Technical efficiency and impact of environmental regulations in farrow-to-finish swine production in Taiwan

This article demonstrates how technical efficiency and the impact of environmental regulations of Taiwanese farrow‐to‐finish swine production can be estimated in the presence of undesirable outputs. The issue of measuring technical efficiencies while considering undesirable outputs has been addressed by past studies. But the proper method of including undesirable outputs has always been a subject of debate. This article develops a data envelopment analysis (DEA)‐based model that includes undesirable outputs. The technologies of desirable output production and undesirable output control are considered simultaneously. This allows one to transform undesirable output into desirable output, whereby a traditional Shephard distance function can be used to measure technical efficiencies. An approach to measuring the impacts due to environmental regulations is then derived. Empirical results show that larger farms are more technically efficient than small‐sized farms, but no clear conclusions can be reached for the measures of regulatory impact among farms with different sizes. On average, the sample farms incurred an opportunity cost due to environmental regulations equivalent to 9.8% of market value. Opportunity costs rise with efficiency.     

Metaheuristics for drilling operation scheduling in Taiwan PCB industries

Among all types of production environment, identical parallel machines are frequently used to increase the manufacturing capacity of the drilling operation in Taiwan printed circuit board (PCB) industries. Additionally, multiple but conflicting objectives are usually considered when a manager plans the production scheduling. Compared to the single objective problem, the multiple-objective version no longer looks for an individual optimal solution, but a Pareto front consisting of a set of non-dominated solutions will be needed and established. The manager then can select one of the alternatives from the set. This research aims at employing a variable neighborhood search (VNS) algorithm and a multiple ant colony optimization (MACO) algorithm to solve the identical parallel-machine scheduling problem with two conflicting objectives: makespan and total tardiness. In VNS, two neighborhoods are defined—insert a job to a different position or swap two jobs in the sequence. To save the computational expense, one of the neighborhoods is randomly selected for the target solution which is also arbitrarily chosen from the current Pareto front. In MACO, a two-phase construction procedure where three colonies are employed in each phase is proposed. These two algorithms are tested on a set of real data collected from a leading PCB factory in Taiwan and their performances are compared. The computational results show that VNS outperforms all competing algorithms—SPGA, MOGA, NSGA-II, SPEA-II, and MACO in terms of solution quality and computational time.     

Some remarks on measurement errors and the identification of panel data models*

We demonstrate that despite the common worry about the possible correlations between the unobserved individual effects and the explanatory variables in panel data models the likelihood approach can provide a unified framework towards the study of the identification of a panel data model subject to measurement errors. In fact, it can also serve as a basis for deriving efficient estimation methods.     

Linear regression using both temporally aggregated and temporally disaggregated data

Economists frequently encounter data which are subject to different temporal aggregation. In this paper we give a maximum likelihood approach to these problems with a minimum of mathematical manipulation. We show that the best prediction of the data by related series and efficient estimation of parameters are inseparable. The relative efficiency of the maximum likelihood estimator to other estimators are also indicated.     

Combining Opinion Surveys with Time-series Data to Forecast the Japanese Economy

We explore the usefulness of combining opinion surveys with time-series data to forecast Japanese economy. We demonstrate that the businessmen's judgemental variables might summarize contemporaneous information beyond that of actual series. The combined models do yield substantially more accurate one-period or multi-period-ahead forecasts and can predict the turning points better than pure time-series models.
JEL Classification Number: C32.     

Estimation of Structural Nonlinear Errors‐in‐Varibles Models by Simulated Least‐Squares Method

This article proposes a simulation approach to obtain least‐squares or generalized least‐squares estimators of structural nonlinear errors‐in‐variables models. The proposed estimators are computationally attractive because they do not need numerical integration nor huge numbers of simulations per observable. In addition, the asymptotic covariance matrix of the estimator has a simple decomposition that may be used to guide selection of appropriate simulation sizes. The method is also useful for models with missing data or imperfect surrogate covariates, where application of conventional least‐squares and maximum‐likelihood methods is restricted by numerical multidimensional integrations.     

The innovation and economic consequences of knowledge spillovers: fit between exploration and exploitation capabilities,knowledge attributes,and transfer mechanisms

The purpose of this study is to investigate the moderating roles of the attributes and transfer mechanisms of knowledge in the relationship between organisational capabilities and innovation and economic performance. Regression analysis on a sample of 120 Taiwanese firms was used to test our model. The findings suggest that the organisational capabilities of exploration and exploitation are positively related to innovation and economic performance. The effect of exploration on performance is positively moderated by tacit knowledge and adaptation knowledge transfer mechanisms. In contrast, exploitation is a stronger predictor of performance when organisations acquire well-defined knowledge and use replication knowledge transfer mechanisms.     

Multiphase Assessment of Project Risk Interdependencies: Evidence from a University ISD Project in Taiwan

Project risks evolve dynamically, so variations in risk influences during the life cycle of an information system development project require analyses to devise risk management strategies cost effectively and at the appropriate stages. This study extends the Decision Making Trial and Evaluation Laboratory technique, using network theory, to assess the risk interdependencies for distinct project phases. A multiphase observation of a university information system development project in Taiwan provides a more in‐depth understanding of the key risk factors. To enhance risk assessments, this study proposes integrating an interdependency indicator with risk exposure measures.