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The current value of the Bankruptcies in Singapore is 79 Companies. The Bankruptcies in Singapore decreased to 79 Companies on 3/1/2024, after it was 99 Companies on 2/1/2024. From 1/1/2001 to 4/1/2024, the average GDP in Singapore was 182.2 Companies. The all-time high was reached on 1/1/2004 with 507 Companies, while the lowest value was recorded on 5/1/2020 with 7 Companies.
Bankruptcies ·
3 years
5 years
10 years
25 Years
Max
Bankruptcies | |
---|---|
1/1/2001 | 206 Companies |
2/1/2001 | 254 Companies |
3/1/2001 | 353 Companies |
4/1/2001 | 266 Companies |
5/1/2001 | 246 Companies |
6/1/2001 | 308 Companies |
7/1/2001 | 279 Companies |
8/1/2001 | 342 Companies |
9/1/2001 | 228 Companies |
10/1/2001 | 259 Companies |
11/1/2001 | 299 Companies |
12/1/2001 | 198 Companies |
1/1/2002 | 286 Companies |
2/1/2002 | 244 Companies |
3/1/2002 | 280 Companies |
4/1/2002 | 311 Companies |
5/1/2002 | 366 Companies |
6/1/2002 | 302 Companies |
7/1/2002 | 311 Companies |
8/1/2002 | 372 Companies |
9/1/2002 | 270 Companies |
10/1/2002 | 320 Companies |
11/1/2002 | 338 Companies |
12/1/2002 | 218 Companies |
1/1/2003 | 438 Companies |
2/1/2003 | 333 Companies |
3/1/2003 | 316 Companies |
4/1/2003 | 350 Companies |
5/1/2003 | 350 Companies |
6/1/2003 | 351 Companies |
7/1/2003 | 392 Companies |
8/1/2003 | 458 Companies |
9/1/2003 | 389 Companies |
10/1/2003 | 456 Companies |
11/1/2003 | 345 Companies |
12/1/2003 | 306 Companies |
1/1/2004 | 507 Companies |
2/1/2004 | 384 Companies |
3/1/2004 | 353 Companies |
4/1/2004 | 423 Companies |
5/1/2004 | 341 Companies |
6/1/2004 | 357 Companies |
7/1/2004 | 366 Companies |
8/1/2004 | 346 Companies |
9/1/2004 | 358 Companies |
10/1/2004 | 426 Companies |
11/1/2004 | 331 Companies |
12/1/2004 | 361 Companies |
1/1/2005 | 312 Companies |
2/1/2005 | 252 Companies |
3/1/2005 | 290 Companies |
4/1/2005 | 378 Companies |
5/1/2005 | 272 Companies |
6/1/2005 | 255 Companies |
7/1/2005 | 310 Companies |
8/1/2005 | 262 Companies |
9/1/2005 | 346 Companies |
10/1/2005 | 284 Companies |
11/1/2005 | 274 Companies |
12/1/2005 | 307 Companies |
1/1/2006 | 211 Companies |
2/1/2006 | 253 Companies |
3/1/2006 | 280 Companies |
4/1/2006 | 225 Companies |
5/1/2006 | 216 Companies |
6/1/2006 | 267 Companies |
7/1/2006 | 217 Companies |
8/1/2006 | 254 Companies |
9/1/2006 | 280 Companies |
10/1/2006 | 226 Companies |
11/1/2006 | 296 Companies |
12/1/2006 | 258 Companies |
1/1/2007 | 263 Companies |
2/1/2007 | 202 Companies |
3/1/2007 | 262 Companies |
4/1/2007 | 216 Companies |
5/1/2007 | 189 Companies |
6/1/2007 | 282 Companies |
7/1/2007 | 198 Companies |
8/1/2007 | 261 Companies |
9/1/2007 | 214 Companies |
10/1/2007 | 221 Companies |
11/1/2007 | 263 Companies |
12/1/2007 | 196 Companies |
1/1/2008 | 215 Companies |
2/1/2008 | 175 Companies |
3/1/2008 | 200 Companies |
4/1/2008 | 191 Companies |
5/1/2008 | 215 Companies |
6/1/2008 | 180 Companies |
7/1/2008 | 238 Companies |
8/1/2008 | 205 Companies |
9/1/2008 | 206 Companies |
10/1/2008 | 205 Companies |
11/1/2008 | 160 Companies |
