Pesticide maximum residue limits and Mercosur–EU grain trade Open Access

Adhering to trading partners' food regulations has become essential for exporters. Such regulations, including permissible levels of chemical residues, underpin the 3 S triad (salubrity, safety and sustainability) reflecting product and process quality by mitigating risks to the environment, consumers and farmers. Risk assessment guides regulatory agencies when authorizing pesticide use in food crops (Akiyama et al., 2024). Consequently, chemical inputs are monitored and controlled through market-specific rules arising from differing risk perceptions and assessments (Xiong and Beghin, 2014).

Regulatory asymmetries impose adaptation costs on exporters, who must adjust production processes to satisfy each market's requirements. The EU's ban on the fungicide mancozeb in 2020 illustrates how divergent MRL regulations shape international markets. To preserve soybean exports to the EU, Brazilian producers must switch to alternative fungicides, raising production costs by 7.6% and potentially reducing output by 1.3% (Ben Naim and Cohen, 2023). If farmers opt not to comply, soybean shipments could fall by 3.5%, allowing the United States to capture displaced market share (USITC, 2020). Additionally, Brazil and other tropical nations face different pest pressures than temperate regions due to high humidity, warmer temperatures and absence of cold winters that interrupt pest cycles. Between 2010 and 2020, 11.1% of agricultural shipments rejected at EU borders exceeded pesticide residue limits (RASFF, 2022).

Countries set maximum residue limits to protect consumers, producers and ecosystems. Divergent standards across markets introduce variability in international trade. When national thresholds fall below Codex limits, measures may restrict trade and be viewed as protectionism (Xiong and Beghin, 2014). Shipments exceeding limits face rejection, destruction or rerouting, imposing costs on exporters (USITC, 2020). Conversely, exporters complying with demanding standards often experience expanded market access (Hejazi et al., 2022; Traoré and Tamini, 2021).

In high-income markets, consumer expectations regarding safety, environmental stewardship and product quality tend to be elevated (Burnquist et al., 2011; Ferro et al., 2015). While bulk commodities such as soybeans and corn generally trade under uniform quality grades, attributes, such as minimal pesticide residues, can command price premiums. To address invisible risks, policymakers in these markets implement regulations that monitor factors like microbial contamination, chemical residues and other non-observable traits. For exporters, meeting these requirements signals compliance with partner standards and supports continued trade flows. However, achieving conformity requires access to technologies and supporting infrastructure, which may pose financial and technical challenges for producers in less developed economies (Hejazi et al., 2022).

Studies examining EU MRL requirements indicate that exporters satisfying stricter thresholds often experience higher demand due to consumer preferences for safety and quality (Swinnen, 2019). However, when compliance costs exceed price premiums, regulations may function as nontariff barriers (Drogué and DeMaria, 2012; Ferro et al., 2015; Hejazi et al., 2022; Traoré and Tamini, 2021; Xiong and Beghin, 2014). Research adopts a dual framework recognizing that MRL policies shape both production costs and importers' purchasing choices (Fiankor et al., 2021a, b; Jiang et al., 2023; Traoré and Tamini, 2021; Xiong and Beghin, 2014).

We quantify how regulatory divergence in MRLs affects Mercosur–EU trade in soybeans and corn. Unlike previous papers that isolate either exporter cost burdens or importer demand shifts, this study explores both dimensions jointly. It compares the rigor of standards applied by Mercosur countries and EU members for identical products, assessing how asymmetries in perception of quality and variation in compliance expenses influence bilateral trade flows. The question is whether consumer-driven demand enhancements prevail over exporter cost increases, or vice versa. Addressing this question supports sector-specific policy advice for grain markets that constitute components of Mercosur exports and EU imports.

