The more development papers I read, the more fascinated I am with how differing empirical strategies can convey very different results. In the paper, Milovich attempts to address two gaps in existing literature regarding the important link between aid and poverty alleviation. The first includes, measuring poverty from a multidimensional view and the second is understanding the endogenous relationship between aid and poverty. I am more interested in the strategy she uses to address the first gap. Although her results demonstrate no statistical significance when poverty is measured from an income perspective, results are positive when taking a multidimensional view of poverty, which considers indicators related to health, education, living standards. I found her estimation strategy appropriate considering the importance of human capital on economic growth. It also reflects Sen’s capabilities framework, since poverty alleviation is measured by the ultimate well-being of the individual. I’m amazed at how economists are able to creatively provide solutions or amendments to existing empirical work, and produce results that are astoundingly different. This is especially important to note, as she emphasizes in the concluding remarks section, that understanding the impact of aid is crucial to attaining the SDG that aspire to reduce poverty to 0% by 2030. Additionally, it is also important to come to a clear consensus on how to define and measure poverty, so that aid is targeted efficiently and accurately.
Often when we discuss development policy, ‘problems’ of dual causality are beneficial despite the endogeneity issues that researchers face. For example, understanding how much education leads to rising income versus how much rising income increases average education levels is not necessarily a huge concern for policymakers, since policies relating to either education or income could potentially cause a virtuous cycle of development. However, reverse causality is completely different. Here, a misspecified model could lead policymakers to pursue policy that has no impact whatsoever. The question of whether or not aid reduces poverty faces this potential problem, because it could be that countries that are already poor receive more development, and thus poverty would drive aid rather than aid driving a reduction in poverty. I think Milovich’s solution to use an instrumental variable was a necessary one, although I am still skeptical that the variable exploits exogenous variation in aid. In other words, I find it difficult to believe that the additional aid that countries received when they were on the United Nations Security Council was uncorrelated with existing levels of poverty in that country. Even though levels of aid dropped back down after countries left the UNSC, this does not mean that the increase in aid was not due to increased attention to a country’s needs (and thus uncorrelated with their poverty level) but could simply be due to the fact that politicians and policymakers have short attention spans. If this is the case, the instrumental variable would be correlated with the outcome variable through channels other than its effect on the independent variable, and the exclusion restriction would be violated. It could be that this problem explains why Milovich found that aid did not reduce income poverty even though it reduced other forms of poverty included in the MPI. However, I doubt that this is a serious problem, and the results are believable for the most part. Whether or not the instrumental variable is a good one, much of the literature on the topic faces serious endogeneity problems, and this study is definitely a step in the right direction when it comes to solving these problems.
When reading this paper, something that sticks out to me is how to different definitions and measurements of poverty can tell us different conclusions in research. Its interesting that the aid has a significant effect on reducing "poverty" when the "poverty" variable is measured by the multidimensional poverty index. When "poverty" is measured through income, we see that the effect of aid is not statistically significant. It was noted in the article that more people qualify as MPI poor than income poor using the headcount method. Does this have influence on the data? The larger number of people that fall under MPI poverty could allow for a greater representation of what aid can actually do to help reduce poverty. I am not sure empirically if this makes any difference, but it was a thought that I had.
On a different note, it seems as though the components of the MPI (education, health, and living standards) could see a faster growth from aid than income would. In other words, in theory, if education and health are improved through aid, would income then slowly rise following those improvements? This echos the discussions that we have had in class on the causality/ correlation between human capital investment and economic growth.
I found this study to be an interesting one as it clearly exemplifies the importance of the ways in which we measure poverty. The most outstanding result of this study is that aid is associated with lower multidimensional poverty but not with lower income poverty. Specifically, they found a 1% increase in the average amount of aid received from the U.S to be associated with a .82%, .36%, and .64% in education, health, and living standards respectively, or a .61% reduction in the MPI on average. The relationship between aid and poverty measured by the poverty gap and headcount ratio doesn’t seem to be statistically significant, but the relationship between aid and multidimensional poverty with deprivations in health, education, and living standards, is statistically significant. This reveals the we need to be careful in the way in which we look at the impacts of poverty alleviation efforts. Just because aid may not decrease income poverty does not mean that it is not beneficial. Reductions in living standards, health, and education, and not just income, is an important indicator that aid is valuable and should be given. This discussion also reminded me of Amartya Sen’s framework of looking at capabilities as an important indicator of quality of life and poverty. I would not want someone to think that, since aid does not decrease income poverty, that we should not be giving it. It is important that we care about, and try to better, individual’s qualities of life.
I found this article to be incredibly convincing. Milovich does a fantastic job in walking through all of the ways in which the article may suffer from bias and has a variety of robustness checks that allow the reader to conclude that we are indeed looking at a causal relationship. This is certainly not an easy task. I had never truly considered the research limitations that the reverse causality between poverty and aid can cause. I found that this paper reinforced the relationship between development and poverty that we have already discussed in detail in this class. Mainly that economies need to grow to alleviate poverty, but growth alone does not cause poverty to go away. Multi-dimensional poverty that takes into account far more than mere income levels is a much better measure of how poverty is changing within a country. I found Milovich’s conclusion to be incredibly strong. The fact that an increase of 1% aid could lead to lower percentages of people deprived in education health and living standards by 0.82%, 0.36% and 0.64% respectively is truly astounding. The spillover effects of aid here become very clear. In general, I wonder how increases in education, health, and living standards continue through generations. One would hope that policies that give large amounts of aid do not end with the current generation. How do we ensure that future generations receive the benefits of those before them? This is perhaps a question revolving more around the politics of the country that is receiving aid than the country that is giving aid but I find it to be interesting nonetheless.
In this paper, Milovich talks about the different types of poverty as well as the United Nations’ Sustainable Development Goals (SDG). The main goal being to “End poverty in all its forms everywhere by 2030”. It is interesting to think about all of the different types of poverty that Milovich talks about through “multidimensional” poverty. When thinking of poverty you typically think of it monetarily. Milovich talks about how poverty is more than just a dollar figure but plays a hand in the well-being of people, education, health, and quality of life. What I question after reading through the paper is whether more focus on particular aid disbursement will have a larger effect on income poverty. Milovich primarily focuses on multidimensional poverty, as he did not see significant results of aid on income poverty. However, income poverty is still very much relevant and is still one of the most concerning factors if the world is to reach the SDG goals by 2030.
