In 2024, understanding the cost of living across different countries is crucial for businesses, expatriates, and policymakers. The Cost of Living Index by Country provides valuable insights into the expenses required to maintain a certain standard of living globally. This analysis examines the latest index, exploring regional trends and the factors influencing living costs, offering a snapshot of economic conditions worldwide.
Source: kaggle
Given the dataset, Powerdrill AI detects and analyzes the metadata, then gives these relevant inquiries:
What are the top 5 countries with the highest Living Index?
What factors affect the Cost of Living Index?
How does the Local Purchasing Power Index vary among countries with similar Cost of Living Index values?
Which countries have the lowest Restaurant Price Index, and how does it correlate with their overall Cost of Living Index?
Is there a significant difference in the Cost of Living Plus Rent Index between countries with high and low Rent Index values?
Which countries have the most balanced indices across all categories (Cost of Living, Rent, Groceries, Restaurant Prices, Local Purchasing Power)?
What trends can be observed in the Cost of Living Index for countries with a high Local Purchasing Power Index?
How do the indices for countries with similar ranks compare in terms of Cost of Living and Rent?
What are the top 5 countries with the highest Living Index?
Based on the provided data, here is a detailed analysis of the top 5 countries with the highest Cost of Living Index:
Switzerland
Cost of Living Index: 101.1 (Highest)
Rent Index: 46.5
Cost of Living Plus Rent Index: 74.9
Groceries Index: 109.1 (Highest)
Restaurant Price Index: 97.0 (Highest)
Local Purchasing Power Index: 158.7 (Highest)
Summary: Switzerland tops the list with the highest indices in almost all categories, indicating a very high cost of living but also a strong local purchasing power.
Bahamas
Cost of Living Index: 85.0
Rent Index: 36.7
Cost of Living Plus Rent Index: 61.8
Groceries Index: 81.6
Restaurant Price Index: 83.3
Local Purchasing Power Index: 54.6
Summary: The Bahamas ranks second, with significantly lower indices compared to Switzerland, especially in local purchasing power.
Iceland
Cost of Living Index: 83.0
Rent Index: 39.2
Cost of Living Plus Rent Index: 62.0
Groceries Index: 88.4
Restaurant Price Index: 86.8
Local Purchasing Power Index: 120.3
Summary: Iceland has a high cost of living with a relatively high local purchasing power, making it third on the list.
Singapore
Cost of Living Index: 76.7
Rent Index: 67.2 (Highest)
Cost of Living Plus Rent Index: 72.1
Groceries Index: 74.6
Restaurant Price Index: 50.4 (Lowest)
Local Purchasing Power Index: 111.1
Summary: Singapore features the highest rent index but lower costs in groceries and restaurant prices compared to other top countries.
Barbados
Cost of Living Index: 76.6
Rent Index: 19.0 (Lowest)
Cost of Living Plus Rent Index: 48.9 (Lowest)
Groceries Index: 80.8
Restaurant Price Index: 69.4
Local Purchasing Power Index: 43.5 (Lowest)
Summary: Barbados, while among the top five, shows the lowest indices in rent, cost of living plus rent, and local purchasing power, indicating a more affordable living situation relative to the other top countries.
Overall Insight: The data reveals a significant variation in the cost of living indices among the top countries, with Switzerland leading by a considerable margin. Each country presents a unique balance between living costs and local purchasing power, reflecting diverse economic landscapes.
What factors affect the Cost of Living Index?
Based on the provided correlation data between the 'Cost of Living Index' and other indices, we can draw several conclusions about the factors that influence the Cost of Living Index:
1. Strong Correlation with Rent Index
Correlation Coefficient: 0.820885
Interpretation: There is a strong positive correlation between the Cost of Living Index and the Rent Index. This suggests that as rent costs increase, the overall cost of living also tends to increase.
2. Very Strong Correlation with Cost of Living Plus Rent Index
Correlation Coefficient: 0.97178
Interpretation: The Cost of Living Index is very strongly correlated with the Cost of Living Plus Rent Index. This indicates that the combined costs of living and rent are a significant determinant of the overall cost of living.
