This diploma paper discusses the importance of implementation of capital into the system national accounts. The purpose of this work is an estimation of capital services for real data of the Czech Republic. Conducted its own calculation is first such comprehensive estimate of the capital services, which was made. The diploma paper is divided into three parts. In the first part there is a explaination of concept of capital services and the methods of estimation and possible ways of calculating the necessary data. In the second part there is already done my own calculations of estimate of capital services used the methodology recommended by the OECD, but subject to certain adjustments, which are better suited to national conditions. Due to the volume of data all the calculations are listed in the Annex. In the text work is illustrative example of one sector of economic activity and the economy as a whole. The last section deals with experimental estimates of impact of capital services on macroeconomic aggregates, particularly gross domestic product. Other possibilities obtained an estimate of capital services, it is possible to estimate multi-factor productivity. Capital services can be used to express the input of capital.

The objective of this thesis is to compare performances of companies operating in regulated industries.The selected industries are natural gas and electricity distribution, water and sewerage systems operation and railway maintenance. Two methodological approaches are used throughout the thesis, each in its own part. The first one focuses on the financial analysis, while the other one uses the total factor productivity analysis. The latter is based on physical units typical for their respective sectors. As the conclusion of this thesis both approaches and the results of individual companies are compared.

The aims of the dissertation thesis are to provide the comprehensive economic-statistical viewpoint on the issue of estimating labour productivity and total factor productivity; to evaluate the quality of the available data sources and to test the usage of new inputs to the production function in the Czech Republic. The first chapter provides a theoretical basis for subsequent estimates of labour productivity and total factor productivity. The second and third chapters concentrate on a detailed definition of data sources and definitions of input and output indicators in the production function. Moreover, the second chapter introduces new approaches to the estimation of the input indicators to the production function (labour services, capital services). The fourth chapter deals with estimates of labour productivity. Specifically, the relationship of labour productivity and educational structures are examined as well as estimates for regions of the Czech Republic and estimates for non-market industry that do not allow the use of the traditional approach. The fifth chapter focuses on possible particularization and improvement of the estimation of total factor productivity using new input variables. The same chapter further compares the index number approach and econometric approach including the test of constant returns to scale. The estimation of total factor productivity in individual Czech regions is also part of the chapter.

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This paper investigates the impact of the increased off-shoring in business and manufacturing to Central and Eastern Europe (CEE). Since the off-shoring process is a relatively new activity, there is no precise definition of how to measure its direct impact on a country’s economy. Thus the study is dedicated to identify the main economic factors associated with off-shoring and to examine their impact on the economic growth. The study has used a dataset on economic characteristics for 9 CEE countries (Estonia, Latvia, Lithuania, Poland, Czech Republic, Hungary, Romania, Slovenia, Croatia) during the time period of 2000 - 2008. After applying fixed and random effects econometric model to the panel data for 9 countries, empirical results showed that FDI inflows that enter the country with offshoring processes have a positive influence on the GDP of those countries. Additionally, exports of manufactured products and ICT services are also shown to have a positive influence on GDP. At the same time, indigenous investments and private consumption do have a stronger impact on economic growth compared to foreign direct investments and exports, respectively.

Civil wars, insecurity, and ethnic disputes have imposed a high human and economic toll in Africa. In this dissertation, I examine the destructive impacts of war on agricultural productivity growth across the continent. Poor agricultural sector performance is more likely to be present around or during times of conflict. Using a panel of 51 countries from 1962-2009 I find that war impedes agricultural productivity growth. But a decline in productivity growth is not associated with the onset of civil war. Results show that low per capita income, stagnant economic growth, a large population, and lack of political freedom correspond to higher incidence of war, while conflict and lack of rainfall are associated with low agricultural productivity growth. I find that armed conflict reduces agricultural productivity growth by 0.76 percent per year and a major armed conflict reduces TFP growth by 1.16 percent. The incidence of a major armed conflict is associated with an efficiency decline in the year by 1.24 percent, substantial setback, for more than three-quarters of countries. This dissertation extends the discussion from productivity and efficiency analysis to the inclusion of the spatial dimension by applying exploratory and confirmatory spatial data analysis and capitalizing on successful spatial techniques and analytical tools proven in geospatial science. The exploratory spatial data analysis provides evidence of spatial autocorrelation in agricultural TFP growth rates in Africa. The results of hot spot analysis reveal that Algeria, Tunisia, Libya in the northern region and Nigeria and Benin in the western region constitute hot spots of agricultural performance and the cold spot, which includes areas of meager productivity, Rwanda and Burundi in central Africa. Africa suffers substantial losses in agricultural productivity when certain countries experience major armed conflict. The dissertation shows that a war may reduce productivity in a given country, but its real effects are larger because it impacts surrounding countries. Overall African TFP declined by 0.0572 percent per year as a result of conflict in Sudan. A war in the Democratic Republic of Congo caused African TFP growth to decline by 0.0285 percent per year.

