Methodology for measuring the impact of mobile technology change from 2nd to 3th generation percerved by users of smes in Barranquilla

This article presents the results of a research project undertaken to obtain a Masters inBusiness Administration from the Business School at the Universidad del Norte, whosepurpose was to identify and test a methodology to measure the impact exerted by thechange from 2nd to 3rd generation mobile tech, based on the perception of users belongingto Barranquilla SME, motivated by the influence of technological changes in behavior andthe knowledge creation among society members, and the importance it has taken to thesurvival of organizations the adoption of applications for process automation, web-basedapplications, voice, data and video that allow the development of competitive advantages,based on information and creativity for new and better products or services.

Measuring and testing for the systemically important financial institutions

This paper analyzes the measure of systemic importance ∆CoV aR proposed by Adrian and Brunnermeier (2009, 2010) within the context of a similar class of risk measures used in the risk management literature. In addition, we develop a series of testing procedures, based on ∆CoV aR, to identify and rank the systemically important institutions. We stress the importance of statistical testing in interpreting the measure of systemic importance. An empirical application illustrates the testing procedures, using equity data for three European banks.

Re-measuring labor's share

Measuring labor's share of an economy's aggregate income seems straightforward, at least in principle. Count up wage and salary income, along with the value of benefits provided to employees, and divide it by total income. However, one fundamental concept of labor's share in macroeconomic theory is not the amount of aggregate income paid out to labor. Rather, it is the share of aggregate production that is attributable to "raw" units of labor. Or, otherwise stated, it is the share of aggregate income that would have been paid to laborers if they had no accumulated stocks of human capital.1 This share corresponds to an aggregate production function parameter: the elasticity of output with respect to physical (i.e. non-augmented or raw) units of labor (Robert Solow, 1957). In this paper we estimate annual raw labor’s share for the US, 1949 to 1996.