Haver’s data services are provided through the DLX platform; delivering tools for data management, visualization, modeling and publishing. DLX is designed to increase productivity and integrates with Excel, PowerPoint, and major statistical software packages; MatLab, R, Python, SAS, E-views and Stata. DLX component application DLXVG3 offers precision graphics, publishing, analytic tools, and easy navigation for all Haver databases.

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Chart and compare multiple data series with accompanying data table of values

Advanced functions (growth rates, moving averages, aggregation, seasonal adjustment)

Analytical tools (cycle charts, scatterplots, trend lines, and recession shading)

Complete graph customization (axis scaling, sizing, formatting, styles)

Excel and PowerPoint direct export and complete integration (dynamic spreadsheets and presentations update on a click)

DLXVG3

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DLX Add-ins for all versions of Excel provide instant data updates of entire workbooks

Use DLXVG3 to locate data series codes from within any file, easily creating new spreadsheets for analysis

Edit date ranges, archive data, apply functions

Excel Spreadsheet Add-ins

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Haver offers timely, accurate, and professionally supported data via an update service, meeting the strictest demands of the institutional research community

AutoUpdate provides fast and reliable data updates within seconds of source releases

Timer service runs continuously on an hourly basis when DLX is running

Manual updates offer clients the independence to update data retrievals on any desired schedule

All database updates retrieve only the data series that have changed and send only the data points that have been updated; including revisions

Timely Updates

DLX software tools to convert data into many different formats needed for diverse analytical frameworks

Haver supports a DLX API permitting clients to leverage and build processes with DLX data

Database Compatibility

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Data Link Express

Platform Independent site delivering DLX Databases across any workstation or device.

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HaverView

[Matlab](http://matlab.com) by The MathWorks lets you access, visualize, and analyze historic time-series data to identify patterns or uncover complex relationships. From within a single environment you can:

- Access data from multiple sources including files, spreadsheets, databases, data providers, and the Web
- Store data in financial time-series objects to simplify data management, data transformation, missing-data handling, and date-math calculations
- Perform technical analysis with moving averages, oscillators, stochastics, and indices
- Create custom analysis routines and visualizations or animations to capture, present, and share your analysis processes and discoveries
- Customize your analysis environment with advanced functionality from signal processing, statistics, or econometrics

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MATLAB

[Stata Data Analysis and Statistical Software](https://www.stata.com) by StataCorp LP is an integrated statistical package designed for researchers of all disciplines. It provides the ability to do data analysis, data management and graphics and has features such as multiple imputation, factor variables, GMM, competing-risks regression, state-space modeling, predictive margins, and more.

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Stata

[SAS](https://www.sas.com) provides an integrated environment for predictive and descriptive modeling, data mining, text analytics, forecasting, optimization, simulation, experimental design and more. From predictive analytics to model deployment and process optimization, SAS provides a range of techniques and processes for the collection, classification, analysis and interpretation of data to reveal patterns, anomalies, key variables and relationships, leading ultimately to new insights and better answers faster.

[SASEHAVR](http://support.sas.com/documentation/cdl/en/etsug/67525/HTML/default/viewer.htm#etsug_sasehavr_gettingstarted01.htm) is a seamless interface between Haver and SAS data processing that enables SAS users to read economic and financial time series data that reside in a Haver Analytics DLX (Data Link Express) database. [SASEHAVR](http://support.sas.com/documentation/cdl/en/etsug/67525/HTML/default/viewer.htm#etsug_sasehavr_gettingstarted01.htm) requires both SAS/ETS and Base SAS Software.

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[RATS (Regression Analysis of Time Series) Econometric Software](https://estima.com) by Estima is a leading econometrics and time-series analysis software package. It provides ability to do linear and non-linear least squares, forecasting, SUR and ARIMA models and in addition, supports advanced techniques such as GMM, ARCH and GARCH models, state space models, and more.

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RATS

Session 1: Bootcamp Part 1

Visualization with GGPlot2 and data analysis

Session 2: Bootcamp Part 2

Session 3: Univariate Models Part 1

Session 4: Univariate Models Part 2

Session 5: Vector Autoregressions

Session 6: Cointegration and error-correction models

A popular open source option for statistical computing and graphics that is available on many UNIX platforms, Windows and MacOS

Estimating, evaluating, and forecasting ARIMA models

Understanding the concept of non-stationarity and testing for unit roots

Estimating autoregressions, granger causality tests, and impulse response functions

Understanding the concept of cointegration and testing using the Enger-Granger test

Estimating and forecasting with vector error correction models

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Teaches econometrics and forecasting at the University of Colorado Denver. He has over 15 years of econometric experience in both the private and public sector.

