1,345 research outputs found

    Roodman David Malin — Television continous to spread

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    Houdaille Jacques. Roodman David Malin — Television continous to spread. In: Population, 51ᵉ année, n°2, 1996. p. 506

    How Do the BRICs Stack Up? Adding Brazil, Russia,India, and China to the Environment Component of the Commitment to Development Index

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    The Commitment to Development Index (CDI) ranks 21 of the world’s richest countries on their dedication to policies that benefit the five billion people living in poorer nations. Moving beyond simple comparisons of foreign aid, the CDI ranks countries on seven themes: quantity and quality of foreign aid, openness to developing-country exports, policies that influence investment, migration policies, stewardship of the global environment, security policies and support for creation and dissemination of new technologies. This year for the first time, CGD research fellow David Roodman extended the environment component of the Index to cover four of the biggest developing countries: Brazil, Russia, India and China, a group Goldman Sachs dubbed the “BRICs.” This working paper explores the indicators that make up the environment component (global climate, sustainable fisheries, and biodiversity and global ecosystems) and explains how the BRIC countries stack up to their right-country counterparts. He finds that the BRICs score remarkably well compared to the 21 rich countries covered by the Index: when thrown in with the usual 21, they rank second, fourth, fifth, and eleventh. They generally perform well on the greenhouse gas emissions, consumption of ozone-depleting substances, and tropical timber imports. And the BRICs have joined important international environmental accords. As a group, their major weakness is low gas taxes. In addition, Amazon deforestation and heavy fossil fuel use pull Brazil and Russia, respectively, below the CDI 21 average on greenhouse emissions per capita. China’s abstention from the U.N. fisheries agreement puts it a half point below the other BRICs.environment, Commitment to Development Index (CDI)

    Replication Data for: Long-term Effects of India’s Childhood Immunization Program on Earnings and Consumption Expenditure: Comment

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    Data and code needed to produce all new results reported in the comment. Data set construction occurs in SQL Server, but that software is not needed to run the replication code

    An Index of Donor Performance

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    The Commitment to Development Index of the Center for Global Development rates 21 rich countries on the “development-friendliness” of their policies. It is revised and updated annually. In the 2004 edition, the component on foreign assistance combines quantitative and qualitative measures of official aid, and of fiscal policies that support private charitable giving. The quantitative measure uses a net transfers con- cept, as distinct from the net flows concept in the net Official Development Assistance measure of the Development Assistance Committee, which does not net out interest received. The qualitative factors are three: a penalty for tying aid; a discounting system that favors aid to poorer, better-governed recipients; and a penalty for “project proliferation.” The selectivity weighting approach avoids some conceptual problems inherent in the Dollar and Levin (2004) elasticity- based method. The proliferation pen-alty derives from a calibrated model of aid transaction cost developed in Roodman (forthcoming). The charitable giving measure is based on an estimate of the share of observed private giving to developing countries that is attributable to a) lower overall taxes (income effect) and b) specific tax incentives for giving (price effect). Despite the adjustments, overall results are dominated by differences in quantity of official aid given. This is because while there is a seven-fold range in net concessional transfers/GDP among the score countries, variation in overall aid quality across donors appears far lower, and private giving is generally small. Denmark, the Netherlands, Norway, and Sweden score highest while the largest donors in absolute terms, the United States and Japan, score in the bottom third. Standings by the 2004 methodology have been relatively stable since 1995.foreign aid, selectivity, performance measurement

    Response to Roodman and Morduch’s ‘The impact of microcredit on the poor in Bangladesh: Revisiting the evidence

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    Abstract: This response to Roodman and Morduch seeks to correct the substantial damage that their claims have caused to the reputation of microfinance as a means of alleviating poverty by providing a detailed explanation of why their replication of Pitt and Khandker (1998) is incorrect. Using the dataset constructed by Pitt and Khandker, as well as the data set Roodman and Morduch constructed themselves, the Pitt and Khandker results standup extremely well, indeed are strengthened, when estimated with Roodman’s cmp program, after correcting for the Roodman and Morduch errors. Recently, David Roodman and Jonathan Morduch [2009] (henceforth RM) have written

    Through the Looking-Glass, and What OLS Found There: On Growth, Foreign Aid, and Reverse Causality

