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, W
indows 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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Initial claims for unemployment insurance rose to 223,000 in the third week of January from an unrevised 217,000 during the prior week. A 215,000 increase in initial claims had been expected in the Action Economics Forecast Survey. Initial claims have risen from a 203,000 low in the first week of January. During the last four weeks, initial claims averaged 213,500, down from 226,750 four weeks earlier.

Continuing claims for jobless insurance increased 46,000 (7.8% y/y) to 1.899 million in the week ended January 11 from 1.853 million in the prior week. Ongoing claims have risen from a low of 1.834 million in the third week of December. The four week moving average of continuing jobless insurance claims eased to 1.866 million, down from a 1.888 million high in the third week of November.

The insured rate of unemployment was 1.2% for the fourth straight week. This level was increased from a 2022 low of 0.9% and compares to the rise in the overall unemployment rate to 4.1% from 3.4% over the same period.

Unemployment rates vary widely across states. The Labor Department reports that for the week ended January 4, the insured unemployment rate was highest in Rhode Island (3.22%), New Jersey (3.07%), Minnesota (2.73%), Washington (2.52%) and Massachusetts (2.41%). The insured unemployment rates were lowest in Florida (0.33%), Virginia (0.43%), Tennessee (0.58%) and Alabama (0.52%) and the Virgin Islands (0.67%). Rates in other notable states include California (2.32%), Pennsylvania (2.24%), New York (2.08%) and Texas (1.13%). These state rates are not seasonally adjusted.

Data on weekly unemployment claims are from the Department of Labor itself, not the Bureau of Labor Statistics. They begin in 1967 and are contained in Haver’s **WEEKLY** database and summarized monthly in **USECON**. Data for individual states are in **REGIONW** back to December 1986. The expectations figure is from the Action Economics Forecast Survey in the **AS1REPNA** database.

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- Initial jobless claims increase to highest level in six weeks. 
- Continuing claims approach four-week high.
- The insured unemployment rate remains low.

U.S. Unemployment Insurance Claims Rise in Latest Week

Robert Brusca

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EU order trends ‘improved’ slightly in January as the net diffusion reading rose from -40 to -34. Still, that improvement leaves orders below their 3-month, 6-month, or 12-month averages. The queue standard of January orders is in the lower 14th percentile of its historic queue of data. Obviously, it remains a historically weak reading. The order series is volatile as the chart shows. But it is still in a clear downtrend even with the uptick this month.

Export orders have approximately the same profile as for orders overall. But export orders weaken slightly in January compared to December. Export orders overall have a slightly weaker queue standing than total orders at a 13.4 percentile level.

The diffusion readings for stocks of finished goods weakened in January but even with its weaker January assessment, stocks have a firm-to-strong 72.5 percentile standing.

Looking ahead, the outlook for output volume over the next three months improved sharply from its stunning weak reading of -31 in December. However, the rise to -19 in January represents only a 4.8 percentile standing.

Unfortunately, average output prices for three months ahead has reading of +27 in January, up from +23 in December and +11 in November; the backtracking in prices expected, has brought the expectation level for the current reading to a high, 90-percentile standing. These rising inflation expectations are going to be a real problem for the Bank of England.

IP data lag the CBI survey responses. The manufacturing IP growth rate, year-on-year, has a 17.4 percentile standing as of its most recent observation in November 2024. That is also very weak. The CBI results are not giving a different message from the industrial production data, but they are timelier.

The ramp up in inflation expectation is not good new with CPI-H inflation at 3.5% year-over-year and with the core pace at 4.2%. Core inflation, sequentially, is looking stable around the 4.2% pace; for the headline, the pace has accelerated from 3.5% over 12 months to a pace of 5.4% over three months. These results, coupled with the rise in CBI expectations, are not good news for the U.K. or for the BOE.

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United Kingdom

U.K. Order Trends Are Still Eroding

Andrew Cates

**Energy and labour markets**
Chart 1 below highlights two key trends: the real consumer price of energy in the OECD economies (indexed to 1970) has shown significant volatility, with sharp spikes during periods of energy crises (e.g., 1970s oil shocks, 2008, and post-pandemic supply constraints) and declines following market adjustments or advances in energy production. Meanwhile, the US labour share of business output has experienced a steady decline since the 1980s, reflecting structural changes in the economy such as globalization, technological advances, a shift in bargaining power away from labour toward capital as well as higher real energy prices. These trends and the interplay between them will arguably form the basis of several policy choices that will be made (or already are being made) by a new US administration.

