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 Housing Market Index, compiled by the National Association of Home Builders/Wells Fargo, rose 2.7% (-17.4% y/y) to 38 in November after surging 15.6% in October and holding steady in September. The latest reading was the highest since April, but remained below the break-even point of 50 where it’s been since May of last year. The index also remains under a July 2023 high of 56 and a November 2020 peak of 90.

The rate on a 30-year fixed rate mortgage averaged 6.23% in the first two weeks of November versus 6.25% during all of October. It was 6.24% last week and remained below the high of 7.79% in the last week of October 2023, according to Freddie Mac.

The single-family home sales measure rose 5.1% (-14.6% y/y) this month to 41, a seven-month high, after rising 14.7% in October. The prospective sales in six months measure fell 5.6% (-19.0% y/y) to 51, after rising 20.0% in October. The traffic of prospective buyers’ index rose 4.0% (-18.8% y/y) to 26 in November, after rising 19.0% in October.

Housing activity was uneven this month across the country. The sales index in the South rose 5.7% (-11.9 y/y) to 37 after increasing 20.7% in October. In the West, the index increased 6.5% (-15.4% y/y) to 33 after rising 19.2% in October. The sales index in the Northeast fell 18.2% (-21.1% y/y) to 45 after rising 25.0% in October. In the Midwest, the sales index declined 4.8% (-16.7% y/y) to 40 after rising 2.4% in October. 

The NAHB has compiled the Housing Market Index since 1985. It reflects survey questions which ask builders to rate sales and sales expectations as "good," "fair" or "poor" and traffic as "very high," "average" or "very low." The diffusion indexes with values over 50 indicating a predominance of "good"/"very high" readings. In constructing the composite index, the weights assigned to the individual index components are: 0.5920 for single-family detached sales, present time, 0.1358 for single-family detached sales, next six months, and 0.2722 for traffic of prospective buyers. The regional indexes run back to December 2004.

These data are included in Haver's **SURVEYS** database.

The Case for Continuing Rate Cuts from Fed Governor Christopher J. Waller can be found [here](https://www.federalreserve.gov/newsevents/speech/waller20251117a.htm).


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- Overall reading is highest in six months.
- Current sales traffic improves; prospective sales backpedal.
- Index is mixed throughout the country.


U.S. Home Builders Index Edges Higher in November

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Retail gasoline prices for all grades remained at an average $3.19 per gallon (+0.7% y/y) in the week ended November 17 after rising from $3.15 in the first week of November. The recent high was $3.79 in the week ending April 22, 2024. Their all-time high of $5.11 occurred in the week ending June 13, 2022. Haver Analytics seasonally adjusts the retail price of regular grade gasoline. That price rose to $3.15 last week from $3.10 in the previous week. Diesel fuel prices rose to $3.87 per gallon last week (10.8% y/y) after increasing to $3.84 per gallon in the prior week.

The price of West Texas Intermediate crude oil fell to an average $59.69 per barrel (-12.3% y/y) in the week ended November 14 after easing to $60.08 per barrel in the prior week. Prices remained below a recent high of $74.17 during the third week of June. The cost of crude oil peaked at $120.46 in the week of June 10, 2022. Yesterday, the price was $59.91 per barrel. The price of European Brent crude declined to $62.87 per barrel (-13.7% y/y) in the week of November 14 after falling to $64.30 in the prior week. Prices remained below a recent high of $95.61 in the week of September 29, 2023 and below a peak of $127.40 in June 2022. Yesterday, the price was $63.16	 per barrel.

Natural gas prices edged higher to an average $3.62/mmbtu (102.2% y/y) in the week ended November 14 after rising to $3.54/mmbtu in the prior week. The increase left prices at the highest level since the second week of April and well above the low of $1.40/mmbtu in the week of March 15, 2024. Yesterday, the price was $3.71 per mmbtu.

Gasoline demand declined 2.6% y/y in the four weeks ending November 7, after falling 2.1% y/y in the prior four weeks. Demand for all petroleum products weakened 0.9% y/y in the four weeks ending November 7, after falling 1.2% y/y in the previous four-week period. Crude oil input to refineries declined 4.3% y/y in the four weeks ending November 7, after falling 4.5% y/y in the prior four weeks.

Gasoline inventories fell 0.9% y/y in the week ending November 7 following a 2.5% y/y decline in the prior week. Residual fuel oil inventories fell 2.6% y/y in the November 7 week after falling 7.1% y/y in the prior week. Working higher, crude oil inventories rose 2.5% y/y in the week of November 7 after increasing 1.9% y/y in the previous week.

Measured in days’ supply, gasoline inventories fell to 23.3 days in the week of November 7 from 23.7 days in the prior week. The recent low was 22.9 days in the week of November 7, 2024. The supply of crude oil held w/w at 27.5 days in the week of November 7. The supply remained below a recent high of 31.9 days in the week of March 3, 2023.

