Práce vymezuje problematiku strukturálních fondů, přičemž důraz je kladen na rozvoj vědy a výzkumu. Součástí práce je přehled a komparace unijních politik upravujících tuto oblast a analýza dopadů operačních programů na rozvoj vědy a výzkumu v Rakousku a v České republice za finanční rámec 2000 - 2006.

In 2003 national heads of African states, including Zambia, met in Maputo and pledged to increase financial resources to the agriculture sector, up to 10 % of their national budgets, in order to meet growth targets. Given the need to increase investments in agriculture, it follows that impact assessment studies have become handy as funding agencies demand better accountability and empirical justification for further investment. However, experts have reasoned that the quantity of resources is as important as the quality of spending in that, if resources are allocated efficiently, more could be achieved with the same level of resources. The lack of an effective strategy and basis upon which investments in agriculture crop research ought to be prioritised in order to improve agricultural productivity is the main concern in Zambia. This study sought to illustrate the use of the Dynamic Research Evaluation for Management (DREAM) model to assess the economic returns of investing in agriculture technologies and to set priorities for crop-based research activities in Zambia. The study hypothesised that the financial outlay allocated to agricultural crop research is not efficiently allocated so as to achieve the nation’s agricultural production potential, and that agricultural crop research investment influences the distribution of welfare effects on producers and consumers. The DREAM model is conceptually based on the economic surplus theory and is designed for research priority setting and ex ante evaluations. It computes the net present value (NPV) of benefits for both producers and consumers as a result of investing in agriculture technology. The findings from this study reveal that investment in agriculture crop research in Zambia is worthwhile as positive net present values were obtained for all crops under consideration in this study. Maize research gives the highest return to both large-scale and smallholder producers. Maize also yielded the highest returns for consumers in Zambia. In order of priority, maize is followed by soya bean, groundnuts, cotton, millet, sunflower and sorghum. In spite of this, the order of priority in terms of financial expenditure on crop research is maize, cotton, sorghum, soya bean, groundnuts, sunflower and millet. Therefore, the allocation of financial resources towards crop research is not efficient for all crops except maize since some crops such as sorghum receiving high financial expenditure in research did not necessarily generate high returns. This is because the Government still conducts the bulk of research in Zambia, and as such, other social objectives such as equity and food security considerations play a major role in determining investment patterns. The study further establishes that the choice of crop research expenditure influences the distribution of welfare benefits on different producer groups; and that smallholder farmers in Central, Eastern and Southern province are among the group that received the highest proportion of benefits even for crops such as maize for which financial resources were efficiently allocated. Therefore, the efficiency objective may not necessarily leave smallholder farmers worse off as long as they have access to complementary infrastructure and institutions for agriculture production and marketing. As such the study recommends that the Government, private sector and other development partners must focus on raising agriculture productivity by expanding investments in crop science-based technologies; and also recommends re-allocation of financial resources between crops in favour of crops with high returns because this benefits both large scale and smallholder farmers. This must be accompanied by further investment in complementary infrastructure and good governance. Copyright / Dissertation (MScAgric)--University of Pretoria, 2010. / Agricultural Economics, Extension and Rural Development / unrestricted

Purpose Various studies suggested that family ownership plays a significant role in R&D investment considering family-owned businesses. This thesis specifically explores sibling ownership and how it influences R&D Investment in their company. Moreover, various factors have been highlighted and explored extensively to understand what makes the difference between sibling owners and sole owners when it comes to their behaviors whether to pursue and invest in R&D for the betterment of the company. Method This paper adopted qualitative research as a method. Data was collected from 5 cases which consisted of sibling owners and sole owners to understand the differences between 2 types. In this multiple case study, two respondent took part in each case. Semi-structured interviews were carried out to have an in-depth understanding of the cases. Furthermore, the analysis of these data was done using the SEWi scale which provided us the three dimensions to scrutinize the impact on R&D investment by sibling owners and compare it with sole owners. Conclusion Using the theoretical lenses, the sibling ownership presents a unique attitude as of any other family ownership. To have a more broader approach, the comparison between a sole owner and sibling owner derived many different factors to take up R&D Investments. It shows that sibling owner does not always initiate investment for the company to prosper but they consider other family members involvement for investing. R&D investments are taking part in the sibling ownership by keeping the family wealth in mind. This tends to provide evidence that sibling owner is careful in investment for R&D. Family values and family unity in sibling owned business create an immense impact on the decision making for the investment. Considering the decision making regarding R&D investment, sibling owner believe that they have ease to make a decision when the family is involved whereas sole owner finds difficulty in taking such decisions, especially under uncertainty. The following observations from our research provided the idea that sibling owner initiative to invest in R&D is not only restricted to the company growth perspective but also the involvement of various family dimensions.

