838 resultados para total factor productivity growth (TFPG)


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Principal Topic: Entrepreneurship is key to employment, innovation and growth (Acs & Mueller, 2008), and as such, has been the subject of tremendous research in both the economic and management literatures since Solow (1957), Schumpeter (1934, 1943), and Penrose (1959). The presence of entrepreneurs in the economy is a key factor in the success or failure of countries to grow (Audretsch and Thurik, 2001; Dejardin, 2001). Further studies focus on the conditions of existence of entrepreneurship, influential factors invoked are historical, cultural, social, institutional, or purely economic (North, 1997; Thurik 1996 & 1999). Of particular interest, beyond the reasons behind the existence of entrepreneurship, are entrepreneurial survival and good ''performance'' factors. Using cross-country firm data analysis, La Porta & Schleifer (2008) confirm that informal micro-businesses provide on average half of all economic activity in developing countries. They find that these are utterly unproductive compared to formal firms, and conclude that the informal sector serves as a social security net ''keep[ing] millions of people alive, but disappearing over time'' (abstract). Robison (1986), Hill (1996, 1997) posit that the Indonesian government under Suharto always pointed to the lack of indigenous entrepreneurship , thereby motivating the nationalisation of all industries. Furthermore, the same literature also points to the fact that small businesses were mostly left out of development programmes because they were supposed less productive and having less productivity potential than larger ones. Vial (2008) challenges this view and shows that small firms represent about 70% of firms, 12% of total output, but contribute to 25% of total factor productivity growth on average over the period 1975-94 in the industrial sector (Table 10, p.316). ---------- Methodology/Key Propositions: A review of the empirical literature points at several under-researched questions. Firstly, we assess whether there is, evidence of small family-business entrepreneurship in Indonesia. Secondly, we examine and present the characteristics of these enterprises, along with the size of the sector, and its dynamics. Thirdly, we study whether these enterprises underperform compared to the larger scale industrial sector, as it is suggested in the literature. We reconsider performance measurements for micro-family owned businesses. We suggest that, beside productivity measures, performance could be appraised by both the survival probability of the firm, and by the amount of household assets formation. We compare micro-family-owned and larger industrial firms' survival probabilities after the 1997 crisis, their capital productivity, then compare household assets of families involved in business with those who do not. Finally, we examine human and social capital as moderators of enterprises' performance. In particular, we assess whether a higher level of education and community participation have an effect on the likelihood of running a family business, and whether it has an impact on households' assets level. We use the IFLS database compiled and published by RAND Corporation. The data is a rich community, households, and individuals panel dataset in four waves: 1993, 1997, 2000, 2007. We now focus on the waves 1997 and 2000 in order to investigate entrepreneurship behaviours in turbulent times, i.e. the 1997 Asian crisis. We use aggregate individual data, and focus on households data in order to study micro-family-owned businesses. IFLS data covers roughly 7,600 households in 1997 and over 10,000 households in 2000, with about 95% of 1997 households re-interviewed in 2000. Households were interviewed in 13 of the 27 provinces as defined before 2001. Those 13 provinces were targeted because accounting for 83% of the population. A full description of the data is provided in Frankenberg and Thomas (2000), and Strauss et alii (2004). We deflate all monetary values in Rupiah with the World Development Indicators Consumer Price Index base 100 in 2000. ---------- Results and Implications: We find that in Indonesia, entrepreneurship is widespread and two thirds of households hold one or several family businesses. In rural areas, in 2000, 75% of households run one or several businesses. The proportion of households holding both a farm and a non farm business is higher in rural areas, underlining the reliance of rural households on self-employment, especially after the crisis. Those businesses come in various sizes from very small to larger ones. The median business production value represents less than the annual national minimum wage. Figures show that at least 75% of farm businesses produce less than the annual minimum wage, with non farm businesses being more numerous to produce the minimum wage. However, this is only one part of the story, as production is not the only ''output'' or effect of the business. We show that the survival rate of those businesses ranks between 70 and 82% after the 1997 crisis, which contrasts with the 67% survival rate for the formal industrial sector (Ter Wengel & Rodriguez, 2006). Micro Family Owned Businesses might be relatively small in terms of production, they also provide stability in times of crisis. For those businesses that provide business assets figures, we show that capital productivity is fairly high, with rates that are ten times higher for non farm businesses. Results show that households running a business have larger family assets, and households are better off in urban areas. We run a panel logit model in order to test the effect of human and social capital on the existence of businesses among households. We find that non farm businesses are more likely to appear in households with higher human and social capital situated in urban areas. Farm businesses are more likely to appear in lower human capital and rural contexts, while still being supported by community participation. The estimation of our panel data model confirm that households are more likely to have higher family assets if situated in urban area, the higher the education level, the larger the assets, and running a business increase the likelihood of having larger assets. This is especially true for non farm businesses that have a clearly larger and more significant effect on assets than farm businesses. Finally, social capital in the form of community participation also has a positive effect on assets. Those results confirm the existence of a strong entrepreneurship culture among Indonesian households. Investigating survival rates also shows that those businesses are quite stable, even in the face of a violent crisis such as the 1997 one, and as a result, can provide a safety net. Finally, considering household assets - the returns of business to the household, rather than profit or productivity - the returns of business to itself, shows that households running a business are better off. While we demonstrate that uman and social capital are key to business existence, survival and performance, those results open avenues for further research regarding the factors that could hamper growth of those businesses in terms of output and employment.

