Top PDF Poverty traps, aid, and growth

Poverty traps, aid, and growth

Poverty traps, aid, and growth

In this section of the paper we discuss one of the most popular models of poverty traps in which the source of the trap is inadequate saving at low levels of development. In these models, aid which augments domestic saving and finances accumulation can play a role in freeing countries from poverty traps. We first illustrate the basic mechanism using a very simple Solow growth model in which saving increases exogenously with the level of development. We next take seriously the main underlying theoretical mechanism why saving rates might increase with income: the influence of subsistence consumption. We present a Ramsey growth model with subsistence consumption and show that, while it does not have a stable low-level equilibrium like the poverty trap in the Solow model, it can exhibit poverty-trap-like features such as persistent slow growth for very long periods of time. Besides being usually cited as an explanation for poverty traps, the subsistence consumption model is representative of a class of models where multiple equilibria result only from the form of the preferences, and we speculate that the conclusions obtained in this case extend to other models of this class. Finally, we go to the data and ask whether there is any evidence that (a) saving rates exhibit the sort of nonlinear relationship with income required for the existence of a poverty trap, and (b) the historical relationship between aid, saving, and growth is consistent with escapes from poverty traps.
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Aid and growth in Malawi

Aid and growth in Malawi

Our contribution is related to the existing body of literature on aid effectiveness. After the early work of Boone (1996), cross-country studies have used instruments such as population size (Burnside and Dollar, 2000; Rajan and Subramanian, 2008) or bilateral relationships (Bjørnskov, 2013). However, these approaches suffer from possibly direct effects on growth (see Bazzi and Clemens, 2009; Dreher et al., 2013). Temple and Van de Sijpe (2017) studies the consequences of aid for macroeconomic ratios. They find that aid increases consumption and has an impact on investment with a lag. Galiani et al. (2017) uses a convincingly excludable instrument and identifies a sizeable impact of aid on real per capita growth. Studies at a regional level have found mixed evidence of a causal effect of aid on growth. To address causality, Dreher and Lohmann (2015) use an interaction between a country’s crossing of the IDA threshold and a measure of the region’s historical probability of receiving aid (see Nunn and Qian, 2013). Dreher and Lohmann find no effect of aid when using this instrumental variable. Dreher et al. (2016), in contrast, does find a role for aid in causing growth at the regional level of Chinese aid flows when using an interaction with Chinese steel production as instrumental variable. Dreher et al. (forthcoming) find that the effect of short-term political favoritism at a country level reduces the effectiveness of aid. Our estimates of the effect of aid may be lower bounds for the true causal role played by aid.
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Aid, growth and decentralization

Aid, growth and decentralization

The last variable to be discussed in detail is our decentralization index. Several measurement con- cepts are used in the literature [see, e.g., Treisman (2002) and Rodden (2004)]. Decentralization is often viewed as the devolution of authority towards sub-national governments, with total gov- ernment authority over society and economy perceived as fixed. Attempts to define and measure decentralization have focused on fiscal authority (rather than political authority). In our context, we are interested in both issues: Is aid spent on the central or local level? Do central or local gov- ernments decide on aid assignment to particular projects? The first issue can be approximated by using the degree of expenditure decentralization, which relates expenditures of sub-national govern- ments (state + local) to total government expenditures. The IMF Government Finance Statistics provides the underlying data. The degree of expenditure decentralization has often been used in the literature, particularly the literature on growth and decentralization, discussed in section 3. However, the degree of expenditure decentralization is unable to reflect the political dimension of the decision-making process. For this purpose, we refer to decentralization measures provided by Treisman (2002). Since it is very difficult to create measures for political processes, Treisman has created several dummy variables based on the constitutions of countries. A sub-national legislature is said to have ‘residual authority’ if the constitution assigns the exclusive right to legislate on issues that are not specifically assigned to one level of government. Another measure captures the ‘autonomy’ of a sub-national legislature regarding a given question, and whether the constitution reserves exclusive decision-making power on that question. From these two dummy variables, Treisman creates a third variable which captures whether sub-national governments have ‘residual authority and/or autonomy’. We use all three dummy variables to test the impact of political decentralization on the aid-growth nexus. 7
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Aid and Growth Regressions

