Linking labour force participation, education, labour wages and household consumption in developing countries:push and pull effects in self-employment - evidence from Nigeria

The contribution of this thesis is in understanding the origins in developing countries of differences in labour wage and household consumption vis-à-vis educational abilities (and by extension employment statuses). This thesis adds to the labour market literature in developing countries by investigating the nature of employment and its consequences for labour wage and household consumption in a developing country. It utilizes multinomial probit, blinder-oaxaca, Heckman and quantile regressions to examine one human capital indicator: educational attainment; and two welfare proxies: labour wage and household consumption, in a developing country, Nigeria. It finds that, empirically, the self-employed are a heterogeneous group of individuals made up of a few highly educated individuals, and a significant majority of ‘not so educated’ individuals who mostly earn less than paid workers. It also finds that a significant number of employers enjoy labour wage premiums; and having a higher proportion of employers in the household has a positive relationship with household consumption. The thesis furthermore discovers an upper educational threshold for women employers not found for men. Interestingly, the thesis also finds that there is indeed an ordering of labour wages into low-income self-employment (which seems to be found mainly in “own account” self-employment), medium-income paid employment, and high-income self-employment (which seems to be found mainly among employers), and that this corresponds to a similar ordering of low human capital, medium human capital and high human capital among labour market participants, as expressed through educational attainments. These show that as a whole, employers can largely be classed as experiencing pulled self-employment, as they appear to be advantaged in all three criteria (educational attainments, labour wage and household consumption). A minority of self-employed “own account” workers (specifically those at the upper end of the income distribution who are well educated), can also be classed as experiencing pulled self-employment. The rest of the significant majority of self-employed “own account” workers in this study can be classed as experiencing pushed self-employment in terms of the indicators used.

GTM: A principled alternative to the self-organizing map

The Self-Organizing Map (SOM) algorithm has been extensively studied and has been applied with considerable success to a wide variety of problems. However, the algorithm is derived from heuristic ideas and this leads to a number of significant limitations. In this paper, we consider the problem of modelling the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. We introduce a novel form of latent variable model, which we call the GTM algorithm (for Generative Topographic Mapping), which allows general non-linear transformations from latent space to data space, and which is trained using the EM (expectation-maximization) algorithm. Our approach overcomes the limitations of the SOM, while introducing no significant disadvantages. We demonstrate the performance of the GTM algorithm on simulated data from flow diagnostics for a multi-phase oil pipeline.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

How well does the theory of planned behaviour predict alcohol consumption? A systematic review and meta-analysis

This study aimed to quantify correlations between theory of planned behaviour (TPB) variables and (i) intentions to consume alcohol and (ii) alcohol consumption. Systematic literature searches identified 40 eligible studies that were meta-analysed. Three moderator analyses were conducted: pattern of consumption, gender of participants and age of participants. Across studies, intentions had the strongest relationship with attitudes (r+ = .62), followed by subjective norms (r+ = .47) and perceived behavioural control (PBC; r+ = .31). Self-efficacy (SE) had a stronger relationship with intentions (r+ = .48) compared with perceived control (PC; r+ = −.10). Intention had the strongest relationship with alcohol consumption (r+ = .54), followed by SE (r+ = .41). In contrast, PBC and PC had negative relationships with alcohol consumption (r+ = −.05 and −.13, respectively). All moderators affected TPB relationships. Patterns of consumption with clear definitions had stronger TPB relations, females reported stronger attitude–intention relations than males, and adults reported stronger attitude–intention and SE–intention relations than adolescents. Recommendations for future research include targeting attitudes and intentions in interventions to reduce alcohol consumption, using clear definitions of alcohol consumption in TPB items to improve prediction and assessing SE when investigating risk behaviours.

Self-affirmation before exposure to health communications promotes intentions and health behavior change by increasing anticipated regret

Health-risk information can elicit negative emotions like anticipated regret that may positively affect health persuasion. The beneficial impact of such emotions is undermined when target audiences respond defensively to the threatening information. We tested whether self-affirming (reflecting on cherished attributes) before message exposure can be used as strategy to enhance the experience of anticipated regret. Women were self-affirmed or not before exposure to a message promoting fruit and vegetable consumption. Self-affirmation increased anticipated regret and intentions reported following message exposure and consumption in the week after the intervention; regret mediated the affirmation effect on intentions. Moreover, results suggest that anticipated regret and intentions are serial mediators linking self-affirmation and behavior. By demonstrating the mediating role of anticipated regret, we provide insights into how self-affirmation may promote healthy intentions and behavior following health message exposure. Self-affirmation techniques could thus potentially be used to increase the effectiveness of health communication efforts.