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Background Data on functioning and disability collected at population level is essential to complement mortality and morbidity, to estimate rehabilitation needs of countries and regions and to monitor the Convention on the Rights of Persons with Disabilities (CRPD) and the Sustainable Development Goals (SDGs). The objective of this paper is to briefly report the development process of the WHO Model Disability Survey, its data analysis strategy as well as its reliability and ability to measure low to high levels of functioning and disability across countries. Methods The development process is described in detail, and a secondary analysis using Rasch methods is conducted to report reliability and targeting using data from eight national and two regional implementations of the survey. Results The currently available versions of the Model Disability Survey are presented. The survey has good to very good internal reliability and good targeting in all included countries. Conclusion The participatory and evidence-based development, consideration of the expertise of stakeholders, the availability of previously developed ICF-based surveys, and WHO tools targeting functioning and disability are reflected in its good to very good psychometric properties. The survey has been implemented to date in Afghanistan, Cameroon, Chile, Costa Rica, India, Laos, Pakistan, Philippines, Sri Lanka, and Tajikistan, and is used to inform policy-making, to monitor the CRPD and SDGs and to plan the delivery of rehabilitation services.
Movement of labor from agriculture to nonagriculture and the associated increase in farm size through structural transformation are at the core of economic development. We conduct a comprehensive review of the literature exploring the causes and consequences of the transformation. We discuss ( a) the size and determinants for the persisting wage gap between agriculture and nonagriculture, ( b) policy-induced barriers to structural changes, ( c) the role of trade costs and technical change in shaping the nature of structural transformation and comparative advantage of regions, and ( d) how the overall development of an economy affects the relationship between farm size and farm productivity and hence changes competitiveness of different scales of farms. We also identify questions for policy and research and the ways in which new sources and interoperability of data can help answer these questions. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
This paper examines the impact of the legal status of overseas migrants on their wages upon return to the home country. Using unique data from Egypt, which allows us to distinguish between return migrants according to whether their international migration was documented or undocumented, we examine the impact of illegal status on wages upon return. Relying on a Conditional Mixed Process model, which takes into account the selection into emigration, into return, and into the legal status of temporary migration, we find that, upon return, undocumented migrants experience a wage penalty compared with documented migrants, as well as relative to non-migrants. Our results are the first to show the impact of undocumented migration on the migrant upon return to the country of origin.
What enables social capital to contribute to sustained poverty escapes, and what could compensate for the negative effects of adverse social norms that inhibit pathways out of poverty? This paper seeks to answer these questions in Ethiopia by analysing three rounds of the Ethiopian Socioeconomic Survey (2011/12, 2013/14, and 2015/16) alongside fieldwork in Tigray, Amhara, Oromia, and SNNPR comprising focus group discussions, life history interviews, and key informant interviews. The study finds that families able to sustain poverty escapes typically possess a combination of material wealth, human, political and social capital, all underpinned by an enabling environment marked by factors including an evolving education system and pro-poor political settlement. Better-off households are then able to draw on social capital during shocks that could otherwise precipitate declines in wellbeing. However, the social events which sustain social capital can be a double-edged sword. Families may spend much on weddings, funerals, children’s christenings and birthdays, and inaugurations of newly houses. Reciprocity is expected when organizing these feasts, which poor families find difficult to maintain. Accordingly, some take credit and become indebted, others sell livestock and limit their ability to cope with shocks, and some young people are also forced to migrate to generate income to settle family debt. Based on these findings, policy suggestions are offered, such as through promoting public discussion of migration risks and mitigation of these risks, group-based insurance to help support costs for feasts, and expanding the scope of PSNP transfers to recognize the importance of idiosyncratic shocks.