This paper provides evidence for the effectiveness of aid in reducing poverty, using alternative measures of poverty contrary to the traditional aid-growth relationship that has been the focus of previous literature concerning aid effectiveness. Not only does this paper take a new approach to investigating whether aid contributes to a reduction in poverty among recipient countries, but it also provides a detailed overview of the past fifty years of literature on aid effectiveness. The findings for the causal effect of aid on poverty reduction have been inconclusive and the relationship between aid and poverty has remained a topic of debate. The majority of previous literature has focused on the relationship between aid and economic growth, but economic growth is only one indicator of reduced poverty and does not measure other important social factors that improve the welfare of citizens. For this reason, the author chooses to use the Multidimensional Poverty Index (MPI) to measure poverty from a multi-dimensional perspective, including education, health, and living standards. The author uses an instrumental variable regression framework to estimate the effect of economic aid disbursed by the United States on reducing poverty in 64 developing countries. When using years spent on the UNSC between 1946 and 1999 as an instrument for the average U.S economic aid received by the country, the author finds that an increase in U.S. aid is associated with a reduction in multidimensional poverty. Specifically, the author found that an increase in U.S. aid is significantly associated with a reduction in schooling deprivation. Overall, the author found that the coefficient on AID remained highly significant and negative with a variety of control variable combinations and that a 1% increase in the average amount of aid received was associated with a 0.61% reduction in the MPI. This paper highlights the need to adopt more comprehensive measures of poverty in order to investigate the effectiveness of aid on alleviating poverty. By shifting to a multidimensional measurement of poverty in developing countries, the author was able to find a significant negative relationship between aid and poverty. The author calls for future research to use alternative measures of poverty in order to better understand the relationship between aid and poverty and help better inform future aid policies.
Last blog post ever! In the theme of our ongoing banter about 'it depends', I will start there. The previous literature on aid and poverty can be grouped into "it works; it doesn't; it can, but it depends". How can there be such divergent conclusions? Well, it depends on how/what the researchers are measuring. When asking my roommate the question 'does aid reduce poverty' (she has studied this question before), her answer was "no, it does not help". And that may be true…when we are solely looking at economic growth. The standard relationship between aid and income poverty is not statistically significant. We must look beyond this traditional relationship into alternative measures to give us a more holistic view on measuring poverty. The MPI looks beyond money to include education, health, and quality of life. These conclusions make me question why it is not the standard to use MPI in policy decisions, even outside the realm of aid. Shouldn't we want to have a broader understanding of policy implications beyond just money?
One of the things that stood out to me most about this paper was that it looked at the effect of aid on poverty—and particularly poverty as defined by the multidimensional poverty index—not simply on growth or income poverty. I think this is really interesting because it reminds me of our discussion about the returns to investments in education being dependent on other factors, such as health and nutrition. It makes sense then, that for aid to be effective, certain conditions must be in place, like functioning healthcare centers and good schools which contribute to human capital formation (this parallels the reading on trade and poverty which highlights that a beneficial relationship between these two variables is conditional on factors like education, institutions, and financial markets). When aid decreases multidimensional poverty, as shown in this paper, factors such as education, health, and living standards improve, and there is now even greater potential to see higher returns to aid as measured by income, productivity, or employment opportunities.
After reading this paper I also immediately connected it to our discussions of disease burden and how specific aid targeted at fighting diseases like malaria has the potential to make significant positive impacts in the developing world, particularly through effects on human capital development. Without this specific aid, in the form of mosquito nets, for example, other monetary aid could have a limited effect. All in all, while considering this case, as well as the provision of aid in the form of de-worming medication in the case about conditional returns to education that I mentioned earlier, I am sure that targeted aid, and I wonder if even ‘in kind aid,’ ought to be a greater focus for at least initiating poverty alleviation, particularly multidimensional poverty, which would then create conditions in which returns to monetary aid could increase. *I know this approach may not actually be better/there are some tradeoffs associated with ‘in kind aid,’ but this is just where my thoughts took me after reading this paper and thinking about our other class discussions
I thought that this paper served as a great final paper for us to discuss, as it incorporates many of the things we have talked about throughout the course of the semester, such as the numerous ways of measuring poverty, the role of economic growth and development on poverty, and the fact that there is rarely a catch-all solution that works everywhere. I found it incredibly interesting that the literature demonstrates that there is a lack of convergence regarding the empirical results, and that there is still a lot of controversy on the effect of aid on poverty alleviation, which again shows us that injecting aid into countries will not necessarily be helpful and also that there is an inherent endogeneity issue associated with attempting to estimate the effect. More generally, it shows how measuring the relationship between aid and poverty is not straightforward, at all, especially given the various ways of measuring poverty. It seems the author was able to relieve some of the endogeneity issues by creating an instrument including the number of years a country has spent on the Security Council of the United Nations, which was a creative way of expanding the literature to try to get a more conclusive answer than (ECON 280 classic), “It depends.” I’m not sure how successful the author was, although it seems as if the paper took a unique approach that was conveyed convincingly and successfully. As the author explains at the end of the paper, it’s necessary that future research focuses on the impact of more precise dimensions of aid on specific indicators over time. It’s unclear when or if we will ever get a straightforward answer, and I would be surprised if there is ever one to be found, since measuring the impact of aid on poverty is so inherently difficult. It’s incredibly important that economists continue to study this relationship, in order to inform policy makers and aid-giving countries, particularly in light of the SDG of eliminating global poverty by 2030.
This paper was a nice paper to have as the last paper of the semester. I particularly found the discussion of whether or not it was poverty driving aid or aid reducing poverty to be quite interesting. In the past when we talked about dual causality, it didn’t matter the direction as both were positive. For example female agency driving development versus development driving female agency. Both of these stories were true and it did not necessarily matter in which way the casual link ran because either way, the outcome was something positive. But, with the issue of aid, it does matter. If poverty leads to more aid, but that aid doesn’t actually reduce poverty, then spending is essentially wasted. Although, if aid does reduce poverty then the spending is justified. What makes this issue even more fascinating is that it is subject to the classic “it depends” phenomenon. Sometimes aid can reduce poverty, but in other instances it might not. What was interesting to me is that this study found that aid may not impact income, but can improve living standards, education, and health when gains from aid are measured using the MPI. I actually think that there may be benefits to aid targeting living standards, education, and health rather than just increasing the income of the poor. This is because households may misallocate funds (not necessarily intentionally, but just not make proper investments in education due to asymmetric information). Furthermore, targeted aid on education and health could cause improvements to human capital that could have greater long term effects.
I firstly agree with the last few blog posts before mine, as this was an interesting and fitting paper for us to read to close out the term. I think some of the major components of this paper are indicative of some of the significant themes that we have learned throughout the term. One of these themes is viewing situations from various perspectives, especially with regard to measures of development and poverty alleviation. As we have seen in this paper, when this empirical strategy was employed to demonstrate a link between aid and income-based poverty, there was inconclusive evidence, though the situation changed when the authors utilized the multidimensional measure of poverty. I think this strategy speaks volumes to the truth about poverty and development in the world - it is more complicated and interconnected than it may seem on the surface. Poverty certainly does embody an income component, but it is more widespread than that, and when you include variables and measures of education, employment opportunities, health outcomes, climate stability, freedoms, gender equality and more, you begin to get a fuller picture of how poverty and development must be addressed through so many different pathways. As the authors demonstrated in this paper tonight, you begin to form different conclusions when you implement this more comprehensive measure of poverty. So I guess that is one of the big takeaways I learned from this paper but also from this course - never to assume, and to look at issues from as many perspectives as possible to be able to find new and creative pathways to address inequality in the world.
