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The current value of the Retail Sales Month-over-Month (MoM) in United States is 0.5 %. The Retail Sales Month-over-Month (MoM) in United States decreased to 0.5 % on 3/1/2024, after it was 0.7 % on 2/1/2024. From 2/1/1992 to 5/1/2024, the average GDP in United States was 0.39 %. The all-time high was reached on 5/1/2020 with 18.8 %, while the lowest value was recorded on 4/1/2020 with -14.5 %.
Retail Sales Month-over-Month (MoM) ·
3 years
5 years
10 years
25 Years
Max
Retail Sales MoM | |
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2/1/1992 | 0.1 % |
4/1/1992 | 0.6 % |
5/1/1992 | 0.5 % |
6/1/1992 | 0.3 % |
7/1/1992 | 0.7 % |
8/1/1992 | 0.3 % |
9/1/1992 | 1 % |
10/1/1992 | 0.7 % |
11/1/1992 | 0.2 % |
12/1/1992 | 1.2 % |
1/1/1993 | 1.2 % |
4/1/1993 | 2.6 % |
5/1/1993 | 0.9 % |
7/1/1993 | 1.5 % |
9/1/1993 | 0.6 % |
10/1/1993 | 0.6 % |
11/1/1993 | 1 % |
12/1/1993 | 0.9 % |
2/1/1994 | 1.6 % |
3/1/1994 | 1.9 % |
6/1/1994 | 1.2 % |
7/1/1994 | 0.3 % |
8/1/1994 | 1.2 % |
9/1/1994 | 0.8 % |
10/1/1994 | 0.9 % |
11/1/1994 | 0.1 % |
12/1/1994 | 0.5 % |
1/1/1995 | 0.4 % |
3/1/1995 | 0.9 % |
4/1/1995 | 0.4 % |
5/1/1995 | 1 % |
6/1/1995 | 1.2 % |
8/1/1995 | 0.8 % |
9/1/1995 | 0.2 % |
11/1/1995 | 1.2 % |
12/1/1995 | 0.8 % |
2/1/1996 | 1.6 % |
3/1/1996 | 0.9 % |
4/1/1996 | 0.4 % |
5/1/1996 | 0.8 % |
7/1/1996 | 0.1 % |
9/1/1996 | 1.3 % |
10/1/1996 | 0.8 % |
12/1/1996 | 0.5 % |
1/1/1997 | 0.7 % |
2/1/1997 | 0.9 % |
3/1/1997 | 0.3 % |
6/1/1997 | 1.4 % |
7/1/1997 | 1.2 % |
8/1/1997 | 0.3 % |
9/1/1997 | 0.4 % |
11/1/1997 | 0.3 % |
12/1/1997 | 0.3 % |
1/1/1998 | 0.2 % |
3/1/1998 | 0.6 % |
4/1/1998 | 1.2 % |
5/1/1998 | 0.5 % |
6/1/1998 | 0.8 % |
9/1/1998 | 0.9 % |
10/1/1998 | 1.7 % |
11/1/1998 | 0.7 % |
12/1/1998 | 0.9 % |
1/1/1999 | 0.1 % |
2/1/1999 | 1.1 % |
3/1/1999 | 0.5 % |
4/1/1999 | 0.7 % |
5/1/1999 | 0.9 % |
6/1/1999 | 0.3 % |
7/1/1999 | 0.8 % |
8/1/1999 | 1.1 % |
9/1/1999 | 0.4 % |
10/1/1999 | 0.2 % |
11/1/1999 | 1.2 % |
12/1/1999 | 1.8 % |
2/1/2000 | 1.5 % |
3/1/2000 | 1.2 % |
5/1/2000 | 0.1 % |
6/1/2000 | 0.7 % |
8/1/2000 | 0.1 % |
9/1/2000 | 1.7 % |
1/1/2001 | 1.1 % |
4/1/2001 | 1.6 % |
5/1/2001 | 0.2 % |
8/1/2001 | 0.7 % |
10/1/2001 | 6.7 % |
2/1/2002 | 0.5 % |
