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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93381完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊豐安 | zh_TW |
| dc.contributor.advisor | Feng-An Yang | en |
| dc.contributor.author | 曹睿 | zh_TW |
| dc.contributor.author | Patrick Joseph M. Carlos | en |
| dc.date.accessioned | 2024-07-30T16:14:01Z | - |
| dc.date.available | 2024-07-31 | - |
| dc.date.copyright | 2024-07-30 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-07-18 | - |
| dc.identifier.citation | Albert, J. R. G., Quimba, F. M. A., Tabuga, A. D., Mirandilla-Santos, M. G., Rosellon, M. A. D., Vizmanos, J. F. V., Muñoz, M. S., & Cabaero, C. C. (2019). Expanded Data Analysis and Policy Research for National ICT Household Survey 2019. Philippine Institute for Development Studies (PIDS).
Ang, A. P. (2020). One-third. Ateneo de Manila University. https://businessmirror.com.ph/2 023/05/26/one-third/ Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46(3), 399-424. Briones, R. M. (2021). Philippine agriculture: Current state, challenges, and ways forward (PIDS Policy Notes 2021-12). Philippine Institute for Development Studies. https://pidswebs.pids.gov.ph/CDN/PUBLICATIONS/pidspn2112.pdf Cabuenas, J. V. D. (2021). Study says SAP failed to give relief to poor, calls for more ambitious pandemic welfare plan. GMA News. Retrieved from https://www.gmanetwork.com/news/topstories/nation/782000/study-says-sap-failed-to-give-relief-to-poor-calls-for-more-ambitious-pandemic-welfare-plan/story/ Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31-72. Cantal, M. B. (2021). Bayanihan E-Konsulta of Office of the Vice President Leni Robredo as a form of e-government for the efficient and effective public service delivery and management during COVID-19 pandemic. University of the Philippines. Retrieved from https://www.researchgate.net/publication/357683411 Coates, J., Colaiezzi, B., & Fiedler, J. (2021). Assessing food security using household consumption expenditure surveys (HCES): A scoping literature review. Public Health Nutrition. https://www.cambridge.org/core/journals/public-health-nutrition/article/assessing-food-security-using-household-consumption-expenditure-surveys-hces-a-scoping-literature-review/96457c0b555e934b56c3f a5785313878 Department of Agriculture. (2023). General Appropriations Act, FY 202312. Retrieved from https://www.dbm.gov.ph/wp-content/uploads/GAA/GAA2023/TechGAA2023/DA/A.pdf. Department of Social Welfare and Development. (2020). Special Guidelines on the Provision of Social Amelioration Program Measures by the Department of Social Welfare and Development to the Most Affected Residents of the Area Under Community Quarantine and Continuation of the Implementation of the Social Pension for Indigent Senior Citizens and the Supplementary Feeding Programs. Retrieved from https://www.dswd.gov.ph/issuances/MCs/MC_2020-004.pdf Department of Trade and Industry. (2017). The Philippines in agribusiness global value chains. DTI Policy Brief, 2017(11). Retrieved from https://www.dti.gov.ph/sdm_downloads/2017-11-the-philippines-inagribusiness-global-value-chains-introduction/ Dy, R. T. (2020, June 15). Department of Trade and Industry. (2022). MADALI: Mapping of Digitalization and e-Commerce. Retrieved from https://ecommerce.dti.gov.ph/madali/mapped.html Doss, C. (2014). If women hold up half the sky, how much of the world’s food do they produce? In A. Quisumbing, R. Meinzen-Dick, T. Raney, A. Croppenstedt, J. Behrman, & A. Peterman (Eds.), Gender in Agriculture: Closing the Knowledge Gap (pp. 69-86). Springer. Emran, S. A., Krupnik, T. J., Aravindakshan, S., Kumar, V., & Pittelkow, C. M. (2021). Factors contributing to farm-level productivity and household