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The goal of this paper is to identity the sectors with the greatest potential to contribute to reducing electricity consumption. To this end, we apply the analysis consumption multiplier and the structural decomposition on the hybrid Input-Output Matrix between which combines data from the National Energy Balance and the National Accounts, are performed. The results for the period 2015-2018 show that many sectors had significant energy efficiency gains. It can also be noted that the implementation of energy efficiency measures today may be more complex than it was in 2001. The transport sector has a relevant connection of electrical consumption with the service and energy sectors, and has a higher multiplier energy demand. Priority for efficiency measures should be given to the Other Industries, Pulp and Paper and Agriculture sectors. Special attention should also be given to the Mining and Pelletizing, Non-metallic Minerals, Aluminum Industry (non-ferrous) and Steel Industry (steel and derivatives) sectors.

The forecasting of government revenues is extremely important for an adequate budget execution, since a good accuracy in the estimation allows the stipulation of an expenditure level that meets the demands of the population. Using data released by the National Council of Treasury Policy, the general objective of this study is to make monthly projections of disaggregated state tax revenue using the dynamic factorial model. These projections are conditioned to the official medium-term macroeconomic scenarios related to prices and economic activity. The results obtained were reasonable, and the accumulated percentage error for six months was around 10%. This considering a sample composed of more than 400 series containing quite disparate trend and seasonality patterns, besides the problem of structural breaks, measurement error, missing data, etc. This study presents a proposal for state tax revenue projections that will benefit public managers in fiscal planning.

Among the aspects related to the quality of electric power supply, continuity stands out, evaluated based on the DEC and FEC indicators that express, respectively, the duration and frequency of supply interruptions. Regarding the continuity of supply, this study aims to present an alternative approach to the current methodology implemented by ANEEL for evaluating the performance of distributors in the Brazilian Electric System. For this purpose, a stochastic frontier analysis is proposed for benchmarking the continuity indicators of electric power distributors. The proposed model estimated based on bayesian inference is still capable of contemplating the temporal dynamics of efficiency. The consideration of this point is fundamental, because the studies done to evaluate the efficiency of the electric sector have neglected the fact that part of the increase in efficiency of a utility comes from the gain of scale due to the expansion of the market, a process that happens over time. Consideration of the dynamic aspect of efficiency is also of great importance for tariff revision. It was observed that actions of the utilities managed to keep the FEC below the regulatory goal, while the DEC exceeded the limit during 2009-2019. In order to assist the regulator in calibrating local continuity targets, it was also proposed to apply the efficiency indexes to define annual global targets for the continuity indicators. The results showed that the limits defined by our methodology are compatible with the limits defined by ANEEL and are perfectly feasible to be exceeded by the utilities.

This paper applies the dynamic linear model (DLM) estimated based on the Bayesian approach to project electricity consumption for five Brazilian regional units. The appeal for the use of DLM in the case of energy consumption is due to the fact that in this model the adjustment occurs in the unit of time ensuring more accurate projections in series with a high degree of variability, such as energy consumption. The results corroborated the expectation regarding the adequacy of DLM for the purpose of making projections. The different forecast validation criteria calculated for a 12-month horizon showed very satisfactory results. In all cases, MLD had a forecast error within the 3% range, taken as a reference for the utilities. In the case of the Center, Northeast and South regions, this indicator was even lower. We tested the robustness of the MDL using a model panel data with random coefficients (MRC) that allows to obtain a set of distinct coefficients for each region, but within a common structure. Regarding forecasting, MRC performance was also reasonable, even underperforming DLM. With the exception of the Southeast region, MRC's Mape was below or in the 3% range for the other regions.

This study aims to analyze the quantile treatment effect of Prouni on the students' Enade grades from 2015 to 2017. The results indicated that the impact of the program was positive throughout the grades distribution, mainly for students who received full scholarship. The impact was also greater for students who declare family income of more than three minimum wages, which reinforces the argument that it is necessary to focus the policy resources on low-income students and prioritize those with the highest budget constraints. The effect of the program was also positive for students enrolled in institutions with quality concept 4 and 5. Thus, the study results confirm that financial aid policies for low-income students are able to combine inclusion and quality in higher education.

