{"doi":"10.1093/jeea/jvaa043","title":"Reevaluating Agricultural Productivity Gaps with Longitudinal Microdata","abstract":"Recent research has pointed to large gaps in labor productivity between the agricultural and non-agricultural sectors in low-income countries, as well as between workers in rural and urban areas. Most estimates are based on national accounts or repeated cross-sections of microsurvey data, and as a result typically struggle to account for individual selection between sectors. This paper uses long-run individual-level panel data from two low-income countries (Indonesia and Kenya) to explore these gaps. Accounting for individual fixed effects leads to much smaller estimated productivity gains from moving into the non-agricultural sector (or urban areas), reducing estimated gaps by roughly 67%-92%. Furthermore, gaps do not emerge up to 5 years after a move between sectors. We evaluate whether these findings imply a re-assessment of the conventional wisdom regarding sectoral gaps, discuss how to reconcile them with existing cross-sectional estimates, and consider implications for the desirability of sectoral reallocation of labor.","journal":"Journal of the European Economic Association","year":2020,"id":55274,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":94,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8497,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":285650,"name":"Marieke Kleemans","orcid":"0009-0007-9310-857X","position":1,"is_corresponding":false},{"id":287224,"name":"Nicholas Y. Li","orcid":null,"position":2,"is_corresponding":false},{"id":285651,"name":"Edward Miguel","orcid":"0000-0001-6927-709X","position":3,"is_corresponding":false},{"id":285649,"name":"Joan Hamory","orcid":"0000-0002-0071-8683","position":0,"is_corresponding":true}],"reference_count":55,"raw_metadata":null,"created_at":"2026-07-18T21:04:59.506324Z","pmid":"37961748","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}