自由现金流量创造力与违约风险——来自A股公司的经验证据

本文基于我国A股上市公司数据,研究了企业自由现金流量创造力与违约风险之间的关系。研究发现：(1)企业自由现金流量创造力越强,其违约风险越低。经过一系列稳健性检验后,该结论依旧成立。(2)自由现金流量创造力越强的企业往往有更低的债务规模、更高的资产收益率和更低的股票波动,因而其违约风险更低。(3)自由现金流量创造力与违约风险的负相关关系,主要存在于货币政策紧缩时期以及外部信息环境较差的企业。本文发现意味着,监管部门和投资者应重视上市公司自由现金流量创造力不足所带来的潜在债务违约风险,通过不断提高公司自由现金流量创造力,助力我国宏观经济与微观企业高质量发展。     

Welfare‐at‐Risk and Extreme Dependency of Regional Wheat Yields: Implications of a Stochastic CGE Model

Stochastic computable general equilibrium (CGE) models have ignored regional correlations in agricultural yields, assuming random shocks to be independent between regions. This could lead to misinterpretation of simulation outputs which ignore extreme positive or negative harvests at the global scale. We develop a multi‐regional CGE model which allows for five types of interregional correlation between wheat yields to analyse the vulnerability of countries against fluctuating international markets, focusing on Value at Risk (VaR) and extreme dependency. We find that global welfare risks could be underestimated by up to 33% if significant interregional correlations in yield shocks are not taken into account. Egypt, Kazakhstan, Ukraine, the former Soviet Union and Northern Africa are particularly vulnerable to global volatilities in terms of economic welfare.     

The effect of output growth volatility on output growth: empirical evidence from Turkey

This article assesses the effect of output growth volatility on output growth within a stochastic-volatility-in-mean model with a time-varying framework for an open small economy: Turkey. Until now, the empirical evidence on industrial production mainly reveals that this relationship is negative. However, in further examining different sectors and sub-sectors of industrial production, we find the sign of the relationship changes depending on the sector. Moreover, there is limited evidence that the sign of the relationship changes over time. Thus, the evidence reveals that the nature of the output growth volatility–output growth relationship is not uniform across sectors.     

Asset price bubbles and crashes with near-zero-intelligence traders

Summary. We examine whether a simple agent-based model can generate asset price bubbles and crashes of the type observed in a series of laboratory asset market experiments beginning with the work of Smith, Suchanek and Williams (1988). We follow the methodology of Gode and Sunder (1993, 1997) and examine the outcomes that obtain when populations of zero-intelligence (ZI) budget constrained, artificial agents are placed in the various laboratory market environments that have given rise to price bubbles. We have to put more structure on the behavior of the ZI-agents in order to address features of the laboratory asset bubble environment. We show that our model of near-zero-intelligence traders, operating in the same double auction environments used in several different laboratory studies, generates asset price bubbles and crashes comparable to those observed in laboratory experiments and can also match other, more subtle features of the experimental data.Received: 15 July 2003, Revised: 28 September 2004, JEL Classification Numbers: D83, D84, G12. Correspondence to: John DuffyWe would like to thank an Anonymous referee, Guillaume Frechette, David Laibson, Al Roth and participants in Harvard Experimental and Behavioral Economics Workshop for their comments, and Charles Noussair for providing his data set.     

Public Procurement Auctions and Competition in Turkey

This paper empirically investigates the effect of the competitive environment (number of participants) on the cost of procurement. We use a unique dataset provided by the Public Procurement Authority (PPA) of Turkey that covers all of the government procurement auctions for the years 2004–2006. First, after controlling for possible endogeneity, we show that the number of bidders significantly and negatively affects the procurement price. Thus, the existence of a more competitive environment significantly decreases procurement costs in Turkey. Second, when auctions are open to foreign participation, the auction price tends to be lower. Finally, prices in services and goods sectors are more sensitive to changes in the number of bidders than is true for the construction sector. The results of this paper have several policy implications for e-procurement and efficient procurement design.     