Aid and Growth Regressions

We compare recent growth studies in which the relationship between aid and growth is modeled as non-linear. On the one side, Burnside and Dollar (1997, 2000) have found evidence of threshold effects by the introduction of an aid-policy interaction term in the growth regressions. In their model, aid contributes positively to growth, but only in good policy environments. On the other side, Hadjimichael et al. (1995), Durbarry et al. (1998), and Lensink and White (1999) have found positive, but decreasing marginal returns to aid flows, by the introduction of aid squared. None of the studies provide mod- els that encompass the other. This is unfortunate. It is important to evaluate contesting regression specifications within a common framework. We therefore formulate such a general model where quadratic aid and policy terms appear alongside the aid-policy in- teraction. It appears that a reduction to the Burnside-Dollar specification is not supported by the data. This is important in view of the widespread attention paid to the Burnside- Dollar results.
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Geopolitics, Aid and Growth

Geopolitics, Aid and Growth

the analysis focusing on US aid only. This comes with two potential problems that might bias against finding a significant interaction: First, overall US aid might be politically motivated to a larger extent than ODA from all donors. It could then be difficult to differentiate between the growth-effects of normal aid and aid given during the recipient‘s time as temporary UNSC member. Second, it might not be possible to detect significant effects when focusing on aid from one donor exclusively as such aid might be insufficiently large to measurably affect growth. Our results are similar to those for all aid, but generally weaker: The interaction terms remain negative in the main regressions, but become significant at the one- percent level only in the BD specification in the Africa sample. Interestingly, however, we find a negative and significant effect at the one and ten-percent level respectively for autocratic countries. This supports the notion that the adverse effects of politically motivated aid are a particular concern in autocratic countries, which might not receive any aid without UNSC membership (see section 3 below).
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Roads out of poverty? assessing the links between aid, public investment, growth, and poverty reduction

Roads out of poverty? assessing the links between aid, public investment, growth, and poverty reduction

The second part of the paper described the application of the model to Ethiopia— a country where the issue of how best to allocate public investment outlays to foster growth and reduce poverty is at the forefront of the policy agenda. After discussing estimation results and calibration issues, various simulations related to the allocation of aid and public investment were presented. The model was also used in “normative” mode to assess by how much nonfood foreign aid should increase in order to cut poverty in half between 2002 and 2015. The results showed that the required increase in foreign assistance could be sizable if the elasticity of poverty with respect to growth is small, despite the positive externalities generated by aid. Moreover, whether absorption constraints may prevent large increases in aid from being effective is an open question. 18 Thus, one should be cautious in interpreting our results regarding the feasibility of a “big push”, given current institutional constraints in Ethiopia. Nevertheless, our results are consistent with other recent studies (such as Nkusu (2004)), which emphasize the fact that in assessing the scope for Dutch disease effects associated with foreign aid, the possibility of a rapid supply response should not be discarded on a dogmatic basis. In addition, our analysis draws attention to the fact that, under a flexible exchange rate regime, substitution effects between aid and debt-creating capital flows may have a large impact on the behavior of the nominal exchange rate and thus on the magnitude of the real appreciation associated with increases in foreign assistance.
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Poverty traps and growth in a model of endogenous time preference

Poverty traps and growth in a model of endogenous time preference

The traditional theories of development predict that as an economy embarks on growth path the size of its backward sector is going to decline. However experiences in Latin American, African and some Asian countries have shown that the presence of the backward sector has been very persistent. The neo-classical growth model predicts improvement in welfare as the economy accumulates more capital. Those models assume exogenous time preference and hence the possibility of poverty traps completely escape their purview. We have provided an alternative motivation behind an economy getting trapped at a low-level equilibrium.
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Aid, policies, and growth

Aid, policies, and growth

We draw on the recent empirical growth literature to develop a model with a range of institutional and policy distortions, and we estimate this equation in a panel with 56 countries and [r]

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Aid Allocation and Fragile States

