Although there exists a vast literature on aid efficiency (the effect of aid on GDP), and that aid allocation determinants have been estimated, little is known about the minute details of aid allocation. This article investigates empirically a claim repeatedly made in the past that aid donors herd. Building upon a methodology applied to financial markets, this article finds that aid donors herd similarly to portfolio funds on financial markets. It also estimates the causes of herding and finds that political transitions towards more autocratic regimes repel donors, but that transitions towards democracy have no effect. Finally, identified causes of herding explain little of its overall level, suggesting strategic motives play an important role.
This paper studies determinants of income inequality using a newly assembled panel of 16 countries over the entire twentieth century. We focus on three groups of income earners: the rich (P99-100), the upper middle class (P90-99), and the rest of the population (P0-90). The results show that periods of high economic growth disproportionately increases the top percentile
income share at the expense of the rest of the top decile. Financial development is also pro-rich and the outbreak of banking crises is associated with reduced income shares of the rich. Trade openness has no clear distributional impact (if anything openness reduces top shares). Government spending, however, is negative for the upper middle class and positive for the nine lowest deciles but does not seem to affect the rich. Finally, tax
progressivity reduces top income shares and when accounting for real dynamic effects the impact can be important over time.
Version of March 25, 2009. Please check for updates https://www.elsevier.com/
Read more research publications at: https://www.hhs.se/site
Recent work on the so-called resource curse has focused on the importance of the interaction between institutional quality and resource abundance. The combination of low quality institutions and easily appropriable resources (such as oil and minerals) tend to be particularly bad for economic development. On the other hand, if institutions are good these same resources contribute more to economic growth than other types of natural wealth. While certainly pointing in the right direction this strand of literature leaves some open questions. First, it is vague on the precise channels through which institutional quality operates. Second, the empirical measures of institutions are often composite measures that arguably include measures of institutional outcomes rather than durable โrules of the gameโ. Using data for the period 1970-2003, this paper study the extent to which combinations of resource-types and constitutional setup determine the degree of appropriative activity in a country. Our results show that parliamentary regimes and majoritarian electoral systems are associated with less (or no) resource curse-effect than are presidential and proportional electoral systems. These effects are particularly strong in countries having much ores, metals and fuels.
By Jesper Roine (with A. Boschini and J. Pettersson), proceedings from "Meeting Global Challenges in Research Cooperation", Uppsala.
Arrangements by which politically connected firms receive economic favors are a common feature around the world, but little is known of the form or effects of influence in business-
government relationships. We present a simple model in which influence requires firms to provide goods of political value in exchange for economic privileges. We argue that political influence improves the business environment for selected firms, but restricts their ability to fire workers. Under these conditions, if political influence primarily lowers fixed costs over variable costs, then favored firms will be less likely to invest and their productivity will suffer, even if they earn higher profits than non-influential firms. We rely on the World Bank's Enterprise Surveys of approximately 8,000 firms in 40 developing countries, and control for a number of biases present in the data. We find that influential firms benefit from lower administrative and regulatory barriers (including bribe taxes), greater pricing power, and easier access to credit. But these firms also provide politically valuable benefits to incumbents through bloated payrolls and greater tax payments. Finally, these firms are worse-performing than their non-influential counterparts. Our results highlight a potential channel by which cronyism leads to persistent underdevelopment.
In this paper I examine the development effects of military coups. Whereas previous economic literature has primarily viewed coups as a form of broader political instability, less research has focused on its development consequences independent of the factors making coups more likely. Moreover, previous research tends to group coups together regardless of whether they overthrew autocratic or democratically-elected leaders. I first show that coups overthrowing democratically elected leaders imply a very different kind of event than those overthrowing autocratic leaders. These differences relate to the implementation of authoritarian institutions following a coup in a democracy, which I discuss in several case studies. Second, I address the endogeneity of coups by comparing the growth consequences of failed and successful coup as well as matching and panel data methods, which yield similar results. Although coups taking place in already autocratic countries show imprecise and sometimes positive effects on economic growth, in democracies their effects are distinctly detrimental to growth. When overthrowing democratic leaders, coups not only fail to promote economic reforms or stop the occurrence of economic crises, but they also have substantial negative effects across a number of standard growth-related outcomes including health, education, and investment.
Read more: https://www.hhs.se/site
In this paper we argue that aid effectiveness may suffer when partnerships with new regimes need to be established. We test this argument using the natural experiment of the break-up of communism in the former Eastern Bloc. We find that commercial and strategic concerns influenced both aid flows and the urgency of entry into new partnerships in the first half of the 1990s, while developmental objectives became more important only over time. These results hold up to a thorough sensitivity analysis, including using a gravity model to instrument for bilateral trade flows. We also find that aid fractionalization increased substantially, and that aid to the region was more likely to be tied, more volatile and less predictable than to aid to other recipients at the time. Overall, these results suggest that the guidelines for aid effectiveness agreed upon in the Paris Declaration are likely to be challenged by the current political transition in parts of the Arab world. Hopefully being aware of these challenges can help donors avoid making the same mistakes.
Arrangements by which influential firms receive economic favors, has been documented in numerous case studies but rarely formalized or analyzed quantitatively. We offer a formal voting model in which political influence is modeled as a contract by which politicians deliver a more preferential business environment to favored firms who, in exchange, protect politicians from the political consequences of high unemployment. From this perspective, cronyism simultaneously lowers a firmโs fixed costs while raising its variable wage costs. Testing several of the implications of the model on firm-level data from 26 transition countries, we find that more influential firms face fewer administrative and regulatory obstacles and carry bloated payrolls, but they also invest and innovate less. These results do not change when using propensity-score matching to adjust for the fact that influence is not randomly assigned.
This policy brief covers a discussion on finance for sustainable development held during a full day conference at the Stockholm School of Economics on May 11, 2015. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs, and was the fifth installment of Development Day โ a yearly development policy conference. With the Millennium Development Goals (MDGs) expiring in 2015, the members of the United Nations are now in the process of defining a post-2015 development agenda. The Sustainable Development Goals (SDGs) build on the eight anti-poverty targets in the MDG but also include a renewed emphasis on environmental and social sustainability. Whatever targets or goals will be agreed upon in the end, we know for certain that reaching the objectives will require substantial financial resources, far beyond the current levels of official development assistance (ODA). To discuss this issue, the conference brought together a distinguished and experienced group of policy-oriented scholars and practitioners from government agencies, international organizations, civil society and the business community.
Dictatorships do not survive by repression alone. Rather, dictatorial rule is often explained as an โ authoritarian bargain by which citizens relinquish political rights for economic security. The applicability of the authoritarian bargain to decision-making in non-democratic states, however, has not been thoroughly examined. We conceptualize this bargain as a simple game between a representative citizen and an autocrat who faces the threat of insurrection, and where economic transfers and political influence are simultaneously determined. Our model yields precise implications for the empirical patterns that are expected to exist. Tests of a system of equations with panel data comprising 80 non-democratic states between 1975 and 1999 confirm the predictions of the authoritarian-bargain thesis, with some variation across different categories of dictatorship.
This paper studies determinants of income inequality using a newly assembled panel of 16 countries over the entire twentieth century. We focus on three groups of income earners: the rich (P99-100), the upper middle class (P90-99), and the rest of the population (P0-90). The results show that periods of high economic growth disproportionately increases the top percentile
income share at the expense of the rest of the top decile. Financial development is also pro-rich and the outbreak of banking crises is associated with reduced income shares of the rich. Trade openness has no clear distributional impact (if anything openness reduces top shares). Government spending, however, is negative for the upper middle class and positive for the nine lowest deciles but does not seem to affect the rich. Finally, tax
progressivity reduces top income shares and when accounting for real dynamic effects the impact can be important over time.
Version of March 25, 2009. Please check for updates https://www.elsevier.com/
Read more research publications at: https://www.hhs.se/site
Recent work on the so-called resource curse has focused on the importance of the interaction between institutional quality and resource abundance. The combination of low quality institutions and easily appropriable resources (such as oil and minerals) tend to be particularly bad for economic development. On the other hand, if institutions are good these same resources contribute more to economic growth than other types of natural wealth. While certainly pointing in the right direction this strand of literature leaves some open questions. First, it is vague on the precise channels through which institutional quality operates. Second, the empirical measures of institutions are often composite measures that arguably include measures of institutional outcomes rather than durable โrules of the gameโ. Using data for the period 1970-2003, this paper study the extent to which combinations of resource-types and constitutional setup determine the degree of appropriative activity in a country. Our results show that parliamentary regimes and majoritarian electoral systems are associated with less (or no) resource curse-effect than are presidential and proportional electoral systems. These effects are particularly strong in countries having much ores, metals and fuels.
By Jesper Roine (with A. Boschini and J. Pettersson), proceedings from "Meeting Global Challenges in Research Cooperation", Uppsala.
Arrangements by which politically connected firms receive economic favors are a common feature around the world, but little is known of the form or effects of influence in business-
government relationships. We present a simple model in which influence requires firms to provide goods of political value in exchange for economic privileges. We argue that political influence improves the business environment for selected firms, but restricts their ability to fire workers. Under these conditions, if political influence primarily lowers fixed costs over variable costs, then favored firms will be less likely to invest and their productivity will suffer, even if they earn higher profits than non-influential firms. We rely on the World Bank's Enterprise Surveys of approximately 8,000 firms in 40 developing countries, and control for a number of biases present in the data. We find that influential firms benefit from lower administrative and regulatory barriers (including bribe taxes), greater pricing power, and easier access to credit. But these firms also provide politically valuable benefits to incumbents through bloated payrolls and greater tax payments. Finally, these firms are worse-performing than their non-influential counterparts. Our results highlight a potential channel by which cronyism leads to persistent underdevelopment.
In this paper I examine the development effects of military coups. Whereas previous economic literature has primarily viewed coups as a form of broader political instability, less research has focused on its development consequences independent of the factors making coups more likely. Moreover, previous research tends to group coups together regardless of whether they overthrew autocratic or democratically-elected leaders. I first show that coups overthrowing democratically elected leaders imply a very different kind of event than those overthrowing autocratic leaders. These differences relate to the implementation of authoritarian institutions following a coup in a democracy, which I discuss in several case studies. Second, I address the endogeneity of coups by comparing the growth consequences of failed and successful coup as well as matching and panel data methods, which yield similar results. Although coups taking place in already autocratic countries show imprecise and sometimes positive effects on economic growth, in democracies their effects are distinctly detrimental to growth. When overthrowing democratic leaders, coups not only fail to promote economic reforms or stop the occurrence of economic crises, but they also have substantial negative effects across a number of standard growth-related outcomes including health, education, and investment.
Read more: https://www.hhs.se/site
In this paper we argue that aid effectiveness may suffer when partnerships with new regimes need to be established. We test this argument using the natural experiment of the break-up of communism in the former Eastern Bloc. We find that commercial and strategic concerns influenced both aid flows and the urgency of entry into new partnerships in the first half of the 1990s, while developmental objectives became more important only over time. These results hold up to a thorough sensitivity analysis, including using a gravity model to instrument for bilateral trade flows. We also find that aid fractionalization increased substantially, and that aid to the region was more likely to be tied, more volatile and less predictable than to aid to other recipients at the time. Overall, these results suggest that the guidelines for aid effectiveness agreed upon in the Paris Declaration are likely to be challenged by the current political transition in parts of the Arab world. Hopefully being aware of these challenges can help donors avoid making the same mistakes.
Arrangements by which influential firms receive economic favors, has been documented in numerous case studies but rarely formalized or analyzed quantitatively. We offer a formal voting model in which political influence is modeled as a contract by which politicians deliver a more preferential business environment to favored firms who, in exchange, protect politicians from the political consequences of high unemployment. From this perspective, cronyism simultaneously lowers a firmโs fixed costs while raising its variable wage costs. Testing several of the implications of the model on firm-level data from 26 transition countries, we find that more influential firms face fewer administrative and regulatory obstacles and carry bloated payrolls, but they also invest and innovate less. These results do not change when using propensity-score matching to adjust for the fact that influence is not randomly assigned.
This policy brief covers a discussion on finance for sustainable development held during a full day conference at the Stockholm School of Economics on May 11, 2015. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs, and was the fifth installment of Development Day โ a yearly development policy conference. With the Millennium Development Goals (MDGs) expiring in 2015, the members of the United Nations are now in the process of defining a post-2015 development agenda. The Sustainable Development Goals (SDGs) build on the eight anti-poverty targets in the MDG but also include a renewed emphasis on environmental and social sustainability. Whatever targets or goals will be agreed upon in the end, we know for certain that reaching the objectives will require substantial financial resources, far beyond the current levels of official development assistance (ODA). To discuss this issue, the conference brought together a distinguished and experienced group of policy-oriented scholars and practitioners from government agencies, international organizations, civil society and the business community.
Dictatorships do not survive by repression alone. Rather, dictatorial rule is often explained as an โ authoritarian bargain by which citizens relinquish political rights for economic security. The applicability of the authoritarian bargain to decision-making in non-democratic states, however, has not been thoroughly examined. We conceptualize this bargain as a simple game between a representative citizen and an autocrat who faces the threat of insurrection, and where economic transfers and political influence are simultaneously determined. Our model yields precise implications for the empirical patterns that are expected to exist. Tests of a system of equations with panel data comprising 80 non-democratic states between 1975 and 1999 confirm the predictions of the authoritarian-bargain thesis, with some variation across different categories of dictatorship.
Poverty is associated with political conflict in developing countries, but evidence of individual grievances translating into dissent among the poor is mixed. We analyze survey data from 40 developing nations to understand the determinants radicalism, support for violence, and participation in legal anti-regime actions as petitions, demonstrations, and strikes. In particular, we examine the role of perceived political and economic inequities. Our findings suggest that individuals who feel marginalized tend to harbor extremist resentments against the government, but they are generally less likely to join collective political movements that aim to instigate regime changes. This potentially explains the commonly-observed pattern in low- and middle-income countries whereby marginalized groups, despite their political attitudes and high-levels of community engagement, are more difficult to mobilize in nation-wide movements. We also find that arenas for active political participation (beyond voting) are more likely to be dominated by upper-middle income groups who are committed, ultimately, to preserving the status quo. Suppressing these forms of political action may thus be counterproductive, if it pushes these groups towards more radical preferences. Finally, our findings suggest that the poor, in developing nations, may be caught in a vicious circle of self-exclusion and greater marginalization.
Anders Olofsgรฅrd (with R. Desai and T. Yousef).
We argue that the tilt towards donor interests over recipient needs in aid allocation and practices may be particularly strong in new partnerships. Using the natural experiment of Eastern transition we find that commercial and strategic concerns influenced both aid flows and entry in the first half of the 1990s, but much less so later on. We also find that fractionalization increased and that early aid to the region was particularly volatile, unpredictable and tied. Our results may explain why aid to Iraq and Afghanistan has had little development impact and serve as warning for Burma and Arab Spring regimes.