income generation in coastal Bangladesh’s rice-based farming systems. PLOS ONE. https://doi.org/10.1371/journal.pone.0256694 Gershon, O., Matthew, O., Osuagwu, E., Osabohien, R., Ekhator-Mobayode, U. E., & Osabuohien, E. (2020). Household access to agricultural credit and agricultural production in Nigeria: A propensity score matching model1. South African Journal of Economic and Management Sciences, 23(1). https://hdl.handle.net/10520/EJC-1d9351402e Hamayun, M., Masukujjaman, M., & Alam, S. S. (2023). Impact of E-Commerce and Digital Marketing Adoption on the Financial and Sustainability Performance of MSMEs during the COVID-19 Pandemic: An Empirical Study. Sustainability, 15(2), 1594. Hong, C., Lu, X., & Pan, J. (2020). Do farmers gain internet dividends from E-commerce adoption? Evidence from China. Food Policy, 91, 101-118. Jain, A. M., & Carandang, C. B. (2018). Development of an online Laguna agricultural trading center. International Journal of Computing Sciences Research, 2(4), 131-1501 Muñoz, A. V., Estioco, J. R. C., Zapanta, J. R. Z., & Delos Reyes, J. A. (Year). Agricultural Glocalization: System Development of Market Mobile Application for Sustainable Local Industry in the Philippines. Muzones, M. N.. (July 12, 2022). Experts share insights about social protection in PH. Philippine Institute for Development Studies. Retrieved from https://www.pids.gov.ph/details/news/in-the-news/experts-shareinsights-about-social-protection-in-ph Nkoko, N., Cronje, N., & Swanepoel, J. W. (2024). Factors associated with food security among small-holder farming households in Lesotho. Agriculture & Food Security, 13(3). https://doi.org/10.1186/s40066-023-00454-0 OECD (2013), “Household income”, in OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth, OECD Publishing, Paris. DOI: https://doi.org/10.1787/9789264194830-7-en Orbeta, A. C. (2005). Children and the labor force participation and earnings of parents in he Philippines. Philippine Journal of Development, 32(1), 19-52. Osabohein, Romanus et al. Household access to agricultural credit and agricultural production in Nigeria: A propensity score matching model. S. Afr. j. econ. manag. sci. [online]. 2020, vol.23, n.1, pp.1-11. ISSN 2222-3436. http://dx.doi.org/10.4102/sajems.v23i1.2688. Philippine agriculture and COVID-19 impact. BusinessWorld. Retrieved from https://www.bworldonline.com/editors-picks/2020/06/15/299804/philippine-agriculture-and-covid-19- impact/#google_vignette Philippine Statistics Authority (PSA). (2020). Census of Agriculture and Fisheries. Philippine Statistics Authority. Retrieved from PSA. Philippine Statistics Authority. (2020). Agricultural wage rate survey. Retrieved from https://psada.psa.gov.ph/catalog/163. Ramon Lopez. (2020, November 23). DTI Secretary Ramon Lopez’s speech at the Go Negosyo 15th Anniversary. Department of Trade and Industry. Retrieved from https://www.dti.gov.ph/archives/archivedspeeches/go-negosyo-angat-lahat-anniversary-msme-conference/ Rappler. (2021). Timeline: The coronavirus pandemic in the Philippines. Retrieved from https://www.rappler.com/nation/timeline-coronavirus-pandemic-philippines/ Reyes, N. O. (April 12, 2020). DA’s “Plant, Plant, Plant Program” to benefit all farmers, fishers, consumers nationwide. Department of Agriculture. Retrieved December 25, 2023, from https://www.da.gov.ph/dasplant-plant-plant-program-to-benefit-all-farmers-fishers-consumers-nationwide/ Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services and Outcomes Research Methodology, 2 (3-4), 169-188 Samanta, D. (2023). Estimating impact of technological adoption in farming in Bihar: a propensity score matching approach. International Journal of Social Economics, 50(7), 1007-1016. https://doi.org/10.1108/IJSE-09-2022-0606 