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"es": "Venezuela", "fr": "Venezuela", "pt_BR": "Venezuela"}, "uri": "https://sws.geonames.org/3625428"}], "groups": [], "relationships_as_subject": [], "relationships_as_object": [], "doi": "10.60966/6x55ayx4", "doi_status": true, "domain": "https://data.iadb.org", "doi_date_published": "2025-11-07", "doi_publisher": "IADB", "data_collection_type": [{"uri": "https://taxonomy.iadb.org/knowledgeProductsTaxonomy/afaa6857-390d-423a-820a-e25d836282d5", "labels": {"en": "Administrative Data", "es": "Datos Administrativos", "fr": "Donn\u00e9es administratives", "pt_BR": "Dados Administrativos"}}], "keyword": {"en": ["public payrolls", "public pay", "public employment", "turnover", "gender pay gaps"], "es": ["n\u00f3minas p\u00fablicas", "remuneraci\u00f3n p\u00fablica", "empleo p\u00fablico", "rotaci\u00f3n de personal", "brechas salariales de g\u00e9nero"], "fr": ["paie du secteur public", "r\u00e9mun\u00e9ration publique", "emploi public", "rotation du personnel", "\u00e9carts de r\u00e9mun\u00e9ration entre les genres"], "pt_BR": ["folhas de pagamento p\u00fablicas", "remunera\u00e7\u00e3o p\u00fablica", "emprego p\u00fablico", "rotatividade", "disparidades salariais de g\u00eanero"]}, "contact_point": "opendata@iadb.org", "description": {"en": "The R code calculates and standardizes payroll key performance indicators (KPIs) using common-format personnel records from Latin America and the Caribbean.\nR code is provided to calculate and standardize core payroll key performance indicators (KPIs) using structured personnel records. These KPIs include:\n- Wage bill growth  \n- Employment growth  \n- Average pay trajectories  \n- Gender pay gap  \n- Pay equity  \n- Turnover rates  \n- Promotion and career progression trends  \n- Retirement projections  \n\nThe code demonstrates how to calculate each KPI accurately using a consistent methodology, supporting cross-country comparability and data reproducibility.\n### Calculating the Gender Pay Gap in Public Sector Payroll\nOne of the key applications is computing the gender pay gap, a critical metric for evaluating pay equity within public administration. The R scripts include methods to:\n- Compare average pay by gender across the entire workforce or by job category  \n- Control for variables such as contract type, tenure, or agency  \n- Identify structural or data-driven discrepancies affecting gender-based pay analysis  \n\nBy applying these standard formulas, LAC governments can monitor progress toward gender pay equality and align with international reporting frameworks.\n\n### Granular Analysis and Error Resolution\nThe code allows for KPI calculations at multiple levels:\n- Whole-of-government  \n- Specific agencies or ministries  \n- Employee subgroups (e.g., by gender, job classification, contract type)  \n\nIt also addresses common data issues\u2014such as missing or inconsistent pay records\u2014ensuring accurate, error-resistant results. This facilitates reliable reporting and supports evidence-based decision-making in human resource management throughout Latin America and the Caribbean.", "es": "Este c\u00f3digo en R permite calcular y estandarizar los indicadores clave de desempe\u00f1o (KPI) de n\u00f3mina a partir de registros de personal con un formato com\u00fan provenientes de Am\u00e9rica Latina y el Caribe. Los KPI se obtienen sobre la base de registros de personal estructurados y abarcan:\n- Crecimiento de la masa salarial  \n- Crecimiento del empleo  \n- Trayectorias de los salarios promedio  \n- Brecha salarial de g\u00e9nero  \n- Equidad salarial  \n- Tasas de rotaci\u00f3n  \n- Tendencias de promoci\u00f3n y trayectoria profesional  \n- Proyecciones de jubilaci\u00f3n  \n\nCada indicador se calcula con una metodolog\u00eda uniforme, de modo que los resultados sean comparables entre pa\u00edses y reproducibles.