Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Regression Toward the Mean01:52

Regression Toward the Mean

7.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.3K
Equity Theory01:26

Equity Theory

370
Equity theory explains how our sense of fairness influences the dynamics of close relationships. Rooted in social psychology, the theory posits that individuals evaluate fairness by comparing the ratio of their contributions to the rewards they receive. Relationship satisfaction is highest when these ratios are perceived as balanced between partners, promoting mutual reciprocity and a sense of justice.Equity vs. Equality in RelationshipsEquity is distinct from equality. Fairness does not...
370
Bias01:22

Bias

7.9K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
7.9K
Epistasis Analysis01:09

Epistasis Analysis

6.2K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
6.2K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

520
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
520
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

570
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
570

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The NBER Orange Book Dataset: A user's guide.

Research policy·2023
Same author

Market design to accelerate COVID-19 vaccine supply.

Science (New York, N.Y.)·2021
Same author

How Do Patents Affect Follow-On Innovation? Evidence from the Human Genome.

The American economic review·2019
Same author

How Do Patents Affect Follow-on Innovation? Evidence from the Human Genome.

The American economic review·2019
Same author

Do Firms Underinvest in Long-Term Research? Evidence from Cancer Clinical Trials.

The American economic review·2018
Same author

How do patents affect research investments?

Annual review of economics·2017

Related Experiment Video

Updated: Mar 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.8K

PATENTS AND RESEARCH INVESTMENTS: ASSESSING THE EMPIRICAL EVIDENCE.

Eric Budish1, Benjamin N Roin2, Heidi L Williams3

  • 1Booth School of Business, University of Chicago, 5807 South Woodlawn Avenue, Chicago, IL 60637 and NBER, eric.budish@chicagobooth.edu.

The American Economic Review
|May 31, 2016
PubMed
Summary

Optimal patent policy balances innovation incentives and access. This study examines how R&D investment responds to patent term length, a crucial factor for effective patent policy design.

More Related Videos

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
06:16

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting

Published on: June 6, 2020

4.7K
Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.5K

Related Experiment Videos

Last Updated: Mar 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.8K
Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
06:16

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting

Published on: June 6, 2020

4.7K
Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.5K

Area of Science:

  • Economics
  • Innovation Policy
  • Intellectual Property

Background:

  • Theoretical literature on optimal patent policy design dates back to Nordhaus (1969).
  • The Nordhaus model presents a core trade-off in patent policy.
  • Empirical evidence on R&D investment elasticity to patent terms is surprisingly limited.

Purpose of the Study:

  • Re-present the core trade-off of the Nordhaus model.
  • Highlight the empirical question of R&D investment elasticity with respect to patent term.
  • Review existing empirical evidence on this critical question for patent policy.

Main Methods:

  • Theoretical economic modeling (Nordhaus framework).
  • Literature review of empirical studies.
  • Analysis of the relationship between patent term and R&D investment.

Main Results:

  • The elasticity of R&D investment with respect to patent term is a key, yet under-researched, input for optimal patent policy.
  • Existing empirical evidence on this elasticity is surprisingly scarce.
  • The theoretical framework highlights the importance of this empirical question.

Conclusions:

  • Further empirical research is needed to quantify the elasticity of R&D investment to patent terms.
  • Understanding this elasticity is crucial for designing effective and optimal patent policies.
  • The limited empirical data presents a significant gap in informing patent policy design.