AN ANALYSIS OF PERSONAL AND MANAGERIAL CHARACTERISTICS OF PERUVIAN SMALLHOLDERS AS AN ALTERNATIVE APPROACH TO IMPROVE THEIR FINANCIAL INCLUSION
DOI:
https://doi.org/10.31413/nat.v14i2.20425Palavras-chave:
financial behaviour, financial inclusion, smallholders, MIMICResumo
Análise das características pessoais e gerenciais dos pequenos produtores peruanos como abordagem alternativa para melhorar sua inclusão financeira
RESUMO: O acesso ao financiamento é um desafio significativo que afeta a capacidade financeira limitada do setor agrícola, bem como a adoção restrita de tecnologias e de modelos técnicos pelos pequenos agricultores. Tal circunstância resulta em uma diminuição da produtividade setorial, mais acentuada em países em desenvolvimento, como o Peru. Para abordar essa lacuna, o estudo examinou a influência das características individuais e empresariais sobre o comportamento financeiro de pequenos agricultores peruanos com e sem acesso ao crédito. Para tanto, foi realizada uma pesquisa com uma amostra de 198 pequenos agricultores peruanos, provenientes de diversas regiões do país. A análise dos dados foi realizada por meio de um modelo de Múltiplos Indicadores e Múltiplas Causas (MIMIC), utilizado para investigar as relações entre variáveis observadas e latentes. Os resultados deste estudo ressaltam a importância de implementar intervenções inovadoras de avaliação para aprimorar as habilidades de tomada de decisão financeira e facilitar o acesso da população rural e agrícola do Peru aos instrumentos financeiros.
Palavras-chave: comportamento financeiro; inclusão financeira; pequenos agricultores; MIMIC.
Referências
ADUSEI, M.; ADELEYE, N. Credit information sharing and non-performing loans: The moderating role of creditor rights protection. International Journal of Finance and Economics, v. 27, n. 4, p. 4756-4769, 2020. https://doi.org/10.1002/ijfe.2398
AMERIKS, J.; CAPLIN, A.; LEAHY, J.; TYLER, T. Measuring self-control problems. American Economic Review, v. 97, n. 3, p. 966-972, 2007. https://doi.org/10.1257/aer.97.3.966
ARRÁIZ, I.; BRUHN, M.; STUCCHI, R. Psychometrics as a tool to improve credit information. The World Bank Economic Review, v. 30, S67-S76, 2017. https://doi.org/10.1093/wber/lhw016
BAKER, R.; BRICK, J. M.; BATES, N. A.; BATTAGLIA, M.; COUPER, M. P.; DEVER, J. A.; GILE, K. J.; TOURANGEAU, R. Summary report of the AAPOR task force on non-probability sampling. Journal of Survey Statistics and Methodology, v. 1, n. 2, p. 90-143, 2013. https://doi.org/10.1093/jssam/smt008
BALANA, B. B.; OYEYEMI, M. A. Agricultural credit constraints in smallholder farming in developing countries: Evidence from Nigeria. World Development Sustainability, v. 1, e100012, 2022. https://doi.org/10.1016/j.wds.2022.100012
BENAMI, E.; CARTER, M. R. Can digital technologies reshape rural microfinance? Implications for savings, credit, & insurance. Applied Economic Perspectives and Policy, v. 43, n. 4, p. 1196-1220, 2021. https://doi.org/10.1002/aepp.13151
BENNI, N. El fortalecimiento de la inclusión financiera digital en zonas rurales y agropecuarias - recomendaciones para América Latina y el Caribe. Roma: FAO, 2022. 70p. Available online: https://doi.org/10.4060/cc2877es
BLAZQUEZ-SORIANO, A.; RAMOS-SANDOVAL, R. Information transfer as a tool to improve the resilience of farmers against the effects of climate change: the case of the Peruvian National Agrarian Innovation System. Agricultural Systems, v. 200, e103431, 2022. https://doi.org/10.1016/j.agsy.2022.103431
BOLLEN, K. A. Structural equations with latent variables. John Wiley & Sons, 1989. 514p. https://doi.org/10.1002/9781118619179
BONNKE, S. M.; NGUEZET, P. M. D.; BIRINGANINE, A. N.; JEAN-JACQUES, M. S.; MANYONG, V.; BAMBA, Z. Farmers’ credit access in the Democratic Republic of Congo: Empirical evidence from youth tomato farmers in Ruzizi plain in South Kivu. Cogent Economics & Finance, v. 10, n. 1, 2022. https://doi.org/10.1080/23322039.2022.2071386
BOUCHER, S.; GUIRKINGER, C. Risk, wealth, and sectoral choice in rural credit markets. American Journal of Agricultural Economics, v. 89, n. 4, p. 991-1004, 2007. https://doi.org/10.1111/j.1467-8276.2007.01009.x
BROWN, T. A. Confirmatory Factor Analysis for Applied Research (Methodology in The Social Sciences Series). 2nd ed. The Guilford Press, 2015. 462p.
