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What does the variable 'a' represent in the context of the coefficients of logx?
What does the variable 'a' represent in the context of the coefficients of logx?
Which country is reported to have the largest value of the Pareto exponent using the Hill estimator?
Which country is reported to have the largest value of the Pareto exponent using the Hill estimator?
How many countries had a Pareto exponent significantly less than 1 using OLS?
How many countries had a Pareto exponent significantly less than 1 using OLS?
What is the correlation coefficient between the OLS estimator and the Hill estimator for the latest available period?
What is the correlation coefficient between the OLS estimator and the Hill estimator for the latest available period?
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Which of the following countries is associated with a low value of the Pareto exponent?
Which of the following countries is associated with a low value of the Pareto exponent?
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What type of distribution do the OLS estimates of the Pareto exponent follow?
What type of distribution do the OLS estimates of the Pareto exponent follow?
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Which of the following variables are indicated to matter more in determining the size distribution of cities?
Which of the following variables are indicated to matter more in determining the size distribution of cities?
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What is the special value of the parameter 'a' in Zipf's Law?
What is the special value of the parameter 'a' in Zipf's Law?
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Which study investigated the value of the Pareto exponent for a sample of 44 countries?
Which study investigated the value of the Pareto exponent for a sample of 44 countries?
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Which of the following estimates of the Pareto exponent was reported for Australia?
Which of the following estimates of the Pareto exponent was reported for Australia?
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What does the variable 'x' represent in the Pareto distribution formula?
What does the variable 'x' represent in the Pareto distribution formula?
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The estimates of the Pareto exponent in how many out of 44 countries exceeded unity?
The estimates of the Pareto exponent in how many out of 44 countries exceeded unity?
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The equation $y = Ax^{-a}$ signifies what aspect of city size distribution?
The equation $y = Ax^{-a}$ signifies what aspect of city size distribution?
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What is the shape parameter of the Pareto distribution in relation to the distribution of cities according to the findings?
What is the shape parameter of the Pareto distribution in relation to the distribution of cities according to the findings?
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What limitation does the paper identify regarding the work of Rosen and Resnick (1980)?
What limitation does the paper identify regarding the work of Rosen and Resnick (1980)?
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Which estimator is suggested by Gabaix and Ioannides for analyzing Zipf’s Law?
Which estimator is suggested by Gabaix and Ioannides for analyzing Zipf’s Law?
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What does the paper find regarding the Pareto exponent for urban agglomerations when using OLS estimation?
What does the paper find regarding the Pareto exponent for urban agglomerations when using OLS estimation?
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What does the study conclude about the applicability of Zipf's Law across countries?
What does the study conclude about the applicability of Zipf's Law across countries?
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What factor could explain the differing results for urban agglomerations compared to earlier studies?
What factor could explain the differing results for urban agglomerations compared to earlier studies?
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What is a significant finding regarding the distribution of the Pareto exponent in the paper?
What is a significant finding regarding the distribution of the Pareto exponent in the paper?
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Which approach does the paper take compared to previous studies like that of Rosen and Resnick?
Which approach does the paper take compared to previous studies like that of Rosen and Resnick?
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What is a key difference between the Hill estimator and the OLS estimator in terms of data assumptions?
What is a key difference between the Hill estimator and the OLS estimator in terms of data assumptions?
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Which country had the highest Pareto exponent value according to the OLS regressions?
Which country had the highest Pareto exponent value according to the OLS regressions?
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Why is the OLS estimator considered heuristic?
Why is the OLS estimator considered heuristic?
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What factor influences the reliability of the Hill estimate according to the findings of Black and Henderson (2003)?
What factor influences the reliability of the Hill estimate according to the findings of Black and Henderson (2003)?
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What is the potential issue with the Hill estimator if the distribution of data is not Pareto?
What is the potential issue with the Hill estimator if the distribution of data is not Pareto?
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What does the Pareto exponent represent in the context of the study?
What does the Pareto exponent represent in the context of the study?
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What is emphasized about the results discussed in the section on Zipf’s Law for cities?
What is emphasized about the results discussed in the section on Zipf’s Law for cities?
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What is the purpose of using the Pareto exponent in the second stage regression?
What is the purpose of using the Pareto exponent in the second stage regression?
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What implication does a negative quadratic term have for the value of b?
What implication does a negative quadratic term have for the value of b?
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What does the acronym OLS stand for in the context of regression analysis?
What does the acronym OLS stand for in the context of regression analysis?
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In the provided regression results, which country had the highest number of urban agglomerations?