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A agropecuária brasileira tem crescido nas últimas décadas e os ganhos de produtividade tem sido importante neste bom desempenho do setor. O presente trabalho tem dois objetivos principais. O primeiro deles foi mensurar o crescimento desta produtividade total dos fatores na agropecuária brasileira estadual, decompondo o crescimento da PTF em progresso tecnológico e eficiência técnica. O segundo objetivo foi analisar o efeito do crescimento da PTF da agropecuária brasileira sobre os preços agrícolas, no Brasil, de 1970 a 2006. O crescimento desta produtividade foi mensurado a partir dos insumos terra, trabalho e capital na função de produção translog sob orientação do produto, a partir do método de Fronteira Estocástica de Produção e do índice de produtividade de Malmquist. Para avaliar o efeito do crescimento da PTF sobre os preços agrícolas foi construído o índice de preços agrícolas utilizando-se o Índice de preços de Laspeyres para estimar o vetor autoregressivo em painel (panel- VAR), acrescentando as variáveis produtividade total dos fatores (PTF), salário rural, financiamento agrícola e renda per capita domiciliar. Além disso, foi aplicado o teste de causalidade, no sentido de Granger, e estimada a função impulso resposta. A base de dados utilizada foi, obtida do Censo Agropecuário, a nível estadual, para os anos de 1970, 1975, 1980, 1985, 1995 e 2006. Os resultados indicaram que a taxa de crescimento da PTF foi crescente no Brasil e nos estados, sendo que, na maior parte das vezes, é explicada pelo progresso tecnológico, positivo e crescente para todos os estados. A eficiência técnica variou ao longo dos anos, apresentado taxas de crescimento médias positivas para a maioria dos estados. Em média, os estados estiveram situados abaixo da fronteira de produção da agropecuária brasileira. São Paulo foi o estado com maior nível de eficiência técnica. Embora a taxa de crescimento médio anual tenha sido positiva ao longo do período analisado, a eficiência reduziu para todos os estados analisados em 2006. Da análise dos efeitos do crescimento da PTF sobre os preços agrícolas, a PTF tem causalidade, no sentido de Granger, sobre os preços agrícolas. Na função impulso resposta, o choque inicial na variável PTF reduziu os preços nos primeiros anos. Assim, o crescimento da PTF do setor agropecuário contribuiu para o aumento da oferta de produtos, reduzindo os preços agrícolas. A maior disponibilidade de alimentos e, com a redução dos preços dos alimentos, os consumidores, principalmente os de renda mais baixa puderam ter maior acesso aos alimentos. / The Brazilian agriculture has grown in recent decades and productivity gains have been important in this good performance of the sector. This work had two main objectives. The first one was measure the growth of this total factor productivity in agriculture by the Brazilian\'s states, decomposing TFP growth by technological progress, technical efficiency and economies of scale. The second objective was to analyze the effect of TFP growth of Brazilian agriculture on agricultural prices. The growth in productivity was measured from the inputs like labor, gross and capital in the translog production function, from the Stochastic Frontier Analysis and of the outputoriented Malmquist productivity index. To analyze the effect of TFP growth on agricultural prices was constructed an index of agricultural prices through the Laspeyres price index to estimate the vector autoregressive panel (panel-VAR) and establish the relationships between TFP, rural wages, agricultural finance and income per capita household. The Granger causality test and the impulse response function were used to the data panel. The database used obtained from the Agricultural Census, at the state level for the years 1970, 1975, 1980, 1985, 1995 and 2006. The results showed that the growth rate of TFP has been growing in Brazil and in the states, and technological progress explained most of the growth being positive and growing for all states. Technical efficiency varied over the years, presented positive average growth rates for most states. The states were located below the production frontier of Brazilian agriculture and São Paulo was the state with the highest level of technical efficiency. Although the average annual growth rate has been increasing over the period analyzed, the efficiency decreased to all state analyzed in 2006. The results also showed that TFP growth has causality in the sense of Granger, on agricultural prices. In the impulse response function, the initial shock in TFP decreased prices in the early years. Thus, TFP growth of the agricultural sector contributed to the increased supply of agricultural products, reducing agricultural prices. The greater availability of food and with reducing food prices, consumers, especially those from lower income might had greater access to food.

Faculty research productivity studies typically focus on the scholarly performance of the individual researcher, although environmental and organizational conditions that are largely outside of the researcher’s control can significantly impact that performance. From an institutional effectiveness perspective, it is imperative for the higher education administrators and leaders who share the responsibility of managing and supporting their university’s research enterprise to understand how the institutional environment itself impacts the productivity of its research community. In this sequential mixed methods study, a quantitative framework was tested for assessing institutional effectiveness in research administration based on the assertion that this concept can be measured indirectly, at the departmental level, based on the calculation of a program’s residual scholarly output. This is the difference between the actual amount of scholarly output a program produces compared to the predicted amount of scholarly output that its resources suggest it is capable of producing. The assumption is that the institution’s effectiveness in supporting research is largely reflected by the extent to which a program over- or under-produces scholarship based on its level of resources. The residual scholarly output was calculated for each Ph.D.-granting biomedical engineering program in doctoral universities with a Carnegie classification of “highest research activity” for the period of 2014 through 2016. A sampling of those programs that achieved among the highest and lowest residual productivity levels then became the subject of a qualitative inquiry where researchers and administrators were interviewed with two goals in mind. The more ostensive goal was to reveal what factors, characteristics, resources, and conditions distinguish under- and over-producing programs for the purpose of informing best and worst practices in research administration. Equally important, the second goal was to determine if the quantitative framework was actually successful in distinguishing institutional effectiveness in supporting research. The study concludes that the quantitative framework proved to be a successful method for detecting institutional effectiveness in supporting research, and that the primary distinguishing characteristic between high and low-functioning environments was how well programs were able to reduce the general administrative burdens that researchers face, particularly in grant management and the operation of research laboratories.

<p>In this dissertation I study substantially the effects of disembodied technical change on the total factor productivity and inputs demand in U.S. Apparel industry during 1958-1996. A time series input-output data set over the sector employs to estimate an error corrected model of a four-factor transcendental logarithmic cost function. The empirical results indicate technical impact on the total factor productivity at the rate of 9% on average. Technical progress has in addition a biased effect on factor augmenting in the sector.</p>