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The current value of the Consumer Credit in China is 55.961 T CNY. The Consumer Credit in China increased to 55.961 T CNY on 8/1/2024, after it was 55.859 T CNY on 7/1/2024. From 1/1/2010 to 9/1/2024, the average GDP in China was 30 T CNY. The all-time high was reached on 1/1/2024 with 56.48 T CNY, while the lowest value was recorded on 1/1/2010 with 5.91 T CNY.
Consumer Credit ·
3 years
5 years
10 years
25 Years
Max
Consumer Loans | |
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1/1/2010 | 5.91 T CNY |
2/1/2010 | 6.03 T CNY |
3/1/2010 | 6.19 T CNY |
4/1/2010 | 6.41 T CNY |
5/1/2010 | 6.59 T CNY |
6/1/2010 | 6.74 T CNY |
7/1/2010 | 6.85 T CNY |
8/1/2010 | 6.97 T CNY |
9/1/2010 | 7.12 T CNY |
10/1/2010 | 7.23 T CNY |
11/1/2010 | 7.38 T CNY |
12/1/2010 | 7.51 T CNY |
1/1/2011 | 7.59 T CNY |
2/1/2011 | 7.64 T CNY |
3/1/2011 | 7.8 T CNY |
4/1/2011 | 7.93 T CNY |
5/1/2011 | 8.05 T CNY |
6/1/2011 | 8.18 T CNY |
7/1/2011 | 8.29 T CNY |
8/1/2011 | 8.41 T CNY |
9/1/2011 | 8.53 T CNY |
10/1/2011 | 8.63 T CNY |
11/1/2011 | 8.75 T CNY |
12/1/2011 | 8.87 T CNY |
1/1/2012 | 8.96 T CNY |
2/1/2012 | 8.97 T CNY |
3/1/2012 | 9.11 T CNY |
4/1/2012 | 9.18 T CNY |
5/1/2012 | 9.31 T CNY |
6/1/2012 | 9.45 T CNY |
7/1/2012 | 9.58 T CNY |
8/1/2012 | 9.75 T CNY |
9/1/2012 | 9.97 T CNY |
10/1/2012 | 10.08 T CNY |
11/1/2012 | 10.27 T CNY |
12/1/2012 | 10.44 T CNY |
1/1/2013 | 10.73 T CNY |
2/1/2013 | 10.78 T CNY |
3/1/2013 | 11.02 T CNY |
4/1/2013 | 11.27 T CNY |
5/1/2013 | 11.53 T CNY |
6/1/2013 | 11.75 T CNY |
7/1/2013 | 11.96 T CNY |
8/1/2013 | 12.19 T CNY |
9/1/2013 | 12.43 T CNY |
10/1/2013 | 12.6 T CNY |
11/1/2013 | 12.82 T CNY |
12/1/2013 | 12.97 T CNY |
1/1/2014 | 13.29 T CNY |
2/1/2014 | 13.3 T CNY |
3/1/2014 | 13.55 T CNY |
4/1/2014 | 13.73 T CNY |
5/1/2014 | 13.96 T CNY |
6/1/2014 | 14.19 T CNY |
7/1/2014 | 14.36 T CNY |
8/1/2014 | 14.53 T CNY |
9/1/2014 | 14.74 T CNY |
10/1/2014 | 14.89 T CNY |
11/1/2014 | 15.13 T CNY |
12/1/2014 | 15.37 T CNY |
1/1/2015 | 15.47 T CNY |
2/1/2015 | 15.61 T CNY |
3/1/2015 | 15.81 T CNY |