One aspect of this paper that immediately stood out to me is its use of the Multidimensional Poverty Index (MPI) to answer their research question of whether aid reduces poverty. By using the MPI, Milovich acknowledges the fact that the level of poverty is not simply a measure of income. Rather, it also has to do largely with social factors and how these factors, such as education and health, impact people’s well-being. Using the MPI as an alternative measure of poverty also allows for a greater understanding of the relationship between aid and poverty alleviation, other than through the traditional lens of economic growth that has been primarily used in previous studies. Interestingly, while the results did not show a significant relationship between aid and poverty alleviation when measured from an income perspective, there was a significant relationship between higher amounts of aid received during 1946–1999 and lower MPI between 2000 and 2014. However, while Milovich notes these results, he also acknowledges the controversy of the topic and the “endogeneity bias” that exists between aid and poverty alleviation that weaken causal links.
While this paper focuses mostly on foreign aid through the lens of major governmental organizations such as UNICEF and the World Bank, I am left wondering how the impact of foreign aid on poverty alleviation may look different if Milovich looked solely at NGOs and other private agencies. Last year, as part of a foreign aid colloquium, I read A White Man’s Burden: Why the West's Efforts to Aid the Rest Have Done So Much Ill and So Little Good by William Easterly. In this account, Easterly scorns governmental aid for actually inflicting more harm than good in developing countries, and maintains that private agents are the solution to this problem. He argues that private agencies work on a far more individualized level in communities. I was reminded of this argument when reading Milovich’s paper and wondered what his response would be to Easterly’s account.
The literature review in this paper was very interesting. I feel that on some level there is this idea that all people need to get out of poverty is money, which of course we know is not true. In this same way, the idea that economic growth decreases poverty seems logical. However, I am surprised to see in this paper that growth was used as a proxy for poverty. It seems to take quite some time for the literature to get past this idea, but we know that there are corrupt and authoritarian governments that may grow the economy and never let the profits reach the people, especially not the poor.
What I find concerning is how important being a member of the UNSC is to receiving aid. For each additional year sitting on the council, a country receives approximately $21M more in aid from the US. It seems that UN should be working to help all countries to alleviate poverty and develop at all times and not just “when its their turn” or there’s an emergency.
A bit of a side note but I really appreciated the way Milovich walked through the statistical analysis and results. The empirical analyses and estimation strategies are my favorite part of economics, so I appreciate how clearly, he explained his methodology. I like how he explained all the potential endogeny with the error term and the independent variables to explain why he ran a two stage least squares regression analysis. This is perhaps not the most relevant take away for the purpose of our class discussion, but interesting and appreciated, nonetheless.
This paper, like others we have read this semester, emphasizes that there is there isn't a recipe for development, there is not a single solution that works everywhere. In some cases aid helps in reducing poverty, in some cases It doesn't... "It depends". This paper is very technical compared to other papers we have read, and there is an interesting technical question when trying to claim causality. Does more aid reduce poverty or does poverty just attract more aid? This reverse causality is an endogeneity problem that they overcome using instrumental variables. In regression analysis, Milovich uses the Multidimensional poverty index as the measure of poverty, where in most studies we've read they measure poverty in terms of ones income. The study concludes that Aid does indeed reduce poverty- in terms of MPI (living standards and health) Milovich establishes causality with results that are statistically significant. However, aid might not reduce poverty in terms of improving income. This suggests studies should be measuring poverty differently. We discussed poverty earlier in the semester and concluded that being poor goes beyond the amount of money you make, and this study follows that line of thinking. Outside of one's income, standard of living, health, and education matter when discussing poverty. Overall this paper is very convincing and ties together a lot of discussions from earlier in the semester
When comparing results from the OLS estimation in Table 2, we see that aid is more significantly related to a decrease in the MPI and the multidimensional headcount ratio than to a decrease in income poverty, where only a negative relationship for the severe income poverty gap is seen. In fact, an increase of just 1% in U.S. aid directly lowers the percentage of people deprived of education, health and living standards. Although the impact is less than 1% for each of the 3 previously mentioned categories, education comes close to having a direct 1:1 ratio (if I’m interpreting correctly in that 1% increase in aid causes a 1% improvement in the education-deprived population.). Furthermore, the MPI as a whole is reduced by 0.61%. This obviously varies for different countries and depends on other factors as well, but these values are on average. This data shows that MPI is a more accurate measure for analyzing the relationship between aid and poverty alleviation. The Multidimensional Poverty Index (MPI) takes into account factors such as nutrition, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, flooring, and assets. Meanwhile, institutional quality is measured by using a country’s level of freedom (political rights, civil liberties) and measures for fractionalization (ethnicity, religion and language). Although this is obviously a more complex and time-consuming measurement than just income or a country’s growth, its findings are interesting, particularly when thinking about the Sustainable Development Goals and the policies that would most effectively help us reach them by- ideally- 2050. I wonder how specifically the application of these findings would alter some of those efforts or progress tracking.
This paper tracks US foreign aid to developing countries as it affects the recipient country’s MPI, or multidimensional poverty index. Consistent with much of our reading, this paper studies the outcomes of aid as it affects education, health, and living standards, instead of simply focusing on changes in income. Previous studies have had mixed success tracking the results of foreign aid, concluding that aid can sometimes help or not help a country's development, and that it depends on external factors. Most of these factors are controlled for in the OPHI study, although that part of the study setup was a little confusing for me. The study tracked US aid from 1949-1997 vs the average poverty levels (MPI) from 2000-2014, and tracked a negative correlation between aid and MPI. I found the discussion of the goals of aid interesting, especially in the context of the US. Aid can often be politically motivated instead of motivated simply by human rights, and I believe when the motives for aid are distorted by political agendas, the return on MPI is likely less important. I’d be interested to hear about further study that can closely track aid through a developing country’s economy to determine the most effective avenues for aid.
I also thought this was quite an interesting paper to conclude our term with, as it strung together quite a few of the major themes and topics we have covered this semester. I was particularly interested by Milovich's use of the concept of "multidimensional poverty", as it is important to realize that poverty is more than just a lack of income, but also can be accounted for by nutrition, education, and human capital. Having this concept in mind, it makes it easy to realize how different forms of poverty are all interconnected, and how they all play such a large role on one another. It is interesting to me to be able to think about how aid can improve certain forms of poverty, but not others. I think that the most traditional way that we (probably as Americans) think of poverty is by wealth, but this is certainly not the entire story and we end up taking things such as health and education for granted. Certainly investments in health and education will produce societies where there are larger incomes, and as we have repeatedly discussed throughout the term, this is where foreign aid would benefit the most.
Juliana Milovich’s paper has an extremely wide berth, considering not only the impacts of aid on poverty but also the differences in institutions, natural resources, and social factors in the 64 sample countries. I found the mechanism of measuring aid particularly interesting. Milovich establishes that there is a large correlation between sitting on the United Nations Security council and the amount of aid received by the United States. In class, I would love to consider the exclusion restriction which assumes the instrument is randomly assigned and that it is not related to the poverty other than through the increased levels of aid (if I understand properly). I wonder if a position on the UNSC provides political power which could aid a nation in decreasing poverty. The results seem to support the hypothesis that the aid associated with a UNSC position does seem to reduce MPI but not an income perspective of poverty. However, the scatter plots seem (at least to me) to suggest there is a large amount of variability for countries which experience less than 5 years as a member of the UNSC. I find these results interesting as well, and I would like to discuss the linkage aid has to the components of the MPI (such as water availability, health, and education).
