Much agricultural production in the Philippines is semi-subsistence in nature and most farms are small - even tiny - units operated by families. Most farms are too small for producers to internalise the costs of infrastructural development. Most investment in physical infrastructure (like irrigation), as well as in marketing networks, credit facilities and agricultural research is undertaken through public expenditures. In addition to fixed and long-term investments there are many government instruments - subsidies, taxes and market interventions - which serve public policy objectives by altering the relative profitability of production in different agricultural subsectors or regions. This thesis presents evidence that public policy towards agriculture has discriminated between agricultural producers in the provision of infrastructure, research and extension services, marketing support and credit programs. It will be argued that in aggregate terms, a useful criterion for distinguishing those producers relatively favoured by public programs is by their access to land of higher than average inherent productivity, and to irrigated land in particular. The concentration of investments for agricultural growth in areas already advantaged by superior land productivity has helped to widen existing differences in relative rates of technicalprogress, and perhaps to turn the direction of technical change biases in the more favoured areas towards the more intensive use of farm inputs whose prices have been subsidised by the government.
An unhappy prediction of the AK endogenous growth model, in which knowledge is regarded only as capital, is that a long run positive growth is not compatible with a possible convergence between various countries. Moreover, it cannot give an account for the possibility of maintaining a positive and optimal growth in an economy where accumulation of capital requires the use of a non-renewable resource. Indeed, the only way of counterbalancing the exhaustion of natural resources and of maintaining a positive growth in the long run consists in involving technicalprogress. However, as much as the accumulation of capital remains the only engine of new knowledge in this model, the acceleration of technicalprogress would lead an increased exhaustion of the natural resource, which can only compromise the growth prospects in the long term, in other words to aggravate the problem which technicalprogress has to lighten. More fundamentally, focusing on the role of the global supply of savings in growth, the AK model neglects the demand and, more specifically, the role of entrepreneurs, institutions and economic policies that will enhance productivity by promoting the incentives of entrepreneurs to innovation.
driven by an endogenous reaction to an improvement in the eﬃciency of a closely-linked good, either as a substitute or complement, in this case vehicles. This shows the importance of modelling energy-intensive household services in general, and private transport in particular, as the output of a number of inputs. Moreover, in determining the overall impact of technicalprogress in vehicles on the demand for fuel, it is fundamental to take into account changes in the quantity demanded of private trans- port. Such changes in the demand for the energy-intensive service gen- erate an additional increase or reduction in the derived demand for the input goods. Whilst there are general equilibrium e ﬀ ects on household fuel consumption, these are dominated by the impacts identiﬁed in partial equilibrium. Using general equilibrium simulation to incorporate en- dogenous variation in intermediate fuel use suggests that these reinforce changes in household fuel consumption.
Since the submission of the scenario specification report to the funding authority two meetings have taken place: one focused on a review of technicalprogress in the project and was attended by members of General Dynamics UK Ltd., the other was a DTC Theme Meeting organized by Martin Ferry who is head of the DIF DTC theme entitled ‘Situational Awareness and Human Factors’. Detailed notes regarding the latter meeting were distributed to project stakeholders in the form of a document entitled ‘DTC Theme Meeting’ (reference: DTC/Notes-28-10-2004#1). In terms of the former technical review meeting a number of issues were raised by the reviewers including decisions surrounding the choice of scenario and relevant contact with other DTC projects. In terms of the latter concern the reviewers were keen to emphasize that contact with Project 7.6 and projects within the Agents and Architectures theme could be relevant for subsequent development efforts. Other contacts of potential value include Nick Beswick (in Andy Tilbrook's team at General Dynamics) and Panos Louvieris at the University of Surrey. These contacts were mentioned in relation to the visualization technologies that could be exploited in the relation to the current project. The DTC review team also commented on the choice of location for the scenario as detailed in the scenario specification document. A suggestion was made to switch the scenario location from Afghanistan to Cambodia because humanitarian operations are currently winding up in Cambodia and a greater number of SMEs may therefore be available with relatively recent operational experience. There are three core concerns we have in relation to this suggestion and which we believe vitiate the recommended alteration of the scenario:
Abstract: The paper examines the economic performance of a large number of African countries using an international comparable data set and the latest technique for analysis. The paper focuses on growth in total factor productivity and its decomposition into technical change and efficiency change components. The analysis is undertaken using the data envelopment analysis (DEA). The present study uses data of 16 countries over the period 1970–2001. It was found that, globally, during that period, total factor productivity has experienced a positive evolution in sampled countries. This good performance of the agricultural sector was due to good progress in technical efficiency rather than technicalprogress. The region suffered a regression in productivity in the 1970s, and made some progress during the 1980s and 1990s. The study also highlights the fact that technical change has been the main constraint of achievement of high levels of total factor productivity during the reference period in sub-Saharan Africa. Contrariwise, in Maghreb coun- tries, technological change has been the main driving force of produc- tivity growth. Finally, the results indicate that institutional factors as well as agro-ecological factors are important determinants of agricultural productivity growth.
