Club Convergence in R&D Expenditure across European Regions

The increasing disparities between European regions constitute a great challenge for sustainable development and require identification of the factors responsible for this process. Given the substantive role of R&D in shaping innovativeness and economic development, understanding its dynamics and spatial patterns can provide new insights into regional growth prospects. Although prior studies have investigated the patterns of innovation convergence, apparently none has attempted to test the convergence club hypothesis in R&D expenditure in the European regional scope. Therefore, the present study aims to fill this gap. The paper aims at examining the convergence path of R&D expenditure across European regions and at identifying the factors conditioning club membership. Data were retrieved from Eurostat’s regional database and Regional Innovation Scoreboard datasets over 2008–2018. Employing a nonlinear time-varying factor model, we reveal that R&D expenditure in the examined regions follows the pattern of club convergence. The results of our research allow to identify five convergence clubs characterised by distinct disparities in the R&D expenditures. We also demonstrate that the emergence of the identified convergence clubs might be attributable to the initial differences in human capital, external knowledge embedded in patents and technological structures across regions as measured by employment in medium-high and high-tech manufacturing and knowledge-intensive services. These results provide policy implications in terms of the formulation and implementation of more tailored innovation policies, based on smart development and specialisation strategies. The presence of business R&D convergence clubs requires shifting EU policy actions towards a more sustainable model promoting both the advantages of the strongest regions and the development opportunities in less-developed ones.

Developing a competitiveness index at sub-national level for India: an economic growth measure

PurposeThe objective of this study is threefold–first, to develop a Regional Competitiveness Index (RCI) for measuring competitiveness of sub-national regions for India; second, to test this index for its ability to explain regional growth, which validates usage and applicability of this index; and third, to further investigate if the competitiveness of states is in turn caused by economic growth, i.e. it is tested if there is a bidirectional causality between competitiveness and regional growth.Design/methodology/approachThe data of indicators used in the index are from sources available freely in public domain. The competitiveness index is constructed using equal weightage supported by principal component analysis (PCA) technique. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMMs) is used for this dynamic regression estimation.FindingsBased on RCI score, states have been ranked and through rank analysis, the authors observe the performance status of these sub-national regions and are able to categorize them as improving, no change or deteriorating in regional competitiveness. Using the GMM estimation, the association between RCI and economic growth is found to be significant at 10% level. This shows that regional competitiveness as captured through the RCI score is able to explain regional economic growth and economic disparity among the sub-national units. Further, that RCI score is found to Granger-cause growth, while growth does not lead to better RCI scores. This establishes the usefulness of RCI as an important policy variable to compare states and provide direction for sectoral reforms.Research limitations/implicationsThe limitations of the study include (1) broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment, and (2) data constraints as it is a longitudinal study. The study implies that the composite index could capture differences in regional competitiveness explaining regional economic disparity and that competitiveness causes higher economic growth and not vice versa.Practical implicationsThe RCI score can prove to be a useful indicator of economic performance of different states and can be used by national and state policymakers to compare and assess regional disparity among different states. The pillar-wise scores will be useful for in-depth study of weakness and strength of the sub-national territories.Originality/valueConstruction of an RCI for sub-national territories and analysis of panel data for longitudinal study of ten years is unique in the regional competitiveness literature.

Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England

Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.

Non-Global Privacy Protection Facing Sensitive Areas in Face Images

Face images, as an information carrier, are naturally weak in privacy. If they are collected and analyzed by malicious third parties, personal privacy will leak, and many other unmeasurable losses will occur. Differential privacy protection of face images is mainly being studied under non-interactive frameworks. However, the ε-effect impacts the entire image under these frameworks. Besides, the noise influence is uniform across the protected image, during the realization of the Laplace mechanism. The differential privacy of face images under interactive mechanisms can protect the privacy of different areas to different degrees, but the total error is still constrained by the image size. To solve the problem, this paper proposes a non-global privacy protection method for sensitive areas in face images, known as differential privacy of landmark positioning (DPLP). The proposed algorithm is realized as follows: Firstly, the active shape model (ASM) algorithm was adopted to position the area of each face landmark. If the landmark overlaps a subgraph of the original image, then the subgraph would be taken as a sensitive area. Then, the sensitive area was treated as the seed for regional growth, following the fusion similarity measurement mechanism (FSMM). In our method, the privacy budget is only allocated to the seed; whether any other insensitive area would be protected depends on whether the area exists in a growing region. In addition, when a subgraph meets the criterion for merging with multiple seeds, the most reasonable seed to be merged would be selected by the exponential mechanism. Experimental results show that the DPLP algorithm satisfies ε-differential privacy, its total error does not change with image size, and the noisy image remains highly available.

Trends in development of Russian Far East’s fishing industry in context of strategic regional growth

This article is devoted to topical issues of the fishing industry development in the Russian Far East. Far East is the largest and the most abundant with fish resources region of Russia, and also it is the largest territorial administrative unit. The main scientific and practical task the research can help to solve is implementation of strategic prospects and scientific support of the industry development government programs. The aim of the research is to update the trends and identify the main problems of the fishing industry development in the Far East of Russia over the past decade. Methodologically the research is based on the concept of regional economy sustainable development. The article analyzes such indicators of the industry development as: number of enterprises in the industry, number of employees at the industry enterprises, volume of fish products production and processing, level of domestic prices for fish products, fish products consumption volume, fish products export value, volume of investments in fixed assets of industry enterprises. The key trends are identified and the most important problems of the regional fishing industry development are noted. Among such problems: the industry’s dependence on the world market situation, insufficient development of domestic market, excessive growth in prices for fish products in the domestic market, low degree of fish products processing, dependence of fish products export on Asian countries’ consumers.

