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The current value of the Manufacturing Payrolls in France is 2.857 M . The Manufacturing Payrolls in France increased to 2.857 M on 3/1/2024, after it was 2.852 M on 12/1/2023. From 12/1/1970 to 6/1/2024, the average GDP in France was 3.88 M . The all-time high was reached on 6/1/1974 with 5.47 M , while the lowest value was recorded on 9/1/2017 with 2.76 M .
Manufacturing Payrolls ·
3 years
5 years
10 years
25 Years
Max
Manufacturing wages | |
---|---|
12/1/1970 | 5.15 M |
3/1/1971 | 5.16 M |
6/1/1971 | 5.19 M |
9/1/1971 | 5.23 M |
12/1/1971 | 5.23 M |
3/1/1972 | 5.24 M |
6/1/1972 | 5.26 M |
9/1/1972 | 5.29 M |
12/1/1972 | 5.32 M |
3/1/1973 | 5.37 M |
6/1/1973 | 5.39 M |
9/1/1973 | 5.42 M |
12/1/1973 | 5.45 M |
3/1/1974 | 5.46 M |
6/1/1974 | 5.47 M |
9/1/1974 | 5.46 M |
12/1/1974 | 5.41 M |
3/1/1975 | 5.36 M |
6/1/1975 | 5.31 M |
9/1/1975 | 5.26 M |
12/1/1975 | 5.25 M |
3/1/1976 | 5.27 M |
6/1/1976 | 5.29 M |
9/1/1976 | 5.3 M |
12/1/1976 | 5.29 M |
3/1/1977 | 5.28 M |
6/1/1977 | 5.26 M |
9/1/1977 | 5.25 M |
12/1/1977 | 5.25 M |
3/1/1978 | 5.22 M |
6/1/1978 | 5.19 M |
9/1/1978 | 5.16 M |
12/1/1978 | 5.14 M |
3/1/1979 | 5.12 M |
6/1/1979 | 5.11 M |
9/1/1979 | 5.11 M |
12/1/1979 | 5.1 M |
3/1/1980 | 5.1 M |
6/1/1980 | 5.08 M |
9/1/1980 | 5.04 M |
12/1/1980 | 4.99 M |
3/1/1981 | 4.95 M |
6/1/1981 | 4.89 M |
9/1/1981 | 4.85 M |
12/1/1981 | 4.84 M |
3/1/1982 | 4.83 M |
6/1/1982 | 4.84 M |
9/1/1982 | 4.82 M |
12/1/1982 | 4.8 M |
3/1/1983 | 4.76 M |
6/1/1983 | 4.73 M |
9/1/1983 | 4.71 M |
12/1/1983 | 4.67 M |
3/1/1984 | 4.64 M |
6/1/1984 | 4.6 M |
9/1/1984 | 4.57 M |
12/1/1984 | 4.53 M |
3/1/1985 | 4.49 M |
6/1/1985 | 4.46 M |
9/1/1985 | 4.43 M |
12/1/1985 | 4.42 M |
3/1/1986 | 4.4 M |
6/1/1986 | 4.38 M |
9/1/1986 | 4.35 M |
12/1/1986 | 4.32 M |
3/1/1987 | 4.29 M |
6/1/1987 | 4.27 M |
9/1/1987 | 4.24 M |
12/1/1987 | 4.22 M |
3/1/1988 | 4.21 M |
6/1/1988 | 4.21 M |
9/1/1988 | 4.21 M |
12/1/1988 | 4.21 M |
3/1/1989 | 4.22 M |
6/1/1989 | 4.24 M |
9/1/1989 | 4.26 M |
12/1/1989 | 4.26 M |
3/1/1990 | 4.27 M |
6/1/1990 | 4.28 M |
9/1/1990 | 4.27 M |
12/1/1990 | 4.26 M |
3/1/1991 | 4.23 M |
6/1/1991 | 4.2 M |
9/1/1991 | 4.17 M |
12/1/1991 | 4.14 M |
3/1/1992 | 4.11 M |
6/1/1992 | 4.07 M |
9/1/1992 | 4.03 M |
12/1/1992 | 3.97 M |
3/1/1993 | 3.92 M |
6/1/1993 | 3.86 M |
9/1/1993 | 3.82 M |
12/1/1993 | 3.79 M |
3/1/1994 | 3.76 M |
6/1/1994 | 3.76 M |
