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Related Concept Videos

Wedges01:24

Wedges

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A wedge is a simple machine that serves various purposes, such as adjusting the elevation of structural or mechanical parts, providing stability for heavy objects, and splitting a body into two parts. This versatile tool can amplify an applied force, making it easier to manipulate large or heavy objects.
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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Aminoglycosides are a class of antibiotics used to treat various bacterial infections. Clinicians must determine the elimination rate constant (k) and volume of distribution (VD) to optimize therapeutic efficacy and minimize toxicity. The k value represents the rate at which the drug is removed from the body, and the VD reflects the degree to which the drug distributes into body tissues. Accurately estimating these parameters allows healthcare professionals to tailor drug dosing to individual...
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How Data are Classified: Categorical Data01:11

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
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How Data are Classified: Numerical Data00:59

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
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Related Experiment Video

Updated: Feb 5, 2026

Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation
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Data for estimating the U.S. labor wedge.

Lini Zhang1

  • 1Central University of Finance and Economics, China.

Data in Brief
|September 8, 2018
PubMed
Summary

This study estimates the U.S. after-tax labor wedge, a measure of economic efficiency, using quarterly data from 1947 to 2017. It decomposes this wedge into components related to the marginal rate of substitution (MRS) and marginal product of labor (MPL).

Area of Science:

  • Economics
  • Macroeconomics
  • Labor Economics

Background:

  • The after-tax labor wedge quantifies the distortionary effects of taxes on labor markets.
  • Understanding this wedge is crucial for analyzing labor market efficiency and economic policy.
  • Previous research has explored the labor wedge, but empirical estimation requires robust data and methods.

Purpose of the Study:

  • To introduce the data and methodology for estimating the U.S. after-tax labor wedge.
  • To provide empirical support for the research article "Credit Crunch, Heterogeneity and the Labor Wedge" (Zhang, 2018).
  • To decompose the after-tax labor wedge into its constituent components: the MPL component and the MRS component.

Main Methods:

  • Definition of the after-tax labor wedge as the log difference between the marginal rate of substitution (MRS) and the marginal product of labor (MPL), excluding taxes.
Keywords:
Business cycleGDPLabor wedgeMPLMRS

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  • Estimation of the U.S. after-tax labor wedge using quarterly data spanning from 1947Q1 to 2017Q3.
  • Decomposition of the estimated wedge into the gap between MPL and real wage (MPL component) and the gap between real wage and MRS (MRS component).

    • Main Results:

    • Successful estimation of the U.S. after-tax labor wedge over the specified period.
    • Quantification of the MPL component and the MRS component of the after-tax labor wedge.
    • The study provides a detailed empirical basis for understanding labor market distortions.

    Conclusions:

    • The methodology presented allows for the empirical measurement and decomposition of the after-tax labor wedge.
    • The findings offer valuable insights into the dynamics of U.S. labor market efficiency over seven decades.
    • This empirical work supports theoretical models examining the impact of credit conditions and heterogeneity on labor market wedges.