房产税能否抑制实体经济"脱实向虚"——来自上海和重庆的经验分析

本文利用我国35个大中城市2006-2018年的平衡面板数据,基于上海和重庆在2011年实施的房产税试点政策,运用合成控制法检验房产税政策能否抑制实体经济"脱实向虚"发展的趋势.研究结果显示,房产税政策能够有效地遏制地区房地产业新增产值占GDP的比重的上升,促使实体企业回归主业,增加实体投资,实现促进实体经济朝着"脱虚返实"方向发展的作用.鉴于此,本文提出应加快推进房产税政策在全国范围内的实施,并在政府补贴、银行贷款等方面采取一系列配套措施鼓励实体企业进行更多的实体投资.     

Factor Heterogeneity,Factor Market Imperfection and Trade

This paper develops a tractable model of examining how factor heterogeneity and imperfect factor market interact for determining a pattern of trade. Institution plays a crucial role for the interaction. In my work, firm productivity is defined as a composition of factor productivity and technology. Thus, input selection should affect the pattern of Melitz’s intra-industry allocation due to the incurring transaction cost. For a simple model, I assume two factors (labor and capital) and two sectors, which are relatively less institution-dependent and relatively more institution-dependent. When the economy is open, effect of the transaction cost on income distribution is more drastic for an institutionally underdeveloped country. Depending on institutional quality, the economic openness reallocates resource across countries through job creation or job destruction. The job turnovers redistribute income between heterogeneous labors within countries. The income redistribution is catalyzed by international mobility of capital. As a result, income disparity is widened between the institutionally developed country and the institutionally underdeveloped country. This paper can contribute to the literature of institution and international trade.     

关于企业成本管理的探讨

成本管理是预算管理和绩效管理的前提,企业需要正确地将成本进行分类、计量和归集。恰当的成本管理制度可以帮助企业提升运营效率和业务绩效,同时企业的流程改善、突破和优化与成本管理密不可分。另外,管理者需要令客户对产品和服务满意,并且有效控制各项成本。企业成本管理不是单纯地降低成本,而是通过利用成本分析工具,有效地管理和规划资源,进而提高总体运营效率,保证企业总体绩效的持续改善。论文通过成本计算制度的制定方法和业务流程改善分析技术两方面对成本管控进行探讨。     

Unfolding the impact of leadership and management on sustainability performance: Green and lean practices and guanxi as the dual mediators

This study aims to empirically evaluate the predictors that influence sustainability performance among manufacturing firms. Leadership and management, green and lean practices, and guanxi were examined to determine whether these predictors are directly and/or indirectly affecting sustainability performance; 160 valid responses were collected and partial-least-squares-structural-equation-modeling (PLS-SEM) was used to analyze the data. The results showed that leadership and management positively influenced green and lean practices and green and lean practices positively influenced sustainability performance. Leadership and management also positively influenced guanxi. Interestingly, leadership and management and guanxi do not exert a significant direct influence on sustainability performance. The findings contributed to the development of the resource-based-view theory further by empirically exploring the significance of leadership and management coupled with green and lean practices as competencies and capability to drive sustainability performance. The testing of the dual mediators' effects further added value to this study.     

Allegations of Sexual Misconduct: A View from the Observation Deck of Power Distance Belief

Journal of Business Ethics - We seek to understand how third-party observers respond to allegations of sexual transgressions, whether their responses vary and if so why, how they determine...     

The effects of power on consumers’ evaluation of a luxury brand's corporate social responsibility

This paper examines how power affects consumers’ responses to corporate social responsibility (CSR) initiatives of luxury brands. The results of three studies show that high‐power individuals evaluated a luxury brand's CSR campaign more positively than low‐power individuals. High‐power individuals viewed CSR activities as being more fluent than low‐power individuals. This study further demonstrates that power influences consumers’ responses to nonluxury brand's CSR activities. Low‐power individuals, who are more receptive to warmth, evaluated nonluxury brand's CSR more favorably rather than high‐power individuals.     

The Moderating Effects of Status-Consumption Motive and Age in the Relationship between CSR Advertising Appeal Type and Purchase Intentions

The primary purpose of this study was to examine factors that influence the effectiveness of benefit appeal types (i.e., help-other vs. help-self) in Corporate Social Responsibility advertising. To that end, we designed and administered a between-subjects experiment where participants viewed one of the two CSR advertisements crafted with help-self and help-other benefit appeals. Results provided evidence supporting the moderating effects of status-consumption motives and age on purchasing intentions. Additional analysis suggested consumers younger than 48 years old were more likely to be persuaded by a help-other ad appeal when they didn't have strong desires for status consumption. Results were discussed in light of the self-concept theory and value-expressive framework in CSR advertising.     

Lobbying as a potent political marketing tool for firm performance: A closer look

This study endeavors to enhance political marketing literature about the impact of lobbying on firm performance. Our sample is composed of 140 U.S. firms and spans the years 2007–2014 to encompass the 2007–2009 recession and the subsequent recovery period. Our findings indicate that lobbying expenses positively contribute to firm performance. Also, government contracts in both ways, dollar amount and number of government contracts, act as mediators between lobbying expenses and firm performance. In addition, organizational slack moderates the relationship between lobbying expenses and government contracts. The managerial implications suggest that lobbying expenses can be leveraged as a potent tool for firm performance. Firms with larger lobbying efforts acquired both, higher dollar amounts and a greater number of government contracts.     

Plausible versus implausible tensile price claim: Selective accessibility model approach

Retailers frequently use exaggerated price discount advertisements with a tensile price claim (TPC; e.g., “Save up to 70%”) to attract consumers because they expect that once consumers enter a store, they will purchase low‐ or medium‐discounted products. Drawing on the selective accessibility model, this study investigated the way in which an implausibly high maximum level of savings stated in a TPC influences consumers’ expected price discount (EPD) and perceptions of actual price discounts across different types of TPCs (i.e., TPC stating a maximum level and TPC stating a range of savings). This study also investigated two situations in which consumers have previous knowledge of a product’s price discount versus when they have less or no knowledge of the discount. For both conditions, a single‐anchor TPC (i.e., “Save up to Y%”) that stated an implausible maximum level of savings led to a higher EPD and lower perceptions of the deal (i.e., perceived savings, price fairness, and perceived value) with respect to the actual price discount than did a TPC with a plausible maximum level of savings. In contrast, when the TPC stated two anchors (i.e., “Save X–Y%”) and consumers had knowledge of the price discount, their EPDs assimilated only toward the plausible anchor (X), and ignored the implausibly high maximum price discount (Y), resulting in a lower EPD and higher perceptions of the deal of the actual price discounts than a TPC that stated a plausibly high maximum level of savings. In contrast, when consumers had no knowledge of the price discount, their EPDs only adjusted toward the more plausible anchor (X), regardless of whether they perceived the maximum anchor as plausible or implausible. Thus, there was no difference in consumers’ perceptions of “Save X–Y%” between implausibly and plausibly high Y%.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.