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**Electricity prices**
Energy prices, their level and their volatility, arguably play a much bigger role in broader macroeconomic fluctuations than they are given credit for. Chart 2 below shows electricity prices (a 2-year average) across six major developed economies. It shows that the US has faced the cheapest electricity at around $44/MWh. The UK and Germany, in contrast, have faced the most expensive electricity at respectively $106/MWh and $94/MWh. This disparity reflects a mix of factors: European countries, particularly the UK and Germany, face elevated prices due to heavy reliance on natural gas imports, exacerbated by geopolitical tensions (e.g., reduced Russian supply), higher renewable energy integration costs, and carbon pricing mechanisms. The US, in contrast, enjoys lower electricity costs due to more abundant domestic energy resources, particularly natural gas, and less exposure to international energy markets. Against this backdrop it is hardly a surprise that the US economy has flourished (relative to other advanced economies) while the UK and Germany have floundered.

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**The UK labour market**
This week’s labour market data additionally suggest that the UK will probably struggle to keep pace with the US economy in the period immediately ahead. The data specifically revealed that employment growth is slowing on all measures, and the PAYE measure of payrolls in particular (see chart 3 below). And while private sector pay growth has also slowed, the 6-month annualised rates of growth still stood at a relatively lofty 5.8% in December. Weaker employment growth will encourage the BoE to cut rates again before too long (probably in February) but weaker wage growth could also be necessary for a much looser policy stance to be enacted over the next few months.

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**Household savings and labour market activity**
At a broader global level, a key risk to the economic outlook at present concerns restrictive monetary policy and its impact on labour market activity and household spending. Chart 4 below shows that household saving rates in the world’s major economies have – on the whole – been rebounding over the past two years. Simultaneously, the unemployment rate in advanced economies has begun to climb. These trends align with the tightening of monetary policy that’s been enacted in recent years and economic uncertainty. But if that combination persists, it could place a bigger brake on the world economy this year than many analysts are anticipating.

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**China’s credit impulse**
Another big source of uncertainty, at present, concerns China. Chart 5 below compares the Citigroup Economic Surprise Index for emerging markets (EM) and Haver’s calculations for China’s credit impulse (the change in new credit as a percentage of GDP). The chart suggests that China's credit growth influences broader EM economic fluctuations. During periods of robust credit growth (e.g., 2020-2021), driven by stimulus measures, EM economies benefited from improved liquidity and demand from China. Conversely, periods of credit tightening (e.g., 2017 and 2023-2024) weighed on economic surprises, reflecting weaker support for growth. These dynamics underline China’s outsized role in shaping sentiment and economic conditions in emerging markets. That its credit impulse, moreover, remained negative in Q4 (of 2024) underscores how China might continue to exert downward pressure on the world economy in the period immediately ahead.

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**South Korean trade**
Another source of uncertainty for the world economy, at present, is the optimism surrounding AI. While proponents highlight its transformative potential to boost productivity, efficiency, and innovation across industries, sceptics question the timeline for a meaningful economic impact. With that in mind it would be inappropriate to draw strong conclusions from chart 6 below but it is certainly of note that South Korea – which has been heavily reliant on AI-fuelled trade – saw a big slowdown in export growth in the first 20 days of January. Much of that slowdown, moreover, could be traced to a big drop in semiconductor trade.

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Financial markets have enjoyed a notable lift in sentiment over recent days, driven by renewed optimism about the domestic economic policies of a new US administration. Investors have certainly been cheered by early signals of a pro-growth strategy, with the energy sector taking centre stage following a ceasefire between Israel and Gaza and the announcement of measures aimed at reducing US energy costs (see charts 1 and 2). Meanwhile, China’s stronger-than-expected growth figures last week and softer-than-expected inflation readings from both the US and the UK have fuelled gains across equity and bond markets, bolstering risk appetite in other markets. However, despite the prevailing optimism, several factors warrant caution. Chief among them is the global uncertainty that surrounds the policy choices of a new US administration. The policy choices of central banks will also be critical, particularly as labour market strength could keep inflation risks alive (charts 3 and 4). Questions also linger about China’s ability to sustain its growth momentum, especially as its property sector and consumer demand face ongoing challenges (chart 5). Finally, while artificial intelligence is increasingly seen as a driver of future growth and productivity, doubts persist over its near-term potential to meaningfully transform the world economy (chart 6). For now, investors appear content to ride the wave of positive sentiment, but vigilance over these risks will be critical as the economic landscape continues to evolve.

Charts of the Week: Trump Cards

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The Conference Board's Leading Economic Index fell 0.1% (-3.0% y/y) during December, following a 0.4% November rise, revised from 0.3%, and a 0.3% October decline, revised from -0.4%. A 0.1% easing in the December index had been expected in the Action Economics Forecast Survey. The Leading Index is comprised of 10 components which tend to precede changes in overall economic activity. The index has been trending lower since January 2022, contrasting with positive real economic growth.

