Spatial competition on rural bank efficiency: Evidence from Indonesia

Abstract

This study empirically examines bank spatial competition within the rural banking setting of Indonesia. The specific focus is on bank cost efficiency. It presents a new competition measure based on two spatial variables: physical distances and Thiessen polygon market boundaries. This study uses panel data from a large sample of more than 1,000 rural banks using quarterly financial data of rural banks in Indonesia from Q1–2014 to Q4–2018. Parametric or stochastic frontier analysis of Model EN is used to handle the endogeneity in bank cost efficiency measurement. The results show that bank efficiency is higher for shorter distances between banks and larger boundaries. Overall, the results support the competition-efficiency hypothesis. It also helps the idea that banks have mark-up pricing (higher market power) and may choose to reduce their effort to maximize profit.

Keywords:

• Physical distance
• market boundaries
• rural banks
• bank cost efficiency
• SFA model

JEL Classifications:

• G21
• G28
• O18
• R12

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Bank Indonesia has only released a license for 11 rural banks to issue ATMs.

2. 1 USD = 14,230.80 IDR (as per December 2018).

3. Commonly abbreviated as OJK (Otoritas Jasa Keuangan), an independent institution which has authority to regulate, supervise, examine, and investigate against the activities in the financial services sector established in 2011.

4. These data are available online via the Indonesian Financial Service Authority (Otoritas Jasa keuangan)’s website http://www.ojk.go.id.

5. Commonly abbreviated as BPS (Badan Pusat Statistik), a government institute of Indonesia that is responsible for conducting statistical surveys established in 1960. These data are available online via BPS’s website http://www.bps.go.id.

6. There are two other cost in the rural bank income statement: Marketing expenses and Research and Development expenses. However most of the banks do not put any amount in these accounts. So the effect is mostly zero.

7. I create the boundary using Thiessen polygon for each province as the border. For Java province, for instance, I run the ArcGIS software to get the these polygons for each bank. Thus, the sea and international boundaries are not included in the boundaries, because rural banks can only operate in one province.

8. The price of physical capital of rural banks in Indonesia is relatively high because their characteristic of high depreciation expenses of building and inventory.

9. The average lending rate for rural banks is 20 percent (2018).