CENAGRO. Censo Nacional Agropecuario 2012. Lima: Instituto Nacional de Estadística e Informática. Available online: https://proyectos.inei.gob.pe/microdatos/
CHAUDHURI, K.; CHOWDHURY, T. Financial performance evaluation: a structural equation approach. Journal of Emerging Market Finance, v. 11, n. 1, p. 1-36, 2012. https://doi.org/10.1177/09726527110110010
CONNING, J.; UDRY, C. Rural financial markets in developing countries. In: EVENSON, R. E.; PINGALI, P.; SCHULTZ, T. P. The Handbook of Agricultural Economics. New Haven, CT: Yale University, Economic Growth Center, 2005. 89p. vol. 3 (Center Discussion Paper, 914). Available online: http://www.econ.yale.edu/~egcenter/http://ssrn.com/abstract=756965http://www.econ.yale.edu/~egcenter/research.htm
DAVIES, S.; FINNEY, A.; COLLARD, S.; TREND, L. Borrowing Behaviour: A systematic review. Bristol: University of Bristol / Standard Life Foundation, 2019. 74p. Available online: http://www.bristol.ac.uk/media-library/sites/geography/pfrc/pfrc1901-borrowing.pdf
DE OLLOQUI, F.; FERNÁNDEZ, C. Financiamiento del sector agroalimentario y desarrollo rural. Banco Interamericano de Desarrollo, 2017. 44p. Available online: rural. http://www.iadb.org
DEVI, J. A.; DEVI, K. U.; VANI, C. S.; UMAR, S. N. Role of digital technologies in enhancing financial inclusion of farmers in Guntur, Andhra Pradesh. Millennial Asia, 0(0), 2026. https://doi.org/10.1177/09763996261416091
DHAMI, S.; ARSHAD, J.; AL-NOWAIHI, A. Psychological and social motivations in microfinance contracts: Theory and evidence. Journal of Development Economics, v. 158, e102912, 2022. https://doi.org/10.1016/j.jdeveco.2022.102912
DLUGOSCH, T. J.; KLINGER, B.; FRESE, M.; KLEHE, U. C. Personality-based selection of entrepreneurial borrowers to reduce credit risk: Two studies on prediction models in low- and high-stakes settings in developing countries. Journal of Organizational Behaviour, v. 39, n. 5, p. 612-628, 2018. https://doi.org/10.1002/job.2236
DUMAN, E.; AKTAS, M. S.; YAHSI, E. Credit Risk Prediction Based on Psychometric Data. Computers, v. 12, n. 12, e248, 2023. https://doi.org/10.3390/computers12120248
ELOSUA, P.; MUJIKA, J.; ALMEIDA, L. S.; HERMOSILLA, D. Procedimientos analítico-racionales en la adaptación de tests. Adaptación al español de la batería de pruebas de razonamiento. Revista Latinoamericana de Psicología, v. 46, n. 2, p. 117-126, 2014. https://doi.org/10.1016/s0120-0534(14)70015-9
ESCOBAL, J.; FAVARETO, A.; AGUIRRE, F.; PONCE, C. Linkage to dynamic markets and rural territorial development in Latin America. World Development, v. 73, p. 44-55, 2015. https://doi.org/https://doi.org/10.1016/j.worlddev.2014.09.017
FU, X.; GUO, C. Digital inclusive finance and the construction of agricultural modernization. International Review of Economics & Finance, v. 102, e104332, 2025. https://doi.org/10.1016/j.iref.2025.104332
FURNHAM, A.; KIRKCALDY, B. D.; LYNN, R. National attitudes to competitiveness, money, and work among young people: first, second, and third world differences. Human Relations, v. 47, n. 1, p. 119-132, 1994. https://doi.org/10.1177/001872679404700106
GALLOWAY, A. Non-Probability Sampling. In: KEMPF-LEONARD, K. (Ed.). Encyclopedia of Social Measurement. Elsevier, 2005. p. 859-864. https://doi.org/10.1016/B0-12-369398-5/00382-0
GANBAT, M.; BATBAATAR, E.; BAZARRAGCHAA, G.; IDER, T.; GANTUMUR, E.; DASHKHOROL, L.; ALTANTSATSRALT, K.; NEMEKH, M.; DASHDONDOG, E.; NAMSRAI, O. E. Effect of psychological factors on credit risk: A case study of the microlending service in Mongolia. Behavioural Sciences, v. 11, n. 4, e47, 2021. https://doi.org/10.3390/bs11040047
GEHRIG, S.; MESOUDI, A.; LAMBA, S. Banking on cooperation: an evolutionary analysis of microfinance loan repayment behaviour. Evolutionary Human Sciences, v. 3, e2, p. 1-23, 2021. https://doi.org/10.1017/ehs.2020.64
GHEZZI-SOLÍS, P. E.; Cómo fortalecer el Agrobanco y el financiamiento agropecuario: Una visión productivista. San José, C.R.: Instituto Interamericano de Cooperación para la Agricultura (IICA), 2021. 50p. Available online: https://hacerperu.pe/wp-content/uploads/2023/05/Comofortalecerelagrobancoyelfinanciamientoagropecuario-PieroGhezzi.pdf.