I found it interesting that there was no statistically significant relationship between income poverty and aid given by the US, as I thought that there would be a more positive correlation. This goes on to show that poverty and a country's economy go far beyond just measuring people's income. This also shows that simply injecting aid into third world countries isn't a reliable way of dealing with poverty (because "it will depend"). As an alternative method of measuring poverty, Milovich talks about the Multidimensional Poverty Index (MPI), which observes poverty from many different aspects (education, health, living standards) and eliminates the reverse causality problem. Using the MPI, Milovich found that an increase of 1% in U.S. aid resulted in lower percentages of "multidimensionally poor people deprived in education, health, and living standards (0.82%, 0.36%, and 0.64%, respectively)." This finding is significant, as this precise measurement/dimension of aid exposes economists and policymakers to better ways of helping people in poverty. For example, these results could be a sign that policymakers should focus less on using figures like income to measure the success of their policies (income reports are prone to dishonesty and inaccuracy). Instead, perhaps they should focus more on education, health, and living standards since these factors seem to provide a more holistic and accurate depiction of poverty and growth.
I thought this paper was interesting in how Milovich prefaced the entire piece saying “I seek to answer this question by closing two gaps left open in previous studies”; highlighting how different studies of the same topic: poverty can yield such a vide variety of outcomes. In reading this paper, I can’t help but reflect on the past 12 weeks and the many different ways we talk about poverty - is it measured in a financial sense, through the advancement of human capital, GDP or other indicators; we have such a preconceived notion (or at least I did, not to generalize) of what poverty encompassed and how it was defined. Milovich evaluates how aid and poverty are linked, does more aid mean less poverty. As he discusses…not exactly, or at least not in a 1 to 1 exchange. When evaluating poverty in the sense of income, the aid has a statistically insignificant impact. This brings us back to how each person and nation define poverty, quite honestly I think to how the fundamental study and relative assumptions of development economics had to be reworked in the not too distant past - that how we interpret and respond to poverty is constantly changing. As the world advances, I wonder if certain aspect and metrics by which we measure poverty will become null, that one day the amount of income a person has is no longer directly tied to their human capital - at that point will the study of development economics again be reworked? I’m not sure, but I think as Milovich discusses and we have surmised throughout the duration of the course, what constitutes an impoverished person or county can be summed up in the infamous two word: “It Depends”.
As most of my classmates have already pointed out, this paper highlights the importance of using a variety of indicators (as in the health, education, and living standard measures that make up the Multidimensional Poverty Index) to measure poverty. The fact that previous literature has indicated that aid ‘works; it doesn’t; it can, but it depends...’ demonstrates just how critical it is that we don't think about financial indicators as being a sufficient signifier of well-being. The paper highlights that economic growth doesn't necessarily lead to a decrease in poverty, which makes sense when thinking about the Kuznet's curve model we talked about briefly toward the beginning of the year, in which as economies grow economic inequality may actually increase before it begins to decrease.
On a separate note, I think this is also a good reminder that we can operate using models for years before we realize that we're going about things the wrong way; how do we ensure that we get things right, the first time? The US's poverty measure still suffers in a lot of ways, and we're 'developed'... how do we ensure that we are measuring poverty correctly in other countries that are still developing, if we can't even measure it properly in our own?
Does Aid Reduce Poverty? by Juliana Yael Milovich delves into a topic rich with over fifty years of previous literature. Ultimately, they conclude that more aid translates into an eventual decline in factors contributing to a nation’s MPI. Milovich identifies that there’s a, “1% increase in the average amount of aid received is associated with a 0.61% reduction in the MPI.” However, they also mention little movement in poverty in the form of income. Education, health, and living standards, all human capital investments, responded favorably with an influx of aid. Glancing at Figure 6, the audience is able to see what sectors aid was able to do the most statistically significant work. Drinking water access and number of years of schooling are the two stand out indicators. Just speculation on my end but perhaps the explanation behind aid causing movement in MPI and not income poverty lies on the Lorenz curve. Aid is helping to alleviate those suffering from the impact of extreme poverty conditions and flattening the nation’s bow closer to a linear plot. In general, this article did a good job on connecting concepts we began this term discussing ( SDGs, MPI, other alternative measures of poverty, etc., economic growth vs. development ) and involved how aid may be a key tool to global benefit.
The fact that the relationship between higher aid amounts and lower poverty levels loses significance when poverty levels are measured by income levels tells me two things. The first thing this makes me think of is statistical significance versus clinical significance. It is a differentiation that is made in econometrics, and it is one I have revisited this semester on my final empirical paper in Professor Shester's US ECON History Course. Some of the results on my research paper aren't statistically significant, but that does not mean there is no significance at all. It is important to remember that these relationships still might mean something. However, the second lesson these findings teach me brings me back to POV 101. We spent a lot of that year attempting to define poverty. Though few conclusive decisions of what poverty actually is were agreed upon, it is easy to tell from from research that income alone is not the right way to define it. So even though these results lost significance, that may not even mean much. Yet, it means even less once the reader realizes potentially the reason for it losing significance which is based on the definition of poverty.
I found this paper to be a great way to wrap up the end of our semester, as it reiterates the "it depends" motto of our class through the differing measurements of poverty. Milovich reveals that aid has a statistically significant effect on reducing poverty when it is measured by the Multidimensional Poverty Index. However, when poverty is measured by income, the effect of aid is not statistically significant. This highlights one of the major insights we have discussed this term that income is not an accurate measure of poverty and that it is much more nuanced and multidimensional than a household’s income. Because the MPI considers factors such as, education, health, and living standards. As we have learned this year, evaluating investments in human capital is critical to understanding the intricacies of poverty on a global scale, and the MPI considers these factors contrary to measurements solely based on income. In a sense, I think this article emphasizes the importance of considering the social benefits of foreign investment, reminding me of the “Returns to Investment in Education” article that highlighted the public benefits of investments in primary schools and education for girls. I think that Milovich’s article reiterates the fundamental takeaway from this year that a comprehensive, multifaceted perspective is essential for evaluating poverty in a global context and that we must consider positive social returns in the long run rather than solely government spending in the short run.
The more development papers I read, the more fascinated I am with how differing empirical strategies can convey very different results. In the paper, Milovich attempts to address two gaps in existing literature regarding the important link between aid and poverty alleviation. The first includes, measuring poverty from a multidimensional view and the second is understanding the endogenous relationship between aid and poverty. I am more interested in the strategy she uses to address the first gap. Although her results demonstrate no statistical significance when poverty is measured from an income perspective, results are positive when taking a multidimensional view of poverty, which considers indicators related to health, education, living standards. I found her estimation strategy appropriate considering the importance of human capital on economic growth. It also reflects Sen’s capabilities framework, since poverty alleviation is measured by the ultimate well-being of the individual. I’m amazed at how economists are able to creatively provide solutions or amendments to existing empirical work, and produce results that are astoundingly different. This is especially important to note, as she emphasizes in the concluding remarks section, that understanding the impact of aid is crucial to attaining the SDG that aspire to reduce poverty to 0% by 2030. Additionally, it is also important to come to a clear consensus on how to define and measure poverty, so that aid is targeted efficiently and accurately.