Anders Olofsgรฅrd (with A. Boschini).
Published in Journal of Development Studies.
In this paper, we test the argument that the sizeable reduction in aggregate aid levels in the 1990โs was due to the end of the Cold War. We test two different models using a dynamic econometric specification on a panel of 17 donor countries, spanning the years 1970-1997. We find aid to be positively related to military expenditures in the former Eastern bloc during the cold war, but not in the 1990โs, suggesting that the reductions in aid disbursements are driven by the disappearance of an important motive for aid. Our results also suggest that aid allocation may have become less strategic in the 1990โs.
In this paper I examine the development effects of coups. I first show that coups overthrowing democratically-elected leaders imply a different kind of event than those overthrowing autocratic leaders, and that these differences relate to the implementation of authoritarian institutions following a coup in a democracy. Secondly, I address the endogeneity of coups by comparing the growth consequences of failed and successful coups as well as implementing matching and panel data methods, which yield similar results. Although coups taking place in already autocratic countries show imprecise and sometimes positive effects on economic growth, in democracies their effects are distinctly detrimental. I find no evidence that these results are symptomatic of alternative hypothesis involving the effects of failed coups or political transitions. Thirdly, when overthrowing democratic leaders, coups not only fail to promote economic reforms or stop the occurrence of economic crises and political instability, but they also have substantial negative effects across a number of standard growth-related outcomes including health, education, and investment.
Find more research publications at https://www.hhs.se/site
When a government creates an agency to gather information relevant to policymaking, it faces two critical organizational questions: whether the agency should be given authority to
decide on policy or merely supply advice, and what should the policy goals of the agency be. Existing literature on the first question is unable to address the second, because the question
of authority becomes moot if the government can simply replicate its preferences within the agency. In contrast, this paper examines both questions within a model of policymaking under time inconsistency, a setting in which the government has a well-known incentive to create an agency with preferences that differ from its own. Thus, our framework permits a meaningful analysis of delegation versus communication with an endogenously chosen agent. The first main finding of the paper is that the government can do equally well with a strategic choice of agent, from which it solicits advice, instead of delegating authority, as long as the time inconsistency problem is not too severe. The second main finding is that the government may strictly prefer seeking advice to delegating authority if there is prior uncertainty with respect to what is the optimal policy.
By Anders Olofsgรฅrd (with R. Luma), published in Journal of Public Economics.
We use newly compiled top income share data and structural breaks techniques to estimate common trends and breaks in inequality across countries over the twentieth century. Our results both confirm earlier findings and offer new insights. In particular, the division into an Anglo-Saxon and a Continental European experience is not as clear cut as previously suggested. Some Continental European countries seem to have experienced increases in top income shares, just as Anglo-Saxon countries, but typically with a lag. Most notably, Nordic countries display a marked โAnglo-Saxonโ pattern, with sharply increased top income shares especially when including realized capital gains. Our results help inform theories about the causes of the recent rise in inequality.
Realized capital gains are typically disregarded in the study of income inequality. We show that in the case of Sweden this severely underestimates the actual increase in inequality and, in particular, top income shares during recent decades. Using micro panel data to average
incomes over longer periods and re-rank individuals according to income excluding capital gains, we show that capital gains indeed are a reoccurring addition to rather than a transitory component in top incomes. Doing the same for lower income groups, however, makes virtually no difference. We also try to find the roots of the recent surge in capital gains-driven inequality in Sweden since the 1980s. While there are no evident changes in terms of who earns these gains (high wage earners vs. top capital income earners), the primary driver instead seems to be the drastic asset price increases on the post-1980 deregulated financial markets.
This policy brief examines the timing of Turkeyโs authoritarian turn using raw data measuring freedoms from the Freedom House (FH). It shows that Turkeyโs authoritarian turn under the ruling AKP is not a recent phenomenon. Instead, the countryโs institutional erosion โ especially in terms of freedoms of expression and political pluralism โ in fact began much earlier, and the losses in the earlier periods so far tend to dwarf those occurring later.
1.. Islamic Rule and the Emancipation of the Poor and Pious
I estimate the impact of Islamic rule on secular education and labor market outcomes with a new and unique dataset of Turkish municipalities. Using a regression discontinuity design, I compare elections where an Islamic party barely won or lost municipal mayor seats. The results show that Islamic rule has had a large positive effect on education, predominantly for women. This impact is not only larger when the opposing candidate is from a secular left-wing, instead of a right-wing party; it is also larger in poorer and more pious areas. The participation result extends to the labor market, with fewer women classified as housewives, a larger share of employed women receiving wages, and a shift in female employment towards higher-paying sectors. Part of the increased participation, especially in education, may come through investment from religious foundations, by providing facilities more tailored toward religious conservatives. Altogether, my findings stand in contrast to the stylized view that more Islamic inโกuence is invariably associated with adverse development outcomes, especially for women. One interpretation is that limits on religious expression, such as the headscarf ban in public institutions, raise barriers to entry for the poor and pious. In such environments, Islamic movements may have an advantage over secular alternatives.
2. Islam and Long-Run Development
I show new evidence on the long-run impact of Islam on economic development. Using the proximity to Mecca as an instrument for the Muslim share of a country's population, while holding geographic factors fixed, I show that Islam has had a negative long-run impact on income per capita. This result is robust to a host of geographic, demographic and historical factors, and the impact magnitude is around three times that of basic cross-sectional estimates. I also show evidence of the impact of Islam on religious influence in legal institutions and women's rights, two outcomes seen as closely associated with the presence of Islam. A larger Islamic influence has led to a larger religious influence in legal institutions and lower female participation in public institutions. But it has also had a positive impact on several measures of female health outcomes relative to men. These results stand in contrast to the view that Islam has invariably adverse consequences for all forms of women's living standards, and instead emphasizes the link between lower incomes and lower female participation in public institutions.
3. The Rise of China and the Natural Resource Curse in Africa
We produce a new empirical strategy to estimate the causal impact of selling oil to China on economic and political development, using an instrumental variables design based on China's economic rise and consequent demand for oil in interaction with the pre-existence of oil in Sub-Saharan Africa.
Despite a voluminous literature on the topic, the question of whether aid leads to growth is still controversial. To observe the pure effect of aid, researchers used instruments that must be exogenous to growth and explain well aid flows. This paper argues that instruments used in the past do not satisfy these conditions. We propose a new instrument based on predicted aid quantity and argue that it is a significant improvement relative to past approaches. We find a significant and relatively big effect of aid: a one standard deviation increase in received aid is associated with a 1.6 percentage points higher growth rate.
https://www.delhipolicygroup.org/publication/policy-reports/dj-vu-in-myanmar.html - Over the past two months, Myanmar has plunged into a political crisis. Myanmarโs tentative political transition towards democracy, which started in 2010 and gained momentum after the 2015 elections, has been reversed. The military (Tatmadaw) has staged a coup dโรฉtat and arrested democratically elected leaders, including President Win Myint and State Counsellor Daw Aung San Suu Kyi.
We use a novel approach to address the question of whether a union of sovereign countries can efficiently raise and allocate a budget, even when members are purely self-interested and participation is voluntary. The main innovation of our model is to explore the link between budget contributions and allocation that arises when countries bargain over union outcomes. This link stems from the distribution of bargaining power being endogenously determined. Generically, it follows that unstructured bargaining gives an inefficient result. We find, however, that efficiency is achieved with fully homogenous countries, and when countries have similar incomes and the union budget is small. Moreover, some redistribution arises endogenously, even though nations are purely self-interested and not forced to participate in the union. A larger union budget, however, entails a trade-off between equality and efficiency. We also analyze alternative institutions and find that majority rule can improve efficiency if nations who prefer projects with high public good spillovers are endogenously selected to the majority coalition. Exogenous tax rules, such as the linear tax rule in the EU, which is designed to increase efficiency on the contribution margin, can also improve overall efficiency despite decreasing the efficiency of the allocation of funds.
This paper takes a systematic look at the economic impact of the crisis that started in earnest in the fall of 2008 across countries and regions. Despite warnings of growing domestic and external imbalances in many countries years ahead of the crisis, the massive impact of the crisis came as a surprise to most. By correlating economic performance in the crisis with an extensive set of early warning, country insurance, and policy indicators, this paper provides some lessons on crisis prevention and management for the future. Although significant efforts have been made to develop robust early warnings systems, the paper shows the mixed success of some commonly analyzed indicators in predicting economic outcomes in this crisis. The only robust early warning indicator was increases in real estate prices while international reserves seem to have insured against the worst crisis outcomes on average. However, much work on building a robust early warning system remains and the analytical and empirical challenges in this area are substantial. The issues confronting early warning systems are also relevant to the more recent field of macro prudential supervision and regulation. Nevertheless, the cost of crises is massive and preventing future ones with better regulation, policies and supervision based on solid research must be a top priority among policy makers and academics alike.
How do political elites prepare the civilian population for participation in violent conflict? We empirically investigate this question using village-level data from the Rwandan Genocide in 1994. Every Saturday before 1994, Rwandan villagers had to meet to work on community infrastructure, a practice called Umuganda. This practice was highly politicized and, in the years before the genocide, regularly used for spreading political propaganda. To establish causality, we exploit cross-sectional
variation in meeting intensity induced by exogenous weather fluctuations. We find that an additional rainy Saturday resulted in a five percent lower civilian participation rate in genocide violence. These results pass a number of indirect tests of the exclusion restriction as well as other robustness checks and placebo tests.
The recent focus on impact evaluation within development economics has lead to increased pressure on aid agencies to provide "hard evidence", i.e. results from randomized controlled trials (RCTs), to motivate how they spend their money. In this paper I argue that even though RCTs can help us better understand if some interventions work or not, it can also reinforce an existing bias towards focusing on what generates quick, immediately verifiable and media-packaged results, at the expense of more long term and complex processes of learning and institutional development. This bias comes from a combination of public ignorance, simplistic media coverage and the temptation of politicians to play to the simplistic to gain political points and mitigate the risks of bad publicity. I formalize this idea in a simple principal-agent model with a government and an aid agency. The agency has two instruments to improve immediately verifiable outcomes; choose to spend more of the resources on operations rather than learning or select better projects/programs. I first show that if the government cares about long term development, then incentives will be moderated not to push the agency to neglect learning. If the government is impatient, though, then the optimal contract leads to stronger incentives, positively affecting the quality of projects/programs but also negatively affecting the allocation of resources across operations and learning. Finally, I show that in the presence of an impatient government, then the introduction of a better instrument for impact evaluation, such as RCTs, may actually decrease aid effectiveness by motivating the government to chose even stronger incentives.
This paper presents new evidence on intergenerational mobility in the top of the income and earnings distribution. Using a large dataset of matched father-son pairs in Sweden, we find that intergenerational transmission is very strong in the top, more so for income than for earnings. In the extreme top (top 0.1 percent) income transmission is remarkable with an IG elasticity above 0.9. We also study potential transmission mechanisms and find that sonsโ IQ, non-cognitive skills and education are all unlikely channels in explaining this strong transmission. Within the top percentile, increases in fathersโ income are, if anything, negatively associated with these variables. Wealth, on the other hand, has a significantly positive association. Our results suggest that Sweden, known for having relatively high intergenerational mobility in general, is a society where transmission remains strong in the very top of the distribution and that wealth is the most likely channel.
Does Islamic political control affect women's empowerment? Several countries have recently experienced Islamic parties coming to power through democratic elections. Due to strong support among religious conservatives, constituencies with Islamic rule often tend to exhibit poor women's rights. Whether this relationship reflects a causal or a spurious one has so far gone unexplored. I provide the first piece of evidence using a new and unique dataset of Turkish municipalities. In 1994, an Islamic party won multiple municipal mayor seats across the country. Using a regression discontinuity (RD) design, I compare municipalities where this Islamic party barely won or lost elections. Despite negative raw correlations, the RD results reveal that over a period of six years, Islamic rule increased female secular high school education. Corresponding effects for men are systematically smaller and less precise. In the longer run, the effect on female education remained persistent up to 17 years after and also reduced adolescent marriages. An analysis of long-run political effects of Islamic rule shows increased female political participation and an overall decrease in Islamic political preferences. The results are consistent with an explanation that emphasizes the Islamic party's effectiveness in
overcoming barriers to female entry for the poor and pious.
Poverty is associated with political conflict in developing countries, but evidence of individual grievances translating into dissent among the poor is mixed. We analyze survey data from 40 developing nations to understand the determinants radicalism, support for violence, and participation in legal anti-regime actions as petitions, demonstrations, and strikes. In particular, we examine the role of perceived political and economic inequities. Our findings suggest that individuals who feel marginalized tend to harbor extremist resentments against the government, but they are generally less likely to join collective political movements that aim to instigate regime changes. This potentially explains the commonly-observed pattern in low- and middle-income countries whereby marginalized groups, despite their political attitudes and high-levels of community engagement, are more difficult to mobilize in nation-wide movements. We also find that arenas for active political participation (beyond voting) are more likely to be dominated by upper-middle income groups who are committed, ultimately, to preserving the status quo. Suppressing these forms of political action may thus be counterproductive, if it pushes these groups towards more radical preferences. Finally, our findings suggest that the poor, in developing nations, may be caught in a vicious circle of self-exclusion and greater marginalization.
Anders Olofsgรฅrd (with R. Desai and T. Yousef).
We argue that the tilt towards donor interests over recipient needs in aid allocation and practices may be particularly strong in new partnerships. Using the natural experiment of Eastern transition we find that commercial and strategic concerns influenced both aid flows and entry in the first half of the 1990s, but much less so later on. We also find that fractionalization increased and that early aid to the region was particularly volatile, unpredictable and tied. Our results may explain why aid to Iraq and Afghanistan has had little development impact and serve as warning for Burma and Arab Spring regimes.
Anders Olofsgรฅrd (with A. Boschini).
Published in Journal of Development Studies.
In this paper, we test the argument that the sizeable reduction in aggregate aid levels in the 1990โs was due to the end of the Cold War. We test two different models using a dynamic econometric specification on a panel of 17 donor countries, spanning the years 1970-1997. We find aid to be positively related to military expenditures in the former Eastern bloc during the cold war, but not in the 1990โs, suggesting that the reductions in aid disbursements are driven by the disappearance of an important motive for aid. Our results also suggest that aid allocation may have become less strategic in the 1990โs.
In this paper I examine the development effects of coups. I first show that coups overthrowing democratically-elected leaders imply a different kind of event than those overthrowing autocratic leaders, and that these differences relate to the implementation of authoritarian institutions following a coup in a democracy. Secondly, I address the endogeneity of coups by comparing the growth consequences of failed and successful coups as well as implementing matching and panel data methods, which yield similar results. Although coups taking place in already autocratic countries show imprecise and sometimes positive effects on economic growth, in democracies their effects are distinctly detrimental. I find no evidence that these results are symptomatic of alternative hypothesis involving the effects of failed coups or political transitions. Thirdly, when overthrowing democratic leaders, coups not only fail to promote economic reforms or stop the occurrence of economic crises and political instability, but they also have substantial negative effects across a number of standard growth-related outcomes including health, education, and investment.