Santiago, A. and Roxas, F. (August 2015). Reviving Farming Interest in the Philippines Through Agricultural Entrepreneurship Education. Journal of Agriculture Food Systems and Community Development 5:1-13. DOI:10.5304/jafscd.2015.054.016. Sianesi B. 2004. An evaluation of the Swedish system of active labor market programs in the 1990s. The Review of Economics and Statistics 86(n1): 133–155. Smith, H. L. (2008)Matching With Multiple Controls to Estimate Treatment Effects in Observational Studies1Sociological Methodology, 27, 325-3532DOI: 10.1111/1467-9531.271030 Smith, J., & Todd, P. (n.d.). Matching on the estimated propensity score. Retrieved from https://economics.mit.edu/sites/default/files/publications/matching%20on%20the%20estimated%20propensity%20score_v2.pdf Valera, H. G., Mayorga, J., Pede, V. O., & Mishra, A. K. (2022). Estimating food demand and the impact of market shocks on food expenditures: The case for the Philippines and missing price data. Q Open, 2(2), qoac030. https://doi.org/10.1093/qopen/qoac030 Wang, L., Chen, Y., & Ding, S. (2022). Examining the impact of digital finance on farmer consumption inequality in China. Sustainability, 14(20), 13575. https://doi.org/10.3390/su142013575 Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. MIT Press. Wordofa, M. G., Hassen, J. Y., Endris, G. S., Aweke, C. S., Moges, D. K., & Rorisa, D. T. (2021). Adoption of improved agricultural technology and its impact on household income: A propensity score matching estimation in eastern Ethiopia. Agriculture & Food Security, 10. https://doi.org/10.1186/s40066-020-00278-2 World Bank. (2020). Transforming Philippine Agriculture: During COVID-19 and Beyond. World Bank, Washington, DC. Retrieved from https://openknowledge.worldbank.org/entities/publication/396cb748- cdd5-575d-b62a-25771ed5f439/ Yan, B., & Liu, T. (2023). Can E-Commerce Adoption Improve Agricultural Productivity? Evidence from Apple Growers in China. Sustainability, 15(1), 150. https://doi.org/10.3390/su15010150 Yi, F., Yao, L., Sun, Y., & Cai, Y. (2023). E-commerce participation, digital finance and farmers' income. China Agricultural Economic Review, 15(4), 833-852. DOI: 10.1108/CAER-03-2023-0053 Yin, Z. H., & Choi, C. H. (2022). Does e-commerce narrow the urban–rural income gap?12 Evidence from Chinese provinces. Internet Research, 32(4), 1427-1452. https://doi.org/10.1108/INTR-04-2021-0227 Yuan, S., Stuart, A. M., Laborte, A. G., et al. (2022). Southeast Asia must narrow down the yield gap to continue to be a major rice bowl. Nature Food, 3(3), 217–226. https://doi.org/10.1038/s43016-022-00477-z Zhou, R., Ji, M., & Zhao, S. (2024). Does E-Commerce Participation among Farming Households Affect Farmland Abandonment? Evidence from a Large-Scale Survey in China. Land, 13(3), 376. https://doi.org/10.3390/land13030376 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93381 | - |
| dc.description.abstract | 從農業產業轉向服務業,菲律賓多年來經歷了這樣的轉變。然而,這導致了該國食品生產的停滯,並受到近期Covid-19大流行帶來的運輸和勞動問題的加劇。其中一個被認為是解決這一挑戰的方法是電子商務。這可能直接將市場銜接到消費者,從而降低了營銷成本,提高了農民的收入和運輸成本。此外,伴隨著這一轉變,食品消費量也可能出現同步增長。該研究旨在評估電子商務銷售對菲律賓農民月收入和食品支出的影響。此外,該研究還調查了幾個可能影響是否參與電子商務的人口統計因素。我們使用了菲律賓統計局發布的年度貧困指標調查中的農業工資調查數據集。該研究使用了傾向得分匹配方法,通過根據觀察到的農民特徵將未接受治療的群體與接受治療的群體進行匹配,以獲得更準確的估計。研究結果顯示,如果農民年輕、女性、已婚且居住在城市地區,他們更有可能參與電子商務。此外,研究發現,電子商務對收入的影響不如對食品支出的影響明顯。在檢驗人口統計特徵對收入和食品消費的異質效應之後,我們發現,電子商務的正邊際效應在教育程度較低且居住在鄉村地區的農民中更為顯著。研究結果顯示,電子商務有望成為提高農民收入和食品消費的工具,從而為通過農業轉型實現可持續經濟發展鋪平道路。 | zh_TW |
| dc.description.abstract | From an agricultural industry, the Philippines has shifted to a service-oriented sector throughout the years. This led to the stagnation of the country’s food production, which was exacerbated by the transportation and labor issues brought by the recent Covid-19 pandemic.