Meta-analyses indicate that the trade impacts of food standards vary according to sector, geographic scope and the type of regulation (Li and Beghin, 2012; Santeramo and Lamonaca, 2019). This paper concentrates on the soybean and corn markets, in contrast with broader studies that cover multiple agricultural goods without issuing tailored policy guidance (Fiankor et al., 2021a, b; Jiang et al., 2023; Xiong and Beghin, 2014). By focusing on these two staple grains, exports for Mercosur and imports for the EU, the analysis yields recommendations applicable to this sector. Mercosur members are chosen because their MRL thresholds tend to be less demanding than those of high-income countries, yet compliance is critical to avoid forfeiting access to destinations such as the EU (Fiankor et al., 2021a, b; Xiong and Beghin, 2014). Unlike examinations of WTO Sanitary and Phytosanitary (SPS) measures, which typically employ qualitative approaches, this study applies a quantitative framework to MRL standards.

The production and trade of corn and soybeans present challenges in relation to pesticide use and MRL policy. Bulk shipments are routinely blended from multiple origins, complicating traceability to individual farms; exporters must therefore meet the lowest MRL across all destination markets (USITC, 2020). As commodity products, these grains can command price premiums when quality attributes, such as lower residue concentrations, are met. Moreover, the sector must adapt to the prohibition or non-renewal of pesticides, exemplified by ongoing debates over glyphosate approval renewal in the EU (European Commission, 2023). Following suggestions by Rau et al. (2010) and Burnquist et al. (2011), this study identifies a subset of the most widely used pesticides in soybean and corn cultivation and evaluates how their restriction may affect trade flows.

Finally, regulatory divergence is integrated into the Melitz (2003) model as a theoretical enhancement, while the strategy employs a structural gravity specification featuring two relative measures of MRL stringency, one based on EU rules and the other on Codex benchmarks.

Regulatory divergence in MRLs shapes firms' production choices and market access. Within the new trade theory framework, product differentiation under monopolistic competition explains how productivity, wages, output and profits separate exporters from non-exporters. Melitz (2003) introduces firm heterogeneity and demonstrates that productive firms bear the fixed entry costs needed to comply with food safety standards, while less productive firms exit foreign markets.

Chen et al. (2008) show compliance costs act as entry barriers while raising per-unit expenses. When an importer tightens MRL thresholds or bans a permitted pesticide, suppliers must diversify inputs, upgrade practices or invest in new technologies. These adjustments favor larger, better-resourced firms; smaller producers may lack capital or technical capacity to meet multiple regimes. In many systems, firms face analytical and operational expenses and certification and documentation costs in destination markets.

Early models treated quality as exogenous, but later work incorporates quality perception as a driver of demand. Stricter standards raise costs yet may ease market access if consumers value the implied safety and environmental attributes (Fiankor et al., 2021a, b). In many agri-food markets, strategies based on price competition have given way to quality-oriented positioning: consumers may accept a quality premium for products that satisfy standards, sharing some of the compliance burden with producers (Xiong and Beghin, 2014). Conversely, mandatory requirements can force lower-quality suppliers to upgrade their practices, narrowing quality dispersion among competitors and intensifying price competition (Disdier and Marette, 2010).

Since the 1990s, gravity models have become the standard tool for quantifying how food safety regulations influence bilateral trade flows (Anderson and Van Wincoop, 2003). Research documents both negative and positive effects of regulatory heterogeneity. Otsuki et al. (2001) estimated that a 1% increase in the stringency of EU aflatoxin limits reduced African cereal trade by 1.1% and fruit, vegetable and nut trade by 0.43%, while harmonization with Codex standards could have boosted EU–Africa trade by up to USD 670 million. Wilson and Otsuki (2004) found that chlorpyrifos limits in high-income markets led to annual banana export losses of USD 5.5 billion.

Studies reinforce this pattern. Chen et al. (2008) show that exports may rise when exporters comply with stricter rules, whereas Ferro et al. (2015) and Hejazi et al. (2022) find that compliance costs outweigh price premiums in some cases. Disdier and Marette (2010) demonstrate that antibiotic residue standards improve social welfare at the expense of reduced trade volumes. Crivelli and Groeschl (2016) and Fiankor et al. (2021a, b) observe that measures can act as nontariff barriers yet boost bilateral flows when firms meet the new criteria. Taken together, heterogeneity tends to lower trade on the extensive margin by raising entry barriers but can increase trade on the intensive margin for exporters that meet standards (Chaney, 2008). A review by Li and Beghin (2012) reports that more than half of MRL studies document trade impacts. This research highlights the interplay between consumer confidence, bolstered by harmonized standards, and the compliance costs imposed on exporters.