Find more research publications at https://www.hhs.se/site
When a government creates an agency to gather information relevant to policymaking, it faces two critical organizational questions: whether the agency should be given authority to
decide on policy or merely supply advice, and what should the policy goals of the agency be. Existing literature on the first question is unable to address the second, because the question
of authority becomes moot if the government can simply replicate its preferences within the agency. In contrast, this paper examines both questions within a model of policymaking under time inconsistency, a setting in which the government has a well-known incentive to create an agency with preferences that differ from its own. Thus, our framework permits a meaningful analysis of delegation versus communication with an endogenously chosen agent. The first main finding of the paper is that the government can do equally well with a strategic choice of agent, from which it solicits advice, instead of delegating authority, as long as the time inconsistency problem is not too severe. The second main finding is that the government may strictly prefer seeking advice to delegating authority if there is prior uncertainty with respect to what is the optimal policy.
By Anders Olofsgรฅrd (with R. Luma), published in Journal of Public Economics.
We use newly compiled top income share data and structural breaks techniques to estimate common trends and breaks in inequality across countries over the twentieth century. Our results both confirm earlier findings and offer new insights. In particular, the division into an Anglo-Saxon and a Continental European experience is not as clear cut as previously suggested. Some Continental European countries seem to have experienced increases in top income shares, just as Anglo-Saxon countries, but typically with a lag. Most notably, Nordic countries display a marked โAnglo-Saxonโ pattern, with sharply increased top income shares especially when including realized capital gains. Our results help inform theories about the causes of the recent rise in inequality.
Realized capital gains are typically disregarded in the study of income inequality. We show that in the case of Sweden this severely underestimates the actual increase in inequality and, in particular, top income shares during recent decades. Using micro panel data to average
incomes over longer periods and re-rank individuals according to income excluding capital gains, we show that capital gains indeed are a reoccurring addition to rather than a transitory component in top incomes. Doing the same for lower income groups, however, makes virtually no difference. We also try to find the roots of the recent surge in capital gains-driven inequality in Sweden since the 1980s. While there are no evident changes in terms of who earns these gains (high wage earners vs. top capital income earners), the primary driver instead seems to be the drastic asset price increases on the post-1980 deregulated financial markets.
This policy brief examines the timing of Turkeyโs authoritarian turn using raw data measuring freedoms from the Freedom House (FH). It shows that Turkeyโs authoritarian turn under the ruling AKP is not a recent phenomenon. Instead, the countryโs institutional erosion โ especially in terms of freedoms of expression and political pluralism โ in fact began much earlier, and the losses in the earlier periods so far tend to dwarf those occurring later.
1.. Islamic Rule and the Emancipation of the Poor and Pious
I estimate the impact of Islamic rule on secular education and labor market outcomes with a new and unique dataset of Turkish municipalities. Using a regression discontinuity design, I compare elections where an Islamic party barely won or lost municipal mayor seats. The results show that Islamic rule has had a large positive effect on education, predominantly for women. This impact is not only larger when the opposing candidate is from a secular left-wing, instead of a right-wing party; it is also larger in poorer and more pious areas. The participation result extends to the labor market, with fewer women classified as housewives, a larger share of employed women receiving wages, and a shift in female employment towards higher-paying sectors. Part of the increased participation, especially in education, may come through investment from religious foundations, by providing facilities more tailored toward religious conservatives. Altogether, my findings stand in contrast to the stylized view that more Islamic inโกuence is invariably associated with adverse development outcomes, especially for women. One interpretation is that limits on religious expression, such as the headscarf ban in public institutions, raise barriers to entry for the poor and pious. In such environments, Islamic movements may have an advantage over secular alternatives.
2. Islam and Long-Run Development
I show new evidence on the long-run impact of Islam on economic development. Using the proximity to Mecca as an instrument for the Muslim share of a country's population, while holding geographic factors fixed, I show that Islam has had a negative long-run impact on income per capita. This result is robust to a host of geographic, demographic and historical factors, and the impact magnitude is around three times that of basic cross-sectional estimates. I also show evidence of the impact of Islam on religious influence in legal institutions and women's rights, two outcomes seen as closely associated with the presence of Islam. A larger Islamic influence has led to a larger religious influence in legal institutions and lower female participation in public institutions. But it has also had a positive impact on several measures of female health outcomes relative to men. These results stand in contrast to the view that Islam has invariably adverse consequences for all forms of women's living standards, and instead emphasizes the link between lower incomes and lower female participation in public institutions.
3. The Rise of China and the Natural Resource Curse in Africa
We produce a new empirical strategy to estimate the causal impact of selling oil to China on economic and political development, using an instrumental variables design based on China's economic rise and consequent demand for oil in interaction with the pre-existence of oil in Sub-Saharan Africa.
Despite a voluminous literature on the topic, the question of whether aid leads to growth is still controversial. To observe the pure effect of aid, researchers used instruments that must be exogenous to growth and explain well aid flows. This paper argues that instruments used in the past do not satisfy these conditions. We propose a new instrument based on predicted aid quantity and argue that it is a significant improvement relative to past approaches. We find a significant and relatively big effect of aid: a one standard deviation increase in received aid is associated with a 1.6 percentage points higher growth rate.
https://www.delhipolicygroup.org/publication/policy-reports/dj-vu-in-myanmar.html - Over the past two months, Myanmar has plunged into a political crisis. Myanmarโs tentative political transition towards democracy, which started in 2010 and gained momentum after the 2015 elections, has been reversed. The military (Tatmadaw) has staged a coup dโรฉtat and arrested democratically elected leaders, including President Win Myint and State Counsellor Daw Aung San Suu Kyi.
We use a novel approach to address the question of whether a union of sovereign countries can efficiently raise and allocate a budget, even when members are purely self-interested and participation is voluntary. The main innovation of our model is to explore the link between budget contributions and allocation that arises when countries bargain over union outcomes. This link stems from the distribution of bargaining power being endogenously determined. Generically, it follows that unstructured bargaining gives an inefficient result. We find, however, that efficiency is achieved with fully homogenous countries, and when countries have similar incomes and the union budget is small. Moreover, some redistribution arises endogenously, even though nations are purely self-interested and not forced to participate in the union. A larger union budget, however, entails a trade-off between equality and efficiency. We also analyze alternative institutions and find that majority rule can improve efficiency if nations who prefer projects with high public good spillovers are endogenously selected to the majority coalition. Exogenous tax rules, such as the linear tax rule in the EU, which is designed to increase efficiency on the contribution margin, can also improve overall efficiency despite decreasing the efficiency of the allocation of funds.
This paper takes a systematic look at the economic impact of the crisis that started in earnest in the fall of 2008 across countries and regions. Despite warnings of growing domestic and external imbalances in many countries years ahead of the crisis, the massive impact of the crisis came as a surprise to most. By correlating economic performance in the crisis with an extensive set of early warning, country insurance, and policy indicators, this paper provides some lessons on crisis prevention and management for the future. Although significant efforts have been made to develop robust early warnings systems, the paper shows the mixed success of some commonly analyzed indicators in predicting economic outcomes in this crisis. The only robust early warning indicator was increases in real estate prices while international reserves seem to have insured against the worst crisis outcomes on average. However, much work on building a robust early warning system remains and the analytical and empirical challenges in this area are substantial. The issues confronting early warning systems are also relevant to the more recent field of macro prudential supervision and regulation. Nevertheless, the cost of crises is massive and preventing future ones with better regulation, policies and supervision based on solid research must be a top priority among policy makers and academics alike.
How do political elites prepare the civilian population for participation in violent conflict? We empirically investigate this question using village-level data from the Rwandan Genocide in 1994. Every Saturday before 1994, Rwandan villagers had to meet to work on community infrastructure, a practice called Umuganda. This practice was highly politicized and, in the years before the genocide, regularly used for spreading political propaganda. To establish causality, we exploit cross-sectional
variation in meeting intensity induced by exogenous weather fluctuations. We find that an additional rainy Saturday resulted in a five percent lower civilian participation rate in genocide violence. These results pass a number of indirect tests of the exclusion restriction as well as other robustness checks and placebo tests.
The recent focus on impact evaluation within development economics has lead to increased pressure on aid agencies to provide "hard evidence", i.e. results from randomized controlled trials (RCTs), to motivate how they spend their money. In this paper I argue that even though RCTs can help us better understand if some interventions work or not, it can also reinforce an existing bias towards focusing on what generates quick, immediately verifiable and media-packaged results, at the expense of more long term and complex processes of learning and institutional development. This bias comes from a combination of public ignorance, simplistic media coverage and the temptation of politicians to play to the simplistic to gain political points and mitigate the risks of bad publicity. I formalize this idea in a simple principal-agent model with a government and an aid agency. The agency has two instruments to improve immediately verifiable outcomes; choose to spend more of the resources on operations rather than learning or select better projects/programs. I first show that if the government cares about long term development, then incentives will be moderated not to push the agency to neglect learning. If the government is impatient, though, then the optimal contract leads to stronger incentives, positively affecting the quality of projects/programs but also negatively affecting the allocation of resources across operations and learning. Finally, I show that in the presence of an impatient government, then the introduction of a better instrument for impact evaluation, such as RCTs, may actually decrease aid effectiveness by motivating the government to chose even stronger incentives.
This paper presents new evidence on intergenerational mobility in the top of the income and earnings distribution. Using a large dataset of matched father-son pairs in Sweden, we find that intergenerational transmission is very strong in the top, more so for income than for earnings. In the extreme top (top 0.1 percent) income transmission is remarkable with an IG elasticity above 0.9. We also study potential transmission mechanisms and find that sonsโ IQ, non-cognitive skills and education are all unlikely channels in explaining this strong transmission. Within the top percentile, increases in fathersโ income are, if anything, negatively associated with these variables. Wealth, on the other hand, has a significantly positive association. Our results suggest that Sweden, known for having relatively high intergenerational mobility in general, is a society where transmission remains strong in the very top of the distribution and that wealth is the most likely channel.
Does Islamic political control affect women's empowerment? Several countries have recently experienced Islamic parties coming to power through democratic elections. Due to strong support among religious conservatives, constituencies with Islamic rule often tend to exhibit poor women's rights. Whether this relationship reflects a causal or a spurious one has so far gone unexplored. I provide the first piece of evidence using a new and unique dataset of Turkish municipalities. In 1994, an Islamic party won multiple municipal mayor seats across the country. Using a regression discontinuity (RD) design, I compare municipalities where this Islamic party barely won or lost elections. Despite negative raw correlations, the RD results reveal that over a period of six years, Islamic rule increased female secular high school education. Corresponding effects for men are systematically smaller and less precise. In the longer run, the effect on female education remained persistent up to 17 years after and also reduced adolescent marriages. An analysis of long-run political effects of Islamic rule shows increased female political participation and an overall decrease in Islamic political preferences. The results are consistent with an explanation that emphasizes the Islamic party's effectiveness in
overcoming barriers to female entry for the poor and pious.
El parking esta en plena trasformaciรณn. La nueva realidad de las ciudades inteligentes les colocan en un situaciรณn preferente. Tanto para personas como para รบltima milla de personas y logรญstica de productos.
Dรฉcouvrez le framework web Spring Boot qui a la cote !
Apprenez comment son systรจme d'auto-configuration fonctionne.
Live coding et exemple de migration vers Spring Boot sont de la partie.
Decision makers often face powerful incentives to increase risk-taking on behalf of others either through bonus contracts or competitive relative performance contracts. Motivated by examples from the recent financial crisis, we conduct an experimental study of risk-taking on behalf of others using a large sample with subjects from all walks of life. We find that people respond to such incentives without much apparent concern for stakeholders. Responses are heterogeneous and mitigated by personality traits. The findings suggest that lack of concern for othersโ risk exposure hardly requires โfinancial psychopathsโ in order to flourish, but is diminished by social concerns. We believe the research reported here is the first to experimentally investigate the effects of incentives on risk-taking on behalf of others, and to do so on a large scale using a random sample of the general population.
By Ola Andersson, Hรฅkan J. Holm, Jean-Robert Tyran and Erik Wengstrรถm
To read more research articles, please visit https://www.hhs.se/site
Rafael P. Ribas: Direct and indirect effects of bolsa famยดฤฑlia on entrepreneu...UNDP Policy Centre
ย
This presentation is part of the programme of the International Seminar "Social Protection, Entrepreneurship and Labour Market Activation: Evidence for Better Policies", organized by the International Policy Centre for Inclusive Growth (IPC-IG/UNDP) together with Canadaโs International Development Research Centre (IDRC) and the Colombian Think Tank Fedesarrollo held on September 10-11 at the Ipea Auditorium in Brasilia.
Running Head Literature Review 1Literatu.docxcowinhelen
ย
Running Head: Literature Review
1
Literature Review
2
Humanitarian Intervention in Libya
Name
Institution
Humanitarian Intervention in Libya
Over the most recent two decades, humanitarianism has encountered gigantic development, as both a field of try and as a point of academic research. In the custom of the International Committee of the Red Cross (ICRC), humanitarianism is customarily connected with unprejudiced, nonpartisan, and autonomous activities embraced to ensure the lives and respect of casualties of the equipped clash and different circumstances of viciousness and to furnish them with help. Following the research that has been doing recently this literature review defines, humanitarianism as the need and desire to relieve human being from suffering (Barnett 2009).
Humanitarianism is of gigantic consequences in contemporary worldwide legislative issues. Around the world, humanitarians help adds up to about 15 billion USD yearly (Global Humanitarian Assistance 2009). There is around 2,600 worldwide guide and improvement offices carrying out their specialty on each landmass and on each side of the globe; nearby and national associations bring the number more like 25,000 (Barnett 2008). In the general population cognizant, humanitarian associations and topics are absolutely ubiquitous. On the TV, on the Internet, in daily papers, and on bulletins, helpful commercials and humanitarianism topics are among the standard methods of experience amongst people groups and generally socially and physically far off universes. It is little pondered, at that point, that researchers and analysts are setting expanding logical weight on humanitarianism.
Simultaneous with the development of the philanthropic segment, the field of humanitarianism investigations has encountered quick advancement, together with its related fields of evacuee studies and improvement considers. Right now, the scene of helpful research comprises of a modest bunch of conspicuous research organizations and focuses of scholastic picking up, including the Feinstein International Center (Tufts University, USA), the Humanitarian Policy Group (Overseas Development Institute, UK), and Humanitarian Outcomes (UK). Philanthropic centered diaries incorporate the Journal of Humanitarian Affairs, Refugee Studies, and Disasters; the grant is additionally distributed in standard scholarly diaries extending from International Organization to Millennium to Voluntas. Throughout the most recent two decades, countless have likewise been distributed on the point. This literature review focuses on one part of this examination, specifically on a determination of vital late strategy centered articles; scholarly work is referenced as fitting.
