Donald J. Kridel

The effects of incentive regulation in the telecommunications industry: A survey

We review recent empirical studies of the performance of incentive regulation in the telecommunications industry. These studies provide evidence that productivity, infrastructure investment, profit levels, telephone penetration, and new service offerings have increased under incentive regulation. Service rates have generally remained stable or decreased slightly, and service quality does not appear to have been affected adversely. There is no evidence that incentive regulation has led to streamlined regulatory proceedings. Strong evidence that incentive regulation has reduced the costs of providing telephone service has not yet materialized.

Residential demand for access to the Internet

The focus in this paper is on the residential demand for access to the Internet, and represents an extension of earlier work on Internet access demand by Rappoport, Taylor, Kridel, and Serad (1998), Kridel, Rappoport, and Taylor (1999), Kridel, Rappoport, and Taylor (2000), and Duffy-Deno (2000). The analysis of broadband demand has been studied by Eisner and Waldon (1999), Madden, Savage, and Coble-Neal (1999) and Madden and Simpspn (1997). With the aggressive marketing of cable modems and ADSL service, a growing number of residential households in the U.S. now have a choice regarding how they access the Internet. The choice set available, however, is not uniform. In some areas, the only form of access is through dial-up modem, while in other areas various forms of high-speed access (cable modems or ADSL) are available as well. This paper reports the results from a set of models of Internet access where the models are differentiated by the availability of Internet access options. The models are based on the analysis of surveys submitted by over 20,000 households during the period January – March, 2000. Among other things, we are able to report broadband penetration rates and compare those to Internet access estimates presented in the NTIA Report, Falling Through the Net: Toward Digital Inclusion. In addition, we present a more complete set of estimated price elasticities for both basic and high-speed access to the Internet.

Option value, telecommunications demand, and policy

Abstract Demand estimation and welfare analysis for telecommunications services have often been plagued by apparent inconsistencies between actual consumer behavior and standard economic theory. The latter posits that consumers will subscribe to services when their consumers surplus exceeds the subscription price. This paper presents an alternative model of subscription behavior under uncertainty. Drawing on the option value literature, we show that expected consumers surplus is generally not an adequate basis for subscription decisions. We present an empirical example in which option value significantly improves demand estimation. We discuss policy implications, including possible ‘market failures’ in which socially beneficial new technology is not deployed.

AN ECONOMETRIC STUDY OF THE DEMAND FOR ACCESS TO THE INTERNET

The increased popularity and explosive growth of the Internet have been widely tracked. A recent Business Week survey estimates that 40 million people are internet users, which is in line with an April 1997 FIND/SVP survey estimate that there are among 40-45 million adult users. 1 These numbers are up sharply from estimates obtained from surveys conducted in the fall of 1996. A November Louis Harris & Associates’ survey, for example, estimated that there were 35 million adult users, while IDC Research estimated that adult users in October 1996 were 31.4 million.2 PNR and Associates’ most recent estimate of households that use the Internet is 16%, which compares with an estimate of 14.8% in 1996. 3 These percentages are consistent with the Harris estimates. Thus, there is ample evidence to support the increased popularity of the Internet and the resulting demand in Internet applications.

An active modeling system for econometric analysis

Abstract This paper examines the feasibility of developing an “artificially intelligent econometrician” as an active decision support system (ADSS) in the sense articulated by [Manheim, 1988]. We review the system components of an ADSS and then relate them to a modeling system for econometric analysis that we have implemented. We present the query language of the PERM (Progressive EconometRic Modeling) system and offer an extension to the language based on process-oriented constructs for model integration. The query language and its extension correspond to the ADSSs user-directed and computer-directed process managers, respectively. Schemas representing statistical strategies are stored as processes in the extended language and serve as the econometric knowledge base. We suggest an approach to building an inference processor for this system based on experiments to record user query protocols and relate them to the schemas in the knowledge base. The connection between user processes and schemas is implemented by demon constructs in the extended language. Finally, we examine the extent to which our proposed system constitutes an ADSS.

A consumer surplus approach to predicting extended area service (EAS) development and stimulation rates

Abstract Little empirical evidence exists as to the behavior of customers as they self-select from usage-senstive to flat rate tariffs. Since this study was performed prior to service availability, neither choice behavior nor usage stimulation were observable. The customers survey response to a price query (‘would you purchase EAS at price

The demand for commodity packages: The case of telephone custom calling features

x’) is observed, however. We assume the customer is at least implicitly comparing his ‘projected’ benefits as measured by consumer surplus to the subscription price. By assuming an underlying demand for toll use, we can calculate the consumer surplus and derive the new usage level in terms of the initial or observed usage quantity. This framework provides a basis for a probabilistic choice model and allows joint prediction of penetration levels and usage stimulation rates. Customer demographics are introduced through the price parameter from the toll demand equation which relates stimulated usage to the initial usage level as well as in the choice parameters directly. Assuming a logistic framework for choice leads to rather a straight-forward maximum likelihood estimation problem. The resulting coefficient estimates are used to predict development and stimulation rates at various price levels.

Automated self-service modeling: predictive analytics as a service

The demand for two custom calling services is investigated. The services may be bought individually or in a discounted package. A micro-theory based on discrete choice model is formulated that explicitly accounts for these purchase options. The model is estimated assuming both dependence and independence of the unobservable choice-influencing variables. The estimated parameters are used to simulate the revenue impact of price and discount changes. Copyright 1993 by MIT Press.

IntraLATA long-distance demand: carrier choice, usage demand and price elasticities

Research into service provision and innovation is becoming progressively more important as automated service-provision via the web matures as a technology. We describe a web-based targeting platform that uses advanced dynamic model building techniques to conduct intelligent reporting and modeling. The impact of the automated targeting services is realized through a knowledge base that drives the development of predictive model(s). The knowledge base is comprised of a rules engine that guides and evaluates the development of an automated model-building process. The template defines the model classifier (e.g., logistic regression, multinomial logit, ordinary least squares, etc.) in concert with rules for data filling and transformations. Additionally, the template also defines which variables to test (“include” rules) and which variables to retain (“keep” rules). The “final” model emerges from the iterative steps undertaken by the rules engine, and is utilized to target, or rank, the best prospects. This automated modeling approach is designed to cost-effectively assist businesses in their targeting activities—independent of the firm’s size and targeting needs. We describe how the service has been utilized to provide “targeting services” for a small to medium business direct marketing campaign, and for direct sales-force targeting in a larger firm. Empirical results suggest that the automated modeling approach provides superior “service” in terms of cost and timing compared to more traditional manual service provision.

Competition in intraLATA long distance: carrier choice models estimated from residential telephone bills

Abstract Competition in the long-distance market in the US continues to intensify; the 1996 Telecommunications Act has led to increased competition in long-distance telephony especially as the Regional Bell Operating Companies have begun to gain entry to long-haul, long-distance markets. In order to better understand the implications of having increased service offerings, models of how customers choose between carriers (and the impact of this choice on subsequent usage) will be useful. We develop the first publicly available models that simultaneously estimate choice and usage for intraLATA long-distance in the US. Utilizing a generalized Tobit model, the price responsiveness of usage and carrier choice are estimated. The results are generally consistent with expectations both in terms of theory and of practical experience in the industry.