Sources of knowledge acquisition for Chinese software engineers

This research adopts a triangulation strategy based on ethnographic case study and questionnaire survey shedding light on how Chinese software engineers acquire codified and tacit knowledge in their daily development work. Software engineers make effective use of complementary resources within a broad spectrum of choices for seeking advice, learning how to solve technical problems, and transferring knowledge to the local community of practice from far beyond the organizational boundary. The analysis focuses on patterns of advice seeking relations within and across project team boundaries, also highlighting the Internet software technology forums as an important channel for technical information sharing across organizational boundaries. The implications for R&D managers are also discussed with special reference to software development and other knowledge intensive computer related work in China.     

ON THE SOURCES OF UNCERTAINTY IN EXCHANGE RATE PREDICTABILITY

In a unified framework, we examine four sources of uncertainty in exchange rate forecasting models: (i) random variations in the data, (ii) estimation uncertainty, (iii) uncertainty about the degree of time variation in coefficients, and (iv) uncertainty regarding the choice of the predictor. We find that models that embed a high degree of coefficient variability yield forecast improvements at horizons beyond one month. At the one‐month horizon, and apart from the standard variance implied by unpredictable fluctuations in the data, the second and third sources of uncertainty listed above are key obstructions to predictive ability. The uncertainty regarding the choice of the predictors is negligible.     

Confidence intervals of the premiums of optimal bonus malus systems

In view of the economic importance of motor third-party liability insurance in developed countries the construction of optimal BMS has been given considerable interest. However, a major drawback in the construction of optimal BMS is that they fail to account for the variability on premium calculations which are treated as point estimates. The present study addresses this issue. Specifically, nonparametric mixtures of Poisson laws are used to construct an optimal BMS with a finite number of classes. The mixing distribution is estimated by nonparametric maximum likelihood (NPML). The main contribution of this paper is the use of the NPML estimator for the construction of confidence intervals for the premium rates derived by updating the posterior mean claim frequency. Furthermore, we advance one step further by improving the performance of the confidence intervals based on a bootstrap procedure where the estimated mixture is used for resampling. The construction of confidence intervals for the individual premiums based on the asymptotic maximum likelihood theory is beneficial for the insurance company as it can result in accurate and effective adjustments to the premium rating policies from a practical point of view.     

Profit efficiency in the European Union banking industry: a directional technology distance function approach

We employ the directional technology distance function approach and present estimates of profit efficiency in the 25 European Union (EU) member states over the period 1998–2008. This method decomposes profit efficiency into its technical and allocative components. We investigate potential efficiency differences across the old EU region and the new EU member states, across countries and across banks of different size. Our results indicate a significant level of profit inefficiency for the EU region, which is predominantly attributed to allocative inefficiency. Our findings also suggest that banks operating in the old EU region are, on average, more profit efficient than credit institutions in the new EU member states. Overall, we observe considerable variation of efficiency scores across countries and different patterns in efficiency change over time, as well as a negative relationship between bank size and efficiency.     

Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors

This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this model to examine the explanatory and predictive power of price range and trading volume for return volatility. Our findings indicate that a negative relation between equity market returns and volatility prevails even after having controlled for the time-varying determinants of conditional volatility within each regime. We also find an asymmetry in the effect of price range on intra- and inter-regime return volatility. While price range has a stronger effect in the high volatility state, it appears to significantly affect only the transition probabilities when the stock market is in the low volatility state but not in the high volatility state. Finally, we provide evidence consistent with the ‘rebound’ model of asset returns proposed by Samuelson (1991), suggesting that long-horizon investors are expected to invest more in risky assets than short-horizon investors.     

Leadership styles, need satisfaction and the organizational commitment of Greek managers

This article presents the results of an empirical study of the relation between the leadership styles, need satisfaction and the organizational commitment of Greek managers. The findings show that there is a negative relationship between need satisfaction and organizational commitment. This relationship is stronger for the higher-order than for the lower-order needs. Furthermore, the results provide some empirical evidence regarding the relationship between the superior's leadership style and the subordinate's organizational commitment. The findings show that in most cases studied, the commitment of the Greek managers was higher when the superior adopted a consultative leadership style. This style was also the one preferred by the majority of our respondents.     

A model for identifying and ranking dangerous accident locations: a case study in Flanders

These days, road safety has become a major concern in most modern societies. In this respect, the determination of road locations that are more dangerous than others (black spots or also called sites with promise) can help in better scheduling road safety policies. The present paper proposes a multivariate model to identify and rank sites according to their total expected cost to the society. Bayesian estimation of the model via a Markov Chain Monte Carlo approach is discussed in this paper. To illustrate the proposed model, accident data from 23,184 accident locations in Flanders (Belgium) are used and a cost function proposed by the European Transport Safety Council is adopted to illustrate the model. It is shown in the paper that the model produces insightful results that can help policy makers in prioritizing road infrastructure investments.     

Asymmetric information and price competition in small business lending

This paper examines the relationship between bank lending rates and their cost of funds in New Zealand. Our results show that on average mortgage rates respond more quickly to changes in the cost of funds than base business lending rates. We also find an asymmetry in the initial (short-run) response of banks to changes in funding costs; in particular, our results show banks adjust mortgage rates downwards faster than upwards. The speed to which lending rates revert back to their equilibrium relationship with funding costs varies across the lending markets. We find the adjustment speed is faster when mortgage rates are below equilibrium, whereas it is slower when business lending rates are above long-run levels in relation to funding costs. Our analysis suggests that banks prefer the plain-vanilla type of lending such as mortgages in comparison to small business lending consistent with asymmetric information associated with business loans.     

FORECASTING INFLATION USING DYNAMIC MODEL AVERAGING*

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods that incorporate dynamic model averaging. These methods not only allow for coefficients to change over time, but also allow for the entire forecasting model to change over time. We find that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.     

Dynamic factor demands under imperfect competition: the Greek manufucturing industry 1958–1981

The intertemporal maximization problem of the firm under adjustment costs for its factors of production and imperfect competition in the output market is considered. The first-order conditions, with respect to capital and labour, the production function and the demand equation have been jointly estimated using Greek manufacturing data and values for the structural parameters have been obtained. The estimates are plausible and most of them significant. Tests of the overidentifying restirctions are unable to reject the overall specification of the model at conventional levels of significance.