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This paper uses a stochastic translog cost frontier model and a panel data of five key mining industries in Australia over 1968-1969 to 1994-1995 to investigate the sources of output growth and the effects of cost inefficiency on total factor productivity (TFP) growth. The results indicate that mining output growth was largely input-driven rather than productivity-driven. Although there were some gains from technological progress and economics of scale in production, cost inefficiency which barely exceeded 1.1% since the mid-1970s in the mining industries was the main factor causing low TFP growth. (C) 2002 Elsevier Science B.V. All rights reserved.

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Geary and Stark find that Ireland’s post-Famine per capita GDP converged with British levels, and that this convergence was largely due to total factor productivity growth rather than mass emigration. In this article, new long-run measurements of human capital accumulation in Ireland are devised in order to facilitate a better assessment of sources of this productivity growth, including the relative contribution of men and women. This is done by exploiting the frequency at which age data heap at round ages, widely interpreted as an indicator of a population’s basic numeracy skills. Because Földvári, van Leeuwen, and van Leeuwen-Li find that gender-specific trends in this measure derived from census returns are biased by who is reporting and recording the age information, any computed numeracy trends are corrected using data from prison and workhouse registers, sources in which women ostensibly self-reported their age. The findings show that rural Irish women born early in the nineteenth century had substantially lower levels of human capital than uncorrected census data would otherwise suggest. These results are large in magnitude and thus economically significant. The speed at which women converged is consistent with Geary and Stark’s interpretation of Irish economic history; Ireland probably graduated to Europe’s club of advanced economies thanks in part to rapid advances in female human capital.

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China’s gradual approach to economic transition has resulted in sustained high growth. However, in recent years Chinese economists have increasingly referred to the growth pattern as “extensive,” generated mainly through the expansion of inputs. Our investigation of the Chinese economy during the reform period finds that reform measures often resulted in one-time level effects on total factor productivity (TFP). China now needs to adjust its reform program toward sustained increases in productivity. Market and ownership reforms, and open door policies have improved the conditions under which Chinese firms operate, but further institutional reforms are required to consolidate China’s move to a full-fledged market economy.

