EFFECT OF SELECTED INSECTICIDE ON WHITEFLY (Bemisia tabaci) INFESTING BRINJAL PLANTS 444 © 2025 AESS Publications. All Rights Reserved. Navigating climate change with bt corn: A study of efficiency in Philippine corn production Aphril Easter Sunday Jaemi Manuel Jaymea Yoonsuk Leeb aInstitute of Agribusiness Management, Don Mariano Marcos Memorial State University, Bacnotan, La Union, Philippines. bKangwon National University, Chuncheon City, Gangwon Province, South Korea.  yoonsuklee@kangwon.ac.kr (Corresponding author) Article History ABSTRACT Received: 14 April 2025 Revised: 27 August 2025 Accepted: 8 September 2025 Published: 24 September 2025 Keywords Bt corn Climate change De Martonne aridity index Efficiency Interrupted time series Philippines Stochastic frontier model. The Philippine corn industry, vital for national food security, faces significant threats from climate change. This study uses stochastic frontier analysis to assess climate's impact on corn production efficiency from 1990 to 2020, focusing on the role of Bt corn adoption. Findings show that while higher temperatures and reduced rainfall increase production inefficiency, adopting Bt corn with fertilizer substantially mitigates these adverse effects. The 2002 commercialization of Bt corn marked a key turning point, reversing production declines and improving sector performance. These results underscore the need for climate-resilient agricultural strategies. Policy should prioritize irrigation expansion, improved rainfall utilization, broader access to crop insurance, and continued support for improved seed varieties like Bt corn. Strengthening these adaptive measures is crucial for enhancing the resilience and stability of the Philippine corn sector against ongoing climate challenges. Contribution/Originality: This study introduces a novel methodology that combines Interrupted Time Series Analysis with a Stochastic Frontier model. We provide the first quantitative evidence that Bt corn adoption mitigates production inefficiencies caused by climate shocks in the Philippines, offering crucial data for the nation's food security strategy. DOI: 10.55493/5005.v15i3.5620 ISSN(P): 2304-1455/ ISSN(E): 2224-4433 How to cite: Jayme, A. E. S. J. M., & Lee, Y. (2025). Navigating climate change with bt corn: A study of efficiency in Philippine corn production. Asian Journal of Agriculture and Rural Development, 15(3), 444–453. 10.55493/5005.v15i3.5620 © 2025 Asian Economic and Social Society. All rights reserved. 1. INTRODUCTION The corn industry plays a vital role in the Philippine economy, supporting national food security and the livelihoods of millions of farmers. Beyond its function as a staple food, corn serves as a primary source of livestock feed and raw material for various industries, supporting the livelihoods of approximately 1.8 million farmers nationwide. In 2020, the agriculture, forestry, and fishing sector accounted for 5.76% of the national Gross Domestic Product (GDP) in the Philippine economy (Biñas Jr, 2021; Department of Agriculture- Bureau of Agricultural Research, 2022; Naval & Dolojan, 2020). However, corn production in the Philippines faces a critical challenge: stagnating productivity. Yields declined from 3.32 metric tons per hectare (mt/ha) in July 2002 to 3.29 mt/ha in July 2023 (Abao, 2023; Philippine Statistics Authority, 2017). Average annual production growth fell from 5.2% (2000–2010) to 3.7% (2010–2020), while yield growth decreased from 4.8% (1987–2000) to just 1.5% (2010–2020) (Department of Agriculture- Bureau of Agricultural Asian Journal of Agriculture and Rural Development Volume 15, Issue 3 (2025): 444-453 https://orcid.org/0009-0002-1856-0439 https://orcid.org/0000-0001-6251-0696 mailto:yoonsuklee@kangwon.ac.kr https://doi.org/10.55493/5005.v15i3.5620 Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 445 © 2025 AESS Publications. All Rights Reserved. Research, 2022). These trends signal an urgent need for strategic interventions to ensure the nation’s economic stability and food security. Among the various factors contributing to this decline, climate change has emerged as a critical driver. Extreme weather events such as typhoons, droughts, and unseasonal heavy rainfall have caused widespread agricultural disruption. Due to its geographic location and climatic conditions, the Philippines ranks as the third most vulnerable country to climate change (National Integrated Climate Change Database Information and Exchange System, 2024). The nation's humid equatorial climate has experienced rising temperatures of approximately 0.68°C over the past 65 years and increasingly erratic rainfall (Climate Change Commission, 2024). While the overall number of tropical cyclones has slightly decreased, the frequency and intensity of severe storms have risen, with devastating events like Typhoon Haiyan, Typhoon Bopha, and Typhoon Mangkhut becoming