A agropecuária brasileira tem crescido nas últimas décadas e os ganhos de produtividade tem sido importante neste bom desempenho do setor. O presente trabalho tem dois objetivos principais. O primeiro deles foi mensurar o crescimento desta produtividade total dos fatores na agropecuária brasileira estadual, decompondo o crescimento da PTF em progresso tecnológico e eficiência técnica. O segundo objetivo foi analisar o efeito do crescimento da PTF da agropecuária brasileira sobre os preços agrícolas, no Brasil, de 1970 a 2006. O crescimento desta produtividade foi mensurado a partir dos insumos terra, trabalho e capital na função de produção translog sob orientação do produto, a partir do método de Fronteira Estocástica de Produção e do índice de produtividade de Malmquist. Para avaliar o efeito do crescimento da PTF sobre os preços agrícolas foi construído o índice de preços agrícolas utilizando-se o Índice de preços de Laspeyres para estimar o vetor autoregressivo em painel (panel- VAR), acrescentando as variáveis produtividade total dos fatores (PTF), salário rural, financiamento agrícola e renda per capita domiciliar. Além disso, foi aplicado o teste de causalidade, no sentido de Granger, e estimada a função impulso resposta. A base de dados utilizada foi, obtida do Censo Agropecuário, a nível estadual, para os anos de 1970, 1975, 1980, 1985, 1995 e 2006. Os resultados indicaram que a taxa de crescimento da PTF foi crescente no Brasil e nos estados, sendo que, na maior parte das vezes, é explicada pelo progresso tecnológico, positivo e crescente para todos os estados. A eficiência técnica variou ao longo dos anos, apresentado taxas de crescimento médias positivas para a maioria dos estados. Em média, os estados estiveram situados abaixo da fronteira de produção da agropecuária brasileira. São Paulo foi o estado com maior nível de eficiência técnica. Embora a taxa de crescimento médio anual tenha sido positiva ao longo do período analisado, a eficiência reduziu para todos os estados analisados em 2006. Da análise dos efeitos do crescimento da PTF sobre os preços agrícolas, a PTF tem causalidade, no sentido de Granger, sobre os preços agrícolas. Na função impulso resposta, o choque inicial na variável PTF reduziu os preços nos primeiros anos. Assim, o crescimento da PTF do setor agropecuário contribuiu para o aumento da oferta de produtos, reduzindo os preços agrícolas. A maior disponibilidade de alimentos e, com a redução dos preços dos alimentos, os consumidores, principalmente os de renda mais baixa puderam ter maior acesso aos alimentos. / The Brazilian agriculture has grown in recent decades and productivity gains have been important in this good performance of the sector. This work had two main objectives. The first one was measure the growth of this total factor productivity in agriculture by the Brazilian\'s states, decomposing TFP growth by technological progress, technical efficiency and economies of scale. The second objective was to analyze the effect of TFP growth of Brazilian agriculture on agricultural prices. The growth in productivity was measured from the inputs like labor, gross and capital in the translog production function, from the Stochastic Frontier Analysis and of the outputoriented Malmquist productivity index. To analyze the effect of TFP growth on agricultural prices was constructed an index of agricultural prices through the Laspeyres price index to estimate the vector autoregressive panel (panel-VAR) and establish the relationships between TFP, rural wages, agricultural finance and income per capita household. The Granger causality test and the impulse response function were used to the data panel. The database used obtained from the Agricultural Census, at the state level for the years 1970, 1975, 1980, 1985, 1995 and 2006. The results showed that the growth rate of TFP has been growing in Brazil and in the states, and technological progress explained most of the growth being positive and growing for all states. Technical efficiency varied over the years, presented positive average growth rates for most states. The states were located below the production frontier of Brazilian agriculture and São Paulo was the state with the highest level of technical efficiency. Although the average annual growth rate has been increasing over the period analyzed, the efficiency decreased to all state analyzed in 2006. The results also showed that TFP growth has causality in the sense of Granger, on agricultural prices. In the impulse response function, the initial shock in TFP decreased prices in the early years. Thus, TFP growth of the agricultural sector contributed to the increased supply of agricultural products, reducing agricultural prices. The greater availability of food and with reducing food prices, consumers, especially those from lower income might had greater access to food.

