Although many studies have investigated the relationship between market structure and the prices of bank services, most have been concerned with metropolitan areas. These studies generally have used bank balance sheet and income statement ratios as bank conduct proxies. Moreover, prior studies have approximated local banking markets with county or SMSA boundaries.
This study develops a methodology for delineating the geographic boundaries of local banking markets through the use of secondary economic and demographic data. This methodology is utilized to delineate rural banking markets in the states of Iowa, Minnesota, and Wisconsin. The relationship between those markets and rural bank conduct is investigated. Conduct is measured with explicit price and nonprice information generated by telephone survey.
The market determination methodology is based on the assumption that people will bank where they live, work, or obtain goods and services. Using a classification system which categorizes communities according to variety and amount of retail business transactions, a gradient concept is developed which initially approximates market boundaries according to local minima in the gradient.
This procedure, which determines where residents are likely to shop, is supplemented with commuting data based on minor civil divisions to determine where residents work. The resulting “areas of convenience” designate the locale where local customers will ordinarily select banking services.
The natural banking markets determined for the entire state of Minnesota are compared with banking markets approximated by county or SMSA boundaries. The counties or SMSAs are allowed to underestimate or overestimate the natural market by as much as 30 percent of total deposits before being classified as unacceptable approximators. According to these criteria, 61 percent of the counties and SMSAs are found to be unacceptable approximators. When the criteria are tightened to permit only 10 percent underestimation or overestimation, 79 percent of the counties and SMSAs are rated unacceptable. This implies that researchers and policy makers should be cautious about approximating local banking markets with political boundaries. Additional methods for testing the procedure and making it operational are suggested.
The methodology is used to delineate local banking markets in Iowa, Minnesota, and Wisconsin. Twenty-five rural markets are randomly selected from each state. A total of 333 banks from these markets forms the basis for the structure-conduct analysis. These banks are surveyed by telephone to determine explicit price and nonprice information.
Three estimation models (linear, hyperbolic, and cubic) are developed to analyze the relationship between rural bank market structure and the survey variables. The basic linear model generally provides the best fit.
Increases in concentration are significantly associated with increases in the rates rural banks charge on each type of loan included in the study. Moreover, increases in market share are significantly associated with increases in nonprice effort. Consequently, policy makers are confronted with selecting between: (1) higher prices and increased provision of ancillary banking services, or (2) lower prices and less service.