4/1/2002 | 1.6 % |
6/1/2002 | 0.8 % |
7/1/2002 | 1 % |
8/1/2002 | 0.8 % |
10/1/2002 | 0.4 % |
11/1/2002 | 0.7 % |
12/1/2002 | 0.8 % |
1/1/2003 | 0.4 % |
3/1/2003 | 1.8 % |
5/1/2003 | 0.3 % |
6/1/2003 | 1.1 % |
7/1/2003 | 1 % |
8/1/2003 | 1.7 % |
11/1/2003 | 1.2 % |
1/1/2004 | 0.6 % |
2/1/2004 | 0.7 % |
3/1/2004 | 1.8 % |
5/1/2004 | 1.7 % |
7/1/2004 | 1.1 % |
8/1/2004 | 0.1 % |
9/1/2004 | 1.8 % |
10/1/2004 | 0.7 % |
11/1/2004 | 0.3 % |
12/1/2004 | 1.2 % |
2/1/2005 | 1.3 % |
3/1/2005 | 0.2 % |
4/1/2005 | 0.9 % |
6/1/2005 | 2.8 % |
7/1/2005 | 0.7 % |
9/1/2005 | 0.2 % |
11/1/2005 | 0.9 % |
1/1/2006 | 2.9 % |
3/1/2006 | 0.3 % |
4/1/2006 | 0.5 % |
6/1/2006 | 0.3 % |
7/1/2006 | 0.3 % |
8/1/2006 | 0.5 % |
11/1/2006 | 0.2 % |
12/1/2006 | 1.2 % |
2/1/2007 | 0.1 % |
3/1/2007 | 0.9 % |
5/1/2007 | 1.3 % |
7/1/2007 | 0.4 % |
8/1/2007 | 0.5 % |
9/1/2007 | 0.4 % |
10/1/2007 | 0.6 % |
11/1/2007 | 1 % |
1/1/2008 | 0.3 % |
3/1/2008 | 0.2 % |
5/1/2008 | 0.9 % |
6/1/2008 | 0.1 % |
1/1/2009 | 1.5 % |
4/1/2009 | 0.5 % |
5/1/2009 | 0.9 % |
6/1/2009 | 1.7 % |
7/1/2009 | 0.2 % |
8/1/2009 | 1.8 % |
10/1/2009 | 0.9 % |
11/1/2009 | 0.8 % |
12/1/2009 | 0.5 % |
2/1/2010 | 0.2 % |
3/1/2010 | 2.1 % |
4/1/2010 | 0.9 % |
7/1/2010 | 0.3 % |
8/1/2010 | 0.5 % |
9/1/2010 | 0.8 % |
10/1/2010 | 1.1 % |
11/1/2010 | 1 % |
12/1/2010 | 0.6 % |
1/1/2011 | 0.7 % |
2/1/2011 | 0.9 % |
3/1/2011 | 0.9 % |
4/1/2011 | 0.5 % |
6/1/2011 | 0.8 % |
8/1/2011 | 0.2 % |
9/1/2011 | 1 % |
10/1/2011 | 0.6 % |
11/1/2011 | 0.4 % |
12/1/2011 | 0.1 % |
1/1/2012 | 1 % |
2/1/2012 | 1.2 % |
3/1/2012 | 0.3 % |
7/1/2012 | 0.5 % |
8/1/2012 | 1.2 % |
9/1/2012 | 0.8 % |
11/1/2012 | 0.5 % |
12/1/2012 | 0.3 % |
1/1/2013 | 0.8 % |
2/1/2013 | 1.2 % |
5/1/2013 | 0.6 % |
6/1/2013 | 0.3 % |
7/1/2013 | 0.6 % |
9/1/2013 | 0.1 % |
10/1/2013 | 0.4 % |
11/1/2013 | 0.3 % |
12/1/2013 | 0.5 % |
2/1/2014 | 1.4 % |
3/1/2014 | 1 % |
4/1/2014 | 1 % |
5/1/2014 | 0.2 % |
6/1/2014 | 0.3 % |
7/1/2014 | 0.2 % |
8/1/2014 | 0.8 % |
10/1/2014 | 0.4 % |
11/1/2014 | 0.3 % |
3/1/2015 | 1.5 % |
4/1/2015 | 0.2 % |
5/1/2015 | 0.7 % |
6/1/2015 | 0.1 % |
7/1/2015 | 0.8 % |
11/1/2015 | 0.4 % |
12/1/2015 | 0.4 % |
2/1/2016 | 1 % |
4/1/2016 | 0.4 % |
5/1/2016 | 0.4 % |
6/1/2016 | 1.1 % |
8/1/2016 | 0.1 % |
9/1/2016 | 0.7 % |