These data are reported by the Energy Information Administration of the U.S. Department of Energy. The price and supply/demand data can be found in Haver’s **WEEKLY** and **USENERGY** databases.



- Gasoline prices hold steady week-to-week.
- Crude oil prices decline.
- Natural gas prices move to highest level since April.
- Demand for gasoline & all petroleum products declines.


U.S. Energy Prices Remain Mixed in Latest Week

Robert Brusca

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Inflation around the world appears to be rather similarly behaved  Canada is a very close trading partner of the United States and so we might expect that there would be a little more connection between the prices in Canada and in the US and possibly we can learn something about the upcoming US CPI report by looking at the just-released Canadian CPI report.  

Canadian inflation is highly correlated with inflation in the US. The US and Canadian CPI's have a correlation of 0.97 on annual percentage changes. Canada's CPIx measure has a correlation with the US headline CPI of 0.94 and the Canadian core inflation rate has the correlation with US core inflation rate of 0.94. All of these measured against year over year inflation.  Clearly with a good deal of trade and a long common border prices in the US and Canada have a chance to mix it up and affect one another and create some degree of homogeneity. However, none of that is really perfect. Despite the strong correlation between headline inflation and core inflation between the US and Canada, Canada's core CPI and the US core CPI have a correlation based on month-to-month changes of less than 0.2 Using an R-squared metric. 

Well, it might be somewhat comforting to look at Canadian inflation, and I think it's giving some guidance for the US. That would only be true over a long period of time, but it probably doesn't provide much guidance for us in terms of what we can expect from the month-to-month changes.

While Canada's correlation with US inflation is high it's correlation with inflation in Japan it's only 0.33: only 1/3 of the variants in these two indicators is in common. In terms of the Euro-Area the correlation is less than -0.1, which tells us the correlation is negative and extremely small and of course not statistically significant. 

The Canadian CPIx measure shows inflation pretty flat at around 2.6% over 3 months and over 12 months. Canada's 6-mo CPI measure accelerates from 2.2% over 12-months to a 2.6% annual rate over 6-months to a 3% pace over three months. US inflation on these horizons essentially replicates what's presented by Canada's CPI X based on existing data. However, the R-squared association between the three month annualized percent change in the Canadian CPI versus the US CPI shows that they share about half of the same variation with an R-squared of about 0.5. And on this comparison Canada’s and US’ recent inflation trends appear to be highly similar.

The Bank of Canada looks at inflation using several different metrics and it also looks at inflation relative to a range unlike the US, leading to a much more measured discussion of what inflation is and how it's performing. 

The decision by the Fed in the US to stick with a simple point forecast at this point is something that probably cannot be changed, at least not until the central bank is able to show that it can hit that target consistently. Even so, the Fed has not showed a great appetite for trying to express inflation in terms of a target band. However, when the Fed changed its framework agreement it did adopt something called flexible average inflation targeting (FAIT) which never really described for us or explained what it was and it has a set that approach aside I think to the pleasure of most economists. 

There continues to be buzzing and differences of opinion over what the inflation target should be in the US. However, the international standard has been set at 2 per cent and at this point adopting a number different than that doesn't seem to make a lot of sense. Adopting 2% with some flexibility might make some sense but, of course, the Fed is already doing that as it's allowed a 4 1/2-year overshoot of its inflation target as it continues to cut rates. This decision, however, does not amount to a change in the Fed’s inflation targeting but rather to a set of decisions that appears to be losing the Federal Reserve credibility. Meanwhile, the Bank of Canada, operating with the range and having had much the same kind of access that the Fed has had in hitting and missing its inflation target midpoint, has emerged from this period with its credibility largely intact.







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Canada

Canadian CPI Trends Show Little Change 

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The Empire State Manufacturing Index of General Business Conditions Index increased to 18.7 in November after rising to 10.7 in October and falling to -8.7 during September, according to the Empire State Manufacturing Survey released by the Federal Reserve Bank of New York. The latest was the highest reading in twelve months, holding above the break-even level of zero for four of the past five months. The Action Economics Forecast Survey expected a reading of 6.0 for November. The percentage of respondents reporting an increase in general business conditions rose to 38.7% in November after increasing to 36.6% in October. The percentage reporting a decline in activity fell to 20.0% after weakening to 26.0% in October. The latest survey was conducted between November 3 and November 10. The headline reflects the answer to a single question concerning the state of economic activity and is not calculated from the components.

Haver Analytics calculates a composite index from the five major components, which is comparable to the ISM manufacturing index. It rose to a nearly three-year high of 55.4 from 52.7 in October. The index is an average of five diffusion indexes: new orders, shipments, employment, supplier deliveries and inventories, each with equal weights of 20% each.