In spite of the fact that there are special cases to this manage, including a few articles referred to underneath, this must be perceived as a hole. In an extensive part, this finding mirrors the impressively constrained ...
Classification Essay Writing. PPT - How to write an Outline for the Classific...Jami Nguyen
ย
Classification Essay Outline. Learn How to Write a Classification Essay with Our Checklist. How to Write a Division Classification Essay - Useful Guide. Classification Essay: Topics, Outline and Writing Tips HandMadeWriting. How to Write a Good Classification Essay CustomEssayMeister.com. How to Write a Classification Essay Steps, Format and Types of a .... How to Write a Classification Essay That Is Worth an A Blog .... Classification Essay. What is classification in writing. 10.4 Classification. 2022-10-23. Classification essay samples. How to Write a Classification Essay .... How to Write a Classification Essay: A Guide with Explanations Wr1ter. CLASSIFICATION ESSAY.doc. How to Write a Classification Essay - Topics amp; Examples. How to Write a Classification Essay: Example and Tips EssayWriters.us. Classification Essay by Alyssa Servie - Issuu. 150 Classification Essay Topics and Ideas. Custom Writing of All Types of Essays. Division essay topics. Classification Essay Topics to Disclose in .... PPT - How to write an Outline for the Classification Essay PowerPoint .... Tips for writing a classification essay. How to write a classification essay definition, step by step. Classification Essay Instruction With Pre Writing Activities Essays .... Essay Format: Classification. Classification Papers in Academic Writing. Classification Essay by Siobhan Gudat - Issuu. Classification essay writing 3. How to write a classification essay. Classification Essay Leadership Applied Psychology. Classification essay consider important attributes for great dealing by .... Classification Essay Examples, Definition and Writing Guidelines .... How to Write a Classification Essay: Outline, Steps, Writing Tips .... Classification Essay by Lingua Franca Systems Teachers Pay Teachers. Classification Essay Writing Tips Classification Essay Writing Classification Essay Writing. PPT - How to write an Outline for the Classification Essay PowerPoint ...
009 Critical Review Essay Example Sample Analysis Paper ~ Thatsnotus. Critical Review Essay | Information | Communication. Scholarship essay: What is a critical review essay.
Case Review PaperThis assignment will need to be typed, double-s.docxbartholomeocoombs
ย
Case Review Paper
This assignment will need to be typed, double-spaced with a cover page, font should be Times New Roman size 12, and inclusive of traditional (normal) one-inch margins. Any references you use need to be completed in APA formatting. For this assignment: (1) APA style must be used correctly, (2) All required relevant course readings and materials must be used, (3) At least 6 scholarly sources used (beyond course materials).The paper must be clear, well organized, and should be 10-15 pgs. not including cover page, references, and any other attachments.
This assignment provides an opportunity for students to complete a thorough case review of a client (Lisa). Students will assess Lisaโs case through a case study that provides several vignetteโs regarding Lisaโs experience child welfare and substance usage. This case study illustrates the journey made by Lisa, a parent involved in the child welfare and addiction treatment systems. Students will follow Lisa through treatment program interviews and subsequent treatment, having to meet deadlines, and her recovery process with typical challenges and a relapse.
This assignment will allow you to demonstrate how you would distinguish, appraise, and integrate multiple sources of knowledge (including research โbased knowledge and practice wisdom). Students will demonstrate their ability to apply Human Behaviors theories to guide basement and practice interventions. It is encouraged that you re-familiarize yourself with theories learned in Human Behaviors & Social Environment as well as Psychopathology courses (ex: Brief
Solution
Focused, Cognitive Behavioral Theory, Attachment Theory, Racial Identity Theory, Ego Psychology, Trauma Informed Theories).
Lisaโs story illustrates clinical issues, observations and decisions made by child welfare and addiction professionals, confidentiality processes and procedures, and decision points related to her children and competing requirements.
After reading Lisaโs Case Study (attached), please adhere to the following guidelines:
For this assignment, students will be expected to answer a series of questions that correspond to each stage of Lisaโs progress through the substance abuse child welfare system. These questions can be found at the bottom of every page of the case study.
Please be sure that your answer for each section is supported with peer-reviewed resources or course literature. Also, please remember to integrate course material throughout your answers.
There must be a theoretical support section in which students must
compare and contrast TWO theories and provide a through explanation and rationale for why one of the theories works best to support their work with the client.Please remember that you should specify the concepts and propositions from each theory that support, explain, and assist in your work with the client. Theories include
Respondent Learning theory, Operant Learning theory, Cognitive-Behavioral.
Essay About Overpopulation. Descriptive essay: Essay overpopulationRocio Garcia
ย
Essay on Overpopulation | Overpopulation Essay for Students and .... Overpopulation: Not What You Think - Free Essay Example | PapersOwl.com. Overpopulation in the World - Free Essay Example | PapersOwl.com. Persuasive essay: Causes of overpopulation essays. Effects of overpopulation in developing countries essay in 2021 | Essay .... (DOC) Overpopulation - Problems and Solutions | Anh Le - Academia.edu. Overpopulation Essay In English || Effects and Causes of Overpopulation .... 008 Over Population Cause And Effect Of Overpopulation Essay ~ Thatsnotus. Overpopulation Effects on Health and the Environment - Free Essay .... History Essay: Overpopulation research paper. โOverpopulation conclusion Essay Example | GraduateWay. Overpopulation essay in english.
Makes for interesting reading, whether you are in the industry or a consumer the message is clear: Funeral Planning should be on your list of things to do, whether you are 50 or 75!
Emotionally and financially it makes sense: Visit www.over50choices.co.uk for more.
Presented by Anastasia Luzgina during the conference "Belarus at the crossroads: The complex role of sanctions in the context of totalitarian backsliding" on April 23, 2024.
Presented by Erlend Bollman Bjรธrtvedt during the conference "Belarus at the crossroads: The complex role of sanctions in the context of totalitarian backsliding" on April 23, 2024.
Presented by Dzimtry Kruk during the conference "Belarus at the crossroads: The complex role of sanctions in the context of totalitarian backsliding" on April 23, 2024.
Presented by Lev Lvovskiy during the conference "Belarus at the crossroads: The complex role of sanctions in the context of totalitarian backsliding" on April 23, 2024.
Presented by Chloรฉ Le Coq, Professor of Economics, University of Paris-Panthรฉon-Assas, Economics and Law Research Center (CRED), during SITE 2023 Development Day conference.
This yearโs SITE Development Day conference will focus on the Russian war on Ukraine. We will discuss the situation in Ukraine and neighbouring countries, how to finance and organize financial support within the EU and within Sweden, and how to deal with the current energy crisis.
This yearโs SITE Development Day conference will focus on the Russian war on Ukraine. We will discuss the situation in Ukraine and neighbouring countries, how to finance and organize financial support within the EU and within Sweden, and how to deal with the current energy crisis.
The (Ce)ยฒ Workshop is organised as an initiative of the FREE Network by one of its members, the Centre for Economic Analysis (CenEA, Poland) together with the Centre for Microdata Methods and Practice (CeMMAP, UK). This will be the seventh edition of the workshop which will be held in Warsaw on 27-28 June 2022.
The (Ce)2 workshop is organised as an initiative of the FREE Network by one of its members, the Centre for Economic Analysis (CenEA, Poland) together with the Centre for Microdata Methods and Practice (CeMMAP, UK). This will be the seventh edition of the workshop which will be held in Warsaw on 27-28 June 2022.
The (Ce)2 workshop is organised as an initiative of the FREE Network by one of its members, the Centre for Economic Analysis (CenEA, Poland) together with the Centre for Microdata Methods and Practice (CeMMAP, UK). This will be the seventh edition of the workshop which will be held in Warsaw on 27-28 June 2022.
The (Ce)2 workshop is organised as an initiative of the FREE Network by one of its members, the Centre for Economic Analysis (CenEA, Poland) together with the Centre for Microdata Methods and Practice (CeMMAP, UK). This will be the seventh edition of the workshop which will be held in Warsaw on 27-28 June 2022.
Seminar: Gender Board Diversity through Ownership NetworksGRAPE
ย
Seminar on gender diversity spillovers through ownership networks at FAME|GRAPE. Presenting novel research. Studies in economics and management using econometrics methods.
BONKMILLON Unleashes Its Bonkers Potential on Solana.pdfcoingabbar
ย
Introducing BONKMILLON - The Most Bonkers Meme Coin Yet
Let's be real for a second โ the world of meme coins can feel like a bit of a circus at times. Every other day, there's a new token promising to take you "to the moon" or offering some groundbreaking utility that'll change the game forever. But how many of them actually deliver on that hype?
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
ย
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
What website can I sell pi coins securely.DOT TECH
ย
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the what'sapp contact of my personal pi merchant to trade with.
+12349014282
1. Elemental Economics - Introduction to mining.pdfNeal Brewster
ย
After this first you should: Understand the nature of mining; have an awareness of the industryโs boundaries, corporate structure and size; appreciation the complex motivations and objectives of the industriesโ various participants; know how mineral reserves are defined and estimated, and how they evolve over time.
^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Duba...mayaclinic18
ย
Whatsapp (+971581248768) Buy Abortion Pills In Dubai/ Qatar/Kuwait/Doha/Abu Dhabi/Alain/RAK City/Satwa/Al Ain/Abortion Pills For Sale In Qatar, Doha. Abu az Zuluf. Abu Thaylah. Ad Dawhah al Jadidah. Al Arish, Al Bida ash Sharqiyah, Al Ghanim, Al Ghuwariyah, Qatari, Abu Dhabi, Dubai.. WHATSAPP +971)581248768 Abortion Pills / Cytotec Tablets Available in Dubai, Sharjah, Abudhabi, Ajman, Alain, Fujeira, Ras Al Khaima, Umm Al Quwain., UAE, buy cytotec in Dubaiโ Where I can buy abortion pills in Dubai,+971582071918where I can buy abortion pills in Abudhabi +971)581248768 , where I can buy abortion pills in Sharjah,+97158207191 8where I can buy abortion pills in Ajman, +971)581248768 where I can buy abortion pills in Umm al Quwain +971)581248768 , where I can buy abortion pills in Fujairah +971)581248768 , where I can buy abortion pills in Ras al Khaimah +971)581248768 , where I can buy abortion pills in Alain+971)581248768 , where I can buy abortion pills in UAE +971)581248768 we are providing cytotec 200mg abortion pill in dubai, uae.Medication abortion offers an alternative to Surgical Abortion for women in the early weeks of pregnancy. Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman Fujairah Ras Al Khaimah%^^%$Zone1:+971)581248768โ][* Legit & Safe #Abortion #Pills #For #Sale In #Dubai Abu Dhabi Sharjah Deira Ajman
Financial Assets: Debit vs Equity Securities.pptxWrito-Finance
ย
financial assets represent claim for future benefit or cash. Financial assets are formed by establishing contracts between participants. These financial assets are used for collection of huge amounts of money for business purposes.
Two major Types: Debt Securities and Equity Securities.
Debt Securities are Also known as fixed-income securities or instruments. The type of assets is formed by establishing contracts between investor and issuer of the asset.
โข The first type of Debit securities is BONDS. Bonds are issued by corporations and government (both local and national government).
โข The second important type of Debit security is NOTES. Apart from similarities associated with notes and bonds, notes have shorter term maturity.
โข The 3rd important type of Debit security is TRESURY BILLS. These securities have short-term ranging from three months, six months, and one year. Issuer of such securities are governments.
โข Above discussed debit securities are mostly issued by governments and corporations. CERTIFICATE OF DEPOSITS CDs are issued by Banks and Financial Institutions. Risk factor associated with CDs gets reduced when issued by reputable institutions or Banks.
Following are the risk attached with debt securities: Credit risk, interest rate risk and currency risk
There are no fixed maturity dates in such securities, and assetโs value is determined by companyโs performance. There are two major types of equity securities: common stock and preferred stock.
๏ Common Stock: These are simple equity securities and bear no complexities which the preferred stock bears. Holders of such securities or instrument have the voting rights when it comes to select the companyโs board of director or the business decisions to be made.
๏ Preferred Stock: Preferred stocks are sometime referred to as hybrid securities, because it contains elements of both debit security and equity security. Preferred stock confers ownership rights to security holder that is why it is equity instrument
<a href="https://www.writofinance.com/equity-securities-features-types-risk/" >Equity securities </a> as a whole is used for capital funding for companies. Companies have multiple expenses to cover. Potential growth of company is required in competitive market. So, these securities are used for capital generation, and then uses it for companyโs growth.
Concluding remarks
Both are employed in business. Businesses are often established through debit securities, then what is the need for equity securities. Companies have to cover multiple expenses and expansion of business. They can also use equity instruments for repayment of debits. So, there are multiple uses for securities. As an investor, you need tools for analysis. Investment decisions are made by carefully analyzing the market. For better analysis of the stock market, investors often employ financial analysis of companies.
Tdasx: Unveiling the Trillion-Dollar Potential of Bitcoin DeFi
ย
Herding in Aid Allocation
1. SITE Working Paper No. 5, 2009
Herding in Aid Allocation
Emmanuel Frot and Javier Santiso
Stockholm Institute of Transition Economics
Stockholm School of Economics
Sveavรคgen 65, P.O. Box 6501
SE โ 113 83 Stockholm
Sweden
http://www.hhs.se/SITE/
2. 1
Herding in Aid Allocationยง
Emmanuel Frot*
and Javier Santiso ร
Abstract
Although there exists a vast literature on aid efficiency (the effect of aid on GDP), and that aid
allocation determinants have been estimated, little is known about the minute details of aid
allocation. This article investigates empirically a claim repeatedly made in the past that aid
donors herd. Building upon a methodology applied to financial markets, this article finds that aid
donors herd similarly to portfolio funds on financial markets. It also estimates the causes of
herding and finds that political transitions towards more autocratic regimes repel donors, but that
transitions towards democracy have no effect. Finally, identified causes of herding explain little
of its overall level, suggesting strategic motives play an important role.
Keywords: aid; herding; volatility; fragmentation.
JEL classification: F34, F35.
ยง
We wish to thank for their comments and insights Torbjรถrn Becker, Thomas Dickinson, Burcu Hacibedel,
Andrew Mold, Elizabeth Nash, and Helmut Reisen. The remaining errors are the sole responsibility of the
authors.
*
email: emmanuel.frot@hhs.se. SITE, SSE, Sveavรคgen 65, PO Box 6501, SE-11383 Stockholm, Sweden.
ร
email: Javier.santiso@oecd.org. OECD, 2 rue Andrรฉ Pascal 75116 Paris, France.
