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDairy beverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eNotes: Over 300 product categories are purchased, each classified individually or grouped under the \u0026ldquo;Others\u0026rdquo; category based on their proportional significance to total school purchases.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe panel allows for the identification of municipalities that adhere to the PNAE rules governing food purchases from family farming in 2017. Compliant municipalities are those whose expenditures comprised 30% or more of family farming products that year. We compare these compliant municipalities with non-compliant ones, the latter serving as control groups, using a differences-in-differences (DiD) method. The goal is to understand the impacts on the production value of agriculture, livestock and forestry from family farmers among compliers. We expect that the compliers have purchased more agricultural, livestock and forestry products from family farmers (a positive effect) and less from non-family farmers (a negative effect). To mitigate potential sample selection bias related to PNAE rule-compliant municipalities, we include a set of fixed effects (Fes) \u0026ndash; municipal, year - and covariates \u0026ndash; average prices as well as local market conditions that affected prices (see more details on the relevance of the controls in Supplementary Appendix S.1).\u003c/p\u003e\u003cp\u003eHowever, as with any DiD approach, our analysis relies on key assumptions, particularly the parallel trends assumption and no anticipation of the policy. Due to data limitations, we observe only one pre-treatment period, which prevents us from formally assessing the feasibility of the parallel trends assumption\u0026mdash;that is, whether compliant and non-compliant municipalities exhibited similar trends in agricultural production prior to the policy. This limitation should be considered when interpreting the results, as unobserved differences in pre-treatment trends could potentially bias our estimates. Despite this constraint, we take steps to strengthen the credibility of our findings by including robustness analysis in the supplementary material. In other words, our identification strategy assumes that differences in agricultural purchases between compliant and non-compliant municipalities remain constant over time. However, it is possible that compliant municipalities made additional efforts to increase purchases from family farmers after the reform, potentially creating spillover effects that prompted non-compliant municipalities to partially adjust their behaviour as well. These dynamics could introduce a conservative bias, causing an underestimation of the true impact of compliance. Therefore, our results should be interpreted as a lower-bound estimate of the policy's effects.\u003c/p\u003e\u003cp\u003eThe econometric regression below describes the estimation for agricultural, livestock and forest products and distinguishes the production value into family and non-family producers:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{ln}\\left(valu{e}_{imst}\\right)={\\alpha\\:}_{0}+\\beta\\:Complie{r}_{m}.Pos{t}_{t}+\\gamma\\:ln\\:\\left(pric{e}_{imst}\\right)+{\\lambda\\:}_{m}+{\\theta\\:}_{t}+{u}_{imst}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:ln\\left(value\\right)\\)\u003c/span\u003e\u003c/span\u003e is the log of the production value of product \u003cem\u003ei\u003c/em\u003e, in municipality \u003cem\u003em\u003c/em\u003e, allocated in sector \u003cem\u003es\u003c/em\u003e (agriculture, livestock or fishing/forestry), and in time \u003cem\u003et\u003c/em\u003e (the years 2006 and 2017). \u003cem\u003eLn(price)\u003c/em\u003e is the logarithm of the price with the same dimensions. \u003cem\u003eα\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e is the constant, \u003cem\u003eλ\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e is a county-fixed effect, \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e is a time-fixed effect, and \u003cem\u003eu\u003c/em\u003e\u003csub\u003e\u003cem\u003eimsjt\u003c/em\u003e\u003c/sub\u003e is the econometric error term. Finally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{}\\:\\)\u003c/span\u003e\u003c/span\u003eis the parameter that measures the effects of our variable of interest (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Complier.Post\\)\u003c/span\u003e\u003c/span\u003e) that captures the effect of the PNAE program in 2017.\u003c/p\u003e\u003cp\u003eWe run the regression for all products and production value by municipality separated by family farmers and non-family farmers. The regressions were weighted by the 2006 baseline production value, enabling our results to be interpreted as national averages. Specifically, the key coefficient in our model represents the weighted average impact of policy compliance across products within the same sector, with weights determined by the contribution of each product to the sector's total production value.