Industrial Policy and Technology Diffusion: Evidence from Paper Making Machinery in Indonesia

In this paper, we analyze the diffusion and adoption of paper making machinery in the Indonesian pulp and paper industry, from 1923 till 2000. We develop a machine level index of technological sophistication (mach), which measures the technological distance of each paper machine to the world technological frontier. The data reveal a pattern of rapid technological catch up. But catch up was not an industrywide phenomenon. Some modern firms installed state-of-the-art machinery, while others installed older vintages. The paper argues that industrial policy has played an important role in the speed and nature of diffusion of paper making machinery.     

Input–Output Structural Decomposition Analysis: A Critical Appraisal

Over the past decade, input–output structural decomposition analysis (SDA) has developed into a major analytical tool. We review the development of SDA and its relationship to other methodologies. We present the fundamental principles of alternative approaches to deriving SDA estimating equations and explore the various decompositions of changes in IO tables. We also identify several complications and unresolved issues. Most importantly, we find that a rigorous grounding in economic theory is lacking for SDA, but we are able to offer some suggestions as to how it might be established.     

Bundling attractions for rural tourism development

Tourism is often regarded as a viable solution to economic crisis, especially for remote areas without many development options. While many tourism destinations have strong cultural or heritage assets, not all destinations have primary attractions that can bring visitors to the region. Rather than developing special interest “themes”, rural areas that do not have enough of any one type of tourism resource to act as a primary draw may consider bundling different attraction types to increase visitation. The purpose of this study is to investigate the preferences of visitors to secondary heritage sites and explore the relationship between heritage tourism and alternative, non-heritage activities in rural areas. Findings revealed that motivation to visit small-scale heritage sites consisted of two dimensions: learning and recreation. The two motivational dimensions influenced visitors’ interest in different heritage attractions and likelihood of visiting heritage tourism “scenarios”. As for alternative activities, there was a cluster of “popular” activities that were enjoyed by both learning-oriented and recreation-oriented respondents, but recreation-oriented visitors were more interested in nature-based activities and sport-related activities than learning-oriented visitors. Findings can help rural communities improve secondary attractions and diversify their tourism product by bundling heritage attractions with non-heritage activities.     

Talent or Not? Employee Reactions to Talent Identification

In this article, we examine the effect of talent identification on employee attitudes. Building on social exchange theory, we analyze the association between employees' perceptions about whether or not they have been formally identified as “talent” and the following attitudinal outcomes: commitment to increasing performance demands, building skills, and supporting strategic priorities; identification with the unit and the multinational enterprise; and turnover intentions. Our analyses of 769 managers and professionals in nine Nordic multinational corporations reveal a number of differences between employees who perceive that they have been identified as “talent” and those who either perceive that they have not been identified or do not know whether they have been identified. We found only limited differences between the two latter categories.     

Interpreting the results of studies using latent variable models to assess data quality: an empirical example using confirmatory factor analysis

Latent variable models (LVMs) offer one route to examine the quality of data collected in surveys. The possibility exists that individuals equivalent in their true level of a construct or variable being measured are unlikely to have equivalent observed responses as a function of an extraneous variable, e.g., group membership. This potential is labeled here as differential item functioning (DIF). Survey methods generally considers measurement bias to be estimators that do no not accurately reflect true values. DIF may be thought of as differential measurement bias, i.e., measurement bias conditional on group membership. As a function of group membership, the degree, amount, or type of measurement bias changes. DIF has the potential to negatively affect the quality of data. LVMs, e.g., confirmatory factor analysis (CFA), offer one tool to assess DIF. However, few published examples exist in the survey research field and training in the interpretation of these models is lacking. The purpose of the current paper is to describe CFA sufficiently for interpretive purposes and demonstrate an empirical application of CFA to assess survey data quality to provide further interpretive guidance. References are provided for analysts wishing to conduct analyses of this type.     

Are there ENSO signals in the macroeconomy?

Whether ENSO has affected U.S. macroeconomic performance has been a matter of dispute. To address the issue we explore whether there has been any co-cyclicality of ENSO fluctuations and the rates of inflation and economic growth over the 1894-1999 timespan and, failing this, whether aperiodic ENSO shocks have had any impact on these variables. Neither co-cyclicality nor aperiodic shocks are discernible. While ENSO may briefly influence the performance of particular sectors of the economy in particular regions, as documented by the previous literature, such locally-important effects vanish into the noise surrounding macroeconomic trends in an economy as large and complex as that of the U.S.     

Pace of work and piece rates

Using cross-industry survey data, I examine how the determinants of the pace of work affect the probability of using piece rates. Internal determinants raise the likelihood of piece rates, while response to external needs lowers the probability.