Tag Archives: data source

What is known about world income inequality?

The World Inequality Report 2018 provides a complete summary of world income inequality.  The executive summary contains thirteen charts to explore such as the one here.

The poorest half of the global population has seen its income grow significantly thanks to high growth in Asia (particularly in China and India). However, because of high and rising inequality within countries, the top 1% richest individuals in the world captured twice as much growth as the bottom 50% individuals since 1980 (Figure E4). Income growth has been sluggish or even zero for individuals with incomes between the global bottom 50% and top 1% groups. This includes all North American and European lower- and middle-income groups.

The executive summary also notes:

Research has demonstrated that tax progressivity is an effective tool to combat inequality. Progressive tax rates do not only reduce post-tax inequality, they also diminish pre-tax inequality by giving top earners less incentive to capture higher shares of growth via aggressive bargaining for pay rises and wealth accumulation. Tax progressivity was sharply reduced in rich and some emerging countries from the 1970s to the mid-2000s. Since the global financial crisis of 2008, the downward trend has leveled off and even reversed in certain countries, but future evolutions remain uncertain and will depend on democratic deliberations. It is also worth noting that inheritance taxes are nonexistent or near zero in high-inequality emerging countries, leaving space for important tax reforms in these countries.

The methodology page includes files with all the data.

How do NYC securities employee bonuses compare to U.S. household income?

Statista has your answer with their post Wall Street Bonuses Outpace Household Income  (3/28/18 by Dyfed Loesche) and their chart here.

Compared to the average U.S. household income this is quite some money, keeping in mind these are payments on top of the regular pay. In 2016, the average Wall Street bonus stood at close to $158,000 and thus 2.5 times as high as the median household income of a little more than $59,000. (The U.S. Census Bureau has not yet released official household figures for 2017). The average number of people living in an American household stands at 2.5.

The post has links to the median household data as well as the bonuses. Not only is this useful data for a stats course, but there is also an interesting discussion to be had on the use of mean and median in this post.

What is the connection between race and generational income mobility?

The recent paper, Race and Economic Opportunity in the United States: An Intergenerational Perspective, by the Equal Opportunity Project, has the answer and makes the data available.  The executive summary has seven key findings, here are three:

Finding #1: Hispanic Americans are moving up in the income distribution across generations, while Black Americans and American Indians are not.

Finding #2: The black-white income gap is entirely driven by differences in men’s, not women’s, outcomes.

Finding #6: Within low-poverty areas, black-white gaps are smallest in places with low levels of racial bias among whites and high rates of father presence among blacks.

There is something in this paper to challenge everyone’s views at some point. For example,

We find analogous gender differences in other outcomes: black-white gaps in high school completion rates, college attendance rates, and incarceration are all substantially larger for men than for women. Black women have higher college attendance rates than white men, conditional on parental income.

At the bottom of the executive summary are links to data, slides, and the full paper. You can go directly to the data here.

Is wage inequality growing?

The EPI article, The State of American Wages 2017 by Elise Gould, has a full summary of growing wage inequality. A few of their key findings:

From 2000 to 2017, wage growth was strongest for the highest-wage workers, continuing the trend in rising wage inequality over the last four decades.

While wage inequality has generally been on the rise for both men and women, wage inequality is higher and growing more among men than among women.

At every decile and at the 95th percentile, wage growth since 2000 was faster for white and Hispanic workers than for black workers.

This is an in depth article with over 30 bullet points of key findings. There are numerous graphs, such as the on posted here, with data sets. The cumulative graph here is broken into female and male graphs farther down in the article. What you will find is that, for example, the increase in the median wages is almost entirely due to increases in the median female wage (7.9% since 2000).  There is a lot to learn in this post and plenty of material for courses.

 

When and where do tornadoes occur?

The distribution of occurrences of tornadoes by time of day is presented in the accompanying graph from NOAA’s Historical Records and Trends page for tornadoes, which is a good example of a skewed distribution.

