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

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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

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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

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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
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- 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

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Visualization with GGPlot2 and data analysis

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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

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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

Andrew Cates

**A Tug of War Between AI Hope and Geopolitical Shock**
The latest Blue Chip Economic Indicators survey highlights a growing divergence between economies benefiting from AI-driven optimism and those more exposed to the inflationary consequences of renewed geopolitical instability. Taiwan stands out as the clearest AI beneficiary, with growth forecasts revised sharply higher while inflation expectations have risen only modestly, reflecting surging semiconductor demand and continued investment in global technology supply chains. China also remains relatively resilient, supported by ongoing AI-related capital spending and stronger technology sectors. By contrast, the euro area and UK have seen much larger upward revisions to inflation forecasts alongside weaker or declining growth expectations, underscoring their greater vulnerability to the recent Middle East shock and higher energy costs. Korea sits somewhere in between: benefiting from the AI hardware cycle but still exposed to trade and energy headwinds. Overall, the chart illustrates the increasingly important push-and-pull shaping the global outlook: AI optimism and productivity hopes on one side, and geopolitical fragmentation, energy insecurity and supply-side inflation pressures on the other.

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**Forecasters See Contained Pass-Through**
Against this backdrop, our latest Blue Chip special question sought to gauge whether economists believe the recent rise in energy prices will remain largely contained — or whether it risks spilling more meaningfully into underlying global inflation dynamics. The results suggest forecasters have become somewhat less concerned about a broad and persistent inflationary impulse since April. A larger share of respondents in the May survey now expect only a “limited and temporary” pass-through into core inflation, while the proportion anticipating “moderate and persistent” effects has declined noticeably. Very few panelists expect significant second-round effects, implying that most still believe inflation expectations and wage-setting behaviour remain relatively well anchored. In part, this reflects confidence in central bank credibility and the view that softer global demand conditions will constrain firms’ pricing power. Yet the persistence of a sizeable minority still expecting moderate pass-through underscores the uncomfortable tension facing policymakers. 

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**Energy Reawakens as a US Inflation Driver**
While survey respondents generally expect only limited pass-through from higher energy prices into broader inflation, the latest US CPI data provide a reminder that the process may already be underway at the margin. April’s CPI report showed core inflation coming in slightly firmer than expected, suggesting underlying price pressures remain more persistent than many policymakers had hoped. The decomposition of CPI inflation highlights that services continue to dominate overall inflation dynamics, reflecting still-elevated wage and labour-intensive price pressures across the economy. However, the more notable recent development has been the renewed contribution from energy prices, which had previously acted as a disinflationary force through much of 2025. Food inflation has also remained comparatively steady, while non-energy goods prices continue to exert only modest upward pressure despite ongoing tariff and supply-chain concerns. Taken together, the data reinforce the idea that the US economy is not facing a classic demand collapse, but rather a more uncomfortable supply-side environment in which geopolitical energy shocks risk colliding with still-resilient domestic demand, AI-related investment spending and sticky service-sector inflation.

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**AI: The Powerful Counterweight to Geopolitical Headwinds**
If rising energy prices and geopolitical instability represent one major force shaping the current macroeconomic outlook, the extraordinary surge in AI-related investment represents the other. The latest data from Our World in Data show global private investment in AI accelerating sharply again in 2025, reaching close to $300 billion — more than double the level seen just two years earlier. The United States continues to dominate the global AI landscape, accounting for the overwhelming majority of private investment spending, while China and Europe remain considerably smaller contributors despite continued growth. The scale and speed of the 2025 increase is particularly striking given the broader backdrop of elevated policy uncertainty, trade fragmentation and concerns about slowing global productivity growth. In effect, the global economy is now being pulled in two competing directions: on one side, geopolitical tensions, supply-chain fragilities and more recent energy shocks are weighing on confidence and raising supply-side costs; on the other, AI enthusiasm is driving an enormous wave of capital expenditure, infrastructure build-out and technology-related demand. This helps explain why growth expectations — particularly in the US and parts of Asia — have remained comparatively resilient despite an increasingly uncertain global environment.