HAIR, J. F.; BLACK, W. C.; BABIN, B. J.; ANDERSON, R. E. Multivariate data analysis. 8th ed. Cengage Learning, 2019. 834p.
HANSSON, H.; SOK, J. Perceived obstacles for business development: Construct development and the impact of farmers’ personal values and personality profile in the Swedish agricultural context. Journal of Rural Studies, v. 81, p. 17-26, 2021. https://doi.org/10.1016/j.jrurstud.2020.12.004
HEIDHUES, P.; KOOSZEGI, B. Exploiting Naïvete about Self-Control in the Credit Market. American Economic Review, v. 100, n. 5, p. 2279-2303, 2010. https://doi.org/10.1257/aer.100.5.2279
INEI_Instituto Nacional de Estadística e Informática. - (2025). Productores Agropecuarios - Principales Resultados de la Encuesta Nacional Agropecuaria (ENA), 2018-2019 y 2022-2024. Lima, Perú. 2025. Available online: https://www.gob.pe/institucion/inei/informes-publicaciones/6879473-productores-agropecuarios-principales-resultados-de-la-encuesta-nacional-agropecuaria-ena-2018-2019-y-2022-2024
INTERNATIONAL FINANCE CORPORATION. Handbook: Digital Financial Services for Agriculture. World Bank Group, 2018. 236p. Available online: https://www.ifc.org/en/insights-reports/2018/dfs-agriculture
JIANG, C.; HAO, W.; WANG, T.; ZHANG, Y. Leveraging agricultural production trusteeship to enhance agricultural production efficiency, promote sustainable agricultural practices, and optimize resources: empirical evidence from China. Frontiers in Sustainable Food Systems, v. 9, e1532013, 2025. https://doi.org/10.3389/fsufs.2025.1532013
JÖRESKOG, K. G.; GOLDBERGER, A. S. Estimation of a model with multiple indicators and multiple causes of a single latent variable. Journal of the American Statistical Association, v. 70, n. 351a, p. 631-639, 1975. https://doi.org/10.1080/01621459.1975.10482485
KAPOOR, S.; SHUSHMA, H. Investigating the agricultural finance sources, access and the factors affecting its demand. Journal of Innovation and Management, v. 1, n. 1, e1, 2024. https://doi.org/10.1177/ijim.241272314
KLINGER, B.; CASTRO, L.; SZENKMAN, P.; KHWAJA, A. Unlocking SME Finance in Argentina with Psychometrics. Inter-American Development Bank (IADB), 2013. 37p. (Technical Note, 532). Available online: http://www.iadb.org
MA, H.; LI, G.; LIU, R.; SHEN, M.; LIU, X. The personal credit default discrimination model based on DF21. Journal of Intelligent & Fuzzy Systems, v. 44, p. 3907-3925, 2023. https://doi.org/10.3233/JIFS-212780
MACCALLUM, R. C.; BROWNE, M. W.; SUGAWARA, H. M. Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, v. 1, n. 2, p. 130-149, 1996. https://doi.org/10.1037/1082-989X.1.2.130
MCNAIR, S.; SUMMERS, B.; DE BRUIN, W. B.; RANYARD, R. Individual-level factors predicting consumer financial behaviour at a time of high pressure. Personality and Individual Differences, v. 99, p. 211-216, 2016. https://doi.org/10.1016/j.paid.2016.05.034
MUÑIZ, J.; ELOSUA, P.; HAMBLETON, R. K. Directrices para la traducción y adaptación de los tests: segunda edición. Psicothema, v. 25, n. 2, p. 151-157, 2013). https://doi.org/10.7334/psicothema2013.24
MWIRIGI, D.; FEKETE-FARKAS, M.; LAKNER, Z. A Bibliometric Analysis of Borrowers’ Behaviour. Journal of Risk and Financial Management, v. 17, n. 3, e111, 2024. https://doi.org/10.3390/jrfm17030111