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the percentage change of production value observed in family production of agriculture, livestock, and forestry products following the implementation of the PNAE rule for family farming purchases. Family farmers in compliant municipalities experience positive effects, particularly in the agricultural and livestock sectors. The average increase in family farming production value in compliant municipalities is 9\u0026middot;8% for agricultural products and 4\u0026middot;5% for cattle products. The findings suggest a positive effect of PNAE in promoting productive agricultural and livestock activities in family farming. The effect for fishing and forestry is, on the other hand, negative, although very small in absolute terms, as this sector represents only 1\u0026middot;6% of total PNAE expenditures.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImpacts of complying with the rules of PNAE in 2017 on family farming production\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAgriculture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLivestock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eForestry/ Fishery\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEffect on PNAE rule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026middot;098***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u0026middot;045***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0\u0026middot;019***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(0\u0026middot;001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0\u0026middot;002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(0\u0026middot;006)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,727,322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e677,436\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e148,847\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Clustered standard errors by municipality in parentheses. P-values: * p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;01.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo compute the changes in final demand for both family farmers and non-family farmers that will be used in the IO model, we use the average effect estimated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. We assume that the increase in production value from family farmers results in a corresponding decrease in production value from non-family farming products. This assumption is based on the fixed PNAE expenditures per student, implying that any increase in purchases from family farmers directly reduces purchases from non-family farmers. This assumption simplifies the analysis by treating the PNAE budget as a zero-sum game, where gains for family farmers result in losses for non-family farmers. While this approach provides a clear-cut way to estimate the impact, it does not fully capture the dynamics of agricultural markets. However, our analysis indicates that the PNAE program\u0026rsquo;s procurement volume represents a relatively small share of the overall food market \u0026ndash; approximately 0.02% of the total food market and 0.3% of the family farmer\u0026rsquo;s food market. This suggests that the rule change is unlikely to have a significant impact on broader price and market dynamics. If the PNAE program represented a larger portion of the market, changes in the program could potentially influence prices.\u003c/p\u003e\u003cp\u003eThe changes in total purchases (in Brazilian reais, R\u003cspan\u003e$\u003c/span\u003e) were used to design the shock in the IO impact analysis during the second part of the analytical framework, better explained in the next section.\u003c/p\u003e\n\u003ch3\u003eInput-output model\u003c/h3\u003e\n\u003cp\u003eWe estimate a national IO matrix disaggregated into family and non-family farming agriculture production and perform an impact analysis to quantify the effects of PNAE on the main macroeconomic variables. The IO matrix depicts the functioning of an economic system considering the interrelationships among sectors to produce goods and services. The IO model is designed to show how changes in consumer demand impact the overall economy based on several assumptions, including that each sector produces using inputs in fixed proportions and with constant returns to scale. It also assumes fixed technical coefficients and output prices, and linear relationships between sectors. The fixed price assumption is considered reasonable for this study, as it focuses on isolating the immediate direct and indirect economic effects of PNAE, where price volatility is not the central focus and price adjustments may be limited. The primary interest lies in the sectoral economic linkages and labour demand induced by changes in PNAE procurement. This section describes the procedures and data employed in the disaggregation process and introduces the IO model for the impact analysis.\u003c/p\u003e\n\u003ch3\u003eDisaggregation of family and non-family production\u003c/h3\u003e\n\u003cp\u003eThe most recent public and official version of the Brazilian IO matrix, provided by the Brazilian Institute of Geography and Statistics (IBGE), is from 2015. It includes 68 sectors and 128 products. However, it does not differentiate between family and non-family agricultural production, which is necessary to assess the direct effects of the policy. This paper advances methodologically by breaking down the agricultural sectors into family and non-family segments, using data from the 2017 Brazilian Agricultural Census (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), the primary source for this type of information. To match with the year of the agricultural census, we opted to use the IO matrix of 2017 estimated by