{ "143300-21892656": { "datetime_modified":"20260330T081853", "datetime_start":"20260407T113000", "datetime_end":"20260407T125000", "has_end_time":1, "date_start":"2026-04-07", "date_end":"2026-04-07", "time_start":"11:30:00", "time_end":"12:50:00", "time_zone":"America\/Detroit", "event_title":"Resource Allocation, Technology Adoption, and Productivity: A Quantitative Analysis with Panel Farm-Level Data (with Duc Nguyen)", "occurrence_title":"", "combined_title":"Resource Allocation, Technology Adoption, and Productivity: A Quantitative Analysis with Panel Farm-Level Data (with Duc Nguyen): Diego Restuccia, University of Toronto", "event_subtitle":"Diego Restuccia, University of Toronto", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"We examine how resource allocation across production units shapes technology adoption and productivity growth, combining a unique panel dataset of the universe of Canadian farms spanning 1986 to 2006 with a quantitative model of heterogeneous producers. The period features the advent and rapid di!usion of a major new seeding technique, zero tillage, whose use expanded from zero percent of cultivated land in 1986 to 60 percent by 2006. We document substantial technology adoption, land consolidation, and productivity growth, facilitated by an economic environment characterized by relatively high allocative e\u201dciency, whereby more productive farms operate at a larger scale. Empirically, we find that adopting zero-tillage raises farm-level productivity substantially. Through quantitative analysis, we estimate that zero-tillage adoption accounts for roughly 30 percent of the near doubling of agricultural productivity over the period and 45\u201370 percent of the observed structural transformation. We show that high allocative e\u201dciency was crucial for the widespread adoption of technology, which would have nearly disappeared with correlated distortions commonly documented in developing countries. We also show that technological progress can be a powerful driver of catch-up growth in developing economies with low correlated distortions.", "occurrence_notes":null, "guid":"143300-21892656@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/143300", "building_id":"1005177", "building_name":"North Quad", "campus_maps_id":"553", "room":"4325", "location_name":"North Quad", "has_livestream":0, "cost":"", "tags":["Macroeconomics","seminar","Economics"], "website":"http:\/\/www.lsa.umich.edu\/econ", "sponsors":[ { "group_name":"Department of Economics", "group_id":"3302", "website":"http:\/\/www.lsa.umich.edu\/econ" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_143300_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_143300_original-1.jpg", 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"occurrence_title":"", "combined_title":"Auctions as Experiments (with Ryota Iijima, Yuhta Ishii, and Nicholas Wu): Mira Frick, Princeton University", "event_subtitle":"Mira Frick, Princeton University", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"We study a seller who does not know the distribution of buyers\u2019 values, but can learn from observing their bids in an auction. Which auction formats provide better information about the value distribution? We show that among a large class of standard auctions (e.g., kth-price, all-pay), the first-price auction is (Lehmann) most informative. Thus, while all these auction formats yield the same expected static revenue, the first-price auction is preferred by a seller who can use today\u2019s bid observations to optimize revenue tomorrow.", "occurrence_notes":null, "guid":"143382-21892969@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/143382", "building_id":"1005177", "building_name":"North Quad", "campus_maps_id":"553", "room":"4300", "location_name":"North Quad", "has_livestream":0, "cost":"", "tags":["Theory","seminar","Economics"], "website":"http:\/\/www.lsa.umich.edu\/econ", "sponsors":[ { "group_name":"Department of Economics", "group_id":"3302", "website":"http:\/\/www.lsa.umich.edu\/econ" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2026\/01\/event_143382_original-1.jpg", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/01\/event_143382_original-1.jpg" }, "occurrence_count":1, "first_occurrence":21892969 } , "143570-21893403": { "datetime_modified":"20260213T081432", "datetime_start":"20260407T143000", "datetime_end":"20260407T155000", "has_end_time":1, "date_start":"2026-04-07", "date_end":"2026-04-07", "time_start":"14:30:00", "time_end":"15:50:00", "time_zone":"America\/Detroit", "event_title":"Transport Infrastructure and Agriculture Productivity: Evidence from the Antebellum United