During December, component changes amongst the leaders diverged. Series which contributed positively to the index change included a longer factory sector workweek, improved factory orders for consumer goods, an increase in orders for nondefense capital goods excluding aircraft, higher stock prices in the S&P 500 index and the leading credit index. Series contributing negatively were higher initial unemployment insurance claims, a lower ISM new orders index, falling building permits, the interest rate yield curve and consumer expectations for business/economic conditions.

The Coincident Economic Index rose 0.4% last month (1.6% y/y) after rising 0.2% in November and holding steady in October. Movement amongst the four components was uniformly positive in December. Industrial production jumped by the largest amount since February, real personal income strengthened steadily, payroll employment improved on prior two months’ increases while real manufacturing & trade sales rose steadily.

The Lagging Economic Index improved 0.1% last month (0.3% y/y) after rising 0.2% in November and remaining unchanged in October. The 6-month change in the services CPI, the 6-month change in unit labor costs and the ratio of consumer installment credit-to-personal income contributed positively to the index change. The business inventory-to-sales ratio contributed nothing to the index change. The duration of unemployment, the prime interest rate charged by banks and commercial & industrial loans outstanding contributed negatively to the index change.

The ratio of coincident-to-lagging indicators, considered another leading indicator, rose 0.3% last month after holding steady for two straight months.

The Conference Board figures are available in Haver's **BCI** database; the components are available there, and most are also in **USECON**. The expectations are in the **AS1REPNA** database. Visit the Conference Board's [website](https://www.conference-board.org/us/) for coverage of leading indicator series from around the world.

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- Movement in leading indicator components remains mixed.
- Coincident indicators strengthen.
- Lagging indicators edge higher.

U.S. Leading Indicators Ease

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Retail gasoline prices for all grades rose to an average $3.23 per gallon (1.5% y/y) in the week ending January 20 from $3.16 in the prior week. The all-time high of $5.11 was in the week ending June 13, 2022. The retail price for on-highway diesel fuel jumped	to $3.72 per gallon (-3.2% y/y) in the week of January 20, the highest level since early-August, from $3.60 in the prior week. The latest price was down from a high of $4.63 in the week ending September 18, 2023 and a peak of $5.81 in the week ending June 20, 2022.

The price of West Texas Intermediate crude oil rose to $78.58 per barrel (7.3% y/y) in the week ending January 17 after increasing to $74.32 in the prior week. It was the highest level in five months but still below the peak of $120.46 in the week of June 10, 2022. Yesterday, the price was $75.89 per barrel. The price of European Brent crude oil rose to $82.53 per barrel (3.0% y/y) in the week of January 17 from $78.14 in the prior week. Prices remained below a peak of $127.40 in the week of June 10, 2022. Yesterday’s price was $80.57 per barrel.

Natural gas prices surged to an average $5.47/mmbtu (87.3% y/y) in the week of January 17 from $3.93 in the prior week, posting the highest level since a high of $5.11/mmbtu in the week of January 12, 2024. Prices reached a low of $1.40/mmbtu in the week of March 15, 2024 and a peak of $9.56 in the week of August 26, 2022. Yesterday, the price was $4.40/mmbtu.

Gasoline demand rose 0.8% y/y in the four weeks ending January 10 on top of a 1.2% y/y gain in the prior four weeks. Demand for all petroleum products increased 1.1% y/y in the four weeks ending January 10. Crude oil input to refineries increased 1.2% y/y in the four weeks ending January 10 after a 1.5% y/y rise in the prior four weeks.

Gasoline inventories fell 1.8% y/y in the week ending January 10 after a 3.0% y/y decline in the prior week. In contrast, residual fuel oil inventories fell 12.1% y/y in the week of January 10 following a 5.7% y/y decrease in the prior week. Crude oil inventories rose 2.7% y/y in the week of January 10, the same as during the prior week.

Measured in days’ supply, gasoline inventories rose to 28.7 days in the week of January 10 from 27.5 days in the prior	 week, registering the highest reading since the end of February 2024. The recent low was 22.9 days in the week of November 8. The supply of crude oil was little changed at 24.6 days in the week of January 10, still near the lowest number since a low of 24.8 days in the week of September 20, 2024 and below a 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** & **USENERGY** database.

- Gasoline prices reach three-month high.
- Crude oil costs surge.
- Natural gas prices strengthen to two-year high.

U.S. Energy Prices Increase Sharply

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