The increase in the Empire State readings this month was paced by a surge in the new orders index to 15.9 from 3.7 in October. A higher thirty-eight percent of respondents reported an increase in order, while the percentage reporting a decline in orders fell to 22.1%. The shipments index strengthened to 16.8, a twelve month-high. Inventories jumped to 6.7 after three straight negative readings. The delivery times measure increased to 7.7 from 3.9. On the labor front, the employment reading strengthened to 6.6, a four-month high. Fourteen percent of survey respondents reported higher employment while 7.2% reported less. The average workweek reading surged to 7.7, after two straight negative readings, climbing to the highest level since May 2022. Moving lower, the unfilled orders index in November fell to -5.8, after improving to -3.9 in October. 

Inflation readings weakened in 	November. The prices paid index fell to 49.0 after rising to 52.4 in October. A lessened 51.9% of respondents reported higher prices while an increased 2.9% indicated a decline. The prices received index eased to 24.0 after rising to 27.2 October. Both prices paid & prices received indexes, however, remain significantly higher than early last year.

Optimism amongst survey respondents about business during the next six months weakened in November. The index for future general business conditions fell to 19.1 from 30.3 in October. Expected new orders, shipments, unfilled orders and delivery time declined. The future workweek reading also declined but the expected employment reading rose to the highest level since January. The future prices paid declined after rising to the highest level since May while prices received in six months fell to a three-month low. The expected capital spending plans reading surged this month to the highest level since January.

The indexes in this report are diffusion indexes and measure the percentage of respondents indicating an increase minus the percentage indicating a decrease with zero separating expansion from contraction.

The New York Fed survey data are contained in Haver’s **SURVEYS** database. The expectations series is in Haver’s **AS1REPNA** database.



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- New orders, shipments, employment & hours rise.
- Prices paid & received decline.
- Six-month outlook deteriorates.


Empire State Manufacturing Index Continues to Strengthen in November

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The Industrial Materials Price Index from the Foundation for International Business and Economic Research (FIBER) increased 0.9% during the four weeks ended November 14, 2025 after easing 0.1% in the prior four-week period. The index increased 1.5% y/y last week following a 0.5% y/y gain in the first week of the month.

**Textile** group prices increased 2.3% during the last four weeks, about the same as they did in the prior four weeks, and rose 3.1% y/y. The cost of burlap surged 23.4% in the last four weeks while rising a steady 48.1% over the last year. Showing a second week of modest improvement, cotton prices rose 0.4% in four weeks but declined 7.1% y/y.

**Metals** sector prices increased 2.7% (9.9% y/y) in the last four weeks after a 1.5% rise in the prior four weeks, as the cost of aluminum rose 3.2% (12.4% y/y). Zinc prices strengthened 3.1% (9.0% y/y) and the cost of steel scrap rose 1.2% (-3.1% y/y). Lead prices increased 4.7% (3.5% y/y) in four weeks and the cost of copper scrap rose 1.7% (19.3% y/y). Reversing earlier declines, tin prices rose 2.7% (20.5% y/y) in four weeks.

**Crude oil & benzene** prices improved 0.9% (-8.7% y/y) in the last four weeks, following a 1.6% decline in the previous four weeks. The cost of West Texas Intermediate crude oil rose 2.0% in four weeks to $59.63 per barrel but declined 13.3% y/y. The price was increased from a low of $58.47 in the third week of last month. The price of the petro-chemical benzene rose 0.9% (-17.8% y/y) in four weeks.

**Excluding crude oil**, the industrial commodity price index increased 0.8% (2.4% y/y) over the last four weeks, after holding steady during the prior four weeks.

**Miscellaneous** sector prices declined 2.0% in the last four weeks and fell 1.9% y/y, after falling 2.9% in the prior four weeks. Framing lumber prices fell 7.0% (-5.2% y/y). The cost of tallow, used for frying & baking, declined 6.9% (+10.5% y/y) in four weeks. Offsetting this weakness, natural rubber prices rose 3.1% in four weeks, but declined 9.3% y/y.

The Foundation for International Business and Economic Research 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.

**Why Inflation Expectations Are Important to Policymakers** from the Federal Reserve Bank of St. Louis can be found [here](https://www.stlouisfed.org/open-vault/2025/nov/why-inflation-expectations-are-important-to-policymakers).

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- Textile and metals prices continue to strengthen. 
- Crude oil prices increase.
- Framing lumber costs decline again.

FIBER: Industrial Commodity Prices Increase in Latest Four Weeks

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Residential Property Index by Region (Sep)

Price Index of Private Rents by Region & Local Authority (Oct)

CPI, RPI, PPI, Price Index of Private Rents (Oct)

Mfrs' Shipments Inventories & Orders (Aug)

Monthly GDP, External Debt, IMACEC Revisions (Sep), BOP, Construction Income of Large Companies, Import & Export Prices, GDP (Q3)