1,356,682 research outputs found
How Do the BRICs Stack Up? Adding Brazil, Russia,India, and China to the Environment Component of the Commitment to Development Index
No full textThe 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)
Julia as a universal platform for statistical software development
No full textThe 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
Through the Looking-Glass, and What OLS Found There: On Growth, Foreign Aid, and Reverse Causality
No full textThe 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
A Test of a Model of Sexual Victimization: A Latent Variable Path Analysis
No full textBoth a recent narrative review and a meta-analytic review of prevalence rates, indicates that prior sexual victimization increases risk for future victimization (Messman & Long, 1996, Roodman & Clum, in press). The purpose of this study was to examine two competing models of sexual victimization that examined the path between child abuse and later sexual victimization. Hypothesized mediating variables were negative cognitive schemas, dissociation, risky behaviors, and coping strategies. Structural equation modeling was used to examine two competing models of sexual victimization. A sample of 276 college students taking introductory psychology were participants. They anonymously completed a packet of questionnaires that provided the indicator variables for the path models that were tested.
Both models tested received minimal support but many of the proposed pathways in the model were not statistically significant suggesting problems with the models. Due to measurement issues with the manifest indicators of the latent factors, any results should be viewed with caution. It appears as though none of the factors in the model mediate the relationship between early and later victimization. However, both models tested demonstrated significant pathways between the factor for child abuse (comprising physical and sexual abuse) and negative cognitive schemas and for child abuse and dissociation. However, the paths from negative cognitive schemas and dissociation to sexual victimization (comprising both adolescent and adult sexual victimization) were not significant suggesting that, although these factors are influenced by child abuse, they do not mediate revictimization. Risky behaviors, as measured by consensual sex and alcohol consumption, do not appear to be influenced by early abuse, but there was a significant pathway between this factor and sexual victimization suggesting that these risky behaviors are independent risk factors for sexual victimization in adolescence and adulthood. In one model there was a significant pathway between child abuse and sexual victimization which is what would be expected given previous findings that suggest past abuse is the best predictor of future victimization experiences (Roodman & Clum, in press). That the other model did not demonstrate this relationship was surprising.Ph. D
Response to Roodman and Morduch’s ‘The impact of microcredit on the poor in Bangladesh: Revisiting the evidence
No full textAbstract: 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
Replicating Replication : Due Diligence in Roodman and Morduch’s Replication of Pitt and Khandker (1998)
No full text"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
An Index of Donor Performance
No full textThe 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
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Estimation of multiprocess survival models with cmp
No full textMultilevel 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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