902 resultados para indirect production function


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El presente proyecto tiene como objeto identificar cuáles son los conceptos de salud, enfermedad, epidemiología y riesgo aplicables a las empresas del sector de extracción de petróleo y gas natural en Colombia. Dado, el bajo nivel de predicción de los análisis financieros tradicionales y su insuficiencia, en términos de inversión y toma de decisiones a largo plazo, además de no considerar variables como el riesgo y las expectativas de futuro, surge la necesidad de abordar diferentes perspectivas y modelos integradores. Esta apreciación es pertinente dentro del sector de extracción de petróleo y gas natural, debido a la creciente inversión extranjera que ha reportado, US$2.862 millones en el 2010, cifra mayor a diez veces su valor en el año 2003. Así pues, se podrían desarrollar modelos multi-dimensional, con base en los conceptos de salud financiera, epidemiológicos y estadísticos. El termino de salud y su adopción en el sector empresarial, resulta útil y mantiene una coherencia conceptual, evidenciando una presencia de diferentes subsistemas o factores interactuantes e interconectados. Es necesario mencionar también, que un modelo multidimensional (multi-stage) debe tener en cuenta el riesgo y el análisis epidemiológico ha demostrado ser útil al momento de determinarlo e integrarlo en el sistema junto a otros conceptos, como la razón de riesgo y riesgo relativo. Esto se analizará mediante un estudio teórico-conceptual, que complementa un estudio previo, para contribuir al proyecto de finanzas corporativas de la línea de investigación en Gerencia.

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Measuring labor's share of an economy's aggregate income seems straightforward, at least in principle. Count up wage and salary income, along with the value of benefits provided to employees, and divide it by total income. However, one fundamental concept of labor's share in macroeconomic theory is not the amount of aggregate income paid out to labor. Rather, it is the share of aggregate production that is attributable to "raw" units of labor. Or, otherwise stated, it is the share of aggregate income that would have been paid to laborers if they had no accumulated stocks of human capital.1 This share corresponds to an aggregate production function parameter: the elasticity of output with respect to physical (i.e. non-augmented or raw) units of labor (Robert Solow, 1957). In this paper we estimate annual raw labor’s share for the US, 1949 to 1996.

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We present an Overlapping Generations Model with two final goods: tradable goods are produced with a standard Cobb-Douglas production function and non-tradable goods are produced with linear production function where the only factor is labor. We maintain the fundamental assumption of factor mobility between sectors so model is consistent with the Balassa-Samuelson hypothesis. Given the general equilibrium structure of our model we can examine the effect of the saving rate on migration and non-tradable relative prices. Under this setting, we find that the elderly have incentives to migrate from economies where productivity is high to economies with low productivity because of the lower cost of living. In more general terms the elderly migration is likely to go from rich to poor countries. We also find that, for poor countries, the elderly migration has a positive effect in wages and capital accumulation.

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The common assumptions that labor income share does not change over time or across countries and that factor income shares are equal to the elasticity of output with respect to factors have had important implications for economic theory. However, there are various theoretical reasons why the elasticity of output with respect to reproducible factors should be correlated with the stage of development. In particular, the behavior of international trade and capital flows and the existence of factor saving innovations imply such a correlation. If this correlation exists and if factor income shares are equal to the elasticity of output with respect to factors then the labor income share must be negatively correlated with the stage of development. We propose an explanation for why labor income share has no correlation with income per capita: the existence of a labor intensive sector which produces non tradable goods.

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We propose a one-good model where technological change is factor saving and costly. We consider a production function with two reproducible factors: physical capital and human capital, and one not reproducible factor. The main predictions of the model are the following: (a) The elasticity of output with respect to the reproducible factors depends on the factor abundance of the economies. (b) The income share of reproducible factors increases with the stage of development. (c) Depending on the initial conditions, in some economies the production function converges to AK, while in other economies long-run growth is zero. (d) The share of human factors (raw labor and human capital) converges to a positive number lower than one. Along the transition it may decrease, increase or remain constant.

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We use annual data on capital’s share and relative factor prices from 35 US industries from 1960 to 2005 to test the induced innovation hypothesis. We derive, from a production function framework, testable implications for the effect of contemporaneous and lagged factor price ratios on capital’s share of production. The predicted effect is positive or negative depending on the elasticity of substitution between labor and capital. From panel regressions, the estimated effect of the contemporaneous factor price ratio implies an elasticity of substitution that is less than unity, consistent with the consensus from the literature. Based on this, our negative estimated effects for lagged price ratios are both statistically significant and consistent with the induced innovation hypothesis.

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We present an endogenous growth model where innovations are factor saving. Technologies can be changed paying a cost and technological change takes place only if the benefits are larger than the costs. Since the gains derived from factor saving innovations depend on factor abundance, biased innovations respond to changes in factors supply. Therefore, as an economy becomes more capital abundant agents try to use capital more intensively. Consequently, (a) the elasticity of output with respect to reproducible factors depends on the capital abundance of the economy and (b) the income share of reproducible factors increases as the economy grows. Another insight of the model is that in some economies the production function converges to an AK in the long run, while in others long-run growth is zero

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Recent evidence show that factor shares, if properly measured, are far from constant. Moreover, the shares of natural resources and raw labor seem to be negatively correlated with income per capita while the share of human and physical capital is positively correlated with income per capita. Now, if factor shares are not constant then (i) growth accounting exercises rely on a false assumption and (ii) there is a measurement problem. The effect that change s in factor shares ha ve on output depend on the relative abundance of factors and, fo r this reason, it is necessary to have correct measures. We propose an empiri cal methodology to solve the measurement issue and estimate TFP growth.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, insecticide-producing 'Bt' varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing insecticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology using a three-year farm-level dataset on smallholder cotton production in Makhathini flats, Kwa-Zulu Natal, South Africa. Stochastic dominance and stochastic production function estimation methods are used to examine the risk properties of the two technologies. Results indicate that Bt technology increases output risk by being most effective when crop growth conditions are good, but being less effective when conditions are less favourable. However, in spite of its risk increasing effect, the mean output performance of Bt cotton is good enough to make it preferable to conventional technology even for risk-averse smallholders.

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Using a choice experiment survey this study examines the UK public's willingness to pay to conserve insect pollinators in relation to the levels of two pollination service benefits: maintaining local produce supplies and the aesthetic benefits of diverse wildflower assemblages. Willingness to pay was estimated using a Bayesian mixed logit with two contrasting controls for attribute non-attendance, exclusion and shrinkage. The results suggest that the UK public have an extremely strong preference to avoid a status quo scenario where pollinator populations and pollination services decline. Total willingness to pay was high and did not significantly vary between the two pollination service outputs, producing a conservative total of £379M over a sample of the tax-paying population of the UK, equivalent to £13.4 per UK taxpayer. Using a basic production function approach, the marginal value of pollination services to these attributes is also extrapolated. The study discusses the implications of these findings and directions for related future research into the non-market value of pollination and other ecosystem services.

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Higher productivity of multinational firms and exporters has been widely documented in the literature, but the sources of this heterogeneity are still a black box. Using an original dataset on Italian firms, we show that higher total factor productivity of international firms can be to some extent explained by higher R&D intensity and managerial capabilities. However, our results suggest that heterogeneity is more in the slope than in the constant of the production function. In particular, allowing international firms to have different return to labour and capital inputs, we are able to account for their entire productivity premium. This has implications for both labour and capital market reforms.

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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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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.