THE ROLE OF EXTENSIVE MARGIN AND INTENSIVE MARGIN IN KAZAKHSTAN’S EXPORT GROWTH

Decomposition of country’s export gives us to opportunity to understand the sources of exports growth. This paper decomposes Kazakhstan export into four margins extensive, intensive, price and quantity. We analyzed Kazakhstan’s export performance using data at the 6-digit level over period 2004-2013. Kazakhstan export showed good results during this period, but this growth was not sustainable. We employed two methods for decomposition of exports, count method and method of shares. Our investigation showed that intensive margin of exports and quantity component of exports was important contributor of the export growth. The result further pointed out that final goods are more important in exports growth than these goods were a decade ago

Classification and Retrieval of Digital Pathology Scans: A New Dataset

In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology. We use the whole scan images of 24 different tissue textures to generate 1,325 test patches of size 1000$\times$1000 (0.5mm$\times$0.5mm). Training data can be generated according to preferences of algorithm designer and can range from approximately 27,000 to over 50,000 patches if the preset parameters are adopted. We propose a compound patch-and-scan accuracy measurement that makes achieving high accuracies quite challenging. In addition, we set the benchmarking line by applying LBP, dictionary approach and convolutional neural nets (CNNs) and report their results. The highest accuracy was 41.80\% for CNN.Comment: Accepted for presentation at Workshop for Computer Vision for Microscopy Image Analysis (CVMI 2017) @ CVPR 2017, Honolulu, Hawai

Population Aging, Saving Rate and Long-term Economic Growth in China: Based on Dynamic CGE Model

Based on China's dynamic computable general equilibrium model (MCHUGE) with endogenous saving rate, the paper analyses and quantifies the impact of population aging in the next four decades on China's macro-economic growth and structural adjustment from the perspective of consumption and investment. This paper firstly studies demographic effects on household saving rates by using econometrical anlysis. The paper also constructs a dynamic CGE model which contains endogenous saving rates and flexible closures according to different saving-investment decision theory. More importantly, the model characterizes the impact of aging on economic growth by influencing saving ,capital formation and investment instead of choosing other channels, such as consumption mechanism and labor supply mechanism in the previous researches. The simulation results shows that the negative effects of the aging of the population which do not appear in the short-term due to the positive pull of the consumption mainly come from the long-term pressure; funding gap caused by labor supply decline and the dropping saving rate in the long-term, are bound to reduce levels of potential economic growth. Secondly, Economic structure has shifted passively towards demand-oriented and service-based economy, and the pulling effect of export and investment are supposed to face challenges. Meanwhile, financial reforms are supposed to further deepen the impact of aging population on China's long-term economic growth along the future investment path

Knowledge Capital, Endogenous Growth and Regional Disparities in Productivity: Multi-level Evidences from China.

This paper examines the role of knowledge capital in persistent regional productivity disparities in developing countries. The hypotheses are tested using regional and firm level longitudinal data from China. It is found that inequalities in knowledge creation and transfer, both inter-generational and international, played a significant role in increasing regional disparities in productivity. These inequalities are exacerbated by the accumulative nature of knowledge capital. All this leads to self-perpetuating cycles of success and failure, particularly compounded with asymmetric financial and human capital between different regions

Spatial Characteristics and Dynamics of Provincial Total Factor Productivity in China.

This paper explores the influence of spatial effects on the convergence of total factor productivity (TFP) across Chinese regions. We use the Moran index, Markov transition matrix and panel data techniques to analyse spatial dependence, transition dynamics and disparities in TFP across Chinese provinces over the period from 1978 to 2004. We find that in the period following 1978, there has been an increase in spatial dependence in provincial-level TFPs across the various regions in China. However, the extent of this dependence is not the same across regions and the direction of movement of provincial TFP does not show convergence. On the contrary, provincial TFPs at the middle quintile level moved to the quintile levels at the highest and lowest levels, suggesting divergence and polarization in TFP across Chinese regions. The ‘New Eastern Region’ appears to be a TFP convergence club over the sampling period but no evidence is found suggesting convergence of TFP between provinces in the other subgroups. Policy implications are discussed

Double-edged effects of the technology gap and technology spillovers: Evidence from the Chinese industrial sector

This paper proposes a new insight that the technology gap plays double-edged roles in the technology spillovers of foreign direct investment (FDI) through two channels, technology choice set and technology absorptive capability. Applying a multiple-threshold model, we examine the non-linear relationship between the technology gap and technology spillovers based on the provincial panel data of the Chinese industrial sector during 1993-2006. The empirical results support the hypothesis of two thresholds, which are 0.3071 and 0.5214 in terms of the technology gap respectively. The estimated thresholds indicate the sufficient absorptive capability is the premise for FDI technology spillovers. Moreover, it implies the marginal decrease of FDI technology spillover effects in the long run.FDI technology gap technology spillovers multiple-threshold model

Regularity for sub-elliptic systems with VMO-coefficients in the Heisenberg group: the sub-quadratic structure case

We consider nonlinear sub-elliptic systems with VMO-coefficients for the case 1 < p < 2 under controllable growth conditions, as well as natural growth conditions, respectively, in the Heisenberg group. On the basis of a generalization of the technique of -harmonic approximation introduced by Duzaar-Grotowski-Kronz, and an appropriate Sobolev-Poincaré type inequality established in the Heisenberg group, we prove partial Hölder continuity results for vector-valued solutions of discontinuous sub-elliptic problems. The primary model covered by our analysis is the non-degenerate sub-elliptic p-Laplacian system with VMO-coefficients, involving sub-quadratic growth terms

An Improved 3D Magnetization Inversion Based on Smoothness Constraints in Spherical Coordinates

In the inverse problem, the traditional way to obtain a stable solution is based on the maximum smoothness criteria. However, this approach cannot generate clearer and more focused images. In this study, we propose an improved inversion method based on the smoothness constraints. In the algorithm, the model weighting functions are updated by adding a model’s total gradient module matrix, which can effectively constrain the boundary of the recovery model in the iterative operation. We invert the 3D magnetization intensity for the three-component magnetic data in the spatial domain by spherical coordinates. The preconditional conjugate gradient algorithm is introduced to improve the efficiency of the solutions. We design two sets of synthetic examples to evaluate the inversion effects, which show that the improved method is more reliable than the smoothness constraint method. The boundary of the magnetic bodies is more precise, and the magnetization ranges are more focused. The method does not rely on the initial model and is suitable for magnetic vector data inversion. We also apply the algorithm to a set of Dabie orogen three-component magnetic data derived from a geomagnetic field model and verify the effectiveness of the inversion method