Submitted by Rafael Reboreda Sbardella (kasd@ig.com.br) on 2013-03-01T00:27:23Z No. of bitstreams: 1 Dissertação_RafaelReboredaSbardella_2013.pdf: 13504519 bytes, checksum: 8fa81c4df5f6826159fadad65819b06d (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-03-01T13:22:03Z (GMT) No. of bitstreams: 1 Dissertação_RafaelReboredaSbardella_2013.pdf: 13504519 bytes, checksum: 8fa81c4df5f6826159fadad65819b06d (MD5) / Made available in DSpace on 2013-03-01T13:24:34Z (GMT). No. of bitstreams: 1 Dissertação_RafaelReboredaSbardella_2013.pdf: 13504519 bytes, checksum: 8fa81c4df5f6826159fadad65819b06d (MD5) Previous issue date: 2013-01-29 / Na última década, a economia brasileira apresentou-se estável adquirindo maior credibilidade mundial. Dentre as opções de investimento, estão os mercados de ações e de títulos públicos. O portfolio de investimento dos agentes é determinado de acordo com os retornos dos ativos e/ou aversão ao risco, e a diversificação é importante para mitigar risco. Dessa forma, o objetivo principal do presente trabalho é estudar a inter-relação entre os mercados de títulos públicos e ações, avaliando aspectos de liquidez e quais variáveis representariam melhor esta relação, verificando também como respondem a um choque (surpresa econômica), pois a percepção de alteração do cenário econômico, ou variações de fluxo financeiro, pode alterar/inverter as relações entre esses mercados. Para isso, estimou-se modelos de vetores auto-regressivos - VAR, com variáveis de retorno, volatilidade e volume negociado para cada um dos mercados em combinações diferentes das variáveis representativas, visando encontrar o(s) modelo(s) mais descritivo(s) das inter-relações entre os mercados, dado a amostra utilizada, para aplicar a dummy de surpresa econômica. Em estudo semelhante Chordia, Sarkar e Subrahmanyam (2005) concluiram que choques de liquidez e volatilidade são positivamente correlacionado nos mercados de ações e títulos públicos em horizontes diários, indicando que os choques de liquidez e volatilidade são muitas vezes de natureza sistêmica. O mesmo não foi observado para a proxy de liquidez utilizada na amostra brasileira. Um resultado interessante a ser ressaltado deve-se as séries SMLL11 (índice Small Caps) e IDkAs (índice de duração constante ANBIMA) não possuírem relação de causalidade de Granger com as demais séries, mas os retornos dos IDkAs Granger causam os retornos do índice SMLL11. Por fim, o choque de surpresa econômica não se mostra explicativo sobre qualquer alteração nas inter-relações entre os mercados de títulos públicos e ações. / In the last decade, the Brazilian economy remained stable gaining credibility worldwide. Among the investment options, are the stock and bond markets. The investment portfolio of agents is determined according to the asset returns and / or risk aversion, and diversification is important to mitigate risk. Thus, the main objective of this work is to study the interrelationship between the stock and bond markets, assessing aspects of liquidity and what variables best represent this relationship, as well as checking account to a shock (economic surprise), because the perception of change economic scenario, or variations in cash flow, can change / reverse relations between these markets. For this, it is estimated models vector autoregressive - VAR with variables of return, volatility and trading volume for each of the markets in different combinations of proxy variables, aiming to find the most descriptive model(s) of the interrelationships between markets, given the sample used, to apply the dummy economic surprise. In a similar study Chordia, Sarkar e Subrahmanyam (2005) conclude that liquidity and volatility shocks are positively and significantly correlated across stock and bond markets at daily horizons, indicating that liquidity and volatility shocks are often systemic in nature. The same was not observed for the liquidity proxy used in the Brazilian sample. An interesting result to be noted due to the SMLL11 (Small Caps index) series e IDkAs (ANBIMA index with constant duration) not have Granger causality relationship with the other series, but the returns of IDkAs Granger cause the returns of the SMLL11 index. Finally, the shock of surprise monetary does not show any change in the explanatory inter-relationships between stock and bond markets.

