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We investigate whether patents on human genes have affected follow-on scientific research and product development. Using administrative data on successful and unsuccessful patent applications submitted to the US Patent and Trademark Office, we link the exact gene sequences claimed in each application with data measuring follow-on scientific research and commercial investments. Using this data, we document novel evidence of selection into patenting: patented genes appear more valuable—prior to being patented—than non-patented genes. This evidence of selection motivates two quasi-experimental approaches, both of which suggest that on average gene patents have had no quantitatively important effect on follow-on innovation.
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For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it. Version 5 release notes: Adds data in the following formats: SPSS, SAS, and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Adds data for 1991.Fixes bug where bias motivation "anti-lesbian, gay, bisexual, or transgender, mixed group (lgbt)" was labeled "anti-homosexual (gay and lesbian)" prior to 2013 causing there to be two columns and zero values for years with the wrong label.All data is now directly from the FBI, not NACJD. The data initially comes as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data. Version 4 release notes: Adds data for 2017.Adds rows that submitted a zero-report (i.e. that agency reported no hate crimes in the year). This is for all years 1992-2017. Made changes to categorical variables (e.g. bias motivation columns) to make categories consistent over time. Different years had slightly different names (e.g. 'anti-am indian' and 'anti-american indian') which I made consistent. Made the 'population' column which is the total population in that agency. Version 3 release notes: Adds data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Hate Crime data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about hate crimes reported in the United States. Please note that the files are quite large and may take some time to open. Each row indicates a hate crime incident for an agency in a given year. I have made a unique ID column ("unique_id") by combining the year, agency ORI9 (the 9 character Originating Identifier code), and incident number columns together. Each column is a variable related to that incident or to the reporting agency. Some of the important columns are the incident date, what crime occurred (up to 10 crimes), the number of victims for each of these crimes, the bias motivation for each of these crimes, and the location of each crime. It also includes the total number of victims, total number of offenders, and race of offenders (as a group). Finally, it has a number of columns indicating if the victim for each offense was a certain type of victim or not (e.g. individual victim, business victim religious victim, etc.). The only changes I made to the data are the following. Minor changes to column names to make all column names 32 characters or fewer (so it can be saved in a Stata format), changed the name of some UCR offense codes (e.g. from "agg asslt" to "aggravated assault"), made all character values lower case, reordered columns. I also added state, county, and place FIPS code from the LEAIC (crosswalk) and generated incident month, weekday, and month-day variables from the incident date variable included in the original data.,Smallest Geographic Unit: police agency,
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Barbetta, G.P:, Sorrenti, G., Turati, G. (2019), Multigrading and Child Achievement, Journal of Human Resources We study how multigrading, which is mixing students of different grades into a single class, affects children’s cognitive achievement in primary school. We build instruments to identify the causal effect of multigrading by exploiting an Italian law that controls class size and grade composition. Results suggest that attendance in multigrade versus single-grade classes increases students’ performance on standardized tests by 19 percent of a standard deviation for second graders, and it has zero effect for fifth graders. The positive impact of multigrading for second graders appears to be driven by children sharing their class with peers from higher grades. This last finding rationalizes the absence of a multigrade effect for fifth graders. , Second and fifth-grade students attending schools in areas with only one primary school. ,
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A geographic cross-sectional fiscal spending multiplier measures the effect of an increase in spending in one region of a monetary union. Empirical studies of such multipliers have proliferated. I review this research and what the evidence implies for national multipliers. Based on an updated analysis of the ARRA and a survey of empirical studies, my preferred point estimate for a cross-sectional multiplier is 1.8. The paper also discusses conditions under which the cross-sectional multiplier provides a rough lower bound for the national, no-monetary-policy-response multiplier. Putting these elements together, the cross-sectional evidence suggests a national no-monetary-policy-response multiplier of 1.7 or above.
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In many global cities the rental housing market is partially regulated. We document that the Paris housing market is dual: a flexible rent sector coexists with a large controlled rent sector. The two sectors have very different rent gradients towards the center of the agglomeration. We develop a model explicitly accounting for these features which allows to investigate general equilibrium effects of rent controls at the city level. In this framework the coexistence of a controlled and flexible rent sector increases the spatial misallocation of households. This mismatch can generally be alleviated by an improvement in urban transport infrastructures.