States", "occurrence_title":"", "combined_title":"Transport Infrastructure and Agriculture Productivity: Evidence from the Antebellum United States: Alexander Klein, University of Sussex", "event_subtitle":"Alexander Klein, University of Sussex", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"This paper investigates the relationship between transport infrastructure and agricultural productivity in the Antebellum United States (1840\u20131860). Leveraging a novel dataset of county-pair transport costs, we utilize time-, region-, and direction-specific freight rates and newly digitized road network to understand how declining transit costs reshaped the agrarian landscape and agricultural production. These data allow for a rigorous evaluation of what we can call an antebellum \"place-based\" transport policies and their heterogeneous effects on antebellum regions. We use minimum spanning tree approach to construct a plausibly exogenous transportation network which is used to assess the causal impact of transportation infrastructure on antebellum agriculture.\n \nOur first set of findings reveal that the impact of canal construction was not uniform, showing considerable variation across different geographic regions. Notably, in the Middle Atlantic, the introduction of canals catalyzed a significant reallocation of resources away from wheat production, signalling a shift in comparative advantage. While canals laid the groundwork, railroads exerted the most transformative influence during the 1850s. In the final decade preceding the Civil War, the expansion of the rail network drove a broad reallocation away from traditional grain production, as improved connectivity facilitated deeper market integration and specialization. By accounting for the nuances of freight directionality and regional specificity, this study provides new evidence on how infrastructure-led cost reductions altered land use and productivity patterns in the nineteenth-century U.S. economy.", "occurrence_notes":null, "guid":"143570-21893403@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/143570", "building_id":"1005177", "building_name":"North Quad", "campus_maps_id":"553", "room":"4325", "location_name":"North Quad", "has_livestream":0, "cost":"", "tags":["Economics","seminar","History"], "website":"http:\/\/www.lsa.umich.edu\/econ", "sponsors":[ { "group_name":"Department of Economics", "group_id":"3302", "website":"http:\/\/www.lsa.umich.edu\/econ" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_143570_original-1.png", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_143570_original-1.png", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2026\/01\/event_143570_original-1.png", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2026\/01\/event_143570_original-1.png", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2026\/01\/event_143570_original-1.png", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2026\/01\/event_143570_original-1.png", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/01\/event_143570_original-1.png" }, "occurrence_count":1, "first_occurrence":21893403 } , "143696-21893658": { "datetime_modified":"20260330T081439", "datetime_start":"20260408T143000", "datetime_end":"20260408T155000", "has_end_time":1, "date_start":"2026-04-08", "date_end":"2026-04-08", "time_start":"14:30:00", "time_end":"15:50:00", "time_zone":"America\/Detroit", "event_title":"Understanding Criminal Record Penalties in the Labor Market", "occurrence_title":"", "combined_title":"Understanding Criminal Record Penalties in the Labor Market: Evan Rose, University of Chicago", "event_subtitle":"Evan Rose, University of Chicago", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"This paper studies the earnings and employment penalties associated with criminal records using linked data on criminal justice interactions, state laws on formal labor market restrictions, and wages and employment. We estimate fixed effects models that decompose earnings into a worker's portable earnings potential and firm pay premia, both of which are allowed to shift after a worker acquires a record. We find that sorting into lower-paying firms explains a small share of the record penalty. Legal record restrictions are not concentrated in higher-paying jobs, meaning that sorting away from them contributes little to the earnings gap. Conditional on earnings potential, however, workers with a record are substantially less likely to be employed. The results suggest that criminal record penalties operate primarily by reducing employment and lowering earnings potential at every firm rather than increasing sorting into lower-paying jobs, although the bulk of the gaps can be