more common. Under the SSP5-8.5 climate scenario, such extreme events are projected to intensify, exacerbating agricultural losses (Climate Change Commission, 2024). Moreover, rising minimum temperatures during the dry season are expected to reduce grain yields by roughly 10% per 1°C increase, further threatening food production and land productivity (Dait, 2022; Lasco, 2022; National Integrated Climate Change Database Information and Exchange System, 2024; Teng, Uy, & Gonzales, 2022). Climate change also disrupts pest dynamics, increasing the prevalence and severity of infestations. Higher temperatures and irregular precipitation patterns have expanded pest distributions and intensified outbreaks, particularly of the Asian corn borer (Ostrinia furnacalis Guenee), the most damaging corn pest in the Philippines and across Asia (Balderama, Alejo, Tongson, & Pantola, 2017; Biñas Jr, 2021; Kaur et al., 2023; Naval & Dolojan, 2020; Subedi, Poudel, & Aryal, 2023). Historically, this pest has caused yield losses of 20–80% in the Philippines Nafus and Schereiner (1991) in Daha, Amin, and Abdullah (2016). To combat these challenges, the Philippine government approved the commercialization of pest-resistant genetically modified (GM) corn, specifically Bt corn, in 2002. Following pilot greenhouse trials at 17 sites starting in 1997 (ISAAA, 2002), the country became the first in Asia to adopt this biotechnology (Polinag, 2020). Bt corn, which offers a 34% yield advantage over conventional varieties (APAARI, 2019), has helped mitigate losses from pest infestations and bolster production. Nevertheless, despite the widespread adoption of Bt corn, climate-related risks continue to threaten corn productivity and national food security. Achieving the objectives set out in the Philippine Corn Industry Road Map 2021-2040 requires a nuanced understanding of the evolving threats posed by climate change and their interaction with technological interventions. This study analyzes historical and contemporary changes in corn production in the Philippines within the context of climate change and the adoption of genetically modified corn. Specifically, it examines how the introduction of Bt corn has influenced production trends through an interrupted time series analysis. In addition, the study investigates the effects of climatic variables, such as temperature and precipitation, on corn output both before and after Bt corn adoption using a stochastic frontier model. The insights derived from this research aim to guide policy formulation and support the development of adaptive agricultural strategies that strengthen the resilience of the Philippine corn sector amid ongoing climatic challenges. 2. MATERIAL AND METHODS 2.1. Data Data on corn production volume, harvested area, and fertilizer use including urea, ammonium sulfate, ammonium phosphate, and complete fertilizers were obtained from the Philippine Statistics Authority (PSA). These variables cover 16 regions of the Philippines from 1990 to 2020. To account for climatic factors, regional data on annual precipitation (millimeters) and average temperature (°C) were formally requested from the Department of Science and Technology- Philippine Atmospheric, Geophysical and Astronomical Services Administration (DOST-PAGASA) National Office. These climate variables were used to calculate the De Martonne Aridity Index, which captures the combined effects of temperature and precipitation on regional dryness. Corn production data from all 16 regions were aggregated to analyze national production trends, particularly to assess the impact of Bt corn adoption. Table 1 summarizes the variables, categorized into two periods: 1990–2002 (pre-Bt corn adoption) and 2003–2020 (post-Bt corn adoption). The independent variables include harvested area and four types of inorganic fertilizers, such as Urea (46-0-0), Ammonium Sulfate (21-0-0), Ammonium Phosphate (16-20-0), and Complete fertilizers (14-14-14), also known as NPK. While various inputs influence corn production such as labor, capital, land, and machinery this study focuses on the roles of genetically modified (Bt) corn and fertilizer use. Notably, fertilizer application patterns shifted significantly following Bt corn adoption. Climate variables, specifically average regional precipitation and temperature, were integrated into the analysis through the De Martonne Aridity Index, calculated as follows: 𝐴𝐼𝐷𝑀 = 𝑃𝑠 𝑇𝑠+10 (1) Where A𝐼𝐷𝑀 is the computed aridity index in year s, 𝑃𝑠 is the total average annual precipitation of region i in year s in millimeters, and 𝑇𝑠 is the annual average temperature of region I in year S in degrees Celsius. The De Martonne Aridity Index provides a comprehensive measure of regional dryness, helping to identify drought conditions that directly affect agricultural productivity by limiting soil moisture and increasing crop water stress. Corn is particularly susceptible to drought during critical growth stages such as flowering and grain filling, often resulting in significant yield reductions. As Oury (1965, cited in (Wang, Ball, Nehring, Williams, & Chau, 2018)) noted, analyzing the relationship between weather and crop production is more effective when considering the combined effects of temperature and precipitation should be evaluated together rather than separately. The aridity index, therefore, serves as a key climate variable in this study. