896 resultados para Productivity analysis


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This paper examines the impact of innovation on the performance of US business service firms. We distinguish between different levels of innovation (new-to-market and new-to-firm) in our analysis, and allow explicitly for sample selection issues. Reflecting the literature, which highlights the importance of external interaction in service innovation, we pay particular attention to the role of external innovation linkages and their effect on business performance. We find that the presence of service innovation and its extent has a consistently positive effect on growth, but no effect on productivity. There is evidence that the growth effect of innovation can be attributed, at least in part, to the external linkages maintained by innovators in the process of innovation. External linkages have an overwhelmingly positive effect on (innovator) firm performance, regardless of whether innovation is measured as a discrete or continuous variable, and regardless of the level of innovation considered.

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We develop a taxonomy that relates foreign direct investment (FDI) motivation (technology- and cost-based) to its anticipated effects on host countries domestic productivity. We then empirically examine the effects of FDI into the United Kingdom on domestic productivity, and find that different types of FDI have markedly different productivity spillover effects, which are consistent with the conceptual analysis. The UK gains substantially only from inward FDI motivated by a strong technology-based ownership advantage. As theory predicts, inward FDI motivated by technology-sourcing considerations leads to no productivity spillovers.

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This paper presents differences in firm-level total factor productivity (TFP) across 22 manufacturing and 17 service industries in Germany over the period 1995–2004. It is an attempt to study whether and to what extent foreign multinational enterprises (MNEs) are more productive relative to German firms. As well as distinguishing between foreign and domestic firms, we also distinguish between German MNEs and domestic firms that do not have any foreign presence. Controlling for endogeneity through semi-parametric techniques, our findings indicate considerable heterogeneity in firm performance across types of firms. The foreign/domestic distinction is not as clear cut as has been suggested elsewhere; multinationality is important in explaining productivity differences rather than foreignness.

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By engaging in trade and foreign direct investment (FDI) with foreign partners, a country can access the R&D and related knowledge stocks of other countries (by accident or by design) and so benefit from those stocks of knowledge at a cost lower than that which would be incurred by developing the knowledge internally. This should lead to beneficial ‘spillover’ effects on the productivity of domestic firms. However, the literature on technology spillovers from trade and FDI is ambiguous in its findings. This may in part be because of the assumption in much of the work that trade and FDI flows are homogeneous in their determinants and thus in their effects. We develop a taxonomy of trade and FDI determinants based on R&D intensity and unit labour cost differentials, and test for the presence of spillovers from inward investment and imports on an extensive sample of UK manufacturing plants. We find that both trade and FDI have measurable spillover effects, but the size of these effects varies depending on the technological and labour cost differentials between the UK and its trading partners. There is therefore an identifiable link between the determinants and effects of trade and FDI which the previous literature has not explored. We also find that absorptive capacity matters for spillovers from FDI, but not from trade. Overall, these findings suggest that the productivity effects of FDI are largely restricted to plants with high absorptive capacity, while the productivity effects of imports occur largely among higher-technology plants regardless of their absorptive capacity.

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The use of Diagnosis Related Groups (DRG) as a mechanism for hospital financing is a currently debated topic in Portugal. The DRG system was scheduled to be initiated by the Health Ministry of Portugal on January 1, 1990 as an instrument for the allocation of public hospital budgets funded by the National Health Service (NHS), and as a method of payment for other third party payers (e.g., Public Employees (ADSE), private insurers, etc.). Based on experience from other countries such as the United States, it was expected that implementation of this system would result in more efficient hospital resource utilisation and a more equitable distribution of hospital budgets. However, in order to minimise the potentially adverse financial impact on hospitals, the Portuguese Health Ministry decided to gradually phase in the use of the DRG system for budget allocation by using blended hospitalspecific and national DRG casemix rates. Since implementation in 1990, the percentage of each hospitals budget based on hospital specific costs was to decrease, while the percentage based on DRG casemix was to increase. This was scheduled to continue until 1995 when the plan called for allocating yearly budgets on a 50% national and 50% hospitalspecific cost basis. While all other nonNHS third party payers are currently paying based on DRGs, the adoption of DRG casemix as a National Health Service budget setting tool has been slower than anticipated. There is now some argument in both the political and academic communities as to the appropriateness of DRGs as a budget setting criterion as well as to their impact on hospital efficiency in Portugal. This paper uses a twostage procedure to assess the impact of actual DRG payment on the productivity (through its components, i.e., technological change and technical efficiency change) of diagnostic technology in Portuguese hospitals during the years 1992–1994, using both parametric and nonparametric frontier models. We find evidence that the DRG payment system does appear to have had a positive impact on productivity and technical efficiency of some commonly employed diagnostic technologies in Portugal during this time span.

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This chapter provides the theoretical foundation and background on data envelopment analysis (DEA) method. We first introduce the basic DEA models. The balance of this chapter focuses on evidences showing DEA has been extensively applied for measuring efficiency and productivity of services including financial services (banking, insurance, securities, and fund management), professional services, health services, education services, environmental and public services, energy services, logistics, tourism, information technology, telecommunications, transport, distribution, audio-visual, media, entertainment, cultural and other business services. Finally, we provide information on the use of Performance Improvement Management Software (PIM-DEA). A free limited version of this software and downloading procedure is also included in this chapter.

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The literature on technology spillovers from trade and FDI is ambiguous in its findings. This may in part be because of the assumption in much of the work that trade and FDI flows are homogeneous in their determinants and thus in their effects. We develop a taxonomy of trade and FDI determinants based on R&D intensity and unit labour cost differentials, and test for the presence of spillovers from inward investment and imports on an extensive sample of UK manufacturing plants. We find that both trade and FDI have measurable spillover effects, but the sign and extent of these effects varies depending on the technological and factor cost differentials between the recipient and host economies. There is therefore an identifiable link between the determinants and effects of trade and FDI which the previous literature has not explored.

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In the wake of the global financial crisis, several macroeconomic contributions have highlighted the risks of excessive credit expansion. In particular, too much finance can have a negative impact on growth. We examine the microeconomic foundations of this argument, positing a non-monotonic relationship between leverage and firm-level productivity growth in the spirit of the trade-off theory of capital structure. A threshold regression model estimated on a sample of Central and Eastern European countries confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth. This estimate can provide guidance to firms and policy makers on identifying "excessive" leverage. We find similar non-monotonic relationships between leverage and proxies for firm value. Our results are a first step in bridging the gap between the literature on optimal capital structure and the wider macro literature on the finance-growth nexus. © 2012 Elsevier Ltd.

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The literature on technology spillovers from trade and FDI is ambiguous in its findings. This may in part be because of the assumption in much of the work that trade and FDI flows are homogeneous in their determinants and thus in their effects. We develop a taxonomy of trade and FDI determinants based on R&D intensity and unit labour cost differentials, and test for the presence of spillovers from inward investment and imports on an extensive sample of UK manufacturing plants. We find that both trade and FDI have measurable spillover effects, but the sign and extent of these effects varies depending on the technological and factor cost differentials between the recipient and host economies. There is therefore an identifiable link between the determinants and effects of trade and FDI which the previous literature has not explored.

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This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivitygrowth estimates derived from growthaccounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.