Social Policy Evaluation Research Articles

Medición de la pobreza multidimensional en México mediante un análisis bibliométrico y de ecuaciones estructurales

Objective. Multidimensional poverty in Mexico was measured through a bibliometric and structural equation analysis. Design/Methodology/Approach. We used the technique developed by the National Council for the Evaluation of Social Development Policy (CONEVAL, in Spanish) in Mexico, based on information from the National Household Income and Expenditure Survey (ENIGH, in Spanish). The Smart PLS software also used the partial least squares (PLS) technique. Regarding the bibliometric part, a descriptive analysis was performed using the Scopus database and VOSviewer as a processing tool. Results/Discussion. The results showed that basic housing services, access to food, quality, housing spaces, and income significantly impact multidimensional poverty. The PLS model showed adequate predictive superiority and goodness of fit. From the bibliometric point of view, there was clear interest on the part of the academic and scientific community in developing knowledge in this field. Conclusions. The effectiveness of the PLS model for measuring multidimensional poverty in Mexico is demonstrated, and several determinants are highlighted. Future studies are recommended to improve social policies and poverty reduction strategies. Originality/Value. The study provides a novel approach by using the PLS model to measure multidimensional poverty in Mexico. It applies a robust exploratory methodology that can be replicated in similar contexts and is supported by bibliometric contrast.

Short‐term changes in financial situation have immediate mental health consequences: Implications for social policy

AbstractPoverty is associated with psychological variables such as increased anxiety, increased depression, steeper time discounting and greater risk aversion. However, less is known about whether short‐term changes in financial circumstances are coupled to immediate psychological responses. We present data from the Changing Cost of Living study, in which panels of adults in France (n = 232) and the UK (n = 240) completed financial and psychological surveys every month for a year (September 2022–August 2023). We found the expected overall socioeconomic gradients in anxiety, depression and time discounting. In addition, monthly fluctuations in financial situation were associated with fluctuations in depression, anxiety and risk preference. Increases in essential costs, considered separately from fluctuations in income, had an immediate impact on depression. Social support, the instrumental and emotional assistance derivable from one's social network, buffered the effects of short‐term financial fluctuations on depression and time discounting, but did not mitigate the overall gradients. We conclude that declines in income or increases in the cost of living have immediate and measurable psychological impacts, which must be borne in mind in the formulation and evaluation of social policy.

Оцінювання актуальності та впливу глобальних викликів для національної політики.

The article is devoted to the presentation of certain results of the scientific project «Evaluation of national social policy in the context of global challenges», which was carried out by a team of specialists of the Ptoukha Institute for Demography and Social Studies of the NAS of Ukraine in 2022—2024. These results were obtained during carrying out tasks related to the identification of global challenges for Ukraine, assessment of their relevance and impact on national policy. The main basis of this work is the theoretical and applied findings of the most famous studies of such categories as global risks, threats and challenges. The study of global risks and challenges is one of the most relevant scientific tasks for today, as humanity is increasingly aware of the urgent need to confront possible threats to its existence both at the level of international cooperation and at the level of national policy. The article provides a brief overview of current research with an emphasis on the Global Risk Perception Survey (GRPS) methodology, according to which the World Economic Forum annually conducts assessments and publishes their results in its reports. By analogy with the international GRPS methodology, as part of the project implementation, for the first time in Ukraine, a series of surveys of national experts was conducted to assess the national context of global challenges perception. The first round was held on the eve of the full-scale invasion of Ukraine’s territory by Russian troops, in the period from February 16 to February 23, 2022, the second round — in the summer of 2022, and the third — in the fall of 2023. The purpose of this study is to determine the composition, degree of relevance and measure of impact of global challenges (at the national level — on the population of the country, at the local level — on the population of the community), as well as to study the temporal component of changes in their perception. For the formation of main postulates of the research, the work uses general scientific methods of generalization, analysis, comparisons, as well as a graphic method — for visualization of obtained results. As a tool for the two-dimensional assessment of the relevance and impact of global challenges, the authors built a matrix that allowed to group the challenges according to the growth rate of the evaluated parameters. The largest group includes eight challenges that have a significant impact on national policy and will be relevant in the next three years: «Employment crisis», «Deterioration of the population’s mental health», «Collapse of social security systems», «Decreasing accessibility and quality of education», «Damaging the ecosystems», «Increasing social inequality», «Deterioration of water resources quality», «Insufficient ensuring of human rights». The experts assessed only one challenge as catastrophic — the «High level of armed violence», by which they obviously meant human losses due to the death and injury of the military personnel and civilian population, loss of health and work capacity. It is these challenges that will require priority attention in the development of national policy strategies. The ability of our country to face global challenges and ensure social and economic resilience depends on the adequacy of the decisions that will be made.