Growth and trend analysis of area, production and yield of rice: A scenario of rice security in Bangladesh

Bangladesh positioned as third rice producing country in the world. In Bangladesh, regional growth and trend in rice production determinants, disparities and similarities of rice production environments are highly desirable. In this study, the secondary time series data of area, production, and yield of rice from 1969–70 to 2019–20 were used to investigate the growth and trend by periodic, regional, seasonal and total basis. Quality checking, trend fitting, and classification analysis were performed by the Durbin-Watson test, Exponential growth model, Cochrane-Orcutt iteration method and clustering method. The production contribution to the national rice production of Boro rice is increasing at 0.97% per year, where Aus and Aman season production contribution significantly decreased by 0.48% and 0.49% per year. Among the regions, Mymensingh, Rangpur, Bogura, Jashore, Rajshahi, and Chattogram contributed the most i.e., 13.9%, 9.8%, 8.6%, 8.6%, 8.2%, and 8.0%, respectively. Nationally, the area of Aus and Aman had a decreasing trend with a -3.63% and -0.16% per year, respectively. But, in the recent period (Period III) increasing trend was observed in the most regions. The Boro cultivation area is increasing with a rate of 3.57% per year during 1984–85 to 2019–20. High yielding variety adoption rate has increased over the period and in recent years it has found 72% for Aus, 73.5% for Aman, and 98.4% for Boro season. As a result, the yield of the Aus, Aman, and Boro seasons has been found increasing growth for most of the regions. We have identified different cluster regions in different seasons, indicating high dissimilarities among the rice production regions in Bangladesh. The region-wise actionable plan should be taken to rapidly adopt new varieties, management technologies and extension activities in lower contributor regions to improve productivity. Cluster-wise, policy strategies should be implemented for top and less contributor regions to ensure rice security of Bangladesh.

ДРУШТВЕНИ КАПИТАЛ У ФУНКЦИЈИ УНАПРЕЂЕЊА РЕГИОНАЛНОГ РАЗВОЈА

Regional development strategies should be based on the sound assessment of regional resources, capabilities, competences and core competences, as well as on dynamic capabilities aiming to develop the resource configurations in order to form their regional competitive advantage. Therefore, new regionalism is basically a bottom-up process, because the prerequisites for its successful implementation are the leadership and vision of local actors and administrations, civic participation, the growth of social capital and administrative decentralization and devolution of power. In that sense, the paper deals with important issues regarding the intangible determinants of regional economic development. The research method that will be dominantly used in this paper is the case-study method which aims to fully and thoroughly reconstruct the presence and role of social capital (primarily its structural dimension - social network platforms) in the regional development of world-famous and successful regions such as Silicon Valley, Baden-Wurttemberg and Emilia-Romagna. The overall conclusion of the paper is that regional growth is a function of the social capital stocks of respective regions to a significant extent. Social capital is positively linked to regional development and economic prosperity by reducing transaction costs, articulating collective actions, encouraging innovation and technology dissemination, discouraging opportunism and increasing monetary and non-monetary cost of fraud.

Theoretical bases for the development of the Chinese-Belarusian industrial park “Veliky kamen” as a center for innovative, regional growth and international competitiveness

The article examines the mechanism of functioning of the Chinese-Belarusian industrial park “Veliky kamen”. The conclusion is made about the expediency of further development of the park as a center of innovative, regional growth and increasing the international competitiveness of the Belarusian economy. A review of theories and concepts that form the theoretical foundations of improving the park model is carried out. Among them: the theory of polarized development, international competitiveness, regional innovation systems, the concept of realizing the spatial advantages of economic activity (agglomeration, urban governance). The policy of further development of the park in the following areas has been substantiated: the formation of an innovative environment for residents; formation of a cluster model; increasing the international competitiveness of the park through the use of management innovations, expanding service services, including using digital technologies, implementing the effects of agglomeration when creating a satellite city on the basis of the park.

Uncertainty Analysis of Regional Rainfall Frequency Estimates in Northeast India

Estimation of rainfall quantile is an important step in regional frequency analysis for planning and design of any water resources project. Related evaluations of accuracy and uncertainty help to further assist in enhancing the reliability of design estimates. In this study, therefore, we investigate the accuracy and uncertainty of regional frequency analysis of extreme rainfall computed from genetic algorithm-based clustering. Uncertainty assessment is explored with prediction of quantiles with a new spatial Information Transfer Index (ITI) and Monte Carlo simulation framework. And, accuracy assessment is done with the comparison of regional growth curves to at-site analysis for each homogenous region. Further, uncertainty assessment with the ITI method is compared with Maximum Likelihood estimation (MLE) optimized by a genetic algorithm (GA) to check the suitability of the method. Results obtained suggest the ITI-based uncertainty assessment for regional estimates outperformed those of at-site estimates. The MLE-GA method based on at-site estimates was found to be better than at-site estimates based on L-moments, suggesting the former as a better alternative to compare with regional frequency estimates. Moreover, minimal bias and least deviation of the regional growth curve were obtained in the rainfall regions. The confidence intervals of regional estimates were seen to be well within the bounds of normality assumptions. Doi: 10.28991/cej-2021-03091762 Full Text: PDF

Achieving a high share of non-hydro renewable integration in Brazil through wind power: regional growth and employment effects

In this policy brief we investigate the wind power development in Brazil and its effects on employment and regional growth. Using the CGE model TERM-BR10, we estimate that in the absence of the policy framework that supported wind power expansion there would have been a GDP loss of 0.15% nationally and of 1.1% in the Northeast region (which concentrates over 90% of wind installed capacity), with negative impacts to labour market mostly over skilled jobs.