发挥经济金融杠杆作用促进房地产市场健康发展

当前城市住房价格上涨过快,房价水平偏高是我省房地产市场发展中的一个突出问题,引起了社会各方的关注，需要认真加以分析研究，并有的放矢地采取措施解决当前存在的突出问题。促进房地产市场健康发展。     

金融系统应在节约型社会的建设中发挥杠杆作用

金融是现代经济的核心,要想实现建设资源节约型社会的战略任务,金融系统能够也必须发挥重要的作用。金融系统不仅自身应当以建立“节约型行业”为目标,更应该发挥其特殊的“杠杆”效应,结合财政政策、产业政策等国家宏观调控手段,共同实现我国经济增长形式的转变和产业结构的调整,以最小代价实现资源的有效配置,从而减少资源浪费,共建节约型社会。     

论欠发达地区如何发挥金融杠杆作用

金融是现代经济建设的核心,是支持经济发展的杠杆,金融已日益广泛地渗透到社会经济生活的各个方面,可以说,“金融搞好了,一着棋活,全盘皆活”。当前,金融在欠发达地区的地位越来越高、作用越来越大、任务也越来越重。     

对区域金融中心建设促进安徽省经济金融协调发展的思考

金融是现代经济的核心,在经济社会发展中的地位日益重要。当前我国金融整体改革和金融资源统筹整合已进入了关键时期,构建多层次、功能互补的金融中心,对促进区域经济协调发展具有积极和重要的意义。本文围绕打造合肥金融中心对于促进安徽省经济社会科学发展的重要意义,以及合肥市金融业发展的基础条件进行了研究分析,并就如何引导合肥金融业发展,进而促进安徽省经济社会持续协调发展提出了对策建议。     

发挥金融杠杆作用 推进国有企业改革

今年以来,特别是十五届四中全会以来．人民银行南京分行积极组织辖内各级金融部门．认真学习十五届四中全会精神,按照国家的统一部署,结合苏皖两省国有企业的实际情况,发挥货币信贷政策的作用,努力加大对国有企业的信贷投入,加强银企合作,进一步推广实施主办银行制度,认真做好封闭贷款的发放和管理工作,     

以区域金融中心建设促进龙头作用的发挥

<正>一、充分认识金融在区域经济发展中的重要作用作为半岛城市群和全省经济发展的龙头城市,近几年来,在省委、省政府的正确领导下,在兄弟城市和各级金融部门的大力支持下,青岛经济社会发展进入了一个崭新的历史阶段,各项工作都取得了显著成绩,已经成为全省开放度最高、经济活力最强、最具竞争力的地区之一。2007年,预计全市     

发挥金融杠杆作用助推县域经济发展

去年四季度以来,为应对复杂多变的国际经济形势,中央决定实行积极的财政政策和适度宽松的货币政策。同时,出台了一系列扩大内需、促进经济增长的措施。在此宏观经济、金融形势下,如何有效发挥金融作用,促进地方经济发展,是摆在我们面前的一个重要课题。     

郑州区域金融中心建设与中原城市群金融发展关系研究

通过金融资源在一定空间的集聚与辐射效应,区域金融中心和城市群形成了互相促进、协调发展的良性互动。研究郑州区域金融中心建设与中原城市群金融发展的关系,对于推动中原城市群科学发展,探寻中原城市群发展新路径,确定中原城市群金融发展时序,实现中原城市群金融资源战略整合具有重要的理论价值和现实意义。政府应确立郑州区域金融中心优先发展战略,大力发展地方商业金融机构,创新中原城市群金融机构合作机制,改善中原城市群金融生态环境状况。     

The relationship between operating leverage and financial leverage

We model the relationship between operating and financial leverage. When operating leverage is exogenously specified, financial leverage is a monotonically decreasing function of operating leverage. When financial leverage is exogenously specified, operating leverage is initially increasing and subsequently decreasing in financial leverage. Finally, when both operating and financial leverage are chosen by the firm, they can be positively related, negatively related or unrelated, depending on which underlying parameter is driving the changes. Thus, operating leverage and financial leverage do not always behave as substitutes, as argued in the traditional literature. The relationship is complex, possibly non-monotonic and dependent on the circumstances; empirical tests need to take this reality into account.     