The indices defined below are implemented within the theoretical framework of Xiong and Beghin (2014). The first index captures the strictness of each exporter's MRLs relative to Codex standards (Equation 1). When a country's limits fall below Codex recommendations, this may signal lower product quality. The same formulation appears in Fiankor et al. (2021a, b) and Traoré and Tamini (2021). This study introduces a second index (Equation 2), which contrasts the exporter's MRL with that of the importer. If the importer's limits are laxer than the exporter's, the higher exporter standards may serve as a quality signal; if the exporter's standards are less demanding, the exporter incurs compliance costs to meet the importer's criteria. As a contribution, this paper applies the second index both to the quality perception component and to the cost component of the model proposed by Xiong and Beghin (2014).

For Equation (1), $MRLCodex$ and $MRLipat$ denote the time-varying maximum residue limits for product $p$ and pesticide $a$⁠, as set by $Codex$ and by exporting country $i$⁠, respectively. $N(p)$ is the total number of pesticides relevant to $p$⁠, here representing the active ingredients in soybean and corn crops. The index ranges from 0 to $(≈2.718)$ . A value of 1 implies alignment with the benchmark $(MRLCodex=MRLipat);$ values below 1 indicate laxer standards $(MRLCodex<MRLipat)$⁠; and values above 1 indicate stricter standards $(MRLCodex>MRLipat)$⁠. Scores approaching 2.718 reflect stringent limits. In Equation (2), $MRLjpat$ and $MRLipat$ are the importer's $(j)$ and exporter's $(i)$ MRLs, respectively, for $p$⁠, at time t. When $MRLjpat<MRLipat$⁠, the index falls below 1, indicating that the importer enforces tighter limits than the exporter, which may restrict market entry.

This study selects a defined subset of pesticides (Table 1) to compute both indices. That choice departs from the literature, which often applies equal weighting to all registered pesticides without identifying those used. Rau et al. (2010) and Burnquist et al. (2011) note the limitation posed by limited technical knowledge of pesticide usage; they therefore assign unit weights to every compound. Other analyses focus on a single chemical (Otsuki et al., 2001; Wilson and Otsuki, 2004).

Because countries vary in which pesticide–crop combinations they regulate, many MRLs are unreported. Following standard practice, unregulated pesticides are assigned a default MRL of 0.01 mg/kg (0.01 ppm) for the EU (Regulation CE 396/2005) and Argentina (Resolution 934–2010) in accordance with national law (European Commission, 2005; SENASA, 2010). For Brazil, missing values use the corresponding Codex MRLs (Shingal and Ehrich, 2024). This approach aligns with each jurisdiction's default provisions when limits are absent. The dataset covers 2010–2018 and is sourced from the Homologa Agrobase platform; access fees explain the choice to end the series in 2018.

Table 2 illustrates index calculation using four pesticides (A-D) in soybean production. Missing MRLs default to 0.01 ppm for Argentina and the EU, while Brazil uses available Codex limits.

Table 3 presents a summary of studies that examine how MRL regulations affect agri-food exports, using indicators to capture the impact of varying degrees of stringency. The results differ across contexts, reflecting the dual nature of these policies. Harmonized standards can strengthen consumer trust in food safety and quality, but divergent requirements and levels of strictness across markets generate compliance costs that may weigh on export performance.

This paper extends Xiong and Beghin (2014), who analyze how MRL regulatory asymmetries affect import demand and export supply (Appendix A), by revising cost and quality equation specifications. We use distinct approaches to capture MRL effects on costs and perceived quality. For costs, we compare importer and exporter MRL stringency directly. Exporters face adjustment costs only when partner limits are stricter. If importer MRLs equal or are less strict than exporter MRLs, no compliance cost arises, even when both differ from Codex. Codex comparisons capture the quality dimension since alignment with Codex signals baseline product safety. Transportation costs enter separately from regulatory compliance costs in the trade cost function.