the Regional and Urban Economics Lab \u0026ndash; NEREUS (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) based on official economic data. The agricultural sectors of the Brazilian Agriculture Census are explicitly represented in the national IO matrix, which facilitates the pairing of information between them. We maintain the original sectoral structure of the agriculture sectors in the IO matrix and create a separate family and non-family farming segment for each of these economic activities in the estimated IO matrix: a) non-family farming agriculture, b) family farming agriculture, c) non-family farming livestock, d) family farming livestock, e) non-family farming forest/fishery and f) family farming forest/fishery. For this analysis, the Brazilian IO matrix exhibits a total of 29 sectors. A detailed description of the sectoral resolution and breakdown approach is given in Supplementary Appendix S.2.\u003c/p\u003e\u003cp\u003eThis Brazilian IO matrix for family farming is a novelty of this study. It can support future investigations on family farming, especially because the economic literature still underexploits the inter-dependence relations of family production in Brazil. Part of this is attributed to the limited availability of detailed statistical information on the flows of goods and other factors specific to family-related production.\u003c/p\u003e\n\u003ch3\u003eInput-output impact analysis\u003c/h3\u003e\n\u003cp\u003eInput-output impact analysis is a valuable tool for understanding how the economy and its sectors respond to policy-driven or behaviour-driven changes, providing insights into the effectiveness and consequences of the interventions. This analysis involves comparing the input-output matrix results both before (ex-ante) and after (ex-post) the changes occur. The basic IO model, its applications and terminologies are provided in (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) while the technical description of the model is available in Supplementary Appendix S.2.\u003c/p\u003e\u003cp\u003eThis economic impact study estimates the effects of using PNAE resources to purchase food directly from family farming. Direct impacts are linked to the additional monetary flow to family production segments whereas indirect impacts are due to intersectoral transactions flowing from the PNAE incentives. Here we consider type 1 multipliers, which incorporate direct and indirect effects to express the total effect on the economy in terms of output, employment, income, GDP, and taxes of a unit increase in final demand for each sector. The employment multiplier is a measure of the number of jobs created by the sector to carry out the increased production activity. In 2017, the FNDE transferred R\u003cspan\u003e$\u003c/span\u003e3\u0026middot;8\u0026nbsp;billion to PNAE food procurement, and the municipalities complemented those resources with R\u003cspan\u003e$\u003c/span\u003e 591\u0026nbsp;million. Therefore, R\u003cspan\u003e$\u003c/span\u003e 4\u0026middot;47\u0026nbsp;billion is the total value of the shock applied to the final demand in the IO model, and more specifically, to the agriculture segments of family and non-family production. Although the analysis assumes a fixed total PNAE funding, local variations in municipal co-financing may amplify or mitigate its impacts in specific regions. These variations could influence the geographical distribution of benefits without altering the total federal funding or the overall interpretation of the national-level impacts of PNAE.\u003c/p\u003e\u003cp\u003eThe simulation scenario is designed based on the share of food purchases in 2017 grouped by food category and classified according to the sectors of the IO matrix. Using the SiGPC data (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), we attributed the portion of FNDE resources to each of the sectors under scrutiny and adjusted the values using the results from the econometric evaluation to reflect the food procurement from family farming demand that complies with the 30% requirement of food procurement from family farming. This reflects the primary focus on family farming procurement rather than on wholesalers and other distributors, which is controlled for in the econometric segment and consequently, in the shock. The final distribution of the shock and corresponding values are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe distribution of shock across family and non-family segments (in R\u003cspan\u003e$\u003c/span\u003e million)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSectors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-family farming\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFamily farming\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgriculture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivestock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForest/fishery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Estimated using the coefficients from Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Values were calculated based on the total expenditures of PNAE in 2017 (R$ 4\u0026middot;47\u0026nbsp;billion) and the participation of agriculture, livestock, and forest/fishery in those expenses using SIGPC data.