Patterns of Entry,Post-Entry Growth and Survival: A Comparison Between Domestic and Foreign Owned Firms

This study compares the patterns of entry, survival and growth of domestic and foreign owned firms. We show that the post-entry behavior of foreign owned firms is quite different from that of their domestic counterparts. Among foreign entrants, we were able to distinguish between those which proceed by creating a new firm and those that acquire an already existing business. Our evidence reveals that the choice of the mode of entry in foreign markets exerts an impact upon the performance of firms that persists long after the moment of entry. As a consequence, our work clearly indicates that there is much to be gained in the understanding ofthe process of entry in foreign markets by studying the behavior of entrants over their first years in these markets.     

Regional innovation and small high technology firms in peripheral regions

This paper highlights the difficulty of developing HT firms in a peripheral region of Spain. Although the endogenous development of HT firms in these regions is possible, their evolution depends on more central regions. The firm's geographical location and the type of HT production are the most important endogenous factors governing the firm's success.     

The dynamics of positive action in UK trade unions: the case of women and black members

This paper considers positive action strategies amongst UK trade unions, aimed at increasing membership and levels of participation and representation among women and black workers. It provides an overview of women’s, black members’ and race structures within large Trades Union Congress unions and a detailed case study of one large UK trade union. We find that there are salient differences in the way that unions approach issues of gender equality, compared with the approach adopted towards race equality. The paper explores possible explanations, justifications and implications of these differences.     

General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions*

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper, we propose general‐to‐specific (Gets) model selection procedures to overcome these limitations. It is shown that single‐equation procedures are generally efficient for the reduction of recursive SVAR models. The small‐sample properties of the proposed reduction procedure (as implemented using PcGets) are evaluated in a realistic Monte Carlo experiment. The impulse responses generated by the selected SVAR are found to be more precise and accurate than those of the unrestricted VAR. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (Review of Economics and Statistics, Vol. 78, pp. 16–34, 1996) . The results are consistent with the Monte Carlo and question the validity of the impulse responses generated by the full system.     

Syndicated Loan Announcements and Borrower Value

Announcements of syndication loans increase borrowers' shareholder wealth if they are revolving credit agreements but not if they are term loans. Share price responses to revolving credit announcements are positive and significant, whereas the wealth effect for term loans is negative and significant. The results show that announcements from both the financial press and commercial information providers can affect borrower share price reaction. Overall, single syndication announcements appear to be more newsworthy than multiple announcements reported in the financial press, and we find evidence of information leakage, post‐announcement drift, or both.     

Noise Trading and the Management of Operational Risk; Firms,Traders and Irrationality in Financial Markets*

abstract Efficient market models cannot explain the high level of trading in financial markets in terms of asset portfolio adjustment. It is presumed that much of this excessive trading is irrational ‘noise’ trading. A corollary is that there must either be irrational traders in the market or rational traders with irrational aberrations. The paper reviews the various attempts to explain noise trading in the finance literature, concluding that the persistence of irrationality is not well explained. Data from a study of 118 traders in four large investment banks are presented to advance reasons why traders might seek to trade more frequently than financial models predict. The argument is advanced that trades do not simply occur in order to generate profit, but it does not follow that such trading is irrational. Trading may generate information, accelerate learning, create commitments and enhance social capital, all of which sustain traders' long term survival in the market. The paper treats noise trading as a form of operational risk facing firms operating in financial markets and discusses approaches to the management of such risk.     

The dynamics of moonlighting in Russia1

This paper uses the Russian Longitudinal Monitoring Survey (RLMS) to analyse the dynamics of moonlighting by the working‐age population. We find that moonlighting is transitory and that a desire to switch jobs expressed in the past is positively related to moonlighting in the present and to actual job changes in the future. We also find that workers who moonlighted as self‐employed in the past represent 26.5 percent of the new self‐employed. These results suggest that moonlighting in Russia can be seen as an effective incubator for setting up new self‐employed businesses, thereby providing long‐term benefits for the economy.     

Improved estimation of portfolio value‐at‐risk under copula models with mixed marginals

Portfolio value‐at‐risk (PVAR) is widely used in practice, but recent criticisms have focused on risks arising from biased PVAR estimates due to model specification errors and other problems. The PVAR estimation method proposed in this article combines generalized Pareto distribution tails with the empirical density function to model the marginal distributions for each asset in the portfolio, and a copula model is used to form a joint distribution from the fitted marginals. The copula–mixed distribution (CMX) approach converges in probability to the true marginal return distribution but is based on weaker assumptions that may be appropriate for the returns data found in practice. CMX is used to estimate the joint distribution of log returns for the Taiwan Stock Exchange (TSE) index and the associated futures contracts on SGX and TAIFEX. The PVAR estimates for various hedge portfolios are computed from the fitted CMX model, and backtesting diagnostics indicate that CMX outperforms the alternative PVAR estimators. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:997–1018, 2006