The ICT Household Survey aims to collect data on information and communication technologies (ICT) access and use in Brazil. We use this research to elaborate two exercises. The first one applies logistic regression to determine the factors responsible for connecting a domicile to the Internet. The second one estimates a demand model for the Internet applying a multinomial model of discrete choice. The model contemplates four types of connection: DSL with fixed telephone line, TV cable or fiber optic and mobile via modem or 3G and 4G chip. In the case of logistic regression, we verified that socioeconomic variables such as schooling, income and social class are factors that influence whether the household is connected or not. We verified that the higher the level of schooling or income, the greater the effect on the probability of the household be connecting to the Internet. We observe that there is no defined pattern concern to the effect of a variable on the probability of choosing a type of connection. Thus, each variable responds differently depending on each type of connection. This study is the first attempt with disaggregated data of estimation of Internet demand for Brazil. Although it contains certain weaknesses due to the limitations of the database, it is still a valid exercise insofar as it suggests important indications for the construction of a more reliable database for the supporting studies of Internet demand in Brazil.

This study evaluated the impact of Fies on the total time and delay in the completion of higher education of students enrolled in presential courses of private institutions, based on information of INEP from 2007 to 2017. Estimates of the Average Treatment Effect on Treated indicated that participation in Fies increased both the results analyzed, total time and delay. In the first phase of the policy, from 2000 to 2009, the increase in completion time for students who received Fies was 8.5 months. In the second phase, from 2010 to 2014, which is characterized by the loosening of the rules for the granting and payment of the loan, the increase was 2.4 years. In the case of the delay in completing the course, the result was significant only in the 2nd phase, indicating an increase of 1.8 years for the students who received the Fies. In this view, it is necessary to introduce incentive mechanisms in the student credit granting policies in order that the student completes the course in regular time.

Although there is agreement that the effect of broadband expansion on the economy, from an general overview, is positive; not an unanimous voice arguments that this impact be positive on all sectors. By applying a multivariate two way panel data model and estimated by bayesian methodology, this study aims to determine the effect of broadband expansion on the sectors of the economy. In order to take into account the geographical, social and economic differences among municipalities cluster analysis was employed in order to isolate groups of municipalities with approximate characteristics. The results illustrate that the impact of broadband is not positive for all sectors, being positive in the most dynamic and technology-intensive sectors such as the industrial and service sectors; and negative where this does not happen as in agricultural sector.

Based on the hypothesis that the rulers of monetary and fiscal policy in Brazil may have been submitted to different regimes, the present study applies Leeper model (1991; 2005) in order to identify the chronology of policy regimes regarding their active and passive character. The policy rules are estimated by the Markov Switching (MS) model in which the regimes are endogenously identified. The results obtained allow us to place that fiscal dominance occurred in 2010 and between 2013 and 2014 while monetary dominance happened in much of 2003 and during the period from 2005 to 2007. The model still seeks to explain why the rate of Inflation during 2015 remained on the rise even though the monetary policy imposed by Central Bank was active.

This study aims to present a model for economic evaluation of the expansion of the broadband network for the Brazilian municipalities. This is done taking into account not only the economic return, but also the cost of expanding the network. Return is calculated from three criteria of prioritization: size of population, HDI, and potential market. Once one of these criteria is chosen, the effect on certain variables of interest, such as the effect on the product, access to the poorest population, etc., is estimated. To determine the potential demand of broadband, we estimated model combining two databases: PNAD 2015 and Census 2010. The effect of broadband on municipal GDP was obtained using the panel data model. To evaluate the cost to expand network we the applied the solution of the minimum generating tree from the graph theory. It was observed that the criterion based on the potential market is the alternative that generates greater economic return. Also the results obtained based on the size of the population are close to this one, whereas the prioritization by the municipal HDI is the criterion that presents the worst performance that penalizes the poor and the extremely poor population.