3. 2
I. Introduction
The literature in economics on foreign aid has so far mainly concerned itself with aid
efficiency, attempting to answer the key question of whether aid indeed promotes growth. The
motivation for this research agenda has been reinforced by the tough criticisms the aid industry
has experienced over recent years. Among others, Paul Collier (2007), after a life devoted to
development economics, in his recent book The Bottom Billion, argues that aid is unable to make
a real difference to the worldโs poor. Others, such as the former World Bank economist William
Easterly, regularly point out the deficiencies in aid allocation mechanisms. For instance, Easterly
and Pfutze (2008) argue that aid is fragmented between many small donors in a given country,
increasing transaction costs and revealing coordination failures.
After many papers evaluating the effect of aid on growth (see Roodman 2007 for a recent
review of the literature) often reaching somewhat disappointing conclusions, some have started to
narrow the question and look at the effect of aid on more specific variables (for instance Mishra
and Newhouse 2007 on the effect of aid on infant mortality). Nevertheless, the question still
remains firmly focused on the effect of aid on a given growth outcome. Much less has been said
about the allocation of aid: while aid determinants have been estimated, donorsโ decision process
in their choice of recipients, or how one donorโs decisions may affect othersโ allocations is still
little understood. This is not a completely new concern. Cassen (1986) already mentioned that
donors moved in herds, suddenly disbursing money into โstarโ countries, and that sudden
increases were followed by long aid declines. However, while this claim has been made (Riddell
2007 argues that there is a โherd instinctโ among donors), no study has yet attempted to measure
herding and to determine its causes.
This paper is a first step in this direction. It is also part of a broader research agenda that
studies donor allocation policies in order to understand the role of aid relative to capital flows.
While herding is now a basic assumption among traders in bonds and equities, much less is
known about aid donors. However if the latter also herd, might not such behaviour from both
public and private actors compound to create even grater overall herding? Because aid donors are
somehow expected to play a different role to that of private investment, we believe it is to
compare these different actorsโ actual behaviour.1
1
For a comparison between aid donors and portfolio funds regarding quantities, volatility and fragmentation, see
Frot and Santiso (2008).
4. 3
The concept of herding was originally developed by sociologists following the seminal work
of French social scientist Gustave Le Bon, who published his famous La psychologie des foules
in 1895 and some years later by George Simmel in another seminal book published in 1903, The
Metropolis and Mental Life. The very first economist to refer to this notion was Thorstein
Veblen; in his 1899 essay The Theory of the Leisure Class, written while at the University of
Chicago, he explained economic behaviour in terms of social influences such as "emulation,"
where some members of a group mimic other members of higher status. The notion has grown to
become used extensively by financial economists over the past decades. Bikhchandani and
Sharma (2000), or Hirshleifer and Teoh (2003), provide overviews of the field. The academic
study of behavioral finance has identified herding as an important factor in the collective
irrationality of investors, particularly the work of Robert Shiller (2000).
This paper offers different measures of herding to test for its presence and evaluate its size.
Our results all reject the hypothesis of no herding, with its importance depending on the chosen
measure and sample. We develop two indexes and apply them to different data sets. The first one
is the most widely used in the finance literature. It was proposed by Lakonishok et al. (1992) and
has subsequently been broadly applied in the field. It is based on the simple intuition that there is
herding when many more traders (donors) buy or sell a stock (increase or decrease aid to a
recipient) than they do on average. The variable on which the herding measure is based is
therefore the proportion of traders (donors) buying (increasing aid to) each stock-quarter
(recipient-year). Frey et al. (2007) recently showed that this measure was negatively biased and
did not consistently estimate herding even for large sample sizes. They proposed an alternative
consistent measure based on the same intuition but relying on a simple structural model, which
we also apply here.
Nevertheless, both these measures are used in this paper with some variations from the
finance literature to capture the specificity of aid allocation. In particular we present results using
two types of data frequency. Yearly data is available for aid allocation, but is likely to be
contaminated by small, โnoisyโ, aid movements and may fail to capture the actual donor
allocation horizon. Longer time periods are therefore used to account for inertia in aid allocation
and eliminate some noise. Our preferred measure uses 3-year data and suggests that herding size
is around 10 per cent. This implies that in a world where 50 per cent of all allocation changes are
increases, the average recipient experiences 60 per cent of its donors changing their allocation in
the same direction. In other words half of recipients see 60 per cent of their donors increase their
allocations, and the other half sees a 60 per cent decrease their aid allocations. Our lower bound
for herding size, based on measures using yearly data, is around 6 per cent.
5. 4
Such a herding level may be difficult to interpret as many factors induce donors to change
their aid allocations along similar lines, and so feed into herding measures. Herding determinants
are therefore estimated to better understand what enters into our measures, and the effects of
various shocks evaluated using appropriate generalized linear model (GLM) techniques.
Predictably, we find that transitions towards less democratic regimes cause donors to
simultaneously decrease aid allocations. However, the opposite does not reveal itself to be the
case. This asymmetry, while somewhat puzzling, is robust to all our specifications. Natural
disasters, unsurprisingly, also create herding, wars, however, do not. This estimation in itself may
contribute to the debate on the determinants of aid, suggesting which factors trigger responses
from donors, positive or negative. If we consider that donors first choose which recipients should
receive more aid than in previous years and then, given a fixed aid budget, subsequently decide
on precise allocation numbers then our results provide empirical estimates of the first step of the
process.
Finally, GLM estimates allow us to calculate the contribution of each determinant to the
herding measure. Observable determinants in fact explain little of herding, with a very large share
that cannot be solely attributed to political factors, natural disasters or wars. Though we must be
careful in interpreting this result, these results suggest that other non-observable factors are at
play, and in particular factors that relate directly to โpureโ herding such as information cascades
or signalling.
Our motivations for studying herding are twofold. First, herding imposes costs and benefits
on recipients. It can be regarded positively as the coordination of donors in cases of emergency.
Humanitarian needs following a natural disaster or a war naturally call for a greater aid effort
from donors. This paper attempts to avoid including such โbeneficialโ herding in its measures by
carefully defining aid.
On the other hand herding is usually associated with sudden swings and an overflow of
money that is not always beneficial. In the case of aid, multiple donors implementing many
missions in an uncoordinated fashion, or aid fragmentation, has been shown to decrease aid
efficiency and may impose an unnecessary burden on already weak administrations in developing
countries (see Djankov et al. 2008a; Djankov et al, 2008b; OECD, 2008; Knack and Rahman
2007). By focusing on the proportion of donors increasing aid allocations, and not on actual aid
quantities, we also hope to contribute to the debate on the causes of aid fragmentation. Cassen
(1986) provides an example of herding leading to fragmentation and a misallocation of resources.
6. 5
He mentions that a large number of donors became involved in the Kenyan rural water supply
sector, resulting in an overflow of administrative procedures that the weak Kenyan Ministry of
Water Development could not face. Both donors and the Kenyan Government agree that aid to
this sector has been a disaster.
The costs of herding also include increased aid volatility. Herding may be an important factor
behind the large swings in the levels of aid experienced by recipients, beyond the conscious
coordination of aid decisions. Aid volatility has been a major concern for many years (see Bulรญล
and Hamann 2006) and its costs have been evaluated to be potentially very high for aid recipients
(Arellano et al. 2008). While Frot and Santiso (2008) showed that other types of private capital
inflows were more volatile, volatility in foreign aid flows is considered harmful for developing
countries, and in particular in low income countries that are aid dependent (for an analysis of
fiscal and budget policy sensitivities on aid dependence, see Mejรญa and Renzio 2008). An
unstable source of finance prevents governments from planning ahead and, as shown by Agรฉnor
and Aizenman (2007), may bring aid recipients to fall into a poverty trap by making it impossible
to invest in projects requiring a steady flow of funds. Bulรญล and Hamann (2006) report that aid
volatility has worsened in recent years. Kharas (2008) also finds the cost of volatility to be large
and argues that herd behaviour, by creating donor darlings and orphans, accentuates collective
volatility, underlining that while a donor can reduce volatility by running counter the overall aid
cycle, the herding phenomenon will render this unlikely.
A second motivation of the paper is to improve our understanding of donor allocation
policies. It has been argued that aid depends on many economic, political and historical
determinants. However, the interaction between members of the donor community has been little
studied. Given the very large number of actors,2
we expect decisions to depend on various signals
(recipient needs, past relationship between donor and recipient, but also other donorsโ decisions).
While we are not the first to empirically investigate this link between donors, to our knowledge
this paper is the first to use herding measures to document it. Past studies have estimated the
effect of total donorsโ aggregated aid on the aid of a specific, individual donor.
Tezanos Vรกzquez (2008), using this methodology, finds a โbandwagon effectโ of Spanish aid.
Berthรฉlemy (2006), Berthรฉlemy and Tichit (2004) and Tarp et al. (1998) use exactly the same
approach. It is however quite different from ours, in that it does not look at simultaneous identical
decisions from donors and so does not have a great deal to say about interactions. It does not treat
2
53 donors reported their activities to the Development Assistance Committee of the OECD in 2007, but these do
not include some other important donors (Brazil, China, Venezuela, etc.) and non-official donors (NGOs, private
foundations and charities).
7. 6
donors equally, as the total aid allocated to a recipient often depends on the decisions of a handful
of large donors. Finally because of the reflection problem defined by Manski (1993) this effect is
not consistently estimated using regressions.
Finally, herding is potentially a force contributing to the emergence of donor darlings and aid
orphans. Though her study is based on NGOs rather than on official donors, Reinhardt (2006)
provides some evidence that donors do herd. She reports donor agents as saying that โwe know
other foundations trust Organization X, so we went straight there and told them we wanted a
partnershipโ. An NGO financial director also acknowledges that โI can't get IDB money if I drop
the ball with the World Bankโ. When repeated this behaviour creates inequalities among aid
recipients even if ex ante they share similar characteristics. Marysse et al. (2006) argue that
political considerations and donor coordination problems have created such donor darlings and
aid orphans in the region of the Great Lakes in Africa.
II. Beyond Fads and Fashions: Beneficial herding
Any herding measure based on the detection of simultaneous and identical donor decisions
must capture aid movements caused by exogenous factors. For instance when a natural disaster
hits a country, there is indeed herding. When donors finance urgent humanitarian needs and
decide simultaneously to increase their aid allocations to the country, we term this โbeneficialโ
herding. It simply reflects suddenly increased needs that are taken into account by the donor
community as a whole. The Asian Tsunami in December 2004 provides an excellent example of
such beneficial herding.
Figure 1 plots the proportion of donors disbursing aid that actually increased their gross aid
allocations compared to the year before. This proportion is calculated for four countries
particularly affected by the tsunami: Indonesia, Maldives, Sri Lanka, and Thailand.
8. 7
Figure 1: Proportion of donors increasing aid
Source: Authors, 2009; based on OECD data, 2009.
During the ten years preceding the tsunami the proportion of donors increasing their gross aid
allocation hovers around 50 percent and remains relatively stable for each recipient, with perhaps
the exception of Sri Lanka. In 2005, the year humanitarian aid was actually disbursed, the
proportion jumps to about 80 percent. In this case, coordinated donor actions are beneficial. It is
herding in reaction to a clear, identifiable, exogenous shock. Other examples are available:
Bosnia-Herzegovina and Timor-Leste faced humanitarian crises and severe reconstruction needs
that triggered simultaneous aid flows from most donors. More recently, in 2008, Georgia
received a USD 4.5 billion dollar aid pledge by 38 countries and 15 multilateral organisations.
Donors also coordinate their actions when they grant debt relief. Many donors tremendously
increased aid to Nigeria in 2005 and 2006, though this was through debt forgiveness mechanisms.
Ideally a measure of herding would distinguish between such coordinated moves, sometimes
decided in international summits, and herding caused by allocation policies, strategic motives,
and competition among donors. A suitable definition of aid allows the elimination of a fair share
of the former. Country Programmable Aid (CPA) does not include items that are not predictable
by nature: humanitarian aid, debt relief and food aid. This variable has been used recently to
study aid fragmentation (OECD 2008) and trends in foreign aid (Kharas 2007). It is calculated by
subtracting humanitarian aid, gross debt relief and food aid from gross aid, as defined by the
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Indonesia Thailand Maldives Sri Lanka
9. 8
Development Assistance Committee (DAC). This quantity constitutes the core of aid that
finances development in a medium to long term perspective. Though not perfect, a herding
measure based on this variable is not subject to the sudden aid swings due to humanitarian
emergency and debt relief.
III. Herding measures
a) Definitions
Evaluating herding in aid allocation is a thorny issue, leading us to turn to the financial
literature where herding has been measured and modelled for many years. Lakonishok et al.
(1992) developed an index based on the idea that herding occurs when traders (donors) deviate
from an โaverageโ behaviour. Their methodology is purely statistical and does not rely on any
structural model. It is therefore quite simple and general, but may not be powerful enough to
detect and evaluate herding correctly. Their index LSVit is defined as follows
๐ฟ๐๐๐๐ก = ๐๐๐ก โ ๐๐ก โ ๐ธ ๐๐๐ก โ ๐๐ก
On financial markets pit is the proportion of funds buying stock i in period t. By analogy
in our aid study it is the proportion of donors increasing their allocation to recipient i in period t.
The basic idea of the measure is that when there is no herding, aid increases and decreases are
randomly distributed. If there are an excessive number of increases or decreases then it is
interpreted as herding behaviour. ฯt provides the benchmark against which herding is assessed. It
is the average proportion of aid increases in all the decisions taken in year t, ๐๐ก =
๐ ๐๐ก๐
๐ ๐๐ก๐
where bit
is the number of aid increases and nit is the number of donors active in recipient i in year t. It is
the probability that a donor increases its aid to a recipient in year t under the hypothesis of no
herding. The first term of the equation is positive even when there is no herding. The second term
is an adjustment factor that serves as a correction. LSVit has therefore a zero expected value under
the hypothesis of no herding. Herding is measured by averaging LSVit for the desired time period
and groups of recipients and we denote this average LSV. This measure has been used by
Lakonishok et al. (1992), Grinblatt et al. (1995), and Wermers (1999), amongst others, to
estimate herding in mutual funds. Uchida and Nakagawa (2007) applied it to the Japanese loan
market, Weiner (2006) to the oil market, and Welch (2000) to financial analysts. Herding
behaviour has been particularly pronounced in emerging markets as underlined by many studies
on financial crisis spillovers (Ornelas and Alemani, 2008; Bekaert and Harvery, 2000).
10. 9
The key intuition behind LSVit is the dispersion of increases and decreases around the
average proportion ฯt. This feature makes it neutral with respect to global trends in aid allocation.
