Effects of trade policy on technology adoption and investment

This paper studies the consequences of trade policy for the adoption of new technologies. It develops a dynamic international trade model with two sectors. Workers in manufacturing decide if new technologies are used, capital owners then choose investment. We analyze three different arrangements: free trade, tariffs, and quotas. In the model economy, free trade as well as tariffs guarantee that the most productive technology available will be used. In contrasL under a quota the most productive technology available will not be used at all times. Further, in the latter case investment and the capital stock are smaller than in the former one. Finally, there exists parameter values for which the computed difference in GDP is a factor of thirty.

Technical change and factor shares

The implications of technical change that directly alters factor shares are examined. Such change can lower the income of some factors of production even when it raises total output, thus offering a possible explanation for episodes of social conflict such as the Luddite uprisings in 19th century England and the recent divergence in the U. S. between wages for skilled and unskilled labor. An explanation also why underdeveloped countries do not adopt the latest technology but continue to use outmoded production methods. Total factor productivity is shown to be a misleading measure of technical progress. Share-altering technical change brings into question the plausibility of a wide class of endogenous growth models.

The failure of early-stage technology startups in Brazil: a study about the contributing factors to the early-death of startups between 2009 and 2014 in Southeastern Brazil

This research aimed to find out which are the main factors that lead technology startups to fail. The study focused on companies located in the Southeast region of Brazil that operated between 2009 and 2014. In the beginning, a review of the literature was done to have a better understanding of basic concepts of entrepreneurship as well as modern techniques for developing entrepreneurship. Furthermore, an analysis of the entrepreneurial scenario in Brazil, with a focus on the Southeast, was also done. After this phase, the qualitative study began, in which 24 specialists from startups were interviewed and asked about which factors were crucial in leading a technology startup to fail. After analyzing the results, four main factors were identified and these factors were validated through a quantitative survey. A questionnaire was then formulated based on the answers from the respondents and distributed to founders and executives of startups, which both failed and succeeded. The questionnaire was answered by 56 companies and their answers were treated with the factor analysis statistical method to check the validity of the questionnaire. Finally, the logistical regression method was used to know the extent to which the factors led to the startups’ failure. In the end, the results obtained suggest that the most significant factor that leads technology startups in southeastern Brazil to fail are problems with interpersonal relationship between partners or investors.