901 resultados para GDP elasticity
Resumo:
This thesis examines the impact of foreign direct investment (FDI) on Vietnamese economy based on Partial Adjustment Model and time series data from 1976 to 2004. FDI is shown to have not only short run but also long run effect on gross domestic product (GDP) of Vietnam. However, elasticity of GDP with respect to FDI is small and it will take many years to fully manifest itself. The impact of trade openness on GDP has also been examined and it is shown to be stronger than that of FDI. The paper offers a number of explanations and discusses briefly suggestions in order to increase the contribution of FDI to Vietnam’s economic development.
Resumo:
Gross domestic product (GDP) is generally considered as the most important index and comprehensive measure of the size of economy. This paper investigates empirically the relationship between transport infrastructure (focus on highways) and GDP growth based on a production function approach. The physical stocks of transport infrastructure were used instead of monetary data to measure public capital together with several other variables (labor and private capital) that were hypothesized to affect economic growth. Then we explore a number of subsequent studies that use panel data covering the period between 1992 and 2004. An investigation was done to compare developed countries and developing countries. Results indicate that physical units are positively and significantly related to economic growth. Furthermore there was an interesting finding that the output elasticity with respect to physical units for developed countries is higher than developing countries.
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Due to health problems and the negative externalities associated with cigarette consumption, many governments try to discourage cigarette consumption by increasing its price through taxation. However, cigarette, like the other addictive goods, is viewed as that it is not sensitive to demand rules and the market forces. This study analyses the effect of price increase on cigarette consumption. We used Swedish time series data from 1970 to 2010. Our results reveal that though cigarette is addictive substance its demand is sensitive to changes in the price. Estimates from this study indicate short-run price-elasticity of -0.29 and the long run price elasticity of -0.47.
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This study aims to investigate the relation between foreign direct investment (FDI) and per capita gross domestic product (GDP) in Pakistan. The study is based on a basic Cobb-Douglas production function. Population over age 15 to 64 is used as a proxy for labor in the investigation. The other variables used are gross capital formation, technological gap and a dummy variable measuring among other things political stability. We find positive correlation between GDP per capita in Pakistan and two variables, FDI and population over age 15 to 64. The GDP gap (gap between GDP of USA and GDP of Pakistan) is negatively correlated with GDP per capita as expected. Political instability, economic crisis, wars and polarization in the society have no significant impact on GDP per capita in the long run.
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This paper examines the relationships among per capita CO2 emissions, per capita GDP and international trade based on panel data sets spanning the period 1960-2008: one for 150 countries and the others for sub-samples comprising OECD and Non-OECD economies. We apply panel unit root and cointegration tests, and estimate a panel error correction model. The results from the error correction model suggest that there are long-term relationships between the variables for the whole sample and for Non-OECD countries. Finally, Granger causality tests show that there is bi-directional short-term causality between per capita GDP and international trade for the whole sample and between per capita GDP and CO2 emissions for OECD countries
Resumo:
The presence of deterministic or stochastic trend in U.S. GDP has been a continuing debate in the literature of macroeconomics. Ben-David and Papell (1995) found evindence in favor of trend stationarity using the secular sample of Maddison (1995). More recently, Murray and Nelson (2000) correctly criticized this nding arguing that the Maddison data are plagued with additive outliers (AO), which bias inference towards stationarity. Hence, they propose to set the secular sample aside and conduct inference using a more homogeneous but shorter time-span post-WWII sample. In this paper we re-visit the Maddison data by employing a test that is robust against AO s. Our results suggest the U.S. GDP can be modeled as a trend stationary process.
Resumo:
This paper has several original contributions. The first is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series- all coincident with GDP from a business-cycle dating point of view. Based on these results, we finally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.
