Welfare effects of the Telecommunication Reform in Mexico

The telecommunication sector in Mexico was highly concentrated until 2013. The sector was mostly composed by a dominant player, a rationed market (low density of services), a poor institutional design, high tariffs, and weak regulation agents. The Herfindahl-Hirschman (HHI) index was 5333 for mobile telephone and 7,029 for fixed telephone services—among the highest scores in the world. In order to promote competition in the sector, Congress approved a reform in 2013 to establish a new regulator empowered to impose asymmetrical rules in the case of the predominance of a single firm. A declaration of preponderance of the dominant player was issued, promoting free interconnection rates and the mandatory sharing of its passive and active infrastructure with the rest of the firms in the industry. The new institutional design led to increased competition in the sector, decreasing the mobile and fixed telephone prices while increasing the coverage and penetration of these services. In this article, an applied general equilibrium model for the Mexican economy is employed to assess the impact of the Telecommunication Reform in Mexico in the telephone sector, consumer welfare, and income distribution. The model is static, encompassing 10 types of consumers (rural and urban and the five income quintiles) and 40 sectors (of which four are disaggregate telecommunications industries). It assumes fixed wages and capital rental prices as well as idle resources. The main results indicate that the effects of the reform are not minor; the drop in telephone prices would reduce the general consumer price index by almost 2%, and the value added would increase by more than 3%, benefiting mainly households in the highest income quantiles.     

Analysing enterprise architecture maturity models: a learning perspective

In order to aid organisations in the adoption of enterprise architecture (EA) best practices, maturity models have been proposed in the literature. These models offer organisational roadmaps and assessment frameworks for increasing EA maturity. However, key questions concerning the implied meaning of the term maturity in the context of these models have been left unexplored by previous research. This research, aided by the field of organisational learning, offers new insights into the implied assumptions of current EA maturity models and offers initial concepts and constructs to guide the conceptualisation, construction and refinement of enterprise maturity models.     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

Collaborative commerce in tourism: implications for research and industry

Technology advances enable people to trade and sell their own travel products, which in turn create numerous transformation changes into the tourism industry structure, the nature of tourism products and experiences, the competitiveness of traditional and new tourism players and the process creating (social) value in tourism. This paper investigates the application and implications of collaborative commerce in tourism and provides suggestions for future research.     

Identifying terms of trade shocks in a developing country using a sign restrictions approach

Using annual data for Botswana from 1960 to 2012, we examine the responses of macroeconomic variables to four generalized positive terms of trade shocks – global demand, globalizing, sector-specific and global supply. A sign-restricted structural vector autoregression model with a penalty function is estimated to identify the four possible shocks. While positive global demand and globalization shocks are both expansionary, they have opposite effects on inflation. A positive commodity market specific shock dampens real GDP growth and is inflationary, suggesting a possible Dutch disease response. A negative global supply shock suppresses both output growth and inflation. All but the last shock leads to a significant declining interest rate. Monetary policy contraction is recommended for the first shock and expansion for the others.     

Combining multiple probability predictions using a simple logit model

This paper begins by presenting a simple model of the way in which experts estimate probabilities. The model is then used to construct a likelihood-based aggregation formula for combining multiple probability forecasts. The resulting aggregator has a simple analytical form that depends on a single, easily-interpretable parameter. This makes it computationally simple, attractive for further development, and robust against overfitting. Based on a large-scale dataset in which over 1300 experts tried to predict 69 geopolitical events, our aggregator is found to be superior to several widely-used aggregation algorithms.     

Multifactor risk loadings and abnormal returns under uncertainty and learning

We explore the time variation of factor loadings and abnormal returns in the context of a four-factor model. Our methodology, based on an application of the Kalman filter and on endogenous uncertainty, overcomes several limitations of competing approaches used in the literature. Besides taking learning into account, it does not rely on any conditioning information, and it only imposes minimal assumptions on the time variation of the parameters. Our estimates capture both short- and long-term fluctuations of risk loadings and abnormal returns, also showing marked variation across US industry portfolios. The results from mean-variance spanning tests indicate that our baseline model yields accurate predictions and can therefore improve pricing and performance measurement.     

Can negative interest rates really affect option pricing? Empirical evidence from an explicitly solvable stochastic volatility model

The profound financial crisis generated by the collapse of Lehman Brothers and the European sovereign debt crisis in 2011 have caused negative values of government bond yields both in the USA and in the EURO area. This paper investigates whether the use of models which allow for negative interest rates can improve option pricing and implied volatility forecasting. This is done with special attention to foreign exchange and index options. To this end, we carried out an empirical analysis on the prices of call and put options on the US S&P 500 index and Eurodollar futures using a generalization of the Heston model in the stochastic interest rate framework. Specifically, the dynamics of the option’s underlying asset is described by two factors: a stochastic variance and a stochastic interest rate. The volatility is not allowed to be negative, but the interest rate is. Explicit formulas for the transition probability density function and moments are derived. These formulas are used to estimate the model parameters efficiently. Three empirical analyses are illustrated. The first two show that the use of models which allow for negative interest rates can efficiently reproduce implied volatility and forecast option prices (i.e. S&P index and foreign exchange options). The last studies how the US three-month government bond yield affects the US S&P 500 index.     

Modeling regional economic dynamics: Spatial dependence,spatial heterogeneity and nonlinearities

Spatial modeling of economic phenomena requires the adoption of complex econometric tools, which allow us to deal with important methodological issues, such as spatial dependence, spatial unobserved heterogeneity and nonlinearities. In this paper we describe some recently developed econometric approaches (i.e. Spatial Autoregressive Semiparametric Geoadditive Models), which address the three issues simultaneously. We also illustrate the relative performance of these methods with an application to the case of house prices in the Lucas County.