10/1/2016 | 0.2 % |
12/1/2016 | 1.2 % |
1/1/2017 | 1.1 % |
4/1/2017 | 0.4 % |
6/1/2017 | 0.4 % |
8/1/2017 | 0.2 % |
9/1/2017 | 2 % |
10/1/2017 | 0.1 % |
11/1/2017 | 1.1 % |
12/1/2017 | 0.5 % |
2/1/2018 | 0.6 % |
4/1/2018 | 0.3 % |
5/1/2018 | 1.3 % |
7/1/2018 | 0.6 % |
10/1/2018 | 1.1 % |
11/1/2018 | 0.3 % |
1/1/2019 | 0.7 % |
2/1/2019 | 0.1 % |
3/1/2019 | 1.6 % |
4/1/2019 | 0.1 % |
5/1/2019 | 0.7 % |
6/1/2019 | 0.2 % |
7/1/2019 | 0.9 % |
8/1/2019 | 0.6 % |
10/1/2019 | 0.3 % |
11/1/2019 | 0.6 % |
12/1/2019 | 0.4 % |
1/1/2020 | 0.1 % |
5/1/2020 | 18.8 % |
6/1/2020 | 8.7 % |
7/1/2020 | 1.6 % |
8/1/2020 | 0.9 % |
9/1/2020 | 2 % |
12/1/2020 | 0.9 % |
1/1/2021 | 3.9 % |
3/1/2021 | 11 % |
4/1/2021 | 1 % |
6/1/2021 | 1.1 % |
8/1/2021 | 0.7 % |
9/1/2021 | 0.6 % |
10/1/2021 | 1.6 % |
11/1/2021 | 1.1 % |
1/1/2022 | 1.8 % |
2/1/2022 | 1 % |
3/1/2022 | 2.1 % |
4/1/2022 | 1.4 % |
6/1/2022 | 0.7 % |
8/1/2022 | 0.6 % |
10/1/2022 | 1.3 % |
1/1/2023 | 4.1 % |
4/1/2023 | 0.7 % |
5/1/2023 | 0.6 % |
7/1/2023 | 0.5 % |
8/1/2023 | 0.7 % |
9/1/2023 | 0.8 % |
11/1/2023 | 0.1 % |
12/1/2023 | 0.4 % |
2/1/2024 | 0.7 % |
3/1/2024 | 0.5 % |
Retail Sales Month-over-Month (MoM) History
Date | Value |
---|---|
3/1/2024 | 0.5 % |
2/1/2024 | 0.7 % |
12/1/2023 | 0.4 % |
11/1/2023 | 0.1 % |
9/1/2023 | 0.8 % |
8/1/2023 | 0.7 % |
7/1/2023 | 0.5 % |
5/1/2023 | 0.6 % |
4/1/2023 | 0.7 % |
1/1/2023 | 4.1 % |
Similar Macro Indicators to Retail Sales Month-over-Month (MoM)
Name | Current | Previous | Frequency |
---|---|---|---|
🇺🇸 Auto Loan Debt Balance | 1.616 Trillion USD | 1.607 Trillion USD | Quarter |
🇺🇸 Bank loan interest rate | 8 % | 8.5 % | Monthly |
🇺🇸 Consumer Confidence | 68.2 points | 69.1 points | Monthly |
🇺🇸 Consumer Loans | 6.4 B USD | 6.27 B USD | Monthly |
🇺🇸 Consumer spending | 16.112 T USD | 15.967 T USD | Quarter |
🇺🇸 Credit Balance Credit Cards | 1.115 Trillion USD | 1.129 Trillion USD | Quarter |
🇺🇸 Credit card accounts | 596.58 M | 594.75 M | Quarter |
🇺🇸 Current Economic Conditions in Michigan | 65.9 points | 69.6 points | Monthly |
🇺🇸 Disposable Personal Income | 21.856 T USD | 21.798 T USD | Monthly |
🇺🇸 Gasoline Prices | 0.83 USD/Liter | 0.85 USD/Liter | Monthly |
🇺🇸 Household Debt to GDP | 72.9 % of GDP | 73.4 % of GDP | Quarter |
