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.     

Overcoming the “recency trap” in customer relationship management

Purchase likelihood typically declines as the length of time since the customer’s previous purchase (“recency”) increases. As a result, firms face a “recency trap,” whereby recency increases for customers who do not purchase in a given period, making it even less likely they will purchase in the next period. Eventually the customer is effectively lost to the firm. We develop and illustrate a modeling approach to target a firm’s marketing efforts, keeping in mind the customer’s recency state. This requires an empirical model that predicts purchase likelihood as a function of recency and marketing, and a dynamic optimization that prescribes the most profitable way to target customers. In our application we find that customers’ purchase likelihoods as well as response to marketing depend on recency. These results are used to show that the targeting of email and direct mail should depend on the customer’s recency and that the optimal decision policy enables the average high recency customer, who currently is virtually worthless to the firm, to become profitable.     

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.     

New class divisions in a modern working life?

This article questions the usefulness of a traditional class divide as a tool for understanding a contemporary working environment among manual and non‐manual workers in the oil service industry. The case of study is an enterprise within a supply chain with asymmetrical relationships between companies. Our findings show that the traditional manual/non‐manual class division is still relevant for understanding differences in perceived work situation in a modern work organisation. However, alongside a cleavage between manual and non‐manual workers, we find a cleavage between workers with differing amounts of contact with employees in organisations higher up in the supply chain.     

A nearly perfect market?

Internet shopbots allow consumers to almost instantly compare prices and other characteristics from dozens of sellers via a single website. We estimate the magnitude of consumer search costs and benefits using data from a major shopbot for books. For the median consumer, the estimated benefit from simply scrolling down to search lower screens is $6.55. This amounts to about 60% of the observed price dispersion and suggests that consumers face significant search costs, even in this “nearly-perfect” market. Price elasticities are relatively high compared to offline markets (−7 to −10 in our base model). Furthermore, contrary to the common assumption, search intensity is not correlated with greater price sensitivity. Instead, consumers who search multiple screens put relatively more weight on non-price factors like brand.     

The current and future sales impact of a retail frequency reward program

This research presents an empirical study of the impact of a retail frequency reward program on store sales. We examine both the “points pressure,” or short-term impact, and the “rewarded behavior,” or long-term impact. The points-pressure impact is due to forward-looking customers increasing their purchase levels in order to earn the reward. The rewarded-behavior impact is evidenced as purchases above baseline levels after an individual has received a reward and could result from either behavioral learning reinforcement or positive affect resulting from the reward. We investigate a turkey reward program that awarded free turkeys to shoppers who accumulated the required sales levels during an 8-week period. We find both a points-pressure and rewarded-behavior impact. These effects are statistically significant and managerially relevant in that the program is apparently profitable. The points-pressure impact is especially strong among customers who do not place value on frequent shopper programs that in general deliver immediate price discounts. The key implications are that frequency reward programs of the form, “buy x, then receive xx” can be profitable, are segmentation strategies, and can complement a store's overall frequent shopper program.