Daniel L. Jerrett, Ph.D.

Abdel M. Zellou, Ph.D.

Bootcamp and Econometric Tools 1 & 2

Econometrics Training: Applied Time Series in R

Session 5: Multivariate Models Part 1

Session 6: Multivariate Models Part 2

Haver partners with SmartMacro Labs to offer a two week immersive online course introducing participants to the power of the Python programming language. This applied hands-on training develops statistical economics skills with a concentration on economics and finance.

Gain proficiency in building modern time-series models in Python through real-world applications. Designed for professionals in both the public and private sector, the course does not require prior experience, assuming only that participants have a basic understanding of regression and statistical concepts.

Proficiency working in Jupyter notebooks and the Python environment

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Remote Training: Applied Time Series in Python

Tom Moeller

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The U.S. Treasury Department reported a U.S. government budget surplus of $258.4 billion during April, which compared to a surplus of $209.5 billion twelve months earlier. The Action Economics Forecast Survey expected a $264.0 billion surplus in April. During the first seven months of the current fiscal year, the government ran a budget deficit of $1.049 trillion versus a deficit of $855.2 billion it the first seven months of FY’24.

Overall revenues in the first seven months of FY’25 increased 4.9% y/y compared to a 10.3% y/y rise in the first seven months of last year. Individual income tax receipts rose 7.0% y/y compared to last year’s 11.4% y/y gain. The level of corporate tax receipts fell 9.2% y/y so far this year after a 27.5% y/y rise in the first seven months of FY’24. Social insurance revenues increased 3.5% y/y after a 6.6% y/y rise in the first seven months of FY’24, while excise taxes rose 20.0% y/y so far in FY’25 compared to a 14.0% gain in the first seven months of last fiscal year. Customs duties rose 34.4% y/y in the first seven months of FY’25 after a 7.4% y/y decline last fiscal year.

Federal government outlays grew 8.9% y/y so far in FY’25 versus a 5.8% y/y 	rise in the first seven months of FY’24. Defense spending rose 7.8% y/y versus a 7.0% y/y rise in the first seven months of last fiscal year. Social Security outlays rose 8.4% y/y in the first seven months of FY’25 versus an 8.7% increase in the first seven months of last fiscal year. Interest payments rose 12.6% y/y so far in FY’25 after a 41.4% rise in the first seven months of last fiscal year. Health program spending rose 7.1% y/y after rising 0.8% early in FY’24 while Medicare payments surged 18.4% y/y versus a 9.1% y/y rise last year. Income security outlays rose 8.0% y/y early this year compared to a 16.3% y/y decline in the first seven months of FY’24.

Haver's data on Federal Government receipts & outlays are contained in **USECON**. The expectations figure is in the **AS1REPNA** database.

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- Federal receipt growth slows in FY 2025.
- Outlay growth surges this fiscal year.

U.S. Federal Government Runs a Budget Surplus in April; Larger Deficit ‘YTD

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The Industrial Materials Price Index from the Foundation for International Business and Economic Research (FIBER) rose 0.6% (-3.6% y/y) during the four weeks ended May 9, 2025. The improvement followed sharp declines in April.

Miscellaneous group prices increased 2.4% (5.9% y/y) over the last four weeks. Natural rubber price soared 13.9% (11.7% y/y). The price of tallow (used in the soap industry) rose 10.6% (41.3% y/y) in four weeks but the cost of framing lumber declined 5.6%, but rose 7.3% y/y.

Prices in the Metals group edged 0.2% higher (-7.3% y/y) over the most recent four weeks. Variation in pricing was wide. Copper scrap prices rose 7.4% (-3.3% y/y) while lead costs rose 4.0% in four weeks (-11.1% y/y). The cost of aluminum increased 2.3% in four weeks, off 4.4% y/y. Working lower, the cost of steel scrap declined 8.1% (-11.6% y/) in four weeks while tin prices followed with a 4.9% decline (-2.9% y/y). Zinc prices eased 0.7% in four weeks and declined 10.3% y/y.

