23 resultados para Multifactor productivity


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O objetivo desse trabalho é medir e analisar a produtividade da indústria extrativa brasileira como um todo e seus subsetores. Primeiramente foi feita a estimação da produtividade multifatorial utilizando o método clássico proposto por Robert Solow de onde se verificou uma queda na produtividade do setor no período entre 1997 e 2009. Posteriormente foi feita uma nova estimação dessa produtividade que corrige as mudanças na qualidade dos minerais extraídos. Observou-se que a queda na produtividade, no período analisado, foi ainda mais acentuada.

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This paper examines structural changes that occur in the total factor productivity (TFP) within countries. It is possible that some episodes of high economic growth or economic decline are associated with permanent productivity shocks, therefore, this research has two objectives. The Örst one is to estimate the structural changes present in TFP for a sample of 81 countries between 1950(60) and 2000. The second one is to identify, whenever possible, episodes in the political and economic history of these countries that may account for the structural breaks in question. The results suggest that about 85% of the TFP time-series present at least one structural break, moreover, at least half the structural changes can be attributed to internal factors, such as independence or a newly adopted constitution, and about 30% to external shocks, such as oil shock or shocks in international interest rates. The majority of the estimated breaks are downwards, indicating that after a break the TFP tends to decrease, implying that institutional rearrangements, external shocks, or internal shocks may be costly and from which it is very di¢ cult to recover.

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This paper investigates cross-country productivity convergence among Mercosur members plus associates (Chile and Bolivia) and Peru, during the period 1960-1999. The testing strategy is based on the definitions of time-series convergence by Bernard and Durlauf (1995), and applies sequentially the multivariate unit root tests proposed by Sarno and Taylor (1998), Flôres, Preumont and Szafarz (1995) and Breuer, Mc Nown and Wallace (1999). The last two tests allow to identify the countries that converge. Our results show evidence of convergence among the four Mercosur countries, using either Argentina or Brazil as benchmark. Weaker evidence of convergence is also found with Bolivia. The results point out that monetary union among the Southern Cone economies, though a far objective, is not without sense.

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This Paper Tackles the Problem of Aggregate Tfp Measurement Using Stochastic Frontier Analysis (Sfa). Data From Penn World Table 6.1 are Used to Estimate a World Production Frontier For a Sample of 75 Countries Over a Long Period (1950-2000) Taking Advantage of the Model Offered By Battese and Coelli (1992). We Also Apply the Decomposition of Tfp Suggested By Bauer (1990) and Kumbhakar (2000) to a Smaller Sample of 36 Countries Over the Period 1970-2000 in Order to Evaluate the Effects of Changes in Efficiency (Technical and Allocative), Scale Effects and Technical Change. This Allows Us to Analyze the Role of Productivity and Its Components in Economic Growth of Developed and Developing Nations in Addition to the Importance of Factor Accumulation. Although not Much Explored in the Study of Economic Growth, Frontier Techniques Seem to Be of Particular Interest For That Purpose Since the Separation of Efficiency Effects and Technical Change Has a Direct Interpretation in Terms of the Catch-Up Debate. The Estimated Technical Efficiency Scores Reveal the Efficiency of Nations in the Production of Non Tradable Goods Since the Gdp Series Used is Ppp-Adjusted. We Also Provide a Second Set of Efficiency Scores Corrected in Order to Reveal Efficiency in the Production of Tradable Goods and Rank Them. When Compared to the Rankings of Productivity Indexes Offered By Non-Frontier Studies of Hall and Jones (1996) and Islam (1995) Our Ranking Shows a Somewhat More Intuitive Order of Countries. Rankings of the Technical Change and Scale Effects Components of Tfp Change are Also Very Intuitive. We Also Show That Productivity is Responsible For Virtually All the Differences of Performance Between Developed and Developing Countries in Terms of Rates of Growth of Income Per Worker. More Important, We Find That Changes in Allocative Efficiency Play a Crucial Role in Explaining Differences in the Productivity of Developed and Developing Nations, Even Larger Than the One Played By the Technology Gap

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Corruption is a phenomenon that plagues many countries and, mostly, walks hand in hand with inefficient institutional structures, which reduce the effectiveness of public and private investment. In countries with widespread corruption, for each monetary unit invested, a sizable share is wasted, implying less investment. Corruption can also be a burden on a nation’s wealth and economic growth, by driving away new investment and creating uncertainties regarding private and social rights. Thus, corruption can affect not only factors productivity, but also their accumulation, with detrimental consequences on a society’s social development. This article aims to analyze and measure the influence of corruption on a country’s wealth. It is implicitly admitted that the degree of institutional development has an adverse effect on the productivity of production factors, which implies in reduced per capita income. It is assumed that the level of wealth and economic growth depends on domestic savings, foster technological progress and a proper educational system. Corruption, within this framework, is not unlike an additional cost, which stifles the “effectiveness” of the investment. This article first discusses the key theories evaluating corruption’s economic consequences. Later, it analyzes the relation between institutional development, factor productivity and per capita income, based on the neoclassical approach to economic growth. Finally, it brings some empirical evidence regarding the effects of corruption on factor productivity, in a sample of 81 countries studied in 1998. The chief conclusion is that corruption negatively affects the wealth of a nation by reducing capital productivity, or its effectiveness.