12/1/2008 | 137 Companies |
1/1/2009 | 210 Companies |
2/1/2009 | 174 Companies |
3/1/2009 | 195 Companies |
4/1/2009 | 263 Companies |
5/1/2009 | 194 Companies |
6/1/2009 | 200 Companies |
7/1/2009 | 151 Companies |
8/1/2009 | 101 Companies |
9/1/2009 | 106 Companies |
10/1/2009 | 169 Companies |
11/1/2009 | 129 Companies |
12/1/2009 | 166 Companies |
1/1/2010 | 107 Companies |
2/1/2010 | 118 Companies |
3/1/2010 | 81 Companies |
4/1/2010 | 141 Companies |
5/1/2010 | 97 Companies |
6/1/2010 | 151 Companies |
7/1/2010 | 209 Companies |
8/1/2010 | 125 Companies |
9/1/2010 | 137 Companies |
10/1/2010 | 95 Companies |
11/1/2010 | 104 Companies |
12/1/2010 | 172 Companies |
1/1/2011 | 101 Companies |
2/1/2011 | 78 Companies |
3/1/2011 | 138 Companies |
4/1/2011 | 134 Companies |
5/1/2011 | 131 Companies |
6/1/2011 | 161 Companies |
7/1/2011 | 131 Companies |
8/1/2011 | 95 Companies |
9/1/2011 | 176 Companies |
10/1/2011 | 113 Companies |
11/1/2011 | 122 Companies |
12/1/2011 | 147 Companies |
1/1/2012 | 114 Companies |
2/1/2012 | 112 Companies |
3/1/2012 | 190 Companies |
4/1/2012 | 164 Companies |
5/1/2012 | 148 Companies |
6/1/2012 | 134 Companies |
7/1/2012 | 122 Companies |
8/1/2012 | 128 Companies |
9/1/2012 | 175 Companies |
10/1/2012 | 117 Companies |
11/1/2012 | 195 Companies |
12/1/2012 | 149 Companies |
1/1/2013 | 191 Companies |
2/1/2013 | 158 Companies |
3/1/2013 | 136 Companies |
4/1/2013 | 157 Companies |
5/1/2013 | 220 Companies |
6/1/2013 | 199 Companies |
7/1/2013 | 159 Companies |
8/1/2013 | 168 Companies |
9/1/2013 | 148 Companies |
10/1/2013 | 164 Companies |
11/1/2013 | 157 Companies |
12/1/2013 | 135 Companies |
1/1/2014 | 164 Companies |
2/1/2014 | 110 Companies |
3/1/2014 | 120 Companies |
4/1/2014 | 212 Companies |
5/1/2014 | 192 Companies |
6/1/2014 | 151 Companies |
7/1/2014 | 154 Companies |
8/1/2014 | 145 Companies |
9/1/2014 | 137 Companies |
10/1/2014 | 164 Companies |
11/1/2014 | 112 Companies |
12/1/2014 | 96 Companies |
1/1/2015 | 175 Companies |
2/1/2015 | 115 Companies |
3/1/2015 | 161 Companies |
4/1/2015 | 158 Companies |
5/1/2015 | 126 Companies |
6/1/2015 | 149 Companies |
7/1/2015 | 161 Companies |
8/1/2015 | 122 Companies |
9/1/2015 | 85 Companies |
10/1/2015 | 204 Companies |
11/1/2015 | 160 Companies |
12/1/2015 | 160 Companies |
1/1/2016 | 140 Companies |
2/1/2016 | 138 Companies |
3/1/2016 | 147 Companies |
4/1/2016 | 134 Companies |
5/1/2016 | 139 Companies |
6/1/2016 | 189 Companies |
7/1/2016 | 166 Companies |
8/1/2016 | 163 Companies |
9/1/2016 | 179 Companies |
10/1/2016 | 137 Companies |
11/1/2016 | 123 Companies |
12/1/2016 | 142 Companies |
1/1/2017 | 124 Companies |
2/1/2017 | 130 Companies |
3/1/2017 | 157 Companies |
4/1/2017 | 131 Companies |
5/1/2017 | 138 Companies |
6/1/2017 | 148 Companies |
7/1/2017 | 118 Companies |
8/1/2017 | 169 Companies |
9/1/2017 | 138 Companies |
10/1/2017 | 129 Companies |
11/1/2017 | 148 Companies |
12/1/2017 | 108 Companies |
1/1/2018 | 111 Companies |
2/1/2018 | 129 Companies |
3/1/2018 | 170 Companies |
4/1/2018 | 126 Companies |
5/1/2018 | 147 Companies |
6/1/2018 | 110 Companies |