Using indices from Equations (1)-(2), exporters face no compliance cost when $MRLjpat≥MRLipat$⁠. Otherwise, exporters must adjust production to meet stricter requirements. Let $MRLijpat,cost$ denote the composite index for these cases. The cost component of the structural gravity model (Equation 3) becomes

where $τpijt$ is the iceberg trade cost for product $p$ shipped from exporter $i$ to importer $j$ at time $t$⁠; $Tarpijt$ denotes the ad valorem tariff; $Distij$ is bilateral distance; $Langij$⁠, $Bordij$⁠, $Colij$ and $Religij$ are, respectively, indicators for common language, shared border, colonial ties and common religion; $bd$⁠, $bp$⁠, $bb$⁠, $bc$ and $br$ are elasticities on those bilateral cost proxies; $γ$ is the semi-elasticity of trade costs with respect to the MRL cost index and $MRLijpat,cost$ is the composite compliance-cost index that activates only when the importer is stricter than the exporter $(MRLjpat<MRLipat)$⁠.

To capture quality effects, we incorporate exporter deviation from Codex and importer–exporter differences. Define $MRLCodex,ipat$ from Equation (1) and $MRLijpat,quality$ from Equation (2). The quality shifter in Equation (4) is then

where $δpjt$ is the demand-side quality shifter with baseline $δpt0$⁠; $MRLCodex,ipat$ and $MRLijpat,quality$ are the stringency indices from Equations (1) and (2), the former comparing exporter limits to Codex and the latter capturing importer–exporter differences used as a quality signal.

Compliance with Codex standards demonstrates conformity with global safety norms, while stricter importer limits provide quality signals beyond those benchmarks. The full gravity specification combines these elements:

$Vpijt$ is bilateral trade value in the structural system; $Yjt$ is the importer expenditure term; $Πjt$ is the exporter-side price index term; $Qpit$ and $Ψsit$ are product- and side-specific supply and demand shifters consistent with structural gravity and $φ$ and $θ$ are model parameters. In this formulation, $MRLijpat,quality$ averages all pesticide-crop pairs, regardless of which party is stricter, to reflect importer quality perception. For $MRLijpat,cost$ observations with $MRLjpat≥MRLipat$ receive value zero.

Our product-level outcomes aggregate firm-level selection and upgrading. Tightening domestic MRLs raises fixed and variable production costs; low-productivity firms exit, while surviving firms internalize compliance and continue exporting. In Equation (5), this operates through the cost shifter $MRL(ijpat,cost)$ and the quality shifter $δpjt$⁠. Transportation costs are modeled separately via $Distij$ and bilateral dummies, not as production costs.

Xiong and Beghin (2014) disentangled MRL impacts on demand and supply but defined both relative to Codex alone. By incorporating direct importer–exporter comparisons, our approach separates quality signaling from adjustment costs induced by regulatory heterogeneity. Additionally, we embed MRL divergence in a Melitz-type. Exporting requires a fixed cost $fijpt$ and an iceberg trade cost $τijpt$⁠. When the importer's MRLs are stricter than the exporter's, compliance adds a fixed component (documentation, certification, sampling plans) and a variable component (changes in active ingredients, monitoring, lab testing): $fijpt=f0exp⁡{κ·MRLijpat,cost}$ and $τijpt=τ0exp⁡{γ·MRLijpat,cost}$⁠. The export cut-off productivity $φijpt*$ rises, fewer firms export and survivors adjust quantities and prices, as in Chaney (2008). Transport frictions are modeled separately by distance and bilateral dummies; they are not part of production costs.

The theoretical model in Equation (14) underpins our empirical specification. Anderson and Van Wincoop (2003) emphasize including multilateral resistance terms to capture price indices of importers and exporters. Fally (2015) recommends directional fixed effects in panel-data frameworks to account for these resistance terms. Olivero and Yotov (2012) extend this by adding importer-year and exporter-year fixed effects, absorbing year-varying factors like income, production capacity, technology and productivity. This technique is necessary for valid structural gravity models (Beverelli et al., 2024), controlling multilateral resistance and national production and consumption levels. Implementation details appear in Fally (2015).