9/1/1994 | 3.75 M |
12/1/1994 | 3.75 M |
3/1/1995 | 3.76 M |
6/1/1995 | 3.77 M |
9/1/1995 | 3.77 M |
12/1/1995 | 3.76 M |
3/1/1996 | 3.74 M |
6/1/1996 | 3.72 M |
9/1/1996 | 3.71 M |
12/1/1996 | 3.69 M |
3/1/1997 | 3.69 M |
6/1/1997 | 3.69 M |
9/1/1997 | 3.68 M |
12/1/1997 | 3.68 M |
3/1/1998 | 3.69 M |
6/1/1998 | 3.7 M |
9/1/1998 | 3.71 M |
12/1/1998 | 3.69 M |
3/1/1999 | 3.68 M |
6/1/1999 | 3.67 M |
9/1/1999 | 3.67 M |
12/1/1999 | 3.68 M |
3/1/2000 | 3.68 M |
6/1/2000 | 3.7 M |
9/1/2000 | 3.73 M |
12/1/2000 | 3.75 M |
3/1/2001 | 3.76 M |
6/1/2001 | 3.75 M |
9/1/2001 | 3.75 M |
12/1/2001 | 3.73 M |
3/1/2002 | 3.71 M |
6/1/2002 | 3.69 M |
9/1/2002 | 3.67 M |
12/1/2002 | 3.65 M |
3/1/2003 | 3.63 M |
6/1/2003 | 3.61 M |
9/1/2003 | 3.58 M |
12/1/2003 | 3.56 M |
3/1/2004 | 3.53 M |
6/1/2004 | 3.5 M |
9/1/2004 | 3.48 M |
12/1/2004 | 3.46 M |
3/1/2005 | 3.44 M |
6/1/2005 | 3.42 M |
9/1/2005 | 3.4 M |
12/1/2005 | 3.38 M |
3/1/2006 | 3.36 M |
6/1/2006 | 3.35 M |
9/1/2006 | 3.34 M |
12/1/2006 | 3.32 M |
3/1/2007 | 3.31 M |
6/1/2007 | 3.3 M |
9/1/2007 | 3.28 M |
12/1/2007 | 3.27 M |
3/1/2008 | 3.26 M |
6/1/2008 | 3.24 M |
9/1/2008 | 3.22 M |
12/1/2008 | 3.2 M |
3/1/2009 | 3.15 M |
6/1/2009 | 3.1 M |
9/1/2009 | 3.06 M |
12/1/2009 | 3.03 M |
3/1/2010 | 2.99 M |
6/1/2010 | 2.97 M |
9/1/2010 | 2.95 M |
12/1/2010 | 2.94 M |
3/1/2011 | 2.94 M |
6/1/2011 | 2.94 M |
9/1/2011 | 2.93 M |
12/1/2011 | 2.93 M |
3/1/2012 | 2.92 M |
6/1/2012 | 2.91 M |
9/1/2012 | 2.91 M |
12/1/2012 | 2.9 M |
3/1/2013 | 2.89 M |
6/1/2013 | 2.87 M |
9/1/2013 | 2.87 M |
12/1/2013 | 2.86 M |
3/1/2014 | 2.85 M |
6/1/2014 | 2.85 M |
9/1/2014 | 2.83 M |
12/1/2014 | 2.82 M |
3/1/2015 | 2.82 M |
6/1/2015 | 2.81 M |
9/1/2015 | 2.8 M |
12/1/2015 | 2.79 M |
3/1/2016 | 2.78 M |
6/1/2016 | 2.77 M |
9/1/2016 | 2.77 M |
12/1/2016 | 2.77 M |
3/1/2017 | 2.77 M |
6/1/2017 | 2.77 M |
9/1/2017 | 2.76 M |
12/1/2017 | 2.77 M |
3/1/2018 | 2.77 M |
6/1/2018 | 2.77 M |
9/1/2018 | 2.77 M |
12/1/2018 | 2.78 M |
3/1/2019 | 2.79 M |
6/1/2019 | 2.79 M |
9/1/2019 | 2.8 M |
12/1/2019 | 2.8 M |
3/1/2020 | 2.79 M |
6/1/2020 | 2.77 M |
9/1/2020 | 2.77 M |
12/1/2020 | 2.77 M |
3/1/2021 | 2.78 M |
6/1/2021 | 2.79 M |
9/1/2021 | 2.8 M |
12/1/2021 | 2.8 M |
3/1/2022 | 2.81 M |
6/1/2022 | 2.81 M |
9/1/2022 | 2.82 M |
12/1/2022 | 2.82 M |
3/1/2023 | 2.83 M |
6/1/2023 | 2.84 M |
9/1/2023 | 2.84 M |
12/1/2023 | 2.85 M |
3/1/2024 | 2.86 M |
Manufacturing Payrolls History