Contribución de la ganadería mexicana a la seguridad alimentaria nacional, a tres sexenios del TLCAN

In recent decades Food Security (FS) has become a topic of global interest, with food shortages and deficient diets at home being a serious problem faced by humanity. The objective was to analyze the role of livestock in the FSof Mexico, period 1994-2012, toevaluate and contrast, livestock production and the availability of food for the national population. A descriptive and comparative multidimensional analysis was carried out with statistics from official sources, finding a significant increase in the volume of livestock production, a significant rise in prices and a sustained deficit trade balance. Therefore, livestock shows a significant contribution to the Mexican food security, supplying with national production the nutritional requirements established by the National Council for the Evaluation of Social Development Policy (CONEVAL) for a balanced and healthy diet.

What makes randomized controlled trials so successful—for now? Or, on the consonances, compromises, and contradictions of a global interstitial field

Randomized controlled trials (RCTs) are a major success story, promising to improve science and policy. Despite some controversy, RCTs have spread toward Northern and Southern countries since the early 2000s. How so? Synthesizing previous research on this question, this article argues that favorable institutional conditions turned RCTs into “hinges” between the fields of science, politics, and business. Shifts toward behavioral economics, New Public Management, and evidence-based philanthropic giving led to a cross-fertilization among efforts in rich and poor countries, involving states, international organizations, NGOs, researchers, and philanthropic foundations. This confluence of favorable institutional conditions and savvy social actors established a “global interstitial field” inside which support for RCTs has developed an unprecedented scope, influence, operational capacity, and professional payoff. However, the article further argues that the hinges holding together this global interstitial field are “squeaky” at best. Because actors inherit the illusio of their respective fields of origin—their central incentives and stakes—the interstitial field produces constant goal conflicts. Cooperation between academics and practitioners turns out to be plagued by tensions and contradictions. Based on this analysis, the article concludes that the global field of RCT support will probably differentiate into its constituent parts. As a result, RCTs may lose the special status they have gained among social science and policy evaluation methods, turning into one good technique among others.

Analysis of poverty as a factor in the dropout rate of university students in Mexico City from 2000 to 2022

The analysis of the correlation between poverty and student dropout has been a phenomenon of deep interest that must be studied, a problem presents in a dynamic and diverse region such as Mexico City. This research covers the last two decades, from 2000 to 2022, taking into account the factors that influence the educational continuity of university students in an environment marked by socioeconomic variability. In this analysis, the complexity of poverty is evident as a determining factor in student dropout in the university context of Mexico City; using indicators developed by the National Council for the Evaluation of Social Development Policy (CONEVAL) and the National Council of Science and Technology (CONACYT); as well as data collected through censuses implemented by the National Institute of Statistics and Geography (INEGI). Seeking to effectively explain the correlation between student dropouts and poverty

The Impact of Bilateral Trade on Economic Diplomacy Effectiveness between Ethiopia and China