Because most tornadoes are related to the strength of a thunderstorm, and thunderstorms normally gain most of their energy from solar heating and latent heat released by the condensation of water vapor, it is not surprising that most tornadoes occur in the afternoon and evening hours, with a minimum frequency around dawn (when temperatures are lowest and radiation deficits are highest). However, tornadoes have occurred at all hours of the day, and nighttime occurrences may give sleeping residents of a community little or no warning.

The page includes the same type of graph by region in the country. If you want to know the distribution of tornadoes by state, NOAA has you covered on their U.S. Tornado Climatology page where you will find a map for the average number of tornadoes by state.  You can download tornado data from NOAA’s Storm Events Database.

Are tornadoes on the rise in the U.S.?

NOAA has an annual tornado report that contains the graph here.  The graphs suggests an increase.

In contrast to the previous four years, tornado activity across the U.S. during 2017 was above average. During January-September there were 1,262 confirmed tornadoes with 144 preliminary tornado reports still pending confirmation for October-December. This brings the preliminary tornado count to 1,406 with the final count expected to be slightly lower. The 1991-2010 annual average number of tornadoes for the U.S. is 1,253.

The page includes a map of the locations of tornadoes for 2017, a drop down menu for years dating back to 2006, and as monthly menu.  You can download tornado data from NOAA’s Storm Events Database.

How well is the world achieving its Sustainable Development Goals – gender equity edition?

You can find out with Our World in Data’s Sustainable Development Goals tracker.

In 2015 the world set a new sustainable development agenda, pledging within the United Nations (UN) to achieve 17 development goals by 2030: The Sustainable Development Goals (also known as The Global Goals). Ranging from eradicating poverty, to ensuring clean energy for all, to reaching sustainable levels of consumption, the array of targets across these goals were selected to drive our efforts in the 15 years up to 2030.

Our World in Data has data for all 17 goals on their SDG page.  For example, their Goal 5: Achieve gender equality and empower all women and girls page has 24 charts including the one posted here on unmet need for contraception. As is always the case with Our World in Data, each chart has easy access to the data and you can download their graphs.

What is the state of Arctic Sea Ice?

We are within about a month of the peak of Arctic sea ice in its yearly cycle of freezing and thawing. At the moment, sea ice is at a record low (see chart) tracking close to 2017 and 2016, where as 2012 holds the record for the lowest extent of ice. NSID has an interactive real time chart (the last data point here is Feb 25) where you can select any and all years from 1979 to the present and download the graph. The data can be downloaded in an Excel spreadsheet from their Sea Ice Data and Analysis Tools page where they also have links to animations.  There are materials in both the Calculus Projects and Statistics Projects pages using this data.

How does income inequality differ by country over time?

Our World in Data has an interactive chart that compares income inequality with gini coefficients. For example the chart here has the United States, United Kingdom, France, Germany, Netherlands, and Japan (you can select other countries too). Of these six countries the U.S. has greater income inequality than the other five.  It has also grown considerably since the mid 1970s.  As always with Our World in Data, you can download the data set so it can be used in statistics courses. You can also download graphs, such as the one here.

What is the history of manufacturing employment in the U.S.?

We can answer this question by using FRED. The accompanying graph was created with FRED’s graphing tool (see below for a quick tutorial on creating this graph), which creates an interactive graph that can be downloaded along with the data. The blue line represents total manufacturing jobs, which consistently decreases during a recession (gray bands). Manufacturing jobs peaked in 1979 at just below 20 million and now stand at about 12.5 million. The red line provides another perspective and represents the percent of manufacturing jobs relative to all employment.  In the 1940s manufacturing represented almost 40% of all employment. It has been decreasing ever since and today it is down to around 8.5%.

How to create the graph: Start by searching FRED for manufacturing employment. You should get this.  On the upper right click edit graph and then add line (second button on top). Search employment and click on All Employees: Total Nonfarm Payrolls.  Add the data series. Go to format (third button across the top)  and click right under y-axis position for LINE 2.  Now go to edit line 2 (first button across the top). Under customize data search manufacturing. Click All Employees: Manufacturing. In formula type b/a. Now click add next to All Employees: Manufacturing.  This does it. FRED offers a powerful tool.