If donors cut their aid budgets, as they did in the nineties, this is captured by ฯt and it does not
affect the herding measure. The overall increasing trend in aid over the last 50 years does not
influence it either. LSVit is also independent of aid concentration at the recipient level. Whether a
very small number of donors represent most of the receipts, or whether all donors disburse
similar quantities to a recipient does not matter. Herding is here based on the idea of similar
decisions, regardless of the quantities involved. For this reason it is also detached from fixed
allocation determinants due to historical ties or political economy factors. For example, the fact
that a donor favours a particular recipient because it is a former colony is irrelevant here. What
matters is the variation in aid from one period to the next, and not the exact quantity allocated
each year.
Recently Frey et al. (2007) have shown that this approach may actually fail to measure
herding properly. They develop a simple structural model to match the use and interpretation of
LSVit and find in simulations that the measure underestimates the true herding parameter. The
adjustment factor overcorrects the estimated parameter unless there are a very high number of
observations per recipient year. Unfortunately this is not the case in aid where the number of
donors never exceeds 53 in our data. Frey et al. (2007) propose an alternative measure Hit not
subject to the inherent bias of LSVit:
๐ป๐๐ก =
๐๐๐ก
2
(๐๐๐ก โ ๐๐ก)2
โ ๐๐๐ก ๐๐ก(1 โ ๐๐ก)
๐๐๐ก (1 โ ๐๐๐ก )
nit is the number of donors giving aid to recipient i in year t. Hit is then averaged over recipient-
years. For a set A of recipient-years they define
๐ป =
1
#๐ด
๐ป๐๐ก
(๐,๐ก)โ๐ด
โ = ๐ป
h is a consistent estimator of their herding parameter. Using Monte Carlo simulations they find
that LSV is a good statistic to test for the presence of herding: if LSV is significantly different
from zero, then there is herding. However LSV does a poor job at estimating the size of herding.
H is also a viable statistic to test the presence of herding and h provides an accurate estimate of
herding. In particular it improves significantly with the number of recipient-years, while LSV
does not. Since our sample contains at most 5171 observations h is expected to perform
11. 10
particularly well. Frey et al. therefore suggest a two step approach: first, test the existence of herd
behaviour using either LSV or H; second if significant herding is found, estimate its level
consistently using h.
Our approach follows their suggestion. For each set of recipient-years where herding is
measured, LSV is reported. If the hypothesis of no herding is rejected then h is calculated to
estimate its size. This approach is not flawless though. It was mentioned above that unlike LSV, h
relies on a structural model. It is simple and quite general but it may not be suited to aid
allocation or may miss some important characteristics. In that case h may not be a good measure.
b) Which recipient-years? Which donors?
The OECD DAC dataset contains 5837 recipient-years where at least one donor is active.3
Aid activities of 60 donors are reported, though no more than 53 are ever present simultaneously.
Herding measures can theoretically be based on all these observations. However there are good
reasons to restrict the set of donors and recipients.
Donors enter and exit the aid market. Some donors did not give any aid before a particular
year (Greece, New Zealand, Spain, etc.) but some also stopped after a particular year or stopped
reporting their activities to the DAC. The fact that a new donor can only increase its aid
allocations is not necessarily an issue because the first year a donor is present is by construction
not used in the herding measure. Only second year allocations onwards are valid for our purpose
since to define aid increases and decreases in year t we need allocations in year t-1. On the other
hand a donor that exits can only decrease its allocations. It may do so gradually over time if it has
planned to cease its activity. Its behaviour is biased and may hide or exaggerate herding. We
consequently compute our herding measure excluding donors that cease their activity. To be on
the safe side we additionally estimate herding using a constant set of donors, made of developed
countries that have been disbursing aid from 1960 to 2007, the full span of the data. Any donor
that enters later or stops its activity earlier is excluded. These two restrictions are quite strong
because they limit the number of observations and disregard some potentially useful data.
A similar issue arises with recipients. Some countries do not โexistโ before a certain date.
That mainly concerns ex-Soviet Republics and regions of former Yugoslavia. There was
beneficial herding towards these countries. Their geographic proximity to many important donors
3
A donor is defined as active in recipient i in year t if it changes its allocation to recipient i from year t-1 to year t.
12. 11
and their needs created an influx of aid.4
This type of herding is conspicuous and it is large. It
inflates any herding measure. Because we do not want our results to rely on these few particular
cases we simply exclude them. Other entries are due to late additions to the OECD DAC recipient
list. Aid to China has been recorded only from 1979, and only from 1975 for Mongolia. Whether
none was given before or whether it was not reported is unclear. These are also excluded from the
set of recipient-years. Any developing country that is not in the dataset in 1960, because it did not
exist at that time, or was not on the DAC list of recipients, is not taken into account when
computing herding measures. This choice is also quite restrictive as it leaves aside observations
where there may be herding.
An intermediate restriction is also applied. Recipients and donors entering after 1960 are
included but their first five years of presence are not. It leaves some time for donors to scale aid
up to new countries and reach a stabilised regime. It also allows donors to increase their
allocations in their first years of presence without this affecting the herding measures.
Finally both LSVit and Hit can be computed as soon as one donor is active in the recipient-
year. Yet to talk about herding when there is only one donor does not make much sense. There
must be a herd to follow in order to have herd behaviour. Recipient-years with fewer than five
active donors are not considered.
To sum up, donors that stop their activity are never included, those that enter after 1960 are
not included, or only after their first five years. Countries whose receipts were not recorded in
1960 are excluded, or are included only after their first five years. Recipient-years with fewer
than five active donors are always excluded. That leaves us with a dataset that contains at most
5171 recipient-years.
LSVit and Hit are computed for different groups of donors. Activities either from all donors are
considered, or only from DAC donors, or only from multilateral donors. Indeed one might think
that bilateral donors herd but that multilateral donors take independent decisions. In that case the
latter are merely adding some noise that makes herding more difficult to detect.
4
It is debatable whether there was herding given their characteristics: other countries under similar conditions might
not have enjoyed similar attention.
13. 12
IV. Results
Table 1 presents herding measures for different groups of donors. Herding is significant in all
groups, regardless of the restrictions imposed, except among multilateral donors. Those do not
herd.5
DAC donors on the other hand, do. LSV is always significant at the 1 per cent level.
Having passed the existence test, h is computed to find herding levels.
Both LSV and h have the same interpretation. Paraphrasing Lakonishok et al. (1992), a
measure of x implies that if ฯ, the average fraction of changes that are increases, was 0.5, then
50+x percent of the donors were changing their allocations to an average recipient in one
direction and 50-x percent in the opposite direction. As emphasised by Frey et al. (2007) LSV
underestimates herding and is always much smaller than h. According to the LSV measure, there
is statistically significant herding but not economically. Only about 1 per cent of the changes can
be attributed to herding. In other words only 1 per cent of the changes in an average recipient-
year cannot happen by chance and so constitute herding. The adjustment factor overcorrects LSV
to the point that it cannot distinguish between randomness and herding. h does not suffer from the
same bias. Its size implies that if the average fraction of changes that are increases is 0.5, on
average around 56% of donors take similar decisions in a recipient-year.
Herding on financial markets using the LSV measure is usually higher. Lakonishok et al.
(1992) find a value of 2.7, Wermers (1999) of 3.40. Herding in aid allocation would be roughly a
third of what is observed in finance according to this measure.
5
It must be clear that multilaterals do not herd among themselves. It does not imply that some of them do not herd
with bilateral donors.
14. 13
Table 1: LSV and h measures
All donors DAC donors
Multilateral
donors
LSV h LSV H LSV h
Donors present until 2007, recipients present
since 1960
1.07
(5171)
6.27 1.05
(4866)
6.53 0.43
(3998)
4.36
Donors present 1960-2007, recipients present
since 1960
1.07
(4788)
6.65 1.08
(4640)
7.08 n.a .
5 year presence threshold 1.02
(5098)
6.03 1.11
(4865)
6.61 0.45
(3803)
4.64
Source: Authors, 2009; based on OECD data, 2009.
V. Alternative measures
The two previous measures rely on the idea of dispersion relative to an average behaviour in
aid allocation. The benchmark is the same for all countries in a given year. It is a cross country
reference, implicitly assuming that all countries are expected to be treated similarly in the
absence of herding.
An alternative is to use past changes within countries. The expected proportion of increases in
recipient i in year t would not be the proportion of increases in that year but instead the average
proportion of increases in i from year t-5 to year t-1. The 5 year window is arbitrary. This
measure does not assume equal treatment across countries but rather that under the assumption of
no herding todayโs proportion of increases is expected to be close to what occurred in the last five
years. The two measures are complementary as they are based on two different conceptions of
herding. Like LSVit it should be made neutral to changes in the global trend in aid. A proportion
of increases can be far from its moving average because of herding or because the general policy
in the current year is to decrease (or increase) aid. In order to shield the measure against such
variations, the variable of interest is not the proportion of increases but instead the difference
between this proportion and the average proportion of increases in that year. The within measure
Wit is defined as:
15. 14
๐๐๐ก = ๐๐๐ก โ ๐๐ก โ ๐๐๐ก โ ๐๐ก โ ๐ธ ๐๐๐ก โ ๐๐ก โ ๐๐๐ก โ ๐๐ก
where the upper bar designates the 5-year moving average.
The analogue of Hit is Hit
w
:
๐ป๐๐ก
๐ค
=
๐๐๐ก
2
๐๐๐ก โ ๐๐ก โ ๐๐๐ก โ ๐๐ก
2
โ ๐๐๐ก ๐๐๐ก 1 โ ๐๐๐ก โ ๐๐๐ก
2
(๐๐ก โ ๐๐๐ก )2
๐๐๐ก 1 โ ๐๐๐ก
Hw and hw are then defined in a similar fashion to H and h. An example may serve to
illustrate the difference between the two measures. Assume that the proportion of increases in
year t is 0.5. 80 per cent of the donors active in a given recipient i in year t increase their
allocations. LSVit interprets this deviation as herding. In the past five years the average proportion
of increases for recipient i has been 0.75. The within measure does not see any significant
difference between year t and the past and returns a non-significant herding value. The two
measures do not necessarily disagree though. Had the past proportion of increases been 0.5 then
both measures would return the exact same herding level.
Wit and Hit
w
are computed for the same group of donors and recipients as LSVit and Hit. In
order to be included a recipient-year and each of the past five years must have at least 5 active
donors. If fewer than five years are available then the observation is discarded.
Table 2: W and hw
measures
All donors DAC donors
Multilateral
donors
W hw
W hw
W hw
Donors present until 2007, recipients present
since 1960
1.45
(4485)
6.96 1.77
(4162)
8.42 0.65
(3234)
5.21
Donors present 1960-2007, recipients present
since 1960
1.90
(4113)
8.95 1.90
(3933)
9.31 n.a
5 year presence threshold 1.57
(4656)
7.80 1.86
(4370)
8.86 0.69
(3066)
5.26
Source: Authors, 2009; based on OECD data, 2009.
Table 2 reports the results using the within measures. Herding is more pronounced when
the benchmark is based on past allocations. hw
indicates values around 7-9 per cent. This means
16. 15
that if in the past five years on average 50 percent of all active donors increased their aid
allocations then in the current year 57-59 percent take a similar decision. Values for multilateral
donors are still very small.
LSV uses yearly data to detect herding. It makes sense because donor disbursements are
allocated on a yearly basis and these are expected to be influenced by herding. On the other hand,
donors, unlike traders, commit to future disbursements over several years. Many projects have a
longer horizon than a year. Even if they herd, donors might find it difficult to stop programs
currently running and shifts in allocation may take some years before taking effect. Year-on-year
changes may fail to capture such movements and on the contrary be oversensitive to small
variations that do not reflect herding but rather marginal changes due to project progression.
Indeed many aid changes are quite small: the median absolute change for all donors is USD 0.80
million but the average is 8.53 million. The distribution of changes is strongly skewed towards
small values. It is difficult to argue that such small variations always reflect donor choices.
However LSV (or h) treat changes regardless of their sizes. It could be argued that these limited
variations inflate herding measures artificially by putting some weight on random variations.
These also create noise in the data that makes herding more difficult to detect.
Two solutions are proposed to address this issue. First โsmallโ changes are not taken into
account. More precisely, focusing on the most stable group of donors and recipients that includes
only donors present continuously from 1960 to 2007 and recipients present since 1960,
25 per cent of all changes are smaller than USD 0.24 million (the median is 1.52, the average
11.99). If a donor changes its allocation by less than USD 0.24 million in absolute terms then it is
not used to compute the two herding measures. However, the requirement that at least 5 valid
donors must be active in a recipient year is not changed. Since a valid donor must change its
disbursement by at least 0.24 million this condition is stronger. Second random variations are
smoothed away by using 3-year periods. Instead of using year-on-year changes, disbursements
are added up over a period of three years and a donor is said to increase its aid to a recipient
between two periods if its disbursements over three years are higher than over the three precedent
years (here again a period is valid only if the donor disbursed aid during each of the three years of
the period). Collapsing the data in such a way drastically reduces the number of observations but
increases the median size of an absolute change from 1.52 to 4.87 million. Lengthening the
period takes into account the medium term perspective of development aid. The exact length is
arbitrary, and results using 5-year periods are also presented.
17. 16
Table 3: LSV and h measures excluding small changes and with 3 and 5-year periods.
Small changes
excluded
3-year periods 5-year
periods
LSV h LSV h LSV h
Donors present until 2007, recipients
present since 1960
1.32
(4573)
7.21 3.37
(1670)
11.20 4.44
(974)
12.92
Donors present 1960-2007, recipients
present since 1960
1.14
(4056)
7.26 3.37
(1582)
11.98 4.25
(935)
13.61
Source: Authors, 2009; based on OECD data, 2009.
The first two columns of Table 3 indicate that the exclusion of small changes does not
have a big impact on herding size. It is only slightly higher, suggesting that small variations tend
to compensate each other on average. The next two columns use three-year periods to detect
herding. Its presence is confirmed and its size is above what has been found in Table 1. For the
same donor and recipient category, h measured on yearly data yielded a value of 6.27. 3-year data
reveal a herding level of 11.20. 5-year data provide a similar and even stronger conclusion. If one
prefers to use the LSV measure for both detection and size to avoid relying on any structural
model, then results are even stronger with size multiplied by three. Magnitudes are now similar to
those observed on financial markets. If we are willing to adopt a slightly longer term perspective,
herding appears to be more pronounced. Given the way aid is disbursed with commitments and
tranche disbursements as projects progress, this perspective seems well suited and avoids
building measures on often small yearly variations.
Table 3 confirms that there is significant herding in aid allocation and that its size is
actually more important than what is derived from yearly data. Longer periods yield levels above
or similar to what has been measured on financial markets with quarterly data. A high frequency
makes sense in finance where investors are quick to respond and modify their portfolio choices,
but much less in development. It is difficult to identify the optimal time span, but a few years are
likely to match allocation policiesโ time frame.
