6 datasets found
  1. J

    Gains from trade: Demand, supply and idiosyncratic shocks (replication data)...

    • journaldata.zbw.eu
    pdf, zip
    Updated Mar 20, 2024
    + more versions
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    Ruben Dewitte; Bruno Merlevede; Glenn Rayp; Ruben Dewitte; Bruno Merlevede; Glenn Rayp (2024). Gains from trade: Demand, supply and idiosyncratic shocks (replication data) [Dataset]. http://doi.org/10.15456/jae.2024058.1334401813
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    pdf(261127), zip(245906692)Available download formats
    Dataset updated
    Mar 20, 2024
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Ruben Dewitte; Bruno Merlevede; Glenn Rayp; Ruben Dewitte; Bruno Merlevede; Glenn Rayp
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Firm-level sales are often used as a proxy for productivity to quantify welfare Gains from Trade (GFT) using firm-level data. This approach ignores the fact that heterogeneity in firm-level sales is driven by factors other than productivity. Our theoretical and empirical analysis reveals that using sales as a proxy conflates persistent productivity with transitory demand and supply shocks, resulting in an over-dispersed productivity distribution. Assigning this shock-inflated productivity to a modeled economy’s supply-side results in overestimated GFT. We show how to obtain unbiased productivity estimates, aggregate trade elasticities, and GFT estimates by exploiting the revenue production function from a single source country.

  2. É

    Inflation, annual around the world | TheGlobalEconomy.com

    • fr.theglobaleconomy.com
    csv, excel, xml
    Updated Mar 26, 2024
    + more versions
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    Globalen LLC (2024). Inflation, annual around the world | TheGlobalEconomy.com [Dataset]. fr.theglobaleconomy.com/rankings/inflation_annual/
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    csv, excel, xmlAvailable download formats
    Dataset updated
    Mar 26, 2024
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    Monde
    Description

    Inflation in the table below is defined as the percent change in the CPI from the same month last year. The first column of numbers shows the latest value available from the national authorities and the next two columns show the levels of annual inflation three months and one year prior to the latest release. The data are updated daily. Over long stretches of time - typically years - inflation is a byproduct of the expansion of money supply. In the short run the inflation rate fluctuates with economic growth as recessions slow down the increase in prices and rapid output growth accelerates it. Shits in exchange rates, commodity prices, and natural phenomena like droughts also have an impact. Over time, however, these factors have only a transitory effect and the only variable that matters is money supply growth. The control of inflation is delegated to central banks that typically try to balance between relatively low inflation and low unemployment. For more, you can read our articles about optimal inflation and the causes of inflation in the short run and the long run.

  3. J

    A Measure of Trend Wage Inflation

    • journaldata.zbw.eu
    pdf, zip
    Updated Mar 20, 2025
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    Richard Audoly; Martin Almuzara; Davide Melcangi; Richard Audoly; Martin Almuzara; Davide Melcangi (2025). A Measure of Trend Wage Inflation [Dataset]. http://doi.org/10.15456/jae.2025063.1717036120
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    pdf(79853), zip(383809)Available download formats
    Dataset updated
    Mar 20, 2025
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Richard Audoly; Martin Almuzara; Davide Melcangi; Richard Audoly; Martin Almuzara; Davide Melcangi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We extend time-series models that have so far been used to study price inflation (Stock and Watson 2016) and apply them to a micro-level data set containing worker-level information on hourly wages. We construct a measure of aggregate nominal wage growth that (i) filters out noise and very transitory movements, (ii) quantifies the importance of idiosyncratic factors for aggregate wage dynamics, and (iii) strongly co-moves with labor market tightness, unlike existing indicators of wage inflation. We show that our measure is a reliable real-time indicator of wage pressures and a good predictor of future wage growth.

