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When static models of the firm are considered regulators make serious errors in the determination of the proper wholesale price as the opportunity cost of the delay option is neglected. For an incumbent, the option is exercised and represents an opportunity cost. For a potential entrant the delay option need not be exercised should the regulator allow the purchase access at below economic cost, i.e., operating cost plus the delay options cost. Thus service-based entry is excessive and facilities-based entry remains suboptimal. To summarize, in a static-regulated paradigm: wholesale prices are below their economic cost; inefficient service entry occurs as prices are not set at the correct marginal cost while an entrant is not required to exercise a delay option; social welfare is suboptimal; incumbent firm’s valuation by the financial markets is less; and the cost of capital for incumbent firms is higher. When a regulated paradigm is dynamic the converse holds: optimal prices are higher than for static calculations; only efficient service entry occurs as prices are set at the correct economic marginal cost; facilities-based entrants receive correct price signals; social welfare is maximal; an incumbent’s valuation by financial markets is higher; and the cost of capital is lower than for a regulated paradigm. This chapter has demonstrated the profound implications for regulatory practices. In particular, dynamics and uncertainty matter for the realization of optimal regulatory pricing outcomes. However, much work remains to develop and quantify precise models to fit the telecommunications context.

This chapter has developed an analytical framework to understand and quantify the valuation of an investment when network externalities are present. Modeling starts from a probabilistic demand modeling stance and the inclusion of an option to terminate the project. These elements allow the more accurate valuation of the investment. Expected free cash flow values are larger on average than values estimated via the deterministic NPV procedures. However, probabilistic NPV estimates require the calculation of confidence intervals to evaluate project risk. Conversely, the integration of the project termination option (put option) increases the project’s value that is linked to the termination probability and savings from the early abandonment of the project. Finally, while the proposed modeling approach appears more realistic it raises questions as to the best means to obtain values for the termination parameters for effective scenario impleme

Stated-preference survey techniques have become established as a means to elicit consumer preferences, particularly when a product is new or only recently exposed to competitive pressure. This development has proved particularly helpful for studying consumer behavior, both actual and potential, in telecommunications markets newly open to competition. The approach is well suited to econometric modeling via discrete choice methods—particularly when data reflect consumer ranking of alternatives in order of preference. The rank-ordered logit model has become a standard tool, particularly the mixed logit form for rank-ordered data. The mixed logit model accommodates variation in consumer response to product attributes and correlation among unobserved factors in consumer choice, e.g., when consumers make repeated choices. Mixed logit models are flexible and permit the estimation of random coefficients, and reduce to a standard logit model should empirical tests show that estimated coefficients possess degenerate distributions. This feature helps to provide insights into certain aspects of consumer behavior that hitherto have only been analyzed by standard logit models. In Particular, the mixed logit model implied much larger market share elasticity estimates for incumbent service providers. Therefore, the combination of ranked stated-preference data and mixed logit models can be a valuable tool for market analysis as the dramatic transformation of the telecommunications industry continues.

This chapter attempts to provide some useful insights into the understanding of fundamental tradeoffs faced by B&M and Virtual firms competing in Virtual marketplaces for Type-2 customers. An innovation contained in the paper is the establishment of a link between firm relative locations within the Virtual market to investment and ultimately profits. This innovation enabled the derivation of some testable predictions. Some ways to move beyond current model assumptions could be the consideration of non-uniform distributions of Virtual consumers (in particular non-symmetric distributions due to the skewed age distribution of customers making purchases online), the introduction of market power and allowing both the B&M and Virtual markets to be made open to competition.

We address the problem of detecting deviations of a binary sequence from randomness, which is very important for ra ndom number (RNA) and pseudorandom number generators (PRNG) and their applications to cryptography. Namely, we consider a hypothesis that a given bit sequence is generated by the Bernoulli source with equal probabilities of 0’s and 1’s and the alternative hypothesis that the sequence is generated by a stationary and ergodic source which differs from the source under . We show that data compression methods can be used as a basis for such testing and describe two new tests for randomness, which are based on ideas of universal coding. Known statistical tests and suggested ones are applied for testing PRNGs which are used in practice. The experiments show that the power of the new tests is greater than of many known algorithms.

When static models of the firm are considered regulators make serious errors in the determination of the proper wholesale price as the opportunity cost of the delay option is neglected. For an incumbent, the option is exercised and represents an opportunity cost. For a potential entrant the delay option need not be exercised should the regulator allow the purchase access at below economic cost, i.e., operating cost plus the delay options cost. Thus service-based entry is excessive and facilities-based entry remains suboptimal. To summarize, in a static-regulated paradigm: wholesale prices are below their economic cost; inefficient service entry occurs as prices are not set at the correct marginal cost while an entrant is not required to exercise a delay option; social welfare is suboptimal; incumbent firm’s valuation by the financial markets is less; and the cost of capital for incumbent firms is higher. When a regulated paradigm is dynamic the converse holds: optimal prices are higher than for static calculations; only efficient service entry occurs as prices are set at the correct economic marginal cost; facilities-based entrants receive correct price signals; social welfare is maximal; an incumbent’s valuation by financial markets is higher; and the cost of capital is lower than for a regulated paradigm. This chapter has demonstrated the profound implications for regulatory practices. In particular, dynamics and uncertainty matter for the realization of optimal regulatory pricing outcomes. However, much work remains to develop and quantify precise models to fit the telecommunications context.

When static models of the firm are considered regulators make serious errors in the determination of the proper wholesale price as the opportunity cost of the delay option is neglected. For an incumbent, the option is exercised and represents an opportunity cost. For a potential entrant the delay option need not be exercised should the regulator allow the purchase access at below economic cost, i.e., operating cost plus the delay options cost. Thus service-based entry is excessive and facilities-based entry remains suboptimal. To summarize, in a static-regulated paradigm: wholesale prices are below their economic cost; inefficient service entry occurs as prices are not set at the correct marginal cost while an entrant is not required to exercise a delay option; social welfare is suboptimal; incumbent firm’s valuation by the financial markets is less; and the cost of capital for incumbent firms is higher. When a regulated paradigm is dynamic the converse holds: optimal prices are higher than for static calculations; only efficient service entry occurs as prices are set at the correct economic marginal cost; facilities-based entrants receive correct price signals; social welfare is maximal; an incumbent’s valuation by financial markets is higher; and the cost of capital is lower than for a regulated paradigm. This chapter has demonstrated the profound implications for regulatory practices. In particular, dynamics and uncertainty matter for the realization of optimal regulatory pricing outcomes. However, much work remains to develop and quantify precise models to fit the telecommunications context.