The aim of this study is to evaluate the effect of broadband on the GDP taking into account regional differences. This is done by using the econometric model of panel data based on database of 5564 municipalities from 2007 to 2014. In order to incorporate the regional differences we use information derived from cluster analysis that isolates homogeneous groups of municipalities. Simultaneous causality between broadband and GDP is identified through instrumental variable method. Regional differentiated effects of broadband among municipalities were observed. The greatest impact of broadband occurs on those municipalities with the highest income per capita and high urban concentration followed by ones with a strong concentration in the service, commerce and construction sectors. The impact of broadband is also significant in the municipalities linked to the dynamic agricultural sector. In poorer municipalities the effect of broadband also occurs although with less intensity. Finally, we test the hypothesis that the effect of broadband on the output has an "inverted U" form that indicates that the effect rises to a certain level of access, but decreases after it is exceeded. The econometric results do not indicate that this hypothesis can be denied so that the impact is more intense in the intermediate levels of access of broadband.

The objective of this study is to predict the potential broadband market in Brazil. This task is done by combining information from two national databases: the Demographic Census of 2010 and the National Survey by Household Sample (Pnad) of 2015. The Pnad 2015 is used to estimate the probability of the household accessing internet by broadband technology using a logit regression. The broadband market is predicted using the estimated model with the same covariates found in the Demographic Census 2010. The prediction indicated a potential market of 45 million households, an additional of 6 million households in relation to the current situation. The new size of the broadband market is estimated if there is a 10% increase in the average penetration of broadband services in the main metropolitan regions. In this scenario, it is observed that the new market reaches 50,7 million households.

This study aims to examine the sustainability of the Brazilian public indebtedness using different approaches. Based on the analysis of the conditioning factors of net debt of the public sector (DLSP) in the period 2002-2014, there seems to be a change in fiscal regime between 2011 and 2014 compared to the previous period from 2002 to 2010. We propose to include Petrobras, Eletrobras and the remains payable into the DLSP. The result indicates that the difference between net debt and gross displays a sensible reduction. We apply three different cointegration tests in the series of government revenue and expenditure in order to check the sustainability of public debt. The results show no empirical evidence that public debt is long-term solvent. Finally, based on the dynamic factor model one forecasts the revenues and expenditures of the central government for 36 months ahead. It was found that the primary outcome may suffer serious deterioration since from September 2015 to August 2018 the values predicted shows a decrease in revenues while the trend for expenses is growing. This implies a further limiting factor to the sustainability and solvency of public debt.

This study aims to revisit the issue of the sustainability of public indebtedness in Brazil, investigating the evolution of gross debt of public sector, the relationship between its liabilities and assets of the public sector, the future implications of gross debt to net debt and to make forecast of the gross debt of the general government for the next two years. We show that the examination of the concept of net debt (gross debt less public sector assets) can cover up important questions about the public indebtedness.We ask if one can have some idea about the future behavior of net debt based on the present performance of gross debt. In this context, we conducted a Granger causality test between the net (DLGG) and gross debt (DBGG) of the general government. Empirical results show that DBGG Granger cause DLGG.We apply the Dynamic Factorial Model (MFD) to make forecast on the gross debt of public sector and its major components. The results display a strong rise in foreign debt and repurchase agreements. In August 2016 they reach, respectively, 10% and 17% of GDP. The results also show the forecast of the net debt (DLSP). It is shown that DLSP reaches 44% of GDP in August 2016. The GDP also shows sharp drop in economic activity. From September 2015 to August 2016 this variable decreases around 3.5%. Finally, we check the effect the indebtedness on economic growth. The empirical results show that the rise of both the gross and the net debt as a proportion of GDP has a negative effect on the growth rate of the GDP.

This study aimed to the application of forecasts combination of model to predict tax revenues in Brazil. Here we combine the predictions obtained from three models: dynamic factor model (DFM), seasonal autoregressive integrated moving average (Sarima) and model of Holt-Winters smoothing. We adopted five criteria for combine predictions: optimal combination, performance, simple regression, simple average and median. We work with monthly data for a total of nine federal taxes for the period from January 2001 to December 2013. The out of sample forecast are done for the year 2014. Considering the results, it can be seen that the combined predictions proved generally superior to those derived from genuine models with the exception of a few taxes. Notwithstanding there is no specific method of combination that provide better forecasts concern the others.

