Referral Networks and Inequality*

2020 ◽  
Author(s):  
Manolis Galenianos

Abstract This is the first paper to study the interaction between labour markets and endogenous referral networks in the context of worker heterogeneity. In equilibrium the structure of the referral network is hierarchical, which is different from the usual assumption of homophily but is consistent with the evidence. Hierarchy exacerbates inequality. The welfare effects of the use of referrals are subtle and depend on the nature of heterogeneity. If heterogeneity is due to productivity differences, referrals improve welfare. If workers face different probability of forming a match despite having the same productivity, as in the case of discrimination, referrals reduce welfare.

1995 ◽  
Vol 214 (3) ◽  
Author(s):  
Hugo Dicke ◽  
Hans H. Glismann

SummaryThe welfare calculus of migration of the recipient country is tackled at the level of macro- and of microeconomics, using the technical apparatus of the welfare economics of international trade. It turns out that - as opposed to the international-trade case - in order to exploit positive welfare effects accruing to an economy which opens its labour markets to immigrants, interventions are necessary. The design of migration policy has to take into account, among others, the degree of homogeneity of preference patterns as well as the functioning of regulated labour markets, and the strain on the national resource base.


2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Thakkar ◽  
T Valente ◽  
J Andesia ◽  
B Njuguna ◽  
J Miheso ◽  
...  

Abstract Introduction The Strengthening Referral Networks for Management of Hypertension Across the Health System (STRENGTHS) trial is creating and testing interventions to improve the effectiveness of referral networks for patients with hypertension in Western Kenya. Purpose Network analysis of facility-based healthcare providers was used to understand the existing network of referrals. The ultimate goal was to identify both structural gaps and opportunities for implementation of the planned intervention. Methods A network survey was administered to providers who deliver care to patients with hypertension asking individuals to nominate a) individuals to whom, and b) facilities to which they refer patients, both up and down the health system. We analyzed survey data using centrality measures of in-degree and out-degree (number of links each provider received and sent, respectively), as well as fitting a core-periphery (CP) model. A higher CP indicates a strong referral network, while a lower CP indicates a relatively weaker network. Results Data were collected from 130 providers across 39 sites within 7 geographically separate network clusters. Each cluster consists of a mix of primary, secondary, and/or tertiary facilities. Compared to a perfect CP referral network model (Correlation Score [CP] = 1.00) and a random referral network model (CP = 0.200), the provider referral networks within each cluster showed a weak tendency for CP structure. There was a large range in CP from 0.334 to 0.639. In contrast, cluster-level facility networks showed a strong tendency for CP structure, with a CP range of 0.857 to 0.949. Core Periphery Correlation Scores [CP] Network Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Cluster 7 Provider Referrals 0.433 0.424 0.334 0.639 0.535 0.448 0.407 Facility Referrals 0.949 0.894 0.871 0.949 0.949 0.904 0.857 Each cluster represents a geographically separate referral network. A random referral network would reveal a CP score of 0.200; while a perfect referral network would give a CP of 1.00. Referral Network Models Conclusions The current health system across Western Kenya does not demonstrate a strong network of referrals between providers for patients with hypertension. While facility-to-facility referrals are more in-line with a perfect referral model, there are gaps in communication between the specific providers. These results highlight the need for STRENGTHS to design and test interventions that strengthen provider referral patterns in order to improve blood pressure control and reduce cardiovascular risk. Acknowledgement/Funding National Institutes of Health: National Heart Lung and Blood Institute, Doris Duke Charitable Foundation:International Clinical Research Fellowship


1986 ◽  
Vol 23 (4) ◽  
pp. 370-378 ◽  
Author(s):  
Peter H. Reingen ◽  
Jerome B. Kernan

Though many marketers—particularly those in the service sector—depend on word of mouth (WOM) for referrals, the traditional sample survey methodology used in previous WOM research does not explicate the interpersonal nature of informal communication. The authors propose network analysis as an alternative method for research on referral behavior. The sampling, data-gathering, and analytic aspects of referral network analysis are described in general terms and illustrated with a case study which, in addition to yielding interesting descriptive information about a service marketer's referral network, affords a test of the strength-of-ties hypothesis in influencing referral flows.


Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Tim Mercer ◽  
Benson Njuguna ◽  
Gerald S. Bloomfield ◽  
Jonathan Dick ◽  
Eric Finkelstein ◽  
...  

Abstract Background Hypertension is a major risk factor for cardiovascular disease (CVD), yet treatment and control rates for hypertension are very low in low- and middle-income countries (LMICs). Lack of effective referral networks between different levels of the health system is one factor that threatens the ability to achieve adequate blood pressure control and prevent CVD-related morbidity. Health information technology and peer support are two strategies that have improved care coordination and clinical outcomes for other disease entities in other settings; however, their effectiveness and cost-effectiveness in strengthening referral networks to improve blood pressure control and reduce CVD risk in low-resource settings are unknown. Methods/design We will use the PRECEDE-PROCEED framework to conduct transdisciplinary implementation research, focused on strengthening referral networks for hypertension in western Kenya. We will conduct a baseline needs and contextual assessment using a mixed-methods approach, in order to inform a participatory, community-based design process to fully develop a contextually and culturally appropriate intervention model that combines health information technology and peer support. Subsequently, we will conduct a two-arm cluster randomized trial comparing 1) usual care for referrals vs 2) referral networks strengthened with our intervention. The primary outcome will be one-year change in systolic blood pressure. The key secondary clinical outcome will be CVD risk reduction, and the key secondary implementation outcomes will include referral process metrics such as referral appropriateness and completion rates. We will conduct a mediation analysis to evaluate the influence of changes in referral network characteristics on intervention outcomes, a moderation analysis to evaluate the influence of baseline referral network characteristics on the effectiveness of the intervention, as well as a process evaluation using the Saunders framework. Finally, we will analyze the incremental cost-effectiveness of the intervention relative to usual care, in terms of costs per unit decrease in systolic blood pressure, per percentage change in CVD risk score, and per disability-adjusted life year saved. Discussion This study will provide evidence for the implementation of innovative strategies for strengthening referral networks to improve hypertension control in LMICs. If effective, it has the potential to be a scalable model for health systems strengthening in other low-resource settings worldwide. Trial registration Clinicaltrials.gov, NCT03543787. Registered on 29 June 2018.


1979 ◽  
Vol 61 (2) ◽  
pp. 234 ◽  
Author(s):  
John W. Freebairn ◽  
Glenn A. Withers

2014 ◽  
Vol 11 (2) ◽  
pp. 125-136 ◽  
Author(s):  
Roland Verwiebe ◽  
Laura Wiesböck ◽  
Roland Teitzer

This article deals mainly with new forms of Intra-European migration, processes of integration and inequality, and the dynamics of emerging transnational labour markets in Europe. We discuss these issues against the background of fundamental changes which have been taking place on the European continent over the past two decades. Drawing on available comparative European data, we examine, in a first step, whether the changes in intra-European migration patterns have been accompanied by a differentiation of the causes of migration. In a second step, we discuss the extent to which new forms of transnational labour markets have been emerging within Europe and their effects on systems of social stratification.


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