Date | Value |
---|---|
3/1/2024 | 2.857 M |
12/1/2023 | 2.852 M |
9/1/2023 | 2.845 M |
6/1/2023 | 2.837 M |
3/1/2023 | 2.831 M |
12/1/2022 | 2.825 M |
9/1/2022 | 2.821 M |
6/1/2022 | 2.812 M |
3/1/2022 | 2.805 M |
12/1/2021 | 2.803 M |
Similar Macro Indicators to Manufacturing Payrolls
Name | Current | Previous | Frequency |
---|---|---|---|
🇫🇷 Average Weekly Hours | 31.1 Hours | 31.3 Hours | Quarter |
🇫🇷 Employed persons | 27.774 M | 27.663 M | Quarter |
🇫🇷 Employment Change | 0.2 % | 0.1 % | Quarter |
🇫🇷 Employment rate | 69 % | 68.8 % | Quarter |
🇫🇷 Full-time employment | 23.647 M | 23.376 M | Quarter |
🇫🇷 Initial Jobless Claims | -12,700 | -26,100 | Monthly |
🇫🇷 Job Opportunities | 309,900 | 305,000 | Monthly |
🇫🇷 Labor costs | 119.2 points | 118.5 points | Quarter |
🇫🇷 Labor force participation rate | 74.5 % | 74.5 % | Quarter |
🇫🇷 Long-term unemployment rate | 1.7 % | 1.8 % | Quarter |
🇫🇷 Minimum Wages | 1,766.92 EUR/Month | 1,766.92 EUR/Month | Quarter |
🇫🇷 Non-farm Payrolls | 27.13 M | 27.142 M | Quarter |
🇫🇷 Nonfarm Private Employment | 21.155 M | 21.163 M | Quarter |
🇫🇷 Part-time work | 4.801 M | 4.768 M | Quarter |
🇫🇷 Population | 68.14 M | 67.93 M | Annually |
🇫🇷 Productivity | 100.152 points | 100.052 points | Quarter |
🇫🇷 Retirement Age Men | 62.25 Years | 62 Years | Annually |
🇫🇷 Retirement Age Women | 62.5 Years | 62.25 Years | Annually |
🇫🇷 State payroll accounting | 6.036 M | 6.02 M | Quarter |
🇫🇷 Unemployed Persons | 2.835 M | 2.816 M | Monthly |
🇫🇷 Unemployment Rate | 7.3 % | 7.5 % | Quarter |
🇫🇷 Wage Growth | 2.9 % | 3.3 % | Quarter |
🇫🇷 Wages | 3,466 EUR/Month | 3,321 EUR/Month | Annually |
🇫🇷 Wages in Manufacturing | 119.9 points | 119.2 points | Quarter |
🇫🇷 Youth Unemployment Rate | 17.7 % | 17.3 % | Monthly |
Macro pages for other countries in Europe
- 🇦🇱Albania
- 🇦🇹Austria
- 🇧🇾Belarus
- 🇧🇪Belgium
- 🇧🇦Bosnia and Herzegovina
- 🇧🇬Bulgaria
- 🇭🇷Croatia
- 🇨🇾Cyprus
- 🇨🇿Czech Republic
- 🇩🇰Denmark
- 🇪🇪Estonia
- 🇫🇴Faroe Islands
- 🇫🇮Finland
- 🇩🇪Germany
- 🇬🇷Greece
- 🇭🇺Hungary
- 🇮🇸Island
- 🇮🇪Ireland
- 🇮🇹Italy
- 🇽🇰Kosovo
- 🇱🇻Latvia
- 🇱🇮Liechtenstein
- 🇱🇹Lithuania
- 🇱🇺Luxembourg
- 🇲🇰North Macedonia
- 🇲🇹Malta
- 🇲🇩Moldova
- 🇲🇨Monaco
- 🇲🇪Montenegro
- 🇳🇱Netherlands
- 🇳🇴Norway
- 🇵🇱Poland
- 🇵🇹Portugal
- 🇷🇴Romania
- 🇷🇺Russia
- 🇷🇸Serbia
- 🇸🇰Slovakia
- 🇸🇮Slovenia
- 🇪🇸Spain
- 🇸🇪Sweden
- 🇨🇭Switzerland
- 🇺🇦Ukraine
- 🇬🇧United Kingdom
- 🇦🇩Andorra
What is Manufacturing Payrolls?