increasing returns to scale term, leading to a greater rate of output growth than can be explained by simply adding up input growth and technicalprogress. However, in order to implement this growth decomposition, we generally need to have some knowledge of the marginal cost prices in the two periods, π 0 and π 1 . Of course, if all of the ad valorem markups are the same in each period or there is only one output, then lnQ T * ( π 0 , π 1 ,y 0 ,y 1 )
From the above refinements, we got results different from Cassetti(2003). An increase in the saving rate does not make the growth rate decrease, but the utilization decrease. This resulted from our formalization that the growth rate is determined by factors of technicalprogress and class conflicts in steady state. In Cassetti(2003), the growth rate decreases in the case as a canonical Kaleckian model because of no labor constraint in it. In addition to that, we got the result that an increase in the rate of labor productivity exerts a positive impact on growth. In Cassetti(2003), the effect is ambiguous because it also has the contrary effect, the slowdown in workers’ aspirations caused by the fall in the employment rate of growth. Our model has does not have that effect in steady state. The direct impact of productivity parameters on the productivity growth also dominates the indirect one through an increase in profit rate.
In the early 1980’s, the strength of patent rights gradually increased in the US. For example, the Ginarte-Park index of patent rights increased from 3.83 in 1975 to 4.88 in 1995. 1 After this patent reform, private R&D expenditure as a percentage of gross domestic product (GDP) in the US increased from 1.2% in 1980 to an average of 2.5% in recent time. Cross-country empirical studies, such as Varsakelis (2001), Kanwar and Evenson (2003) and Park (2005), employ the Ginarte-Park index to examine the effects of patent strength on R&D and innovation, and they generally find a positive and significant effect. 2 As for the effects of technicalprogress on the volatility of economic growth, empirical studies, such as Tang (2002) and Tang et al. (2008), generally find a negative effect; in other words, technicalprogress reduces growth volatility.
Over long periods technological or technical change is the most important determinant of productivity growth. Because of the labour-intensive nature of many construction activities, which limits the possibilities of mechanization, the pace of technicalprogress in construction in recent decades appears slower than it was in earlier periods and slower than it was in other sectors. The number of site person-hours needed to build a house in the mid-1940s totalled 2,400, but by the mid-1960s had fallen to 950, a decrease of 4.5 per cent per year. These large improvements were attributable to changes in production methods in the area of excavation, basement construction, wall framing, roofing, siding, plumbing and heating, interiors, and windows/cabinetry/doors, all of which significantly reduced on-site labour requirements. In contrast, between the mid - 1960s and mid-1980s there was little further technicalprogress in production methods, with the result that there has been little additional decline in on -site labour requirements.
Changes in the factor prices have important impacts on characteristics of investments, such as the expected lifetime, the factor intensity and the factor productivity of new capital goods. Considering both changes in factor prices as well as technicalprogress, different effects arise at either high substitutability or low substi- tutability in production. It can be shown that for a production function close to the Cobb-Douglas case, higher interest rates and technicalprogress will decrease the expected lifetime, the capital intensity and pro- ductivity, while the reversed outcome occurs at lower substitutability between factor inputs.
