Agroindustrialization through institutional innovation Transaction costs, cooperatives and milk-market development in the east-African highlands

Some small-holders are able to generate reliable and substantial income flows through small-scale dairy production for the local market; for others, a set of unique transaction costs hinders participation. Cooperative selling institutions are potential catalysts for mitigating these costs, stimulating entry into the market, and promoting growth in rural communities. Trends in cooperative organization in east-African dairy are evaluated. Empirical work focuses on alternative techniques for effecting participation among a representative sample of peri-urban milk producers in the Ethiopian highlands. The variables considered are a modern production practice (cross-bred cow use), a traditional production practice (indigenous-cow use), three intellectual-capital-forming variables (experience, education, and extension), and the provision of infrastructure (as measured by time to transport milk to market). A Tobit analysis of marketable surplus generates precise estimates of non-participants' 'distances' to market and their reservation levels of the covariates — measures of the inputs necessary to sustain and enhance the market. Policy implications focus on the availability of cross-bred stock and the level of market infrastructure, both of which have marked effects on participation, the velocity of transactions in the local community and, inevitably, the social returns to agroindustrialization.     

New development: All change? Performance assessment regimes in UK local government

Contrasting approaches to assessing the performance of public services highlight important issues for policy-makers and future research. We need systematic comparisons between countries. We should use a broader range of evidence. The public ought to have a greater role in designing performance criteria, and we need to know more about the impacts of assessments.     

African Agricultural Development: Lessons and Challenges

This paper reviews what has been learned from experiences of African agriculture and hence what policy lessons may be. Views of African agriculture over the last 130 years have changed from optimism to pessimism and at least halfway back again as the performance of the sector has fluctuated. Fortunately it seems the deep pessimism about agricultural prospects expressed in the 1980s and 1990s has receded. The performance of African agriculture since 1990 suggests that neither those who doubt that any significant advances are taking place, nor those who see advances in some remarkable but perhaps isolated cases of rapid transformation of farming and agricultural supply chains, have sufficient evidence – either from national data or small‐scale studies – to support their positions. Hence policy has to rely largely on general principles and historic lessons, rather than more clearly proven propositions. Policy debates over African agricultural development may sharply divide on some topics, but there is little debate over the importance of basic conditions for agricultural development of an enabling investment climate and the provision of rural public goods. Beyond these basics, the challenge is to remedy the failings of markets that deny most smallholders access to inputs, financial services and insurance. Here opinion divides between whether to return to public provision, as with fertiliser subsidies, or whether private and collective institutional innovations will be sufficient. Recent initiatives to test and scale up the latter look promising, but most have yet to be evaluated. If agricultural development is first and foremost about establishing the basic conditions for growth, then most countries in Africa may be better placed than they have been in the past. Given the many examples that show African smallholders investing and innovating when they have the chance, then there are reasons to hope that the modest growth of production and productivity seen in the last two decades may accelerate in the future – thereby allowing African countries to make the transition from agrarian to urban economies.     

具有智能交互的网络教学系统

由于在网络教学中,缺乏传统教学的灵活性,因此在网络教学中引入agent,设计基于浏览器/Agent/服务器的网络教学系统,并提出了各个模块的主要功能,使得网络教学更加智能化和个性化。     

Helpful Reviewers in TripAdvisor,an Online Travel Community

Online communities need a critical mass for communication, information, and entertainment and should provide useful information for their members in order to obtain this critical mass. The abundance of online travel reviews increases cognitive costs of travelers, and travelers use extrinsic cues to judge the quality of online reviews to eliminate costs associated with the information process. Of various cues used in online environments, this study examined an online reputation system in TripAdvisor.com and profiled the reviewers who post helpful reviews in the online travel community. The key findings include that helpful reviewers are those who travel more, actively post reviews, belong to any age and gender groups, and give lower hotel ratings. This study adds to research of online travel reviewers by characterizing helpful information creators among online content creators.     