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A standard response of both policy-makers and private citizens to hardships—from natural disasters to mass shootings—is to offer “thoughts and prayers.” Critics argue that such gestures are meaningless and may obstruct structural reforms intended to mitigate catastrophes. In this study, we elicit the value of receiving thoughts and prayers from strangers following adversity. We find that Christians value thoughts and prayers from religious strangers and priests, while atheists and agnostics are “prayer averse”—willing to pay to avoid receiving prayers. Further, while indifferent to receiving thoughts from other secular people, they negatively value thoughts from Christians.
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Leading empiricists and theorists of cities have recently argued that the generation and exchange of ideas must play a more central role in the analysis of cities. This paper develops the first system of cities model with costly idea exchange as the agglomeration force. The model replicates a broad set of established facts about the cross section of cities. It provides the first spatial equilibrium theory of why skill premia are higher in larger cities and how variation in these premia emerges from symmetric fundamentals.
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These files contain citations from U.S. patents 1926-2018 to articles in the Microsoft Academic Graph from 1800-2018. Please cite Marx, M. and A. Fuegi, "Reliance on Science in Patenting." available in this distribution as reliance_on_science.pdf and also at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686. These data make use of and redistribute portions of the Microsoft Academic Graph. Please see https://www.microsoft.com/en-us/research/project/academic/ for details about the Microsoft Academic Graph (MAG), which is provided under an ODC-BY license (https://opendatacommons.org/licenses/by/1-0/index.html). Academic papers making use of the MAG data should cite the following paper: Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MA) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246.
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This paper evaluates the role of redistribution in the transmission mechanism of monetary policy to consumption. Three channels affect aggregate spending when winners and losers have different marginal propensities to consume: an earnings heterogeneity channel from unequal income gains, a Fisher channel from unexpected inflation, and an interest rate exposure channel from real interest rate changes. Sufficient statistics from Italian and US data suggest that all three channels are likely to amplify the effects of monetary policy.
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This survey was conducted as part of the evaluation of the Aligning Forces for Quality (AF4Q) initiative, which is the Robert Wood Johnson Foundation's effort to lift the overall quality of health care in 17 targeted communities, reduce racial and ethnic disparities, and provide models of national reform. The survey was administered to adults with one or more of five chronic illnesses, diabetes, hypertension, heart disease, asthma and depression, in the AF4Q communities and a national sample residing in non-AF4Q communities to provide a basis for comparison between the AF4Q communities and the rest of the United States. Survey questions focused on patient activation; consumer knowledge of publicly available performance reports that highlight quality differences among physicians, hospitals, and health plans; the ability to be an effective consumer in the context of a physician visit; patient knowledge about her/his illness; skills and willingness to self-manage one's illness; the impact of insurance and payment models; and the relationship between out-of-pocket costs and health care utilization. In 2011 the AF4Q evaluation team contracted with RTI International (RTI) to conduct the Aligning Forces for Quality Consumer Survey 2.0 (AF4Q 2.0).,Aligning Forces for Quality (AF4Q) is a national program of the Robert Wood Johnson Foundation (RWJF) to help communities dramatically improve the quality of the health care they provide. The AF4Q specifically aims to align three key drivers of quality improvement: Performance measurement and public reporting; capacity for quality improvement; and consumer engagement.,ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created online analysis version with question text.; Checked for undocumented or out-of-range codes..,Response Rates: The second round of the survey consisted of both panel respondents (individuals who also participated in round 1) and a new Random Digit Dial (RDD) sample. The panel sample had an unweighted response rate of 63.3% (60.9% weighted). RDD cases were classified based on their response and eligibility for the screener and the full interview. The RDD sample had an unweighted American Association for Public Opinion Research (AAPOR) response rate of 16.5% (9.9% weighted).,Datasets: DS0: Study-Level Files DS1: Public-Use Version of the Data DS2: Restricted-Use Version of the Data,computer-assisted telephone interview (CATI),Adult-aged individuals with one of more of the following chronic illnesses: asthma, diabetes, coronary heart disease, hypertension, and depression. Smallest Geographic Unit: City,For the panel component of the survey, respondents from the first round of Aligning Forces for Quality (AF4Q) data collection who agreed to a follow-up were sampled and contacted for the AF4Q 2.0. RTI International (RTI) fielded a total of 7,445 sample records. All baseline respondents sampled for the panel component were considered eligible for AF4Q 2.0 except those who were identified as either institutionalized or deceased. The Random Digit Dial (RDD) component of the sample was a dual frame design comprised of landline and cell phone samples. RTI designed new cross-sectional samples for the 16 markets surveyed in the baseline AF4Q study, including 15 AF4Q markets and a national control sample. In addition, RTI designed four supplemental samples for markets where counties have been added to the original AF4Q communities since baseline.,
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