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 446 © 2025 AESS Publications. All Rights Reserved. Table 1. Summary statistics of variables. Year of Bt corn adoption Variable Unit Mean Std. Dev. Min. Max. 1990-2002 (Before Bt corn) Dependent variable Volume of production Metric tons 277,982 350,351 17,118 1,809,734 Production input Area Harvested Hectares 179,991 164,595 11,590 806,530 Inefficiency De Martonne Aridity Index Millimeter per degree Celsius 67 35 0 221 Rainfall Millimeters 2,433 1,086 561 5,739 Temperature Degree celsius 26 2 18 33 2003-2020 (After Bt corn) Dependent variable Volume of production Metric tons 432,250 456,900 42,772 1,875,623 Production input Area harvested Hectares 159,500 133,341 22,984 437,728 Urea 50kgs/Bag 112 62 19 364 Ammonium sulfate 50kgs/Bag 25 31 0 400 Ammonium phosphate 50kgs/Bag 26 25 0 121 Complete 50kgs/Bag 71 41 1 230 Inefficiency De Martonne Aridity Index Millimeter per degree Celsius 74 36 0 281 Rainfall Millimeters 2,659 1047 757 7,083 Temperature Degree celsius 27 2 19 31 Source: Climate and Agrometerological Data Section(CADS), Philippine Atmospheric, Geophysical and Astronomical Services Administration(PAGASA). 2.2. Methods 2.2.1. Interrupted Time Series Analysis To assess the impact of adopting Bt corn in the Philippines, this study applies Interrupted Time Series Analysis (ITSA). ITSA is a statistical method used to evaluate changes in outcomes over time by comparing trends before and after the implementation of a policy (Li et al., 2023). This approach considers both the timing and effect of the policy, allowing for the identification of significant shifts in the outcome variable following Bt corn. ITSA is used to examine the effects of the policy that introduced and commercialized Bt corn in the Philippines, which began in 2003. By comparing production trends prior to and following the adoption of Bt corn, this method isolates the impact of the policy from other time-related factors that may influence corn production. The ITSA model is specified as follows: 𝑌𝑡 =  0 +  1 𝑋𝑡 +  2 𝐵𝑡𝑡 +  3 (𝑋𝑡 ∙ 𝐵𝑡𝑡) + 𝑡 (2) Where 𝑌𝑡 is the volume of corn production in the Philippines at time t, 𝑋𝑡 represents inputs at time t,𝐵𝑡𝑡 is a dummy variable that takes the value 0 (before Bt corn) and 1 (After Bt corn). This is the intervention regarding the commercialization and use of Bt Corn variety in the Philippines at time t, and 𝑡 represents the error term, accounting for random variability in the volume of production variable that is not explained by the model. 2.2.2. Stochastic Frontier Model This study applies Stochastic Frontier Analysis (SFA) to analyze efficiency and identify technical inefficiency in corn production (Wang et al., 2018). The empirical framework estimates the efficiency of corn production across Philippine regions while accounting for the influence of key inputs and environmental factors. The stochastic production frontier is specified as: Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 447 © 2025 AESS Publications. All Rights Reserved. 𝑙𝑛𝑦𝑖𝑡 = 𝛽0 + ∑ 𝛽𝑘𝑙𝑛𝑥𝑘𝑖𝑡 + 𝑣𝑖𝑡 − 𝑢𝑖𝑡 𝐾 𝑘=1 (3) Where 𝑙𝑛 𝑦𝑖𝑡 is the log of the total volume of corn production of region i and at time t, 𝑥𝑘𝑖 are the inputs of region i and at time t. Before Bt corn, the SFA model includes area harvested as an production input, while after Bt corn, the estimation model includes areas harvested and various inorganic fertilizers as inputs. To model production inefficiency, the following specification is used: 𝑙𝑛𝜎𝑢 2 𝑖𝑡 = 𝛾0 + ∑ 𝛾𝑚𝑧𝑚𝑖𝑡 + 𝜔𝑖𝑡 𝑀 𝑚=1 (4) Where 𝜔𝑖𝑡 is the disturbance term with normal distribution and, z contains the climatic variables, such as temperature and precipitation, incorporated as an aridity index. Given this study’s focus on climate change impacts, particular attention is given to temperature and precipitation. These climatic factors are incorporated into the inefficiency component to assess how weather variability affects production efficiency and whether unfavorable conditions cause production to fall below the optimal frontier. Climatic stress during key stages of corn development, such as flowering and grain filling, can significantly reduce yields (Wang et al., 2018), making these variables essential to the analysis. To capture the combined effects of temperature and precipitation, this study employs the De Martonne Aridity Index, originally proposed by Emmanuel De Martonne in 1926. This index