3. Strong Correlation with Groceries Index
Correlation Coefficient: 0.958452
Interpretation: There is a strong positive correlation between the Cost of Living Index and the Groceries Index. This implies that grocery prices significantly impact the overall cost of living.
4. Strong Correlation with Restaurant Price Index
Correlation Coefficient: 0.945483
Interpretation: The Cost of Living Index also shows a strong positive correlation with the Restaurant Price Index. This suggests that dining out expenses influence the overall cost of living.
5. Moderate Correlation with Local Purchasing Power Index
Correlation Coefficient: 0.692688
Interpretation: There is a moderate positive correlation between the Cost of Living Index and the Local Purchasing Power Index. This indicates that regions with higher local purchasing power tend to have a higher cost of living, although this relationship is not as strong as with other indices.
Summary
The Cost of Living Index is primarily influenced by the Rent Index, Groceries Index, and Restaurant Price Index, with the strongest influence coming from the combined Cost of Living Plus Rent Index. These factors should be considered carefully when assessing the cost of living in different regions.
How does the Local Purchasing Power Index vary among countries with similar Cost of Living Index values?
Key Observations:
Variability in Local Purchasing Power: Despite similar Cost of Living Index values, there is significant variability in the Local Purchasing Power Index among the countries.
Range of Local Purchasing Power Index: The Local Purchasing Power Index ranges from as low as 29.1 in Pakistan to as high as 158.7 in Switzerland, indicating a wide disparity in how far the local currency goes in purchasing goods and services relative to the cost of living.
Detailed Insights:
Low Purchasing Power in Low Cost Countries: Countries like Pakistan, Libya, Egypt, and India, which have lower Cost of Living Index values (around 18.8 to 20.9), also tend to have lower Local Purchasing Power Indices, ranging from 29.1 to 48.2.
Moderate Purchasing Power in Medium Cost Countries: Countries grouped in the middle range of the Cost of Living Index, such as Latvia and Slovenia, show moderate Local Purchasing Power Indices around 51.4 to 81.2.
High Purchasing Power in High Cost Countries: Countries with a high Cost of Living Index like Denmark, Iceland, and Switzerland not only have high costs but also significantly higher Local Purchasing Power Indices, suggesting that the higher cost of living is offset by proportionally higher local incomes.
Visual Analysis:
The bar chart visually represents the disparity in Local Purchasing Power Indices. Countries like Switzerland stand out with a very high index, whereas countries like Pakistan are at the lower end of the spectrum.
Conclusion:
The analysis reveals that while some countries maintain a balance between cost of living and purchasing power, others do not, leading to varying degrees of economic pressure on the residents. This highlights the importance of considering both indices when assessing the economic health and quality of life in different countries.
Which countries have the lowest Restaurant Price Index, and how does it correlate with their overall Cost of Living Index?
Countries with the Lowest Restaurant Price Index
Based on the provided data, the countries identified with the lowest Restaurant Price Index are:
Bangladesh: Restaurant Price Index = 12.8
Pakistan: Restaurant Price Index = 12.9
Indonesia: Restaurant Price Index = 13.5
Algeria: Restaurant Price Index = 14.0
Madagascar: Restaurant Price Index = 14.3
These countries have been selected as they have the lowest values in the dataset provided, which includes a total of 10 countries.
Correlation Analysis
The correlation coefficient between the Restaurant Price Index and the Cost of Living Index for these countries is 0.182485. This value indicates a very weak positive correlation. This suggests that within the dataset of countries with the lowest restaurant prices, changes in the Restaurant Price Index do not significantly correlate with changes in the Cost of Living Index.
Key Observations
Low Correlation: The very weak correlation suggests that other factors might be more influential in determining the cost of living in these countries, beyond just restaurant prices.
Variability in Cost of Living: Despite similar restaurant prices, the Cost of Living Index varies significantly among these countries (from 18.8 in Pakistan to 28.9 in Algeria), further supporting the low correlation finding.
This analysis provides a foundational understanding of the relationship between dining costs and overall living expenses in countries with lower restaurant pricing. Further investigation could explore additional factors that impact the cost of living to provide a more comprehensive analysis.