On the Rate of Convergence of Discrete‐Time Contingent Claims

This paper characterizes the rate of convergence of discrete‐time multinomial option prices. We show that the rate of convergence depends on the smoothness of option payoff functions, and is much lower than commonly believed because option payoff functions are often of all‐or‐nothing type and are not continuously differentiable. To improve the accuracy, we propose two simple methods, an adjustment of the discrete‐time solution prior to maturity and smoothing of the payoff function, which yield solutions that converge to their continuous‐time limit at the maximum possible rate enjoyed by smooth payoff functions. We also propose an intuitive approach that systematically derives multinomial models by matching the moments of a normal distribution. A highly accurate trinomial model also is provided for interest rate derivatives. Numerical examples are carried out to show that the proposed methods yield fast and accurate results.     

Intraday Volatility in Interest‐Rate and Foreign‐Exchange Markets: ARCH,Announcement, and Seasonality Effects

We explore the determinants of intraday volatility in interest‐rate and foreign‐exchange markets, focusing on the importance and interaction of three types of information in predicting intraday volatility: (a) knowledge of recent past volatilities (i.e., ARCH or Autoregressive Conditional Heteroskedasticity effects); (b) prior knowledge of when major scheduled macroeconomic announcements, such as the employment report or Producer Price Index, will be released; and (c) knowledge of seasonality patterns. We find that all three information sets have significant incremental predictive power, but macroeconomic announcements are the most important determinants of periods of very high intraday volatility (particularly in the interest‐rate markets). We show that because the three information sets are not independent, it is necessary to simultaneously consider all three to accurately measure intraday volatility patterns. For instance, we find that most of the previously documented time‐of‐day and day‐of‐the‐week volatility patterns in these markets are due to the tendency for macroeconomic announcements to occur on particular days and at particular times. Indeed, the familiar U‐shape completely disappears in the foreign‐exchange market. We also find that estimates of ARCH effects are considerably altered when we account for announcement effects and return periodicity; specifically, estimates of volatility persistence are sharply reduced. Separately, our results show that high volatility persists longer after shocks due to unscheduled announcements than after equivalent shocks due to scheduled announcements, indicating that market participants digest information much more quickly if they are prepared to receive it. However, contrary to results from equity markets, we find no evidence of a meaningful difference in volatility persistence after positive or negative price shocks. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 517–552, 2001     

How do institutions affect corruption and the shadow economy?

This paper analyzes a simple model that captures the relationship between institutional quality, the shadow economy, and corruption. It shows that an improvement in institutional quality reduces the shadow economy and affects the corruption market. The exact relationship between corruption and institutional quality is, however, ambiguous and depends on the relative effectiveness of institutional quality in the shadow and corruption markets. The analytics also show that the shadow economy and corruption are substitutes. The predictions of the model are empirically tested and confirmed.     

Business Ethics on the Internet: 2

In a previous article the authors provided an introduction to using the internet as a resource for business ethics. In this sequel they look at newsgroups and chatrooms, and conclude by looking at the websites of Shell and a Shell critic on the controversial ethical aspects of its corporate policy and behaviour. Ben Fairweather is a Research Fellow, and Steve Dixon is Webmaster, at the Centre for Computing and Social Responsibility, De Montfort University, The Gateway, Leicester LEl 9BH, England (email: ccsr@dmu.ac.uk) (website http://www.ccsr.cms.dmu.ac.uk/).     

Analyst following and count-data econometrics

This paper reexamines the determinants of the number of analysts following a firm using econometric models based on count distributions. We replicate Bhushan's (1989) analyst-following study to demonstrate the effects of using count-data econometrics, in lieu of OLS, in studying phenomena where the dependent variable ranges among nonnegative integers. In contrast with the original paper, our findings indicate the number of institutional investors is inversely related with analyst following. We also provide econometric evidence to support the preferred use of the negative binomial model in estimating cross-sectional, analyst-following regressions.