This article investigates the intricate relationship between bilateral trade and economic diplomacy, focusing specifically on the case of Ethiopia and China. Through a qualitative approach integrating interviews, focus group discussions, and thematic analysis, the study delves into the evolving dynamics of their multifaceted partnership. It examines various dimensions of economic relations, including trade agreements, infrastructure projects, and cultural exchanges, while addressing the significance of economic diplomacy in shaping international economic policies and advancing mutual interests. Drawing on insights from scholars and historical context, the research explores specific research questions pertaining to trade policies, tariffs, trade imbalances, quality and type of traded goods, trade-related disputes, and diplomatic negotiations. Findings reveal the transformative power of economic diplomacy, evidenced by the historical trend of bilateral trade volume and the influence of trade policies, tariffs, and agreements on economic diplomacy outcomes. Trade imbalances and trade diversification emerge as critical factors shaping economic diplomacy effectiveness, highlighting the importance of strategic policy alignment and diplomatic negotiations. Theoretical perspectives including liberalism, realism, interdependence theory, constructivism, and institutionalism provide a comprehensive framework for understanding the evolving Ethiopia-China economic relationship. The study underscores the pivotal role of diplomatic negotiations in navigating trade dynamics and fostering resilient economic partnerships. Recommendations offered in the study provide strategic pathways for policymakers to enhance economic relations between Ethiopia and China in the global context, emphasizing the need for strategic engagement in trade negotiations, balancing trade deficit, promoting investment and industrial development, strengthening regulatory and legal frameworks, fostering cultural and academic exchanges, and enhancing infrastructure and connectivity. Moreover, suggestions for future studies outline avenues for further research to deepen understanding of this complex relationship, encompassing longitudinal analysis, comparative studies, sector-specific investigations, stakeholder perspectives, environmental and social dimensions, policy evaluation, and cultural and societal impacts. Addressing these aspects will contribute to a more comprehensive understanding of the impact of bilateral trade on economic diplomacy between Ethiopia and China.

Reflection on the application of the Consolidated Framework for Implementation Research to a national policy to improve inclusion of people with disabilities

People with disabilities face many barriers in the built environment impacting their mobility, health, and social participation. In the US, under the Americans with Disabilities Act (ADA), municipalities were required to develop and implement barrier-removal plans for pedestrian infrastructure, called ADA transition plans, but very few have done so. Many communities know they need a plan but do not know how to get it done because of a lack of understanding of the many different implementation considerations. Implementation science offers a useful approach for understanding complex policy implementation such as ADA plans. This paper provides a reflection on the adaptation of the Consolidated Framework for Implementation Research (CFIR) to evaluate the implementation of ADA transition planning. To apply the CFIR, we tailored the construct definitions and modified them to fit the specific context of the ADA transition planning process. We documented the constructs that were more challenging to apply, those that were not relevant, and those that were particularly useful. This paper can serve as a valuable example that other researchers can use when considering adapting the CFIR or other implementation frameworks for the evaluation of complex social policy beyond the ADA.

SOCIOECONOMIC POLICY EVALUATION: PARTISANSHIP AND PARTISAN BIAS EFFECT

Public support of socioeconomic reforms is one of the most important factors for their successful implementation, and conversely, lack of public approval doesn’t allow achieving the expected effect and may result in negative externalities. In this regard, it is relevant to study the origins of people’s opinions and factors affecting their evaluation of social and economic policies. This paper is devoted to the following aspects of this multidimensional problem as partisanship and partisan bias. Their research has been actively promoted by foreign scientists, but so far presented extremely limited in Ukrainian literature. In this paper the critical review of foreign scientific papers devoted to this topic is presented; the main hypotheses about the influence of party identification on public opinion and the effect of partisan bias are highlighted; features of the methodology are noted and research results are summarized. The methodology used by foreign specialists for research of this problem is based on experimental methods, among them the main place belongs to laboratory experiments. A laboratory experiment means observing people’s behavior (participants’ behavior) under strictly controlled conditions when the influence of uncontrolled factors is limited to a minimum. In foreign studies of partisan bias and its influence on citizens' evaluation of socioeconomic policies, laboratory experiments serve as the main tool for testing hypotheses. The results of the research give evidence, on the one hand, that the partisan bias mechanism provides wide possibilities to manipulate the people’s opinion and public opinion in general, on the other hand, that correct objective information about the policy content and goals can significantly weaken the partisan bias effect. Foreign studies prove that party signal influence depends on the people’s properties, policy content, political systems, and party characteristics. In Ukraine, there is a lack its own research in this field, however, as democratic institutions, civil society, and people’s political consciousness and activity develop, these studies become more relevant to the political and economic life in Ukrainian society.