Baier and Bergstrand (2007) recommend including country-pair fixed effects alongside bilateral fixed effects. This captures time-invariant trade-cost measures like distance, colonial ties and common language, and addresses endogeneity between agrifood standards and trade flows. Combining importer-year, exporter-year and country-pair fixed effects controls for time-varying, pair-specific factors. Similar specifications appear in Fiankor et al. (2021a, b), Traoré and Tamini (2021), Jiang et al. (2023) and Shingal and Ehrich (2024).

Piermartini and Yotov (2016) advise using panel data with non-overlapping intervals rather than pooling consecutive years. This allows bilateral trade flows to adjust to policy changes or shifts in trade costs, since policy decisions may not immediately affect trade volumes. When data are grouped over consecutive years, fixed-effect estimators can misalign with policy timing. Our biennial MRL dataset aligns with this recommendation and avoids temporal inconsistencies.

To accommodate zero trade flows from no exports of certain products in specific year-country pairs, Santos Silva and Tenreyro (2006) recommend the Poisson Pseudo-Maximum Likelihood (PPML) estimator. Unlike OLS, which drops zero observations and risks sample-selection bias, PPML handles zeros naturally and addresses heteroscedasticity common in trade data. PPML ensures fixed effects correspond to their theoretical counterparts and enables computation of general-equilibrium trade-policy effects consistent with the structural model (Piermartini and Yotov, 2016).

The econometric specification for estimating trade flows between Mercosur countries and the EU appears in Equation (14). Exports include only Argentina and Brazil, which account for approximately 90% ^[1] of the bloc's commodity exports and maintain independent MRL regulations. Paraguay and Uruguay follow Codex standards and are excluded. Importers comprise the 27 EU member states. The analysis covers 2010–2018. Trade flows for corn and soybeans are disaggregated at the six-digit Harmonized System ^[2] level.

On the supply side, bilateral trade costs are captured by $ln⁡MRLjipat,costs$⁠, which applies only when importer MRLs are stricter than exporter MRLs (denoted by the “∅”). On the demand side, quality effects enter through $ln⁡MRLijpat$ and $ln⁡MRLCodex,ipat$⁠. The dependent variable $Xijtp$ takes three forms: (1) export probability, $Prijtp$⁠; (2) import ^[3] value of product $p$ by country $j$ from $i$ in year $t,$ $Imijtp$⁠; (3) unit price, $Pijtp$⁠. Multilateral resistance terms are absorbed by fixed effects for country pairs $(αij)$⁠, exporter-year $(αit)$⁠, importer-year $(αjt)$⁠, product $(αp)$ and $tariffijpt$ refer to effectively applied ad valorem tariffs, $c$ is the constant and $εijtp$ is the error term.

To estimate export probability (1), we define a dummy equal to 1 if $j$ imports positive quantities of $p$ from $i$ in year $t$⁠, and 0 otherwise. Estimation uses a linear probability model via OLS. Nonlinear models (probit/logit) are avoided to prevent incidental-parameter bias from numerous fixed effects; moreover, the linear probability model yields straightforward average marginal effects (Fiankor et al., 2021a, b; Traoré and Tamini, 2021).

For import values (2), the PPML estimator is applied as it accommodates zero trade flows and heteroscedasticity common in gravity models. To estimate unit prices (3), OLS with country-pair, importer-year and exporter-year fixed effects is used, following Traoré and Tamini (2021). The RESET test assesses PPML specification, with the null hypothesis of correct model specification. Trade data (in USD and metric tons, used to compute unit prices) are sourced from UN COMTRADE via WITS. Descriptive statistics appear in Table IV, Appendix B.

Table 4 contrasts a reference specification that includes the two demand-side indices, $MRLCodex,ipat$ and $MRLijpat,quality$⁠, plus the supply-side cost index $MRLijpat,cost$⁠, with a restricted version that omits the bilateral quality gap. We report the restricted model because the Codex-based index already delivers the food-safety cue that matters for bulk grains, while the bilateral quality gap can overlap with the cost term once the importer is stricter. Institutionally, EU harmonization compresses importer-side dispersion, so most informative variation comes from exporters and the bilateral quality term becomes weakly identified in this setting (European Commission, 2005; Shingal and Ehrich, 2024).