Cities have adopted evolving urban digitization strategies, and most of those increasingly focus on data, especially in the field of public transportation. Transportation data have intuitively spatial and temporal characteristics, for they are often described with when and where the trips occur. Since a trip is often described with many attributes, the transportation data can be presented with a tensor, a container which can house data in $N$-dimensions. Unlike a traditional data frame, which only has column variables, tensor is intuitively more straightforward to explore spatio-temporal data-sets, which makes those attributes more easily interpreted. However, it requires unique techniques to extract useful and relatively correct information in attributes highly correlated with each other. This work presents a mixed model consisting of tensor decomposition combined with seasonal vector autoregression in time to find latent patterns within historical taxi data classified by types of taxis, pick-up and drop-off times of services in NYC, so that it can help predict the place and time where taxis are demanded. We validated the proposed approach using the experiment evaluation with real NYC tax data. The proposed method shows the best prediction among alternative models without geographical inference, and captures the daily patterns of taxi demands for business and entertainment needs.

This study will be investigating the relationship between short-term and long-term interest rates with the OMX30 stock return expressed in percentage, as well as the effect that the interest rates have on the stock return. The data used in this study has been collected from the dataprogram Datastream with monthly observations from January 2003 until December 2022 resulting in 240 different variables within all three factors over a period of 20 years. While performing OLS estimation, the result estimated by using R-studio shows a negative correlation between the interest rates and the percentage return of OMX30. Furthermore, the Granger causality test shows that the short-term interest rate does have an impact on the market whilst the long-term interest rate does not have any direct effect on the stock market in Sweden.

台灣幅員狹小，天然資源不足，唯有藉著大量出口才能換取外匯，情況使得台灣逐漸發展成一小型開放經濟。長久以來，美國一直是台灣最大的貿易夥伴，使得台灣產品對美輸出的多寡往往直接影響台灣總體經濟的表現。隨著政府外匯政策的逐漸自由化，匯率在總體經濟中所扮演的角色也越顯重要。近幾年來，台幣匯價在外匯市場上時有波動，不但影響政府政策的擬定、經貿活動的往來，外匯市場上的投炒作更造成熱錢的流動。是故，新台幣對美元匯率的決定及波動因素是值得我們深入探討的課題。基於此點，本文擬建立一個可供實証的小型開放經濟模型，試圖探討新台幣對美元匯率的決定因素。首先，參照Frankel(1979)所提出的實質利率差價模型(Real Interest Rate Differential Model)，作為實証研究的基礎。其次，利用Johansen(1988,1991)、Johansen & Juselius(1990)的共整合(cointegration)分析方法，以台灣地區1981年至1993年間的月資料，驗証縮減式的長期關係是否成立。最後，採用誤差修正模型(error correction model)，估計匯率的動態調整途徑，並對匯率變動率進行樣本後預測。 　　實証結果發現：(1)實質匯率差價模型所刻畫的匯率與其他經濟變數的長期關係在台灣是可以成立的；(2)傳統貨幣學派對兩國結構喜數相同的假設過於嚴苛，對於台灣及美國並不適用；(3)除了名目利率外，台灣及美國的貨幣供給、產出水準及通貨膨脹率具有一對一的關係；(4)以誤差修正模型預測台幣／美元匯率變動率，其效果優於隨機漫步模型。

銅價在近年來不斷的創下歷史新高，由於台灣蓬勃的電子、半導體、工具機產業皆需要銅，因此銅進口量位居全球第五(ICSG,2009)，使得台灣企業的生產成本受國際銅價的波動影響甚鉅，全球有70%的銅價是按照英國倫敦金屬交易所(London Metal Exchange, LME)的牌價進行貿易，因此本研究欲建置預測模式以預測銅價未來趨勢。 　　本研究之資料來源為2003年1月2日至2011年7月14日的LME三月期銅價，並依文獻探討選取LME的銅庫存、三月期鋁價、三月期鉛價、三月期鎳價、三月期鋅價、三月期錫價，以及金價、銀價、石油價格、美國生產者物價指數、美國消費者物價指數、聯邦資金利率作為影響因素的分析資料。時間序列分析、類神經網路已被廣泛的用於預測股市及期貨，本研究先藉由向量自我迴歸模型篩選出有影響力的變數，同時建置GARCH時間序列預測模型與具有遞迴的Elman類神經網路預測模型，再整合兩者建置GARCH-Elman類神經網路預測模型。 本研究之向量自我迴歸模型顯示銅價與金、鋁、銅庫存前第1期；自身前第2期；鎳、錫前第3期；鋅前第4期的變動有負向的影響；受到石油前第2期的變動有正向的影響，這其中以銅的自我解釋變異最高，銅庫存最低，推測其影響已有效率地反映到銅價上。也驗證預測模型必須考量總體經濟變數，且變數先經向量自我迴歸模型的篩選能因減少雜訊而提升類神經網路的預測能力。依此建置的GARCH模型有33.81%的累積報酬率、Elman類神經網路38.11%、整合兩者的GARCH-Elman類神經網路56.46%，皆優於實際銅價指數的累積報酬率。對銅有需求的企業者，能更為準確的預測漲跌趨勢，依此判斷如何跟原物料供應商簽訂合約的價格與期間，使其免於價格趨勢的誤判而提高生產成本，並提出五點建議供未來研究者參考。 / The recent copper price in London Metal Exchange (LME) has breaking the historical high. Taiwan’s booming electronics, semiconductor and machine tool industry causing copper import volume ranked fifth in the world (ICSG, 2009). Because of 70% of copper worldwide trade in accordance with the price of the London Metal Exchange, this study using time series and neural networks to build the LME copper price forecast model. 　　This study considering copper, copper stocks, aluminum, lead, nickel, zinc, tin, gold, silver, oil ,federal funds rate, CPI and PPI during the period of 2003/1/2 to 2011/7/14. Time series model and neural networks have been widely used for forecasting the stock market and futures. In this study, using Vector Autoregressive (VAR) model screened influential variables, building GARCH model and Elman neural network to forecast the LME copper price; and further, integrating this two models to build GARCH-Elman neural network prediction model. 　　