Manufacturing Payrolls: A Critical Indicator for Economic Health Manufacturing payrolls stand as a pivotal barometer for assessing the overall economic health of a nation. On Eulerpool, where macroeconomic data is meticulously curated and displayed for professional scrutiny, manufacturing payrolls represent a vital segment. This category provides profound insights into industrial productivity, employment trends, wage growth, and broader economic stability. In essence, manufacturing payrolls refer to the total compensation paid to individuals employed in the manufacturing sector. This includes wages, salaries, and other forms of compensation. By examining these payrolls, experts can evaluate the immediate and long-term performance of the manufacturing industry, which is foundational to any robust economy. One primary reason that manufacturing payrolls are so closely monitored is their role in employment statistics. Manufacturing is traditionally labor-intensive, thus contributing significantly to job creation. Variations in payroll data can indicate shifting employment trends. A rising payroll often translates to increased job creation, highlighting economic growth and robustness. Conversely, stagnant or declining payrolls could signify economic distress, prompting in-depth analysis and potential policy adjustments. Moreover, manufacturing payrolls serve as an indicator of wage growth within the sector. With changing economic conditions, wages within the manufacturing sector can fluctuate. A rise in payrolls might suggest not only an increase in employment but also a corresponding rise in wage rates, indicative of higher spending power among workers. This, in turn, can stimulate consumer spending, driving further economic growth. Conversely, stagnant wages, despite rising employment numbers, could denote potential issues in labor negotiations or an oversupply of labor, both of which warrant further investigation. Analyzing manufacturing payrolls also provides insights into industrial productivity. Enhanced payroll figures could imply increased productivity driven by higher demand for manufactured goods. This can be particularly illuminating during economic cycles where consumer confidence and business investments oscillate. Greater demand typically necessitates a ramp-up in production capacities which, in a healthy economy, should reflect an increase in payrolls as more labor is required to meet production goals. However, it is crucial to differentiate between short-term spikes and sustainable growth trends for a thorough economic understanding. Particularly, the data on manufacturing payrolls is an indispensable tool for policymakers. Governments and economic planners rely on these figures to craft policies that help sustain industrial growth and stability. For instance, a consistent rise in payrolls might prompt investment in infrastructure or innovation grants aimed at bolstering manufacturing capacities. On the other hand, declining payrolls might push for intervention strategies to revive the sector, such as tax incentives, skill development programs, or measures to enhance export competitiveness. Furthermore, the impact of manufacturing payrolls extends beyond mere industrial data to affect broader economic parameters such as inflation and GDP growth. For example, a robust increase in manufacturing payrolls often correlates with economic expansion reflected in GDP growth. This is because manufacturing typically constitutes a substantial part of national output. Similarly, wage increases within payrolls can influence inflationary trends. Rising wages generally lead to higher disposable incomes and increased spending, eventually driving demand-led inflation. An in-depth understanding of these relationships is critical for stakeholders across the economic spectrum. Globalization and technological advancements further underscore the importance of keeping a close eye on manufacturing payrolls. As economies become more interconnected, fluctuations in one region's manufacturing sector can have ripple effects worldwide. For example, payroll increases in countries with robust manufacturing bases like China or Germany can influence global supply chains and international trade dynamics. Similarly, technological advances such as automation can alter payroll statistics, often leading to more efficient production processes but also requiring a reevaluation of workforce deployment and compensation structures. For investors, financial analysts, and business leaders who utilize the data available on Eulerpool, manufacturing payrolls offer a window into future market conditions. Investors often consider these payroll data points when making decisions about stock performance, particularly within the industrial and manufacturing sectors. A burgeoning payroll figure can be a harbinger of positive earnings reports and market expansions, paving the way for potentially lucrative investment opportunities. Similarly, understanding the intricacies of payroll data can assist businesses in strategic planning, resource allocation, and competitive positioning. In summary, manufacturing payrolls encapsulate a myriad of economic dimensions, from employment trends and wage dynamics to productivity, policy-making, and global economic implications. Eulerpool’s sophisticated macroeconomic data displays provide a comprehensive platform for professionals to analyze these variables, enabling informed decisions and strategic interventions. By consistently monitoring manufacturing payroll data, stakeholders can ensure they remain attuned to underlying economic currents, ready to leverage insights for growth and stability. In the ever-evolving economic landscape, the relevance of manufacturing payrolls as a key indicator cannot be overstated. As such, it demands the continuous attention and analysis of those dedicated to understanding and shaping economic futures.