Posted by: Stelifanie | 11/10/2020 at 05:24 PM
Often when we discuss development policy, ‘problems’ of dual causality are beneficial despite the endogeneity issues that researchers face. For example, understanding how much education leads to rising income versus how much rising income increases average education levels is not necessarily a huge concern for policymakers, since policies relating to either education or income could potentially cause a virtuous cycle of development. However, reverse causality is completely different. Here, a misspecified model could lead policymakers to pursue policy that has no impact whatsoever. The question of whether or not aid reduces poverty faces this potential problem, because it could be that countries that are already poor receive more development, and thus poverty would drive aid rather than aid driving a reduction in poverty. I think Milovich’s solution to use an instrumental variable was a necessary one, although I am still skeptical that the variable exploits exogenous variation in aid. In other words, I find it difficult to believe that the additional aid that countries received when they were on the United Nations Security Council was uncorrelated with existing levels of poverty in that country. Even though levels of aid dropped back down after countries left the UNSC, this does not mean that the increase in aid was not due to increased attention to a country’s needs (and thus uncorrelated with their poverty level) but could simply be due to the fact that politicians and policymakers have short attention spans. If this is the case, the instrumental variable would be correlated with the outcome variable through channels other than its effect on the independent variable, and the exclusion restriction would be violated. It could be that this problem explains why Milovich found that aid did not reduce income poverty even though it reduced other forms of poverty included in the MPI. However, I doubt that this is a serious problem, and the results are believable for the most part. Whether or not the instrumental variable is a good one, much of the literature on the topic faces serious endogeneity problems, and this study is definitely a step in the right direction when it comes to solving these problems.
Posted by: Danny Lynch | 11/12/2020 at 12:39 PM
When reading this paper, something that sticks out to me is how to different definitions and measurements of poverty can tell us different conclusions in research. Its interesting that the aid has a significant effect on reducing "poverty" when the "poverty" variable is measured by the multidimensional poverty index. When "poverty" is measured through income, we see that the effect of aid is not statistically significant. It was noted in the article that more people qualify as MPI poor than income poor using the headcount method. Does this have influence on the data? The larger number of people that fall under MPI poverty could allow for a greater representation of what aid can actually do to help reduce poverty. I am not sure empirically if this makes any difference, but it was a thought that I had.
On a different note, it seems as though the components of the MPI (education, health, and living standards) could see a faster growth from aid than income would. In other words, in theory, if education and health are improved through aid, would income then slowly rise following those improvements? This echos the discussions that we have had in class on the causality/ correlation between human capital investment and economic growth.
Posted by: Gus Wise | 11/12/2020 at 02:06 PM
I found this study to be an interesting one as it clearly exemplifies the importance of the ways in which we measure poverty. The most outstanding result of this study is that aid is associated with lower multidimensional poverty but not with lower income poverty. Specifically, they found a 1% increase in the average amount of aid received from the U.S to be associated with a .82%, .36%, and .64% in education, health, and living standards respectively, or a .61% reduction in the MPI on average. The relationship between aid and poverty measured by the poverty gap and headcount ratio doesn’t seem to be statistically significant, but the relationship between aid and multidimensional poverty with deprivations in health, education, and living standards, is statistically significant. This reveals the we need to be careful in the way in which we look at the impacts of poverty alleviation efforts. Just because aid may not decrease income poverty does not mean that it is not beneficial. Reductions in living standards, health, and education, and not just income, is an important indicator that aid is valuable and should be given. This discussion also reminded me of Amartya Sen’s framework of looking at capabilities as an important indicator of quality of life and poverty. I would not want someone to think that, since aid does not decrease income poverty, that we should not be giving it. It is important that we care about, and try to better, individual’s qualities of life.
Posted by: Christina Cavallo | 11/12/2020 at 03:08 PM
I found this article to be incredibly convincing. Milovich does a fantastic job in walking through all of the ways in which the article may suffer from bias and has a variety of robustness checks that allow the reader to conclude that we are indeed looking at a causal relationship. This is certainly not an easy task. I had never truly considered the research limitations that the reverse causality between poverty and aid can cause. I found that this paper reinforced the relationship between development and poverty that we have already discussed in detail in this class. Mainly that economies need to grow to alleviate poverty, but growth alone does not cause poverty to go away. Multi-dimensional poverty that takes into account far more than mere income levels is a much better measure of how poverty is changing within a country. I found Milovich’s conclusion to be incredibly strong. The fact that an increase of 1% aid could lead to lower percentages of people deprived in education health and living standards by 0.82%, 0.36% and 0.64% respectively is truly astounding. The spillover effects of aid here become very clear. In general, I wonder how increases in education, health, and living standards continue through generations. One would hope that policies that give large amounts of aid do not end with the current generation. How do we ensure that future generations receive the benefits of those before them? This is perhaps a question revolving more around the politics of the country that is receiving aid than the country that is giving aid but I find it to be interesting nonetheless.
Posted by: Jack Parham | 11/12/2020 at 03:35 PM
In this paper, Milovich talks about the different types of poverty as well as the United Nations’ Sustainable Development Goals (SDG). The main goal being to “End poverty in all its forms everywhere by 2030”. It is interesting to think about all of the different types of poverty that Milovich talks about through “multidimensional” poverty. When thinking of poverty you typically think of it monetarily. Milovich talks about how poverty is more than just a dollar figure but plays a hand in the well-being of people, education, health, and quality of life. What I question after reading through the paper is whether more focus on particular aid disbursement will have a larger effect on income poverty. Milovich primarily focuses on multidimensional poverty, as he did not see significant results of aid on income poverty. However, income poverty is still very much relevant and is still one of the most concerning factors if the world is to reach the SDG goals by 2030.
Posted by: Austin Lee | 11/12/2020 at 03:55 PM
This paper provides evidence for the effectiveness of aid in reducing poverty, using alternative measures of poverty contrary to the traditional aid-growth relationship that has been the focus of previous literature concerning aid effectiveness. Not only does this paper take a new approach to investigating whether aid contributes to a reduction in poverty among recipient countries, but it also provides a detailed overview of the past fifty years of literature on aid effectiveness. The findings for the causal effect of aid on poverty reduction have been inconclusive and the relationship between aid and poverty has remained a topic of debate. The majority of previous literature has focused on the relationship between aid and economic growth, but economic growth is only one indicator of reduced poverty and does not measure other important social factors that improve the welfare of citizens. For this reason, the author chooses to use the Multidimensional Poverty Index (MPI) to measure poverty from a multi-dimensional perspective, including education, health, and living standards. The author uses an instrumental variable regression framework to estimate the effect of economic aid disbursed by the United States on reducing poverty in 64 developing countries. When using years spent on the UNSC between 1946 and 1999 as an instrument for the average U.S economic aid received by the country, the author finds that an increase in U.S. aid is associated with a reduction in multidimensional poverty. Specifically, the author found that an increase in U.S. aid is significantly associated with a reduction in schooling deprivation. Overall, the author found that the coefficient on AID remained highly significant and negative with a variety of control variable combinations and that a 1% increase in the average amount of aid received was associated with a 0.61% reduction in the MPI. This paper highlights the need to adopt more comprehensive measures of poverty in order to investigate the effectiveness of aid on alleviating poverty. By shifting to a multidimensional measurement of poverty in developing countries, the author was able to find a significant negative relationship between aid and poverty. The author calls for future research to use alternative measures of poverty in order to better understand the relationship between aid and poverty and help better inform future aid policies.
