Balancing Openness and Protection:Homogenization of Regulatory Laws in Digital Service Trade

Digital service trade has emerged as a pivotal engine for global economic transformation and development.However,the implementation of differentiated regulatory measures for trade in digital services among economies has led to increasingly frequent trade disputes.This paper constructs a regulatory homogeneity network for digital service trade in 60 major economies,and systematically evaluates the structural characteristics of the network and the regulatory homogeneity among economies from 2014 to 2021.Furthermore,this paper empirically examines the impact of the partnership characteristics of regulatory homogenization in the network of major economies on their exports.The analysis of the network structure shows that major economies are more inclined to optimize and simplify existing trade partnerships,and are moving towards more diversified restrictive measures in the regulatory model of digital services trade,which has led to the rise of trade protectionism.The empirical text results show that expanding and deepening the regulatory homogeneous partnership of trade in digital services promotes the export of digital services in major economies.This promotion effect is mainly achieved by reducing the cost of digital service trade and enhancing business trust.In addition,the export promotion effect of developing regulatory homogenization partnerships is better than that of increasing the openness of digital service trade,and the homogenization of policies between openness and protection is more important.This paper provides important implications for coordinating the openness and security of digital services trade:China should actively cooperate with multilateral and bilateral digital service trade partners to jointly build a homogeneous environment for regulatory regulations.In particular,it is necessary to deepen the regulatory homogeneity partnership with Asian and developing economies to expand the infl uence of the“China model”in the global regulation of digital services trade.

Labour Markets in China： A Study of the Structure and Evolution of Wages

This paper examines the development of labour markets and the evolution of a structure of wages in China, using household surveys for 1988, 1995, 2002 and 2007. It finds evidence of both provincial and sectoral segmentation in labour markets, with eastern regions and the state-controlled sector enjoying high wage premiums in the early reform period. During the reform, China has progressed slowly towards an integrated labour market with convergence in incomes between the rural non-agriculture sector and the urban market-based sector by 1995, when industry flourished in the rural areas. The wage gap between the rural non-agriculture sector and other sectors increased and the urban state-controlled sector remained segmented with respect to all other sectors up to 2002. However, the data from 2007 show there has been increasing sectoral and spatial integration.

Employment Structure,Lewis Turning Point and the Labor Share of Income:Theoretical and Empirical Analysis

In the context of the labor market segmentation in China and its reaching the Lewis turning point,this paper interprets the changing trend of the labor share of income in China from the changing perspective of the employment ownership structure.The theoretical analysis reveals that the labor share of income follows a U-shaped curve when the agricultural labor force gradually moves into the private and self-employed sectors.Using the Chinese provincial-level panel dataset between 1990 and 2016,our empirical study finds that there is a critical threshold.When the share of agricultural labor force is above this threshold value,the impact of the increase in the employment share of the urban private sector on the labor share of income is negative.In contrast,the impact becomes positive when the share of the agricultural labor force is less than or equal to this threshold value.Moreover,the impacts of other variables of employment ownership structure don’t show this kind of feature on both sides of this threshold value.The increase in the employment share of the urban private sector accounted for about 29.37%of the growing labor share of income between 2007 and 2016.This paper provides policy implications in the following four areas:institutional guarantee improvement,harmonious labor relations establishment,redistribution policy imposition and economic development pattern transformation.

Misallocation in Chinese Manufacturing and Services: A Variable Markup Approach

Cross-country comparison reveals an unusually small service sector in China. Using firm-level data from Chinas 2008 economic census, we find two facts that speak to a novel mechanism of misallocation within service and between manufacturing and service sectors. First, compared with the manufacturing sector, there are more stateowned enterprises and fewer entrants in the service sector. Second, markups increase with firm size, and the increase is more dramatic among service firms. We interpret these facts through the lens of a monopolistic competition model with heterogeneous firms and variable markups. A multisector model shows a new channel that translates asymmetric barriers to entry across sectors into sectoral markup differences, which in turn cause sectoral misallocation. Quantitative analysis shows that when reducing entry barriers to service firms to the extent observed for manufacturing firms, the model predicts a 12-percentage-point increase in the service employment share.

Versatile HAR model for realized volatility: A least square model averaging perspective

A rapidly growing body of literature has documented improvements in forecasting financial return volatility measurement using various heterogeneous autoregression(HAR)type models.Most HAR-type models use a fixed lag index of(1,5,22)to mirror the daily,weekly,and monthly components of the volatility process,but they ignore model specification uncertainty.In this paper,we propose applying the least squares model averaging approach to HAR-type models with signed realized semivariance to account for model uncertainty and to allow for a more flexible lag structure.We denote this approach as MARS and prove that the MARS estimator is asymptotically optimal in the sense of achieving the lowest possible mean squared forecast error.Selected by the data-driven model averaging method,the lag combination in the MARS method changes with various data series and different forecast horizons.Employing high frequency data from the NASDAQ 100 index and its 104 constituents,our empirical results demonstrate that acknowledging model uncertainty under the HAR framework and solving with the model averaging method can significantly improve the accuracy of financial return volatility forecasting.

Network-based naive Bayes model for social network

Naive Bayes(NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes(NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational efficiency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance.A real data example is also analyzed for illustration purpose.