Crude Oil & Benzene group prices edged 0.1% higher (-19.4% y/y) in four weeks. The cost of West Texas Intermediate crude oil weakened 4.0% to $58.50 per barrel and was 25.6% lower y/y. The cost of the petrol-chemical benzene, used for making plastics & synthetic fibers, strengthened 8.5% (-41.8% y/y) in the last four weeks. Excluding crude oil, the industrial commodity price index rose 0.9% (-2.1% y/y) during the last four weeks.

Textile group prices edged 0.9% lower (-0.5% y/y) during the last four weeks. Burlap costs declined 14.3% (+7.4% y/y) but the cost of cotton rose 4.5% (-7.7% y/y) over four weeks.

The Foundation for International Business and Economic Research (FIBER) develops economic measurement techniques as applied to business cycles and inflation in the U.S. and other market economies. The commodity price data can be found in Haver's **DAILY**, **WEEKLY**, **USECON** and **CMDTY** databases.

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- Metals prices are mixed.
- Crude oil prices fall sharply.
- Textile prices ease.

FIBER: Industrial Commodity Price Movement Diverges in Latest Four Weeks

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Wholesale trade inventories increased 0.4% (2.2% y/y) during March after rising 0.5% in February, revised from 0.3% after a 0.8% January rise. The increase compared to expectations for a 0.5% rise in the Informa Global Markets Survey and compared to a 0.6% gain in the advance report issued two weeks ago.

Durable goods inventories rose 0.6% in March (1.5% y/y) after rising 0.5% in February. Machinery inventories, the largest sector, increased 0.6% (1.7% y/y) while inventories of motor vehicles & parts, the second largest grouping, rose 1.2% (0.8% y/y). Furniture inventories strengthened 2.7% (6.8% y/y) while electrical equipment inventories declined 1.0% (-3.1% y/y). Inventories of nondurable goods edged 0.1% higher (3.4% y/y). Drug inventories, which make up one-quarter of nondurable inventories, advanced 1.0% (4.6% y/y). Grocery inventories, the second largest category, rose 0.4% (8.3% y/y). Apparel inventories fell 0.8% (-6.5% y/y) and chemical inventories rose 2.1% both m/m and y/y. Petroleum inventories increased 0.7% (0.3% y/y).

Sales at the wholesale level rose 0.6% (6.1% y/y) in March after rising 2.0% in February and falling 0.9% in January. A 0.9% March rise had been expected in the Action Economics Forecast Survey.

Durable goods sales rose 1.0% (8.5% y/y) in March after strengthening 3.2% in February. Sales of electrical equipment & electronic goods, the largest sector, rose 2.5% (20.9% y/y), after a 2.3% rise. Professional and commercial equipment sales, which includes computers, rose 1.2% (11.9% y/y), while vehicle sales declined 1.0% (1.1% y/y). Sales of machinery improved 0.7% (4.2% y/y). Nondurable product sales rose 0.3% (3.9% y/y) in March after gaining 0.9% in February. Drug store sales, the largest category, increased 2.8% (13.4% y/y), while grocery store sales eased 0.2% (+4.3% y/y). Sales of apparel weakened 0.8% (+3.5% y/y) while paper sales declined 1.7% (0.5% y/y). Petroleum product sales fell 4.6% both m/m and y/y.

The inventory-to-sales (I/S) ratio at the wholesale level remained at 1.30 in March and has been moving lower for the last two years.

The wholesale I/S ratio for durable goods eased to 1.69 in March and also has been trending lower. The machinery ratio fell to 2.92 while motor vehicles rose to 1.78. The I/S ratio for nondurable goods slipped to 0.93 and remained down from 1.02 early in 2023. The drug industry ratio eased to 0.94. Apparel's I/S ratio held at 2.06, but remained below its 2.28 level one year earlier, and has been declining since early 2023. The petroleum industry I/S ratio rose to 0.33.

The wholesale trade figures are available in Haver's **USECON** database. The expectations figure for inventories is contained in the **MMSAMER** database. Expectations for sales are from the **AS1REPNA** database.

**Assessing Maximum Employment** from Federal Reserve Governor Adriana D. Kugler is available [here](https://www.federalreserve.gov/newsevents/speech/kugler20250509a.htm).

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- Inventories trend higher y/y.
- Sales increase broadly.
- Inventory-to-sales ratio steadies.