Vulnerable road users (VRU) such as pedestrians, motorcyclists, and bicyclists, account for more than half of total road traffic fatalities in developing countries. In urban India, VRU consist of more than 80% of the fatalities. Although in Indian cities, the share of VRU is considerably high, suitable VRU-friendly facilities are not efficiently planned. In this context, the present paper aims to develop a systematic approach to enhance VRU safety at the urban intersection level in the context of a developing country. Using 6 years’ crash data (2011–2016) from “Kolkata Police”, India, the applicability of the present research framework is demonstrated. To examine the major risk factors associated with pedestrians, motorcyclists, and non-motorized transport users (NMT: bicycle, cycle-rickshaw, and hand-pull carts), three sets of crash prediction models are developed with the help of Poisson and negative binomial analysis. The study outcome reveals that vehicle volume and speed, inadequate sight distance, and the absence of designated bus stops significantly affect the likelihood of fatal pedestrian crashes. Alternatively, overspending and overtaking behavior by motorcyclists, and restricted sight distance increase the fatality risk of motorcyclists. Speed inconsistency between motorized and non-motorized vehicles, insufficient street lighting, and inadequate sight distance increase the risk of NMT users. The overall study outcomes specify the need for segregation between motorized traffic and VRU at urban intersections by providing dedicated lanes for VRU along with suitable crossing facilities; implementing signalization with a distinct phase for VRU. The study also highlights the importance of speed management measures in urban India.
What are the basic types of social network ties captured by name generators? While there have been several classifications proposed, and a large proliferation of name generators capturing various tie content has emerged, there is no clear way to map a given name generator to a particular tie type. Building on previous research, this paper proposes a framework for doing so in a principled way based on two studies. Study 1 is a dimension reduction of 24 common name generators. We find two dimensions (Valence and Social Distance), three positive tie types (Admiration, Closeness, Socialize), and three negative tie types (Active Conflict, Passive Conflict, Contempt) and use Youden's J statistic as a metric to identify the name generator that best maximizes sensitivity and specificity for detecting our tie types. We find that the most common name generators used by researchers fall within just one tie type (Closeness). Study 2 models these six tie types as predictors and outcomes of important sociological variables and finds that each tie type is associated with distinct patterns of emotions, social support, social status, and social roles. Our taxonomy makes a contribution to network theory as well as study design. In particular, it advances our understanding of the nature of signed ties. We find that negative ties are both bipolar and orthogonal, and distinguish between two types of ambivalence. Moreover, the findings contribute to the further refinement and elaboration of a comprehensive taxonomy of network ties.
The present paper examines the role of the built environment on pedestrian-vehicular crashes, pedestrians’ risk perception, and pedestrians’ unsafe activities at the urban signalized junctions in the context of a developing nation. A conceptual framework is established to recognize the possible associations between the built environment, risk exposures, pedestrian activity, risk perception, and pedestrian crashes. The proposed research work is demonstrated with reference to the metropolitan city of Kolkata, India. The Negative binomial models are developed to study the association between the built environment and police-reported crashes. Likewise, to examine the role of the built environment on pedestrian risk perception Ordered logit models are developed. The study outcome shows that an increase in average vehicular speed by 10 km per hour at a junction is expected to increase the chance of pedestrian fatalities by 50%. With an increase in minor road width by one unit, pedestrian fatality risk is likely to rise by 7%. The lack of a pedestrian signal head is expected to increase pedestrians’ perceived risk by 1.2 times; whereas the absence of adequate sight distance is probable to increase pedestrians’ perceived risk by 2.3 times. Subsequently, a set of beta regression models are developed to examine the impact of the built environment on pedestrians’ unsafe activities. The outcomes confirm that ‘pedestrian’s usage of mobile phones while crossing’ (distraction) increases the possibility of pedestrian signal violation behavior by 1.7 times. Inaccessible zebra crossing and on-street parking are likely to increase pedestrians’ risky crossing behavior by 16% and by 14%, respectively.
During the last decades, the United States experienced an increase in the number of natural disasters and their destructive capability. Several studies suggest a damaging effect of natural disasters on income. In this paper, I estimate the effects of natural disasters on the entire income distribution using county-level data in the United States. In particular, I determine the income fractions that are affected by natural disasters. The results suggest that in the short-term natural disasters primarily affect middle incomes, thereby leaving income inequality levels unchanged. In addition, the paper examines potential channels that intensify or mitigate the effects, such as unemployment insurance or disaster severity. The findings show that unemployment benefits are an important adaptation tool that reduces the effects of natural disasters. In contrast, the occurrence of multiple and severe disasters aggravate the effects. Finally, the analysis detects heterogeneous effects on incomes by disaster type.
