Tag Archives: BLS products and services

New Measures of Prices for Global Trade

Shipping containers sitting on a dock at a port.How do prices for U.S. manufacturing exports compare to prices for goods manufactured abroad? How has the balance of export and import prices between the United States and Mexico changed over time? BLS has new measures to answer these and other questions on the competitiveness of U.S. production. We have published data on import and export price indexes since 1973. Since then we have made many improvements to the data we provide. Our latest improvements are the locality of destination export price indexes and the U.S. terms of trade indexes.

What are the locality of destination indexes?

Each locality of destination index measures price changes in dollars for U.S. goods exported to another country, region, or group of countries. These include major U.S. trade partners like China and the European Union. The indexes are available for all goods and for manufacturing and nonmanufacturing goods industries for some localities. The locality of destination indexes are a counterpart to the locality of origin import price indexes, which we have published since 1990. The locality of origin indexes let us examine price trends for goods imported from other countries, regions, and groups of countries.

What do the locality of destination indexes tell us?

The locality of destination indexes show how export price movements can vary depending on where U.S. goods are sold. For instance, from August to September 2018, prices for manufacturing exports to Latin America increased 0.3 percent. During the same period, manufacturing export prices to the European Union did not change. Comparing the two price movements, we can conclude market prices for U.S. exports arriving in Latin America increased relative to exports bound for Europe. Identifying these trends allows data users to dig deeper to see how currency exchange rates or shifts in global supply and demand affect price movements across trade partners.

What are the terms of trade indexes?

Each terms of trade index measures the purchasing power of U.S. exports, in terms of imports, for a specific country, region, or group of countries. In other words, the terms of trade index for China provides information on the price for exports to China, and how those export prices compare to prices for imports coming from China. Prices for exports and imports are measured in U.S. dollars, so exchange rates are already taken into account. We calculate the terms of trade index for China by dividing the China export index by the China import index, then multiplying by 100. An increase in the China terms of trade index means prices for exports to China are rising faster than prices for imports from China.

What does a terms of trade index price change mean?

A change in a terms of trade index provides information on the competitiveness of U.S. goods in the global market. Take the previous example, an increase in the China terms of trade index. U.S. producers are receiving higher prices for exported goods, meaning U.S. companies can now afford to purchase more imports. The U.S. terms of trade—or competitiveness—with China have improved. When looking at the trends, remember that the types of goods U.S. businesses export to and import from China are different, and underlying price changes may have different causes.

How broad is the coverage of the terms of trade indexes?

We have terms of trade indexes for each country, region, or group of countries where we publish both a locality of destination export index and a locality of origin import index. These countries include major trading partners:

  • Canada
  • Mexico
  • Germany
  • China
  • Japan

They also include regions or groups of countries:

  • Industrialized Countries (Western Europe, Canada, Japan, Australia, New Zealand, and South Africa)
  • European Union
  • Latin America (Mexico, Central America, South America, and the Caribbean)
  • Pacific Rim (China, Japan, Australia, Brunei, Indonesia, Macao, Malaysia, New Zealand, Papua New Guinea, Philippines, and the Asian Newly Industrialized Countries)

We publish the terms of trade indexes and the locality of destination indexes monthly. Data are available beginning with December 2017.

Why did we develop these new indexes?

The locality of destination and terms of trade indexes come from an ongoing effort to better measure the competitiveness of U.S. goods. We began expanding our measures of competitiveness in 2010 by extending the locality of origin import indexes to more detailed industries. Next we began work on the locality of destination and terms of trade indexes, eventually introducing them in September 2018.

Want to learn more?

Making It Easier to Find Data on Pay and Benefits

We love data at the U.S. Bureau of Labor Statistics. We have lots of data about the labor market and economy, but we sometimes wish we had more. For example, we believe workers, businesses, and public policymakers would benefit if we had up-to-date information on employer-provided training. I recently wrote about the challenges of collecting good data on electronically mediated work, or what many people call “gig” work. I know many of you could make your own list of data you wish BLS had. One topic for which we have no shortage of data is pay and benefits. In fact, we have a dozen surveys or programs that provide information on compensation. We have so much data on compensation that it can be hard to decide which source is best for a particular purpose.