One of the perceived solutions to this challenge is e-commerce. Potentially providing direct market linkage to consumers, this minimizes marketing costs, which increases farmer’s income and transportation costs. Coupled with this, a simultaneous rise in food consumption could be expected. The study aims to assess the impact of e-commerce selling on monthly income and food expenditure of Filipino farmers. Additionally, the study investigates several demographic factors that may be involved in deciding whether to engage in e-commerce or not. We use the dataset from the Agricultural Wage Rate Survey as part of the Annual Poverty Indicators Survey, published by the Philippine Statistics Authority. The study uses the Propensity Score Matching Method to acquire a more accurate estimate by matching the untreated group with the treated based on observed famers characteristics. The results show that farmers are inclined to engage in e-commerce if they are younger, women, married, and living in urban areas. Moreover, the study finds that the effect of e-commerce on income was not as pronounced as its effect on food expenditure. After examining the heterogenous effects of their demographic characteristics on income and food consumption, we find that the positive marginal effect of e-commerce is more prominent among farmers who have low educational attainment and rural residences. The research outcome demonstrates the potential of e-commerce as a tool in raising farmers’ income and food consumption, thereby paving the way for sustainable economic development through agricultural transformation. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-07-30T16:14:01Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-07-30T16:14:01Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | ABSTRACT i
LIST OF FIGURES iii LIST OF TABLES iv Chapter 1: INTRODUCTION 1 Chapter 2: LITERATURE REVIEW 5 2.1 The Philippine agriculture during Covid-19 5 2.2 Government programs and policy support in 2020 6 2.3 Post-pandemic and agricultural e-commerce 7 Chapter 3: DATA AND DESCRIPTIVE STATISTICS 11 3.1 Data Source 11 3.2 Theoretical Intuition of Variables 14 3.3 Outcome Variables 15 3.4 Treatment Variable 17 3.5 Descriptive statistics 17 Chapter 4: METHODOLOGY 21 Chapter 5: RESULTS 25 5.1 Propensity score estimation 25 5.2 Post-matching results 25 5.3 Estimation of ATT. 27 Chapter 6: DISCUSSION 40 6.1 The effect of e-commerce selling participation on farmer’s monthly income and food consumption 40 6.2 Sub-category analysis 41 Chapter 7: SUMMARY AND CONSLUSION 47 7.1 Conclusion 47 7.2 Policy Recommendations 48 7.3 Recommendations for Future Research 50 REFERENCES 51 | - |
| dc.language.iso | en | - |
| dc.subject | 農業 | zh_TW |
| dc.subject | 經濟學 | zh_TW |
| dc.subject | 菲律賓 | zh_TW |
| dc.subject | Economics | en |
| dc.subject | Philippines | en |
| dc.subject | Agriculture | en |
| dc.subject | e-Commerce | en |
| dc.title | 電子商務與農民收入和食品支出的相關性分析:菲律賓的實證分析 | zh_TW |
| dc.title | The Association of E-Commerce with Income and Food Consumption of Farmers: Empirical Evidence from Philippines | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 何率慈;喬翰林 | zh_TW |
| dc.contributor.oralexamcommittee | Shuay-Tsyr Ho;Chiao-Han Lin | en |
| dc.subject.keyword | 農業,經濟學,菲律賓, | zh_TW |
| dc.subject.keyword | Agriculture,Economics,Philippines,e-Commerce, | en |
| dc.relation.page | 54 | - |
| dc.identifier.doi | 10.6342/NTU202401872 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-07-18 | - |
| dc.contributor.author-college | 生物資源暨農學院 | - |
| dc.contributor.author-dept | 農業經濟學系 | - |
| 顯示於系所單位: | 農業經濟學系 | |
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