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**Industrial Winners and Losers in a Fragmenting Global Economy**
The divergence in industrial performance across advanced economies has become increasingly striking. Taiwan has emerged as one of the clearest beneficiaries of the global AI boom, with industrial production surging as semiconductor demand, data-centre investment and advanced electronics exports continue to accelerate. Denmark has also significantly outperformed, though for very different reasons, with the extraordinary global success of its pharmaceutical sector — particularly weight-loss and diabetes drugs — driving a powerful expansion in manufacturing output. By contrast, the UK and Germany have experienced a far weaker industrial recovery. In both cases, elevated energy costs and greater dependence on imported energy have weighed heavily on industrial competitiveness since the post-pandemic energy shock. Germany’s large manufacturing sector has been particularly exposed to higher natural gas prices and weaker external demand, while the UK has continued to struggle with a combination of high energy costs, weak productivity growth and subdued business investment. The chart highlights an increasingly important feature of the global economy: countries exposed to powerful structural growth themes such as AI or pharmaceuticals are pulling away from those still burdened by energy dependence and deteriorating industrial competitiveness.

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**China’s Pulse Is Picking Up Again**
China’s economic backdrop has shown clearer signs of improvement in recent months, with both the Citigroup Economic Surprise Index and the Yicai High Frequency Economic Activity Index moving higher. The rebound suggests that incoming data have begun consistently outperforming expectations after a prolonged period of disappointment. Part of the recent improvement likely reflects the cumulative effects of policy easing, including targeted fiscal support, infrastructure spending and further efforts to stabilise the property sector. Export demand has also remained more resilient than many expected, helped in part by the continued strength of global technology and AI-related supply chains. At the same time, improving domestic mobility and energy usage indicators point to firmer underlying activity momentum. The Yicai index itself is designed to provide a near real-time pulse of the Chinese economy using a basket of high-frequency indicators including subway usage, air pollution, coal consumption, freight activity, unemployment and bankruptcy trends. While China still faces significant structural headwinds — including weak household confidence, property-sector fragilities and deflationary pressures — the recent pickup suggests that growth momentum may be stabilising at a time when several other major economies are becoming more vulnerable to geopolitical and energy-related shocks.

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The global economy is still caught between two powerful and competing forces. On one side, the AI investment boom continues to support growth, industrial activity and equity markets, particularly in the US and parts of Asia. On the other, renewed Middle East tensions and higher energy prices are adding to inflation risks and broader policy uncertainty. The latest Blue Chip survey reflects this divide clearly: growth expectations have generally held up best in economies tied to AI-related investment and technology supply chains, while inflation forecasts have risen more sharply in more energy-exposed economies such as the UK and euro area (chart 1). Forecasters still largely expect only limited pass-through from higher energy prices into core inflation, although recent US CPI data suggest underlying price pressures remain somewhat sticky (charts 2 and 3). At the same time, the extraordinary continued surge in global AI investment — now approaching $300 billion annually — highlights the sheer scale of capital being deployed into semiconductors, data centres and digital infrastructure, particularly in the United States (chart 4). The divergence in industrial production trends also reinforces the growing gap between economies benefiting from structural growth drivers — such as Taiwan’s semiconductor sector and Denmark’s pharmaceutical industry — and those struggling with higher energy costs and weaker competitiveness, notably Germany and the UK (chart 5). Meanwhile, improving Chinese activity indicators suggest policy support and stronger technology demand may finally be helping to stabilise growth (chart 6). Overall, the world economy remains resilient, but increasingly uneven, with AI-related investment continuing to offset — though not eliminate — the drag from geopolitical fragmentation and rising energy insecurity.

Charts of the Week: The Tug of War

Sandy Batten

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Total retail sales rose a solid 0.5% m/m (4.9% y/y) in April on top of a slightly downwardly revised 1.6% monthly jump in March (previously 1.7%), according to data released by the U.S. Census Bureau. The Action Economics Forecast Survey looked for a 05% m/m gain. Excluding autos, other sales increased 0.7% m/m (6.3% y/y) in April following an unrevised 1.9% monthly jump in March. Expectations were for a 0.6% monthly increase. The strong performance in March and the additional solid gain in April put the April level up 7.8% at an annual rate from the Q1 average, providing a very solid start for Q2.

As expected, the continued rise in retail gasoline prices boosted gasoline sales further in April. Gasoline sales increased 2.8% m/m in April following a 13.7% m/m surge in March and accounted for more than 40% of the April increase in total sales. However, sales were solid even without gasoline sales. Total sales excluding gasoline rose 0.3% m/m in April versus a 0.7% monthly gain in March. Sales excluding both autos and gasoline increased 0.5% m/m in April following a 0.7% m/m rise in March.

