Alan Wall

The effects of stochastic demand and expense preference behaviour on public hospital costs and excess capacity

The literature to date on the effect of demand uncertainty on public hospital costs and excess capacity has not taken into account the role of expense preference behaviour. Similarly, the research on expense preference behaviour has not taken demand uncertainty into account. In this paper, we argue that both demand uncertainty and expense preference behaviour may affect public hospital costs and excess capacity and that ignoring either of these effects may lead to biased parameter estimates and misleading inference. To show this, we extend the analysis of Rodríguez-Alvarez and Lovell (Health Econ. 2004; 13: 157-169) by incorporating demand uncertainty into the technology to account for the hospital activity of providing standby capacity or insurance against the unexpected demand. We find that demand uncertainty in Spanish public hospitals affects hospital production decisions and increases costs. Our results also show that overcapitalization in these hospitals can be explained by hospitals providing insurance demand when faced with demand uncertainty. We also find evidence of expense preference behaviour. We conclude that both stochastic demand and expense preference behaviour should be taken into account when analysing hospital costs and production.

A Parametric Approach to Estimating Eco-Efficiency

The concept of eco-efficiency is becoming increasingly popular as a tool to capture economic and environmental aspects of agricultural production. The literature to date has exclusively used the Data Envelopment Analysis (DEA) approach to measure producers’ eco-efficiency. We show that it can also be estimated using a Stochastic Frontier Analysis (SFA) approach. Our approach not only allows controlling for random noise in the data but also permits an analysis of the potential substitutability between environmental pressures. We provide an empirical application of our model to data on a sample of Spanish dairy farms.

Dynamic Cost Efficiency in Port Infrastructure Using a Directional Distance Function: Accounting for the Adjustment of Quasi-Fixed Inputs Over Time

This paper analyzes dynamic efficiency in ports. Using parametric techniques we estimate a stochastic cost frontier to measure overall long-run cost efficiency and an input-oriented directional distance to measure dynamic technical efficiency for a set of 26 Spanish port authorities observed over the period 1993–2012. Technical inefficiency is conceived as the ability of ports to simultaneously expand gross investment and contract variable inputs while maintaining output constant. Ports in this framework are assumed to invest with a view to minimizing the present value of future production costs. Our results show that ports could achieve long-run cost savings of over 38%, two-thirds of which could be achieved by reducing input use and the remainder to changing the input-mix used.

Reserve capacity of public and private hospitals in response to demand uncertainty.

A feature of hospitals is that they face uncertain demand for the services they offer. To cover fluctuations in demand, they need to maintain reserve service capacity in the form of beds, equipment, personnel, etc. to minimize the probability of excess queuing or turning away patients, creating a trade-off between reserve service capacity and economic costs. Using a simple theoretical framework, we show how the reserve capacity established depends on institutional characteristics that can affect the objective of the hospital. In particular, we show that private and public hospitals may provide different levels of reserve capacity. In an empirical application using a panel data set of Spanish hospitals over the period 1996-2006, we model reserve service capacity using a distance frontier approach. Our results show that private hospitals generally react to a lesser extent to demand uncertainty than public hospitals.

Measuring Eco-efficiency Using the Stochastic Frontier Analysis Approach

The concept of eco-efficiency has been receiving increasing attention in recent years in the literature on the environmental impact of economic activity. Eco-efficiency compares economic results derived from the production of goods and services with aggregate measures of the environmental impacts (or ‘pressures’) generated by the production process. The literature to date has exclusively used the Data Envelopment Analysis (DEA) approach to construct this index of environmental pressures, and determinants of eco-efficiency have typically been incorporated by carrying out bootstrapped truncated regressions in a second stage. We advocate the use of a Stochastic Frontier Analysis (SFA) approach to measuring eco-efficiency. In addition to dealing with measurement errors in the data, the stochastic frontier model we propose allows determinants of eco-efficiency to be incorporated in a one stage. Another advantage of our model is that it permits an analysis of the potential substitutability between environmental pressures. We provide an empirical application of our model to data on a sample of Spanish dairy farms which was used in a previous study of the determinants eco-efficiency that employed DEA-based truncated regression techniques and that serves as a useful benchmark for comparison.

Trading in Alternative Organized Markets Based on Individual and Aggregate Behavior of Participants

We study competition between stock exchanges in a game where the wealth of individuals varies over time, creating liquidity and investment needs. On the basis of a profit-maximizing investment rule, participants must decide how to allocate their wealth between bank deposits and securities. In each stage there is a shock to the price of the security, and participants may pay a fee to become analysts in order to determine the nature of this shock and trade on the information. As any player may become an analyst, the number of analysts is endogenously determined. Certain players (insiders) may receive information on the shock without becoming analysts. We carry out a numerical analysis which allows us to study competition between exchanges and to determine the threshold levels associated with switching from one exchange to another. In our model, we find that traders cluster together and liquidity follows liquidity, further reducing the order flow of the stock exchange with the lower order flow. This result is similar to those of Chowdhry and Nanda (1991) and Admati and Pfleiderer (1988). However, in our case, we are able to quantify not only the effect of the volume of the order flow on the decision of participants to trade in a given stock exchange but also the joint effect of other additional factors such as the costs of submitting an order to each of the stock exchanges that compete simultaneously or the differences in terms of the probability of informed trading in both exchanges.