The Information Environment,Informed Trading,and Volatility

The relation between informed trading and volatility is analyzed using the change in the proportion of informed transactions calculated through the probability of informed trading variable. The analysis relates to the Spanish market during 1997–2010, given that the Spanish market covers a very diverse range of listed companies. Some companies are comparable to companies listed on U.S. markets while others are smaller in size and have a lower trading volume and inferior quality of information. The methodology is based on a modification of the model proposed by Avramov, Chordia, and Goyal [2006 Avramov, D., T. Chordia, and A. Goyal. “The Impact of Trades on Daily Volatility.” Review of Financial Studies, 19, (2006), pp. 1241–1277.[Crossref], [Web of Science ®] , [Google Scholar]]. The authors’ proposal incorporates the change in the proportion of informed transactions, calculated with intraday data, into the volatility model. The results are also presented using a conditional volatility model in which the change in the proportion of informed transactions is incorporated. These results attest to the influence of informed trading as a price-stabilizing factor in heavily traded and highly capitalized stocks (familiar stocks). Informed trading leads to a marked decrease in volatility for these particular stocks both in periods of calm and crisis.     

Relationships among functional units and new product performance: The moderating effect of technological turbulence

Though there has been plenty of research into new product success factors, only a few studies have tried to analyse whether these factors are important in different settings. In this study, we propose and test a model that links physical proximity among functional units, presence of product champions, cross-functional harmony, and new product program performance. The moderating effects of perceived technological turbulence on relationships between new product performance and its antecedents are also tested. Our results, obtained from 151 managers working for Spanish firms with a R&D department, confirm the different impact of these factors on the three measures of performance considered and also on two groups of organizations, the ones that perceive high technological turbulence and the ones that perceive low technological turbulence.     

Can Insider Power Affect Employment?

Abstract. Do firms reduce employment when their insiders (established, incumbent employees) claim higher wages? The conventional answer in the theoretical literature is that insider power has no influence on employment, provided that the newly hired employees (entrants) receive their reservation wages. The reason given is that an increase in insider wages gives rise to a countervailing fall in reservation wages, leaving the present value of wage costs unchanged. Our analysis contradicts this conventional answer. We show that, in the context of a stochastic model of the labor market, an increase in insider wages promotes firing in recessions, while leaving hiring in booms unchanged. Thereby insider power reduces average employment.     

Effects of brand-related and market signals on franchisees’ entrepreneurial decisions: a multi-country panel data analysis

This paper analyses the influence of market and brand-related signals on franchisees’ decisions when choosing a franchise brand with which to open an outlet for the first time. Panel data methodology was used to analyse a sample of 1277 chains operating in Spain, Mexico and Peru between 2004 and 2013. The results show that market signals prevail over brand-related signals. Within brand-related signals, franchisees first seek information relating to the brand’s sector and then seek information relating to the brand’s value. Franchisors should match the content of the signals they send to the market to the true characteristics of the franchise. Franchisors should also endeavour to ensure the country where they operate has general and franchise-specific legislation that fosters business activity by both franchisor and franchisee. The use of institutional quality as a signal in a multi-country study represents a significant contribution to the literature on franchising.

     

Forecast combination through dimension reduction techniques

This paper considers several methods of producing a single forecast from several individual ones. We compare “standard” but hard to beat combination schemes (such as the average of forecasts at each period, or consensus forecast and OLS-based combination schemes) with more sophisticated alternatives that involve dimension reduction techniques. Specifically, we consider principal components, dynamic factor models, partial least squares and sliced inverse regression.Our source of forecasts is the Survey of Professional Forecasters, which provides forecasts for the main US macroeconomic aggregates. The forecasting results show that partial least squares, principal component regression and factor analysis have similar performances (better than the usual benchmark models), but sliced inverse regression shows an extreme behavior (performs either very well or very poorly).     

