Aiming to encourage the domestic production chain

Aiming to encourage the domestic production chain and to encourage technological development and work qualification, the Brazilian government established as a requirement in the bidding for the exploration of fields, patterns of Local Content (LC), in which companies must meet certain percentage commitment to purchase domestic goods and services. Since the first round of grant of exploration fields (completed in 1999), ANP applies the concept of CL. However, from the 5th round, completed in 2003, the concession contracts now require minimum percentages to offer CL, established in bids, ranging between 37% and 77%, according to the activity and the location of field exploration and development of production (Bone, 2011; Xavier, 2011). However, many controversies surround this policy of local content because of potential order paricalcitol in the supply that still would be unable to meet the demand of Petrobras and also the other operators in the industry chain. According to a study by the Institute of Economics of UFRJ, the local industry would only have capacity to meet the need of oil in five of the 24 categories of equipment critical to the exploration and production (EXAME, 2012). Moreover, according to the ANP (2012), for 80% of the equipment that will be demanded there are few suppliers in the country. Foreign companies are the only suppliers in about 75% of the items. Domestic suppliers prevail or hold exclusivity in only 4–7% of the items, such as automation systems, pumps and heat exchangers. To study and simulate the impact of the Pre-Salt, it is necessary to take a global simulation model that captures the participation of countries in the oil trade, their supply chains and the insertion of Brazil in this market. For this we use a global dynamic computable general equilibrium model, GDyn, a dynamic version of the GTAP model (Hertel, 1997), widely used and documented in the literature. As far as we know, this is the first application of the GDyn model for Brazil. Besides this introduction, this paper is divided into 4 more parts. The Section 2 presents the model and the database used in this work. Sections 3 and 4 discuss the simulations and the results obtained, and finally the last section weaves his final remarks.
Methodology
Simulations In this section we report the procedures used in the simulations for the later discussion of the main results of the exploration of megareserves oil from Pre-Salt. Fig. 3 illustrates the dynamics of the simulations and how the model is fed with information from the 2007 base year model. The baseline scenario should reflect as much as possible, the projected changes in the global economy over the study period (2007–2020). Therefore, it represents what would be the trajectory of the economy without the shock exploration of Pre-Salt layer, for example. The preparation of a base or confractual scenario is an important component in the simulation when using a dynamic model, and your choice may affect the results of the scenario into account (Adams and Parmenter, 2000). Such a construction allows viewing two trajectories for each variable of interest: a trajectory that shows how the variable would change over time not considering the issue under study; and the trajectory that determines how the variable behave with the “shock” of the Pre-Salt, as is the case of this work. The difference between these trajectories (base scenario and the scenario with the shock of the Pre-Salt) represents the additional effect of increased exploration and production of oil due to the Pre-Salt. Typically, these differences are accumulated over the period of analysis to illustrate the impact on certain variable, as shown in the example of Fig. 3.
Discussion of results
Final remarks
Introduction Economic growth and the increase in demand for jobs have generated significant changes in the Brazilian job market dynamics. Besides that, the recent phenomenon of income inequality reduction has a direct implication for the transformations that have occurred in the demand and supply sides of the market occupational distribution (Barros et al., 2007).