Board of directors and top management team: a study on CEO relative power and financial return

Best corporate governance practices published in the primers of Brazilian Securities and Exchange Commission and the Brazilian Corporate Governance Institute promote board independence as much as possible, as a way to increase the effectiveness of governance mechanism (Sanzovo, 2010). Therefore, this paper aims at understanding if what the managerial literature portraits as being self-evident - stricter governance, better performance - can be observed in actual evidence. The question answered is: do companies with a stricter control and monitoring system perform better than others? The method applied in this paper consists on comparing 116 companies in respect to the their independence level between top management team and board directors– being that measured by four parameters, namely, the percentage of independent outsiders in the board, the separation of CEO and chairman, the adoption of contingent compensation and the percentage of institutional investors in the ownership structure – and their financial return measured in terms return on assets (ROA) from the latest Quarterly Earnings release of 2012. From the 534 companies listed in the Stock Exchange of Sao Paulo – Bovespa – 116 were selected due to their level of corporate governance. The title “Novo Mercado” refers to the superior level of governance level within companies listed in Bovespa, as they have to follow specific criteria to assure shareholders ´protection (BM&F, 2011). Regression analyses were conducted in order to reveal the correlation level between two selected variables. The results from the regression analysis were the following: the correlation between each parameter and ROA was 10.26%; the second regression analysis conducted measured the correlation between the independence level of top management team vis-à-vis board directors – namely, CEO relative power - and ROA, leading to a multiple R of 5.45%. Understanding that the scale is a simplification of the reality, the second part of the analysis transforms all the four parameters into dummy variables, excluding what could be called as an arbitrary scale. The ultimate result from this paper led to a multiple R of 28.44%, which implies that the combination of the variables are still not enough to translate the complex reality of organizations. Nonetheless, an important finding can be taken from this paper: two variables (percentage of outside directors and percentage of institutional investor ownership) are significant in the regression, with p-value lower than 10% and with negative coefficients. In other words, counter affirming what the literature very often portraits as being self-evident – stricter governance leads to higher performance – this paper has provided evidences to believe that the increase in the formal governance structure trough outside directors in the board and ownership by institutional investor might actually lead to worse performance. The section limitations and suggestions for future researches presents some reasons explaining why, although supported by strong theoretical background, this paper faced some challenging methodological assumptions, precluding categorical statements about the level of governance – measured by four selected parameters – and the financial return in terms of financial on assets.

Economic landscapes, what are they? an application to the Brazilian economy and to the sugar cane complex

In assessing the economic impact of a sector or group of sectors on a single or multiregional economy, input-output analysis has proven to be a popular method. . However, there has a problem in displaying all the information that can be obtained from this analytical approach. In this paper, we have tried to set new directions in the use of input-output analysis by presenting an improved way of looking at the economic landscapes. While this is not a new concept, a new meaning is explored in this paper; essentially, it will now be possible to visualize, in a simple picture, all the relations in the economy as well as being able to view how one sector is related to the other sectors/regions in the economy. These relations can be measured in terms of structural changes, production, value added, employment, imports, etc. While all the possibilities cannot be explored in this paper, the basic idea is given here and the smart reader can uncover all the various possibilities. To illustrate the power of analysis provided by the economic landscapes, an application is made to the sugar cane complex using an interregional inputoutput system for the Brazilian economy, constructed for 2 regions (Northeast and Rest of Brazil), for the years of 1985, 1992, and 1995.