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eThe macroeconomic effects of PNAE\u0026acute;s direct procurement mandate from family farming\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea shows the macroeconomic and sectoral impacts of the abovementioned shifts in economic activity for all sectors and family farmers in agriculture and livestock. The macroeconomic effect refers to the net national effect or the aggregate economic impact of the policy on the Brazilian economy as whole. It captures the overall balance of gains and losses across all sectors. These results should be interpreted as the change in million R\u003cspan\u003e$\u003c/span\u003e relative to the input-output baseline (before PNAE). The economic impacts of PNAE depend upon its productive structure and the total amount of resources FNDE transfers to PNAE each year. This is captured in our results. From a nationwide perspective, there is a positive net impact of PNAE on national GDP. This effect is small in magnitude, R\u003cspan\u003e$\u003c/span\u003e 15\u0026nbsp;million (a total GDP increase of 0\u0026middot;0003%, or an increase of 0\u0026middot;004% of the PNAE GDP from the baseline). Previous school-feeding assessments have found similar positive impacts on GDP for different contexts and countries (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The total net income and tax results are negative but relatively minor, while national output decreases by R\u003cspan\u003e$\u003c/span\u003e 28\u0026nbsp;million. This decline stems from sectoral characteristics and interdependencies, whereby a reduction in non-family farming demand reduces production and subsequently input purchases from other sectors, causing the observed decrease. Although these results may not have substantial implications for the broader context of the Brazilian economy, their socioeconomic effects demonstrate the importance of family farming-oriented policies to potentially address existing and emerging social issues in rural areas.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e(a) Macroeconomic and sectoral effects of family farming procurement under PNAE, in R\u003cspan\u003e$\u003c/span\u003e million\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe net gain is the strongest in family farming segments, especially agriculture, but while benefiting family farming production, PNAE\u0026rsquo;s success in buying directly from family farming shifts production and slightly shrinks non-family/conventional agriculture. This outcome brings the program closer to attaining the objective of procuring food from family farming operations, which is to serve as a to be an instrument to support local and smallholder farmers and to help integrate them into markets (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This is observed in the sectoral results of Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, which reveals gains in output resulting from the reservation rule of PNAE for purchases from family production segments of R\u003cspan\u003e$\u003c/span\u003e 390\u0026nbsp;million (an increase of 0\u0026middot;61%). In Brazil, 67% of all workers involved in agricultural activities are family farmers, occupying 77% of the rural establishments registered.\u003c/p\u003e\u003cp\u003eFamily production agriculture benefits economically the most from the policy, with an increase of 0\u0026middot;65% in income. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that when giving access to family farmers, the program provides an opportunity to improve living conditions in terms of employment. It displays the sectoral effects on employment expressed in absolute terms (or man-equivalent-year). Overall, the change in the PNAE rule implies a net effect of approximately 24 thousand direct and indirect jobs at national level. These are mostly concentrated in family farming agriculture, with the creation of 27,243 job opportunities. Non-family farming, agriculture and livestock segments lose approximately 3 thousand jobs due to the substitution effects. Both family and non-family livestock segments play a key role in the PNAE value chain, being responsible for 11\u0026middot;8% and 18\u0026middot;5% of the total employment effect, respectively. This decomposition highlights \u0026lsquo;winners and losers\u0026rsquo; resulting from the policy, where winners are those experiencing increases due to the higher demand for their goods and services, while losers refer to sectors facing declines as resources are reallocated or demand shifts within the economy.\u003c/p\u003e\u003cp\u003eOther sectors absorb the effects differently. In addition to the economic relationships between producers (family and non-family farmers) and the consumer (schools, in the case of school feeding), there are additional, often stronger, linkages between these producers and other sectors of the economy. These indirect impacts are due to intersectoral transactions flowing from the changes in school purchases from family and non-family farmers to the linked sectors. They account for 0\u0026middot;63% of the total increase in the number of jobs, reflecting the varying labour intensity across different economic activities.