Examining the behavior of renewable‐energy fund investors

Mutual fund investors could contribute to sustainable development by encouraging fund managers to channel their savings into the funding of sustainable energy projects adopted by firms. This study examines whether renewable‐energy investors take into account financial and/or nonfinancial factors when making the decision to invest in a specific fund, comparing their investment behavior with that of black‐energy and conventional investors. To this end, we have gathered information about 4,368 mutual funds (76 renewable‐energy funds, 109 black‐energy funds, and 4,183 conventional mutual funds) from January 2007 to December 2017. For this sample, we adopt a panel‐data approach with Petersen's standard errors clustered by fund and year. Our results indicate that renewable‐energy fund investors are less sensitive to past financial performance than are black‐energy and conventional fund investors, indicating that the former derive their utility from nonfinancial attributes whereas black‐energy investors derive their utility from a conditional multiattribute and conventional fund investors derive their utility from financial attributes.     

AHP-Group Decision Making: A Bayesian Approach Based on Mixtures for Group Pattern Identification

This paper proposes a Bayesian estimation procedure to determine the priorities of the Analytic Hierarchy Process (AHP) in group decision making when there are a large number of actors and a prior consensus among them is not required. Using a hierarchical Bayesian approach based on mixtures to describe the prior distribution of the priorities in the multiplicative model traditionally used in the stochastic AHP, this methodology allows us to identify homogeneous groups of actors with different patterns of behaviour for the rankings of priorities. The proposed procedure consists of a two-step estimation algorithm: the first step carries out a global exploration of the model space by using birth and death processes, the second concerns a local exploration by means of Gibbs sampling. The methodology has been illustrated by the analysis of a case study adapted from a real experiment on e-democracy developed for the City Council of Zaragoza (Spain). Partially funded under the research project Electronic Government. Internet-based Complex Decision Making: e-democracy and e-cognocracy (Ref. PM2004-052) approved by the Regional Government of Aragon (Spain) as part of the multi-disciplinary projects programme.     

Inequity in inpatient healthcare utilisation 10 years after Apartheid

This paper provides evidence about socioeconomic inequity in inpatient healthcare utilisation in South Africa after 10 years of reform after Apartheid, and examines which are the contributing determinants. We use the South African sample of the World Health Survey from 2002–03 and estimate horizontal inequity in inpatient healthcare utilisation using the concentration index. We further decompose inequity in inpatient care to explore the contribution of the different determinants of use. We find that inpatient healthcare utilisation is found to be pro-rich distributed in South Africa. The rich are more likely to use inpatient healthcare than the poor, given the same level of need. In addition, race is found to be the most important contributor (42%) to socioeconomic inequity in inpatient healthcare utilisation in South Africa. Gender, education and the consumption level are also found to be important contributors, but to a lesser degree than race. Our findings provide evidence that socioeconomic inequity in inpatient healthcare utilisation still exists in post-Apartheid South Africa and that policies, regulations and research should contribute to a more equitable utilisation. The implementation of National Health Insurance could help to reduce the major problems and large (socioeconomic and racial) inequalities of the South African healthcare system.     

Relationship between the Mean and the Constant in a Box–Jenkins Time Series Model

In some publications the mean is identified with the constant of a Box–Jenkins time series model. In this paper the relation between both terms is demonstrated. Furthermore, by means of an example, the errors which may be made if one does not use each term adequately are shown.     

The tourism SMEs in the global value chains: the case of Andalusia

This paper examines the implications of the globalization of value chains for the role of small and medium-sized enterprises (SMEs) in the tourism industry. To begin with, the configuration of the global tourism value chain is analysed. Next, the participation of Andalusian SMEs in the global tourism value chains is investigated. A number of case studies have been developed in two relevant sectors, hotels and travel agencies, giving priority to the main tourist typologies existing in Andalusia: sun and sand, business and congress, cultural and rural. As a result, a SWOT analysis has been produced. Finally, from the key findings some policy recommendations supporting the role of tourism SMEs in global value chain are made.