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    The cross-country literature on foreign aid effectiveness has relied on the use of instruments to distinguish causality from mere correlation. This paper uses simple non-instrumental techniques in the spirit of Granger to demonstrate that the main aid-growth connection is a negative causal relationship from growth to aid—-aid, that is, as a fraction of recipient GDP. Coarsely, when GDP goes up, aid/GDP goes down. The endogeneity of aid, long suspected, is real. Less understood is that adding certain common controls to regressions puts this relationship through the looking glass, flipping both its sign and apparent direction: aid seems to cause growth. Ideally, instrumentation expunges the endogeneity shown here. In practice, estimates of aid’s impact have run into problems. Autocorrelation in the errors is widespread, and can render endogenous lagged variables used as regressors or instruments. The pitfalls of “difference” and “system” include invalidity and proliferation of instruments. Multicollinearity in term pairs of interest, such as aid and aid2 or “project” and “program” aid, can amplify endogeneity bias. The combination of specification problems and widespread fragility (shown in earlier work) leads to pessimism about the ability of cross-country econometrics to demonstrate aid effectiveness. This does not rule an average positive effect, nor does it contradict the fact that aid has saved millions of lives, but it does suggest that the average effect on economic growth is too small to be detected statistically.foreign aid, economic growth

    Julia as a universal platform for statistical software development

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    The julia package integrates the Julia programming language into Stata. Users can transfer data between Stata and Julia, issue Julia commands to analyze and plot, and pass results back to Stata. Julia's econometric ecosystem is not as mature as Stata's or R's or Python's. But Julia is an excellent environment for developing high-performance numerical applications, which can then be called from many platforms. For example, the boottest program for wild bootstrap-based inference (Roodman et al. 2019) and fwildclusterboot for R (Fischer and Roodman 2021) can both call the same Julia back end. And the program reghdfejl mimics reghdfe (Correia 2016) in fitting linear models with high-dimensional fixed effects but calls a Julia package for tenfold acceleration on hard problems. reghdfejl also supports nonlinear fixed-effect models that cannot otherwise be fit in Stata--though preliminarily, as the Julia package for that purpose is immature

    Replicating Replication : Due Diligence in Roodman and Morduch’s Replication of Pitt and Khandker (1998)

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    "The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence," by David Roodman and Jonathan Morduch (2011) is the most recent of a sequence of papers and postings that seeks to refute the findings of the Pitt and Khandker (1998) article "The Impact of Group-Based Credit on Poor Households in Bangladesh: Does the Gender of Participants Matter?" that microcredit for women had significant, favorable effects on poverty reduction. In this paper the authors show that these latest Roodman and Morduch claims are based on seriously flawed econometric methods and theory and a lack of due diligence in formulating models and interpreting output from packaged software. On the basis of Roodman and Morduch's preferred two-stage least squares regression, an alternative calculation of the standard errors would lead one to conclude that the problem with Pitt and Khandker is that they underestimate the positive and statistically significant effect of women's credit on household consumption. As in their previous efforts, the methods of Roodman and Morduch are shown to bias the findings in the direction of rejecting the results of Pitt and Khandker. We also further examine two aspects of our instrumental variable approach that have been attacked by Roodman and Morduch. The first is the validity of the exclusion restrictions underlying the use of interactions between program choice and the set of exogenous variables (including the village fixed effects) as instruments. The second is the application of the "one-half acre" program eligibility rule. The authors show that identification does not require both of these, and present new results dropping each assumption in turn. The results originally reported in the Pitt and Khandker paper hold up extremely well in this new analysis

    Replication data for: New Data, New Doubts: Revisiting "Aid, Policies, and Growth"

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    CGD working paper 26, New Data, New Doubts: Revisiting "Aid, Policies, and Growth, by CGD non-resident fellow William Easterly, research fellow David Roodman, and Ross Levine (also published as "Aid, Policies, and Growth: Comment" in the American Economic Review, June 2004), concludes that the Burnside and Dollar (2000) finding that aid raises growth in a good policy environment is not statistically robust. This dataset is a four-year panel covering 1966–97. It includes all the Burnside and Dollar data, and Easterly, Levine and Roodman's expanded data set. The data used in this Working Paper is available in Excel format and Stata 7 format. A .do command file generates all the results in the paper in Stata 7 format. All are included in the zip file

    Estimation of multiprocess survival models with cmp

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    Multilevel multiprocess hazard models are routinely used by demographers to control for endogeneity and selection effects. These models consist of multilevel proportional hazards equations, and possibly probit equations, with correlated random effects. Although Stata currently lacks a specialized command for fitting systems of multilevel proportional hazards models, systems of seemingly unrelated lognormal survival models can be fit with the user-written cmp command (Roodman 2011, Stata Journal 11: 159–206). In this article, we describe multiprocess survival models and demonstrate theoretical and practical aspects of estimation. We also illustrate the application of the cmp command using examples related to demographic research. The examples use a dataset shipped with the statistical software aML
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