This study’s VAR models show that the copper has negative effect with gold, aluminum, copper stocks, nickel, tin, zinc and itself. And has positive impact with oil prices. The highest of explained variance is copper. Copper stocks are lowest, speculating that its impact has been efficiently reflecting on the price of copper. Verifying the prediction model must consider the macroeconomics variables. Using VAR model screened influential variables can reduce noise to enhance the predictive ability of the neural network. This study’s GARCH model has 33.81% of the cumulative rate of return, Elman neural network has 38.11% and the GARCH-Elman neural network has 56.46%. All of them are better than the actual price of copper.

Submitted by Felipe Dexheimer (felipe.dex@gmail.com) on 2017-08-30T17:01:27Z No. of bitstreams: 1 DissertacaoEnvio.pdf: 1900582 bytes, checksum: 347a4791d6eeac1e6b4919e40e275ffa (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2017-08-30T19:13:58Z (GMT) No. of bitstreams: 1 DissertacaoEnvio.pdf: 1900582 bytes, checksum: 347a4791d6eeac1e6b4919e40e275ffa (MD5) / Made available in DSpace on 2017-08-31T12:32:24Z (GMT). No. of bitstreams: 1 DissertacaoEnvio.pdf: 1900582 bytes, checksum: 347a4791d6eeac1e6b4919e40e275ffa (MD5) Previous issue date: 2017-08-11 / The objective of this paper is to seek insights into the Great Recession, which started after the Financial Shock of 2008 and still casts a shadow on the growth of Developed Economies. Common features such as near zero interest rates, disappointing growth and low inflation - with a constant fear of deflation - have been observed in most of these countries in the last few years. The Secular Stagnation Hypothesis argues that the causes are a depressed demand, both for investments and finished products and services, and that to avoid a deflation trap governments should step in, helping economies reach their potential again. The Credit Supercycle Hypothesis puts the deleveraging cycle on focus: the large credit expansion that happened prior to the shock must be dealt with, through inflation, growth, restructuring or a combination of those, before economic agents go back to their normal behavior. The analysis of their main differences leads to the investigation of the credit cycle and its impact on productivity growth. Two approaches are used, with the time frame ranging from 1995 to 2014: a Vector Autoregressive (VAR) analysis focused on twenty developed countries and a Real Business Cycle analysis of the American Economy, both replicated from previous studies with similar focus, but different context. The results show the importance of credit formation to the growth of productivity, both directly and through fixed capital investment, and also that the low productivity growth on recent years may be not a symptom of slow technological improvement, but instead caused by the lack of credit access, notwithstanding the low interest rates and credit spreads. Policy makers overlooking this evidence might be surprised by an unforeseen rise in productivity growth after the financial system returns to a more normal behavior. / O objetivo deste artigo é buscar informações sobre a Grande Recessão, que começou após o Choque Financeiro de 2008 e ainda gera uma sombra sobre o crescimento das Economias Desenvolvidas. Características comuns, como taxas de juros próximas de zero, decepções de crescimento e baixa inflação - com um medo constante da deflação - foram observados na maioria desses países nos últimos anos. A Hipótese da Estagnação Secular argumenta que as causas é uma demanda deprimida, tanto para investimentos quanto para produtos e serviços finais, e para evitar uma armadilha de deflação, os governos devem intervir, ajudando as economias a alcançar seu potencial novamente. A Hipótese do Superciclo de Crédito coloca o processo de desalavancagem em foco: a grande expansão de crédito que aconteceu antes do choque deve ser tratada, por meio da inflação, crescimento, reestruturação ou uma combinação desses, antes que os agentes econômicos voltem ao seu comportamento normal. A análise das principais diferenças dessas hipóteses leva à investigação acerca do ciclo do crédito e seu impacto no crescimento da produtividade. São utilizadas duas abordagens, com o intervalo de tempo entre 1995 e 2014: um modelo Vetorial Autoregressivo (VAR) focado em vinte países desenvolvidos e uma análise de Ciclo Real de Negócios (Real Business Cycle) da economia americana, ambas replicadas de estudos anteriores que tinham foco semelhante, mas contexto diferente. Os resultados mostram a importância da formação de crédito para o crescimento da produtividade, tanto diretamente como através do investimento em capital fixo, e também que o baixo crescimento da produtividade nos últimos anos pode não ser um sintoma de melhoria tecnológica lenta, mas sim causado pela falta de acesso a crédito, não obstante as baixas taxas de juros e spreads de crédito. Ao negligenciar essas evidências formadores de políticas econômicas podem se surpreender com um aumento imprevisto do crescimento da produtividade após o sistema financeiro retornar a um comportamento mais normal.