  4. Indonesia, Vulnerability to Food Insecurity 2015

    • cloud.csiss.gmu.edu
    zipped shapefile
    Updated Jul 23, 2019
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    UN Humanitarian Data Exchange (2019). Indonesia, Vulnerability to Food Insecurity 2015 [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/indonesia-vulnerability-to-food-insecurity-2015
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    zipped shapefile(4692205)Available download formats
    Dataset updated
    Jul 23, 2019
    Dataset provided by
    United Nationshttp://un.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Indonesia
    Description

    The FSVA includes 13 indicators based on a review of data availability at the district level and their ability to measure various aspects of food and nutrition security. The FSVA divides these indicators into two sets: chronic food and nutrition insecurity and transitory food insecurity. Within chronic, indicators measure food availability, food access, and food utilization. The transitory indicators describe climatic and environmental factors that affect food insecurity from an availability and access perspective. The nine indicators that relate to chronic food insecurity are combined into a single composite indicator to describe the overall district food security classification.

  5. c

    Replication Data for: Consequences of transient and persistent changes in...

    • datosdeinvestigacion.conicet.gov.ar
    • ri.conicet.gov.ar
    Updated Jul 20, 2021
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    Crespo, José Emilio; Castelo, Marcela Karina; Martinez, Gustavo Agustin (2021). Replication Data for: Consequences of transient and persistent changes in environmental factors on the foraging behaviour of developing Blaberidae cockroaches [Dataset]. https://datosdeinvestigacion.conicet.gov.ar/handle/11336/254763
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    Dataset updated
    Jul 20, 2021
    Authors
    Crespo, José Emilio; Castelo, Marcela Karina; Martinez, Gustavo Agustin
    License

    Attribution-NonCommercial-ShareAlike 2.5 (CC BY-NC-SA 2.5)https://creativecommons.org/licenses/by-nc-sa/2.5/
    License information was derived automatically

    Dataset funded by
    Ministerio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica
    Description

    Son datos experimentales de laboratorio de orientacion y preferencia por diferentes tipos de macronutrientes ante diferentes condiciones de temperatura de cria y presion barometrica.

  6. o

    Replication data for: The Substitution Elasticity, Factor Shares, and the...

    • openicpsr.org
    • test.openicpsr.org
    Updated Oct 1, 2017
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    Robert S. Chirinko; Debdulal Mallick (2017). Replication data for: The Substitution Elasticity, Factor Shares, and the Low-Frequency Panel Model [Dataset]. http://doi.org/10.3886/E114105V1
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    Dataset updated
    Oct 1, 2017
    Dataset provided by
    American Economic Association
    Authors
    Robert S. Chirinko; Debdulal Mallick
    Description

    The value of the elasticity of substitution between labor and capital (σ) is a crucial assumption in understanding the secular decline in the labor share of income. This paper develops and implements a new strategy for estimating this crucial parameter by combining a low-pass filter with panel data to identify the low-frequency/long-run relations appropriate to production function estimation. Standard estimation methods, which do not filter out transitory variation, generate downwardly biased estimates of 40 percent to 70 percent relative to the benchmark value. Despite correcting for this bias, our preferred estimate of 0.40 is substantially below the Cobb-Douglas assumption of σ = 1.

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    Learn how you can add new datasets to our index.

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Ruben Dewitte; Bruno Merlevede; Glenn Rayp; Ruben Dewitte; Bruno Merlevede; Glenn Rayp (2024). Gains from trade: Demand, supply and idiosyncratic shocks (replication data) [Dataset]. http://doi.org/10.15456/jae.2024058.1334401813

Gains from trade: Demand, supply and idiosyncratic shocks (replication data)

Explore at:
pdf(261127), zip(245906692)Available download formats
Dataset updated
Mar 20, 2024
Dataset provided by
ZBW - Leibniz Informationszentrum Wirtschaft
Authors
Ruben Dewitte; Bruno Merlevede; Glenn Rayp; Ruben Dewitte; Bruno Merlevede; Glenn Rayp
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Firm-level sales are often used as a proxy for productivity to quantify welfare Gains from Trade (GFT) using firm-level data. This approach ignores the fact that heterogeneity in firm-level sales is driven by factors other than productivity. Our theoretical and empirical analysis reveals that using sales as a proxy conflates persistent productivity with transitory demand and supply shocks, resulting in an over-dispersed productivity distribution. Assigning this shock-inflated productivity to a modeled economy’s supply-side results in overestimated GFT. We show how to obtain unbiased productivity estimates, aggregate trade elasticities, and GFT estimates by exploiting the revenue production function from a single source country.

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