🇺🇸 Index of Economic Optimism | 44.2 points | 40.5 points | Monthly |
🇺🇸 Michigan Consumer Expectations | 69.6 points | 68.8 points | Monthly |
🇺🇸 Mortgage Debt | 12.52 Trillion USD | 12.44 Trillion USD | Quarter |
🇺🇸 Personal Expenses | 0.2 % | 0.1 % | Monthly |
🇺🇸 Personal Income | 0.3 % | 0.2 % | Monthly |
🇺🇸 Personal Savings | 3.6 % | 3.6 % | Monthly |
🇺🇸 Private Sector Credit | 12.485 T USD | 12.47 T USD | Monthly |
🇺🇸 Redbook Index | 5.8 % | 5.3 % | frequency_weekly |
🇺🇸 Retail Sales Excluding Autos | 0.4 % | 0.1 % | Monthly |
🇺🇸 Retail Sales Excluding Gas and Autos MoM | 0.7 % | 0.3 % | Monthly |
🇺🇸 Retail Sales YoY | 1.7 % | 2.2 % | Monthly |
🇺🇸 Sales of retail stores | 2.332 B USD | 2.317 B USD | Monthly |
🇺🇸 Student Loan Debt Balance | 1.6 Trillion USD | 1.601 Trillion USD | Quarter |
🇺🇸 Total Debt Balance | 17.7 USD Trillion | 17.503 USD Trillion | Quarter |
🇺🇸 Used Car Prices MoM | -0.1 % | -0.5 % | Monthly |
🇺🇸 Used Car Prices YoY | -12.1 % | -14 % | Monthly |
The Retail Sales report in the US delivers an aggregated measure of sales for retail goods and services over a month. The report categorizes sales data from thirteen major types of retailers: Motor vehicle and parts dealers (approximately 20% of total sales), Food and beverage stores (13%), General merchandise stores (12.5%), Food services and drinking places (11%), Gasoline stations (10%), Nonstore retailers (9.2%), Building material and garden dealers (6%), Health and personal care stores (6%), Clothing and clothing accessories stores (5%), Miscellaneous store retailers (2.3%), Furniture stores (2%), Electronics and appliance stores (2%), and Sporting goods, hobby, book, and music stores (1.7%).
Macro pages for other countries in America
- 🇦🇷Argentina
- 🇦🇼Aruba
- 🇧🇸Bahamas
- 🇧🇧Barbados
- 🇧🇿Belize
- 🇧🇲Bermuda
- 🇧🇴Bolivia
- 🇧🇷Brazil
- 🇨🇦Canada
- 🇰🇾Cayman Islands
- 🇨🇱Chile
- 🇨🇴Colombia
- 🇨🇷Costa Rica
- 🇨🇺Cuba
- 🇩🇴Dominican Republic
- 🇪🇨Ecuador
- 🇸🇻El Salvador
- 🇬🇹Guatemala
- 🇬🇾Guyana
- 🇭🇹Haiti
- 🇭🇳Honduras
- 🇯🇲Jamaica
- 🇲🇽Mexico
- 🇳🇮Nicaragua
- 🇵🇦Panama
- 🇵🇾Paraguay
- 🇵🇪Peru
- 🇵🇷Puerto Rico
- 🇸🇷Suriname
- 🇹🇹Trinidad and Tobago
- 🇺🇾Uruguay
- 🇻🇪Venezuela
- 🇦🇬Antigua and Barbuda
- 🇩🇲Dominica
- 🇬🇩Grenada
What is Retail Sales Month-over-Month (MoM)?