To go a step further, notice that these two phenomena go hand-in-hand and are both relevant in explaining the standstill of labour productivity. Capital accumulation is important because, as is well known at least since Solow (1957), most of technicalprogress is embodied in new capital goods. In fact, what the data about capital deepening show is that in the Italian economy during the last 15 years there occurred a shift towards less capital intensive techniques, thus reducing the eﬃciency of employment. This shift and the lack of adoption of new technologies, especially of the ICT variety, have been favoured by the particular structure of the Italian specialization, skewed towards the traditional sectors with low technological content and less skilled workers. That is, not only the investment pace decreased in the last 15 years but it was also redirected toward traditional sectors rather than the innovative ones. Such a change in capital accumulation mix explains why both TFP and capital intensity rates decreased at the same time.
It follows from the first reason that production relations alone do not determine wage and profit rates. This indeterminacy can be removed by introducing demand. For instance, wage and profit rates in steady states are determined by the saving and consumption rates. One degree of indeterminacy may remain, for employment is not necessarily determined. Some of the marginal relations derived from production functions can hold for comparisons between steady states, which means they are mathematical relations, not relations of cause and effect. And they cannot be used to describe change over time outside steady states, for wages and profits change and cause the plant and machinery that are fixed capital and relative prices to change, too. Such changes are too complicated to describe or for households and firms to calculate optimal expenditure and production, and, as is evident, real economies are not in equilibrium, for expectations are not all realised. Intertemporal general equilibrium models can show, with some assumptions that seem general and others impossible, that there is equilibrium with full employment apart from steady states, but these models are just mathematical existence theorems unrelated to reality. Their very generality and abstractness obscure the extent to which the assumptions can allow for the complications of reality. It is not known, for instance, to what extent their assumptions can accommodate R&D and the technicalprogress it results in. These models are also illogical in the sense that they require perfect foresight, though technicalprogress is inherently unpredictable, certainly over the long run.
In these terms, capture theory extends to processes concerned with legitimation of risk assessment standards supposed to protect public health when regulatory agencies cede organizational control of those processes to industry. The evidence suggests that capture theory provides a more plausible social scienti ﬁ c understanding of the development of carcinogenicity-testing standards than a theory of regulatory learning from techno-scienti ﬁ c progress. Speci ﬁ cally, the GEM-tests ’ validation process did not seek maximum scienti ﬁ c knowledge about their validity, but instead was an exercise, accommodated by regulators, in establishing whether the tests were consistent with industry interests by prioritizing avoidance of false positives. Similarly, our ﬁ ndings suggest that industry framing of GEM-tests ’ use around commercial preoccupations with costs and maximization of product success was tolerated by regulators longer than would be expected if regulatory agencies had been merely on a scienti ﬁ c learning curve to improve public-health protective carcinogenic risk assessment.
To estimate total factor productivity in agriculture we use the Mamquist Index (Färe et al., 1994), a non-parametric methodology that uses data envelopment analysis (DEA) methods to construct a piece-wise linear production frontier for each country and year in the sample. This methodology has been used extensively for measuring agricultural productivity, as it offers some advantages (Coelli et al., 2005). This approach: i) does not require price information, ii) does not assume that all countries are efficient, iii) does not assume a behavioral objective function such as cost minimization or revenue/profit maximization, and iv) allows for TFP decomposition into technical change, efficiency change and scale change.
miRNAs are non-coding RNAs that play a regulatory role in expression of genes and are associated with diseases. Quantitatively measuring expression levels of miRNAs can help in understanding the mechani- sms of human diseases and discovering new drug targets. There are three major methods that have been used to measure the expression levels of miRNAs: real- time reverse transcription PCR (qRT-PCR), microar- ray, and the newly introduced next-generation sequen- cing (NGS). NGS is not only suitable for profiling of known miRNAs as qRT-PCR and microarray can do too but it also is able to detect unknown miRNAs which the other two methods are incapable of doing. Pro- filing of miRNAs by NGS has progressed rapidly and is a promising field for applications in drug develo- pment. This paper reviews the technical advancement of NGS for profiling miRNAs, including comparative analyses between different platforms and software packages for analyzing NGS data. Examples and future perspectives of applications of NGS profiling miRNAs in drug development will be discussed. Keywords: miRNAs; Next-Generation Sequencing; Expression; Data Analysis; Drug Development