Demand estimation and consumer welfare in the banking industry

This paper estimates a structural demand model for commercial bank deposit services in order to measure the effects on consumers given dramatic changes in bank services throughout US branching deregulation in the 1990s. Following the discrete choice literature, consumer decisions are based on prices and bank characteristics. Consumers are found to respond to deposit rates, and to a lesser extent, to account fees, in choosing a depository institution. Moreover, consumers respond favorably to the branch staffing and geographic density, as well as to the bank’s age, size, and geographic diversification. Consumers in most markets experience a slight increase in welfare throughout the period.     

Increasing the length of parents' birth-related leave: The effect on children's long-term educational outcomes

Investments in children are generally seen as investments in the future economy. In this study I focus on time investments in children as I investigate the long-term educational effects on children of increasing parents' birth-related leave from 14 to 20 weeks using a natural experiment from 1984 in Denmark. The causal effect of the reform is identified using regression discontinuity design to compare a population sample of children born shortly before and shortly after the reform took effect. Results indicate that increasing parents' access to birth-related leave has no measurable effect on children's long-term educational outcomes. Mothers' incomes and career opportunities are slightly positively affected by the reform.     

Information Barriers to Adoption of Agricultural Technologies: Willingness to Pay for Certified Seed of an Open Pollinated Maize Variety in Northern Uganda

We examine smallholder farmers’ willingness to pay for agricultural technology and whether information is a constraint to adoption of certified maize seed in Northern Uganda. The uptake of improved maize varieties by smallholder farmers in Uganda remains persistently low, despite the higher yield potential compared to traditional varieties. A recently growing body of literature identifies information constraints as a potential barrier to adoption of agricultural technologies. We used incentive compatible Becker‐DeGroot‐Marschak auctions to elicit willingness to pay for quality assured improved maize seed by 1,009 smallholder farmers, and conducted a randomised evaluation to test the effect of an information intervention on farmers’ knowledge of seed certification. Our results show that the randomised information treatment enhanced farmers’ knowledge of certified seed. However, using the information treatment as an instrumental variable for knowledge, we find no evidence of a causal effect of knowledge on willingness to pay, suggesting that even though farmers are information constrained, this constraint does not affect adoption of certified seed directly. Nevertheless, only 14% of sampled farmers were willing to pay the market price, which corresponds closely with actual observed demand for certified seed in the previous season. This suggests that there are other barriers to adoption than information and awareness.     

Benchmarking and firm heterogeneity: a latent class analysis for German electricity distribution companies

In January 2009, the German Federal Network Agency introduced incentive regulation for the electricity distribution sector based on results obtained from econometric and nonparametric benchmarking analysis. One main problem for the regulator in assigning the relative efficiency scores is unobserved firm-specific factors such as network and technological differences. Comparing the efficiency of different firms usually assumes that they operate under the same production technology, thus unobserved factors might be inappropriately understood as inefficiency. To avoid this type of misspecification in regulatory practice, estimation is carried out in two stages: in the first stage observations are classified into two categories according to the size of the network operators. Then separate analyses are conducted for each subgroup. This article shows how to disentangle the heterogeneity from inefficiency in one step, using a latent class model for stochastic frontiers. As the classification is not based on a priori sample separation criteria it delivers more robust, statistically significant, and testable results. Against this background, we analyze the level of technical efficiency of different subgroups from a sample of 200 regional and local German electricity distribution companies for a balanced panel data set (2001–2005). Testing the hypothesis if larger distributors operate under a different technology than smaller ones, we assess if a single step latent class model provides new insights to the use of benchmarking approaches within the incentive regulation schemes.     

Testing Prediction Performance of Poverty Models: Empirical Evidence from Uganda

This paper examines the performance of a method of predicting poverty rates. Because most developing countries cannot justify the expense of frequent household budget surveys, additional low‐cost methods have been developed and used. The prediction method is based on a model linking the proportion of poor households to suitable explanatory variables (consumption proxies). These consumption proxies are variables that can be collected at much lower cost through smaller annual surveys. Several applications have shown that such models can produce poverty estimates with confidence intervals of a similar magnitude to the poverty estimates from the household budget surveys. There is, however, limited evidence of how well the methods perform out‐of‐sample. A series of seven household budget surveys conducted in Uganda in the period 1993–2005 allows us to test the prediction performance of the model. We test the poverty models by using data from one survey to predict the proportion of poor households in other surveys, and vice versa. The results are encouraging, as all models predict similar poverty trends. Although in most cases the predictions are precise, sometimes they differ significantly from the poverty level estimated from the survey directly.