Unraveling a puzzle: the case of value line timeliness rank upgrades

We examine a sample of Value Line’s timeliness rank upgrades that occur immediately following earnings announcements and find that pre-event price momentum has significant incremental explanatory power for post-event drift, after controlling for the level of earnings surprise. Therefore, the stock price drift following Value Line’s timeliness upgrades cannot be viewed as driven only by the post-earnings announcement drift phenomenon. Instead, these findings indicate that, among other factors, Value Line has been exploiting the price momentum effect for decades. Black (Financ. Anal. J. 29:10–14, 1973) clearly stated that it does indeed do this, but his assertion has not yet been verified as an explanation of the puzzling drift that follows Value Line rank upgrades.     

How much does KIBS contribute to the generation and diffusion of innovation?

This article aims to estimate the contribution of KIBS to the innovation system. Data on innovation gathered from national and European databases are analyzed using a methodology based on an input–output framework to estimate the drive for innovation in the Spanish economy and the contribution of KIBS. KIBS are found to be crucial to both the creation and diffusion of innovation. From among the four classifications of sectors analyzed herein, KIBS is found to be the only significant net generator of innovation.     

Pecking Order Theory versus Trade-Off Theory: are service SMEs�� capital structure decisions different?

This paper seeks to analyse if the capital structure decisions of service small and medium-sized enterprises (SMEs) are different from those of other types of firm. To do so, we consider four research samples: (i) 610 service SMEs; (ii) 126 service large firms; (iii) 679 manufacturing and construction SMEs; and (iv) 132 manufacturing and construction large firms. Using the two-step estimation method, the empirical evidence obtained in this study shows that the capital structure decisions of service SMEs are different from those of other types of firm. Service SMEs’ capital structure decisions are closer to the assumptions of Pecking Order Theory and further removed from those of Trade-Off Theory compared with the case of other types of firm.     

Land Value: Seven Major Questions in the Analysis of Urban Land Values

A review of the literature on land and its value reveals seven sources of ambiguity: 1) a precise definition of the type of land under investigation is frequently absent, 2) the temporal, and 3) the spatial aspects of the land value attributes might be inconsistently specified, 4) the relevance of the valuation methods used is often overlooked, 5) the separate land value is a mere by‐product of the total property value as a rule, and thus lacks proper focus, 6) the different agents involved in land markets are not always taken into account, and finally, 7) the explanations for the unpredictable aspects of land value are sporadic. This article explores each of these areas of ambiguity.     

Learning About Computers: An Analysis of Information Search and Technology Choice

We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs). To estimate the model, we use a panel data set that contains the search and purchase behavior of a set of consumers who were in the market for a PC. The data includes the information sources visited each period, search durations, as well as measures of price expectations and stated attitudes toward the alternatives during the search process. Our model extends recent work on estimation of Bayesian learning models of consumer choice behavior in environments characterized by uncertainty by estimating a model of active learning—i.e., a model in which consumers make optimal sequential decisions about how much information to gather prior to making a purchase. Also, following the suggestion of Manski (2003), we use our data on price expectations to model consumers’ price expectation process, and, following the suggestion of McFadden (1989a), we incorporate the stated brand quality information into our likelihood function, rather than modeling only revealed preference data.Our analysis sheds light on how consumer forward-looking price expectations and the process of learning about quality influence the consumer choice process. A key finding is that estimates of dynamic price elasticities of demand exceed estimates that ignore the expectations effect by roughly 50%. This occurs because our estimated expectations formation process implies that consumers expect mean reversion in price changes. This enhances the impact of a temporary price cut. Finally, while our work focuses specifically on the PC market, the modeling approach we develop here may be useful for studying a wide range of high-tech, high-involvement durable goods markets where active learning is important.JEL Classification: C15, C33, C35, C42, C51, C52, D83, D84