Posted by: GrahamJameson | 11/12/2020 at 06:05 PM
Last blog post ever! In the theme of our ongoing banter about 'it depends', I will start there. The previous literature on aid and poverty can be grouped into "it works; it doesn't; it can, but it depends". How can there be such divergent conclusions? Well, it depends on how/what the researchers are measuring. When asking my roommate the question 'does aid reduce poverty' (she has studied this question before), her answer was "no, it does not help". And that may be true…when we are solely looking at economic growth. The standard relationship between aid and income poverty is not statistically significant. We must look beyond this traditional relationship into alternative measures to give us a more holistic view on measuring poverty. The MPI looks beyond money to include education, health, and quality of life. These conclusions make me question why it is not the standard to use MPI in policy decisions, even outside the realm of aid. Shouldn't we want to have a broader understanding of policy implications beyond just money?
Posted by: Didi Pace | 11/12/2020 at 06:19 PM
One of the things that stood out to me most about this paper was that it looked at the effect of aid on poverty—and particularly poverty as defined by the multidimensional poverty index—not simply on growth or income poverty. I think this is really interesting because it reminds me of our discussion about the returns to investments in education being dependent on other factors, such as health and nutrition. It makes sense then, that for aid to be effective, certain conditions must be in place, like functioning healthcare centers and good schools which contribute to human capital formation (this parallels the reading on trade and poverty which highlights that a beneficial relationship between these two variables is conditional on factors like education, institutions, and financial markets). When aid decreases multidimensional poverty, as shown in this paper, factors such as education, health, and living standards improve, and there is now even greater potential to see higher returns to aid as measured by income, productivity, or employment opportunities.
After reading this paper I also immediately connected it to our discussions of disease burden and how specific aid targeted at fighting diseases like malaria has the potential to make significant positive impacts in the developing world, particularly through effects on human capital development. Without this specific aid, in the form of mosquito nets, for example, other monetary aid could have a limited effect. All in all, while considering this case, as well as the provision of aid in the form of de-worming medication in the case about conditional returns to education that I mentioned earlier, I am sure that targeted aid, and I wonder if even ‘in kind aid,’ ought to be a greater focus for at least initiating poverty alleviation, particularly multidimensional poverty, which would then create conditions in which returns to monetary aid could increase. *I know this approach may not actually be better/there are some tradeoffs associated with ‘in kind aid,’ but this is just where my thoughts took me after reading this paper and thinking about our other class discussions
Posted by: Sarah Hollen | 11/12/2020 at 06:34 PM
I thought that this paper served as a great final paper for us to discuss, as it incorporates many of the things we have talked about throughout the course of the semester, such as the numerous ways of measuring poverty, the role of economic growth and development on poverty, and the fact that there is rarely a catch-all solution that works everywhere. I found it incredibly interesting that the literature demonstrates that there is a lack of convergence regarding the empirical results, and that there is still a lot of controversy on the effect of aid on poverty alleviation, which again shows us that injecting aid into countries will not necessarily be helpful and also that there is an inherent endogeneity issue associated with attempting to estimate the effect. More generally, it shows how measuring the relationship between aid and poverty is not straightforward, at all, especially given the various ways of measuring poverty. It seems the author was able to relieve some of the endogeneity issues by creating an instrument including the number of years a country has spent on the Security Council of the United Nations, which was a creative way of expanding the literature to try to get a more conclusive answer than (ECON 280 classic), “It depends.” I’m not sure how successful the author was, although it seems as if the paper took a unique approach that was conveyed convincingly and successfully. As the author explains at the end of the paper, it’s necessary that future research focuses on the impact of more precise dimensions of aid on specific indicators over time. It’s unclear when or if we will ever get a straightforward answer, and I would be surprised if there is ever one to be found, since measuring the impact of aid on poverty is so inherently difficult. It’s incredibly important that economists continue to study this relationship, in order to inform policy makers and aid-giving countries, particularly in light of the SDG of eliminating global poverty by 2030.
Posted by: Olivia Indelicato | 11/12/2020 at 06:49 PM
This paper was a nice paper to have as the last paper of the semester. I particularly found the discussion of whether or not it was poverty driving aid or aid reducing poverty to be quite interesting. In the past when we talked about dual causality, it didn’t matter the direction as both were positive. For example female agency driving development versus development driving female agency. Both of these stories were true and it did not necessarily matter in which way the casual link ran because either way, the outcome was something positive. But, with the issue of aid, it does matter. If poverty leads to more aid, but that aid doesn’t actually reduce poverty, then spending is essentially wasted. Although, if aid does reduce poverty then the spending is justified. What makes this issue even more fascinating is that it is subject to the classic “it depends” phenomenon. Sometimes aid can reduce poverty, but in other instances it might not. What was interesting to me is that this study found that aid may not impact income, but can improve living standards, education, and health when gains from aid are measured using the MPI. I actually think that there may be benefits to aid targeting living standards, education, and health rather than just increasing the income of the poor. This is because households may misallocate funds (not necessarily intentionally, but just not make proper investments in education due to asymmetric information). Furthermore, targeted aid on education and health could cause improvements to human capital that could have greater long term effects.
Posted by: Sydney Goldstein | 11/12/2020 at 07:02 PM
I firstly agree with the last few blog posts before mine, as this was an interesting and fitting paper for us to read to close out the term. I think some of the major components of this paper are indicative of some of the significant themes that we have learned throughout the term. One of these themes is viewing situations from various perspectives, especially with regard to measures of development and poverty alleviation. As we have seen in this paper, when this empirical strategy was employed to demonstrate a link between aid and income-based poverty, there was inconclusive evidence, though the situation changed when the authors utilized the multidimensional measure of poverty. I think this strategy speaks volumes to the truth about poverty and development in the world - it is more complicated and interconnected than it may seem on the surface. Poverty certainly does embody an income component, but it is more widespread than that, and when you include variables and measures of education, employment opportunities, health outcomes, climate stability, freedoms, gender equality and more, you begin to get a fuller picture of how poverty and development must be addressed through so many different pathways. As the authors demonstrated in this paper tonight, you begin to form different conclusions when you implement this more comprehensive measure of poverty. So I guess that is one of the big takeaways I learned from this paper but also from this course - never to assume, and to look at issues from as many perspectives as possible to be able to find new and creative pathways to address inequality in the world.