provides an integrated measure of regional dryness, calculated as the ratio of annual precipitation to the average annual temperature plus ten (Jafarpour, Adib, Lotfirad, & Kisi, 2023). The De Martonne Index is widely used to classify regional climates and identify drought conditions, which directly affect soil moisture availability and crop water requirements (Integrated Drought Management Programme, 2022). Drought stress is particularly detrimental to corn, as water shortages during critical growth stages can lead to substantial yield losses. By incorporating the aridity index into the model, this study assesses how increasing dryness, driven by changing climate patterns, contributes to inefficiencies in corn production across the Philippines. 3. RESULTS Extreme weather events significantly impact crop yields worldwide, presenting a major concern for food security. In the Philippines, agricultural systems are particularly vulnerable to these conditions due to the country's archipelagic geography, which creates substantial climate variation, with some regions experiencing tropical climates while others do not. Understanding how these climate fluctuations affect crop production is essential, as they directly influence crop yields. Notably, the Philippines is the first Asian country to adopt Bt corn. This study first estimates the effects of Bt corn adoption in addressing pest issues that may intensify with climate change and then evaluates how Bt corn and inorganic fertilizer impact overall resilience to environmental stressors. 3.1. Changes in Corn Production before and after Bt Corn In 2002, the Bureau of Plant Industry under the Department of Agriculture approved the commercial distribution of the hybrid variety Bt Corn which paved the way for its legal use and utilization. According to ISAAA (2017, cited in Bequet (2022)), upon the approval for commercial distribution of Bt corn, farmers immediately adopted this technology, and around 65% of the total area utilized for corn was planted with the improved corn seeds. Table 2 presents the results of the interrupted time series analysis for the impact of Bt corn in the Philippines from 1990-2020. The results indicate that the use of Bt corn has a sustained effect or long-term impact, which is significant at 1 percent. This implies that after the implementation of Bt corn in the country, total corn production increased by 205,465 metric tons annually. The results further reveal that the immediate effect of the use of Bt corn was an additional 1,242,805 metric tons of total corn production. Table 2. Impact of Bt Corn in the Philippines. Variable Coefficient Newey-West Std. Err. P-value Before Bt Corn -33611.06 16739.78 0.055 Immediate effect 1242805 343214 0.001 Sustained effect 205465.5 29352.67 0.000 Constant 4683001 121832.7 0.000 To visualize the effect of Bt corn in the country, Figure 1 is shown. This figure presents the impact of the commercialization and use of the improved seed variety in addition to intensifying the subsidy for inputs, such as fertilizers, for the country. The result shows that from 1990 to 2002, the actual trend in corn production was decreasing. As Bt corn adoption started in 2003, with the approval of the use of new technology with subsidized inputs, there has been a significant increase in the production level as shown in Figure 1. This supports the result presented in Table 2 that the implementation of the use of Bt corn had a positive short-term and long-term effect on the volume of corn production in the Philippines. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 448 © 2025 AESS Publications. All Rights Reserved. Figure 1. The effect of the use of Bt corn in production in the Philippines from 1990 to 2020. 3.2. Stochastic Frontier Analysis before and after Bt Corn The maximum likelihood estimates of the parameters in the stochastic frontier and the inefficiency estimates for corn production in the Philippines from 1990 to 2020 are presented in Table 3, 5, and 6, respectively. The research study analyzed corn production by separating the analysis into two categories. First, the effect of climatic variables on the volume of production was examined in two time periods, namely before Bt corn (1990 to 2002) and after Bt corn (2003 to 2020). For the second analysis, the effect of climatic variables was also analyzed with the consideration of added input variables such as fertilizers. This allows for examining how climatic variables contribute to inefficiency in corn production before and after the use of Bt corn seeds, and with and without fertilizer inputs. The Likelihood Ratio test was initially conducted before estimating the stochastic frontier model for the different analyses to check whether inefficiency effects are present, and the results shown in Table 3, 5, and 6 indicate that inefficiency effects exist, and the stochastic frontier approach is valid