Measuring economic downside risk and severity - Growth at Risk

Output collapses, and crises are a fact of life. Severe economic downturns occur periodically, and have grave consequences on the poor. The authors propose a new measurement for economic downside risk, and severity: Growth at risk. Similar to the concept of Value at Risk in finance, Growth at Risk summarizes the expected maximum economic downturn over a target horizon at a given confidence level. After providing a taxonomy of growth risks, the authors construct a panel data, set on Growth at Risk for 84 countries, over the period 1980-98. On average, different regional groups experience very distinct Growth at Risk patterns over time. 1) Non-OECD countries experience a higher downturn risk, while OECD countries'downturn risks for both big, and small recessions are the lowest among all groups. 2) East Asia countries, which had been growing faster, had a high Growth at Risk for big downturns, at around six percent, and it rose dramatically at the end of the 1990s. 3) Latin America, and Sub-Saharan Africa also maintained high Growth at Risk for both big, and small recessions through 1980-98. But for Latin America, Growth at Risk for big recessions declined in the 1990s. The authors then investigate the relationship between downside risks, and long-term average growth in a cross-country analysis. They find that higher perceived levels of downside growth risk, seem to be negatively associated with long-term growth. When a country's perceived level of downside growth risk is relatively high, both domestic, and foreign investors might be deterred from making long-term investments in the country, and instead invest elsewhere. The results suggest that prudent, and consistent pursuit of socioeconomic, and political stability, contributes to long-term growth, and that risk management in a broader sense, should be a vital part of the pro-growth, and poverty reduction strategy.Public Health Promotion,Economic Theory&Research,Economic Conditions and Volatility,Health Monitoring&Evaluation,Labor Policies,Achieving Shared Growth,Economic Growth,Economic Theory&Research,Governance Indicators,Health Monitoring&Evaluation

Sources of China's economic growth, 1952-99 : incorporating human capital accumulation

China's performance in economic growth, and poverty reduction has been remarkable. There is an ongoing debate about whether this growth is mainly driven by productivity, or factor accumulation. But few past studies have incorporated information on China's human capital stock, and thus contained an omission bias. The authors construct a measure of China's human capital stock from 1952 to 1999, and, using a simple growth accounting exercise, incorporate it in their analysis of the sources of growth, during the pre-reform (1952-77), and the reform period (1978-99). They find that the accumulation of human capital in China (as measured by the average years of schooling for the population aged 15 to 64) was quite rapid, and contributed significantly to growth, and welfare. After incorporating human capital, they also find that the growth of total factor productivity, still plays a positive, and significant role during the reform period. In contrast, productivity growth was negative in the pre-reform period. The results are robust to changes in labor shares in GDP. The recent declining rate of human capital accumulation is a cause for concern, if China is to sustain its improvements in growth, and welfare in the coming decade. Funding for basic education is unevenly distributed, and insufficient in some poor regions.Labor Policies,Environmental Economics&Policies,Capital Markets and Capital Flows,Economic Theory&Research,Public Health Promotion,Achieving Shared Growth,Health Monitoring&Evaluation,Economic Theory&Research,Economic Growth,Environmental Economics&Policies

Compensation for the setup instability in ptychographic imaging

The high-frequency vibration of the imaging system degrades the quality of the reconstruction of ptychography by acting as a low-pass filter on ideal diffraction patterns. In this study, we demonstrate that by subtracting the deliberately blurred diffraction patterns from the recorded patterns and adding the properly amplified subtraction to the original data, the high-frequency components lost by the vibration of the setup can be recovered, and thus the image quality can be distinctly improved. Because no prior knowledge regarding the vibrating properties of the imaging system is needed, the proposed method is general and simple and has applications in several research fields.Comment: 13pages, 10figure

Regional Income Divergence in China

Numerous policy studies have argued that conditions have prevailed in China since the open door economic reforms of the late 1970s that have encouraged rapid growth at the expense of regional income inequality across the provinces of China. In this paper we use recently developed nonstationary panel techniques to provide empirical support for the fact that the long run tendency since the reforms has been for provincial level incomes to continue to diverge. More importantly, we show that this divergence cannot be attributed to the presence of separate, regional convergence clubs divided among common geographic subgroupings such as the coastal versus interior provinces. Furthermore, we also show that the divergence cannot be attributed to differences in the degree of preferential open-door policies. Rather, we find that the divergence is pervasive both nationally and within these various regional and political subgroupings. We argue that these results point to other causes for regional income divergence, and they also carry potentially important implications for other regions of the world.China, convergence, nonstationary panels

Finger Vein Image Deblurring Using Neighbors-Based Binary-GAN (NB-GAN)

Vein contraction and venous compression typically caused by low temperature and excessive placement pressure can blur the captured finger vein images and severely impair the quality of extracted features. To improve the quality of captured finger vein image, this paper proposes a 26-layer generator network constrained by Neighbors-based Binary Patterns (NBP) texture loss to recover the clear image (guessing the original clear image). Firstly, by analyzing various types and degrees of blurred finger vein images captured in real application scenarios, a method to mathematically model the local and global blurriness using a pair of defocused and mean blur kernels is proposed. By iteratively and alternatively convoluting clear images with both kernels in a multi-scale window, a polymorphic blur training set is constructed for network training. Then, NBP texture loss is used for training the generator to enhance the deblurring ability of the network on images. Lastly, a novel network structure is proposed to retain more vein texture feature information, and two residual connections are added on both sides of the residual module of the 26-layer generator network to prevent degradation and overfitting. Theoretical analysis and simulation results show that the proposed neighbors-based binary-GAN (NB-GAN) can achieve better deblurring performance than the the-state-of-the-art approaches