Where can you get pay data on the age, sex, or race of workers? Where should you go if you want pay data for teachers, nurses, accountants, or other occupations? What about if you want occupational pay data for a specific metro area? Or if you want occupational pay data for women and men separately? What if you want information on workers who receive medical insurance from their employers? Where can you find information on employers’ costs for employee benefits? Here’s a short video to get you started.

But wait, there’s more! To make it easier to figure out which source is right for your needs, we now have an interactive guide to all BLS data on pay, benefits, wages, earnings, and all the other terms we use to describe compensation. Let me explain what I mean by “interactive.” The guide lists 12 sources of compensation data and 32 key details about those data sources. 12 x 32 = a LOT of information! Having so much information in one place can feel overwhelming, so we created some features to let you choose what you want to see.

For example, the guide limits the display to three data sources at a time, rather than all 12. You can choose which sources you want to learn about from the menus at the top of the guide.Snippet of interactive guide on BLS compensation data.

If you want to learn about one of the 32 key details across all 12 data sources, just press or click that characteristic in the left column. For example, if you choose “Measures available by occupation?” a new window will open on your screen to describe the pay data available from each source on workers’ occupations.

There are links near the bottom of the guide to help you find where to go if you want even more information about each data source.

Check out our overview of statistics on pay and benefits. The first paragraph on that page has a link to the interactive guide. We often like to say, “We’ve got a stat for that!” When it comes to pay and benefits, we have lots of stats for that. Let us know how you like this new interactive guide.

New BLS Local Data App Now Available

BLS has partnered with the U.S. Department of Labor’s Office of the Chief Information Officer to develop a new mobile app for iPhones that is now available for free in the App Store! Search “BLS Local Data.”

The BLS Local Data app is ideal for customers who want to know more about local labor markets, such as jobseekers and economic and workforce development professionals. You can search using your current location, a zip code, or a location name to find relevant data quickly without having to navigate through the huge BLS database. With one click, you can find data for states, metro areas, or counties.

Using the BLS API, the app quickly presents local data and national comparisons for unemployment rates, employment, and wages.

In the coming months, look for more features and data in the app. We’re already working on future releases that will include industry and occupation drilldowns and comparisons between local areas.

Check out the app and explore the wealth of local labor market data produced by BLS! And don’t worry, Android users! An Android version of the app will be available in the future.

iPhone screen image for BLS Local Data app

A Clearer Look at Response Rates in BLS Surveys

Hands holding a tablet computer and completing a surveyPeople know BLS for our high-quality data on employment, unemployment, price trends, pay and benefits, workplace safety, productivity, and other topics. We strive to be transparent in how we produce those data. We provide detailed information on our methods for collecting and publishing the data. This allows businesses, policymakers, workers, jobseekers, students, investors, and others to make informed decisions about how to use and interpret the data.

We couldn’t produce any of these statistics without the generous cooperation of the people and businesses who voluntarily respond to our surveys. We are so grateful for the public service they provide.

To improve transparency about the quality of our data, we recently added a new webpage on response rates to our surveys and programs. We previously published response rates for many of our surveys in different places on our website. Until now there hasn’t been a way to view those response rates together in one location.

What is a response rate, and why should I care?

A response rate is the percent of potential respondents who completed the survey. We account for the total number of people, households, or businesses we tried to survey (the sample) and the number that weren’t eligible (for example, houses that were vacant or businesses that had closed). Response rates are an important measure for survey data. High response rates mean most of the sample completed the survey, and we can be confident the statistics represent the target population. Low response rates mean the opposite, and data users may want to consider other sources of information.

Do response rates tell the whole story?