京都大学 / 0048 / 新制・課程博士 / 博士(経済学) / 甲第20784号 / 経博第556号 / 新制||経||282(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 矢野 誠, 教授 島本 哲朗, 教授 新後閑 禎 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

Institutions are considered a fundamental determinant of economic growth. And agriculture is the key sector for poverty reduction and sustainable economic growth in low and middle-income countries. The vital role of agriculture would not materialize without sustained agricultural productivity growth driven by public investments in agricultural Research and Development (R&D). The objective of the thesis is threefold: (i) to measure the effect of institutions on agricultural productivity and on public agricultural R&D investments in low and middle incomes countries, (ii) to estimate the impact of public R&D investment on agricultural productivity, and (iii) to test the hypothesis that agricultural R&D spending would differ across countries at different stages of economic development (i.e., examine the role of per capita GDP in determining agricultural R&D spending).Agricultural productivity is measured by yield (cereal yield); institutions are measured by four indicators: protection of property rights, impartial public administration, judicial independence, and legal enforcement of contracts; agricultural R&D is represented by public investments in R&D. Data were collected from the World Bank, the FRASER Institute, and the Agricultural Science and Technology Indicators (ASTI) over the period of 2000 to 2011 and in 49 low-and middle-income countries (25 from sub-Saharan Africa, 11 from LAC, and 13 from Asia). Panel data with fixed effects models were estimated to address the three objectives. The multiple linear regression analysis reveals the protection of property rights and legal enforcement of contracts have a substantial but opposite impact on agricultural productivity (cereal yield) across low-and middle-income countries. The same result suggests that impartial public administration affect positively public agricultural R&D investment while property rights, judicial independence, and legal enforcement of contracts have no significant implications on public agricultural R&D investment. The analysis also indicates that agricultural R&D investment positively impacts cereal yield across low-and middle-income countries. The same analysis carried out in the three regions has shown that the four institution indicators have different effects on agricultural productivity (cereal yield) and public agricultural R&D investment. In addition, the analysis suggests that public agricultural R&D investment significantly impacts agricultural productivity in Asia and the LAC regions but not in sub-Saharan Africa. Furthermore, the result confirms that agricultural R&D spending differs across countries at different stages of economic development.