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In order to establish the concentrations of glucose, cholesterol, total protein and growth factor insulin-like type I (IGF-I) in the follicular fluid, 26 Murrah breed river buffaloes, between 45 and 70 days postpartum, empty, multiparous, with average live weight of 675 +/- 56 kg and average body condition of 3.5 points on a scale of 1-5, were used in this study. The fluid was collected from dominant follicles with diameters between 8 and 12 mm by OPU, and was not taken into account the stage of the estrous cycle. Using this technique, the wave of follicular development was synchronized six days prior to collection. Biochemical analysis was performed to glucose and cholesterol through the enzymatic colorimetric method using commercial kit glicose CHOLESTEROL GOD-PAP and CHOD-PAP (Kovalent), respectively. Determination of total protein was carried out by using total protein commercial kit (Kovalent) Biuret method, and the readings were performed using absorption spectrophotometry with visible light. Concentration of IGF-I was measured by Radioimmunoassay (RIA) technique using commercial IRMA Kit IGF-I (INMUNOTECH). Descriptive statistics were developed using the PROC MEANS procedure of SAS (2009). Concentration of glucose (4.0 +/- 0.75 mmol / L-1) and IGF-I (340 +/- 129.83 ng / mL (-1)) were higher than those reported by other authors in river buffaloes and cows, respectively. However, cholesterol levels (0.51 +/- 0.12 mmol / L (-1)) and total protein (58.4 +/- 4.43 g / L (-1)) behaved inferior to other studies in same species. The results indicated that there is relationship among the nutritional aspects, diameter of follicles aspirated and productive period in the concentration of biochemical indicators.

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In the long term, productivity and especially productivity growth are necessary conditions for the survival of a farm. This paper focuses on the technology choice of a dairy farm, i.e. the choice between a conventional and an automatic milking system. Its aim is to reveal the extent to which economic rationality explains investing in new technology. The adoption of robotics is further linked to farm productivity to show how capital-intensive technology has affected the overall productivity of milk production. The empirical analysis applies a probit model and an extended Cobb-Douglas-type production function to a Finnish farm-level dataset for the years 2000–10. The results show that very few economic factors on a dairy farm or in its economic environment can be identified to affect the switch to automatic milking. Existing machinery capital and investment allowances are among the significant factors. The results also indicate that the probability of investing in robotics responds elastically to a change in investment aids: an increase of 1% in aid would generate an increase of 2% in the probability of investing. Despite the presence of non-economic incentives, the switch to robotic milking is proven to promote productivity development on dairy farms. No productivity growth is observed on farms that keep conventional milking systems, whereas farms with robotic milking have a growth rate of 8.1% per year. The mean rate for farms that switch to robotic milking is 7.0% per year. The results show great progress in productivity growth, with the average of the sector at around 2% per year during the past two decades. In conclusion, investments in new technology as well as investment aids to boost investments are needed in low-productivity areas where investments in new technology still have great potential to increase productivity, and thus profitability and competitiveness, in the long run.

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Abstract There is considerable evidence that high-growth firms (HGFs) contribute significantly to employment and economic growth. However, the literature so far does not adequately explore the link between HGFs and productivity. This paper investigates the empirical link between total factor productivity (TFP) growth and HGFs, defined in terms of sales growth, in the United Kingdom over the period 2001-2010, by examining two related research questions. Firstly, does higher TFP growth lead to HGF status and secondly, does HGF experience help firms achieve faster TFP growth? Our findings reveal that firms in both the manufacturing and services sectors are more likely to become HGFs when they exhibit higher TFP growth. In addition, firms that have had HGF experience tend to enjoy faster TFP growth following the high-growth episodes. Policy implications are drawn based on the self-reinforcing process of the high-growth phenomenon that is revealed by our results. © 2014 The Author(s).

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The current study was motivated by statements made by the Economic Strategies Committee that Singapore’s recent productivity levels in services were well below countries such as the US, Japan and Hong Kong. Massive employment of foreign workers was cited as the reason for poor productivity levels. To shed more light on Singapore’s falling productivity, a nonparametric Malmquist productivity index was employed which provides measures of productivity change, technical change and efficiency change. The findings reveal that growth in total factor productivity was attributed to technical change with no improvement in efficiency change. Such results suggest that gains from TFP were input-driven rather than from a ‘best-practice’ approach such as improvements in operations or better resource allocation.