Posted by: Eric Schleicher | 11/12/2020 at 07:13 PM
One aspect of this paper that immediately stood out to me is its use of the Multidimensional Poverty Index (MPI) to answer their research question of whether aid reduces poverty. By using the MPI, Milovich acknowledges the fact that the level of poverty is not simply a measure of income. Rather, it also has to do largely with social factors and how these factors, such as education and health, impact people’s well-being. Using the MPI as an alternative measure of poverty also allows for a greater understanding of the relationship between aid and poverty alleviation, other than through the traditional lens of economic growth that has been primarily used in previous studies. Interestingly, while the results did not show a significant relationship between aid and poverty alleviation when measured from an income perspective, there was a significant relationship between higher amounts of aid received during 1946–1999 and lower MPI between 2000 and 2014. However, while Milovich notes these results, he also acknowledges the controversy of the topic and the “endogeneity bias” that exists between aid and poverty alleviation that weaken causal links.
While this paper focuses mostly on foreign aid through the lens of major governmental organizations such as UNICEF and the World Bank, I am left wondering how the impact of foreign aid on poverty alleviation may look different if Milovich looked solely at NGOs and other private agencies. Last year, as part of a foreign aid colloquium, I read A White Man’s Burden: Why the West's Efforts to Aid the Rest Have Done So Much Ill and So Little Good by William Easterly. In this account, Easterly scorns governmental aid for actually inflicting more harm than good in developing countries, and maintains that private agents are the solution to this problem. He argues that private agencies work on a far more individualized level in communities. I was reminded of this argument when reading Milovich’s paper and wondered what his response would be to Easterly’s account.
Posted by: Julia Foxen | 11/12/2020 at 07:16 PM
The literature review in this paper was very interesting. I feel that on some level there is this idea that all people need to get out of poverty is money, which of course we know is not true. In this same way, the idea that economic growth decreases poverty seems logical. However, I am surprised to see in this paper that growth was used as a proxy for poverty. It seems to take quite some time for the literature to get past this idea, but we know that there are corrupt and authoritarian governments that may grow the economy and never let the profits reach the people, especially not the poor.
What I find concerning is how important being a member of the UNSC is to receiving aid. For each additional year sitting on the council, a country receives approximately $21M more in aid from the US. It seems that UN should be working to help all countries to alleviate poverty and develop at all times and not just “when its their turn” or there’s an emergency.
A bit of a side note but I really appreciated the way Milovich walked through the statistical analysis and results. The empirical analyses and estimation strategies are my favorite part of economics, so I appreciate how clearly, he explained his methodology. I like how he explained all the potential endogeny with the error term and the independent variables to explain why he ran a two stage least squares regression analysis. This is perhaps not the most relevant take away for the purpose of our class discussion, but interesting and appreciated, nonetheless.
Posted by: Emma | 11/12/2020 at 07:37 PM
This paper, like others we have read this semester, emphasizes that there is there isn't a recipe for development, there is not a single solution that works everywhere. In some cases aid helps in reducing poverty, in some cases It doesn't... "It depends". This paper is very technical compared to other papers we have read, and there is an interesting technical question when trying to claim causality. Does more aid reduce poverty or does poverty just attract more aid? This reverse causality is an endogeneity problem that they overcome using instrumental variables. In regression analysis, Milovich uses the Multidimensional poverty index as the measure of poverty, where in most studies we've read they measure poverty in terms of ones income. The study concludes that Aid does indeed reduce poverty- in terms of MPI (living standards and health) Milovich establishes causality with results that are statistically significant. However, aid might not reduce poverty in terms of improving income. This suggests studies should be measuring poverty differently. We discussed poverty earlier in the semester and concluded that being poor goes beyond the amount of money you make, and this study follows that line of thinking. Outside of one's income, standard of living, health, and education matter when discussing poverty. Overall this paper is very convincing and ties together a lot of discussions from earlier in the semester
Posted by: Frances McIntosh | 11/12/2020 at 07:41 PM
When comparing results from the OLS estimation in Table 2, we see that aid is more significantly related to a decrease in the MPI and the multidimensional headcount ratio than to a decrease in income poverty, where only a negative relationship for the severe income poverty gap is seen. In fact, an increase of just 1% in U.S. aid directly lowers the percentage of people deprived of education, health and living standards. Although the impact is less than 1% for each of the 3 previously mentioned categories, education comes close to having a direct 1:1 ratio (if I’m interpreting correctly in that 1% increase in aid causes a 1% improvement in the education-deprived population.). Furthermore, the MPI as a whole is reduced by 0.61%. This obviously varies for different countries and depends on other factors as well, but these values are on average. This data shows that MPI is a more accurate measure for analyzing the relationship between aid and poverty alleviation. The Multidimensional Poverty Index (MPI) takes into account factors such as nutrition, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, flooring, and assets. Meanwhile, institutional quality is measured by using a country’s level of freedom (political rights, civil liberties) and measures for fractionalization (ethnicity, religion and language). Although this is obviously a more complex and time-consuming measurement than just income or a country’s growth, its findings are interesting, particularly when thinking about the Sustainable Development Goals and the policies that would most effectively help us reach them by- ideally- 2050. I wonder how specifically the application of these findings would alter some of those efforts or progress tracking.
Posted by: Jackie Tamez | 11/12/2020 at 07:49 PM
This paper tracks US foreign aid to developing countries as it affects the recipient country’s MPI, or multidimensional poverty index. Consistent with much of our reading, this paper studies the outcomes of aid as it affects education, health, and living standards, instead of simply focusing on changes in income. Previous studies have had mixed success tracking the results of foreign aid, concluding that aid can sometimes help or not help a country's development, and that it depends on external factors. Most of these factors are controlled for in the OPHI study, although that part of the study setup was a little confusing for me. The study tracked US aid from 1949-1997 vs the average poverty levels (MPI) from 2000-2014, and tracked a negative correlation between aid and MPI. I found the discussion of the goals of aid interesting, especially in the context of the US. Aid can often be politically motivated instead of motivated simply by human rights, and I believe when the motives for aid are distorted by political agendas, the return on MPI is likely less important. I’d be interested to hear about further study that can closely track aid through a developing country’s economy to determine the most effective avenues for aid.
Posted by: Adelaide Burton | 11/12/2020 at 07:51 PM
I also thought this was quite an interesting paper to conclude our term with, as it strung together quite a few of the major themes and topics we have covered this semester. I was particularly interested by Milovich's use of the concept of "multidimensional poverty", as it is important to realize that poverty is more than just a lack of income, but also can be accounted for by nutrition, education, and human capital. Having this concept in mind, it makes it easy to realize how different forms of poverty are all interconnected, and how they all play such a large role on one another. It is interesting to me to be able to think about how aid can improve certain forms of poverty, but not others. I think that the most traditional way that we (probably as Americans) think of poverty is by wealth, but this is certainly not the entire story and we end up taking things such as health and education for granted. Certainly investments in health and education will produce societies where there are larger incomes, and as we have repeatedly discussed throughout the term, this is where foreign aid would benefit the most.
