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This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market.

To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which of these processes were more efficient in capturing volatility of interest rates of each of the sample countries.

The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events.

It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.

Este estudio analiza la volatilidad del mercado de renta fija de once países (Brasil, Rusia, India, China, Sudáfrica, Argentina, Chile, México, Estados Unidos, Alemania y Japón) de enero de 2000 a diciembre de 2011, mediante el examen de las tasas de interés interbancarias de cada mercado.

Para la volatilidad de los retornos de las tasas de interés, se utilizaron modelos de heteroscedasticidad condicional autorregresiva: ARCH, GARCH, EGARCH, TGARCH y PGARCH, y una combinación de estos con modelos ARIMA, comprobando cuáles de los procesos eran más eficientes para capturar la volatilidad de interés de cada uno de los países de la muestra.

Los resultados sugieren que para la mayoría de los mercados estudiados la volatilidad es mejor modelada por procesos GARCH asimétricos —en este caso el EGARCH— demostrando que las malas noticias conducen a un mayor incremento en la volatilidad de estos mercados que las buenas noticias. Además, las causas de una mayor volatilidad parecen estar más asociadas a eventos que ocurren internamente en cada país, como cambios en las políticas macroeconómicas, que los eventos externos generales.

Se espera que este estudio contribuya a un mejor entendimiento de la volatilidad de las tasas de interés y de los principales factores que afectan a este mercado.

Ingreso fijo, Volatilidad, Países emergentes, Modelos ARCH-GARCH

Artículo de investigación

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

Despite the institutional calls to include the development of non-technical skills as objectives in accounting curriculum and the attempts to do so, a gap between the level of skills exhibited by graduates and those needed to succeed as a professional is still perceived. One of the possible causes could be students' overconfidence, defined as a very optimistic assessment of their own abilities. The main objective of the paper is to assess the existence of overconfidence.

Two samples, students and employers were surveyed regarding the exhibited level of accounting graduates in a set of 22 non-technical skills, highlighted as relevant in the literature. This enabled a comparison of the opinions of employers with the perceptions of students concerning the demonstrated level of such skills.

The results of this study support the existence of students' overconfidence. In all the skills students score their ability higher than employers do with those differences being statistically significant in 21 out of 22 skills. Employers who are in closer contact with entry level accountants perceive even lower exhibited skills levels in graduates.

Overconfident students would be less motivated to actively participate in activities designed to improve skills resulting in underachievement and in lower performance. This low performance in highly valued skills could potentially harm their employability.

Although the literature focussing on non-technical skills in accounting is prolific there are few papers comparing the views of employers and students, and there are no previous studies focussing on overconfidence.

The need to improve the efficiency and quality of public services has increased the interest in innovation. This study seeks to understand the relationship between the Public Service Motivation (PSM) index and the profile of strategic-level public servants who are considered innovative.

Questionnaires were applied to the group of government managers who registered their projects in an innovation competition. Data were analyzed using t-test, multiple correspondence analysis (MCA) and hierarchical cluster analysis (HCA).

This paper concluded that the PSM level of these innovative public servants is significantly greater than public servants overall. In terms of the profile of these innovative government managers, it was found that the majority were female, with a high level of education and a background in Information Technology.

The discovery that innovative government managers have a significantly higher PSM (p < 0.05) than public servants overall may be relevant, because it confirms a statistical tendency that it would be advantageous for policy-makers to invest in actions that increase public servant PSM since these servants with high PSM are more innovative.

This article has sought to fill a gap in studies that associate the level of PSM with the innovation practices in the public sector, as well as verify the profile of public servants with high levels of motivation in public service (PSM).