The cost of Corporate Social Responsibility: the case of the Community Reinvestment Act

A Data Envelopment Analysis (DEA) cost minimization model is employed to estimate the cost to thrift institutions of achieving a rating of ‘outstanding’ under the anti-redlining Community Reinvestment Act, which is viewed as an act of voluntary Corporate Social Responsibility (CSR). There is no difference in overall cost efficiency between ‘outstanding’ and minimally compliant ‘satisfactory’ thrifts. However, the sources of cost inefficiency do differ, and an ‘outstanding’ rating involves annual extra cost of $6.547 million or, 1.2% of total costs. This added cost is the shadow price of CSR since it is not an explicit output or input in the DEA cost model. Before and after-tax rates of return are the same for the ‘outstanding’ and ‘satisfactory’ thrifts, which implies a recoupment of the extra cost. The findings are consistent with CSR as a management choice based on balancing marginal cost and marginal revenue. An incidental finding is that larger thrifts are less efficient.

On the price of risk in a mean-risk optimization model

We investigate a mean-risk model for portfolio optimization where the risk quantifier is selected as a semi-deviation or as a standard deviation of the portfolio return. We analyse the existence of solutions to the problem under general assumptions. When the short positions are not constrained, we establish a lower bound on the cost of risk associated with optimizing the mean–standard deviation model and show that optimal solutions do not exist for any positive price of risk which is smaller than that bound. If the investment allocations are constrained, then we obtain a lower bound on the price of risk in terms of the shadow prices of said constraints and the data of the problem. A Value-at-Risk constraint in the model implies an upper bound on the price of risk for all feasible portfolios. Furthermore, we provide conditions under which using this upper bound as the cost of risk parameter in the model provides a non-dominated optimal portfolio with respect to the second-order stochastic dominance. Additionally, we study the relationship between minimizing the mean–standard deviation objective and maximizing the coefficient of variation and show that both problems are equivalent when the upper bound is used as the cost of risk. Additional relations between the Value-at-Risk constraint and the coefficient of variation are discussed as well. We illustrate the results numerically.