Land taxes in a Latin American context

Since Henry George (1839-1897) economists have been arguing that a tax on unimproved land is an ideal tax on efficiency grounds. Output taxes, on the other hand, have distortionary effects on the economy. This paper shows that under asymmetric information output taxes might be used along with land tax in order to implement an optimal taxation scheme in a Latin American context, i.e., where land rental markets are relatively thin, land property provides non-agricultural payoffs and there is nonrevenue objectives of land taxation. Also, the model has two implications that can be tested empirically: (i) there is evasion when schemes based only on land taxes are implemented; (ii) this evasion is more severe for large landholders.

The optimality of the Friedman rule when some distorting taxes are exogenous

This paper investigates the optimality of the Friedman rule in a two-sector small open economy. That policy prescription is found to be a necessary condition for Pareto efficiency. If a planner can select all conceivable distorting taxes, then, for some initial values of public debt, money balances and foreign assets, it is possible to decentralize a Pareto efficient allocation. If the planner can select only some of these tax rates, then second-best policies may also satisfy the Friedman rule. However, this last result depends on the set of tax instruments the planner can choose from.

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.