The different measures we have used all point in the same direction. Herding in aid allocation
is present. However its exact size depends on how we think it should be evaluated. Yearly
allocations in a pure cross country framework return a limited size. Within measures improve on
the cross country ones by having the advantage of taking into account country fixed effects.
Within herding is somewhat higher. Finally, year-on-year changes might not reflect decisions but
be contaminated by random variations. Longer periods reveal larger herding levels that have
18. 17
important consequences for aid recipients. Using all the different approaches, the measure h
estimates herding to be between 6 and 12 per cent.
VI. Geographical distribution of herding
Even though we focus on the average level of herding across developing countries, we show
here how herding differs across countries. The following map indicates herding levels in each
country. Herding is computed using the LSV index with 3-year periods, donors present until 2007,
and with more than 5 donors per recipient-period. Unlike the previous tables, we do not exclude
developing countries that entered later than 1960, since the point here is to provide as
comprehensive a picture as possible. Interval bounds are chosen such that each category includes
the same number of countries.
Figure 2: LSV herding, 3-year data
Source: Authorsโ calculations, 2009.
19. 18
VII. Herding determinants
Which factors cause donors to act similarly? By subtracting debt relief, humanitarian and
food aid from official development assistance, some of them have already been excluded from
our analysis. Others are expected to influence donors in a similar fashion: political transitions that
promote or jeopardise democracy, armed conflicts, income shocks, etc. These are determinants
we can take into account but must leave aside more subtle ones related to strategic behaviour or
informational cascades that are more difficult to identify. This section quantifies the effect of
those observable shocks that create herding.
As argued in Section II, such allocation changes can be regarded positively. Following a
democratic transition, donors may all respond to better governance and more transparent
institutions with increased aid flows to further foster democracy. A more nuanced view would
still caution against herding even in these situations. While it makes no doubt that these constitute
valid reasons to increase aid, donors might still herd and overreact all together. Donors that do
not participate in the aid splurge may fear being left out and missing some future investment or
diplomatic opportunities. They may follow the crowd, increasing aid fragmentation in the country
and inflating aid disbursements above the recipient countryโs absorptive capacity. The border
between legitimate, well planned aid increases (or decreases) and herding is usually difficult to
delimit. This section does not attempt this difficult exercise but provides a first study of herding
determinants.
We also see this estimation as a valuable result in its own right. Beyond the issue of herding
proper, this result sheds a new light on aid allocation to what has been done in the past.
Researchers have always related aid quantities to recipientsโ characteristics (see Alesina and
Dollar 2000, Alesina and Weder 2002, Berthรฉlemy 2006, Berthรฉlemy and Tichit 2004). The
approach taken here is more basic as it considers the proportion of donors increasing aid,
regardless of quantities. Donor decisions can be decomposed in two steps. First, they have to
decide which recipients should receive more aid, and this is what is investigated here. Second,
once where to increase and decrease aid is known, actual quantities are decided upon, and this is
what the aid allocation literature has studied so far.
The dependent variable in the estimations is pit. Because it is a proportion it only takes values
between zero and one. OLS estimation is not well suited for this type of bounded dependent
variable because predicted values cannot be ensured to lie in the unit interval. Papke and
Wooldridge (1996) provide suitable estimators based on quasi-maximum likelihood methods.
20. 19
They propose a method using a generalised linear model with a logit link, the binomial family
and robust standard errors. More specifically, they assume that:
E pit/xit = G(xit ฮฒ)
where G(.) is the logistic function and xit is a vector of explanatory variables. The herding
measures suggest a slightly different approach because the variable of interest is pit-ฯt, and not pit.
To take the benchmark into account, however poses no difficulty. Instead of G being the logistic
function
1
1+exp โก(โxit ฮฒ)
, it is chosen to be G xit ฮฒ =
ฯt
1โฯt
1+
ฯt
1โฯt
exp โก(โxit ฮฒ)
. That is equivalent to changing
the exposure of the dependent variable, or to have an offset ln
ฯt
1โฯt
. The method developed by
Papke and Wooldridge (1996) can readily be applied using this function G.
Results following this estimation technique are complemented by more standard techniques
using OLS with and without country fixed effects. These are not our preferred estimators due to
the dependent variable being a proportion but we provide them as a further robustness check.
Country fixed effects are added to remove any time-invariant unobserved characteristics that
would affect herding (for instance Cuba may not fit our general model; a fixed effect removes its
particular status).
a) Variables
The dependent variable in the estimations is based on the 3-year period herding. Yearly data
maximize the sample size but are very noisy. As argued before, they are based on many small
allocation changes and are unlikely to correspond to donor time horizons, but results using yearly
data are still presented as a robustness check. The 3-year herding measure is calculated for two
samples: one only with donors present from 1960 to 2007, the other with all the donors that do
not exit the market. Both only include recipients present from 1960. The first sample offers the
advantage of a stable group with no entry, but misses some large donors and may fail to capture
some herding. The 3-year measure also allows for some time before a new donor actually enters
the data and so measures are unlikely to be contaminated by periods of portfolio increases. To use
the maximum amount of information we prefer the second measure but we also present results
using the stable set of donors.
Independent variables are constructed from four different categories: economy, politics,
conflict, and natural disasters. Economic variables include GDP growth and GDP per capita,
from the World Development Indicators of the World Bank. Political variables are constructed
21. 20
from the Polity IV Project dataset. We exploit political transitions that result in more democratic
or authoritarian regimes. A dummy variable is defined for each type of transition if it occurs in
any of the three years of the period. Because of the 3-year structure of the data it is unclear that
donors react during the same period. It might be the case when the transition is short and occurs
at the beginning of the period, but not when the transition takes place in the last year of the
period. To avoid missing such effects we create another dummy variable equal to 1 if there was a
transition last period and not in the current period. We also use dummies for โnewโ countries,
that is countries that gained independence6
and for foreign interventions. Because 3-year periods
are used, dummy variables take a value of 1 if the event occurred in any of the three years. GDP
growth and GDP per capita are averages over the three years.
The number of deaths in a country caused by natural disasters is provided by the Emergency
Events Database (EM-DAT). Figures for each year of the period under consideration are added to
proxy for natural disaster intensity during the period. This number is then divided by the average
population size in thousands during the period. The unit of measure is therefore the number of
deaths due to a natural disaster by thousands of people. Aid in this paper does not include
emergency aid but natural disasters are still expected to affect the number of aid increases for
various reasons. First, humanitarian aid is not reported before 1995 in the data, and so enters our
aid variable before that date. Second a natural disaster causes an influx of humanitarian aid and
more long term investments that do not necessarily enter into this category. It also attracts
attention to the affected country and may trigger simultaneous aid flows from many donors.
Armed conflict data comes from the UCDP/PRIO Armed Conflict Dataset, as described in
Gleditsch et al. (2002). The war dummy takes a value of 1 if there was a conflict in any of the
three years of the period.
b) Results
The main empirical question is to estimate the effect of political, natural, and conflict shocks
that cause similar allocation changes by donors. The first set of estimates uses 3-year data and is
presented in Table 4. The first sample used includes all donors present until 2007. Column (1)
uses the GLM estimator. Coefficients reported are marginal effects at the means to make them
comparable with OLS estimates.
6
Countries that have not been present since 1960 are excluded from the data. Some countries gained independence
later but aid flows had been recorded as early as 1960.
22. 21
Table 4: Herding determinants, 3-year data
Standard errors clustered at the country level in parentheses. *
p < 0.10, **
p < 0.05, ***
p < 0.01. GLM estimation is done
using a logit link and a binomial family. In columns (1) and (4) the dependent variable is pit and ฯt is included as an
offset. Estimates are marginal effects estimated at the mean pit. For dummy variables the marginal effect is for discrete
change from 0 to 1. In columns (2), (3), (5) and (6) the dependent variable is pit-ฯt.
GDP per capita is significant but the size of the coefficient is extremely small given that
income is measured in thousands of dollars. A transfer of USD 1000 per capita, arguably a very
large change, reduces pit by 1.1 per cent. The inclusion of GDP per capita is not directly linked to
any shock but rather controls for different treatments towards rich and poor countries. Growth, on
Donors present until 2007 Donors present 1960-2007
(1) (2) (3) (4) (5) (6)
GLM OLS FE GLM OLS FE
Real GDP per capita -0.011***
(0.0023)
-0.011***
(0.0023)
-0.012
(0.0085)
-0.0097***
(0.0020)
-0.0095***
(0.0019)
-0.0099
(0.010)
Real GDP growth -0.0019
(0.0012)
-0.0019
(0.0012)
-0.0011
(0.0014)
-0.0011
(0.0014)
-0.0010
(0.0013)
0.00012
(0.0014)
New polity 0.20***
(0.050)
0.17***
(0.043)
0.15***
(0.048)
0.21***
(0.062)
0.18***
(0.052)
0.17***
(0.058)
Foreign intervention 0.038
(0.065)
0.038
(0.068)
-0.11
(0.10)
0.0024
(0.057)
0.0013
(0.058)
-0.22***
(0.038)
Democratic transition 0.0043
(0.016)
0.0045
(0.016)
-0.00043
(0.018)
0.021
(0.019)
0.021
(0.019)
0.016
(0.021)
Democratic transition, post year 0.011
(0.018)
0.011
(0.018)
0.0044
(0.019)
0.011
(0.021)
0.012
(0.021)
0.0067
(0.024)
Authoritarian transition -0.062***
(0.018)
-0.060***
(0.018)
-0.058***
(0.019)
-0.079***
(0.020)
-0.076***
(0.019)
-0.068***
(0.020)
Authoritarian transition, post year -0.015
(0.019)
-0.015
(0.018)
-0.012
(0.019)
-0.028
(0.022)
-0.027
(0.021)
-0.022
(0.022)
Natural disaster 0.033**
(0.013)
0.027***
(0.0093)
0.022*
(0.011)
0.029**
(0.013)
0.024**
(0.0099)
0.018
(0.012)
Conflict -0.011
(0.0099)
-0.011
(0.0097)
0.0015
(0.014)
-0.0096
(0.012)
-0.0093
(0.012)
0.0073
(0.017)
Conflict, post year 0.0050
(0.015)
0.0049
(0.014)
0.019
(0.016)
0.010
(0.019)
0.0099
(0.018)
0.025
(0.020)
Observations 1377 1377 1377 1376 1376 1376
Adjusted R2
0.045 0.021 0.028 0.017
23. 22
the other hand, is not related to herding. The coefficient has the expected sign but is far from
being significant.
The variable โnew polityโ is very large and significant, implying that โnewโ countries receive
aid from 20 per cent more donors than the average recipient. Political transitions offer interesting
results. Democratic transitions do not trigger simultaneous positive responses from donors neither
during nor afterwards. On the other hand donors do react to authoritarian transitions and reduce
their allocations during transitions. The asymmetry between the two types of transitions is rather
unexpected. We would expect donors to punish transitions towards authoritarianism but to reward
those towards democracy. It is only mildly the case.
Contrary to what Rodrรญguez and Santiso (2008) found for private bank flows, there is no
democratic premium in donor herding behaviour. Donors are not attracted by a democratic
transition, though they shy away from authoritarian transitions. This result is consistent with
previous ones underlined by Easterly and Pfutze (2008) and Knack (2004) that found no evidence
that aid rewards democracy. Kalyvitis and Vlachaki (2008) found an even more disturbing result
and robust evidence that aid flows are negatively associated with the likelihood of observing a
democratic regime in the recipient country.
Natural disasters have a very significant effect. The number of deaths per 1000 persons due to
natural disasters has a standard deviation of 0.46. A one-standard deviation from the mean
increases the proportion of donors allocating more aid by 1.5 per cent. Finally, armed conflicts do
not affect herding. Column (2) replicates the results using OLS. Estimates are surprisingly similar
to those using GLM. Column (3) includes country fixed effects and confirms most results, with
similar magnitudes. Once country time invariant characteristics are controlled for, GDP does not
enter significantly in the regression. The significance levels of the GDP coefficient in column (1)
was due to cross-section regression, and might have captured country fixed characteristics.
Columns (4), (5), and (6) use the same specification but restrict the sample to the fixed set of
donors present from 1960 to 2007. Results are very similar. The negative impact of authoritarian
transitions is even larger than with the first specification. Though we think 3-year data constitutes
a better and less volatile indicator of herding, we now present results using yearly data to check
whether only aggregation drives the findings. Some definitions are slightly changed to
accommodate for the new frequency. The new polity dummy takes a value of 1 during the first
three years of the new regime. This is to allow for a longer time span than the exact year the
polity is created. Similarly, post transition dummies are equal to 1 in the two years following the
last year of a transition, unless there is a transition in that specific year.
24. 23
Results do not depend on the exact time frame.
Table 5: Herding determinants, yearly data
Donors present until 2007 Donors present 1960-2007
(1) (2) (3) (1) (2) (3)
GLM OLS FE GLM OLS FE
Real GDP per capita -0.0051***
(0.00087)
-0.0051***
(0.00087)
-0.0064
(0.0049)
-0.0051***
(0.0010)
-0.0050***
(0.0010)
-0.0077
(0.0057)
Real GDP growth 0.000015
(0.00041)
0.000014
(0.00040)
0.00026
(0.00041)
0.00026
(0.00052)
0.00026
(0.00051)
0.00053
(0.00050)
New polity 0.14***
(0.028)
0.13***
(0.024)
0.13***
(0.024)
0.15***
(0.028)
0.13***
(0.024)
0.14***
(0.024)
Foreign intervention 0.037***
(0.0037)
0.037***
(0.0037)
0.029*
(0.016)
0.052***
(0.013)
0.052***
(0.014)
-0.070***
(0.010)
Democratic transition 0.0040
(0.012)
0.0040
(0.012)
0.0023
(0.012)
0.0078
(0.015)
0.0077
(0.014)
0.0047
(0.015)
Democratic transition, post year 0.0055
(0.012)
0.0054
(0.012)
-0.00010
(0.012)
0.0047
(0.014)
0.0047
(0.014)
-0.0043
(0.014)
Authoritarian transition -0.035***
(0.012)
-0.034***
(0.012)
-0.033***
(0.012)
-0.038***
(0.014)
-0.038***
(0.013)
-0.039***
(0.014)
Authoritarian transition, post year -0.0080
(0.012)
-0.0079
(0.012)
-0.0080
(0.012)
-0.027*
(0.014)
-0.026*
(0.014)
-0.027*
(0.014)
Natural disaster 0.026*
(0.013)
0.024**
(0.012)
0.022*
(0.012)
0.020
(0.012)
0.019*
(0.012)
0.017
(0.013)
Conflict 0.0089*
(0.0051)
0.0088*
(0.0051)
0.013*
(0.0077)
0.014**
(0.0064)
0.013**
(0.0064)
0.017*
(0.0090)
Observations 3784 3784 3784 3784 3784 3784
Adjusted R2
0.032 0.027 0.022 0.020
Standard errors clustered at the country level in parentheses. *
p < 0.10, **
p < 0.05, ***
p < 0.01. GLM estimation is done
using a logit link and a binomial family. In columns (1) and (4) the dependent variable is pit and ฯt is included as an offset.
