A Bayesian approach for parameter estimation in multi-stage models

Multi-stage time evolving models are common statistical models for biological systems, especially insect populations. In stage-duration distribution models, parameter estimation for the models use the Laplace transform method. This method involves assumptions such as known constant shapes, known constant rates or the same overall hazard rate for all stages. These assumptions are strong and restrictive. The main aim of this paper is to weaken these assumptions by using a Bayesian approach. In particular, a Metropolis-Hastings algorithm based on deterministic transformations is used to estimate parameters. We will use two models, one which has no hazard rates, and the other has stage-wise constant hazard rates. These methods are validated in simulation studies followed by a case study of cattle parasites. The results show that the proposed methods are able to estimate the parameters comparably well, as opposed to using the Laplace transform methods.     

The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data

Widespread concern over the credibility of published results has led to scrutiny of statistical practices. We address one aspect of this problem that stems from the use of balance tests in conjunction with experimental data. When random assignment is botched, due either to mistakes in implementation or differential attrition, balance tests can be an important tool in determining whether to treat the data as observational versus experimental. Unfortunately, the use of balance tests has become commonplace in analyses of “clean” data, that is, data for which random assignment can be stipulated. Here, we show that balance tests can destroy the basis on which scientific conclusions are formed, and can lead to erroneous and even fraudulent conclusions. We conclude by advocating that scientists and journal editors resist the use of balance tests in all analyses of clean data. Supplementary materials for this article are available online     

Impact of microcredit on rural household welfare and economic growth in Vietnam

Since its birth in 1970s, microcredit has been growing rapidly with the aim to reduce poverty and to promote economic growth. Using the large panel data of the Vietnam Access to Resources Household Surveys, the objectives are twofold: (i) to evaluate the micro-impact of microcredit on rural household economy, particularly on output value and net income of rural households, using Matched Difference-in-Difference method; and (ii) to evaluate its macro-impact on economic growth, especially the aggregate effect of production increase and income growth, using Input–Output analysis. The results at micro level find that microcredit benefits self-employment rather than other economic activities of households. The salient results from the macro-economic analysis reveal that, not as expected, the effect of microcredit on output increase is not so large. The findings suggest that microcredit is an effective development strategy at both micro and macro levels, thus the Vietnamese government should enact the relevant policies to enhance the effectiveness and outreach of microcredit.     

Heterogeneous impacts of provincial governance on household welfare in Vietnam

This study investigated the role of provincial governance in the growth of per capita income of Vietnamese households, using a balanced panel data set for the period 2012–2014. Although we found no evidence for the influence of provincial governance when a linear fixed‐effect regression estimator was used, the results from a fixed‐effect quantile regression estimator revealed that provincial governance has a positive effect on all groups (but not the poorest) and that the effect tends to be greater for better‐off households. In addition, we found that wage employment plays a larger role in the income growth of poorer households, whereas returns on education are greater for richer households. The findings suggest that a mean regression approach that looks only a t the role of explanatory variables on mean household welfare, and does not consider differences in the distribution of household welfare, may miss some heterogeneity that is of interest to policymakers. Key Practitioner Message: ? Using a quantile regression approach has allowed the current study to provide new insight into the role of household‐related factors in household welfare. ? Finding shows that good governance tends to provide greater benefits to richer households than to other groups in the population.     

Indirect evidence of the contribution of prenatal sex selection practices to the high sex ratio at birth in Vietnam

This paper reports indirect evidence that prenatal sex selection is a contributor to the recent increase in sex ratio at birth in Vietnam. The paper uses birth data from the Population Change Survey 2006 to assess the associations between sex ratio at birth and variables that predict increased opportunities to practise prenatal sex selection, including maternal knowledge of foetal sex before birth, the use of ultrasound for foetal sex determination, the gestation week when foetal sex was disclosed, and access to abortion services. The high sex ratio of most recent births was significantly associated with the use of ultrasound to determine the foetal sex in gestation weeks 12–22 and with access to family planning services that provide abortion. Prenatal sex selection in health facilities are likely to contribute to the recent increase in sex ratio at birth in Vietnam.     

Does nurture matter: Theory and experimental investigation on the effect of working environment on risk and time preferences

Building upon the reference dependent preferences model, we develop a theoretical framework to examine the relationship between environment and preferences. To verify the model’s prediction, we use a combined artefactual field experiment and household survey data in Vietnam to investigate whether involvement is risky and has long-run targeted benefits, thereby causing fishermen to exhibit different risk and time preferences than workers in other occupations. Using a structural model approach, we integrate prospect theory and hyperbolic time discounting into a single framework, to simultaneously estimate and correlate the parameters of both risk and time preferences with other demographic variables. The key finding that fishermen are found to be less risk-averse and more patient than others asserts the theoretical prediction about the influence of the working environment on preferences.     

The flexible blocking job shop with transfer and set-up times

The Flexible Blocking Job Shop (FBJS) considered here is a job shop scheduling problem characterized by the availability of alternative machines for each operation and the absence of buffers. The latter implies that a job, after completing an operation, has to remain on the machine until its next operation starts. Additional features are sequence-dependent transfer and set-up times, the first for passing a job from a machine to the next, the second for change-over on a machine from an operation to the next. The objective is to assign machines and schedule the operations in order to minimize the makespan. We give a problem formulation in a disjunctive graph and develop a heuristic local search approach. A feasible neighborhood is constructed, where typically a critical operation is moved (keeping or changing its machine) together with some other operations whose moves are “implied”. For this purpose, we develop the theoretical framework of job insertion with local flexibility, based on earlier work of Gröflin and Klinkert on insertion. A tabu search that consistently generates feasible neighbor solutions is then proposed and tested on a larger test set. Numerical results support the validity of our approach and establish first benchmarks for the FBJS.     

Nonparametric Identification of a Contract Model With Adverse Selection and Moral Hazard

This paper studies the nonparametric identification of a contract model with adverse selection and moral hazard. Specifically, we consider the false moral hazard model developed by Laffont and Tirole (1986). We first extend this model to allow for general random demand and cost functions. We establish the nonparametric identification of the demand, cost, deterministic transfer, and effort disutility functions as well as the joint distribution of the random elements of the model, which are the firm's type and the demand, cost, and transfer shocks. The cost of public funds is identified with the help of an instrument. Testable restrictions of the model are characterized.