\n### C\u00e1lculo de la brecha salarial de g\u00e9nero en la n\u00f3mina del sector p\u00fablico\nEntre sus usos m\u00e1s relevantes est\u00e1 el c\u00e1lculo de la brecha salarial de g\u00e9nero, una m\u00e9trica esencial para evaluar la equidad salarial en la administraci\u00f3n p\u00fablica. Para ello, los scripts en R permiten:\n- Comparar los salarios promedio por g\u00e9nero, tanto en el conjunto de la fuerza laboral como por categor\u00eda del puesto  \n- Aislar el efecto de variables como el tipo de contrato, la antig\u00fcedad o la entidad  \n- Detectar diferencias estructurales o atribuibles a los propios datos que inciden en el an\u00e1lisis salarial por g\u00e9nero  \n\nCon estas f\u00f3rmulas estandarizadas, los gobiernos de Am\u00e9rica Latina y el Caribe (ALC) pueden dar seguimiento a sus avances hacia la igualdad salarial de g\u00e9nero y ajustarse a los marcos internacionales de presentaci\u00f3n de informes.\n\n### An\u00e1lisis granular y tratamiento de errores\nLos KPI pueden calcularse en distintos niveles de detalle:\n- El conjunto del gobierno  \n- Entidades o ministerios en particular  \n- Subgrupos de personal (por ejemplo, seg\u00fan g\u00e9nero, clasificaci\u00f3n del puesto o tipo de contrato)  \n\nEl c\u00f3digo tambi\u00e9n contempla los problemas habituales de los datos \u2014como registros de pago ausentes o inconsistentes\u2014 para que los resultados sean precisos y poco sensibles a errores. As\u00ed se facilita una presentaci\u00f3n de informes fiable y se sustenta la toma de decisiones basada en evidencia en la gesti\u00f3n de recursos humanos en toda Am\u00e9rica Latina y el Caribe.", "fr": "Ce code R sert \u00e0 calculer et \u00e0 harmoniser les indicateurs cl\u00e9s de performance (KPI) de la paie en s'appuyant sur des dossiers du personnel pr\u00e9sent\u00e9s selon un format commun en Am\u00e9rique latine et dans les Cara\u00efbes. \u00c0 partir de dossiers structur\u00e9s, il produit les KPI essentiels, parmi lesquels :\n- la croissance de la masse salariale ;  \n- la croissance de l'emploi ;  \n- l'\u00e9volution des salaires moyens ;  \n- l'\u00e9cart de r\u00e9mun\u00e9ration entre les genres ;  \n- l'\u00e9quit\u00e9 salariale ;  \n- les taux de rotation ;  \n- les tendances de promotion et de progression de carri\u00e8re ;  \n- les projections de d\u00e9part \u00e0 la retraite.  \n\nChaque KPI repose sur une m\u00e9thodologie coh\u00e9rente, gage de comparabilit\u00e9 entre les pays et de reproductibilit\u00e9 des donn\u00e9es.\n### Calculer l'\u00e9cart de r\u00e9mun\u00e9ration entre les genres dans la paie publique\nParmi ses applications majeures figure le calcul de l'\u00e9cart de r\u00e9mun\u00e9ration entre les genres, mesure d\u00e9terminante pour appr\u00e9cier l'\u00e9quit\u00e9 salariale au sein de l'administration publique. \u00c0 cette fin, les scripts R permettent de :\n- comparer les salaires moyens selon le genre, pour l'ensemble des effectifs ou par cat\u00e9gorie de poste ;  \n- neutraliser des variables telles que le type de contrat, l'anciennet\u00e9 ou l'organisme ;  \n- rep\u00e9rer les \u00e9carts structurels ou imputables aux donn\u00e9es qui p\u00e8sent sur l'analyse salariale selon le genre.  \n\nGr\u00e2ce \u00e0 ces formules normalis\u00e9es, les gouvernements d'Am\u00e9rique latine et des Cara\u00efbes (ALC) peuvent mesurer leurs progr\u00e8s vers l'\u00e9galit\u00e9 salariale entre les genres et se conformer aux cadres internationaux de reporting.\n\n### Analyse fine et traitement des erreurs\nLes KPI se calculent \u00e0 diff\u00e9rents niveaux de granularit\u00e9 :\n- l'ensemble du gouvernement ;  \n- des organismes ou minist\u00e8res d\u00e9termin\u00e9s ;  \n- des sous-groupes d'agents (par exemple selon le genre, la classification du poste ou le type de contrat).  \n\nLe code prend \u00e9galement en charge les difficult\u00e9s courantes li\u00e9es aux donn\u00e9es \u2014 dossiers de paie manquants ou incoh\u00e9rents \u2014 afin de produire des r\u00e9sultats exacts et peu sensibles aux erreurs. Il favorise ainsi un reporting fiable et une prise de d\u00e9cision fond\u00e9e sur des donn\u00e9es probantes dans la gestion des ressources humaines \u00e0 l'\u00e9chelle de l'Am\u00e9rique latine et des Cara\u00efbes.", "pt_BR": "Este c\u00f3digo em R calcula e padroniza os indicadores-chave de desempenho (KPIs) da folha de pagamento a partir de registros de pessoal em formato comum da Am\u00e9rica Latina e do Caribe. Tomando como base registros de pessoal estruturados, ele gera os principais KPIs, que abrangem:\n- Crescimento da massa salarial  \n- Crescimento do emprego  \n- Trajet\u00f3rias dos sal\u00e1rios m\u00e9dios  \n- Lacuna salarial de g\u00eanero  \n- Equidade salarial  \n- Taxas de rotatividade  \n- Tend\u00eancias de promo\u00e7\u00e3o e de progress\u00e3o na carreira  \n- Proje\u00e7\u00f5es de aposentadoria  \n\nCada KPI \u00e9 calculado segundo uma metodologia uniforme, o que torna os resultados compar\u00e1veis entre pa\u00edses e reproduz\u00edveis.\n### C\u00e1lculo da lacuna salarial de g\u00eanero na folha de pagamento do setor p\u00fablico\nEntre suas aplica\u00e7\u00f5es mais importantes est\u00e1 o c\u00e1lculo da lacuna salarial de g\u00eanero, m\u00e9trica decisiva para avaliar a equidade salarial na administra\u00e7\u00e3o p\u00fablica. Para isso, os scripts em R permitem:\n- Comparar os sal\u00e1rios m\u00e9dios por g\u00eanero, seja em toda a for\u00e7a de trabalho, seja por categoria de cargo  \n- Isolar o efeito de vari\u00e1veis como tipo de contrato, tempo de servi\u00e7o ou \u00f3rg\u00e3o  \n- Identificar discrep\u00e2ncias estruturais ou decorrentes dos pr\u00f3prios dados que afetam a an\u00e1lise salarial por g\u00eanero  \n\nCom essas f\u00f3rmulas padronizadas, os governos da Am\u00e9rica Latina e do Caribe (ALC) conseguem acompanhar o avan\u00e7o rumo \u00e0 igualdade salarial de g\u00eanero e alinhar-se aos marcos internacionais de relat\u00f3rio.\n\n### An\u00e1lise granular e tratamento de erros\nOs KPIs podem ser calculados em diferentes n\u00edveis de detalhe:\n- Todo o governo  \n- \u00d3rg\u00e3os ou minist\u00e9rios espec\u00edficos  \n- Subgrupos de funcion\u00e1rios (por exemplo, por g\u00eanero, classifica\u00e7\u00e3o de cargo ou tipo de contrato)  \n\nO c\u00f3digo ainda trata problemas comuns dos dados \u2014 como registros de pagamento ausentes ou inconsistentes \u2014 para assegurar resultados precisos e pouco sujeitos a erros. Dessa forma, viabiliza relat\u00f3rios confi\u00e1veis e apoia a tomada de decis\u00f5es baseada em evid\u00eancias na gest\u00e3o de recursos humanos em toda a Am\u00e9rica Latina e o Caribe."}}}