In the provided regression results, which country had the highest number of urban agglomerations?
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Which country reported a Hill estimate of 0.5058 in the year 1991?
Which country reported a Hill estimate of 0.5058 in the year 1991?
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What does a 95% confidence interval in the context of Pareto exponent estimates indicate?
What does a 95% confidence interval in the context of Pareto exponent estimates indicate?
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Which variable represents the log of city size in the analysis?
Which variable represents the log of city size in the analysis?
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What was the Hill exponent of Colombia in 1993?
What was the Hill exponent of Colombia in 1993?
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In the regression results, which country had an OLS estimate for aV as 3.4992 in the year 2000?
In the regression results, which country had an OLS estimate for aV as 3.4992 in the year 2000?
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What does the variable AGG represent in the data?
What does the variable AGG represent in the data?
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Which country's OLS values showed a significant negative correlation in the quadratic terms?
Which country's OLS values showed a significant negative correlation in the quadratic terms?
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What effect do greater scale economies in manufacturing have on city formation?
What effect do greater scale economies in manufacturing have on city formation?
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How do lower transport costs affect the distribution of cities?
How do lower transport costs affect the distribution of cities?
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What role does the share of manufacturing in an economy play in city distribution?
What role does the share of manufacturing in an economy play in city distribution?
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According to Ades and Glaeser, which of the following factors influences the concentration of population in the capital city?
According to Ades and Glaeser, which of the following factors influences the concentration of population in the capital city?
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What is a predicted outcome of political instability according to the discussed models?
What is a predicted outcome of political instability according to the discussed models?
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Which of the following statements about international trade and economic activity distribution is true?
Which of the following statements about international trade and economic activity distribution is true?
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What can be concluded about regional capitals in a dictatorship?
What can be concluded about regional capitals in a dictatorship?
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What challenge is mentioned regarding existing models of economic geography?
What challenge is mentioned regarding existing models of economic geography?
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Study Notes
Zipf's Law for Cities: A Cross-Country Investigation
- This study investigates the empirical validity of Zipf's Law for city size distributions across 73 countries.
- Two estimation methods were used: Ordinary Least Squares (OLS) and the Hill estimator.
- Zipf's Law, which posits that city sizes follow a Pareto distribution, was rejected far more often than expected by chance in both estimation methods.
- OLS estimates of the Pareto exponent are roughly normally distributed, while Hill estimator estimates are bimodal.
- Variations in the Pareto exponent are better explained by political economy variables than by economic geography variables.
- The study used new data on 73 countries, including data on city sizes.
- The original study of Zipf's Law was based on relatively old data from 1970.
Introduction
- Economic activity is concentrated in cities.
- Understanding the size distribution of cities within an urban system is a key area of research.
- Pareto distribution is commonly used to model city size distributions.
- Zipf's Law proposes that the size distribution follows a specific form of a Pareto distribution where cities' sizes and their rank correlate.
- The study assesses if Zipf's Law holds for a larger range of countries with more recent data.
Data and Methods
- This study leveraged a larger, more recent dataset of countries than previous research.
- Cities with population thresholds of at least 10,000 were included.
- The study used the Hill estimator as well as OLS for estimation.
- The Hill estimator is the maximum likelihood estimator under a power law model while the OLS method is a more heuristic/approximate estimation technique.
- Additional checks were done: robustness checks were done using a Cook-Weisberg test, and instrumental variables (IV) estimation methods were used for the original OLS results.
- The analysis explores the relationship between the Pareto exponent and political economy variables (e.g., political rights, government expenditure) as well as economic geography variables to explain variations in the exponent.
Results
- When applying OLS, the majority of countries do not follow a Pareto distribution, and even when they do, the Pareto exponent frequently departs significantly from 1.
- For urban agglomerations, estimates of the Pareto exponent using OLS are often significantly less than 1, which this analysis suggests could be due to recent suburbanization patterns (different than existing results).
- Using the Hill estimator, estimates of the Pareto exponent are bimodal, suggesting that neither estimator may be completely appropriate.
- The study discovered that political variables seem to have more explanatory power.
Conclusion
- The study found that Zipf's Law often does not hold true for modern data
- Political variables appear to be more important determinants of city size distribution than just economic geographic variables and other models.
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Description
Test your understanding of the Pareto exponent and its applications, particularly in the context of city size distribution and Zipf's Law. This quiz covers key concepts such as correlation coefficients, country-specific analyses, and the significance of various variables in size distribution. Perfect for students studying economics and urban studies.