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The current value of the Retail Sales Month-over-Month (MoM) in China is 0.01 %. The Retail Sales Month-over-Month (MoM) in China decreased to 0.01 % on 4/1/2024, after it was 0.17 % on 3/1/2024. From 2/1/2011 to 6/1/2024, the average GDP in China was 0.71 %. The all-time high was reached on 5/1/2020 with 4.98 %, while the lowest value was recorded on 1/1/2020 with -10.77 %.
Retail Sales Month-over-Month (MoM) ·
3 years
5 years
10 years
25 Years
Max
Retail Sales MoM | |
---|---|
2/1/2011 | 1.35 % |
3/1/2011 | 1.26 % |
4/1/2011 | 1.3 % |
5/1/2011 | 1.39 % |
6/1/2011 | 1.49 % |
7/1/2011 | 1.57 % |
8/1/2011 | 1.5 % |
9/1/2011 | 1.33 % |
10/1/2011 | 1.36 % |
11/1/2011 | 1.26 % |
12/1/2011 | 1.41 % |
1/1/2012 | 0.19 % |
2/1/2012 | 1.01 % |
3/1/2012 | 1.21 % |
4/1/2012 | 0.93 % |
5/1/2012 | 1.11 % |
6/1/2012 | 1.12 % |
7/1/2012 | 1.03 % |
8/1/2012 | 1.11 % |
9/1/2012 | 1.32 % |
10/1/2012 | 1.18 % |
11/1/2012 | 1.21 % |
12/1/2012 | 1.23 % |
1/1/2013 | 0.14 % |
2/1/2013 | 0.87 % |
3/1/2013 | 1.5 % |
4/1/2013 | 0.99 % |
5/1/2013 | 0.95 % |
6/1/2013 | 1.09 % |
7/1/2013 | 1.08 % |
8/1/2013 | 0.92 % |
9/1/2013 | 1.02 % |
10/1/2013 | 0.96 % |
11/1/2013 | 1 % |
12/1/2013 | 0.94 % |
1/1/2014 | 0.85 % |
2/1/2014 | 0.91 % |
3/1/2014 | 1.1 % |
4/1/2014 | 0.81 % |
5/1/2014 | 1.01 % |
6/1/2014 | 0.79 % |
7/1/2014 | 0.94 % |
8/1/2014 | 0.8 % |
9/1/2014 | 0.79 % |
10/1/2014 | 0.91 % |
11/1/2014 | 0.87 % |
12/1/2014 | 0.96 % |
1/1/2015 | 0.8 % |
2/1/2015 | 0.84 % |
3/1/2015 | 0.86 % |
4/1/2015 | 0.74 % |
5/1/2015 | 0.81 % |
6/1/2015 | 0.93 % |
7/1/2015 | 0.79 % |
8/1/2015 | 0.89 % |
9/1/2015 | 0.83 % |
10/1/2015 | 0.81 % |
11/1/2015 | 0.91 % |
12/1/2015 | 0.82 % |
1/1/2016 | 0.82 % |
2/1/2016 | 0.6 % |
3/1/2016 | 0.9 % |
4/1/2016 | 0.81 % |
5/1/2016 | 0.8 % |
6/1/2016 | 0.91 % |
7/1/2016 | 0.79 % |
8/1/2016 | 0.89 % |
9/1/2016 | 0.81 % |
10/1/2016 | 0.72 % |
11/1/2016 | 0.94 % |
12/1/2016 | 0.86 % |
1/1/2017 | 0.55 % |
2/1/2017 | 0.98 % |
3/1/2017 | 0.85 % |
4/1/2017 | 0.76 % |
5/1/2017 | 0.79 % |
6/1/2017 | 0.91 % |
7/1/2017 | 0.77 % |
8/1/2017 | 0.82 % |
9/1/2017 | 0.83 % |
10/1/2017 | 0.81 % |
11/1/2017 | 0.79 % |
12/1/2017 | 0.6 % |
1/1/2018 | 0.63 % |
2/1/2018 | 0.51 % |
3/1/2018 | 0.85 % |
4/1/2018 | 0.75 % |
5/1/2018 | 0.15 % |
6/1/2018 | 0.71 % |
7/1/2018 | 0.88 % |
8/1/2018 | 0.62 % |
9/1/2018 | 0.65 % |