7/1/2018 | 129 Companies |
8/1/2018 | 149 Companies |
9/1/2018 | 156 Companies |
10/1/2018 | 137 Companies |
11/1/2018 | 173 Companies |
12/1/2018 | 119 Companies |
1/1/2019 | 152 Companies |
2/1/2019 | 122 Companies |
3/1/2019 | 134 Companies |
4/1/2019 | 140 Companies |
5/1/2019 | 172 Companies |
6/1/2019 | 126 Companies |
7/1/2019 | 124 Companies |
8/1/2019 | 143 Companies |
9/1/2019 | 144 Companies |
10/1/2019 | 167 Companies |
11/1/2019 | 106 Companies |
12/1/2019 | 116 Companies |
1/1/2020 | 157 Companies |
2/1/2020 | 127 Companies |
3/1/2020 | 91 Companies |
4/1/2020 | 22 Companies |
5/1/2020 | 7 Companies |
6/1/2020 | 110 Companies |
7/1/2020 | 109 Companies |
8/1/2020 | 101 Companies |
9/1/2020 | 56 Companies |
10/1/2020 | 72 Companies |
11/1/2020 | 60 Companies |
12/1/2020 | 52 Companies |
1/1/2021 | 62 Companies |
2/1/2021 | 70 Companies |
3/1/2021 | 50 Companies |
4/1/2021 | 72 Companies |
5/1/2021 | 45 Companies |
6/1/2021 | 69 Companies |
7/1/2021 | 96 Companies |
8/1/2021 | 119 Companies |
9/1/2021 | 94 Companies |
10/1/2021 | 110 Companies |
11/1/2021 | 75 Companies |
12/1/2021 | 143 Companies |
1/1/2022 | 77 Companies |
2/1/2022 | 89 Companies |
3/1/2022 | 112 Companies |
4/1/2022 | 90 Companies |
5/1/2022 | 96 Companies |
6/1/2022 | 106 Companies |
7/1/2022 | 59 Companies |
8/1/2022 | 49 Companies |
9/1/2022 | 64 Companies |
10/1/2022 | 58 Companies |
11/1/2022 | 57 Companies |
12/1/2022 | 100 Companies |
1/1/2023 | 58 Companies |
2/1/2023 | 59 Companies |
3/1/2023 | 105 Companies |
4/1/2023 | 115 Companies |
5/1/2023 | 108 Companies |
6/1/2023 | 91 Companies |
7/1/2023 | 77 Companies |
8/1/2023 | 139 Companies |
9/1/2023 | 102 Companies |
10/1/2023 | 91 Companies |
11/1/2023 | 86 Companies |
12/1/2023 | 64 Companies |
1/1/2024 | 57 Companies |
2/1/2024 | 99 Companies |
3/1/2024 | 79 Companies |
Bankruptcies History
Date | Value |
---|---|
3/1/2024 | 79 Companies |
2/1/2024 | 99 Companies |
1/1/2024 | 57 Companies |
12/1/2023 | 64 Companies |
11/1/2023 | 86 Companies |
10/1/2023 | 91 Companies |
9/1/2023 | 102 Companies |
8/1/2023 | 139 Companies |
7/1/2023 | 77 Companies |
6/1/2023 | 91 Companies |
Similar Macro Indicators to Bankruptcies
Name | Current | Previous | Frequency |
---|---|---|---|
🇸🇬 Business Climate | 23 points | 22 points | Quarter |
🇸🇬 Changes in Inventory Levels | 921.3 M SGD | -1.472 B SGD | Quarter |
🇸🇬 Composite PMI | 55.2 points | 54.2 points | Monthly |
🇸🇬 Industrial production | 21 % | 2 % | Monthly |
🇸🇬 Industrial Production MoM | 6.7 % | 10.2 % | Monthly |
🇸🇬 Leading Indicator | 107.7 points | 106.4 points | Quarter |
🇸🇬 Manufacturing PMI | 50.4 points | 50.6 points | Monthly |
🇸🇬 Service Sentiment | 13 points | 7 points | Quarter |
🇸🇬 Vehicle Registrations | 6,132 Units | 5,803 Units | Monthly |
In Singapore, bankruptcies occur when insolvent corporations are unable to repay their debts to creditors and continue their operations.
Macro pages for other countries in Asia
- 🇨🇳China
- 🇮🇳India
- 🇮🇩Indonesia
- 🇯🇵Japan
- 🇸🇦Saudi Arabia
- 🇰🇷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 Bankruptcies?