An interdisciplinary approach to environmental conservation policy: a case of Satoyama redevelopment in the peri-urban area

This study proposes a practice and discussion for an interdisciplinary approach to policies for the conservation of suburban and peri-urban ecosystems. We highlight the need for evidence-based assessment of the current quality of the targeted nature from perspectives of natural science and problem formulation, and that causes should be investigated from the combined perspectives of social science, economic evaluation, and policy design and evaluation, with an awareness of the possibility of consensus building. In this study, based on the ongoing international trend of ecosystem conservation, an economic analysis was conducted to examine the direction of Satoyama development as a case study of urban and peri-urban ecosystem conservation. The result identified the preference and needs of citizens with regard to Satoyama ecosystems and discussed the consistency between policy targets and citizens’ evaluation.

The Full SPECTRUM: Developing a Tripartite Partnership between Community, Government and Academia for Collaborative Social Policy Research


 
 
 Problem: In Canadian society, public policies guide the development and administration of social services and systems, including the public education system, the justice system, family services, social housing and income support. However, because social services are often planned and implemented in a ‘siloed’ manner, coordination and collaboration across departments, sectors and organisations is sorely lacking. Data and resource constraints may prevent services being evaluated to ensure they meet the needs of the people for whom they are intended. When the needs of individuals are not addressed, the result is poor outcomes and wasted resources across multiple areas.Our Response: In 2018, we formed the SPECTRUM Partnership in response to a recognised need for collaborative cross-sector approaches to strengthening the policies that shape social services and systems in our country. The tripartite SPECTRUM partnership comprises representatives from community organisations, government and academia, and is an entity designed to conduct social policy research and evaluation, incorporating interdisciplinary perspectives and expertise from its members. Guided by community-driven research questions and building on existing data resources, SPECTRUM seeks to address specific knowledge gaps in social programs, services and systems. New research findings are then translated into viable public policy options, in alignment with government priorities, and presented to policy-makers for consideration.Implications: In this practice-based article, we describe the key steps we took to create the SPECTRUM partnership, build our collective capacity for research and evaluation, and transform our research findings into actionable evidence to support sound public policy. We outline four of SPECTRUM’s achievements to date in the hope that the lessons we learned during the development of the partnership may serve as a guide for others aiming to optimise public policy development in a collaborative evidence-based way.
 
 

On the Curvature Properties of “Long” Social Welfare Functions

This study characterizes the concavity properties of the Jorgenson and Slesnick’s social welfare function that is likely the most empirically relevant function among the family of “long” welfare functions. We bridge this knowledge gap using the definition of generalized concavity to show the conditions necessary for the long social welfare function of interest to be decreasing and quasi-convex with respect to prices. Thanks to this result, “long” social welfare functions with regular curvature can be suitable for applied social welfare analysis and policy evaluations.

Measuring happiness for social policy evaluation: a multidimensional index of happiness

There are multiple indices based on positive psychology and the economics of happiness for measuring, evaluating and developing social policies. Based on univariable scales, they reflect a more hedonic view rather than a complex perspective on social reality and human behavior, which renders them unfit for purpose in the field of sociology. This paper proposes a multidimensional model that includes social relationships and human happiness, focusing more on eudaimonic than hedonic happiness. It contains an affective dimension, an ethical dimension, and a welfare system’s evaluation dimension. Based on the sociology of emotions, it includes elements from Shalom Schwartz’s theory of values and Jacques Thomassen’s study of societies with consolidated political and welfare systems. The model was validated using an Exploratory Factor Analysis with 28 variables from the European Social Survey (ESS). A multidimensional index is proposed, composed of five factors: the welfare system, positive and negative emotional states, altruism, and egocentrism.