attributed to differences that existed prior to acquiring a record.", "occurrence_notes":null, "guid":"143696-21893658@events.umich.edu", "permalink":"http:\/\/events.umich.edu\/event\/143696", "building_id":"1005177", "building_name":"North Quad", "campus_maps_id":"553", "room":"4325", "location_name":"North Quad", "has_livestream":0, "cost":"", "tags":["Economics","Labor","seminar"], "website":"http:\/\/www.lsa.umich.edu\/econ", "sponsors":[ { "group_name":"Department of Economics", "group_id":"3302", "website":"http:\/\/www.lsa.umich.edu\/econ" } ], "image_url":"https:\/\/events.umich.edu\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "styled_images":{ "event_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_thumb\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_large":"https:\/\/events.umich.edu\/media\/cache\/event_large\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_large_2x":"https:\/\/events.umich.edu\/media\/cache\/event_large_2x\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/event_large_lightbox\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "group_thumb":"https:\/\/events.umich.edu\/media\/cache\/group_thumb\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "group_thumb_square":"https:\/\/events.umich.edu\/media\/cache\/group_thumb_square\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "group_large":"https:\/\/events.umich.edu\/media\/cache\/group_large\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "group_large_lightbox":"https:\/\/events.umich.edu\/media\/cache\/group_large_lightbox\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_large_crop":"https:\/\/events.umich.edu\/media\/cache\/event_large_crop\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_list":"https:\/\/events.umich.edu\/media\/cache\/event_list\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_list_2x":"https:\/\/events.umich.edu\/media\/cache\/event_list_2x\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_grid":"https:\/\/events.umich.edu\/media\/cache\/event_grid\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_grid_2x":"https:\/\/events.umich.edu\/media\/cache\/event_grid_2x\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_feature_large":"https:\/\/events.umich.edu\/media\/cache\/event_feature_large\/media\/attachments\/2026\/01\/event_143696_original-1.jpg", "event_feature_thumb":"https:\/\/events.umich.edu\/media\/cache\/event_feature_thumb\/media\/attachments\/2026\/01\/event_143696_original-1.jpg" }, "occurrence_count":1, "first_occurrence":21893658 } , "143683-21893642": { "datetime_modified":"20260401T090119", "datetime_start":"20260409T103000", "datetime_end":"20260409T115000", "has_end_time":1, "date_start":"2026-04-09", "date_end":"2026-04-09", "time_start":"10:30:00", "time_end":"11:50:00", "time_zone":"America\/Detroit", "event_title":"Improved Inference for Nonparametric Regression (joint with G.Cavaliere, M. Nielsen, and E. Zanelli)", "occurrence_title":"", "combined_title":"Improved Inference for Nonparametric Regression (joint with G.Cavaliere, M. Nielsen, and E. Zanelli): Silvia Goncales, McGill University", "event_subtitle":"Silvia Goncales, McGill University", "event_type":"Workshop \/ Seminar", "event_type_id":"21", "description":"Nonparametric regression estimators, including those employed in regression-discontinuity designs (RDD), are central to the economist\u2019s toolbox. Their application, however, is complicated by the presence of asymptotic bias, which undermines coverage accuracy of conventional confidence intervals. Extant solutions to the problem include debiasing methods, such as the widely applied robust bias-corrected (RBC) confidence interval of Calonico et al. (2014, 2018). We show that this interval is equivalent to a prepivoted interval based on an invalid residualbased bootstrap method. Specifically, prepivoting performs an implicit bias correction while adjusting the nonparametric regression estimator\u2019s standard error to account for the additional uncertainty introduced by debiasing. This idea can also be applied to other bootstrap schemes, leading to new implicit bias corrections and corresponding standard error adjustments. We propose a prepivoted interval based on a bootstrap that generates observations from nonparametric regression estimates at each regressor value and show how it can be implemented as an RBCtype interval without the need for resampling. Importantly, we show that the new interval is shorter than the existing RBC interval. For example, with the Epanechnikov kernel, the length is reduced by 17%, while maintaining accurate coverage probability. 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