Credit Rationing of Farm Households and Agricultural production: Empirical Evidence in the Rural Areas of Central Sulawesi, Indonesia

The agricultural sector provides the highest contribution to economic development in the Central Sulawesi Province, Indonesia. On average, the share of the agriculture in the Product Domestic Regional Bruto (GRDP) is more than 40% (2003). However, poverty is a widespread problem found in this area, as indicated by almost 46% of the total households are categorized as poor and most of them are farmers. Smallholders and poor farmers may perpetually be trapped in poverty due to lack of finance needed to undertake productive investment. This is indicated by lower rate of advance agricultural technology adoption, which results the productivity of some agricultural products in this area are lower compared to the national average. This paper addresses the question of whether greater access to financial services increase agricultural production. Specific research questions addressed are as follow: (1) How many households have access to formal credit markets? (2) How many households are credit constrained? (3) What factors influence that households are credit constrained? (4) How does credit rationing influences agricultural production? As many studies have shown, many rural households lack access to either formal or informal credit institutions. In the rural areas of Central Sulawesi Province, particularly in the vicinity of the Lore Lindu National Park only 21.5% of the households have access to formal credits. The results also show that under certain conditions, only 18.1% of the households are not credit constrained. Most households are credit constrained due to a lack of collateral and because of the self-selection problem. The econometric analysis consists of two parts. The first part explores the determinants for a household to be credit constrained, focusing on the formal credit market by using a Probit model. In the second part of the analysis, we investigate the influence of being credit constrained on the rice production by applying a switching regression model. The results of the Probit model show that human capital (i.e. education and age of the head of household) as well as wealth and risk-bearing indicators are significant in determining whether a household is credit constrained. Introduction Most developing countries continue to rely on their agricultural sectors for economic growth, poverty alleviation, food security, and environmental sustainability. In Indonesia, agriculture contributed 15.6 percent to the Gross Domestic Product (GDP) in 2001 (BPS, 2005). Although its contribution to economic development has a tendency to decline, agriculture remains important to the majority of the Indonesian population, particularly to those who live in rural areas. More than 50 percent of the 1 1 Institut of Rural Development. Georg August University of Goettingen. Contact: nnuryar@gwdg.de or nnuryartono@yahoo.com households in Indonesia depend on agriculture activities as their main source of income. However, more than half (56.5 percent) of these farm households are categorized as smallholders with landholdings of less than 0.5 ha. The agricultural sector makes the largest contribution to the economic development in the Central Sulawesi province. On the average, the share of agriculture in the Regional Gross Domestic Product (GDPR) is more than 40%. Since 1999, the contribution of agriculture has been increasing and this indicates the important role of agriculture in the development process. In 1999, 2000, and 2001, the contributions were 41.1%, 43.4%, and 44.3% respectively. This fact shows that the agricultural sector in Central Sulawesi Province is a major driving force for economic growth. A lot of importance has been placed on the role of agricultural innovations in improving the welfare situation of the smallholders. Technology adoption significantly influences agricultural productivity and, in turn, household income. In addition to its importance in income generation, the adoption of new technology is important as an alternative to extensive agricultural practices. However, to undertake productive investments in agricultural technology, smallholders require sufficient access to financial capital. Smallholders may be perpetually trapped in poverty due to the lack of finances needed to undertake productive investments (J.D Von Pischke et al., 1983). Market imperfections in credit markets is hypothesized lead some potential borrowers to be rationed out of the credit markets. The credit rationing can cause a misallocation of resource in farm production. The misallocation of inputs in agricultural production lead that in the case of the credit rationed farmer to have lower profit than the non credit-constrained farmer (Carter, 1989) and ( Feder et al., 1990) Objectives of the study In Central Sulawesi the relative importance of crop income in the research area as reported by (Schwarze, 2004) is 44 percent of the total household income, with 56 percent generated from perennial and 44 percent from annual crops. This study is intended to contribute to an improved understanding of the interlinkages between access to credit and agricultural productions, particularly for rice farming activities. , Therefore the main research questions are: 1. What factors contribute to households being credit constrained in formal credit markets? 2. How does credit rationing influence agricultural profitability in rice production? The data was collected in 2000 and 2001 using standardised formal questionnaires in 293 randomly selected households out of 12 villages in rural Central Sulawesi, particularly in the vicinity of the Lore Lindu National Park. This study was part of the Collaborative Research Centre 552 “Stability of Rain Forest Margins”. For more details on the sampling and data collection see (Zeller et al., 2002) Methodology The switching regression model (SRM) is used to correct for possible sample selection bias which may arise from other interventions that provide multiple services to farmers in addition to credit. Sample selection bias arises when factors unobserved by the researcher but known to the farmer affect both the choice of technology as well as other decision variables (Fuglie and Bosch, 1995). The SRM approach is divided into two stages. It has been hypothesized that access to credit markets and liquidity constraints have a significant effect on agricultural activities. A Probit model in the first stage will be applied to determine the relationship between a farmer’s credit constraint conditions and a number of socioeconomic and credit variables, is employed as follow: C* = γ’Zi + εi, . (1)