in the study. Additionally, as observed in Table 3 and Table 5, there is a transition from a significant 𝜂 before Bt corn to an insignificant 𝜂 after Bt corn, with and without overall inputs. This implies that the use of Bt corn potentially stabilized the inefficiency trends, resulting in more consistent corn production and increased resilience to factors that previously contributed to inefficiency growth. Table 3 presents the results of the stochastic frontier model before Bt corn with harvested area. For this model, the area harvested was considered as an input, after which the inefficiency was estimated. The results for the efficiency estimation show that the area harvested has a significant positive coefficient of 1.26. For the inefficiency estimates, the De Martonne Aridity Index came out negative and significant for the period before Bt, with a coefficient of -0.39. This implies that a 1 percent decrease in the De Martonne Aridity Index (indicating more arid conditions) increased the inefficiency by 39 percent. Table 3. Results of stochastic frontier analysis before bt corn (1990-2002). Factor Variables Coefficient Std. Err P-value Efficiency factors Constant 1169.60 810.56 0.150 Area harvested 1.26 0.13 0.000 Inefficiency factors Constant 1173.70 0.28 0.000 De martonne aridity index -0.39 0.07 0.000 Error component LR test of inefficiency 13.48*** Gamma(γ) 0.908*** Sigma-squared(𝜎2) 0.345** Eta(𝜂) 0.00003*** Note: Efficiency estimation used bootstrap standard errors and inefficiency estimation used robust standard errors. *** , ** indicate significance at the 5%, 10% level, respectigely. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 449 © 2025 AESS Publications. All Rights Reserved. The efficiency scores of the regions were also computed. Table 4 shows the efficiency scores of the regions in the Philippines before Bt corn use. It is observed from the result that the most efficient regions include Region III, Region II, and Region I with the efficiency scores of 0.95, 0.88, and 0.85, respectively. Figure 2 shows the location of regions in the Philippines. Table 4. Efficiency scores of each Region for 1990-2002. Region I. Efficiency scores (1990-2002) CAR 0.70 Region I 0.85 Region II 0.88 Region III 0.95 Region IV-A 0.40 MIMAROPA 0.65 Region V 0.33 Region VI 0.35 Region VII 0.23 Region VIII 0.32 Region IX 0.33 Region X 0.71 Region XI 0.31 Region XII 0.78 Region XIII 0.45 BARMM 0.73 Furthermore, Table 5 shows the results of the stochastic frontier model after Bt corn with harvested area. In the table, a similar result is observed as the area harvested is still significant and positive with the coefficient of 1.12. Likewise, for the inefficiency estimation, the De Martonne Aridity index is -0.24, implying that a 1 percent increase in temperature increases the inefficiency of production by 24 percent after Bt corn. Table 5. After Bt corn SFA results (2003-2020). Factor Variables Coefficient Std. err P-value Efficiency factors Constant 675.11 660.31 0.307 Area harvested 1.12 0.13 0.000 Inefficiency factors Constant 1.66 0.25 0.000 De Martonne aridity index -0.24 0.06 0.000 Error component LR test of inefficiency 140.10786*** Gamma(γ) 0.952*** Sigma-squared(𝜎2) 0.27** Eta(𝜂) 0.00004 Note: Efficiency estimation used bootstrap standard errors and inefficiency estimation used robust standard errors. *** , ** indicate significance at the 5%, 10% level, respectigely. To further the analysis, inputs such as fertilizers were considered since after the introduction of Bt corn seeds, fertilizer use has been intensified throughout the country. Table 6 shows that among the production factors, area harvested and complete fertilizers were positive and significant. After including fertilizer inputs in the analysis, area harvested still appeared significant with a positive coefficient of 1.1, while complete fertilizer has a positive coefficient of 0.07. The positive significant result of 0.07 for complete fertilizer emphasizes the role of its use in increasing the efficiency of corn production after Bt corn. This implies that a 1 percent increase in area harvested and complete fertilizer also increases production efficiency by 1.13 and 0.07 percent, respectively. The De Martonne Aridity index remains significant and negative at -0.08, indicating that a 1 percent increase in temperature increases production inefficiency by 8 percent. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 450 © 2025 AESS Publications. All Rights Reserved. Table 6. After bt corn with overall inputs SFA results. Factor Variables Coefficient Std. Err P-value Efficiency factors Constant 11.53 682.47 0.990 Area harvested 1.13 0.12 0.000 Urea 0.06 0.05 0.250 Ammonium sulfate -0.11 0.01 0.440 Ammonium phosphate -0.002 0.01 0.830 Complete 0.07 0.03 0.050 Inefficiency factors Constant 0.63 0.11 0.000 De Martonne aridity index -0.08 0.02 0.001 Error component LR test of inefficiency 56.54*** Gamma(γ) 0.95** Sigma-squared(𝜎2) 0.222** Eta(𝜂) 0.002 Note: Efficiency estimation used bootstrap standard errors and inefficiency estimation used robust standard errors. *** , **, and indicate significance at the 5%, 10% level, respectigely. Additionally, Table 7 shows the computed efficiency scores of the different regions in the Philippines after Bt corn use, with area harvested as input of production. In this table, it is revealed that the regions performed similarly in terms of their efficiency in utilizing their inputs of production after Bt corn use, as observed from the computed efficiency scores. Table 7. Efficiency scores of region for 2003-2020. Region II. Efficiency scores (2003-2020) CAR 0.82 Region I 0.83 Region II 0.82 Region III 0.86 Region IV-A 0.67 MIMAROPA 0.79 Region V 0.68 Region VI 0.77 Region VII 0.50 Region VIII 0.73 Region IX 0.77 Region X 0.82 Region XI 0.72 Region XII 0.76 Region XIII 0.81 BARMM 0.88 Table 8 presents the simple comparison of the technical efficiency, with an emphasis on the mean technical efficiency scores, of the different regions before and after Bt corn. It is observed that the regions improved after Bt corn use (2003-2020) compared to before Bt corn use (1990-2002). The mean TE of the different regions also increased from 0.56 in 1990-2002 to 0.76 in 2003-2020. Table 8. Comparison of technical efficiency. Variable Mean Std. dev. Min. Max. Technical efficiency (1990-2002) 0.56 0.2346 0.2278 0.9457 Technical efficiency (2003-2020) 0.76 0.1186 0.3172 0.9479 Lastly, Figure 2 illustrates the results presented in Table 4 and Table 7 which are the computed technical efficiency scores of the different regions in the Philippines before Bt corn use (1990-2002) and after Bt corn use (2003-2020) with area harvested as input of production. It can be observed that when the two periods are compared, most of the regions have improved their efficiency in using the input for production, and most of these regions are from Southern Luzon, Visayas, and Mindanao. This implies that the regions became more efficient in utilizing their land area after the introduction of Bt corn in the country. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 451 © 2025 AESS Publications. All Rights Reserved. Figure 2. Technical efficiency scores per region before and after Bt corn1. 4. DISCUSSION AND RECOMMENDATIONS The agricultural sector in the Philippines plays a vital role in providing livelihoods for millions of Filipinos, ensuring national food security, and contributing to economic growth. Over the years, it has been the focus of numerous government policies and programs designed to address productivity constraints and mitigate the long-term risks of climate change. One of the earliest adaptive strategies was the introduction of genetically modified (GM) corn, particularly Bt corn, which significantly boosted national production. Given the importance of corn to the Philippine economy, this study examines production patterns with a focus on how climatic factors influence output in relation to the adoption of improved corn varieties. Using regional data from various government sources from 1990 to 2020, we evaluated the introduction of Bt corn in the country and determined the factors affecting corn production. To assess the impact of the intervention that allows the commercialization of Bt corn in the country, an Interrupted Time Series Analysis was employed. The results of this study show that the approval of the commercialization and use of Bt corn in the Philippines had a significant positive effect on corn production. The Philippines, as the first country in Asia to implement this technology, experienced a substantial increase in corn production, reversing the previous declining trend observed between 1990 and 2002. The Stochastic Frontier Analysis results indicate that climatic variables, represented by the De Martonne Aridity Index, significantly influence the inefficiency of production. High temperatures resulted in higher inefficiency in corn production, which indicates the challenges posed by extreme weather conditions, such as drought, on agricultural output. The study also revealed the effect of certain fertilizers on the volume of production. The positive and significant relationship of complete fertilizer application to the volume of production emphasizes the role of using this fertilizer, as it increases the volume of production. Furthermore, the magnitude of the impact of climate change, represented by the DMAI, has been observed to decrease when fertilizer inputs were included in the analysis. The mean technical efficiency has improved between two time periods, indicating that farmers became more efficient in using inputs of production, such as land and fertilizer, after the introduction of Bt corn seeds. 