Retail Sales MoM, or Month-over-Month retail sales, is a critical economic indicator that reflects the changes in consumer spending within the retail sector compared to the previous month. Retail sales data are essential in macroeconomic analysis, serving as a powerful barometer for assessing the overall health and direction of a nation's economy. On Eulerpool, we provide comprehensive and up-to-date retail sales data to help economists, financial analysts, and investors make informed decisions based on current economic conditions. Consumer spending is a crucial driver of economic growth, typically accounting for a significant portion of a country's Gross Domestic Product (GDP). By examining Retail Sales MoM figures, analysts can gain valuable insights into consumer behavior, sentiment, and confidence. A consistent increase in retail sales over several months may signal economic expansion, as consumers feel comfortable spending their disposable income. Conversely, a decline in retail sales may indicate economic contraction, suggesting that consumers are saving more or spending less due to uncertainty or economic challenges. The Retail Sales MoM metric includes a broad range of retail categories, such as automotive sales, clothing, electronics, food and beverages, and more. By assessing these individual components, analysts can identify which sectors are thriving and which are underperforming. This granular level of analysis allows for a comprehensive understanding of the retail landscape and helps predict future economic trends. Seasonality can have a significant impact on retail sales, necessitating careful interpretation of MoM data. For example, retail sales often increase during holiday seasons, such as Christmas, due to heightened consumer spending. To account for such seasonal variations, data may sometimes be seasonally adjusted to present a clearer picture of underlying trends. Analysts must be adept at distinguishing between seasonal effects and genuine changes in consumer behavior to draw accurate conclusions from the data. Moreover, Retail Sales MoM figures are often presented alongside other economic indicators to provide a more holistic view of the economy. For instance, retail sales data can be analyzed in conjunction with consumer confidence indices, employment rates, and inflation figures. Such a multifaceted analysis enables analysts to understand the intricate interplay between various economic factors and the retail sector's performance. From an investor's perspective, Retail Sales MoM data can be a valuable tool for making strategic decisions in the stock market. For instance, if the retail sales figures show robust growth, it may indicate a potential increase in the revenues of retail companies, prompting investors to consider purchasing stocks in the retail sector. On the other hand, weak retail sales data could lead to investor caution and a potential sell-off of retail stocks. Thus, staying informed about Retail Sales MoM trends is crucial for making sound investment decisions. In addition to its relevance for financial markets, Retail Sales MoM data also holds significant importance for policymakers. Central banks and government entities analyze retail sales figures to assess the effectiveness of economic policies and determine the need for intervention. For example, if retail sales are declining, policymakers may consider implementing measures to stimulate consumer spending, such as interest rate cuts or fiscal stimulus. Therefore, Retail Sales MoM data plays a vital role in shaping economic policy decisions. At Eulerpool, we understand the critical importance of providing accurate and timely macroeconomic data, including Retail Sales MoM figures. Our platform offers a user-friendly and comprehensive database of retail sales data, allowing users to track and analyze trends effectively. We employ sophisticated data collection and analysis techniques to ensure the reliability and accuracy of our information, enabling users to make well-informed economic, financial, and investment decisions. Furthermore, our platform offers tools for comparing retail sales data across different time periods and regions, facilitating a deeper understanding of global economic trends. By providing access to a wealth of detailed data, Eulerpool empowers users to conduct thorough and meaningful analyses that can drive strategic decision-making processes. Understanding Retail Sales MoM figures requires a keen appreciation of the multifaceted nature of consumer spending and broader economic conditions. Analysts must consider various factors, including changes in consumer preferences, technological advancements, and demographic shifts. For instance, the rise of e-commerce has significantly impacted traditional brick-and-mortar retail sales, necessitating an in-depth analysis of online versus offline sales trends. Moreover, geopolitical events and macroeconomic policies can dramatically influence retail sales. Tariffs, trade agreements, and diplomatic relations between countries can affect the import and export of goods, thereby impacting retail prices and consumer spending. Analysts must remain vigilant in monitoring such developments to accurately interpret Retail Sales MoM data and its implications for the broader economy. In conclusion, Retail Sales MoM is a vital economic indicator that provides significant insights into consumer spending patterns and overall economic health. Accurate interpretation of this data requires a comprehensive understanding of various factors influencing consumer behavior and the ability to contextualize retail sales within the broader economic landscape. By offering reliable and detailed retail sales data, Eulerpool supports economists, financial analysts, investors, and policymakers in making informed decisions to navigate the complexities of the modern economy efficiently. Our commitment to providing high-quality macroeconomic data ensures that users have access to the essential information needed to drive strategic and impactful outcomes.