Posted by: Mason Shuffler | 11/12/2020 at 07:54 PM
Juliana Milovich’s paper has an extremely wide berth, considering not only the impacts of aid on poverty but also the differences in institutions, natural resources, and social factors in the 64 sample countries. I found the mechanism of measuring aid particularly interesting. Milovich establishes that there is a large correlation between sitting on the United Nations Security council and the amount of aid received by the United States. In class, I would love to consider the exclusion restriction which assumes the instrument is randomly assigned and that it is not related to the poverty other than through the increased levels of aid (if I understand properly). I wonder if a position on the UNSC provides political power which could aid a nation in decreasing poverty. The results seem to support the hypothesis that the aid associated with a UNSC position does seem to reduce MPI but not an income perspective of poverty. However, the scatter plots seem (at least to me) to suggest there is a large amount of variability for countries which experience less than 5 years as a member of the UNSC. I find these results interesting as well, and I would like to discuss the linkage aid has to the components of the MPI (such as water availability, health, and education).
Posted by: John Lavette | 11/12/2020 at 07:55 PM
I found it interesting that there was no statistically significant relationship between income poverty and aid given by the US, as I thought that there would be a more positive correlation. This goes on to show that poverty and a country's economy go far beyond just measuring people's income. This also shows that simply injecting aid into third world countries isn't a reliable way of dealing with poverty (because "it will depend"). As an alternative method of measuring poverty, Milovich talks about the Multidimensional Poverty Index (MPI), which observes poverty from many different aspects (education, health, living standards) and eliminates the reverse causality problem. Using the MPI, Milovich found that an increase of 1% in U.S. aid resulted in lower percentages of "multidimensionally poor people deprived in education, health, and living standards (0.82%, 0.36%, and 0.64%, respectively)." This finding is significant, as this precise measurement/dimension of aid exposes economists and policymakers to better ways of helping people in poverty. For example, these results could be a sign that policymakers should focus less on using figures like income to measure the success of their policies (income reports are prone to dishonesty and inaccuracy). Instead, perhaps they should focus more on education, health, and living standards since these factors seem to provide a more holistic and accurate depiction of poverty and growth.
Posted by: YoungJae | 11/12/2020 at 08:01 PM
I thought this paper was interesting in how Milovich prefaced the entire piece saying “I seek to answer this question by closing two gaps left open in previous studies”; highlighting how different studies of the same topic: poverty can yield such a vide variety of outcomes. In reading this paper, I can’t help but reflect on the past 12 weeks and the many different ways we talk about poverty - is it measured in a financial sense, through the advancement of human capital, GDP or other indicators; we have such a preconceived notion (or at least I did, not to generalize) of what poverty encompassed and how it was defined. Milovich evaluates how aid and poverty are linked, does more aid mean less poverty. As he discusses…not exactly, or at least not in a 1 to 1 exchange. When evaluating poverty in the sense of income, the aid has a statistically insignificant impact. This brings us back to how each person and nation define poverty, quite honestly I think to how the fundamental study and relative assumptions of development economics had to be reworked in the not too distant past - that how we interpret and respond to poverty is constantly changing. As the world advances, I wonder if certain aspect and metrics by which we measure poverty will become null, that one day the amount of income a person has is no longer directly tied to their human capital - at that point will the study of development economics again be reworked? I’m not sure, but I think as Milovich discusses and we have surmised throughout the duration of the course, what constitutes an impoverished person or county can be summed up in the infamous two word: “It Depends”.
Posted by: Jay Walton | 11/12/2020 at 08:06 PM
As most of my classmates have already pointed out, this paper highlights the importance of using a variety of indicators (as in the health, education, and living standard measures that make up the Multidimensional Poverty Index) to measure poverty. The fact that previous literature has indicated that aid ‘works; it doesn’t; it can, but it depends...’ demonstrates just how critical it is that we don't think about financial indicators as being a sufficient signifier of well-being. The paper highlights that economic growth doesn't necessarily lead to a decrease in poverty, which makes sense when thinking about the Kuznet's curve model we talked about briefly toward the beginning of the year, in which as economies grow economic inequality may actually increase before it begins to decrease.
On a separate note, I think this is also a good reminder that we can operate using models for years before we realize that we're going about things the wrong way; how do we ensure that we get things right, the first time? The US's poverty measure still suffers in a lot of ways, and we're 'developed'... how do we ensure that we are measuring poverty correctly in other countries that are still developing, if we can't even measure it properly in our own?
Posted by: Joey Dickinson | 11/12/2020 at 08:12 PM
Does Aid Reduce Poverty? by Juliana Yael Milovich delves into a topic rich with over fifty years of previous literature. Ultimately, they conclude that more aid translates into an eventual decline in factors contributing to a nation’s MPI. Milovich identifies that there’s a, “1% increase in the average amount of aid received is associated with a 0.61% reduction in the MPI.” However, they also mention little movement in poverty in the form of income. Education, health, and living standards, all human capital investments, responded favorably with an influx of aid. Glancing at Figure 6, the audience is able to see what sectors aid was able to do the most statistically significant work. Drinking water access and number of years of schooling are the two stand out indicators. Just speculation on my end but perhaps the explanation behind aid causing movement in MPI and not income poverty lies on the Lorenz curve. Aid is helping to alleviate those suffering from the impact of extreme poverty conditions and flattening the nation’s bow closer to a linear plot. In general, this article did a good job on connecting concepts we began this term discussing ( SDGs, MPI, other alternative measures of poverty, etc., economic growth vs. development ) and involved how aid may be a key tool to global benefit.
Posted by: abrahamr22 | 11/12/2020 at 08:28 PM
The fact that the relationship between higher aid amounts and lower poverty levels loses significance when poverty levels are measured by income levels tells me two things. The first thing this makes me think of is statistical significance versus clinical significance. It is a differentiation that is made in econometrics, and it is one I have revisited this semester on my final empirical paper in Professor Shester's US ECON History Course. Some of the results on my research paper aren't statistically significant, but that does not mean there is no significance at all. It is important to remember that these relationships still might mean something. However, the second lesson these findings teach me brings me back to POV 101. We spent a lot of that year attempting to define poverty. Though few conclusive decisions of what poverty actually is were agreed upon, it is easy to tell from from research that income alone is not the right way to define it. So even though these results lost significance, that may not even mean much. Yet, it means even less once the reader realizes potentially the reason for it losing significance which is based on the definition of poverty.
Posted by: Bridget Bartley | 11/12/2020 at 09:23 PM
I found this paper to be a great way to wrap up the end of our semester, as it reiterates the "it depends" motto of our class through the differing measurements of poverty. Milovich reveals that aid has a statistically significant effect on reducing poverty when it is measured by the Multidimensional Poverty Index. However, when poverty is measured by income, the effect of aid is not statistically significant. This highlights one of the major insights we have discussed this term that income is not an accurate measure of poverty and that it is much more nuanced and multidimensional than a household’s income. Because the MPI considers factors such as, education, health, and living standards. As we have learned this year, evaluating investments in human capital is critical to understanding the intricacies of poverty on a global scale, and the MPI considers these factors contrary to measurements solely based on income. In a sense, I think this article emphasizes the importance of considering the social benefits of foreign investment, reminding me of the “Returns to Investment in Education” article that highlighted the public benefits of investments in primary schools and education for girls. I think that Milovich’s article reiterates the fundamental takeaway from this year that a comprehensive, multifaceted perspective is essential for evaluating poverty in a global context and that we must consider positive social returns in the long run rather than solely government spending in the short run.
Posted by: Savannah Corey | 11/12/2020 at 10:15 PM