Global Development Goals: The Folly of Technocratic Pretensions

This article argues that, although effective strategic choices for achieving global development goals need to be based on assessments of the costs and benefits of alternative approaches, existing methods of arriving at such assessments are highly unreliable, in particular deriving from implausible and restrictive assumptions and often depending on data of poor quality, and on the pretence that the future can be adequately known. Such weaknesses can be mitigated, but not easily overcome, without abandoning deeply held technocratic presumptions.     

DECENTRALIZATION AND PARTICIPATORY SERVICE DELIVERY

User participation has been promoted to improve the quality, responsiveness, and outreach of public services in India. This qualitative study evaluates new grassroots institutions—Village Education Committees and Mothers’ Committees—in Andhra Pradesh, which promoting parents’ participation in the management and monitoring of local schools and maternal/child health services. Although the committees were found to have increased participation in public affairs by the poor and brought about some improvements in service quality, inclusive and meaningful participation has often been hindered by illiteracy and lack of information, as well as caste, gender, and socioeconomic inequalities. The article suggests that there are considerable tensions between inclusive participation and committee effectiveness as members need skills, status, and resources in order to have a meaningful impact on service provision. In addition, research findings point to the need for more structured opportunities for committee members to interact with authorities and service providers, as well as for children to voice their concerns and ideas. Lastly, in order to tackle childhood poverty more holistically, the focus of these committees should be revised to give greater emphasis to improving service quality improvements and cross-sectoral synergies, rather than the current move narrow focus on infrastructural development and singlesector initiatives.     

Effects of method on participants and disclosure rates in research on sensitive topics

This study replicates and extends the research of Rosenbaum, Rabenhorst, Reddy, Fleming, and Howells, which also appears in this special issue. Responses from 398 randomly assigned participants regarding differentially sensitive topics were collected via four methods of data collection: written questionnaires, face-to-face interviews, telephone interviews, and an automated telephonic data collection system (ATDC). Several significant differences in data collection methodology and topic area were found, including greater disclosure of sensitive information via the ATDC system than via face-to-face and paper-and-pencil conditions. Participants who were assigned to the ATDC condition felt significantly more comfortable answering questions compared to those in the face-to-face interview condition. Participants in the telephone interview condition reported answering significantly more carefully than participants answering via written questionnaire. Taken together, the results of this study and the previous one it replicates suggest that the ATDC produces disclosure rates that are at least equivalent to, if not greater than, those generated using traditional methods for collecting sensitive data.     

Optimal Workforce Mix in Service Systems with Two Types of Customers

We consider a service system with two types of customers. In such an environment, the servers can either be specialists (or dedicated) who serve a specific customer type, or generalists (or flexible) who serve either type of customers. Cross‐trained workers are more flexible and help reduce system delay, but also contribute to increased service costs and reduced service efficiency. Our objective is to provide insights into the choice of an optimal workforce mix of flexible and dedicated servers. We assume Poisson arrivals and exponential service times, and use matrix‐analytic methods to investigate the impact of various system parameters such as the number of servers, server utilization, and server efficiency on the choice of server mix. We develop guidelines for managers that would help them to decide whether they should be either at one of the extremes, i.e., total flexibility or total specialization, or some combination. If it is the latter, we offer an analytical tool to optimize the server mix.     

Kernel density estimation on grouped data: the case of poverty assessment

Grouped data have been widely used to analyze the global income distribution because individual records from nationally representative household surveys are often unavailable. In this paper we evaluate the performance of nonparametric density smoothing techniques, in particular kernel density estimation, in estimating poverty from grouped data. Using Monte Carlo simulations, we show that kernel density estimation gives rise to nontrivial biases in estimated poverty levels that depend on the bandwidth, kernel, poverty indicator, size of the dataset, and data generating process. Furthermore, the empirical bias in the poverty headcount ratio critically depends on the poverty line. We also undertake a sensitivity analysis of global poverty estimates to changes in the bandwidth and show that they vary widely with it. A comparison of kernel density estimation with parametric estimation of the Lorenz curve, also applied to grouped data, suggests that the latter fares better and should be the preferred approach.     

Optimal stratification in stratified designs using weibull-distributed auxiliary information

Sampling has evolved into a universally accepted approach for gathering information and data mining as it is widely accepted that a reasonably modest-sized sample can sufficiently characterize a much larger population. In stratified sampling designs, the whole population is divided into homogeneous strata in order to achieve higher precision in the estimation. This paper proposes an efficient method of constructing optimum stratum boundaries (OSB) and determining optimum sample size (OSS) for the survey variable. The survey variable may not be available in practice since the variable of interest is unavailable prior to conducting the survey. Thus, the method is based on the auxiliary variable which is usually readily available from past surveys. To illustrate the application as an example using a real data, the auxiliary variable considered for this problem follows Weibull distribution. The stratification problem is formulated as a Mathematical Programming Problem (MPP) that seeks minimization of the variance of the estimated population parameter under Neyman allocation. The solution procedure employs the dynamic programming technique, which results in substantial gains in the precision of the estimates of the population characteristics.     

Measuring Inequality of Opportunity for the Backward Communities: Regional Evidence from the Indian Labour Market

The affirmative action policy for socially and economically backward communities in employment has been a debated issue in India. In this context, this paper aims to analyze the level of inequality by distinguishing between ‘circumstance’ and ‘effort’ factors in the Roemer’s framework on equality of opportunity. We measure inequality of opportunities due to two circumstances: caste and religion. Our empirical analysis, at state-level, utilizes a recent household survey data, which provides information related to efforts as well as circumstances of workers. The paper estimated inequality in the labour market and then decomposed it to know the circumstances that cause income inequality. Our estimates indicated that inequality and inequality of opportunity is substantially higher in India. Specifically, the outcome of our analysis evidently indicated that the socially backward communities do have economically disadvantageous position in some of the Indian states. However, the degree of circumstances based on inequality varies to a great extent among the states. Therefore, we suggest that the country does not need a nation-level affirmative action policy instead a state-level policy could be more appropriate as the intensity of the problem differ significantly among the Indian states.     

Understanding Drivers of Risk‐Adjusted Performance for Service Firms with International Operations*

This article investigates whether international operations of service firms increase performance while reducing risk. The article draws on a longitudinal dataset of 584 internationally operating service firms from the United States. Analysis indicates that international diversification is negatively related to risk‐adjusted performance. However, it is established that international diversification interacts with internationalization and positively influences risk‐adjusted performance. This finding offers significant promise for firms, as it indicates that international operations (if managed well), through exposure to varied foreign markets coupled with adequate global scope, can lead to firms’ increased risk‐adjusted performance. The results provide a mechanism for decision‐makers to better understand international operations of service firms and present a strategy for achieving success in international markets by effectively managing two important levers: internationalization and international market diversification.     

Economic Cost of Human Capital Loss from Fiji: Implications for Sustainable Development1

Small island nations in the South Pacific are facing a serious problem of loss of human capital. The loss of skilled and qualified personnel from the small pool is causing a major setback in terms of providing the technical expertise to forge ahead with reform programs that these economies are undertaking. Fiji's policymakers are increasingly confronting this issue, because the nation has experienced a massive outflow of skilled labor following the political instability in 1987. While there is an outflow of skilled labor, the country is also losing a large amount of financial capital. The extent of the outflow has yet to be measured due to lack of a methodology. This study advances a methodology to measure the loss to the economy arising out of human capital loss in a small island economy.