Inteligencia artificial y planeación presupuestaria en México: promesas y retos en América Latina para la asignación del gasto público

Public budgeting is a complex process that depends on multiple factors, including the consideration of scarce resources and the quality of available information. Artificial intelligence (AI) has the potential to discover models that help explain complex social phenomena, such as the budget planning. However, currently there is little work exploring the application of AI in this context. This paper aims to propose an algorithmic perspective for the allocation of public budget in Mexico by exploring the potential of multilayer perceptron and multi-objective genetic algorithms. The guiding research question is: what is the potential of the multilayer perceptron and multi-objective genetic algorithms in decision making regarding the allocation of the Mexican public budget? The study analyzes open data from the World Bank related to Mexico’s expenditure budget and poverty measurement data provided by the National Council for the Evaluation of Social Development Policy for the period 1990-2020. Additionally, some limitations of this work derived from the inherent complexity of the public expenditure allocation are identified. The model showed indicators that allow us to understand the importance Mexican public budget expenditures in promoting economic development, as well as potentially reducing inflation and inequality. From the analysis, based on AI techniques, it was found that the most important aspects to generate an effective and efficient public budget should focus mainly on fighting poverty, investing in the agricultural sector, encouraging industry, generating policies for the improvement of the health sector, as well as promoting research and development.

Beyond the Buzzword: A Framework for an Indigenous Relational Evaluation in Traditional Communities in Ghana

The notions of indigenous knowledge and cultural philosophies are becoming ubiquitous in many social inquiries, and evaluation is no exception. Nonetheless, the pursuit to embed relevant indigenous philosophies in contemporary evaluation has yet to succeed. In this article, we discuss indigenous relational philosophies, approaches, and practices as they relate to evaluation. Using qualitative research approaches, we interviewed 43 Indigenous development leaders and other local representatives in three local government areas in Ghana. Utilizing evidence synthesis approaches through a triangulation process, we conclude that indigenous knowledge and other cultural ethos were distinct in community-based development evaluation processes. There was an elusive intersection between indigenous and contemporary evaluation paradigms. Indigenous evaluation has principles such as community spirit, mutual trust, self-organization, relational patterns or networks, “ubuntu” ideals, consensus building, and collective action that can complement contemporary evaluation for the effective and efficient evaluation of community development programs and social policies. We identify key indigenous elements and other indigenous relational assessment patterns to aid in the design of an indigenously driven relational evaluation framework. The evaluative competencies embedded in indigenous philosophies are vast, thus, a call for future research is proposed.

Analysis of the relationship between the establishment of Community Based-Tourism and multidimensional poverty reduction in rural households

The aim of this document is to analyze the relationship between the implementation of Community Based Tourism –CBT– and the reduction of multidimensional poverty in rural households in Mexico, from 2010 to 2018. For this, a multinomial logit model is used. The data were obtained from databases of poverty of the National Council for the Evaluation of Social Development Policy –CONEVAL–, and from databases of the National Household Income and Expenditure Survey –ENIGH–. The results reveal that the CBT is a model of tourism governance that contributes to decrease multidimensional poverty in rural households in Mexico, emphasizing that the greatest effect is shown on extreme poverty situations. Advancing from a condition of extreme poverty to one of moderate poverty constitutes a titanic change, not only because people can increase their ability to satisfy their basic food needs and their well-being, but also because their conditions of vulnerability are reduced.