\u003c/p\u003e\u003cp\u003ePNAE\u0026rsquo;s regulatory framework connects family farming and institutional markets, whereby the federal budget is allocated to the acquisition of food for school feeding. The government tax losses from the increase in the purchases of family and decrease in non-family products is R\u003cspan\u003e$\u003c/span\u003e 3\u0026middot;8\u0026nbsp;million in tax collection annually. Non-family production is more consolidated and dominated by larger producers, which contribute significantly to government tax revenues through higher utilization of labour, inputs, and greater overall revenue generation. From a socioeconomic perspective, and given the evidence provided, this total accumulated loss in tax collection represents an annual cost from the government side of R\u003cspan\u003e$\u003c/span\u003e 160 per job created in the economy. This is of paramount importance for promoting healthier and more sustainable food systems, as well as generating jobs. Most importantly, to address food insecurity within and outside the school environment while reducing poverty. As argued in (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), more financial and political incentives are, hence, necessary and they could help develop shorter and closer production chains to schools but also enhance local development dynamization.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe role of family and non-family farming in the economy\u003c/h3\u003e\n\u003cp\u003eFamily farming is seen as a key element in building sustainable and healthy food systems but has also been identified as socially vulnerable. They are characterised by low incomes, and proportionally higher food insecurity and nutrition than urban areas, leading to a constant risk of rural-urban migration. Among our findings, family and non-family production accounted for 5\u0026middot;3% of the Brazilian GDP in 2017, of which 21\u0026middot;7% is family-farming-led. However, in an input-output analysis conducted in 1996 (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), family farming comprised approximately one-third of the Brazilian agribusiness landscape, indicating the sector has been shrinking.\u003c/p\u003e\u003cp\u003eIn the agriculture sector, family farmers have usually lower incomes than farmers from non-family agriculture. According to the 2017 Census, the annual income of almost 44% of family farmers varies between US\u003cspan\u003e$\u003c/span\u003e1250 and US\u003cspan\u003e$\u003c/span\u003e12500 whereas for 42% the income remains below US\u003cspan\u003e$\u003c/span\u003e1250 per year. This reflects the small scale of farms as well as the lack of physical and human capital, which is a determinant factor in low-income levels and high poverty rates (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). A growing output and GDP effect have the potential to help address these issues. More importantly, they drive the creation of employment opportunities for family and non-family segments.\u003c/p\u003e\u003cp\u003eThe multipliers presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e are outputs derived from the input-output model. Comparing these multipliers, the increase in the PNAE demand would lead to a larger multiplying GDP effect on agriculture and livestock family segments than non-family ones. A similar multiplier effect is observed for the income of livestock and forest and fishery sectors, where there is a larger effect on the family over non-family sectors. In contrast, family agriculture producers experience a lower income multiplier effect than non-family. Despite not specifying the mechanisms driving the employment impacts, the input-output analysis provides a general estimate of demand for additional labour across sectors and segments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInput-output type 1 multipliers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSectors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOutput\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEmployment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGDP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTax\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgriculture (non-family)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgriculture (family farmers)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivestock (non-family)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivestock (family farmers)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForestry/Fishery (non-family)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForestry/Fishery (family farmers)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtractive Sector\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMachinery and Equipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFood Beverages Industry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther Manufacturing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElec. Gas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater.Waste\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsumer Prod\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommerce\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransportation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccom. And Food services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfo. Communication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReal Estate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScient. Technical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdministrative Services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernment Services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrivate Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrivate Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArts and Culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther Services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomestic Services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMandating that a fraction of the Brazilian school food procurement national funding be used to source directly from family farmers - prioritizing the most socio-economically vulnerable and those with the most sustainable food systems (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) -, extends the impacts of the program beyond providing healthy meals to students. In fact, we found a multiplying effect of the program\u0026acute;s direct food procurement from family farmers on GDP. For every R\u003cspan\u003e$\u003c/span\u003e 1.00 increase in demand for family farming and family livestock products for the PNAE, Brazilian GDP grow by R\u003cspan\u003e$\u003c/span\u003e 1.52 (agriculture) and R\u003cspan\u003e$\u003c/span\u003e 1.66 (livestock), respectively.\u003c/p\u003e\u003cp\u003eThis approach can impact employment and income levels within this segment. Such policies potentially foster sustainable food systems (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) by integrating nutrition, food and agriculture through the strengthening of local food production and processing (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). This integration is achieved by engaging local, small and medium-sized food enterprises, women, youth and/or other vulnerable groups, including settlement, indigenous, quilombola and other traditional communities, while simultaneously promoting healthy and sustainable diets (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Hence, this dynamic also potentially reduces barriers to market participation and contributes to more inclusive food systems.\u003c/p\u003e\u003cp\u003eOur findings on the socioeconomic impacts of PNAE highlight the importance of food procurement from family farming policies in supporting local communities, and the need to strengthen regulatory policies to promote healthier and more sustainable food systems in Brazil. PNAE generates positive primary and secondary benefits, including increased income, job creation, potentially contributing to improved livelihoods for family farmers. It also supports the preservation of food landscapes and local cultural practices, and the promotion of environmentally friendly, sustainable production systems. A third of the food used in the preparation of school meals is required to be sourced from these sustainable family farming practices (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe shift in the food procurement regulations enacted in 2009 produced a net national effect of R\u003cspan\u003e$\u003c/span\u003e15\u0026nbsp;million increase in GDP and the creation of approximately 24 thousand jobs. However, this was accompanied by an annual tax loss of R\u003cspan\u003e$\u003c/span\u003e 160 (approximately US\u003cspan\u003e$\u003c/span\u003e 32) per job created, which can be attributed to changes in the sectoral composition of food supply to schools and the demand for intermediate inputs. As the policy shift favoured more labour-intensive family farming sectors over higher-taxed non-family farming sectors, the overall tax revenue generated by the economy decreased. Most of the jobs and positive economic results are more pronounced for family farming producers, whose income increases by R\u003cspan\u003e$\u003c/span\u003e 39\u0026nbsp;million (or approximately US\u003cspan\u003e$\u003c/span\u003e 8\u0026nbsp;million) and observed a creation of 27,243 jobs. The number of jobs created is relatively small compared to the total number of people employed in family farming, but this increase is significant given the trend of declining employment in family farming over recent decades. This highlights the importance of policy interventions in reversing negative employment trends and boosting economic activity within this sector. Of the 15\u0026nbsp;million people employed in the Brazilian agriculture sector, 10\u0026nbsp;million are engaged in family farming. In 2017, family farmers contributed an annual production value of R\u003cspan\u003e$\u003c/span\u003e106.5\u0026nbsp;billion or US\u003cspan\u003e$\u003c/span\u003e 17,2\u0026nbsp;billion (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Family agriculture producers are the most economically affected by the policy, resulting in a 0.65% increase in income.\u003c/p\u003e\u003cp\u003eThrough a substitution effect, where food procurement from non-family agriculture farmers reduces to accommodate the increase in purchases from family farmers, the new mandate implies modest losses for non-family farmers. This segment has historically benefited from substantial governmental support, which has reinforced its significant contribution to the Brazilian economy. Our results show that giving access to family farmers over other suppliers does not cause significant economic harm. Moreover, the social, environmental, and cultural benefits\u0026mdash;while not accounted for in this analysis\u0026mdash;are important factors that warrant further exploration in future studies. These benefits emphasize the value of strengthening family farming procurement programs. More importantly, it has important implications for rethinking the global food system. The growth in