Does computer penetration increase farmers’ income? An empirical study from China

The diffusion and adoption of modern information technology provide new chance for China to close urban-rural income gap. This paper uses China's provincial panel data from 2002 to 2013 to investigate the effect of computer penetration on rural residents' income. A public program aiming to connect every village with broadband Internet and other rural facilities provides plausibly exogenous variation in rural residents' availability and adoption of the broadband Internet, which is used to explore the instrument variable for rural computer penetration. The results show that rural computer penetration tends to increase rural residents' income over time, but the average effect remains limited. The dynamic panel threshold effects model, which allows for both the threshold variable and other covariates to be endogenous, is further used to explore the constraints of the income-increase effect of rural computer penetration. It shows that the effect is at least doubled over the average effect estimated from instrument variables method, once the digital divide causes are removed. Our findings have important implications for the government to increase rural residents' income and reduce urban-rural income gap by encouraging rural computer usage and removing the digital divide.     

The dynamics of ex-ante weighted spread: an empirical analysis

We model the evolution of the ex-ante weighted spread (EWS) embedded in an open Limit Order Book (LOB) and investigate the impact of observed market-related variables on the spread. Our modeling involves decomposing the joint distribution of the weighted spread into simple and interpretable distributions. Our main results have several implications: (i) EWS features high persistence in autocorrelation; (ii) lower-level LOB remains liquid even after a high trade imbalance; (iii) lower- and higher-level LOB react to temporal spread change and trade imbalance in different ways; and (iv) both trade durations and quote durations have seasonality effects. We also show, through a simple high frequency trading exercise, that the use of the model can be economically important. Further, our model provides an estimation of market resilience.     

Which formula for national happiness?

The World Happiness Report is published by the United Nations Sustainable Development Solutions Network and contains an international ranking of national average happiness, as measured by surveys of personal life evaluations. It also contains an analysis which tries to explain the happiness figures from more than 150 countries using data on six key variables. That analysis assumes the factors combine in an additive manner and therefore operate independently of each other. By contrast, we explore a multiplicative model, which allows for interactivity or synergy between factors, as well as the possibility of diminishing marginal benefit at higher levels of achievement. We find that this model provides a better fit to the data and is therefore superior in its explanatory power. The implication for policy-makers is that they should focus on improving those factors which are the lowest for their nation as this will provide greater relative benefits to subjective well-being. At an individual level this means focusing on improving conditions for those who are experiencing the lowest levels of well-being.     

Collaboration and innovation: An empirical study of Indian technological enterprises

In 2010, the Indian government declared 2010–2020 to be the ‘Decade of Innovation’ and established the State Innovation Councils and Sectoral Innovation Councils to encourage and facilitate innovation by technological firms. In this paper, we study the relationship between collaboration and innovation in a cross‐section of Indian firms, paying particular attention to the impact of the innovation councils. Our results suggest that domestic collaborations have an important impact on firm innovation, as do the innovation councils, but that the impact of the councils is less for firms that collaborate.     

Personality traits,basic individual values and GMO risk perception of twitter users

Abstract

The present study investigates how the most foundational factors to individual differences – personality traits and personal values – affect the perceived safety of genetic modification and their relative importance. Publicly available communication data from 522 Twitter accounts discussing genetically modified foods and their safety was processed in two steps. First, accounts were categorized by the researchers as viewing GM foods as either safe or not safe. Second, using the IBM Watson platform, the Twitter communication data were subjected to lexical analysis to assign scores according to the Five Factor Model for personality traits and Schwartz’s basic individual values to the individual accounts. Logistic regression analyses were performed to determine how perceived GM food safety is linked to personality traits and individual values. Although both traits and values significantly contribute to explaining GM attitudes, personality traits strongly moderate the effect of individual values on risk perception.     

TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration

This article estimates agglomeration effects via calculating EG (Elilsion & Glaeser) and TFP growth (Total Factor Production) by considering the undesired output of the industrial enterprise database and the entropy weight method. Using panel data of 207 county-level cities in China and 28 two-digit manufacturing industries from 2003 to 2013 based on SIC codes, this paper analyzes the relationship between agglomeration and TFP growth through the smooth transition model under different regions and factor-intensity. The results are as follows. (1) A negative relationship appears in manufacturing productivity. The agglomeration effect changes to the crowded effect. Environmental pollution is also generated by transportation and inadequate pollution treatment technology. (2) The excessive agglomeration phenomenon of developed areas (eastern region) is less than the less developed areas (central and western regions). (3) Resource-intensity industries present two thresholds that indicate complex regional features. For various intensive industries in different regions, the relationship between GML and agglomeration is different. High agglomeration does not always promote TFP growth. (4) At different levels of urban industrial agglomeration, the influences of efficiency change and technical change on GML are different. Overall, moderate agglomeration in all regions helps promote economic development.     

The financial advice puzzle: The role of consumer heterogeneity in the advisor choice

We investigate motivational drivers of financial advisor use, accounting for investor heterogeneity, with the goal of helping institutions increase the use of financial advisor services. The results from a latent class choice model reveal two distinct segments that differ in their approach to the financial advice decision. While higher levels of risk tolerance, trust, and self-efficacy increase financial advice use for both segments, albeit at much higher propensities for Segment 1, personality only matters for Segment 1. Moreover, their regulatory focus differs with Segment 1 being promotion and Segment 2 being prevention focused. Using these results, we offer suggestions for marketing strategies.     

No‐arbitrage implies power‐law market impact and rough volatility

Market impact is the link between the volume of a (large) order and the price move during and after the execution of this order. We show that in a quite general framework, under no‐arbitrage assumption, the market impact function can only be of power‐law type. Furthermore, we prove this implies that the macroscopic price is diffusive with rough volatility, with a one‐to‐one correspondence between the exponent of the impact function and the Hurst parameter of the volatility. Hence, we simply explain the universal rough behavior of the volatility as a consequence of the no‐arbitrage property. From a mathematical viewpoint, our study relies, in particular, on new results about hyper‐rough stochastic Volterra equations.     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.     

Heterogeneity and netting efficiency under central clearing: A stochastic network analysis

This paper examines the effect of heterogeneity in clearing members’ exposure management practices under central clearing. Our network model specifies the dynamics of prenetted interbank exposures to shape interdependent exposure distributions beyond normality. Employing over-the-counter derivatives market data from the U.S. Office of the Comptroller of the Currency, our simulation results indicate that heterogeneity in bank-to-bank exposure dynamics is systemically desirable, while the entire system benefits more from the central clearing in more homogeneous environments. Policymakers should incentivize individual clearing members to enhance resiliency and stability in counterparty exposure management to maximize netting efficiency under central clearing.