10/1/2018 | 0.75 % |
11/1/2018 | 0.6 % |
12/1/2018 | 0.74 % |
1/1/2019 | 0.83 % |
2/1/2019 | 0.49 % |
3/1/2019 | 0.79 % |
4/1/2019 | 0.81 % |
5/1/2019 | 0.48 % |
6/1/2019 | 0.57 % |
7/1/2019 | 0.59 % |
8/1/2019 | 0.56 % |
9/1/2019 | 0.89 % |
10/1/2019 | 0.8 % |
11/1/2019 | 0.82 % |
12/1/2019 | 0.7 % |
2/1/2020 | 0.94 % |
3/1/2020 | 0.87 % |
4/1/2020 | 0.44 % |
5/1/2020 | 4.98 % |
6/1/2020 | 1.02 % |
7/1/2020 | 0.24 % |
8/1/2020 | 0.63 % |
9/1/2020 | 3.73 % |
10/1/2020 | 0.14 % |
11/1/2020 | 1.23 % |
12/1/2020 | 0.85 % |
2/1/2021 | 0.68 % |
3/1/2021 | 0.93 % |
4/1/2021 | 0.02 % |
5/1/2021 | 0.89 % |
6/1/2021 | 0.28 % |
8/1/2021 | 0.52 % |
9/1/2021 | 0.21 % |
10/1/2021 | 0.64 % |
1/1/2022 | 0.06 % |
2/1/2022 | 0.49 % |
6/1/2022 | 2.56 % |
7/1/2022 | 1.82 % |
9/1/2022 | 0.28 % |
1/1/2023 | 0.72 % |
2/1/2023 | 2.09 % |
3/1/2023 | 1.02 % |
4/1/2023 | 1.06 % |
5/1/2023 | 0.15 % |
6/1/2023 | 0.01 % |
8/1/2023 | 0.75 % |
9/1/2023 | 0.36 % |
10/1/2023 | 0.42 % |
11/1/2023 | 0.16 % |
12/1/2023 | 0.18 % |
1/1/2024 | 0.04 % |
2/1/2024 | 0.03 % |
3/1/2024 | 0.17 % |
4/1/2024 | 0.01 % |
Retail Sales Month-over-Month (MoM) History
Date | Value |
---|---|
4/1/2024 | 0.01 % |
3/1/2024 | 0.17 % |
2/1/2024 | 0.03 % |
1/1/2024 | 0.04 % |
12/1/2023 | 0.18 % |
11/1/2023 | 0.16 % |
10/1/2023 | 0.42 % |
9/1/2023 | 0.36 % |
8/1/2023 | 0.75 % |
6/1/2023 | 0.01 % |
Similar Macro Indicators to Retail Sales Month-over-Month (MoM)
Name | Current | Previous | Frequency |
---|---|---|---|
🇨🇳 Bank loan interest rate | 4.35 % | 4.35 % | frequency_daily |
🇨🇳 Consumer Confidence | 88.2 points | 89.4 points | Monthly |
🇨🇳 Consumer Loans | 56.142 T CNY | 55.961 T CNY | Monthly |
🇨🇳 Consumer spending | 49.325 T CNY | 45.047 T CNY | Annually |
🇨🇳 Disposable Personal Income | 51,821 CNY | 49,282.94 CNY | Annually |
🇨🇳 Gasoline Prices | 0.84 USD/Liter | 0.9 USD/Liter | Monthly |
🇨🇳 Household Debt to GDP | 62.6 % of GDP | 62.1 % of GDP | Quarter |
🇨🇳 Retail Sales YoY | 4.8 % | 3.2 % | Monthly |
In China, the Retail Sales report offers an aggregated measure of retail goods and services sales over a specified period. Retail sales in China are characterized by seasonality, volatility, and significant importance to the overall economy.
Macro pages for other countries in Asia
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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.