The CEO Arms Race

This article constructs a game‐theoretic model in which high chief executive officer (CEO) pay emerges as the outcome of an arms race, with each firm hiring a highly paid CEO to protect its competitive position against rivals who also hire highly paid CEOs. For an arms race to emerge, highly paid CEOs must generate idiosyncratic, privately known internal effects on profit, and CEO pay disparities must also generate asymmetric profit differences from external effects beyond the simple differences in pay. If the distribution of internal effects satisfies a key uniformity condition, an arms race emerges as the only equilibrium of the game.     

REMOVING THE “VEIL OF IGNORANCE”: NONLINEARITIES IN EDUCATION EFFECTS ON GENDER WAGE INEQUALITIES

A large literature studies the mean gender wage gap in developing countries and finds mixed evidence about the role of education policies in closing gender earnings inequalities. We contribute to this literature by exploring two types of nonlinearities in wage earning regressions: (1) nonlinearities on the effects of education on expected earnings along the distribution of education endowments; and (2) heterogeneities on the contributions of education to the gender wage gap at different quantiles of the wage distribution. Our analyses provide new insights on how these nonlinear effects can be used to set up better targeted gender and development policies. (JEL I26, C14)     

Consumers’ preference modeling to price bundle offers in the telecommunications industry: a game with competition among operators

Network operators are merging their services, such as fixed or wireless telephony, internet or television, into single offers, called bundles. It is essential to understand consumers’ preferences to define the most profitable bundles, with their associated prices, especially in the fierce competitive current market. We start by defining a random linear utility model and then, analyze the competition between an integrated operator and new entrants proposing substitutable services. Each operator ignores the consumers’ reservation prices for his offers and has to deal with uncertainties about the marketing strategies of competitors, due to potential different size and cost structure. A two-level game is introduced and solved by backward induction. In the second level, the operators determine their optimal offer prices for each possible combination of marketing strategies while the consumers select their most profitable purchasing processes; the natural framework is that of Bayesian game theory. Finally at the top level, knowing the outcome of the other level, the operators identify which marketing strategy to use between market share expansion, segment targeting or multi-level price discrimination, to maximize their expected utilities conditionally to their private informations.     

Exporting to new destinations and the effects of tariffs: the case of meat commodities

This study uses a random parameter probit estimation to examine the effects of tariff liberalization on the probability of establishing new trading relationships in meat commodities. Our simulation results indicate that the effects of tariff reductions decrease with distance, but increase with the level of development. The probabilities of trade increase at an increasing rate with the size of tariff reductions thus justifying calls for ambitious liberalization schemes. Canada and Mexico are the NAFTA countries that are most likely to export in response to EU tariff reductions on bovine and poultry meats, while Brazil and Argentina emerge as the MERCOSUR countries most likely to penetrate the EU bovine meat market after EU tariff reductions. Uruguay's probability to export poultry meat is most responsive to EU tariff reductions.     

Open innovation: Are inbound and outbound knowledge flows really complementary?

One novel implication of the open innovation paradigm is that inflows and outflows of knowledge are complementary. We argue that engaging simultaneously in buying and selling knowledge should allow firms to increase innovation outcomes. At the same time, we identify some of the relevant costs (cognitive, transaction, and organizational costs) that “open” firms can reduce by combining knowledge inflows and outflows. Empirically, however, we find no evidence for such complementarity in a sample of Belgian manufacturing firms. Firms buying and selling knowledge do increase their sales of new products, but at the same time their R&D costs increase more than proportionally. Our findings, therefore, indicate the need for research into a better understanding of the drivers of actual costs of organizing for open innovation. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling insurgent-incumbent dynamics: Vector autoregressions,multivariate Markov chains,and the nature of technological competition

The struggle between sail and steam is a long-standing theme in economic history. But this technological competition story has only partly tackled, since most studies have appreciated the rivalry between the two alternative modes of commercial sea carriage in the late 19th century while the early period has remained relatively under-analysed. This paper models the early dynamics between the two capital goods using a vector autoregression approach (VAR) and a Multivariate Markov Chain approach (MMC). We find evidence that the relationship was non-linear, with a strong indication of complementarities and cross-technology learning effects.     

Developing the marketing concept in public accounting firms

As the American Institute of Certified Public Accounts relaxes its practice development restrictions, CPA firms find themselves with a need to develop more aggressive approaches to the markets they serve. This paper focuses on the development of a marketing strategy for an illustrative market, that of small, rapidly-growing high technology firms. Results from a telephone survey of company executives serve as the basis for strategy development. In addition, the evaluation of a small firm and its accounting needs are provided in a hypothetical example to dramatize the conclusions. The results suggest that the burden may be on CPA firms to anticipate, recognize, and meet the accounting needs of their clientele.     

U-Convolutional model for spatio-temporal wind speed forecasting

The increasing penetration of intermittent renewable energy in power systems brings operational challenges. One way of supporting them is by enhancing the predictability of renewables through accurate forecasting. Convolutional Neural Networks (Convnets) provide a successful technique for processing space-structured multi-dimensional data. In our work, we propose the U-Convolutional model to predict hourly wind speeds for a single location using spatio-temporal data with multiple explanatory variables as an input. The U-Convolutional model is composed of a U-Net part, which synthesizes input information, and a Convnet part, which maps the synthesized data into a single-site wind prediction. We compare our approach with advanced Convnets, a fully connected neural network, and univariate models. We use time series from the Climate Forecast System Reanalysis as datasets and select temperature and u- and v-components of wind as explanatory variables. The proposed models are evaluated at multiple locations (totaling 181 target series) and multiple forecasting horizons. The results indicate that our proposal is promising for spatio-temporal wind speed prediction, with results that show competitive performance on both time horizons for all datasets.     

THE HIDDEN ECONOMY: STATE AND PROSPECTS FOR MEASUREMENT1

To know the size and development of the hidden or underground economy is important for policy making, mainly because the measures undertaken may be misdirected if they are based on biased official statistics. The hidden economy can be measured by considering indicators. The direct methods are based on voluntary surveys and on tax auditing and other compliance methods. The indirect estimation methods rely on the identification of residuals with respect to income and expenditures, as well as in the labor and money markets. The strengths and weaknesses of each of these measurement approaches are discussed and the resulting estimates of the size of the hidden economy are compared. A different approach to measurement is to look at the determinants leading to the existence and growth of the hidden economy. Finally, the method of “unobserved variables” allows the combination of the two approaches by simultaneously considering the determinants and indicators of the under- ground economy. The results show a considerable range of sizes for a given country and year. Though there is a broad range of size estimates, there is general agreement that the hidden economy's size has been growing for all countries over recent decades. Further progress in quantitative knowledge about the hidden economy requires the development of a theoretical model which analyses the interdependencies between the official private sector, the hidden economy, and the public sector.     

USING LABORATORY EXPERIMENTS TO DESIGN EFFICIENT MARKET INSTITUTIONS: THE CASE OF WHOLESALE ELECTRICITY MARKETS

ABSTRACT ** :  This paper assesses the contribution of laboratory experiments to the economics of design applied to the electricity industry. The analysis is dedicated to wholesale markets, and reviews the results accumulated to date concerning both the general architecture of power markets and the very details of the market rules or institution, that is the auction rule. We argue that these experimental results contribute to a better understanding of the performances properties and implementation features of competitive market designs and that experimental economics has proven very useful to public authorities to inform the restructuring of the electricity industry. It thus confirms the role of experimental economics as a complement to theoretical approaches in the design effort.