Agent-based modelling application for social forestry policy evaluation

Social forestry (SF) as a community involvement program in forest areas needs to be frequently evaluated, particularly on policy aspects considering the dynamics of program implementation. Policy issues related to SF program have not been well identified. As a result, the implementation of SF policies may not achieve the target and recurrently lead to new problems. This research aims to develop the best scenario to support the achievement of SF target but is limited to SF areas adjacent to oil palm plantations. The actor-based modelling was developed using Netlogo 6.2 analytical tool. The results showed that the implementation of SF program should include the economic welfare improvement of local communities as a main consideration. The best scenario to achieve SF target is providing full access for local communities to manage forest areas and developing a mechanism to market the commodities by considering domestic wood consumption. The model simulation indicates that this management approach would be able to maintain forest cover as well as increase the community’s income. Therefore, information on wood consumption level needs to be promoted as an investment opportunity in the forestry sector, which has not been well considered previously in SF program. This strategy can be used to increase the participation of local communities in SF program by providing sufficient economic benefit as well as improving the inclusion of local communities in sustainable forest management.

The future of Nordic criminal policy evaluation

Nordic criminal policy evaluation has unique features, such as ones related to policy context, policy content, and the availability of excellent register data. This paper briefly lays out these features and argues that the future of Nordic criminal policy evaluation could well lie in exploiting these features even more. It is argued that we should aim to tie criminal policy evaluation to social policy evaluation more broadly. And that we should aim to use policy evaluations to study margins of behavior rather than “just” measure average effects of reforms or policies. These aims will be hard to reach unless we think of and search for even better data than we already have.

A análise do ciclo das políticas: uma ferramenta para Assistentes Sociais

This article aims to present some theoretical concepts and models of public policy analysis. The aim is to provide social workers with a theoretical analysis of the social policy process with special relevance to the model of analysis of the policy cycle in phases or moments. This option is related to the perspective of the social worker as an implementing agent of public policy, following the perspective of Michael Lipsky (1976, 2010), who considers implementers as active agents with influence on policy, as real "policy makers". Thus, the article presents the three phases of the cycle - formulation, implementation and evaluation - in order to present a general framework that can be operationalised and used as a tool to analyse the policies that these professionals implement. Facing the need to analyse the policy one implements contributes to the politicisation of intervention, through the mobilisation of power in the struggle of forces that characterise the social field, to combat inequality and defend rights and social justice. If this challenge is not taken up, the social services profession may be assumed to be merely executive, abdicating its propositional function and its active role in the formulation, implementation and evaluation of social policies.  

PREDICTION OF SOCIAL LAG IN MEXICO: A MACHINE LEARNING APPROACH FROM ECONOMIC UNIT DATA

Social lag in Mexico is officially calculated at the municipal level every five years, based on data from the population and housing census, by the National Council for the Evaluation of Social Development Policy (Consejo Nacional para la Evaluación de la Política de Desarrollo Social, CONEVAL). However, it is advisable to have annual forecasts of social lag for the follow-up of public policies. This study presents a machine learning approach to predict the classes or degrees of social lag (high, medium, low) at the municipal level in Mexico, based on information on economic units from the 2015 National Statistical Directory of Economic Units (Directorio Estadístico Nacional de Unidades Económicas, DENUE). Three supervised machine learning classifiers were implemented: logistic regression, support vector machine and random forests; and they were trained and tested in prediction based on information from counts of economic units, in their different categories, population and geographic coordinates of the municipalities; likewise, objective social lag classes were used at the municipal level, calculated with 2015 census information, reported in the literature. The criteria for evaluating the performance of the classifiers were the F-macro value, the overall accuracy and the area under the curve (ROC). The results indicate that the best overall performance was obtained with the random forest classifier with an F-macro value of 0.713 and an overall classification accuracy of 0.716; and F1-macro values for the high, medium, and low social lag classes of 0.596, 0.730, and 0.822, respectively. This classifier was used to predict social lag for 2016 and 2017. The results showed that there is a relationship between social lag and economic units aggregated at the subsector level, and that the proposed approach represents a viable and low-cost alternative for predicting social lag when census information is lacking.