Aid Allocation and Fragile States

of aid via non-government channels, such as NGOs, the private sector or independent service authorities. The levels at which aid becomes counterproductive in fragile states also needs to be clarified. Third, we need to learn much more about which aid modalities work well in fragile states and about the optimal sequencing of interventions. There is some evidence that ring-fenced, long-term investments in human capital and working with civil society and the private sector has potential to increasing absorptive capacity even prior to government-wide reform. After reform efforts take off, fast and flexible technical assistance might be key, laying the basis for more substantial funds for capital investment and service delivery once institutions have been strengthened and governance improved. This has in part been the experience aid to post-conflict countries, which has been shown to work particularly well if appropriate governance and institutional settings are in place. Fourth, further consideration of the different variables that can make aid more or less effective in generating growth and poverty reduction is warranted. The current dominant paradigm does not sufficiently take factors other than policy and institutional quality into account. Yet research suggests that a number of additional variables, such as structural vulnerability and political stability, are important in converting aid into growth and poverty reduction. Taking into account these other factors might ensure that more aid is allocated to poorer countries, without compromising the poverty-reducing efficiency of these flows. It should also be recognised that growth is not the only benefit of aid. Prevention of instability and conflict, improvements in human rights, avoiding deterioration of human development indicators and preventing spillovers on neighbouring countries are other benefits. We need to learn more about the impact of aid on these factors. If we accept them as legitimate objectives of development aid, we need to make further adjustments to the paradigm.
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Aid, agriculture and poverty in developing countries

Aid, agriculture and poverty in developing countries

throughout the early 1990s on area expansion rather than the dramatic yield increases seen ephemerally in Mashonaland (northern, eastern and central Zimbabwe), north-central Malawi, and the South African homelands. But under the impetus of effective extension, yields did build up also in the late nineties, most spectacularly in Ugandan cassava, a classic drought-resistant ‘protectional’ crop, whose yields have doubled since 1996; but in Ethiopia also, foodcrop production grew, according to FAOSTAT data, by 69% between 1994 and 2003 14 . The sustainability of these successes, in poverty and conflict reduction as well as in agricultural growth, then bred a virtuous circle – including the reward of debt cancellation by donors under HIPC - and this helped to avert the ‘fiscal turning-point’ which brought down Malawi, Zimbabwe, and also, outside our sample, Kenya and even South Africa 15 . In Malawi, the risks facing peasant farmers were further increased by the dissolution of the state-financed ADMARC (Agricultural Development and Marketing Corporation) system which, for all its faults, had offered them a measure of protection against risks associated with the input supply chain (Harrigan 1995, Kydd and Dorward 2002) and in Zimbabwe, by the
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Social Network Capital, Economic Mobility and Poverty Traps

Social Network Capital, Economic Mobility and Poverty Traps

In this setting, analogous to other poverty traps models, some initially poor households will be caught in a low-level equilibrium because they lack access, through either endowments, market or social mechanisms, to the productive assets needed in order for the most productive technology available to be the households’ optimal choice, albeit perhaps after a period of initial investment. Initially poor households without such access must resort to autarkic savings if they are to finance adoption of the improved technology. Some find such investment attractive and thereby climb out of poverty of their own accord. Others find the necessary sacrifice excessive and optimally choose to remain relatively unproductive and thus poor. A third subpopulation might find bootstrapping themselves out of poverty unattractive, but will make the necessary investment if they receive some help from others, i.e., social network capital becomes necessary for an escape from persistent poverty. A fourth subpopulation is able and willing to make the necessary investment autarkically, but will find it more attractive to invest in social relations that offer a lower cost pathway to higher productivity. The initially poor are thus quite a heterogeneous lot, some enjoying independent growth prospects, others with socially-mediated growth prospects, with social relations either complementing or substituting for own capital in economic mobility, while still others have no real growth prospects at all.
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Innovation, Technology Diffusion and Poverty Traps: The Role of Valuable Skills

Innovation, Technology Diffusion and Poverty Traps: The Role of Valuable Skills

equipment to real GDP ($US). We use the NBER-UN world trade dataset (see Feenstra et al. 2005, for details). Print media includes books, pamphlets, maps, newspapers, journals and periodicals. IT equipment consists of typesetting & founding machinery, printing machinery, bookbinding machinery, typewriters, word-processing machines, calculating machines, photocopying apparatus, office machines, data processing machines and equipment, and storage units for data processing. In terms of SITC Rev. 2 (4-digit) codes in Feenstra et al. (2005), we used classes 7263-7269; 7511-7529, and 8921-8922. Note, Botswana was merged with South Africa and 2000 figures and imports for India were missing. We re-distributed South Africa values on the basis of population and extrapolated the 2000 figures for India based on growth trends between 1997 and 1999. Summary of exp(T_ICT): Min= 0.00002; Max=0.29, and Mean=0.008.
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Wage traps as a cause of illiteracy, child labor, and extreme poverty