U.S. Wholesale Inventories & Sales Increase in March

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Nonfarm labor productivity fell 0.8% (SAAR) during Q1’25 after increasing 1.7% in Q4’24, revised from 1.5%. A 0.6% decline had been expected in the Action Economics Forecast Survey. It was the first productivity decline since Q2’22. The y/y increase during Q1 fell to 1.4% from 2.1% in Q4. It was below a 3.3% high in the first quarter of last year. Productivity fell as real value-added output dropped 0.3% last quarter (+2.2% y/y) after increasing 2.5% in Q4, and hours worked lengthened 0.6% (0.8% y/y) following a 0.8% gain.

Compensation per hour increased 4.8% last quarter following a 3.7% Q4 rise. Despite the strength of these last two increases, y/y growth decelerated to 2.7% from a 6.8% high one year earlier. Nevertheless, the productivity decline raised unit labor costs by 5.7% (1.3% y/y) in Q1 versus expectations for a 5.2% increase. It followed a 2.0% gain during Q4 and was the strongest quarterly increase in a year.

Factory sector productivity surged 4.5% (1.5% y/y) during Q1’25 following three consecutive increases of roughly 0.5%. This strength was accompanied by a 6.2% rise (2.2% y/y) in hourly compensation which came after two consecutive increases of approximately 4.1%. The strength in productivity lowered the rise in unit labor costs to 1.6% from 3.8% in Q4. The y/y gain fell to 0.7% from 2.0% in Q4 and stood below the 6.2% y/y increase in Q1’24.

The productivity and labor cost data are available in Haver’s **USECON** database. The Action Economics expectations figures are in the **AS1REPNA** database.

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- Productivity declines with lower output.
- Compensation surge exacerbates labor market stress.
- Factory sector productivity surge lessens cost pressure.

U.S. Productivity Declines in Q1’25; Unit Labor Costs Surge

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The National Association of Realtors' Fixed Rate Mortgage Housing Affordability Index (HAI) rose 0.6% (3.2% y/y) in March to 103.2 after rising 0.9% to 102.6 in February and rising 0.8% in January to 101.7. The level of home affordability has risen 14.8% from its low of 89.9 in October 2023. It remains 42.4% below the high of 179.2 in April 2020.

The rise in affordability in March occurred as the median price of an existing single-family home rose 1.8% (2.9% y/y) to $408,000 which was offset by a decline in mortgage rates to 6.73% from 6.92% in February. The price compared to the record $432,900 in June 2024. The decline in mortgage rates compared to a recent low of 6.26% in September of last year and a 7.70% high during October of 2023. It remained well above a December 2020 low of 2.73%. These changes lowered the principal & interest payment by 0.2% (+1.1% y/y) to $2,113 per month. That was well above the most recent low of $984 in February 2020. Monthly mortgage payments averaged a lessened 24.2% of income during March. They remained up from a low of 14.0% of income in April 2020.

The rise in housing costs in March was accompanied by improvement in median family income. It increased 0.4% (4.4% y/y) to a record $104,705 after rising 0.4% in February and 0.7% in January.

Housing affordability improved m/m across the country in March. The index edged 0.1% higher (2.8% y/y) to 134.5 in the Midwest. It remains the most affordable region of the country. In the South, the index 0.9% (5.4% y/y) to 106.6 and the affordability index in the Northeast increased 2.1% (-2.6% y/y) to 95.7. In the West, where homes are the least affordable, the index rose 0.8% (3.3% y/y) to 71.8 in March.

The Housing Affordability Index (HAI) equals 100 when a median-income borrower qualifies for an 80% mortgage on a median-priced existing single-family home. The HAI had exceeded 100 in each month since July 1990 and reached its all-time high of 213.3 in January 2013; since then, it fell below 100 for the first time in June 2022.

Data on Housing Affordability can be found in Haver’s **REALTOR** database. Median home sales prices are also available in **USECON**. Higher frequency interest rate data are found in **SURVEYS**, **WEEKLY**, and **DAILY**.

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- Home prices rise but mortgage rates decline.
- Median income improves.
- Affordability increases across the country.

U.S. Housing Affordability Improves Slightly in March

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International Transactions in Securities, Lending to Finl Institutions, Teikoku Databank Corporate Bankruptcies (Apr)

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