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This paper proposes different methods to aggregate heterogeneous policies for renewable energy. We compare time-varying indicators built using principal component analysis with average-based indicators. The main goal of the paper is to account for the evolution of both types of policy indicators with a set of common variables. Our empirical results are consistent with predictions of political-economy models of environmental policies as lobbying, income and, to a less extent, inequality have expected effects on policy. The brown lobbying power, proxied by entry barriers in the energy sector, has negative influence on the policy indicators even when taking into account endogeneity in its effect. The results are also robust to dynamic panel specifications and to the exclusion of groups of countries. Interestingly, too, corruption has only an indirect effect on policy mediated by entry barriers, while the negative effect of inequality is much stronger for the richer countries.

This paper examines the consequences of data error in data series used to construct aggregate indicators. Using the most popular indicator of country level economic development, the Human Development Index (HDI), we identify three separate sources of data error. We propose a simple statistical framework to investigate how data error may bias rank assignments and identify two striking consequences for the HDI. First, using the cutoff values used by the United Nations to assign a country as 'low', 'medium', or 'high' developed, we find that currently up to 45% of developing countries are misclassified. Moreover, by replicating prior development/macroeconomic studies, we find that key estimated parameters such as Gini coefficients and speed of convergence measures vary by up to 100% due to data error. -- Measurement error ; international comparative statistics

This paper proposes different methods to aggregate heterogeneous policies for renewable energy. Wecompare time-varying indicators built using principal component analysis with average-based indicators. The main goal of the paper is to account for the evolution of both types of policy indicators with a set of common variables. Our empirical results are consistent with predictions of politicaleconomy models of environmental policies as lobbying, income and, to a less extent, inequality have expected effects on policy. The brown lobbying power, proxied by entry barriers in the energy sector, has negative influence on the policy indicators even when taking into account endogeneity in its effect. The results are also robust to dynamic panel specifications and to the exclusion of groups of countries. Interestingly, too, corruption has only an indirect effect on policy mediated by entry barriers, while the negative effect of inequality is much stronger for the richer countries.

This paper proposes different methods to aggregate heterogeneous policies for renewable energy. Wecompare time-varying indicators built using principal component analysis with average-based indicators. The main goal of the paper is to account for the evolution of both types of policy indicators with a set of common variables. Our empirical results are consistent with predictions of politicaleconomy models of environmental policies as lobbying, income and, to a less extent, inequality have expected effects on policy. The brown lobbying power, proxied by entry barriers in the energy sector, has negative influence on the policy indicators even when taking into account endogeneity in its effect. The results are also robust to dynamic panel specifications and to the exclusion of groups of countries. Interestingly, too, corruption has only an indirect effect on policy mediated by entry barriers, while the negative effect of inequality is much stronger for the richer countries.

Objective: In the first six months of the pandemic, information on race and ethnic­ity was missing for half of the US COVID-19 cases. Combining case ascertainment with census-based zip code indicators may iden­tify COVID-19 race-ethnicity disparities in the absence of individual-level data.Design: Ecological retrospective study for the period March-July 2020.Setting: Population-based investigation, Al­legheny County, Pennsylvania.Participants: All COVID-19 cases, adjusted for zip code area population, in the early period of the pandemic.Main Outcome Measures: Monthly COVID-19 incidence and requests for hu­man services by zip code level indicators of race-ethnicity and poverty.Results: In the early period of the pan­demic, COVID-19 incidence was higher in zip codes with a greater proportion of racial and ethnic minorities. Zip codes with the highest quartile of minority residents (>25.1% of population) had a COVID-19 incidence of 60.1 (95% CI: 51.7-68.5) per 10,000 in this period; zip codes with the lowest quartile of minority residents (<6.3%) had an incidence of 31.3 (95% CI: 14.4-48.2). Requests for human services during this period (volume of 211 calls and county services) confirm these disparities.Conclusion: Use of census-defined race-ethnicity proportions by zip code offers a way to identify disparities when individual race-ethnicity data are unavailable.Ethn Dis. 2021;31(3):399-406; doi:10.18865/ed.31.3.399

Progress in measuring governance is assessed using a simple framework that distinguishes between indicators that measure formal rules and indicators that measure the practical application or outcomes of these rules. The analysis calls attention to the strengths and weaknesses of both types of indicators as well as the complementarities between them. It distinguishes between the views of experts and the results of surveys and assesses the merits of aggregate as opposed to individual governance indicators. Some simple principles are identified to guide the use and refinement of existing governance indicators and the development of future indicators. These include transparently disclosing and accounting for the margins of error in all indicators, drawing from a diversity of indicators and exploiting complementarities among them, submitting all indicators to rigorous public and academic scrutiny, and being realistic in expectations of future indicators.

Empirical evidence linking monetary aggregates to variables such as inflation and economic growth has weakened over the past two decades. In this study we re‐examine these relationships by creating composite monetary aggregates that switch among existing monetary aggregates, using quarterly data over the sample 1971–99. Overall, composite monetary aggregates appear to be useful in explaining or forecasting short‐run movements in GDP growth and inflation. Also, the most successful composite monetary aggregates produce switch dates that overlap with the introduction of financial innovations. These subsequently prompted the Bank of Canada to revise or introduce new monetary aggregates. JEL Classification: E51, E52, C52, C53 Les agrégats monétaires en tant qu'indicateurs de l'activitééconomique: résultats empiriques. Les résultats empiriques jaugeant les liens entre les agrégats monétaires et des variables telles que l'inflation et la croissance économique montrent que ces liens se sont affaiblis au cours des deux dernières décennies. Ce mémoire examine ces relations en créant des agrégats monétaires composites qui se déplacent entre les agrégats usuels selon certains critères statistiques. L'étude utilise des données trimestrielles pour la période 1971–99. Dans l'ensemble, les agrégats monétaires composites semblent plus utiles pour expliquer ou prévoir les mouvements à court terme dans le niveau de croissance du PIB et de l'inflation. De plus, les agrégats monétaires composites qui ont le plus de succès suggèrent des moments de déplacement qui correspondent à des discontinuités marquant la mise en place d'innovations financières. Celles‐ci ont entraîné la Banque du Canada à reviser les agrégats monétaires usuels ou à en suggérer de nouveaux.

USING TIME SERIES DATA FROM 15 POST-WORLD WAR II CONGRESSIONAL ELECTIONS, A NINE-EQUATION SOCIAL INDICATORS MODEL OF AGGREGATE AMERICAN POLITICAL BEHAVIOR IS ESTIMATED. FINDINGS INDICATE THAT RELATIVELY SHORT-TERM SOCIAL AND POLITICAL CONDITIONS EXERT GREATER EFFECTS ON ELECTION OUTCOMES THAN DO LONG-TERM PARTISAN ALIGNMENTS.