Wage traps as a cause of illiteracy, child labor, and extreme poverty

Foreign aid. Standard measures of development aid in terms of grants or long- term loans at favorable interest rates, earmarked for investment in infrastructure, technology, education or private investment subsidies, would mainly target the labor demand curve. Effects from such measures may take a long time to materialize. Also, help needs to be substantial in order to push the economy out of the wage- trap region, similar to big-push proposals advanced in the context of conventional poverty traps such as those that derive from inadequate savings rates at low income levels. And, as already mentioned in Section 2, effects may be rather small in the very region where the low labor-income equilibrium is positioned, since the productivity of child labor may not respond very strongly to capital accumulation and the influx of established technology from the global economy. Other help, in kind or in money, that covers at least part of the subsistence gap in labor income, may improve the situation for families and their children during the time needed to move out of the wage trap, and in fact, may speed things up by making aid conditional on children returning to schools.
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Fate, fear or fight : aspirations and educational poverty traps across generations

Fate, fear or fight : aspirations and educational poverty traps across generations

Source: Years except 2011 and 2015: Annual Statistical Report of National Economy and Social Development from the National Bureau of Statistics of China (国民经济和 社会发展统计公报 ). 2011 and 2015: The report and news on the web of State Council Leading Group Office of Poverty Alleviation and Development (CPAD). The government’s poverty alleviation programmes have not been entirely successful at the micro-level. According to the National Bureau of Statistics by the end of 2014, there are 70.17 million people lived in chronic and extreme poverty concentrating in 14 “clustered ultra-poor areas” listed by the State Council: that is, these people remain poor for all of their lives with daily livelihood below 2,300 yuan per capita annual income at the 2010 price level (equivalent to US$0.98 per person per day) and their children are likely to inherit their poverty as well. Despite income growth at the county level in the mid to late 1990s (Meng, 2013), poverty has haunted persistently individuals in “nationally designated poor counties” (Park and Wang, 2010). In the recent panel survey (2010-2014) supported by the State Council in 5 provinces hosting most of the listed “clustered ultra-poor areas”, the income poverty rate was 63% based on the US$1.25-a-day line was in 2010 (You et al., 2015c), which was equivalent to Tanzania (68%), and remained as high as 48% in 2014.
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Poverty alleviation in Africa: The Impact of China’s Aid

Poverty alleviation in Africa: The Impact of China’s Aid

Another factor which has been crucially important for China’s recent development is investment in infrastructure, from both domestic and international resources. Throughout the country, unreliable, inefficient and poorly maintained infrastructure – especially for transport, energy, water and sanitation and irrigation - was a major bottleneck. Over the last 30 years, there has been substantial support for infrastructure in rural areas, for example for irrigation systems, agricultural market development and processing techniques. This has made it possible to improve agricultural production despite extremely scarce arable land per capita. Railways, roads and other transport infrastructure has also been rapidly developed, which has made a substantial contribution to reaping the comparative advantage from crossing domestic regions and facilitated entry into global markets. The pertinence of the expression “if you want to be rich, first build a road” has been demonstrated numerous times across all parts of China. The key experience of China’s infrastructure development is not just the investment, but the policies that enabled fruitful use of resources and the capacity to maintain them. Policies were developed so as to promote economic growth and poverty reduction within a well-defined institutional and financial framework. This included decentralized financial investments and revenue redistribution. It also included a division of responsibilities between the central and local authorities, between the state and private markets and between public and private actors, all of which was based on a cross-regional approach. Many countries in sub-Saharan Africa suffer from a huge backlog of needed infrastructure. In sub-Saharan Africa, annual infrastructure needs have been costed at USD 17-22 billion while annual spending (domestic and foreign, public and private) is about USD 10 billion. The region’s infrastructure financing gap is thus USD 7-12 billion per year, or an estimated 4.7% of GDP. China is helping to fill this financing gap and is now the largest external source of infrastructure projects in Africa.
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Using Asset Poverty Measures to Understand Poverty Dynamics, Poverty Traps and Farmer Behavior in Sub-Saharan Africa: A Focus on Rural Ethiopia

Using Asset Poverty Measures to Understand Poverty Dynamics, Poverty Traps and Farmer Behavior in Sub-Saharan Africa: A Focus on Rural Ethiopia

