A theory of socialistic internal capital markets

We develop a model of a two-division firm in which the “strong” division has, on average, higher quality investment opportunities than the “weak” division. We show that, in the presence of agency and information problems, optimal effort incentives are less powerful and thus managerial effort is lower in the strong division. This leads the firm to bias its project selection policy against the strong division. The selection bias is more severe when there is a larger spread in the average quality of investment opportunities between the two divisions.     

Testing the Empirical Relationship between Best Management Practice Adoption and Farm Profitability

Several "best management practices" (BMPs) aimed at reducing movement of nutrients, pesticides, and sediment into surface water resources have been developed and promoted by Extension and other agencies over the past several years. This study utilizes actual farm-level economic and BMP adoption data to rigorously analyze the relationship between BMP use and farm profitability. Results indicate that adoption of nutrient BMPs has a significant positive effect on net farm income (NFI) for wheat and corn, while herbicide BMP adoption, particularly use of BMPs related to the application of atrazine on corn, has a small (but statistically significant) negative impact on income. Adoption of soil conservation BMPs is not shown to have a statistically significant impact on farm income.     

Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.     

Management fads, pedagogies, and other soft technologies

We present a model for the diffusion of management fads and other technologies which lack clear objective evidence about their merits. The choices made by non-Bayesian adopters reflect both their own evaluations and the social influence of their peers. We show, both analytically and computationally, that the dynamics lead to outcomes that appear to be deterministic in spite of being governed by a stochastic process. In other words, when the objective evidence about a technology is weak, the evolution of this process quickly settles down to a fraction of adopters that is not predetermined. When the objective evidence is strong, the proportion of adopters is determined by the quality of the evidence and the adopters’ competence.     

The effect of entry restrictions on price: evidence from the retail gasoline market

I exploit a change in Spanish regulations to test the effect of the relaxation of entry restrictions on the equilibrium retail price of diesel. In February 2013, a Central Government reform permitted gasoline stations to operate in industrial and commercial areas. Over the following 2-year period, this deregulation led to a high number of new market entrants in these newly designated free entry areas. By isolating markets exposed to entry and markets unaffected by new entrants, and adopting a difference-in-difference approach, results show that gasoline stations exposed to a new market entrant within a one-mile radius lower their prices by an average 1.04%. This result is significant, representing almost one fifth of the average retail margin. Additionally, the results show that the reduction in the equilibrium price is caused by the first market entrant and that the effect decreases over time.     

Contractual restrictions on insider trading: a welfare analysis

Summary. This paper analyzes the welfare effects of permitting firms to negotiate contractually the right to allow corporate insiders to trade shares in the firm on private information. A computational framework is employed to (i) analyze formally the effects of insider trading on managerial investment choice, the informational efficiency of stock prices, and the welfare of all investor types; and (ii) examine the effectiveness of various compensation schemes (such as stock and insider trading rights) to mitigate conflicts of interest between managers and shareholders. I show that shareholders will typically choose not to grant insider trading rights to managers. This decision is socially optimal. Received: September 23, 2000; revised version: December 12, 2000     

Partitioning uncertain workloads

We present a method for determining the ratio of the tasks when breaking any complex workload in such a way that once the outputs from all tasks are joined, their full completion takes less time and exhibit smaller variance than when running on the undivided workload. To do that, we have to infer the capabilities of the processing unit executing the divided workloads or tasks. We propose a Bayesian Inference algorithm to infer the amount of time each task takes in a way that does not require prior knowledge on the processing unit capability. We demonstrate the effectiveness of this method in two different scenarios; the optimization of a convex function and the transmission of a large computer file over the Internet. Then we show that the Bayesian inference algorithm correctly estimates the amount of time each task takes when executed in one of the processing units.