The economic and social development of nations relies on their population having physical access to services and employment opportunities. For the vast majority of the 3.4 billion people living in rural areas, this largely depends on their access to urban centers of different sizes. Similarly, urban centers depend on their rural hinterlands. Building on the literature on functional areas/territories and the rural–urban continuum as well as insights from central place theory, this review article advances the notion of catchment areas differentiated along an urban-to-rural continuum to better capture these urban–rural interconnections. This article further shows how a new, publicly available dataset operationalizing this concept can shed new light on policymaking across a series of development fields, including institutions and governance, urbanization and food systems, welfare and poverty, access to health and education services, and environmental and natural resource management. Together, the insights support a more geographically nuanced perspective on development.
UK power sector decarbonisation is an important step toward achieving the country’s 2050 net zero target. Two uncertainties are particularly relevant to this effort: future electricity demand and biomass availability, the latter due to the potential for negative emissions in the power sector from biomass energy with carbon capture and storage. Using the dynamic simulation model FTT:Power, this work explores the impacts of different power sector policy portfolios on emissions, electricity prices, and government spending under these uncertainties. It finds that deep decarbonisation of the UK power sector is possible, including substantial negative emissions, but that this will require ambitious and diversified policy. Carbon pricing is found to be the single most important decarbonisation policy instrument. Direct regulatory phase-out of unabated fossil fuel power generation is similarly crucial for power sector decarbonisation, and for building resilience to biomass availability uncertainty. That said, under all policy portfolios biomass availability plays a key role in enabling net negative emissions in the power sector. This suggests the importance of securing and improving UK biomass supply, and of decarbonisation outside the power sector to reduce the need for negative emissions to begin with.
There is an urgent need to raise awareness of the risks for generalizing 'flood' within the development of new risk assessment framework and adaptation strategies, and further outline opportunities for ensuring current and future multiform flood risk can be both assessed and reduced in particular for the most vulnerable populations. This requires enhancing modelling capabilities to embed the different yet interlinked dimensions of subtypes of climate shocks and their feedbacks. As we continue to see an increase in occurrence of compound risk, the importance of flood type specificity will grow, especially as areas experience certain types of floods for the first time. In this perspective we review current efforts to integrate flood risk within public and private sectors across the hazard modelling, financial and macroeconomic and humanitarian communities. We argue that while there are ongoing efforts in compound risk assessment, compound risk financing and compound risk anticipatory action, they remain almost exclusively focused on compounding of a primary disaster type, and fail to highlight the important differences of 'subtypes' of events (which from an impact profile perspective, can be as different as primary types). We then provide recommendations for developing climate change-responsive risk assessment methods and risk mitigation policy for multiform flood events.
Urban challenges are increasingly framed in the context of broader objectives of socio-economic development and macro-regional evolutions. Cities and the myriad networks in which they are embedded have thus been placed at the center of regional integration agendas. This paper benchmarks contemporary regional integration levels in the Horn of Africa by examining its cities' connectivities in transport networks. To this end, we specify a composite network consisting of air/train/road connectivity and analyze cities' eigenvector and betweenness centralities within these networks. We find that the importance of national spaces for inter-city connectivity is much more evident in the Horn of Africa than in other parts of the world, which is also visible in the peripheralization of cities in borderlands. We argue that the region's connectivity needs to be understood from a multiscalar and multimodal perspective and provide a baseline against which the impact of future interventions aimed at enhancing city connectivity/regional integration can be examined.
Using a sample of Chinese households, we study how a type of social capital, private social networks, affects access to credit and its implications for consumption. We find a strong and likely causal link between private social networks, use of informal credit, and household consumption. Informal credit via private social networks facilitates household consumption especially for households that experienced a recent health shock, that face financial constraints, and that do not have access to formal finance, and the effects are more pronounced in poor regions and rural areas.
