Limiting Government Predation Through Anonymous Banking: A Theory with Evidence from China

China's economic performance of the past two decades presents a puzzle for the economics of transition and development: Enormous private business incentives were unleashed that have fueled rapid economic growth despite the fact that China has had very weak "conventional institutions" (such as the rule of law and separation of powers) to constrain the government from arbitrary intrusion into economic activities. We argue that one mechanism that has limited the government's ability for predation and harassment is commitment through information decentralization, where the key institutiton is "anonymous banking," that is, a combination of the use of cash for transactions and the use of anonymous savings deposits. The government's incentive for such a mechanism comes form the increased quasi-fiscal revenues collected from the state banking system through "financial repression," a combination of controls on international capital flows with restrictions on domestic interest rates. The major features of China's economy concerning its fiscal decline, financial deepening, and the sectoral dual-track can be better understood using this analytical framework.http://deepblue.lib.umich.edu/bitstream/2027.42/39659/3/wp275.pd

The Return to Capital in China

China's investment rate is one of the highest in the world, which naturally leads one to suspect that the return to capital in China must be quite low. Using the data from China's national accounts, we estimate the rate of return to capital in China. We find that the aggregate rate of return to capital averaged 25% during 1978-1993, fell during 1993-1998, and has become flat at roughly 20% since 1998. This evidence suggests that the aggregate return to capital in China does not appear to be significantly lower than the return to capital in the rest of the world. We also find that the standard deviation of the rate of return to capital across Chinese provinces has fallen since 1978.

Limiting Government Predation Through Anonymous Banking: A Theory with Evidence from China

China's economic performance of the past two decades presents a puzzle for the economics of transition and development: Enormous private business incentives were unleashed that have fueled rapid economic growth despite the fact that China has had very weak "conventional institutions" (such as the rule of law and separation of powers) to constrain the government from arbitrary intrusion into economic activities. We argue that one mechanism that has limited the government's ability for predation and harassment is commitment through information decentralization, where the key institutiton is "anonymous banking," that is, a combination of the use of cash for transactions and the use of anonymous savings deposits. The government's incentive for such a mechanism comes form the increased quasi-fiscal revenues collected from the state banking system through "financial repression," a combination of controls on international capital flows with restrictions on domestic interest rates. The major features of China's economy concerning its fiscal decline, financial deepening, and the sectoral dual-track can be better understood using this analytical framework.

High spatial-resolution imaging of label-free in vivo protein aggregates by VISTA

Amyloid aggregation, formed by aberrant proteins, is a pathological hallmark for neurodegenerative diseases, including Alzheimer's disease and Huntington's disease. High-resolution holistic mapping of the fine structures from these aggregates should facilitate our understanding of their pathological roles. Here, we achieved label-free high-resolution imaging of the polyQ and the amyloid-beta (Aβ) aggregates in cells and tissues utilizing a sample-expansion stimulated Raman strategy. We further focused on characterizing the Aβ plaques in 5XFAD mouse brain tissues. 3D volumetric imaging enabled visualization of the whole plaques, resolving both the fine protein filaments and the surrounding components. Coupling our expanded label-free Raman imaging with machine learning, we obtained specific segmentation of aggregate cores, peripheral filaments together with cell nuclei and blood vessels by pre-trained convolutional neural network models. Combining with 2-channel fluorescence imaging, we achieved a 6-color holistic view of the same sample. This ability for precise and multiplex high-resolution imaging of the protein aggregates and their micro-environment without the requirement of labeling would open new biomedical applications

The Return to Capital in China

China’s investment rate is one of the highest in the world, a fact that leads one to suspect that the return to capital in China must be quite low. Using data from China’s national accounts, this paper estimates the return to capital in China. We find that the aggregate annual return to capital averaged 25 percent during 1978-93, fell during 1993-98, and has remained roughly stable at around 20 percent since 1998. Thus the aggregate return to capital does not appear to be significantly lower in China than in the rest of the world. We also find that the dispersion in the return to capital across Chinese provinces has fallen since 1978.macroeconomics, China, Capital, Chinese, China investment rate

Do College Entrance Examination Scores Predict Undergraduate GPAs? A Tale of Two Universities

Each year, millions of Chinese high school students sit the National College Entrance Examination (CEE). For the majority of students, the CEE score is the single determinant in whether they gain admission into a college and to what college they enter. The purpose of this paper is to determine whether and how well the CEE score predicts college academic success. We also consider high school achievement and admission route in predicting college grades. We obtain administrative data on CEE and undergraduate GPAs from two Chinese universities with very different rankings. We find that, for both universities the CEE total score predicts undergraduate GPAs for all four years in college. Even the size of the estimates for CEE is similar for the two universities. High school achievement and admission routes are also significant predictors of college grades. However, we do not find consistent results as to which CEE subject test scores predict students’ academic performance in college

Do College Entrance Examination Scores Predict Undergraduate GPAs? A Tale of Two Universities

Each year, millions of Chinese high school students sit the National College Entrance Examination (CEE). For the majority of students, the CEE score is the single determinant in whether they gain admission into a college and to what college they enter. The purpose of this paper is to determine whether and how well the CEE score predicts college academic success. We also consider high school achievement and admission route in predicting college grades. We obtain administrative data on CEE and undergraduate GPAs from two Chinese universities with very different rankings. We find that, for both universities the CEE total score predicts undergraduate GPAs for all four years in college. Even the size of the estimates for CEE is similar for the two universities. High school achievement and admission routes are also significant predictors of college grades. However, we do not find consistent results as to which CEE subject test scores predict students’ academic performance in college

An Experimental Study for the Effects of Noise on Hyperspectral Imagery Classification

Hyperspectral image (HSI) classification is a very important topic in remote sensing. There are many published methods for HSI classification in the literature. Nevertheless, it is not clear which method is the most robust to noise in HSI data cubes. In this paper, we conduct a systematic study to examine the effects of noise in HSI data cubes on classification methods. We compare ten existing methods for HSI classification when Gaussian white noise (GWN) and shot noise are present in the HSI data cubes. We have figured out which method is the most robust to GWN and shot noise respectively by experimenting on three widely used HSI data cubes. We have also measured the CPU computational time of every method compared in this paper for HSI classification