4/1/2015 | 16.08 T CNY |
5/1/2015 | 16.35 T CNY |
6/1/2015 | 16.72 T CNY |
7/1/2015 | 16.99 T CNY |
8/1/2015 | 17.33 T CNY |
9/1/2015 | 17.7 T CNY |
10/1/2015 | 17.91 T CNY |
11/1/2015 | 18.31 T CNY |
12/1/2015 | 18.66 T CNY |
1/1/2016 | 19.18 T CNY |
2/1/2016 | 19.2 T CNY |
3/1/2016 | 19.77 T CNY |
4/1/2016 | 20.21 T CNY |
5/1/2016 | 20.75 T CNY |
6/1/2016 | 21.37 T CNY |
7/1/2016 | 21.85 T CNY |
8/1/2016 | 22.47 T CNY |
9/1/2016 | 23.04 T CNY |
10/1/2016 | 23.48 T CNY |
11/1/2016 | 24.14 T CNY |
12/1/2016 | 24.64 T CNY |
1/1/2017 | 25.27 T CNY |
2/1/2017 | 25.58 T CNY |
3/1/2017 | 26.25 T CNY |
4/1/2017 | 26.81 T CNY |
5/1/2017 | 27.37 T CNY |
6/1/2017 | 28 T CNY |
7/1/2017 | 28.53 T CNY |
8/1/2017 | 29.1 T CNY |
9/1/2017 | 29.72 T CNY |
10/1/2017 | 30.16 T CNY |
11/1/2017 | 30.69 T CNY |
12/1/2017 | 30.98 T CNY |
1/1/2018 | 31.68 T CNY |
2/1/2018 | 31.92 T CNY |
3/1/2018 | 32.38 T CNY |
4/1/2018 | 32.87 T CNY |
5/1/2018 | 33.37 T CNY |
6/1/2018 | 33.91 T CNY |
7/1/2018 | 34.48 T CNY |
8/1/2018 | 35.06 T CNY |
9/1/2018 | 35.65 T CNY |
10/1/2018 | 36.21 T CNY |
11/1/2018 | 36.79 T CNY |
12/1/2018 | 37.19 T CNY |
1/1/2019 | 37.94 T CNY |
2/1/2019 | 37.92 T CNY |
3/1/2019 | 38.6 T CNY |
4/1/2019 | 39.07 T CNY |
5/1/2019 | 39.62 T CNY |
6/1/2019 | 40.17 T CNY |
7/1/2019 | 40.62 T CNY |
8/1/2019 | 41.17 T CNY |
9/1/2019 | 41.75 T CNY |
10/1/2019 | 42.15 T CNY |
11/1/2019 | 42.75 T CNY |
12/1/2019 | 43.3 T CNY |
1/1/2020 | 43.72 T CNY |
2/1/2020 | 43.42 T CNY |
3/1/2020 | 44.04 T CNY |
4/1/2020 | 44.53 T CNY |
5/1/2020 | 45.04 T CNY |
6/1/2020 | 45.67 T CNY |
7/1/2020 | 46.26 T CNY |
8/1/2020 | 46.87 T CNY |
9/1/2020 | 47.48 T CNY |
10/1/2020 | 47.87 T CNY |
11/1/2020 | 48.44 T CNY |
12/1/2020 | 48.85 T CNY |
1/1/2021 | 49.62 T CNY |
2/1/2021 | 49.63 T CNY |
3/1/2021 | 50.27 T CNY |
4/1/2021 | 50.7 T CNY |
5/1/2021 | 51.14 T CNY |
6/1/2021 | 51.61 T CNY |
7/1/2021 | 51.97 T CNY |
8/1/2021 | 52.37 T CNY |
9/1/2021 | 52.85 T CNY |
10/1/2021 | 53.31 T CNY |
11/1/2021 | 53.93 T CNY |
12/1/2021 | 54.16 T CNY |
1/1/2022 | 54.61 T CNY |
2/1/2022 | 54.27 T CNY |
3/1/2022 | 54.54 T CNY |