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This article analyses the relationship between infrastructure and total factor productivity (TFP) in the four major Latin American economies: Argentina, Brazil, Chile and Mexico. We hypothesise that an increase in infrastructure has an indirect effect on long-term economic growth by raising productivity. To assess this theory, we use the traditional Johansen methodology for testing the cointegration between TFP and physical measures of infrastructure stock, such as energy, roads, and telephones. We then apply the Lütkepohl, Saikkonen and Trenkler Test, which considers a possible level shift in the series and has better small sample properties, to the same data set and compare the two tests. The results do not support a robust long-term relationship between the series; we do not find strong evidence that cuts in infrastructure investment in some Latin American countries were the main reason for the fall in TFP during the 1970s and 1980s.

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We develop and calibrate a model where differences in factor endowments lead countries to trade intermediate goods, and gains from trade reflect in total factor productivity. We perform several output and growth decompositions, to assess the impact that barriers to trade, as well as changes in terms of trade, have on measured TFP. We find that for very poor economies gains from trade are large, in some cases representing a doubling of GDP. Also, that an improvement in the terms of trade - by allowing the use of a better mix of intermediate inputs in the production process - translates into productivity growth.

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Due to widespread government intervention and import-substitution industrialization, there has been a general presumption that Latin America has been much less productive than the leading economies in the last decades. In this paper, however, we show that until the late seventies Latin America had high total factor productivity (TFP) levels relative to the US and other regions. It is only after the late seventies that we observe a fast decrease of relative TFP in Latin America. Results are robust to the use of diferent methodologies and data sources.

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Although the subject of a large number of studies, the debate on the links between trade reform and productivity growth is still unresolved and most studies at the micro level have not been able to establish a relationship between the two phenomena. Brazil provides a natural experiment to study this issue that is seldom available: it was one of the closest economies in the world until 1988, when trade reform was launched, and intra-industry data are available on an annual basis before, during and after liberalization. Using a panel of industry sectors this paper tests and measures the impact of trade reform on productivity growth. Results confirm the association between the former and the latter and show that the magnitude of the impact of tariff reduction on the growth rates of TFP and output per worker was substantial. Our data reveal large and widespread productivity improvement, so that the estimations in this paper are an indication that liberalization had an important effect on industrial performance in the country. Cross-sectional differences in protection are also investigated.

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This article presents a group of exercises of level and growth decomposition of output per worker using cross-country data from 1960 to 2000. It is shown that at least until 1975 factors of production (capital and education) were the main source of output dispersion across economies and that productivity variance was considerably smaller than in late years. Only after this date the prominence of productivity started to show up in the data, as the majority of the literature has found. The growth decomposition exercises showed that the reversal of relative importance of productivity vis-a-vis factors is explained by the very good (bad) performance of productivity of fast (slow) growing economies. Although growth in the period, on average, is mostly due to factors accumulation, its variance is explained by productivity.

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This article investigates the impact of trade protection on the evolution of labor productivity and total factor productivity (TFP) of the Brazilian manufacturing sector. An annual panel-dataset of 16 industries for the years 1985 through 1997, a period that includes a major trade liberalization, was used. The regressions reported here are robust to openness indicator (nominal tari®s and e®ective protection rate were used), control variables and time period and suggest that barriers to trade negatively a®ects productivity growth at industry level: those sectors with lower barriers experienced higher growth. We were also able to link the observed increase of industry productivity growth after 1991 to the widespread reduction on exective protection experienced in the country in the nineties.

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We develop and calibrate a model where diferences in factor en-dowments lead countries to trade di¤erent goods, so that the existence of international trade changes the sectorial composition of output from one country to another. Gains from trade re ect in total factor productivity. We perform a development decomposition, to assess the impact of trade and barriers to trade on measured TFP. In our sample, the median size of that e¤ect is about 6.5% of output, with a median of 17% and a maximum of 89%. Also, the model predicts that changes in the terms of trade cause a change of productivity, and that efect has an average elasticity of 0.71.

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We investigate the role of sectorial differences in labor productivity and the process of structural transformation (reallocation of labor across sectors) in accounting for the time path of aggregate productivity across six Latin American countries (Brazil, Chile, Argentina, Colombia, Mexico and Venezuela) from 1950 to 2003. We used a general equilibrium model with three sectors (agriculture, industry and services) calibrated to those six economies. The model is used to compare the trajectory of productivity in each sector of activity with that of the United States and it impact on aggregate productivity.While in Brazil and Argentina, the Service Sector was responsible for reversing the process of catch up in productivity that occurred until the 1980s, in others, like Colombia, Mexico and Venezuela, low productivity growth of the three sectors explain their poor performance.