Firms’ research and development (R&D) efforts are known to generate spillover effects on other firms’ outcomes, e.g., innovation and productivity. Policy recommendations that ignore spillover effects may not be optimal from a social perspective whence the importance of accounting for spillover effects. Quantifying R&D spillover effects typically requires a spatial matrix that characterises the structure of interaction between firms. In practice, the spatial matrix is often unknown due to factors that include multiplicity of forms of connectivity and unclear guidance from economic theory. Estimates can be biased if the spatial matrix is misspecified, and they can also be sensitive to the choice of spatial matrix. This dissertation develops robust techniques that estimate the spatial matrix alongside other parameters from data using a two-pronged approach: (1) model elements of the spatial matrix using spatial covariates (e.g., geographic and product market proximity) and a parameter vector of finite length and (2) estimate the spatial matrix as a set of parameters from panel data. Approaches (1) and (2) address two identification challenges - uncertainty over relevant forms of connectivity and high-dimensionality of the design matrix - in single-index models. In this three-chapter dissertation, the first approach is applied in the first and third chapters, while the second approach is applied in the third chapter. Chapter 1 proposes a parsimonious approach to estimating the spatial matrix and parameters from panel data when the spatial matrix is partly or fully unknown. By controlling for several forms of connectivity between firms, the approach is made robust to misspecification of the spatial matrix. Also, the flexibility of the approach allows data to determine the degrees of sparsity and asymmetry of the spatial matrix. The chapter establishes consistency and asymptotic normality of the MLE under conditional independence and conditional strong-mixing assumptions on the outcome variable. The empirical results confirm positive spillover and private effects of R&D on firm innovation. There is evidence of time-variation and asymmetry in the interaction structure between firms. Geographic proximity and product market proximity are confirmed as relevant forms of connectivity between firms. Moreover, connectivity between firms is not limited to often-assumed notions of proximity; it is also linked to past R&D and patenting behaviour of firms. Single-index models suffer non-identification due to rank deficiency when the design matrix is high-dimensional. Chapter 2 proposes an estimator that projects a high-dimensional parameter vector into a reduced consistently estimable one. This estimator generalises the assumption of sparsity which is required for shrinkage methods such as the Lasso, and it applies even if the high-dimensional parameter vector’s support is bounded away from zero. Monte Carlo simulations demonstrate high approximating ability, improved precision, and reduced bias of the estimator. The estimator is used to estimate the network structure between firms in order to quantify the spillover effects of R&D on productivity using panel data. The empirical results show that firms on average generate positive R&D spillovers on firm productivity. The spatial autoregressive (SAR) model has wide applicability in economics and social networks. It is used to estimate, for example, equilibrium and peer effects models. The SAR model, like other spatial econometric models, is not immune to challenges associated with misspecification or uncertainty over the spatial matrix. Chapter 3 applies the approach developed in Chapter 1 to estimate the spatial matrix in the SAR model with autoregressive disturbances in a parsimonious yet flexible way using GMM. The asymptotic properties of the GMM estimator are established, and Monte Carlo simulations show good small sample performance. / Economics

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No / This paper investigates the dynamics of R&D and capital investment using a large sample of US firms during the period 2002–2016. A partial adjustment approach is employed with a specific focus on the impact of the financial crisis on target adjustment speed. Evidence suggests that firms have a target in both types of investment and adjust to it at varying speeds. Specifically, firms adjusted to the capital investment target faster than to R&D investment. However, firms increased the adjustment speed in R&D investment significantly during the crisis, and it has remained at similar levels during the post-crisis period. The changes in adjustment speeds can be explained by several firm-specific characteristics that are related to the ability of firms to raise internal finance.

This paper investigates the effect of R&D intensity on firm resilience during the COVID-19 recession. I use firm-level data on European technology firms to identify the relation between R&D intensity and resilience, where firm resilience is measured through financial flexibility and firm performance. To investigate deeper into firm performance I distinguish between performance using accounting measures and market performance. I find that R&D intensity has a positive effect on resilience as viewed from accounting measures. I find mixed results regarding performance: No significant positive evidence between R&D intensity and stock performance is found, whereas evidence suggesting a significant non-linear relationship between R&D intensity and return on assets is found. Nevertheless, the results indicate that there seem to be some positive effect of R&D on firm resilience. This is of value to policymakers and corporate managers aiming to enhance firm resilience through strategic R&D investments. Further research with more detailed data are needed to explore the mechanisms behind this relationship.

The purpose of this thesis is to investigate the impact of government non-investment and applied R&D subsidies on the firm level competitiveness. According to many literature sources the indicators of competitiveness are assumed to be Return on Assets, Return on Equity, Return on Sales and Asset Turnover ratio. The tool used to test the effect is counterfactual analysis. The subsidized companies are compared to a control group drawn by Propensity Score Matching, the effect is tested by Average Treatment Effect on the Treated and the difference in size of other financials is derived by Difference in Differences. The study focuses on two industries NACE C25 (metallurgy) and C28 (manufacture of machines). The subsidized companies show no added significant growth of competitiveness whatsoever. The financials (Total Assets, Equity, Turnover) grew, compared to the control group, only for industry C25. JEL Classification O31, O38, H21 Keywords R&D, Innovation, non-investment, subsidies, applied R&D, competitiveness Author's e-mail petr.rotr@post.cz Supervisor's e-mail petr.teply@fsv.cuni.cz