Estimates are marginal effects estimated at the mean pit. For dummy variables the marginal effect is for discrete change from
0 to 1. In columns (2), (3), (5) and (6) the dependent variable is pit-ฯt.
Source: Authors, 2009.
Table 5 essentially confirms the results from Table 4. Yearly data exhibit the same pattern, except
for a less precisely estimated effect of natural disasters. Both tables show consistent results and
make us confident that they are quite robust.
Having identified herding determinants, we now evaluate to what extent they explain the results
of Sections IV and V.
25. 24
VIII. Corrected herding measure
GLM estimation ensures that predicted values of pit are within the interval [0,1]. That allows
us to compute hypothetical proportions had some events not happened and compute the
โcorrected herding measureโ using the predicted proportions. OLS estimations usually provide
predicted values smaller than 0 or larger than 1 and would make the exercise inconsistent.
Consider a recipient year whose real proportion is pit and is characterised by the vector xit. We
want to find the proportion had the characteristics been zit instead of xit. Using the definition of
the function G, we obtain that :
๐๐๐ก ๐๐๐ =
๐๐๐ก ๐๐๐
exp โ ๐๐๐ โ ๐๐๐ + ๐๐๐ก ๐๐๐ 1 โ exp โ ๐๐๐ โ ๐๐๐ ๐ท
The quantity pit(zit) can be calculated by using the estimate value of beta from the
regressions. pit(zit) is the proportion of donors that would have increased aid to recipient i in year t
had its characteristics been zit instead of xit. The functional form adopted ensures, unlike a linear
specification, that the number obtained can be interpreted as a proportion because it is between 0
and 1.
All the dummy variables are to be successively switched off to zero to see how much they
account for herding. Natural disasters will also be assumed away. Once the new proportions are
obtained, it is only a small step to obtain the corrected herding measures. The only remaining
issue concerns the benchmark to be used for these new measures. The observed benchmark is
affected by recipientsโ characteristics. Changing these necessarily implies that the benchmark
would have been different. To find the new benchmark we convert proportions in number of
positive changes by multiplying them by the number of active donors in the recipient-year. That
implicitly assumes that the number of donors would have been the same under the two sets of
characteristics xit and zit. While this is not necessarily the case, this assumption provides a natural
way to find the new benchmark proportion and should not greatly affect the results. The new
benchmark is then computed using these hypothetical allocation changes and herding measures
are calculated as in Section III.
The sample and estimates using the 3-year period data with donors present until 2007 is
used. Table 6 shows the effect of each variable on the herding measure.
26. 25
Table 6: Effects of each determinant on the 3-year herding measure
Original
measure
New
polity
Foreign
intervention
Democratic
transition
Authoritarian
transition
Natural
disasters
Conflicts
LSV 3.37 3.35 3.35 3.35 3.30 3.26 3.24
h 11.20 10.85 10.87 10.87 10.75 10.66 10.63
Source: Authors, 2009.
Starting from the original herding measure found in Table 3, each column removes the
effect of a variable. For instance, deducting herding caused by new polities reduces h from 9.83
to 9.76. Foreign intervention and democratic transition hardly change this result. Authoritarian
transition and natural disasters have a larger effect. Conflicts also reduce herding but this should
be taken with caution given that the regressions in Table 4 did not show any significant effect of
conflicts. All the identified factors reduce h from 11.20 to 10.63, or LSV from 3.37 to 3.24. It is a
modest fall (5 and 3 per cent respectively) and although some of these factors have been found to
be significantly correlated with herding, they do not explain it well. In the absence of other easily
identifiable factors a tentative conclusion is that the corrected herding levels reveal โirrationalโ
herding due to some unobservable characteristics or strategic donor behaviour.
Two extreme views are available to interpret Table 6. The deviations from the benchmark
must be interpreted as herding and these events only serve as triggers, without any rationale. The
other view is that these events cause โrationalโ deviations from the benchmark. They merely
reflect conditions that cause similar allocation changes. Donors react similarly to natural
disasters, not because they herd but because they all agree natural disasters call for increased aid
flows. The reality is likely to stand between these two extreme views. The former seems too
strong as shocks are highly unlikely to be mere triggers that provoke aid surges for no good
reason. On the other hand the latter may be too optimistic. As Section VI has already argued,
even if donors follow motivations based on hard facts (natural disasters, political transitions, etc.)
it does not prevent them from herding when these events occur. Their response is likely to be
based on a mixture of herding and sound motivations. Exactly which share herding represents
remains a complex question to address.
27. 26
IX. Conclusion
This paper proposes different ways to measure herding in aid allocation. We chose to use two
measures initially developed in finance and adapted them to the specifics of foreign aid. Our
different estimates all reject the hypothesis of no herding.
Its size however varies according to the measure used. Our preferred measure, using 3-year
data and correcting for the bias inherent to the LSV measure, finds a herding level around 11 per
cent. That implies that in a world where 50 per cent of all allocation changes are increases, the
average recipient experiences 61 per cent of its donors changing their allocation in the same
direction. In other words, half of the recipients see 61 per cent of their donors increase their
allocations, and the other half sees 61 per cent decrease their aid allocations. The determinants of
aid allocation, common to many donors, warn us against interpreting this quantity as โpureโ
herding, instead of similar responses to similar factors.
We therefore moved on to estimate herding determinants. Shocks are expected to create
swings in aid allocations and we primarily focused on these. Their influence has been shown to
be relatively limited. It therefore remains that a large share of the measured herding cannot solely
be explained by these shocks. We also see this estimation as a supplementary contribution of the
paper, as previous research on aid allocation has mainly focused on aid quantities but not on
increased generosity from many donors simultaneously. The asymmetry we found between
democratic and authoritarian transitions is a novel result in the literature.
Our strategy for measuring herding in aid allocation is a first step in an otherwise unexplored
field. It is still unclear which measure would best suit our purpose. A structural model would
clearly help but here again such models do not yet exist. The fact that all our indicators point in
the same direction makes us confident that herding is present in aid allocation. Finding that
herding does not seem to occur for observable reasons leads us to believe that some unobserved
motives are driving the results. This is what we would expect if donors did not herd โrationallyโ
and followed what others did in an informational cascade fashion with no clear rationale.
This paper suggests there is still a lot to learn about donor allocation policies. It also shows
that beneficial herding is unlikely to explain herding levels, which might be worrisome in a world
of globalised flows. Aid allocation decisions are not pro or counter-cyclical with respect to many
variables (growth, democratic transitions and wars). It implies that large aid variations are not
28. 27
necessarily due to identifiable factors. Donor coordination would help to prevent such variations
in cases where they stood to be harmful, and perhaps boost them when they were useful.
This study leaves for future research the fundamental question of the motivations for donors
to herd. It also leaves unanswered questions that we plan to investigate in the future. We have not
investigated herding at the sector level. The analysis realised at the country level could be
completed with a focus on sectors (education, infrastructure, water sanitation, etc.) in order to
underline donor herding behaviour at that level and identify the shifting fashions that drive the
aid industry, or, in another words, to identify both donor darling countries and donor darling
sectors. We have not estimated the costs of herding. These could be evaluated in terms of higher
volatility since the costs of volatility have already been estimated. They could also be related to
overcrowding in countries or sectors, and so to inefficiencies due to aid fragmentation.
References
Agรฉnor, P.-R. and J. Aizenman (September 2007). Aid volatility and poverty traps. Working
Paper 13400, National Bureau of Economic Research.
Alesina, A., and D. Dollar (2000). Who Gives Foreign Aid to Whom and Why? Journal of
Economic Growth, 5, 33-63.
Alesina, A., B. Weder (2002). Do Corrupt Governments Receive Less Foreign Aid? The
American Economic Review, 92(4), 1126-1137.
Arellano, C., A. Bulรญล, T. Lane, and L. Lipschitz (2008). The dynamic implication of foreign aid
and its variability. Journal of Development Economics, forthcoming.
Bekaert, G., and C.R. Harvery (2000). Foreign speculators and emerging equity markets. Journal
of Finance, 55, pp. 565-613.
Berthรฉlemy, J-C. (2006). Bilateral Donorsโ Vested Interest vs. Recipientsโs Development
Motives in Aid Allocation: Do All Donors behave the Same? Review of Development Economics,
10(2), 179-194.
Berthรฉlemy. J-C., and A. Tichit (2004). Bilateral Donorsโ Aid Allocation Decisions โ a Three-
Dimensional Panel Analysis. International Review of Economics and Finance, 13, 253-274.
29. 28
Bikhchandani, S., and S. Sharma (2000). Herd Behavior in Financial Markets. IMF Staff Papers
47 (3), 279โ310.
Bulรญล, A. and J. Hamann, (2006). Volatility of development aid: From the frying pan into the
fire?, International Monetary Fund, IMF Working Paper, 06/65.
Cassen, R. (1986). Does Aid Work?: Report to an Intergovernmental Task Force. Oxford, Oxford
University Press.
Collier, P. (2007), The bottom billion. Oxford, Oxford University Press.
Djankov, S., J.G. Montalvo, and M. Reynal-Querol (2008). Aid with Multiple Personalities.
Journal of Comparative Economics, forthcoming.
Easterly, W., and T. Pfutze (Spring 2008). Where does the money go? Best and worst practices in
foreign aid. Journal of Economic Perspectives, Vol. 22 (2), pp. pp. 29-52, See also
http://www.nyu.edu/fas/institute/dri/Easterly/File/Where_Does_Money_Go.pdf
Fielding, D. and G. Mavrotas (2005). The volatility of aid. UNU-WIDER Discussion Paper, 6.
Frey, S., P. Herbst, and A. Walter (2007). Measuring Mutual Fund Herding โ A Structural
Approach, Working Paper.
Frot, E. and J. Santiso (2008). Development aid and portfolio funds: Trends, volatility, and
fragmentation. OECD Development Centre, Working Paper, 275.
Gleditsch, N.P.; P. Wallensteen, M. Eriksson, M. Sollenberg, and H. Strand, 2002. Armed Conflict
1946โ2001: A New Dataset. Journal of Peace Research 39(5), 615โ637.
Grinblatt, M., S. Titman, and R. Wermers (1995). Momentum investment strategies, portfolio
performance, and herding: A study of mutual fund behaviour. The American Economic Review,
85 (5), pp, 1088-1105.
Hirshleifer, D., and S. H. Teoh (2003). Herd Behaviour and Cascading in Capital Markets: A
Review and Synthesis. European Financial Management 9 (1), 25โ66.
30. 29
Kalyvitis, S. and I. Vlachaki (2008). More Aid, Less Democracy? An Empirical Examination of
the Relationship between Foreign Aid and the Democratization of Recipients. Athens University
of Economics and Business (unpublished).
Kharas, H. J. (2008). Measuring the cost of aid volatility. Working Paper, Wolfensohn Center for
Development, The Brookings Institution. See http://www.brookings.edu/experts/kharash.aspx
Kharas, H. J. (November 2007). Trends and issues in development aid. Working Paper,
Wolfensohn Center for Development, The Brookings Institution. See
http://www.brookings.edu/experts/kharash.aspx
Knack, S., and A. Rahman (2007). Donor Fragmentation and Bureaucratic Quality in Aid
Recipients. Journal of Development Economics, 83, 176-197.
Lakonishok, J., A. Shleifer, and R. W. Vishny (1992). The impact of institutional trading on stock
prices. Journal of Financial Economics, 32 (1), pp. 23-43.
Marysse, S., A. Ansoms, and D. Cassimon (2006). The Aid โDarlingsโ and โOrphansโ of the
Great Lakes Region in Africa. Institute of Development Policy and Management, Discussion
Paper, 2006/10.
Mejรญa Acosta, A. and P. de Renzio (2008). Aid, rents and the politics of budget process. IDS
Working Paper, Institute of Development Studies at Sussex University. See
http://www.ids.ac.uk/UserFiles/File/governance_team/people/Andr/AMA-Renzio-aidrents.pdf
Mishra, P., and D. Newhouse (2007). Health Aid and Infant Mortality, IMF Working Paper,
07/100.
OECD (2008). Scaling up: Aid fragmentation, aid allocation and aid predictability. OECD
Development Co-Operation Directorate.
Ornelas, J. R. H. and B. Alemanni (2008). Herding Behaviour by Equity Foreign Investors on
Emerging Markets, Banco Central do Brasil Working Paper, No. 125.
Papke, L.E., and J.M. Wooldridge (1996). Econometric Methods for Fractional Response
Variables with an Application to 401(k) Plan Participation Rates. Journal of Applied
Econometrics, 11(6), 619-632.
31. 30
Reinhardt, G. Y. (2006). Shortcuts and signals: An analysis of the micro-level determinants of aid
allocation, with case study evidence from Brazil. Review of Development Economics, 10 (2), 297-
312.
Reisen, H. and S. Ndoye (2008). Prudent versus imprudent lending to Africa. From debt relief to
emerging lenders. OECD Development Centre, Working Paper, 268.
Riddell, R. (2007). Does foreign aid really work?, Oxford University Press, USA.
Rodrรญguez, J. and J. Santiso (November 2007). Banking on development: private banks and aid
donors in developing countries. OECD Development Centre, Working Paper, 263.
Rodrรญguez, J. and J. Santiso (March 2008). Banking on Democracy: The Political Economy of
International Private Bank Lending in Emerging Markets. International Political Science Review,
29, pp. 215-246.
Roodman, D. (2007). Macro Aid Effectiveness Research: a Guide for the Perplexed, Working
Paper Number 134, Center for Global Development.
Shiller, R. J. (2000). Irrational Exuberance. Princeton University Press.
Tarp, F., Bach, C. F., Hansen, H., & Baunsgaard, S. (1998). Danish aid policy: Theory and
empirical evidence. Discussion Paper, vol. 98/06. Copenhagen: Institute of Economics,
University of Copenhagen.
Tezanos Vรกzquez, S. (2008). The Spanish Pattern of Aid Giving. Instituto Complutense de
Estudios Internacionales, Working Paper 04/08.
Uchida, H. and R. Nakagawa (2007). Herd behavior in the Japanese loan market: Evidence from
bank panel data. Journal of Financial Intermediation 16 (4), pp. 555-583.
Weiner, R.J. (2006). Do Birds of a Feather Flock Together? Speculator Herding in the World Oil
Market. Discussion Paper 06-31, Resources for the Future.
Welch, I. (2000). Herding among security analysts. Journal of Financial Economics, 38, pp. 369-
396. See also http://welch.econ.brown.edu/academics/journalcopy/2000-jfe.pdf
32. 31
Wermers, R. (1999). Mutual fund herding and the impact on stock prices. The Journal of
Finance, 54 (2), pp. 581-622.