A number of developing countries have been on a quest to attract foreign direct investment (FDI) with the intention of increasing capital inflow through technological spillovers and transfer of managerial skills. FDI can increase economic growth and development of a country by creating employment, and by doing so, increasing economic activity that will lead to economic growth. South Africa is one of the economies that strive to attract more FDI inflows into the country to be able to improve its economy, and the country has adopted policies that drive the motive to attract FDI inflows. This study investigated the effect of FDI on sectoral growth over the period 1970–2014. The purpose was to find out where in the three key sectors of South Africa FDI is more significant. The review of theoretical and empirical literature on FDI revealed that FDI has a diverse effect on economic growth, both in developed and developing countries. Theoretical literature analysed the behaviour of multinational firms and the motive behind multinationals investing in foreign countries. According to Dunning (1993), firms have four motives to decide to produce abroad, namely natural resource-seeking, market-seeking, efficiency-seeking and strategic asset-seeking. Empirical studies on sectors show that FDI inflows affect different sectors in different ways, and that the agricultural sector does not usually gain from FDI inflows, whereas subsectors in the industry and services sector grow from receiving FDI inflows. Sectoral analysis revealed that the services sector receives more FDI inflows, when compared to the agriculture and industry sector. The study followed an econometric analysis technique to test the effect of FDI inflows on the agriculture, industry and services sectors. The augmented Dickey–Fuller and Phillips–Perron tests were used to test for unit root. Both tests revealed that variables were not stationary at level, but that they become stationary at first difference. Vector autoregressive (VAR) models were estimated, and four types of diagnostic tests were performed on them to check the fitness of the models. The tests showed that residuals of the estimated VARs were robust and well behaved. The Johansen cointegration test suggested there is cointegration and that there is a long-run relationship between variables. Following the existence of cointegration, the estimated Vector error correction model (VECM) results showed that FDI has a significant effect on the services and industry sector, but has a negative effect on the agricultural sector. Impulse response analysis results revealed the correct signs, and confirmed the VECM results. FDI inflows explain a small percentage of growth in agriculture and industry, but a sizable and significant percentage in the services sector. / Economics / M. Com. (Economics)

This research studies the relationships in Electric Energy Consumption, Carbon Dioxide Emission and Theil Index in Brazil. The period of analysis includes annual data from 1980 to 2011 in a total of 31 observations. The series presented order of integration equal one with the presence of cointegration thus to measure these influences we used a vector error correction model (VEC). By Function Impulse Response (FIR) and Variance Decomposition Analysis (ADV) we observed how each variable behaves to an abrupt change. To analyze the behavior of variables, methods of vector autoregressive (VAR) and residues control charts were used. The VAR modeling revealed that there is a significant interrelationship among the variables under study, thus showing that there is a short-term relationship between these variables. As for the residues control chart to individual measures, a problem in the original variables was avoided tha were the the autocorrelation, and showed that all variables had a period of instability and also enabled the identification of this period. The emission of carbon dioxide and Theil Index are determining factors in the