4/1/2022 | 54.39 T CNY |
5/1/2022 | 54.48 T CNY |
6/1/2022 | 54.83 T CNY |
7/1/2022 | 54.9 T CNY |
8/1/2022 | 55.08 T CNY |
9/1/2022 | 55.3 T CNY |
10/1/2022 | 55.26 T CNY |
11/1/2022 | 55.36 T CNY |
12/1/2022 | 55.34 T CNY |
1/1/2023 | 55.24 T CNY |
2/1/2023 | 55.18 T CNY |
3/1/2023 | 55.6 T CNY |
4/1/2023 | 55.33 T CNY |
5/1/2023 | 55.37 T CNY |
6/1/2023 | 55.65 T CNY |
7/1/2023 | 55.5 T CNY |
8/1/2023 | 55.59 T CNY |
9/1/2023 | 55.98 T CNY |
10/1/2023 | 56.01 T CNY |
11/1/2023 | 56.15 T CNY |
12/1/2023 | 56.14 T CNY |
1/1/2024 | 56.48 T CNY |
2/1/2024 | 55.96 T CNY |
3/1/2024 | 56.22 T CNY |
4/1/2024 | 55.86 T CNY |
5/1/2024 | 55.79 T CNY |
6/1/2024 | 55.96 T CNY |
7/1/2024 | 55.86 T CNY |
8/1/2024 | 55.96 T CNY |
Consumer Credit History
Date | Value |
---|---|
8/1/2024 | 55.961 T CNY |
7/1/2024 | 55.859 T CNY |
6/1/2024 | 55.964 T CNY |
5/1/2024 | 55.786 T CNY |
4/1/2024 | 55.857 T CNY |
3/1/2024 | 56.218 T CNY |
2/1/2024 | 55.961 T CNY |
1/1/2024 | 56.48 T CNY |
12/1/2023 | 56.138 T CNY |
11/1/2023 | 56.155 T CNY |
Similar Macro Indicators to Consumer Credit
Name | Current | Previous | Frequency |
---|---|---|---|
🇨🇳 Bank loan interest rate | 4.35 % | 4.35 % | frequency_daily |
🇨🇳 Consumer Confidence | 88.2 points | 89.4 points | 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 MoM | -0.12 % | 0.23 % | Monthly |
🇨🇳 Retail Sales YoY | 4.8 % | 3.2 % | Monthly |
Macro pages for other countries in Asia
- 🇮🇳India
- 🇮🇩Indonesia
- 🇯🇵Japan
- 🇸🇦Saudi Arabia
- 🇸🇬Singapore
- 🇰🇷South Korea
- 🇹🇷Turkey
- 🇦🇫Afghanistan
- 🇦🇲Armenia
- 🇦🇿Azerbaijan
- 🇧🇭Bahrain
- 🇧🇩Bangladesh
- 🇧🇹Bhutan
- 🇧🇳Brunei
- 🇰🇭Cambodia
- 🇹🇱East Timor
- 🇬🇪Georgia
- 🇭🇰Hong Kong
- 🇮🇷Iran
- 🇮🇶Iraq
- 🇮🇱Israel
- 🇯🇴Jordan
- 🇰🇿Kazakhstan
- 🇰🇼Kuwait
- 🇰🇬Kyrgyzstan
- 🇱🇦Laos
- 🇱🇧Lebanon
- 🇲🇴Macau
- 🇲🇾Malaysia
- 🇲🇻Maldives
- 🇲🇳Mongolia
- 🇲🇲Myanmar
- 🇳🇵Nepal
- 🇰🇵North Korea
- 🇴🇲Oman
- 🇵🇰Pakistan
- 🇵🇸Palestine
- 🇵🇭Philippines
- 🇶🇦Qatar
- 🇱🇰Sri Lanka
- 🇸🇾Syria
- 🇹🇼Taiwan
- 🇹🇯Tajikistan
- 🇹🇭Thailand
- 🇹🇲Turkmenistan
- 🇦🇪United Arab Emirates
- 🇺🇿Uzbekistan
- 🇻🇳Vietnam
- 🇾🇪Yemen
What is Consumer Credit?
