O impacto do crédito rural no produto agropecuário brasileiro

Abstract

Resumo: O trabalho avalia a relação existente entre crédito rural e produto agropecuário nos anos de 1999 a 2018. Utilizando-se da metodologia de Vetores Autorregressivos, causalidade de Granger e o método dos mínimos quadrados ordinários e generalizados, foram estimados tanto os impactos expressos via elasticidades quanto à relação ótima decorrentes desta relação. Ao longo do período analisado, observou-se significativo aumento real do crédito rural, porém tal ampliação ficou limitada a um menor número de estabelecimentos rurais e a contratos com valores mais elevados. A despeito do ambiente de racionamento de crédito rural existente no país, conclui-se que o impacto do crédito rural total sobre o produto agropecuário foi de 0,20%. Quanto aos testes de causalidade de Granger, os resultados indicam que há precedência temporal do crédito rural ao produto agropecuário e, portanto, de forma unidirecional, o crédito rural causa, no sentido de Granger, PIB agropecuário. Por fim, quanto à relação ótima entre produto agropecuário e crédito rural, o valor estimado de crédito rural que maximiza o produto agropecuário foi de, aproximadamente, R$ 58 bilhões ao trimestre.

Heterogeneous regional effects of rural credit on agricultural production in Brazil

“…Impacts of rural credit have been widely investigated in the literature, in which the effects are measured on different outcome variables of the agricultural sector (economic and environmental) through different methodological approaches. In the Brazilian case, for example, evidence can be found on the effect of rural credit on agricultural or agribusiness GDP (Araújo et al, 2021;Borges & Parré, 2022;Gasques et al, 2017), on Total Factor Productivity (TFP), land or labor productivity and/or technical efficiency (Araújo & Vieira Filho, 2018;Costa & Freitas, 2018;Figueira, 2020;Freitas et al, 2020;Garcias & Kassouf, 2016;Gasques et al, 2017); on the quantity produced (Costa & Vieira Filho, 2018;Figueira, 2020;Souza et al, 2021); and on the income of rural producers (Araújo et al, 2020a). Furthermore, recent studies have investigated the effects of rural credit on environmental aspects such as land use, and planted and harvested areas (Araújo & Vieira Filho, 2018;Assunção & Souza, 2019;Costa & Vieira Filho, 2018;Figueira, 2020;Souza et al, 2021).…”

“…Silva & Vian (2021) classified Brazilian municipalities according to the standard of agricultural modernization, identifying a concentration of municipalities with a low standard in North and Northeast regions.4 The proportion of rural establishments that received some funding decreased from 17.76% in 2006 to 15.46% in 2017 (Instituto Brasileiro de Geografia e Estatística, 2022).5 Positive effects on agricultural income and participation in agricultural activities(Ely et al, 2019;Khandker & Koolwal, 2016;Luan & Bauer, 2016;Neves et al, 2020;Chen et al, 2021); on farmland rental market participation of rural households(Li et al, 2020); on GDP(Borges & Parré, 2022); on land use, agricultural practices and deforestation(Assunção et al, 2020;Assunção & Souza, 2019;Carrer et al, 2020;Porgo et al, 2018).…”

The Impact of Agricultural Credit on the Growth of the Agricultural Sector in Angola

“…Notably, all the above authors agreed on the positive impact of agri-credit on the formation of agricultural GDP. With regard to the development of the present study, the work of Borges and Parré [16] served as a particularly important reference.…”

“…where Y t is the endogenous variable (GDP); Y t−i represents the lagged values of the endogenous variable; X t is the exogenous variable included in the model (agricultural credit); X t−i represents the lagged values of the exogenous variable; α is the parameter; ε 1t represents the error terms of the model. According to Borges and Parré [16], it is necessary to verify the degree of stationarity of the series used in the ARDL model. The Dickey and Fuller [18] test is used to determine the level of integration of the series and to consider the possible differences that make the series stationary.…”