The results document three patterns and a robustness message. First, $MRLCodex,ipat$ is positively associated with market entry and import values and negatively associated with unit prices. Second, $MRLijpat,cost$ lowers entry and import values and raises unit prices. Panel B, which removes the bilateral quality-gap term $MRLijpat,quality$⁠, delivers the same qualitative message: the estimated effects on $MRLCodex,ipat$ and $MRLijpat,cost$ are stable in sign and close in magnitude to Panel A, so the interpretation does not change. This stability is consistent with the EU's harmonized regime compressing bilateral dispersion in MRLs and with the idea that, for bulk grains, the binding standard and the cost channel carry most of the commercial content (Shingal and Ehrich, 2024; Xiong and Beghin, 2014).

On the extensive margin, exporter rules tighter than Codex are linked to higher entry, whereas an importer–exporter gap that activates compliance costs lowers entry. For a 0.1 increase in $MRLCodex,ipat$⁠, the probability of a positive flow rises by about 0.014 percentage points. For a 0.1 tightening in $MRLijpat,cost$⁠, entry falls by roughly 0.007 percentage points. This pattern matches the selection mechanism in Melitz (2003), where stricter domestic requirements push low-productivity firms out and leave exporters able to cover fixed and variable compliance outlays. Traoré and Tamini (2021) show that strict OECD thresholds lower the chance that African mango shipments pass the requirement but, once they do, compliant exporters expand flows. Xiong and Beghin (2014) separate a demand channel raised by safety cues from a cost channel that screens marginal suppliers, the same duality seen here at the entry stage. The bilateral quality-gap term $MRLijpat,quality$ is not different from zero once costs are controlled, which is consistent with standardized grain transactions that depend on the binding requirement rather than an extra quality cue.

For import values, a 0.1 rise in $MRLCodex,ipat$ is associated with about 1.95% higher EU purchases in Panel A and about 2.20% in Panel B. Jiang et al. (2023) find that meeting destination-oriented residue rules is associated with larger Chinese agri-food exports to the and Xiong and Beghin (2014) argue that alignment with Codex reduces residue-related disruptions, which supports demand. A 0.1 tightening in $MRLijpat,cost$ lowers values by about 2.74% in Panel A and about 2.65% in Panel Ferro et al. (2015) document that more restrictive standards curb bilateral trade decisions across several food sectors, and Hejazi et al. (2022) show that compliance burdens depress fresh produce exports when costs outweigh any demand lift.

We assess the net effect on import values using the Wald test $β1+β2+β3=0$ [⁴]. The null is not rejected in Panel A $(p=0.957)$ nor in Panel B $(p=0.285)$⁠. Jiang et al. (2023) find that whether residue rules inhibit or promote trade depends on the balance between opposing forces and varies by product and destination. Here, the positive demand shifter tied to Codex alignment is offset by the compliance-cost channel, so the combined effect on traded values is neutral. This interpretation aligns with Traoré and Tamini (2021), who argue that for commodities sold under standardized grades, any added quality attribute must be compensated by higher prices, or exporters redirect shipments to less demanding markets. The contrast with findings for fresh produce, where importers reward stricter compliance with premiums exceeding compliance costs $(β1+β2+β3>0)$⁠, highlights how outcomes vary across product categories and reflect different risk perceptions for products consumed raw versus processed.

Price estimates show pass-through rather than a quality premium. A 0.1 increase in $MRLijpat,cost$ raises unit prices by about 5.3% in Panel A and 5.7% in Panel B. Wilson and Otsuki (2004) document that tighter pesticide rules for bananas induce cost pressures that are partly passed on to buyers. By contrast, a 0.1 rise in $MRLCodex,ipat$ is associated with lower prices, around −6.5% in Panel A and −5.1% in Panel Otsuki et al. (2001) show that stricter aflatoxin limits reduce African exports without evidence of compensating price rewards, and Disdier and Marette (2010) report welfare gains with falling quantities, which helps explain why unilateral rigor beyond the binding threshold is not priced in commodity contracts.