Resumo:
Este trabalho tem por objetivo estimar um modelo empírico para relacionar os gastos em publicidade com a receita das firmas, de forma a servir como ferramenta de tomada de decisão, para isso vamos fazer um estudo de caso da indústria de telecomunicações. A Indústria de comunicação (publicidade) no Brasil, segundo dados do IBGE de 2008, é responsável por 4% do PIB, gerando receitas da ordem 115 bilhões de reais. Com 113 mil empresas que geram 711 mil empregos, ocupam 866 mil pessoas e pagam 11,8 bilhões em salários e encargos. No entanto, a maioria dos gestores de marketing declara não ter instrumentos para medir o impacto de suas ações no resultado das empresas. O modelo empírico será estimado tendo como base dados mensais dos serviços de ligações de longa distância nacional da Embratel para o período de janeiro de 2009 até dezembro de 2011. As informações quase sempre não disponíveis, só puderam ser usadas devido ao compromisso de confidencialidade. A partir de técnicas de cointegração, foi calculada a elasticidade de longo prazo da receita em relação aos gastos com publicidade e ao preço, assim com as respectivas velocidades de ajustamento aos desvios de curto prazo. Os resultados sugerem que a receita responde positivamente às variações dos gastos em publicidade, embora o percentual seja relativamente baixo, através do teorema de Dorfman-Steiner conseguimos indicar que o ponto ótimo da relação entre gastos com publicidade e a receita seria de aproximadamente 20%, respeitadas as limitações do modelo.
Resumo:
This paper has several original contributions. The rst is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we nally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.
Resumo:
This paper constructs an indicator of Brazilian GDP at the monthly ftequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle were explicitly modeled within nonlinear ftameworks. In particular, a Markov switching dynarnic factor model was used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict ali recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined. The estimated indicator displays a better in-sample and out-of-sample predictive performance in forecasting growth rates of real GDP, compared to a linear autoregressive model for GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.
Resumo:
This paper estimates the elasticity of substitution of an aggregate production function. The estimating equation is derived from the steady state of a neoclassical growth model. The data comes from the PWT in which different countries face different relative prices of the investment good and exhibit different investment-output ratios. Then, using this variation we estimate the elasticity of substitution. The novelty of our approach is that we use dynamic panel data techniques, which allow us to distinguish between the short and the long run elasticity and handle a host of econometric and substantive issues. In particular we accommodate the possibility that different countries have different total factor productivities and other country specific effects and that such effects are correlated with the regressors. We also accommodate the possibility that the regressors are correlated with the error terms and that shocks to regressors are manifested in future periods. Taking all this into account our estimation resuIts suggest that the Iong run eIasticity of substitution is 0.7, which is Iower than the eIasticity that had been used in previous macro-deveIopment exercises. We show that this lower eIasticity reinforces the power of the neoclassical mo deI to expIain income differences across countries as coming from differential distortions.
Resumo:
This paper has several original contributions. The rst is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we nally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil- the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, whichmay not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.
Resumo:
The first contribution of this paper is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). The second contribution, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), is to propose and test a myriad of inter-polation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we finally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil - the Brazilian Economic Activity Index - (IBC-Br). We found that our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, which may not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. The third contribution is to illustrate, in a nowcasting and forecasting exercise, the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.
Resumo:
A madeira roliça possui grande emprego nas construções civis, desempenhando a função de vigas, colunas, fundações, postes para distribuição de energia elétrica, entre outras, apresentando a vantagem de não ser processada, como é o caso da madeira serrada. O projeto envolvendo elementos roliços requer, além de outras variáveis estruturais, o conhecimento do módulo de elasticidade. No Brasil, os documentos normativos que tratam da determinação das propriedades de rigidez e resistência para peças roliças de madeira estão em vigência há mais de vinte anos sem revisão técnica. A madeira roliça, por geralmente possuir eixo com curvatura não nula, pode apresentar, segundo a posição da peça no ensaio de flexão, valores diferentes do módulo de elasticidade. Este trabalho tem como objetivo analisara influência da posição de peças roliças de madeira de Eucalyptus grandis na determinação do módulo de elasticidade na flexão. O ensaio de flexão utilizado é o de três pontos, sendo cada peça avaliada em duas posições distintas, definidas mediante o giro da seção transversal em torno do eixo. Os resultados encontrados indicam a necessidade do ensaio de flexão em, pelo menos, duas posições distintas da peça.