Timing and Commitment of Environmental Policy,Adoption of New Technology,and Repercussions on R&;D

We investigate the interplay between environmental policy, incentives to adoptnew technology, and repercussions on R&D. We study a model where a monopolistic upstream firm engages in R&D and sells advanced abatement technology to polluting downstream firms. We consider four different timing and commitment regimes of environmental tax and permit policies: ex post taxation (or issuing permits), interim commitment to a tax rate (a quota of permits) after observing R&D success but before adoption, and finally two types of ex antecommitment before R&D activity, one with a unique tax rate (quota of permits), the other one with a menu of tax rates (permit quotas). We study the second best tax and permit policies and rank these with respect to welfare. In particular, we find that commitment to a menu of tax rate dominates all other policy regimes.     

Central bank disclosure as a macroprudential tool for financial stability

The Basel Capital Accord (pillar 3) states that disclosure of information (transparency) is essential to financial stability. This study analyzes, through inflation reports, the disclosure of information from the Central Bank of Brazil concerning the credit market. We consider credit risk and capital buffers as measures of financial stability in this analysis. Furthermore, in order to measure the perception of the monetary authority on the credit market, we built two indices based on the central bank’s communication on credit development. We performed a panel data analysis based on a sample of 125 banks for the period from June 1999 to September 2014 (7000 observations). The findings suggest that central bank communication regarding expectations concerning the credit market contributes to financial stability. Therefore, this kind of communication of central banks (about credit development) may constitute an important macroprudential tool to improve financial stability.     

Are there major differences in the attitudes and service quality of standard and seasonal employees? An empirical examination and implications for practice

Despite the increased use of seasonal employees by organizations, few studies have been completed on the attitudes and service quality of seasonal office workers. Using Lautsch's classification model, we analyzed the organizational context in which the standard and seasonal workers in this study were employed. Hypotheses were developed based upon the organizational analysis and social exchange theory. Results from archival data obtained from a web‐based organizational survey of 205 clerical and professional workers indicated contrary to expectations, standard and seasonal employees did not significantly differ in terms of perceptions of overall job conditions, perceived organizational support (POS), or job engagement. However, seasonal employees did report significantly fewer opportunities to work on challenging tasks, less comfortable physical working conditions, and less job security than the standard workers. As predicted, standard employees reported significantly higher levels of service quality performance than seasonal employees. Additionally, job engagement mediated the relationship between POS and service quality for both the standard and seasonal employees. Implications for managing seasonal employees are discussed.     

A dual‐sequence framework for B2C relationship formation: Moderating effects of employee communication style in online group chat

Past research on B2C relationships has typically focused on unidimensional constructs of satisfaction, trust, and commitment, ignoring underlying psychological dimensions. Although some studies have examined cognitive and affective dimensions of these relational constructs, dual sequential effects in relationship formation have not been investigated. This study proposes and finds (in the context of online group chat) that parallel cognitive and affective sequences of relationship formation take place, thus expanding scholarly understanding of underlying psychological processes and offering marketing practitioners two different ways to build relationships with consumers. The proposed dual‐sequence relational framework further advances theory by shedding light on counterintuitive findings in past research. The study also supports the proposed moderating effects of employee communication style, such that sequential effects of cognitive (affective) relational constructs are stronger with a task‐oriented (socially oriented) employee, thus offering insights to practitioners in hiring and training employees to match specific organizational goals for building relationships with consumers. © 2009 Wiley Periodicals, Inc.     

中国加入 WTO后房地产市场与国际市场接轨的答案

中国加入WTO后房地产市场与国际接轨的答案即应构建并发展房地产的二级市场和租赁市场 ,精心培育房地产的中介服务行业 ,同时改变粗放型的经营运作方式为精耕细作 ,以形成与一级市场联动完整的房地产大市场。     

Economic consequences of intifada

In 2003 the World Bank (WB) and the International Monetary Fund (IMF) published estimates of macro-economic indicators for 2002 of the economy of Palestine. The WB used a micro-founded recursive dynamic computable general equilibrium (CGE) model, calibrated on the 1998 Social Accounting Matrix (SAM) of Palestine, to which shocks were applied, whereas the IMF based its estimates on a macro-founded income-expenditure model relying on more recent data. It turned out that there were substantial differences: the estimate by the WB of the real gross national income (at 1998 prices) was 25% less than the corresponding figure calculated by the IMF. This huge difference is not only relevant for a full understanding of the economic consequences of the intifada, but also for the size of the international community intervention. In this paper we propose our own evaluation with the help of a static CGE model, based on the 1998 SAM and the so-called intifada shock derived from data of the WB that we constructed for the analysis of some forms of emergency assistance in a previous article. It turns out that our estimates, based on an entirely different methodology, are remarkably close to those of the IMF.     

Predicting Corporate Failure Using a Neural Network Approach

This paper investigates the performance of Artificial Neural Networks for the classification and subsequent prediction of business entities into failed and non-failed classes. Two techniques, back-propagation and Optimal Estimation Theory (OET), are used to train the neural networks to predict bankruptcy filings. The data are drawn from Compustat data tapes representing a cross-section of industries. The results obtained with the neural networks are compared with other well-known bankruptcy prediction techniques such as discriminant analysis, probit and logit, as well as against benchmarks provided by directly applying the bankruptcy prediction models developed by Altman (1968) and Ohlson (1980) to our data set. We control the degree of ‘disproportionate sampling’ by creating ‘training’ and ‘testing’ populations with proportions of bankrupt firms ranging from 1% to 50%. For each population, we apply each technique 50 times to determine stable accuracy rates in terms of Type I, Type II and Total Error. We show that the performance of various classification techniques, in terms of their classification errors, depends on the proportions of bankrupt firms in the training and testing data sets, the variables used in the models, and assumptions about the relative costs of Type I and Type II errors. The neural network solutions do not achieve the ‘magical’ results that literature in this field often promises, although there are notable 'pockets' of superior performance by the neural networks, depending on particular combinations of proportions of bankrupt firms in training and testing data sets and assumptions about the relative costs of Type I and Type II errors. However, since we tested only one architecture for the neural network, it will be necessary to investigate potential improvements in neural network performance through systematic changes in neural network architecture.