We develop a new Bayesian estimator that is able to deal with multivariate panel data structure in the presence of spatial correlation. The analysis of panel data introduced here allows us to analyze not only the fixed effect but also the random effect model. This work extends the previous study undertaken by Gamerman and Moreira (2004) which only spatial scale is considered. To estimate the random effect model we use the hierarchical analysis that can be applied to estimate some categories of longitudinal data models. The Monte Carlo simulations demonstrate the ability of this new estimator to replicate quite well simulated data. To show the empirical relevance of this new estimator we apply it to the deforestation data in the Brazilian Amazon.

This paper uses Brazilian quarterly data, from the period January/2002 to June/2015, to estimate the impact of taxes over gross domestic product (GDP) per capita. The econometric results show a negative and statistically significant impact of the overall tax burden over per capita GDP. In average, an increase of 1 percent in the overall tax burden decreases GDP per capita by 0.3 percent. This result is very similar in magnitude with those presented by Heady et al. (2011). Furthermore, additional econometric results pointed out that a revenue neutral fiscal policy which changes the tax structure toward consumption taxes and personal income taxes would improve economic growth. Besides that, we strongly recommend against both taxes over the capital stock (mainly the recurrent ones) and the corporate income taxes.

In this article we estimate the relationship between inflation and trade openness [e.g., Romer (1993)] using modern panel data techniques. The advantage here is that we are able to explicit test the hypothesis proposed by Terra (1998) that the negative relationship between openness and inflation is due to severely indebted countries in the debt crisis period. The econometric results give support to Romer (1993) showing that the negative relationship between inflation and openness are neither restrict to a subset of countries or a time period.

This article estimates the monetary policy rule followed by the Brazilian Central Bank for setting its main policy instrument, the SELIC rate, for the period after the Real Plan. In order to overcome the uncertainty over the dates at which changes in parameters occurred, this paper uses regime-dependent-switching probabilities according to a hidden Markov chain to model possible deviations from a simple linear reaction function. From July 1996 to January 2006 the Brazilian monetary policy can be fully characterized by four policy regimes. The changes in monetary policy in this period are best described by recurring regime changes, instead of once-and-for-all shifts. We have identified substantial differences in the way monetary policy was conducted in the subperiods before and after 1999, when the Brazilian exchange rate policy regime changed from crawling peg to free-floating. At each of these subperiods there are two recurring regimes and the two regimes of one subperiod differ from the two regimes of the other.

This article aims to estimate the dynamic factor model for prediction tax receipts in Brazil using monthly data for the period 2001-2013. The factorial model allows to reduce the dimensionality of the high number of taxes taking into account the information contained in the existing interrelations between them and allowing to identify only the relevant information through the variables named factors. Further, in our model the seasonal component of the series of taxes is treated endogenously. This procedure permits to obtain better data fitting and more reliable predictions - once seasonality is a hallmark of certain series of tributes. We confront the predictions of the factorial model with those generated by linear dynamic model applied to each tribute separately and found that the factor model brings considerable gains in terms of efficiency and prediction.

Based on the relation between investment and domestic saving proposed by Feldstein and Horioka (1980) to verify capital mobility, this study performs some exogeneity tests in order to determine the capacity of the FH equation of supporting and implementing economic policies in Brazil. We then use the result of weak exogeneity test to identify a structural vector autoregressive (SVAR) involving investment and saving in order to evaluate the effect of exogenous shocks through impulse response functions (IRFs) on both variables. The main findings of this paper are: a) the elasticity of domestic saving estimated using appropriate methods points out to high capital mobility for Brazil; b) domestic saving is weakly exogenous in the FH equation; c) domestic saving is not strongly exogenous, therefore this equation should not be used to make forecasts for the Brazilian economy; d) superexogeneity is accepted for domestic saving, meaning that Lucas' criticism does not apply; and e) the IRFs showed that investment is sensitive to contemporaneous innovation on saving and this effect lasts for a long time. Regarding to domestic saving, the response of this variable to a non-expected shock on investment has a more is more complicate description. Initially domestic saving goes down. After some lags this movement changes and domestic saving begins to react positively to the shock.