A low response rate may mean the data don’t represent the target population well, but not necessarily. How much a low response rate affects how well the estimates represent the population is called nonresponse bias. Some important research by Robert M. Groves and Emilia Peytcheva published in the January 2008 issue of Public Opinion Quarterly looked at the connection between response rates and nonresponse bias in 59 studies. The authors found that high response rates can reduce the risk of bias, but there is not a strong correlation between response rate and nonresponse bias. Some surveys had a very low response rate but did not have evidence of high nonresponse bias. Other surveys had high nonresponse bias despite high response rates.

This means we should look at response rates with other measures of data quality and bias. BLS has studied nonresponse bias for many years. We have links to many of those studies in our library of statistical working papers.

What should I be looking for on the new page?

With response rates from multiple surveys in a single place, you can look for patterns across surveys and across time. For example, across every graph we see that response rates are declining over time. This is happening for nearly all surveys, government and private, on economic and other topics. It is simply getting harder to persuade respondents to answer our surveys.

Individual survey response rates are also interesting compared with other BLS surveys. We see that some surveys have higher response rates than others. To understand why this might be, we’ll want to look at the differences between the surveys. Each survey has specific collection procedures that affect response rates. For example, the high response rate for the Annual Refiling Survey (shown as ARS in the second chart) may catch your eye. When you see that it has a 12-month collection period and is mandatory in 26 states, the rate makes more sense.

We also can see how survey-specific changes have affected a survey’s response rate. For example, we see a drop in the response rate for the Telephone Point of Purchase Survey around 2012. This drop likely resulted from a change in sample design, as the survey moved from a sample of landline telephones to a dual-frame sample with both landlines and cell phones. Because the response rate for this survey continues to decline, we are developing a different approach for collecting the needed data.

What should I know before jumping into the new page?

There’s a lot of information! We’ve tried to make it as user friendly as possible, including a glossary page with definitions of terms and a page to show how each survey calculates their response rates. On the graphs, you can isolate a single survey by hovering over each of the lines. You can also download the data shown in each graph to examine it more closely.

We hope you will find this page helpful for understanding the quality of BLS data. Please let us know how you like it!

BLS Big Data Delivers Hurricane Flood Zone Maps

Information is key to preparing for a natural disaster. That’s why we have updated our maps of businesses and employment in flood zones for states on the Atlantic and Gulf Coasts that are vulnerable to hurricanes and tropical storms.

These maps combine data from the Quarterly Census of Employment and Wages with the most up-to-date information from the U.S. Census Bureau and U.S. Geological Survey. The result is high-resolution graphics for every county with hurricane flood zones along or inland from the Atlantic and Gulf Coasts.

The Quarterly Census of Employment and Wages is our “Big Data” program. It gathers data from 9.9 million reports that almost every employer in the United States, Puerto Rico, and the U.S. Virgin Islands files each quarter. We have been producing maps of businesses and employment in disaster areas since 2001, when we created zip code maps and tables of Lower Manhattan. We began mapping hurricane zones in 2014, combining BLS data with flood zones created by the U.S. Army Corps of Engineers and state emergency management agencies.

These maps are one way we use Big Data to create new products without increasing the burden on our respondents. Within BLS, we use these maps for research into the data collection and economic effects of a storm. We also provide these maps to state labor market information offices to use for their statistical analysis and emergency response.

Hurricane maps highlight how we use emerging technologies. We create these maps with open source mapping software, part of our open data practices that make it easier for decision makers to get and use the data.

This isn’t our only example of matching Quarterly Census of Employment and Wages data with data from other federal agencies to deliver new insights. We have matched our data with publicly available Internal Revenue Service data to measure employment and wages in nonprofit organizations. We also are working with our colleagues at the Bureau of Economic Analysis to improve understanding of foreign direct investment in the United States. When these data become available, users can analyze employment and wages by industry and occupation in firms with and without foreign direct investment.

All of these efforts improve the quality and breadth of information available for decision makers. If you have ideas about other partnerships with our Big Data team, please send us a message or give us a call!