1This map is sourced from https://www.freeusandworldmaps.com/world-countries-philippines-pdf-printable-pdf-maps/. Asian Journal of Agriculture and Rural Development, 15(3) 2025: 444-453 452 © 2025 AESS Publications. All Rights Reserved. Based on our findings, we recommend policy implementation of Bt corn to be provided to vulnerable regions. With this, the national government could provide farmers with training and resources to adapt to extreme weather conditions and increase information regarding the benefits of using improved seed varieties, leveraging local government units, agricultural cooperatives, and state universities to reach small farmers effectively. This would make the implementation of this strategy more effective because agricultural cooperatives and state universities are situated in every part of the country. Additionally, regions experiencing high levels of aridity and precipitation, as indicated by the De Martonne Aridity Index, may require support and adaptation strategies to address the challenges posed by extreme weather events. The government needs to provide further support for irrigation systems in regions or areas with high aridity. While for extreme precipitation, the government can promote the diversification of crops and rainfall utilization strategies. The former involves cultivating crops that are more tolerant of excessive precipitation, while effective utilization of rainfall can be achieved through different means, one of which is storing and reapplying drainage waters in farming activities. The Philippines is situated in the Pacific Region, where typhoons frequently pass through. While the country is expected to experience rain throughout the year, the presence of a hot and drier climate cannot be disregarded. Therefore, when water supply for farming is lacking, the strategy of storing and reapplying drainage water could be effective. In addition, the government can promote and intensify the existing crop insurance for farmers. Crop insurance serves as a safety net and reduces risk exposure (Falco, Adinolfi, Bozzola, & Capitanio, 2014) for farmers in vulnerable regions. This would ensure them of financial compensation when their crops are damaged by extreme weather conditions and pest problems. This strategy would help mitigate the financial losses due to climate-related disasters that are brought about by climate change. This study also highlights the importance of balanced fertilizer use for improving production efficiency. Extension services should be strengthened and focused on the proper application of fertilizers to maximize yields while minimizing negative impacts on soil fertility and degradation. Fertilizer application is considered a solution to unexpected weather events like floods or dry periods (Mustafa, Hayat, & Alotaibi, 2023). While the government provides support and subsidies to farmers in terms of fertilizers, this should be followed by the promotion of using optimized fertilizers that increase efficiency in the volume of production and focus on the need for proper fertilizer application. Furthermore, the adoption and dissemination of the Bt corn variety among farmers in the regions have been found to significantly increase corn production in the country since its commercialization in 2002. If the use of the Bt corn variety is continuously supported, this will improve the productivity of the domestic corn sector and enhance the local grain supply, which would lead to reducing the country’s reliance on corn imports (Mutuc, Rejesus, Pan, & Yorobe Jr, 2012). 5. CONCLUSION Overall, these recommendations are in line with the Philippine Corn Industry Road Map 2021-2040, highlighting that since the growth in corn productivity has remained stagnant at 4.1 to 4.2 mt/ha since 2013, there is a need to enhance productivity in the country through various strategies such as optimizing rainfall utilization, effective use of fertilizer, and farm mechanization. Therefore, by addressing the challenges brought by climate change, promoting improved seed varieties, and optimizing agricultural input use such as fertilizers, the Philippines can achieve an increase in total corn production that could help attain the longstanding goal of corn self-sufficiency. Funding: This research received no specific financial support. Institutional Review Board Statement: Not applicable. Transparency: The authors state that the manuscript is honest, truthful, and transparent, that no key aspects of the investigation have been omitted, and that any differences from the study as planned have been clarified. This study followed all writing ethics. Competing Interests: The authors declare that they have no competing interests. Authors’ Contributions: Both authors contributed equally to the conception and design of the study. Both authors have read and agreed to the published version of the manuscript. REFERENCES Abao, L. (2023). Grain and feed update (Nos. 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