Is there a significant difference in the Cost of Living Plus Rent Index between countries with high and low Rent Index values?
Key Findings:
Countries with High Rent Index Values:
The average Cost of Living Plus Rent Index for countries classified under the high Rent Index group is 40.31. This indicates a significantly higher cost of living when rent is considered in these countries.
Countries with Low Rent Index Values:
The average Cost of Living Plus Rent Index for countries classified under the low Rent Index group is 20.57. This reflects a considerably lower cost of living including rent compared to countries with high Rent Index values.
Summary:
The analysis clearly shows a substantial difference in the Cost of Living Plus Rent Index between countries with high and low Rent Index values. Countries with high Rent Index values have almost double the Cost of Living Plus Rent Index compared to those with low Rent Index values, highlighting the impact of rent on the overall cost of living in different regions.
Which countries have the most balanced indices across all categories (Cost of Living, Rent, Groceries, Restaurant Prices, Local Purchasing Power)?
Based on the analysis of standard deviations of indices across various categories (Cost of Living, Rent, Groceries, Restaurant Prices, and Local Purchasing Power), the top 5 countries with the most balanced indices are identified. Lower standard deviations indicate a more balanced performance across these indices.
Top 5 Countries with the Lowest Standard Deviation:
1. Madagascar - Standard Deviation: 6.34
2. Egypt - Standard Deviation: 6.78
3. Iran - Standard Deviation: 6.79
4. Tanzania - Standard Deviation: 6.87
5. Kyrgyzstan - Standard Deviation: 7.47
These countries exhibit the least variability in their indices, suggesting a more consistent cost environment across different aspects of living. This information can be particularly useful for individuals or businesses considering relocation or investment in these regions.
What trends can be observed in the Cost of Living Index for countries with a high Local Purchasing Power Index?
Key Observations from Data:
Mean Cost of Living Index: The average Cost of Living Index for countries with a high Local Purchasing Power Index is 53.37. This indicates a relatively high cost of living in these countries.
Median Cost of Living Index: The median value is 52.15, which is very close to the mean, suggesting a symmetric distribution of the Cost of Living Index values among these countries.
Standard Deviation: The standard deviation is 15.58, indicating that there is a moderate variability in the Cost of Living Index among these countries.
Visual Representation:
The bar chart provided visualizes the statistical measures of the Cost of Living Index:
The Mean and Median values are depicted by two high bars, both exceeding 50, which underscores the high cost of living in these nations.
The Standard Deviation bar is significantly shorter, illustrating the spread of the data around the mean.
Conclusion:
Countries with a high Local Purchasing Power Index generally exhibit a high Cost of Living Index, with a mean and median above 50. The moderate standard deviation indicates that while there is some variability in the cost of living among these countries, it does not exhibit extreme fluctuations. This analysis helps in understanding the economic landscape of countries where residents have greater local purchasing power relative to the cost of living.
How do the indices for countries with similar ranks compare in terms of Cost of Living and Rent?
Key Observations:
Similarity in Rankings: The bar chart visually represents the Cost of Living Rank and Rent Rank for various countries. It is evident that for many countries, these two indices are closely ranked, indicating a correlation between the cost of living and rent expenses.
High-Rank Countries: Countries like Switzerland, Singapore, and the United States show very high rankings in both indices, suggesting that these are among the most expensive countries in terms of both living costs and rent.
Consistency Across Indices: The visual similarity between the blue and purple bars for most countries suggests that a higher cost of living generally corresponds to higher rent costs.
Detailed Analysis:
Top Ranked Countries: Switzerland has the highest ranks in both indices (121 for Cost of Living and 119 for Rent), closely followed by Singapore (118 for Cost of Living and 121 for Rent).
Low Variance in Rank Difference: The rank difference between the Cost of Living and Rent indices is relatively small for most countries, typically within a range of 0 to 5. This small variance further supports the strong relationship between these two indices.
Conclusion:
The analysis and visualization clearly show that countries with a high cost of living typically also have high rent costs, and vice versa. This trend is consistent across a diverse set of countries, indicating that the cost of living and rent are closely interconnected economic factors.
Try Now
Try Powerdrill AI now, explore more exciting data stories in an effective way!