Two features of the setting help explain these patterns. First, indices are computed from the subset of active ingredients actually used in soy and corn. When the basket is widened to all registered molecules, elasticities are diluted, while the cost index keeps shaping entry and prices. Rau et al. (2010) and Burnquist et al. (2011) flag that heterogeneity metrics built on all registrations inject noise, and Shingal and Ehrich (2024) show that EU harmonization compresses importer-side dispersion, making exporter alignment the informative variation. Second, blending in bulk logistics means the tightest destination limit governs the lot. USITC (2020) documents how such blending constraints propagate the strictest MRL across shipments.

Policy implications follow directly. Aligning domestic MRLs with Codex reduces information frictions and supports volumes, but a premium is not automatic in standardized grains unless buyers specify and pay for it. Traoré and Tamini (2021) show that volumes rise only when the price paid for compliance offsets added costs. Priority should be on lowering marginal compliance costs that drive $MRLijpat,cost$⁠: expand accredited laboratory capacity and sampling, enable targeted substitution of active ingredients, and use import tolerances where agronomically justified within the EU regime set by Regulation 396/2005 of the European Commission (2005). Private strategies should segment lots to the strictest intended destination to avoid blending penalties. These steps allocate the adjustment burden more efficiently along the chain and narrow the scope for nontariff protection masked as safety policy, as argued by Xiong and Beghin (2014) when separating cost and demand channels in regulatory design.

Two exercises assess baseline result stability. First, MRL-stringency indices are recalculated using all pesticides registered by EU and Mercosur authorities (Table VI, Appendix C). Second, the bilateral trade equation is re-estimated using Heckman two-stage specification, following Xiong and Beghin (2014) [⁵]. Supplementary estimates appear in Table 5.

MRL-stringency indices recalculated using all pesticides registered by EU and Mercosur authorities show that widening the index weakens explanatory power of the exporter-versus-Codex gap. The cost-related index continues to influence market entry probability and unit prices. Re-estimation with Heckman two-stage specification confirms that main conclusions are unaffected: stricter EU limits raise compliance costs that are partly embedded in prices, discourage market participation when the regulatory gap is large, and do not generate compensating quality premiums for bulk commodities such as soybeans and corn.

This study advances understanding of how MRLs affect agricultural trade by examining both demand-enhancing quality effects and supply-restricting cost effects simultaneously. By developing dual stringency indices that contrast exporters' MRLs with Codex benchmarks and measure exporter-importer differences specifically for soybeans and corn, we offer methodological refinements that reduce measurement bias and yield more precise estimates of regulatory effects.

Our econometric results reveal that standards imposing compliance costs on exporters significantly reduce both trade occurrence probability and shipment volumes. When EU limits are stricter than those applied by Mercosur exporters, market entry likelihood decreases and trade volumes decline. However, exporters can effectively transfer these compliance costs to importers through price adjustments. The combined cost-and-quality effect is statistically neutral according to our Wald tests, indicating that increased compliance costs are offset by corresponding price adjustments in destination markets.

This premium finding is noteworthy for commodities like soybeans and corn, which are traditionally traded under uniform quality grades. By offering grain that meets additional food safety requirements, Mercosur suppliers can command higher prices and convey conformity signals. Our research demonstrates that regulatory alignment with Codex standards, while beneficial for reducing trade frictions, is insufficient to guarantee unimpeded access to stringent markets. Exporters still face adaptation costs when importer limits exceed international benchmarks.

The political economy implications are multifaceted. While importing countries may use strict standards as protectionist measures, our analysis reveals that regulatory differences reshape exporters' cost structures and can lead to quality upgrading throughout supply chains. Suppliers capable of meeting demanding limits can render their products less substitutable and potentially benefit from price premiums that offset compliance costs. For Mercosur exporters with sufficient scale, compliance costs can be spread over large sales volumes, helping them maintain competitive positions in EU grain markets.

Our findings suggest that policymakers should consider differential impacts of MRL regulations across product categories rather than applying uniform approaches to agricultural trade. They highlight the importance of providing technical assistance and capacity building for producers in developing countries to help them meet stringent standards and capture potential price premiums. Finally, they underscore the value of international coordination on MRL standards, particularly for widely traded commodities like soybeans and corn.

The supplementary material for this article can be found online.