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This paper uses an aggregate quantity space to decompose the temporal changes in nitrogen use efficiency and cumulative exergy use efficiency into changes of Moorsteen–Bjurek (MB) Total Factor Productivity (TFP) changes and changes in the aggregate nitrogen and cumulative exergy contents. Changes in productivity can be broken into technical change and changes in various efficiency measures such as technical efficiency, scale efficiency and residual mix efficiency. Changes in the aggregate nitrogen and cumulative exergy contents can be driven by changes in the quality of inputs and outputs and changes in the mixes of inputs and outputs. Also with cumulative exergy content analysis, changes in the efficiency in input production can increase or decrease the cumulative exergy transformity of agricultural production. The empirical study in 30 member countries of the Organisation for Economic Co-operation Development from 1990 to 2003 yielded some important findings. The production technology progressed but there were reductions in technical efficiency, scale efficiency and residual mix efficiency levels. This result suggests that the production frontier had shifted up but there existed lags in the responses of member countries to the technological change. Given TFP growth, improvements in nutrient use efficiency and cumulative exergy use efficiency were counteracted by reductions in the changes of the aggregate nitrogen contents ratio and aggregate cumulative exergy contents ratio. The empirical results also confirmed that different combinations of inputs and outputs as well as the quality of inputs and outputs could have more influence on the growth of nutrient and cumulative exergy use efficiency than factors that had driven productivity change. Keywords: Nutrient use efficiency; Cumulative exergy use efficiency; Thermodynamic efficiency change; Productivity growth; OECD agriculture; Sustainability

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The current study was motivated by statements made by the Economic Strategies Committee that Singapore’s recent productivity levels in services were well below countries such as the US, Japan and Hong Kong. Massive employment of foreign workers was cited as the reason for poor productivity levels. To shed more light on Singapore’s falling productivity, a nonparametric Malmquist productivity index was employed which provides measures of productivity change, technical change and efficiency change. The findings reveal that growth in Total Factor Productivity (TFP) was attributed to technical change with no improvement in efficiency change. Such results suggest that gains from TFP were input-driven rather than from a ‘best-practice’ approach such as improvements in operations or better resource allocation.

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This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity change and Simar and Wilson’s (J Econ, 136:31–64, 2007) bootstrapped truncated regression approach. In the first stage, the nonparametric data envelopment analysis is used to measure technical efficiency. To quantify the economic drivers underlying inefficiencies, the second stage employs a bootstrapped truncated regression whereby bias-corrected efficiency estimates are regressed against explanatory variables. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Most industries were technically inefficient throughout the period except for ‘Pharmaceutical Products’. Sources of efficiency were attributed to quality of worker and flexible work arrangements while incessant use of foreign workers lowered efficiency.

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This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity (TFP) change and Simar and Wilson’s (2007) bootstrapped truncated regression approach which first derives bias-corrected efficiency estimates before being regressed against explanatory variables to help quantify sources of inefficiencies. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Sources of efficiency were attributed to quality of worker and flexible work arrangements while the use of foreign workers lowered efficiency.

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Total factor productivity plays an important role in the growth of the Indian economy. Using state-level data from 1993 to 2005 that were recently made available, we find widespread regional variation in productivity changes. In the years immediately following economic liberalization, productivity growth improved technical efficiency; however, in subsequent years, productivity growth was propelled by technological progress. We find a tendency toward convergence with regard to productivity growth among states; however, the states that were technically efficient when the economic reforms were instituted remained innovative in later years.

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In this study we use region-level panel data on rice production in Vietnam to investigate total factor productivity (TFP) growth in the period since reunification in 1975. Two significant reforms were introduced during this period, one in 1981 allowing farmers to keep part of their produce, and another in 1987 providing improved land tenure. We measure TFP growth using two modified forms of the standard Malmquist data envelopment analysis (DEA) method, which we have named the Three-year-window (TYW) and the Full Cumulative (FC) methods. We have developed these methods to deal with degrees of freedom limitations. Our empirical results indicate strong average TFP growth of between 3.3 and 3.5 per cent per annum, with the fastest growth observed in the period following the first reform. Our results support the assertion that incentive related issues have played a large role in the decline and subsequent resurgence of Vietnamese agriculture.