What is it about?

Social programs have been adopted by many nations to help their citizens manage a range of challenges, from economic struggles to health risks. Historically, post-Industrial Revolution, developed nations like those in Europe and the United States began implementing these programs in the late 19th to early 20th centuries. However, many developing countries only began to focus on these protections in the latter part of the 20th century, often encouraged by international organizations, especially after growth-driven policies failed. Yet, there's a potential downside in these developing nations. While these programs aim to help the vulnerable, they might unintentionally interfere with pre-existing local support systems. Think of it this way: if a government program provides financial help to a family, will their neighbors or extended family still see the need to assist them as they did before? This phenomenon, where public aid reduces private help, is known as "crowding-out." If severe enough, it could nullify the benefits of these government programs or even make things worse. Our study dives deep into this crowding-out effect in developing countries. We meticulously analyzed recent research, specifically studies that can pinpoint cause-and-effect relationships, to understand the real impact of these social programs. We looked at different types of social protections, methodologies used in studies, geographic regions, and over time. What did we find? For one, there's strong evidence that public benefits do indeed reduce private support, sometimes by as much as 91%. Interestingly, this displacement seems more pronounced in developing countries than in developed ones. Secondly, this effect is consistent across all types of social protections. Lastly, the extent of crowding out can depend on factors like the recipient's gender, education, and financial status. In essence, while social programs are invaluable, it's crucial to understand their broader implications in different settings, especially in developing countries where community support plays a pivotal role.

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Why is it important?

Understanding the crowd-out effect is crucial, and here's why: 1. Efficiency Concerns: When we design public support programs, the idea is to help the vulnerable. However, if the introduction of these programs significantly reduces the assistance people receive from private sources, we have to ask – are these programs really benefiting the recipients? In extreme cases, if private support drops more than the public support provided, it might mean that beneficiaries end up worse off. This isn't just about one kind of program, but a concern across various initiatives, be it health insurance, cash transfers, or pensions. 2. Impacts on Program Evaluation: Imagine you're assessing the success of a public program. You gather household data and see an increase in income due to the program. Great, right? But what if, due to crowding out, the household's private assistance has gone down? If you don't account for this, you'll have an inflated view of the program's success and its effects on things like poverty reduction. 3. Social Dynamics Insights: The crowd-out effect isn't just about money and people, families, and communities. When we observe how people react to these public programs, we learn about the fabric of society. Do families share resources? How connected are individuals to their extended families or communities? How people adjust their support in response to public programs offers a window into these deeper social dynamics. In a nutshell, examining the crowd-out effect is more than just a technical exercise. It's about ensuring our public programs truly benefit the intended recipients, accurately gauging their impact, and deepening our understanding of societal relationships.

Perspectives

Because social protection programs generate displacement of private transfers, policymakers need to factor in the magnitude of this behavioral response. We document stark heterogeneity of the estimates by important demographic characteristics, such as gender and poverty status. We find that the two aspects of the crowd-out effect, the extensive (the probability of receiving any positive private transfers) and the intensive margin (the number of private transfers received by those who receive positive transfers), strongly reinforce each other. This reinforcing nature of the two aspects of crowding out may be of use to researchers who are constrained by data limitations—it may not be out of the question, for example, to assume the existence of crowding-out if one finds a strong decrease in the probability of receiving private transfers along with other indications. In specific circumstances, crowding-in could occur (especially if the recipient is of low-income status and the existing pre-program private transfers are negligible). Our interpretation of the accumulating evidence is that, while robust evidence exists that social protection programs could result in non-trivial displacements of already existing private support systems, there are a number of important caveats related to the type of public program, country-setting, and characteristics of the recipient and their extended support network. We document consistently large crowd-out effects in response to all social protection types. Furthermore, gender and the income level of safety-net recipients can interact in important ways with the willingness of family networks to provide transfers. In sum, the relative merit of introducing various safety net benefits and the potential leakage, disincentive costs to the program recipients, and displacement effects among inter vivos transfers should be compared in choosing an appropriate program. Moving forward, future research should focus on understanding the role of various mechanisms mediating the magnitude of crowding-out. Factors such as the demographics of the country, living standards, the type of risk, and the strength of family networks likely play an important role in influencing the magnitude of the behavioral response. Expanding the evidence-base with additional research on the role of each of these factors is paramount. More broadly, our findings suggest that efforts to account for the displacement of private transfers is likely to be crucial for achieving the long-term objectives of effective public policy.

Dr. Plamen Nikolov
Harvard Institute for Quantitative Social Science

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This page is a summary of: Do public program benefits crowd out private transfers in developing countries? A critical review of recent evidence, World Development, October 2020, Elsevier,
DOI: 10.1016/j.worlddev.2020.104967.
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