Adjusted accounting beta,operating leverage and financial leverage as determinants of market beta: A synthesis and empirical evaluation

This article reexamines and synthesizes two streams of research dealing with the relationship between market beta and accounting risk measures. It is shown that, with some minor rearrangement the Mandelker and Rhee (1984) model can be shown to be as a decomposition of the familiar accounting beta (Beaver, Kettler and Scholes 1970) into operating leverage, financial leverage, and an adjusted accounting beta. The adjusted accounting beta can be further decomposed into productivity gains and the relative cyclical sensitivity of the accounting flows of the firm. Empirical estimates of this extension made using three accounting flow measures in addition to earnings show that the intrinsic business risk factor not identified in the original Mandelker and Rhee model is the most significant explanatory factor related to market beta.     

Taming polysemous signals: The role of marketing intensity on the relationship between financial leverage and firm performance

This study traces the degree of integration and volatility spillover effect between the Pakistani and leading foreign stock markets by analyzing the Meteor shower hypothesis. Daily data are used from nine worldly equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period of 2005 to 2014. First, we used the whole data set and after that we split data set into two subsets, First subset of data contains the era of global financial crisis of 2008 from 2005 to 2009 and Second subset is after global financial crisis time period from 2010 to 2014 (The global crisis prevailed till end of 2009). By following the Hamao et al. (1990) technique the univariate GARCH type models are employed to explore the dynamic linkages between Pakistani and leading foreign stock markets. The results from whole data set illustrate that there is mixed co‐movements between leading foreign stock markets and Pakistani stock market. The results from both subsets provide an evidence that there is a unidirectional mean and volatility spillover effect from S&P 500, NASDAQ 100, DJI and DFMGI to KSE 100. Also we found bidirectional spillover effect between DFMGI and KSE 100 from both subsets of data. We concluded that there is only one indirect linkage through which may the information transmitted to KSE 100. This linkage is developed due to the co‐movement among KSE 100, DFMGI and NASDAQ 100 in crisis period. This integration between these markets may provide a sign of indirect linkage. It also exhibits the volatility in Pakistan stock market returns is instigated through direct effects as well as indirect effects. Our study brings important conclusions for financial institutions, portfolio managers, market players and academician to diagnose the nature and level of linkages between the financial markets.     

An additional analysis of estimation techniques for the degree of financial leverage

This study compares three different empirical proxies for the financial leverage component of a systematic risk‐composition model employed in prior financial research. We consider one static accounting measure and two elasticity‐based measures. We find that the traditional static accounting measure of financial leverage provides statistically different estimates of financial leverage when compared to estimates from elasticity‐based measures of the degree of financial leverage. The findings are important because the elasticity‐based models for the degree of financial leverage have clear theoretical links to market‐based models of systematic risk, while the static accounting measure of financial leverage does not. Practitioners and researchers should carefully consider why they are estimating financial leverage and choose the appropriate method for doing so given the goals and potential consequences for biased estimation.     

What explains the value premium? The case of adjustment costs,operating leverage and financial leverage

This paper empirically examines and compares the different theoretical predictions on how adjustment costs, operating and financial leverage influence the value premium. Consistent with Ozdagli (2012), financial leverage plays a dominant role, supported by adjustment costs (which represent the degree of investment irreversibility). Specifically, the observed value premium is driven by the financial leverage differences between value and growth firms, partially neutralized by investment irreversibility. The relation between the value premium and investment irreversibility is contrary to the intuition in Zhang (2005) and Cooper (2006). Operating leverage does not significantly influence the value premium.     