Consumer Credit: A Cornerstone of Macroeconomic Analysis Welcome to Eulerpool, where we delve into the intricacies of macroeconomic data to provide comprehensive, data-driven insights. One of the critical categories in our macroeconomic analysis is 'Consumer Credit'. This term refers to the borrowing habits and debt patterns of individuals, which play a pivotal role in economic activity and overall financial stability. Understanding consumer credit is essential for economists, policymakers, financial analysts, and even individual investors who seek to navigate the complexities of modern economies. In this detailed overview, we aim to dissect the components, significance, and implications of consumer credit within the broader macroeconomic framework. Consumer Credit, at its core, involves various types of loans that individuals can access to purchase goods and services. It encompasses credit card debt, automobile loans, personal loans, student loans, and mortgages, among others. The dynamics of consumer credit can significantly influence economic growth, consumer spending patterns, monetary policy effectiveness, and financial stability. By analyzing trends in consumer credit, one can gain valuable insights into the health and direction of an economy. Historically, consumer credit has been a double-edged sword. On one hand, it enables consumers to make purchases that they might otherwise have postponed, thereby stimulating economic activity. On the other hand, excessive borrowing can lead to higher debt levels, which might become unsustainable and pose risks to both individuals and the broader financial system. Let's examine each of these aspects closely. Consumer spending is a major component of Gross Domestic Product (GDP) in many advanced economies. When consumers have access to credit, they are more likely to spend, driving demand for goods and services. This demand, in turn, spurs production, investment, and job creation, creating a virtuous cycle that propels economic growth. For instance, during periods of economic expansion, robust consumer credit growth often correlates with increased consumer spending and higher GDP growth rates. However, when consumer credit growth becomes unmanageable, it can lead to a buildup of household debt. High levels of indebtedness can constrain future spending as households prioritize debt repayment over consumption. This phenomenon is known as the "debt overhang" effect. During economic downturns, the burden of debt can exacerbate the downturn as indebted households cut back on spending, leading to a vicious cycle of reduced demand, lower production, and higher unemployment. The role of consumer credit in monetary policy cannot be overstated. Central banks often monitor consumer credit trends to gauge the effectiveness of monetary policy measures. For example, when interest rates are lowered to stimulate economic activity, one of the channels through which this policy works is by making borrowing cheaper for consumers. An increase in consumer credit can signal that monetary policy is having the desired effect, boosting spending and investment. Conversely, if consumer credit remains sluggish despite lower interest rates, it may indicate underlying issues such as low consumer confidence or tighter lending standards. Financial stability is another crucial aspect linked to consumer credit. The 2008 global financial crisis vividly demonstrated how excessive consumer borrowing, particularly in the housing market, can lead to severe economic repercussions. High levels of consumer debt can strain financial institutions if borrowers default on their loans. As seen during the crisis, the contagion effect can spread rapidly, affecting the entire financial system and the broader economy. Regulators and policymakers therefore closely monitor consumer credit levels and lending practices to mitigate systemic risks. At Eulerpool, we analyze a wide range of macroeconomic data, and consumer credit is a significant category. Our data can help users understand various dimensions of consumer credit, such as total outstanding credit, delinquency rates, average interest rates on different types of loans, and the distribution of credit across different demographic groups. These data points are vital for a holistic understanding of the consumer credit landscape. One of the key metrics in this domain is the credit-to-GDP ratio, which provides a sense of how much consumer debt is relative to the size of the economy. A rising credit-to-GDP ratio suggests that debt is growing faster than the economy, which can be a red flag indicating potential over-leverage. Another important metric is the household debt service ratio, which measures the portion of disposable income that households spend on debt repayments. Higher ratios indicate greater financial strain on households, which can affect their ability to consume and save. Delinquency rates are also a critical indicator of the health of consumer credit. Rising delinquency rates suggest that more consumers are struggling to repay their debts, which can be a precursor to higher default rates and financial instability. By tracking delinquency rates across different types of loans, one can identify emerging risks in specific sectors, such as student loans or housing. Interest rates on consumer credit are another key focus area. They influence borrowing costs and thus consumer behavior. For instance, lower interest rates on mortgages can stimulate housing market activity, while higher credit card interest rates might discourage excessive spending and encourage savings. By analyzing trends in interest rates, one can gain insights into the cost of credit and its implications for consumer behavior and economic activity. The distribution of consumer credit across different demographic groups also provides valuable insights. For example, younger age groups might have higher levels of student loan debt, while older age groups might carry more mortgage debt. Understanding these patterns can help policymakers design targeted interventions to address specific issues, such as student loan forgiveness programs or mortgage relief measures. In conclusion, consumer credit is a multifaceted component of macroeconomic analysis that has far-reaching implications for economic growth, financial stability, and monetary policy. At Eulerpool, we strive to provide accurate and comprehensive data to help our users navigate this complex landscape. By understanding the intricacies of consumer credit, stakeholders can make informed decisions that promote sustainable economic development and financial well-being. Thank you for visiting Eulerpool, and we hope our insights into consumer credit prove valuable in your endeavors.