Data and methods

Data, and the methods used to analyze them, are the foundation for evidence-based research. Articles in this subject area discuss the value of different types of data collection, and explain important statistical and econometric methods that provide ways to summarize and present information, and to identify and quantify correlation or causality.

  • Performance measures and worker productivity Updated

    Choosing the right performance measures can inform and improve decision-making in policy and management

    Jan Sauermann, April 2023
    Measuring workers’ productivity is important for public policy and private-sector decision-making. Due to the lack of a general measure that captures workers’ productivity, firms often use one- or multi-dimensional performance measures, which can be used, for example, to analyze how different incentive systems affect workers’ behavior. The public sector itself also uses measures to monitor and evaluate personnel, such as teachers. Policymakers and managers need to understand the advantages and disadvantages of the available metrics to select the right performance measures for their purpose.
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  • Gross domestic product: Are other measures needed? Updated

    GDP summarizes only one aspect of a country’s condition; other measures in addition to GDP would be valuable

    Barbara M. Fraumeni, April 2022
    Gross domestic product (GDP) is the key indicator of the health of an economy and can be easily compared across countries. But it has limitations. GDP tells what is going on today, but does not inform about sustainability of growth. The majority of time is spent in home production, yet the value of this time is not included in GDP. GDP does not measure happiness, so residents can be dissatisfied even when GDP is rising. In addition, GDP does not consider environmental factors, reflect what individuals do outside paid employment, or even measure the current or future potential human capital of a country. Hence, complementary measures may help to show a more comprehensive picture of an economy.
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  • Statistical profiling of unemployed jobseekers

    The increasing availability of big data allows for the profiling of unemployed jobseekers via statistical models

    Statistical models can help public employment services to identify factors associated with long-term unemployment and to identify at-risk groups. Such profiling models will likely become more prominent as increasing availability of big data combined with new machine learning techniques improve their predictive power. However, to achieve the best results, a continuous dialogue between data analysts, policymakers, and case workers is key. Indeed, when developing and implementing such tools, normative decisions are required. Profiling practices can misclassify many individuals, and they can reinforce but also prevent existing patterns of discrimination.
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  • Correspondence testing studies Updated

    What is there to learn about discrimination in hiring?

    Dan-Olof Rooth, January 2021
    Anti-discrimination policies play an important role in public discussions. However, identifying discriminatory practices in the labor market is not an easy task. Correspondence testing provides a credible way to reveal discrimination in hiring and provide hard facts for policies, and it has provided evidence of discrimination in hiring across almost all continents except Africa. The method involves sending matched pairs of identical job applications to employers posting jobs—the only difference being a characteristic that signals membership to a group.
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  • Recruiting intensity Updated

    Recruiting intensity is critical for understanding fluctuations in the labor market

    R. Jason Faberman, July 2020
    When hiring new workers, employers use a wide variety of different recruiting methods in addition to posting a vacancy announcement, such as adjusting education, experience, or technical requirements, or offering higher wages. The intensity with which employers make use of these alternative methods can vary widely depending on a firm’s performance and with the business cycle. In fact, persistently low recruiting intensity partly helps to explain the sluggish pace of job growth in the US economy following the Great Recession, and the historically subpar wage growth during the subsequent expansion.
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  • Using natural resource shocks to study economic behavior

    Natural resource shocks can help studying how low-skilled men respond to changes in labor market conditions

    Dan A. Black, December 2019
    In the context of growing worldwide inequality, it is important to know what happens when the demand for low-skilled workers changes. Because natural resource shocks are global in nature, but have highly localized impacts on labor prospects in resource extraction areas, they offer a unique opportunity to evaluate low-skilled men's behavior when faced with extreme variations in local labor market conditions. This situation can be utilized to evaluate a broad range of outcomes, from education and income, to marital and fertility status, to voting behavior.
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  • Transparency in empirical economic research

    Open science can enhance research credibility, but only with the correct incentives

    The open science and research transparency movement aims to make the research process more visible and to strengthen the credibility of results. Examples of open research practices include open data, pre-registration, and replication. Open science proponents argue that making data and codes publicly available enables researchers to evaluate the truth of a claim and improve its credibility. Opponents often counter that replications are costly and that open science efforts are not always rewarded with publication of results.
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  • Measuring income inequality

    Summary measures of inequality differ from one another and give different pictures of the evolution of economic inequality over time

    Ija Trapeznikova, July 2019
    Economists use various metrics for measuring income inequality. Here, the most commonly used measures—the Lorenz curve, the Gini coefficient, decile ratios, the Palma ratio, and the Theil index—are discussed in relation to their benefits and limitations. Equally important is the choice of what to measure: pre-tax and after-tax income, consumption, and wealth are useful indicators; and different sources of income such as wages, capital gains, taxes, and benefits can be examined. Understanding the dimensions of economic inequality is a key first step toward choosing the right policies to address it.
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  • The importance and challenges of measuring work hours Updated

    Measuring work hours correctly is important, but different surveys can tell different stories

    Work hours are key components in estimating productivity growth and hourly wages as well as being a useful cyclical indicator in their own right, so measuring them correctly is important. The US Bureau of Labor Statistics (BLS) collects data on work hours in several surveys and publishes four widely used series that measure average weekly hours. The series tell different stories about average weekly hours and trends in those hours but qualitatively similar stories about the cyclical behavior of work hours. The research summarized here explains the differences in levels, but only some of the differences in trends.
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  • Measuring individual risk preferences

    Incentivized measures are considered to be the gold standard in measuring individuals’ risk preferences, but is that correct?

    Catherine C. Eckel, June 2019
    Risk aversion is an important factor in many settings, including individual decisions about investment or occupational choice, and government choices about policies affecting environmental, industrial, or health risks. Risk preferences are measured using surveys or incentivized games with real consequences. Reviewing the different approaches to measuring individual risk aversion shows that the best approach will depend on the question being asked and the study's target population. In particular, economists’ gold standard of incentivized games may not be superior to surveys in all settings.
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