Personal Income Tax Reform in China in 2018 and Its Impact on Income Distribution

In the context of personal income tax (PIT) reform in China in 2018, this paper examines some of the major issues of concern regarding the reform and income distribution. Using the China Personal Income Tax Micro‐simulation model, the paper compares the differences between the 2011 and 2018 PIT systems, and finds that residents relying on different income sources may face a large degree of real tax rate change. Once the tax system is altered to PIT 2018, the coverage of PIT for wage earners will decrease from 46.9 to 23.4 percent, the income redistributive effect will drop from 1.95 to 1.22 percent and the PIT's role in fiscal revenue will also be negatively affected. Nevertheless, if individual income continues to grow, the share of PIT in fiscal revenue is expected to return to the 2018 level in 2022, but its income redistribution function is difficult to recover in the short term. The paper finds that the effect of PIT on income distribution depends on the tax structure. Gradual transition to an “entirely comprehensive” tax system when conditions are appropriate will achieve better income redistribution results at a lower average tax rate.     

Impact of state-dependent oil price on US stock returns using local projections

In this paper, we investigate the impact of oil prices on both aggregate and industry US real stock returns over the period 1973–2017. The empirical analysis contributes to the related literature introducing a state-dependent oil price (high and low) and the local projections approach. Our main finding is that, depending on the nature of the shock and industry, the negative effects of oil price shocks become exacerbated -and the positive effects get moderated- if oil prices are already high.     

Why will Trump lose the trade war?

ABSTRACT

The escalating U.S.–China trade conflicts have increasingly shadowed the outlook of the world economy. The Trump administration aims to achieve its strategic goals including reducing current account deficits, promoting the U.S. manufacturing sector, and curbing Chinese high-tech industries by waging the trade war against China. This paper argues that the current account deficits and the declining manufacturing sector in the U.S. are mainly driven by its internal structural factors, such as low saving rates, high labor costs, and rising service sector, rather than by the import competition from China. Moreover, the trade war further deteriorates the U.S. current account deficits and erode its comparative advantage, and it forces China to invest more in technological innovation and human capital, and thus promote its progress in high-tech industries. Thus, the U.S. will not be able to achieve its strategical goals and eventually lose the trade war.     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

Competing for Good Immigrants

I analyze the competition among different countries for ‘desirable’ and ‘undesirable’ potential immigrants, using both an immigration quota and a level of (imperfect) ‘scrutiny’ that would‐be immigrants face. Scrutiny imposes costs on immigrants and therefore makes it less attractive to immigrate. The number of applying undesirable immigrants increases in immigration quota and decreases in the level of scrutiny. In contrast, the number of desirable applicants can go in either direction as scrutiny increases and is independent of the immigration quota, because an increase in the immigration quota is completely crowded out by more applications by undesirable immigrants.     

In Data We Trust? An Analysis of Indonesian Socioeconomic Survey Data

What if a popular dataset that has generated a large amount of literature has been misunderstood and has led to misleading inferences? This paper examines household expenditure data from the Indonesian National Socio-economic Survey (Susenas), which started more than 50 years ago. Appropriate use of Susenas data for policy analysis requires an understanding that the survey’s expenditure variable does not measure true out-of-pocket expenses, because it includes subsidies received by households when obtaining goods and services. We also highlight an abrupt change in the survey instrument that occurred in 2015, when the reference period for certain items was extended. For health items, this generated a change in the expenditure series that can be misinterpreted as being the result of a social health insurance reform introduced in 2014 to lower the health care burden on households. Accordingly, we propose a way to account for this artificial expenditure movement in Susenas.     

Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

LEADERSHIP IN CLIMATE CHANGE MITIGATION: CONSEQUENCES AND INCENTIVES

Initiatives in favor of unilateral action on climate change are frequently challenged by concerns over free riding. Nevertheless, we observe an increasing number of unilateral efforts at different administrative levels and in different parts of the world. Previous academic literature described various individual mechanisms where emissions abroad may increase or decrease as a reaction to unilateral emission reductions. In this paper, we collect a comprehensive set of both positive and negative reactions and analyze them in stylized models. This allows us to identify the most important characteristics that determine the potential of a leader to boost mitigation efforts abroad. We find that this potential depends on (i) a strong ability to generate knowledge through leadership, (ii) a high degree of credibility in the international community, and (iii) a similar economic structure to the most important emitters. While most effects are difficult to quantify, this comprehensive assessment suggests that leakage effects resulting from unilateral mitigation may well be outweighed by positive reactions.     

Are China’s regional agricultural productivities converging: How and why?

This article tests the hypotheses of convergence to a single level of total factor productivity (TFP), and a steady state of TFP growth rate in China’s agricultural sector. Based on multilateral TFP estimates we found that China’s agricultural sector has rebounded in recent years from a slower TFP growth in the 2005–2007 period. While convergence test results confirm a “catch-up” effect that provinces with lower TFP levels tend to grow faster than others, estimated rates of β convergence are conditional on how we capture the heterogeneity effect across regions. The rates of β convergence range from 0.016 to 0.039 under different model specifications. Estimates show that higher growth rates of educational attainment, R&D, and intermediate goods density (per unit of labor) can enhance TFP growth. Unfortunately, there is no evidence of an overall σ convergence, indicating that TFP levels are not converging except in the South region. It implies that to catch up with leading provinces, it would require extra efforts for those lagging behind by increasing their region-specific research investment, promoting rural educational attainment, and enhancing embodied technical change.     

Interventions in Markets with Adverse Selection: Implications for Discount Window Stigma

I study the implications for central bank discount window stigma of a workhorse model of adverse selection in financial markets. In the model, firms (banks) need to borrow to finance a productive project. There is limited liability and firms have private information about their ability to repay their debts, which gives rise to the possibility of adverse selection. The central bank can ameliorate the impact of adverse selection by lending to firms. Discount window borrowing is observable and it may be taken as a signal of firms' credit worthiness. Under some conditions, firms borrowing from the discount window may pay higher interest rates to borrow in the market, a phenomenon often associated with the presence of stigma. I discuss these and other outcomes in detail and what they suggest about the relevance of stigma as an empirical phenomenon.