NAYAK, N. C.; MAHAKUD, J.; MAHALIK, M. K.; JENAMANI, M.; SAMAL, A.; SEN, S.; MOHANTY, A. R. (What determines financial inclusion? A household-level investigation in rural Odisha, India. Journal of Social and Economic Development, v. 26, n. 3, p. 888-906, 2024. https://doi.org/10.1007/s40847-023-00302-8
OVIEDO, H. C.; CAMPO‐ARIAS, A. Aproximación al uso del coeficiente alfa de Cronbach. Revista Colombiana De Psiquiatría, v. 34, n. 4, p. 572-580, 2005. https://www.redalyc.org/pdf/806/80634409.pdf
ÖZŞAHIN, M.; YÜRÜR, S.; COŞKUN, E. A field research to identify psychological factors influencing the debt repayment behaviour in Turkey. Emerging Markets Journal, v. 8, n. 2, p. 1-9, 2018. https://doi.org/10.5195/emaj.2018.156
PENG, Y.; REN, Y.; LI, H. Do credit constraints affect households’ economic vulnerability? Empirical evidence from rural China. Journal of Integrative Agriculture, v. 20, n. 9, p. 2552-2568, 2021. https://doi.org/10.1016/s2095-3119(20)63557-2
PERRY, V. G.; MORRIS, M. D. Who is in control? the role of self-perception, knowledge, and income in explaining consumer financial behaviour. Journal of Consumer Affairs, v. 39, n. 2, p. 299-313, 2006. https://doi.org/10.1111/j.1745-6606.2005.00016.x
PHIRI, A.; CHIPETA, G. T.; CHAWINGA, W. D. Information behaviour of rural smallholder farmers in some selected developing countries: A literature review. Information Development, v. 35, n. 5, p. 831-838, 2018. https://doi.org/10.1177/0266666918804861
PING, L.; XIAOSONG, S.; JINZHAO, L. Research on farmers’ household credit behaviour and social capital acquisition. Frontiers in Psychology, v. 13, e961862, 2022. https://doi.org/10.3389/fpsyg.2022.961862
RABBANI, N. Financial conditions and borrowing behaviour of university students during the COVID-19 Pandemic: Evidence from Bangladesh. Sustainability, v. 15, n. 19, e14123, 2023. https://doi.org/10.3390/su151914123
RAHMAN, M.; AZMA, N.; MASUD, M. A. K.; ISMAIL, Y. Determinants of indebtedness: Influence of behavioural and demographic factors. International Journal of Financial Studies, v. 8, n. 1, e8, 2020. https://doi.org/10.3390/ijfs8010008
RAYHAN, M. J.; RAHMAN, S. M. M.; MAMUN, A. A.; SAIF, A. N. M.; ISLAM, K. M. A.; ALOM, M. M.; HAFIZ, N. FinTech solutions for sustainable agricultural value chains: A perspective from smallholder farmers. Business Strategy & Development, v. 7, n. 2, e358, 2024. https://doi.org/10.1002/bsd2.358
RAMOS-SANDOVAL, R.; LARA, R. Geographic data science for analysis in rural areas: a study case of financial services accessible in the Peruvian agricultural sector. In: SILHAVY, R.; SILHAVY, P. (Eds.). Artificial intelligence application in networks and systems – CSOC 2023. Lecture Notes in Networks and Systems, vol. 724, Springer, 2023. p. 246-259. https://doi.org/10.1007/978-3-031-35314-7_24
RAMOS-SANDOVAL, R.; MENDIBURU-DÍAZ, C. Why do small farmers have less access to credit? a microdata analysis of the Peruvian case. Nativa, v. 12, n. 2, p. 215-225, 2024. https://doi.org/10.31413/nativa.v12i2.16758
RAMOS-SANDOVAL, R.; GARCÍA-ÁLVAREZ-COQUE, J. M.; MAS-VERDÚ, F. (2016). Innovation behaviour and the use of research and extension services in small-scale agricultural holdings. Spanish Journal of Agricultural Research, v. 14, n. 4, e0106-e0106, 2016. https://doi.org/10.5424/sjar/2016144-8548
