Bagging bundle benefits in broadband and media mergers: Lessons from Sky/Vodafone for antitrust analysis

The historic precedents in telecommunications antitrust findings have tended towards finding harm to competition when network operators integrate downstream and bundle the provision of applications and services. The reason for this is that market power in network provision is thought to be extended into the applications market(s). More recently however, proposed mergers have been between telecommunications and media distribution firms, both of whom have some degree of market power, already sell their own services in bundles, and who may or may not have been offering combined bundles already via contractual agreements. Examples include Sky/Vodafone in New Zealand, and Time Warner/AT&T in the United States as well as Vodafone/Unitymedia in Germany and Media Capital/Altice in Portugal. These complex proposed arrangements pose challenges to competition authorities, whose legal and procedural rules and precedents, especially those defining the relevant markets affected by the merger or vertical integration activity, have been developed from the analysis of simpler cases. These precedents may not be sufficient to analyse current cases, characterized by multiple products catering to heterogeneous consumer preferences, and consumers are not constrained to buying only one variant of the products in each of the upstream and downstream markets.We illustrate the challenges by way of a case study of the proposed merger between Sky and Vodafone, declined by the New Zealand Commerce Commission in February 2017. Limitations in existing market definition processes and the evaluation of market power where bundling already occurs risk overlooking complex demand-side interactions that influence the profitability and efficiency of various structural and contractual strategic choices. We propose that classic merger and antitrust analysis based on econometric cost-benefit analysis can be augmented by using simulation and numerical analysis of a range of bundle offers expected to be relevant in decision-making. We develop a simple model and use it to illustrate how it may be used to inform broadband and content mergers, and other complex antitrust cases, such the assessment of the effects of two-sided markets and firm pricing decisions.     

A New Regulatory Paradigm for the Digital Sector in Europe

The new regulatory framework in the digital sector in Europe is likely to fall short of expectations. A fragmented digital market with insuffi cient incentives for investment is the probable outcome. European regulators should abandon their approach in favour of a new and more flexible set of ideas discussed in this paper.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Foreign competition and the durability of US firm investments

How does the exposure to product market competition affect the investment horizon of firms? We study if firms have an incentive to shift investments toward more short‐term assets when exposed to tougher competition. Based on a stylized firm investment model, we derive a within‐firm estimator using variation across investments with different durabilities. Exploiting the Chinese World Trade Organization (WTO) accession, we estimate the effects of product market competition on the composition of US firm investments. Firms that experienced tougher competition shifted their expenditures toward investments with a shorter durability. This effect is larger for firms with lower total factor productivity.     

New Evidence on Housing Wealth and Consumption Channels

The Journal of Real Estate Finance and Economics - This paper provides new evidence on the effect of housing wealth on consumption by focusing on the impact of home-equity extraction. We develop a...     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Firm age and performance

Amid increasing interest in firm age and its effects on firm performance, this special issue offers an exhaustive review of the literature and a novel collection of evidence on the effects of firm age on performance, including a special focus of interest on innovation performance, financial performance, exports, survival and growth. This editorial positions the theme in the extant literature, and provides key definitions and challenges ahead in the field of evolutionary economics. It introduces the collection of articles composing the special issue. The papers offer a diversity of country contexts, as well as analytical approaches and methods. They include an exhaustive review of the literature on age and firms’ performance, and present original empirical studies focusing on the effects of age on firms’ economic outcomes on the one hand, and on innovation outcomes on the other hand. While most of the papers use econometric analysis, the level of analysis ranges from firm to individual.     

Sweatshop Regulation and Workers’ Choices

The choice argument against sweatshop regulations states that public officials should not prohibit workers from accepting jobs that require long hours, low pay, and poor working conditions, because enforcing such regulations would be disrespectful to the workers who choose to work in sweatshops. Critics of the choice argument reply that these regulations can be justified when workers only choose to work in sweatshops because they lack acceptable alternatives and are unable to coordinate to achieve better conditions for all workers. My thesis is that the presence of unacceptable alternatives to sweatshop labor or barriers to coordination cannot justify sweatshop regulations such as minimum wage and maximum hour laws. Although officials should promote alternatives to difficult and dangerous sweatshop labor, they should not do so by limiting workers’ and employers’ options through coercive regulation. And the fact that sweatshop workers may face coordination problems does not undermine the claim that sweatshop workers choose to work in sweatshops, just as other workers face coordination problems but nevertheless make occupational choices. Furthermore, efforts to restrict sweatshop workers’ choices are morally risky and may not promote workers’ wellbeing or wellbeing in general.