employment, incomes and GDP offsets the losses identified, such as tax reductions. Since the 1980s, the modernisation of agriculture, the food industry, and retail sectors has reshaped the landscape of food production and consumption. These transformations have been the major drivers of poor health and environmental degradation, particularly through changes in food systems and dietary patterns associated to reduced biodiversity (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Food systems have become increasingly concentrated in distribution, commercialisation, and retail, especially within the food industry and supermarket chains, with production decisions shaped by the economic logic of these sectors (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). In this context, reallocating resources towards family farmers has the potential to challenge and shift this entrenched dynamic, which has been consolidated over the past four decades.\u003c/p\u003e\u003cp\u003eDespite the recent advances of PNAE, and its fragrant potential, that have led to both economic and social benefits, these remain limited, in part because not all local and state governments reach the 30% minimum mandated threshold of direct procurement of locally sourced and family-produced food. If all Brazilian municipalities complied with the rule, the impacts on jobs and total GDP would be higher. Access to all food procurement data by municipality facilitates monitoring and enforcement, potentially lowering costs for policymakers, yet the extent of these potential cost reductions remains to be quantifiable. This investigation brings evidence that should encourage future research and dialogue into the opportunities available to align the socioeconomic and health impacts of the school feeding program within a broader research agenda on healthy diets from sustainable food systems. By doing so and overcoming socioeconomic limitations, especially via investments that increase the sector\u0026rsquo;s dynamism, school meals can help achieve multiple SDGs.\u003c/p\u003e\u003cp\u003eThese dimensions, including sustainability-related outcomes, should be explored in future studies. Acknowledging the limitations of the IO model, future research could build upon our findings by employing a Computable General Equilibrium (CGE) approach using the estimated IO matrix to capture price dynamics, factor substitutions, and more nuanced behavioural responses from both the socioeconomic and environmental perspectives. This would provide a more comprehensive analysis of the economic impacts of PNAE, an aspect beyond the scope of this study. Several limitations of this paper, such as simplifying assumptions about production value shifts between family and non-family farmers, the focus on municipal-level data, and the inability to test the parallel trends assumption, could be addressed in future research. Specifically, the assumption that an increase in production value for family farmers corresponds to a decrease for non-family farmers oversimplifies the complexities of agricultural markets, overlooking price differences between farm types. Additionally, while the focus on municipal-level data assumes that the effects of PNAE compliance are primarily local, we note that approximately 88.8% of municipalities in Brazil can be supplied by local family farmers. Finally, although the empirical approach provides valuable insights, the inability to test the parallel trends assumption presents a limitation.\u003c/p\u003e\u003cp\u003eThe multifaceted feature of PNAE lays the foundation for a healthier and more resilient future. In this study, we advance in finding that well-designed school feeding programs can contribute to economic development more equitably.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Bloomberg Philanthropies, through a partnership between the University of North Carolina at Chapel Hill and the Center for Epidemiological Studies in Nutrition and Health (NUPENS) at the University of São Paulo.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe input-output matrix for family farming generated for the study is available as SI. Both the econometric and input-output models are summarised in the Supplementary Appendix, including mathematical descriptions and other relevant information. Additional data is available on request to TDO and PCP.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript does not involve human or animal participants. It is our original work and has not been published elsewhere in any form or language.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTDO developed the input-output model, conducted the analysis, interpreted the results, and developed the figures. PCP developed the econometric model, conducted the analysis and interpreted the results. TDO, PCP and LPE wrote the manuscript and collected the data. PCP, LPE and ACD were involved in conceptualization. ACD was responsible for the funding acquisition. All authors commented on the manuscript draft and had final responsibility for the decision to submit for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work the authors used ChatGPT in order to review grammar, cohesion and clarity of the text. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGait\u0026aacute;n-Cremaschi D, Klerkx L, Aguilar-Gallegos N, Duncan J, Pizzol\u0026oacute;n A, Dogliotti S, et al. Public food procurement from family farming: A food system and social network perspective. Food Policy. 