SAQIB, S. E.; AHMAD, M. M.; PANEZAI, S.; ALI, U. Factors influencing farmers’ adoption of agricultural credit as a risk management strategy: the case of Pakistan. International Journal of Disaster Risk Reduction, v. 17, p. 67-76, 2016. https://doi.org/10.1016/j.ijdrr.2016.03.008
SARFO, Y.; MUSSHOFF, O.; WEBER, R. Farmers’ awareness of digital credit: Does financial literacy matter? Journal of International Development, v. 35, n. 8, p. 2299-2317, 2023. https://doi.org/10.1002/jid.3774
SIFRAIN, R. Does Psychometric Testing in Microfinance Actually Work? - The Case of Sogesol. Journal of Financial Risk Management, v. 9, n. 3, p. 278-313, 2020. https://doi.org/10.4236/jfrm.2020.93016
TABER, K. S. The use of Cronbach’s Alpha when developing and reporting research instruments in science education. Research in Science Education, v. 48, n. 6, p. 1273-1296, 2017. https://doi.org/10.1007/s11165-016-9602-2
TAN, Y.; HU, W. Social capital, family wealth and normal credit rationing to famers. Financial Forum, v. 22, p. 37-49, 2017.
TANG, T. L.-P. The development of a short Money Ethic Scale: Attitudes toward money and pay satisfaction revisited. Personality and Individual Differences, v. 19, n. 6, p. 809-816, 1995. https://doi.org/10.1016/S0191-8869(95)00133-6
TRIVELLI, C. Finanzas agropecuarias desafío pendiente en la agenda agraria en Perú. Lima: Instituto de Estudios Peruanos, 2021. 35p. https://doi.org/10.2499/p15738coll2.134248
TRIVELLI, C.; CABALLERO, E. ¿Cerrando brechas?: las estrategias nacionales de inclusión financiera en América Latina y el Caribe. Lima: Instituto de Estudios Peruanos, 2018. 114p. Available online: https://doi.org/10.2499/p15738coll2.134248
VO, H. H.; MIZUNOYA, T.; NGUYEN, C. D. Determinants of farmers’ adaptation decisions to climate change in the central coastal region of Vietnam. Asia-Pacific Journal of Regional Science, v. 5, n. 2, p. 327-349, 2021. https://doi.org/10.1007/s41685-020-00181-5
WORLD BANK. The Global Findex Database 2017: Measuring financial inclusion and the fintech revolution. The World Bank Group, 2018. 151p. Available online: https://documents1.worldbank.org/curated/en/332881525873182837/pdf/126033-PUB-PUBLIC-pubdate-4-19-2018.pdf
XIAO, J. J. Applying behaviour theories to financial behaviour. In: XIAO, J. J. (Ed.). Handbook of Consumer Finance Research. New York, NY: Springer, p. 69-81, 2008. https://doi.org/10.1007/978-0-387-75734-6_5
YAZDANPARAST, A.; ALHENAWIB, Y. Personality and borrowing behaviour: An examination of the role of need for material resources and need for arousal traits on household’s borrowing decisions. Financial Services Review, v. 26, n. 1, p. 55-85, 2017. https://doi.org/10.61190/fsr.v26i1.3296
ZHANG, A.; WANG, S.; LIU, B.; LIU, P. How fintech impacts pre- and post-loan risk in Chinese commercial banks. International Journal of Finance and Economics, v. 27, n. 2, p. 2514-2529, 2022. https://doi.org/10.1002/ijfe.2284
ZHAO, Q.; SHEN, Y.; LI, C. Credit behaviours of rural households in the perspective of complex social networks. Complexity, v. 2021, 9975856, p. 1-13, 2021. https://doi.org/10.1155/2021/9975856
ZULFIQAR, F.; SHANG, J.; ZADA, M.; ALAM, Q.; RAUF, T. Identifying the determinants of access to agricultural credit in Southern Punjab of Pakistan. GeoJournal, v. 86, n. 6, p. 2767-2776, 2021. https://doi.org/10.1007/s10708-020-10227-y
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