财政压力、技术创新与绿色全要素生产率

经济社会转型期典型的中国式"压力型"财政，对地方创新活动和绿色可持续发展具有重要影响。运用2004~2017年中国256个地级市面板数据，实证考察了财政压力对绿色全要素生产率的影响以及传导机制。基准检验结果显示，财政压力显著抑制了绿色全要素生产率的提升，技术创新对绿色全要素生产率具有显著的促进作用；中介效应检验发现，财政压力通过抑制技术创新进而阻碍绿色全要素生产率的提升，即验证了财政压力→技术创新→绿色全要素生产率的传导机制；进一步门槛效应检验表明，技术创新对绿色全要素生产率的影响存在基于财政压力的双门槛效应，在财政压力的不同门槛值区间，技术创新对绿色全要素生产率的促进效应呈现出明显的阶梯性降低趋势。未来需综合完善中国式"压力型"财政激励制度，合理控制财政压力的区间范围，助力技术创新以提升城市绿色全要素生产率。     

Migration,population aging,and income inequality in China

In this study, we examine the effects of four demographic factors, namely, birth, death, natural aging, and net migration, on population aging and income inequality in China. We use the official Chinese data and the China Household Income Project Survey data for the 2007–2013 period and apply a decomposition model based on the Shapley method. Unlike previous studies, we include migration in our decomposition model and find that natural aging is the primary factor contributing to population aging in both urban and rural areas. Further, migration may accelerate population aging in rural areas. Moreover, migration contributes to reducing income inequality in urban areas, while widening income inequality in rural areas. The effect of migration is larger than those of birth, death, and natural aging on income inequality. The robustness checks confirm these conclusions.     

Factor extraction using Kalman filter and smoothing: This is not just another survey

Dynamic factor models have been the main “big data” tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing data, mixed frequency data, time-varying parameters, non-linearities, non-stationarity, and many other characteristics often observed in real systems of economic variables. The main contribution of this paper is to provide a comprehensive updated summary of the literature on latent common factors extracted using KFS procedures in the context of dynamic factor models, pointing out their potential limitations. Signal extraction and parameter estimation issues are separately analyzed. Identification issues are also tackled in both stationary and non-stationary models. Finally, empirical applications are surveyed in both cases. This survey is relevant to researchers and practitioners interested not only in the theory of KFS procedures for factor extraction in dynamic factor models but also in their empirical application in macroeconomics and finance.     

Perseverance and suspense in tug-of-war

We study a tug-of-war game between two players using the lottery contest success function (CSF) and a quadratic cost (of effort) function. We construct a pure strategy symmetric Markov perfect equilibrium of this game, show that it is unique, and provide closed-form solutions for equilibrium strategies and values. In stark contrast to a model of tug-of-war with an all-pay auction CSF, players exert positive efforts until the very last battle in this equilibrium. We deliver a set of empirically appealing results on effort dynamics.     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.     

老龄化与碳排放：消费效应还是生产效应？——基于2002-2017年中国省级面板数据的实证研究

人口老龄化是经济增长的一大阻碍,它对碳排放的影响是做出环境政策抉择的关键因素.以中国2002—2017年的省级面板数据为研究样本,从理论与实证两个层面分析人口老龄化与碳排放的关系及影响机制.一方面,构建包含碳排放的世代交叠模型(overlapping generations,OLG),发现老龄化主要通过消费效应和生产效应两个路径对碳排放产生影响;另一方面,从实证层面发现老龄化与碳排放之间存在倒"U"形关系,而且消费效应在人口老龄化与碳排放的关系中起到部分中介作用,生产效应的影响则不显著.     

Spillovers between sovereign CDS and exchange rate markets: The role of market fear

As important variables in financial market, sovereign credit default swaps (CDS) and exchange rate have correlations and spillovers. And the volatility spillovers between the two markets become further complicated with the effect of market fear caused by extreme events such as global pandemic. This paper attempts to explore the complex interactions within the “sovereign CDS-exchange rate” system by adopting the forecast error variance decomposition method. The results show that there is a relatively close linkage between the two markets and the total spillover index of the system is dynamic. For most of the past, the exchange rate has a higher spillover effect on the sovereign CDS than vice versa. Moreover, after the market fear variables are introduced, the “sovereign CDS-exchange rate” system and market fear variables present bidirectional spillovers. The results of the study have particular significance for maintaining the financial stability and preventing risk contagion between markets.     

Does online observational learning matter? Empirical evidence from panel data

The information presented on a product sales page plays an important role in consumers' purchase decisions. This study examines the persuasive effect, whether a customer's choice is heavily driven by information inferred from others' behavior, and how these impacts are moderated by market age and product type. Results show that online customer choice was significantly affected by historical cumulative sales and times saved. Positive cumulative sales and shop service quality have a significant positive impact on product sales. The times saved have no direct impact on product sales. For different types of products, the times saved of experiential products has a significant impact on product sales, while the shop service quality information of search products has a greater impact on product sales. The influence of online observation learning on product sales will be significantly moderated by a combination of product type and market age. These findings not only offer important theoretical contributions to e-commerce research but also provide practical implications for online sellers and managers of social commerce platforms.     

Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.