2022 Aug;111:102325. \u003c/li\u003e\n\u003cli\u003eKelly S, Swensson LFJ. Leveraging institutional food procurement for linking small farmers to markets. FAO; 2017. (FAO Agricultural Development Economics Technical Studies). \u003c/li\u003e\n\u003cli\u003eBoklis-Berer M, Rauber F, Azeredo CM, Levy RB, Louzada ML da C. School meals consumption is associated with a better diet quality of Brazilian adolescents: results from the PeNSE 2015 survey. 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Available from: https://linkinghub.elsevier.com/retrieve/pii/S1574007206030556\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e These family farmers must comply with the Family Farming Law (Lei n\u0026ordm; 11.326, 2006), which characterizes family farmers in the country as those engaged in family-run, small- to medium-scale and family-based agricultural practices whose income is derived from farming activities\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7717673/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7717673/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn 2009, the Brazilian School Feeding Program (PNAE) became the first national initiative worldwide to mandate that at least 30% of federal resources - previously spent on public tenders – be directed toward the direct procurement of food from family farmers. In Brazil, these producers are more likely to adopt environmentally sustainable agricultural practices. This policy, therefore, aimed to both improve students’ diet quality and strengthen local food systems through support for family farmers. Despite its ambition, the nationwide socioeconomic effects of this procurement reform remain understudied. This paper aims to fill this gap by using an integrated economic modelling framework which combines a differences-in-differences and input-output model. With the differences-in-differences model we estimate the change in family and non-family farmer production value due to the modification in the PNAE procurement requirements. The input-output model was used to assess the effects on employment and gross domestic product (GDP), with a representation of family and non-family farming productive segments using information provided by the Brazilian Agricultural Census. Our findings indicate a positive socioeconomic effect of the program by improving employment and GDP. During the follow-up period, changes in PNAE food procurement policies generated a net increase of R$15 million in GDP and approximately 24 thousand new jobs nationally. Most of the jobs and positive economic results were greater for family farmers, whose income increased by R$ 39 million (or approximately US$ 8 million). Those gains can be attributed to the economic structure depicted in the estimated input-output, which identified livestock family production as a labour-intensive economic segment. Economic modelling suggests that PNAE has the potential to promote more equitable economic development. Addressing the identified compliance problems in several municipalities could enhance the estimated effects. Improved monitoring and provision of technical support to both local school feeding program managers and family farmers can enhance compliance and contribute to the promotion of healthier, more equitable and sustainable food systems.\u003c/p\u003e","manuscriptTitle":"Socioeconomic Effects of the Direct Procurement from Family Farming in the Brazilian School Feeding Program","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-13 17:25:05","doi":"10.21203/rs.3.rs-7717673/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-30T12:01:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-28T12:42:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92614928114077648109363603405533103114","date":"2025-10-25T21:12:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118109413724931031661732787536415825258","date":"2025-10-25T18:56:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-24T14:41:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-15T22:21:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2368256297974558931146982734675784068","date":"2025-10-13T13:43:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209149740557027846968676224179078549719","date":"2025-10-02T20:20:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-30T20:03:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-30T11:15:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-30T11:15:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2025-09-26T04:39:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a2e4f6e-abf9-4f0a-ba79-64bc471efd27","owner":[],"postedDate":"October 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:01:27+00:00","versionOfRecord":{"articleIdentity":"rs-7717673","link":"https://doi.org/10.1007/s43621-025-02396-y","journal":{"identity":"discover-sustainability","isVorOnly":false,"title":"Discover Sustainability"},"publishedOn":"2025-12-14 15:57:34","publishedOnDateReadable":"December 14th, 2025"},"versionCreatedAt":"2025-10-13 17:25:05","video":"","vorDoi":"10.1007/s43621-025-02396-y","vorDoiUrl":"https://doi.org/10.1007/s43621-025-02396-y","workflowStages":[]},"version":"v1","identity":"rs-7717673","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7717673","identity":"rs-7717673","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}