In this article we use the theory of conditional forecasts to develop a new Monetary Conditions Index (MCI) for Brazil and compare it to the ones constructed using the methodologies suggested by Bernanke and Mihov (1998) and Batini and Turnbull (2002). We use Sims and Zha (1999) and Waggoner and Zha (1999) approaches to develop and compute Bayesian error bands for the MCIs. The new indicator we develop is called the Conditional Monetary Conditions Index (CMCI) and is constructed using, alternatively, Structural Vector Autoregressions (SVARs) and Forward-Looking (FL) models. The CMCI is the forecasted output gap, conditioned on observed values of the nominal interest rate (the Selic rate) and of the real exchange rate. We show that the CMCI, when compared to the MCI developed by Batini and Turnbull (2002), is a better measure of monetary policy stance because it takes into account the endogeneity of variables involved in the analysis. The CMCI and the Bernanke and Mihov MCI (BMCI), despite conceptual differences, show similarities in their chronology of the stance of monetary policy in Brazil. The CMCI is a smoother version of the BMCI, possibly because the impact of changes in the observed values of the Selic rate is partially compensated by changes in the value of the real exchange rate. The Brazilian monetary policy, in the 2000:9- 2005:4 period and according to the last two indicators, has been expansionary near election months.

This study aims to analyse the demand for credit in Brazilian market for vehicles. Based on the Markov Switching model to dealing with regime change, we estimate a demand function using aggregated monthly data from Oct./2000 to Dec./2012. The results showed that the demand for credit was subject to three distinct states during this period. The first one marks the state where the credit was determined by the market fundamentals. This regime most appeared from 2004 to 2008 in which one perceives a cycle of continued and strong expansion of credit. After it follows one state strongly influenced by the economic crisis occurred in the beginning of 2008. In this period there was a great fall in credit. The third regime that rushes in a single cycle between Dec./2008 Oct./2010 happened as a result of countercyclical measures adopted by the Central Bank and the Federal Government with the aim of mitigating the effects of the economic crisis. Such measures promoted the quickly expansion of credit leading to the process of bubble formation in market for vehicles that led to the need for the introduction of so-called macro prudential measures by the Central Bank when there was already an ongoing trend of continuous increase in default.

Switching model, we estimate the demand for mortgage using aggregate monthly data from January 2003 to September 2012. The results show that this variable has been subject to cycles of contraction and expansion since 2003. The boom starts at the end of 2005 is marked by the alternation of two distinct regimes. The first one that concentrates between late 2005 until early 2009 seems to be driven by factors pro-market resulting from changes in legislation, economic growth, rising in real income, etc. The situation changes at the beginning of 2009 when the condition of the demand for mortgage is mainly motivated by countercyclical measures adopted by the federal government with the aim of mitigating the effects of the world economic crisis of 2007-2008. The recessive phase of the credit cycle is linked to a single regime that extends until 2005 returning around March 2012 when the series of credit seems to slow down. We also applied the structural VAR model with the purpose of evaluating the effect of a monetary policy shock on the demand mortgage. According to the results, a contractionary shock produces a negative effect on real estate. We note a continuous and sharp decline in mortgage demand, price home, industrial output construction as well as a rising on defaults.

This study aims to estimate the system of bank credit demand and supply in Brazil. Understanding how the balance is established in this market is the key to know the importance of the credit channel. Based on the aggregated data from June 2000 to August 2012 not only for firms but also for individuals we founded the following results. First, credit demand is pro-cyclical, reacting negatively to the unemployment and positively to GDP. Second, the price elasticity of demand for firms is higher for firms than for individuals, corroborating the fact that companies may have other sources of funding. Thirdly, it was not possible to determine the bank credit supply to individuals. This fact seems to indicate that there is no reverse causality in the personnel credit in the sense that, for this segment, the credit demand has no effect on the loan rate. Fourth, we observe the expected signs into default, the cost of funding and inflation in credit supply function in both segments. Finally, it appears that the introduction of payroll loans on personnel credit brought down the cost of the loan.

This article verifies the occurrence of a real estate bubble in the Brazilian economy. Overall, our results suggest the existence of a bubble in the real estate sector of the economy. The Austrian School of economics provides a solid explanation to this phenomenon, which are reinforced by statistical techniques, suggesting the Federal government, with equivocate fiscal and monetary policy, as the main responsible for the creation of this problem.