All posts by Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science Alexander is a Ph.D. student in Computer Science. He currently holds B.S. and M.S. degrees in Applied Math. He has experience working for industry major companies performing research in the fields of machine learning, data mining and natural language processing. In his free time, Alexander enjoys hiking, Nordic skiing and traveling.

Are business industries sensitive to climate?

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

The geographic properties of an area often dictate the type of businesses that can locate there. For example, you can’t have an inland naval base. Farms and agriculture, in general, are less likely to prosper on rocky mountains than on sunny plains. But today, with all the technological advancements we have, many jobs in intellectual labor, including IT and finance, hi-tech manufacturing and other new industries seem less likely to depend on climatic features.

To summarize climate features of a territory, we used the existing climate zones classification prepared by the U.S. Department of Energy. Each county is assigned to one of eight climate zones. Definitions of these zones depend not on temperatures, but rather on accumulated heat (the unit is called “degree-days”). Zone 1 has the warmest climate, while zone 8 has the coldest – in the U.S., only certain parts of Alaska belong to this climate zone. We present a map of the climate zones below; you can click to zoom in on a state of interest.

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Airline industry in the U.S.

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

The United States has an extensive airline transportation network. According to statistics from Airports Council International, 12 of the world’s largest airports by passenger traffic are located in the U.S. In fact, the world’s busiest airport is Hartsfield–Jackson in Atlanta, Georgia; over 100 million passengers went through this airport in 2015 (a 5.5 percent increase over the previous year).

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Time use patterns in the last decade

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

In this post, we will explore the data from the American Time Use Survey and attempt to put the numbers in perspective — using data for the years of 2003-2014 will show us changes in daily activities in the last decade.

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U.S. economic growth: gross domestic product

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

Gross domestic product is commonly used to measure the economic performance of a country. GDP equals the value of all the goods and services produced in the economy minus the value of any goods or services used during the production process. Another name for this quantity is “value added.” Recently, the Bureau of Economic Analysis released data on GDP by industry for 2016. Today we will look at this data to see different industries’ contributions to the U.S. economy’s growth in the last year.

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Commodities flow in U.S. industry

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

The United States Bureau of Economic Analysis provides a lot of quantitative information on the country’s economic activities. The Bureau’s Industry Economic Program prepares one particularly interesting type of data: commodity input-output tables. These tables show how industries interact to provide input to and take output from one another.

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Connected cars

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

A connected car is a car equipped with internet access and occasionally connected to a local wireless network as well. This allows the car to communicate with other devices, both inside and outside the car, to provide the driver and passengers with additional functions. Typically, a connected car offers entertainment, navigation, safety and diagnostic capabilities. The concept of a connected car is related to technologies such as self-driving cars and the internet of things.

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Same-occupation couples: new estimates

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

In this post, we will revisit the topic of occupation and marriage dependency, and same-occupation couples in particular. Recently, new five-year American Community Survey data was released by IPUMS USA. This is the most comprehensive version of the survey, having the widest coverage of the population (even in smaller areas).

Same-occupation couples

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Occupational standing through time

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

One’s occupation is often associated with a certain level or group in society. This “general standing” or prestige of an occupation is often studied by sociologists. There is a significant debate about whether it can be broken down to individual characteristics like expected salary and education level or training to perform the job or requires analysis of a much more complex characteristic.

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U.S. economic growth: gross output

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

Gross output represents the market value of all services and goods produced in a nation’s economy. This value differs slightly from gross domestic product (GDP), which is often used to measure the economic performance of a country. Gross output consists of products sold to final consumers (the GDP) as well as products sold to other industries where it is used as material or input. Today we will explore historical data (provided by the Bureau of Economic Analysis) on the gross output of the U.S. economy.

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Age distribution among same-sex couples

Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

In this post, we will continue to investigate same-sex couples and their demographic features. We will once again use American Community survey data, namely the ACS 2015 five-year sample processed by the IPUMS project. In this version, IPUMS USA has introduced a specially-constructed variable to their version of American Community Survey. Using answers to different questions of the survey form, they attempt to pinpoint the location of the respondent’s potential spouse in the same household. This allows us to identify both same- and opposite-sex couples.

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