The effect of financial leverage on real and accrual-based earnings management

Past research has documented a substitution effect between real earnings management (RM) and accrual-based earnings management (AM), depending on relative costs. This study contributes to this research by examining whether levels of (and changes in) financial leverage have an impact on this empirically documented trade-off. We hypothesise that in the presence of high leverage, firms that engage in earnings manipulation tactics will exhibit a preference for RM due to a lower possibility – and subsequent costs – of getting caught. We show that leverage levels and increases positively and significantly affect upward RM, with no significant effect on income-increasing AM, while our findings point towards a complementarity effect between unexpected levels of RM and AM for firms with very high leverage levels and changes. This is interpreted as an indication that high leverage could attract heavy outsider scrutiny, making it necessary for firms to use both forms of earnings management in order to achieve earnings targets. Furthermore, we document that equity investors exhibit a significantly stronger penalising reaction to AM vs. RM, indicating that leverage-induced RM is not as easily detectable by market participants as debt-induced AM, despite the fact that the former could imply deviation from optimal business practices.     

A two-part fractional regression model for the financial leverage decisions of micro,small, medium and large firms

In this paper we examine the following two hypotheses, which traditional theories of capital structure are relatively silent about: (i) the determinants of financial leverage decisions are different for micro, small, medium and large firms; and (ii) the factors that determine whether or not a firm issues debt are different from those that determine how much debt it issues. Using a binary choice model to explain the probability of a firm raising debt and a fractional regression model to explain the relative amount of debt issued, we find strong support for both hypotheses. Confirming recent empirical evidence, we find also that, although larger firms are more likely to use debt, conditional on their having some debt, firm size is negatively related to the proportion of debt used by firms.     

The relative influence of competitive intensity and business strategy on the relationship between financial leverage and performance

This study empirically investigates the effects of competitive intensity and business strategy on the relationship between financial leverage and the performance of firms. Based on a sample of US manufacturing firms, this study confirms the hypothesis that the cost of debt is higher for product differentiation firms than cost leadership firms. Furthermore, the results indicate that competitive intensity has a negative effect on the leverage-performance relationship, suggesting that competition acts as a substitute for debt in limiting manager's opportunistic behavior. These findings reinforce the need to consider moderating factors such as strategic choice and the environment in which a firm operates when investigating the effects of leverage on performance.     

The role of on- and off-balance-sheet leverage of banks in the late 2000s crisis

Extensive regulatory changes and technological advances have transformed banking systems to a great extent. Banks have reacted to the challenges posed by the new operating environment by creating new products and expanding their activities to some uncharted business areas. In this paper, we study how modern banking which gave birth to the off-balance-sheet leverage activities affected the risk profile of U.S. banks as well as the level of systemic risk before and after the onset of the late 2000s financial crisis. Towards this, we separate on- from off-balance-sheet leverage and capture the latter with different, yet complementary, measures which do not exist in the current literature. Special attention is paid on the deleveraging process that occurred in the banking market after the crisis erupted, which is an additional innovative feature of this study. Our findings reveal that leverage, both explicit and hidden off-the-balance-sheet, increases the individual risk of banking firms making them vulnerable to financial shocks. Reverse leverage, on the other hand, is beneficial for individual banks’ health, but is found to be harmful for financial stability. We also demonstrate that the banks which concentrate on traditional lines of business typically carry less risk compared to those involved with modern financial instruments.     

Local social environment and the speed of leverage adjustment

This study examines the impact of social capital on firms’ leverage adjustment speed. Using a comprehensive dataset of 83,374 firm-year observations for 744 US counties for 1990–2016, we find that both underleveraged and overleveraged firms located in US counties with higher levels of social capital incur slower leverage adjustment towards their optimal target capital structure. This finding is robust to alternative measures of leverage and social capital, different model specifications, controlling for county- and firm-level characteristics, and endogeneity. We further identify two mechanisms through which social capital affects leverage adjustments: monitoring (channel for underleveraged firms) and disciplinary (channel for overleveraged firms) mechanisms.