This chapter uses panel data from rural Ethiopia and appropriate econometric techniques to estimate the relationship between assets and consumption expenditure and consequently generate an asset index. It then computes static and dynamic asset poverty-lines that can be used to classify households by both their current expenditures and their capacity to independently maintain or raise expenditures, based on their assets. This analysis also uses the asset index generated to further test empirically for the existence of an asset threshold (Micawber threshold) around which household accumulation trajectories split, thus indicating the existence of multiple equilibria of asset bundles and possibly a poverty trap(Carter and Barrett, 2006). Based on their initial asset base and asset dynamics, the Micawber threshold permits a distinction between deep-rooted, persistent structural poverty and transitory poverty that passes naturally with time due to systemic growth processes. The threshold makes it possible to identify those households who will most likely never get out of poverty(or to a higher possible equilibrium) without external assistance (and are thus in a poverty trap), those who are vulnerable (these could be poor or non-poor given their current asset stock) and headed downwards towards a poverty trap ( or lower level
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Social Network Capital, Economic Mobility and Poverty Traps

Social Network Capital, Economic Mobility and Poverty Traps

The persistent poverty widely observed in developing countries has motivated much research on poverty traps into which households may fall and from which they have difficulty escaping. The fundamental feature of most poverty trap models centers on the existence of financial market imperfections that impede investment in productive assets or technology, and thus prevent households with poor initial endowments from reaching higher-level equilibria in systems characterized by multiple equilibria. 1 Meanwhile, a parallel literature emphasizes multiple pathways through which social network capital might facilitate productivity growth, technology adoption and access to (informal) finance. 2 However, various studies also document the existence of exclusionary mechanism that can effectively prevent some poor from utilizing social networks to promote growth. 3 Advances in understanding the nature and limits of social network capital formation could offer insights into whether and how poor households might avoid or escape poverty traps. There have been some notable recent efforts to make these links explicit. 4
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Is aid contributing to poverty reduction? An analysis of the poverty-efficiency of Norwegian aid

Is aid contributing to poverty reduction? An analysis of the poverty-efficiency of Norwegian aid

Openness to trade is a matter that to a certain degree can be decided by the government of a country. Empirical evidence suggests that openness is positively related to economic growth (Dollar & Kraay, 2004). The Sachs Warner Index has not been updated since the early 2000s when Wacziarg & Welch made some adjustments to the openness measure (Wacziarg & Welch, 2008). For most countries the status is likely to be the same today as ten years ago, as from 1995 to 2003 only ten to twenty countries changed status from closed to open or the reverse. I still prefer to use a different measure of openness as these data are a bit old. The most widely used in the literature besides Sachs-Warner is the rate of exports plus imports to GDP. I here apply a dummy variable which takes the value 0 if the share of trade to GDP is lower than 40 percent and 1 otherwise. One possible drawback with using this measure is that large countries will tend to have a lower “natural” level of openness, whereas small countries would be deemed more open simply as a result of their dependence on trade. This is not necessarily related to the countries’ policies toward openness. For many developing countries the trade policies of others will be just as important for their trade volumes as their own policies. This measure is however the most easily available, and also widely used in the literature.
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Spatial poverty traps?

Spatial poverty traps?

poverty traps, using a micro model of consumption They estimate the model using farm-household panel growth incorporating geographic externalities, whereby data from post-reform [r]

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Assets, Shocks, and Poverty Traps in Rural Mozambique

Assets, Shocks, and Poverty Traps in Rural Mozambique

osyncratic shocks. The estimation of equation (4) assesses the impact of drought in more detail, with OLS estimates displayed in Table 6. At first glance, drought has a counterintuitive effect on asset growth (Column 2): d by the 2004–2005 drought (DROUGHT) experience a ts the finding of a single equilibrium towards which all households converge. The second polynomial term of baseline assets (ASSETS02^2) is individually significant and the null hy- pothesis that higher order polynomials are jointly zero is strongly rejected (with an F-statistic of 15.24). Therefore, polynomial terms are useful for adjusting the regression fit to nonlinearities in the data. Surprisingly, of all the community infrastructure measures included in the regression, only the presence of an electricity tower in the community (ELECTR) has a significant positive effect on asset growth. There is no evidence for life cycle effects in asset growth, with AGE- HEAD and its square term being both individually and jointly statistically insignificant. Male- headed households and larger households have significantly higher asset growth, as have households using improved agricultural techniques (IRRIG) and growing improved varieties of crops (NEWCROPINDEX). This again supports the evidence for the strong impact of education. To conclude, there is no evidence for a poverty trap that discriminates against house- holds based on their initial asset endowments. This finding contrasts with most other em- pirical studies on sub-Saharan Africa that do find poverty traps, as has been pointed out in Section 2. Still, better-educated households and households employing more sophisticated agricultural strategies that involve more risk and investment but also higher potential re-
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