explanation of environmental impacts as well as the development of the country. The variance decomposition indicates that the carbon dioxide emission is primarily responsible for mainly caused damage to the environment. / Esta pesquisa estudou as relações existentes no Consumo de Energia Elétrica, Emissão de Dióxido de Carbono e Índice de Theil no Brasil. O período de análise se refere a dados anuais de 1980 a 2011 perfazendo um total de 31 observações do Brasil. As séries apresentaram ordem de integração igual a um com a presença de cointegração, assim, para mensurar essas influências foi utilizado um modelo de Vetor de Correção de Erros (VEC). Por meio da Função Impulso Resposta (FIR) e Análise de Decomposição da Variância (ADV) foi possível verificar como cada variável se comporta a uma mudança abrupta. Para analisar o comportamento das variáveis, foram utilizadas as metodologias de vetores auto regressivos (VAR) e gráficos de controle de resíduos. Já a modelagem VAR revelou que há um inter-relacionamento significativo entre as variáveis em estudo, mostrando assim que há uma relação de curto prazo entre estas variáveis. Quanto aos gráficos de controle de medidas individuais aos resíduos, contornou-se um problema presente nas variáveis originais que era o de autocorrelação, e mostrou-se que todas as variáveis apresentaram um período de instabilidade o que também possibilitou a identificação deste período. A Emissão de Dióxido de Carbono e o Índice de Theil são fatores determinantes na explicação dos impactos ambientais, assim como no desenvolvimento do país. A decomposição da variância indica que a Emissão de Dióxido de Carbono é o principal responsável pelos danos causados principalmente ao meio ambiente.

Submitted by Karla Malafaia (karlamalafaia@gmail.com) on 2013-02-26T23:31:57Z No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) / Approved for entry into archive by Vera Lúcia Mourão (vera.mourao@fgv.br) on 2013-02-27T13:25:04Z (GMT) No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) / Made available in DSpace on 2013-02-27T13:29:38Z (GMT). No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) Previous issue date: 2013-01-29 / Este trabalho se propõe a testar e quantificar a importância do investimento de longo prazo, captado pela série de desembolsos da linha BNDES Finem, na produção industrial brasileira. Através dos modelos de causalidade de Granger e Função resposta ao impulso, podemos verificar as respostas acumuladas ao longo de três anos da linha Finem a choques positivos de um desvio padrão nas variáveis inflação, produção industrial, spread, e, da mesma forma um choque na variável Finem com resposta nas variáveis acima descritas. Além disso, é possível identificar a importância do BNDES como um ator anticíclico em períodos de crise como na economia brasileira. Como resultado, encontramos que apesar dos desembolsos Finem não Granger causarem a produção industrial brasileira, se testadas em conjunto com dados de inflação e a diferença entre a Selic e a TJLP rejeita-se a hipótese nula de não causalidade a 1% de significância. Já os testes de funções de resposta ao impulso indicam que a taxa de crescimento da produção industrial tem resposta positiva a um choque de desvio padrão nos desembolsos de Finem. Contudo, se testada em conjunto um choque no Finem apesar de impactar positivamente a produção industrial acaba pressionando a inflação. / This work is to test and quantify the importance of a long-term investment captured by the series of disbursements of BNDES Finem line in brazilian industrial production. Through Granger causality and impulse-response function, it was possible to check the Finem line accumulated answers along three years to positive shocks of a standard deviation on the variables inflation, industrial production, spread, and a shock on Finem variable with answer on the previous described variables. Furthermore, it's possible to identify the BNDES's importance as a countercyclical tool in crisis period as in brazilian economy. As a result, we found that despite causing the brazilian industrial production, if the no Granger Finem's disbursements are tested with inflation data and the difference between Selic and TJLP, the null hypothesis of no causality at 1% of significance is rejected. Yet, the tests of impulse-response function indicate that the industrial production growth rate has positive answer to a shock of standard deviation on Finem's disbursements. However, despite impacting the industrial production positevely, it pressures the inflation if it's tested with a shock on Finem.