This paper assesses the effects of monetary policy shocks on the macroeconomy and the euro area banking sector after the global financial crisis. First, financial risk-return indicators of the banking sector based on a compound option-based structural credit risk model are embedded in a large macro-financial quarterly database covering the period 2008Q4-2019Q4. Second, a SFAVAR identifies and estimates the shocks’ responses relating them to the endogenous build-up of banks’ vulnerabilities which are consistent with the internally coherent structure of the credit risk model. By introducing structure in the understanding of banks’ asset-liability management behavior following monetary policy shocks, the research strategy contributes to disentangling results that are often mixed in the empirical literature. The study finds that unconventional monetary policy, in particular the Asset Purchase Program of the European Central Bank, seems to have been more successful than conventional monetary policy in raising output and inflation. The desired boost to bank lending has been muted and loan cyclicality has varied across countries and loan types. The performance of the banking sector following monetary policy shocks can be characterized by a drop in expected return on equity and assets, a relaxation of lending conditions and increased correlation between banks’ assets return and the market return, a mechanism pointing to enhanced risk-taking. While banks’ probabilities of default fall following monetary policy shocks, the price of risk increases. Banks’ net worth rises via higher market capitalization and implied assets value together with lower volatility, despite often incurring more debt. Risk-taking in the banking sector may pose a risk to financial stability, especially if its effects on banks’ vulnerability spread and increase systemic risk. The unintended endogenous build-up of macro-financial vulnerabilities may need to become part of monetary policymaking.
Plain English Summary Firms that increase their sales quickly are responsible for a large part of industry-level productivity growth, but only during their high-growth phase. In contrast, firms that increase their employment quickly often experience falling productivity. This paper quantifies the contribution of high-growth firms (HGFs) to industry-level productivity growth, using Hungarian data. We find that i) the contribution depends strongly on the way growth is measured: firms growing in terms of revenue tend to contribute more than firms growing in terms of employment, ii) HGFs contribute to productivity growth mainly through their high-growth period, but not afterwards, iii) these contributions are not strongly associated with industry characteristics, though they tend to be larger in industries with more young firms. Our results are relevant for policymakers who are interested in the productivity effects of HGFs not only job creation, and suggest that expected productivity effects i) depend on the type of high growth, ii) are concentrated to the high-growth period, and iii) might not be enhanced by industry targeting.
We study the dynamics of wage inequality in Latin America in the past two decades. We find a consistent trend reversal in wage inequality in the region since the early 2000s: wage inequality fell across all countries in a way not predicted by the trends each country had experienced in the 1990s. The decline in wage inequality is explained by a disproportional expansion in the real hourly wage among low‐paid workers, reducing both lower and upper tail inequality. About 40% of the observed reduction in wage variance was a response to the more equal wage structure, while the rest derived from a reduction in wage dispersion among workers with similar observable traits. The equalization of the wage structure in the 2000s is correlated with a reduction in the wage premium across education, experience, and place of residence. The reduction in the gender gap contributed, to a lesser extent, to the trend reversal.
Using data drawn from 2010, 2012, and 2013 American Time Use Survey Well-Being Modules, this paper examines the existence of son preference among fathers in the U.S. by estimating the effect of child gender on the fathers’ subjective well-being. A wide range of subjective well-being measures, including happiness, pain, sadness, stress, tiredness, and meaningfulness, is analyzed, and fixed-effects models are adopted to control for unobserved individual heterogeneity. The results from the full sample show that fathers feel less sad and tired when interacting with both sons and daughters versus with daughters only. In families with only one child, fathers report no difference in subjective well-being when spending time with a son versus with a daughter. By further stratifying this sample of fathers by child’s age of three, we continue to find no difference in paternal subjective well-being between being with a son and with a daughter when the child is younger than three. However, when the child is three or older, we find that fathers feel less stressed and more meaningful being with a son versus with a daughter. The results from Asian fathers, in contrast, show a tremendous reduction in stress in activities with sons only than with daughters only. These results indicate son preference does not exist in the general population. If there is any, it only exists among Asian fathers.
Data scarcity has hindered studies on the impacts of climate change on land prices in the coastal regions of developing countries. Focused on the Indian Sundarbans, this paper is at the forefront of such research. Market conditions in the region feature unregulated transactions, unenforced zoning, and a lack of disaster insurance. For many residents with hereditary land ownership, stark poverty eliminates any risk buffer provided by savings or other non-essential liquid assets. Using new household surveys and environmental data, our study hypothesizes that salinization and cyclone strikes have already adversely affected land prices. We quantify such impacts using a georeferenced panel of 342 salinity monitoring stations and a spatial raster database on all cyclonic storm strikes since 1970. Our econometric results reveal highly significant negative impacts for both factors. We use the regression results to predict land prices for the most and least favourable environmental conditions recorded in our database. The results show that these climate change–related conditions account for spatial differentials greater than an order of magnitude in land prices. Such extreme risk differentials suggest high financial and fiscal stakes, underscoring the critical importance of appropriately targeted adjustment policies.
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