Bankruptcies are a critical component of macroeconomic analysis, providing invaluable insights into the health and stability of economies around the world. Eulerpool, your trusted source for comprehensive macroeconomic data, is dedicated to offering a detailed and nuanced understanding of bankruptcies as a category within the broader economic landscape. Bankruptcy is a legal process that provides relief to individuals or corporations who are unable to repay their outstanding debts. This process serves as a vital safety mechanism within the financial system, both for debtors in distress and for creditors seeking to reclaim their assets. Bankruptcies can be driven by an array of factors, including but not limited to economic downturns, mismanagement, changing market conditions, and unforeseen crises such as pandemics or natural disasters. Each bankruptcy case provides unique data points that contribute to the global economic narrative, making this category an indispensable area of study for economists, policy makers, and financial analysts. At Eulerpool, we categorize and display bankruptcy data in a way that allows for deep macroeconomic analysis. By examining trends in bankruptcies, economists and analysts can infer a lot about the underlying economic conditions. For instance, a surge in corporate bankruptcies may indicate deteriorating business conditions, possibly triggered by a recession, while a decline in personal bankruptcies might suggest improving household financial health. Furthermore, regional and sectoral analysis of bankruptcy data may reveal stress points within specific parts of an economy, thus enabling targeted policy interventions. A crucial aspect of understanding bankruptcies from a macroeconomic perspective is the differentiation between various types of bankruptcies. In most jurisdictions, bankruptcy filings are categorized primarily as Chapter 7, Chapter 11, or Chapter 13 (or their equivalents outside the United States). Chapter 7 bankruptcy, often referred to as "liquidation bankruptcy," involves the sale of a debtor’s non-exempt assets to repay creditors. This type usually indicates severe financial distress as it often leads to a complete cessation of business operations. Chapter 11 bankruptcy, or "reorganization bankruptcy," allows a business to continue operating while restructuring its debts under court supervision. This type can provide a more optimistic outlook as it aims at enabling the debtor to eventually regain financial stability. Chapter 13 bankruptcy, known as "wage earner’s bankruptcy," enables individuals with regular income to create a plan to repay all or part of their debts within a three to five-year period. Comprehensively tracking these different types of bankruptcies provides a richer, more detailed picture of economic health. For example, in times of economic strain, an increase in Chapter 11 filings relative to Chapter 7 filings might indicate that businesses are still trying to survive and see potential for future recovery. Conversely, a sharp increase in Chapter 7 filings could signal that businesses see no viable path forward. Moreover, bankruptcy data is not only critical for understanding current economic conditions but also for forecasting future trends. Historical data on bankruptcies can be utilized to build predictive models, helping stakeholders anticipate potential economic slowdowns or recoveries. For instance, a rising trend in bankruptcies over a prolonged period may precede a broader economic downturn, offering an early warning signal for investors, businesses, and policymakers. Businesses, in particular, benefit immensely from understanding bankruptcy trends within their industries. By analyzing industry-specific bankruptcy rates, companies can gauge the competitive landscape and assess risks associated with market entry, expansion, or contraction. Moreover, during economic downturns, knowledge of bankruptcy trends can aid in crafting strategies to mitigate financial distress, such as diversifying product lines or seeking alternative financing options. From a policy perspective, monitoring bankruptcy data is essential for central banks, finance ministries, and regulatory bodies. Analyzing this data helps in formulating monetary and fiscal policies aimed at cushioning the economy during adverse periods. For example, a spike in bankruptcies might necessitate interventions such as lowering interest rates, providing stimulus packages, or implementing regulatory reforms to support struggling businesses and individuals. The implications of bankruptcy trends extend beyond pure economics into social realms as well. High rates of bankruptcies can lead to increased unemployment, reduced consumer confidence, and social instability. Therefore, macroeconomic analysis of bankruptcies also requires considering the broader socio-economic context. Policies aimed at reducing bankruptcy rates must address underlying issues such as income inequality, access to credit, and financial literacy. Furthermore, bankruptcy data is indispensable for investors. Institutional and individual investors alike scrutinize this data to make informed decisions about asset allocation and risk management. By understanding trends in bankruptcies, investors can identify sectors or regions that are more likely to face economic difficulties, allowing them to adjust their portfolios accordingly. In contrast, stable or declining bankruptcy rates might indicate robust economic conditions, presenting investment opportunities. In conclusion, the macroeconomic category of bankruptcies offers profound insights into the financial and economic health of nations, industries, and individuals. Eulerpool is committed to providing comprehensive, timely, and accurate bankruptcy data to facilitate informed decision-making for economists, businesses, policymakers, and investors. By understanding the multifaceted aspects of bankruptcies, stakeholders can better navigate the complexities of the economic environment, anticipate future trends, and implement strategies that promote stability and growth. Our platform aims to be the definitive resource for all your macroeconomic data needs, ensuring that you remain well-informed and equipped to address the challenges and opportunities within the global economy.