The control group of sales (total sales excluding food services, autos, gasoline and building materials that the BEA uses to construct PCE in the national accounts) posted another solid increase in March, rising 0.5% m/m in April following an upwardly revised 0.8% m/m increase in March (previously (0.7% m/m). The solid performances of the control group sales in March and April provide a strong start to Q2. April control-group sales are 5.4% at an annual rate above the Q1 average, in line with the 5.7% annualized increase in Q1. Consumer spending remains surprisingly resilient notwithstanding the recent hit to disposable income from the marked increase in energy prices.

Sales across major sectors were varied in April. Consumers clearly spent more on necessities, owing largely to higher prices. Food sales increased 0.8% m/m in April on top of a 1.0% m/m rise in March. And as already noted, gasoline sales posted another outsized monthly increase. By contrast, department store sales slumped 3.2% m/m, clothing sales fell 1.5% m/m, auto sales declined 0.4% m/m and furniture sales fell 2.0% m/m. More encouragingly, sales of nonstore retailers rose 1.1% m/m, their fourth consecutive solid monthly gain. And sales at restaurants increased 0.6% m/m in April, their third consecutive monthly rise. Analysts frequently use restaurant sales as a barometer of consumer attitudes, believing that consumers would not eat out regularly if they were under serious financial stress.

Retail sales data can be found in Haver’s **USECON** database. The expectations figures are from the Action Economics Forecast Survey in **AS1REPNA**.


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- Total sales increase 0.5% m/m in April after a 1.6% monthly jump in March.
- Gasoline sales rose 2.8% m/m in April on top of a 13.7% surge in March.
- Auto sales fell 0.4% m/m after a 0.6% m/m rise in March.
- Excluding auto and gasoline sales, remaining sales increased by a solid 0.5% m/m in April versus a 0.7% m/m rise in March.
- Sales of the retail control group that is used to construct PCE rose 0.5% m/m in April and are 5.4% annualized above the Q1 average, providing a good start to Q2.


U.S. Retail Sales Slowed in April But Remained Solid

Kathleen Stephansen, CBE

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Initial claims for unemployment insurance rose by 12,000 to 211,000 in the week ending May 9, from 199,000 in the week ending May 2, revised from 200,000. The four-week average rose 750 to 203,750 in the week ending May 9, from 203,000 the May 2 week, revised from 203,250. The Action Economics/Haver Analytics Survey looked for 205,000 claims to have been filed. 

The total number of unemployment insurance beneficiaries—also known as “continuing claims”—rose by 24,000 to 1.782 million in the week ending May 2, from 1.758 million in the week ending April 25, revised from 1.766 million. The four-week moving average declined to 1.781 million in the latest week from 1.788 million in the April 25 week. The four-week moving average reached the lowest level since May 2024. The insured unemployment rate rose back to 1.2% in the week of May 2 from the one-week dip to 1.1% in the April 25 week. It had been at 1.2% since the week of November 29, 2025.

The insured unemployment rate varied greatly across individual states and territories. In the week ending April 25, the highest unemployment rates were in Rhode Island (2.29%), New Jersey and Massachusetts (both 2.20%), and Washington (2.15%). The lowest rates were in Florida and Louisiana (both 0.31%), South Dakota (0.32%), Alabama and Arkansas (both 0.36%), North Carolina (0.38%), Tennessee (0.47%) and Iowa, Kansas and Virginia (all 0.48%). Rates in other notable states include California (1.99%), New York (1.66%), Illinois (1.56%), Pennsylvania (1.28%), and Texas (1.03%). These state data 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.


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- New claims rose by 12,000 to 211,000.
- Continuing claims rose by 24,000 to 1.782 million.
- The insured unemployment rate was back up to 1.2% in the week of May 2, from the one-week dip to 1.1% the prior week.

U.S. Initial Unemployment Claims rose in the Week of May 9

Michael J. Moran

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The Producer Price Index surged 1.4% in April, far in excess of the expected increase of 0.5%. Energy prices accounted for much of the increase with a jump of 7.8%, a much sharper change than the advance of 3.8% in the CPI. The marked difference between the energy components of the CPI and the PPI was primarily due to the nature of the customers. The Consumer Price Index, naturally, collects prices paid by individuals; the PPI, in addition to individuals, collects prices paid by businesses, governments, and exporters. Energy prices paid by governments and exporters rose sharply (12.1% and 15.8%, respectively). The PPI also showed a sharp increase in energy prices paid by individuals (6.1% versus 3.8% in the CPI).

Service prices also contributed to the high-side surprise in the PPI, posting an increase of 1.2%. This area often moves erratically, but still the latest move can be viewed as unusual, as it marked the second largest increase in service prices since the current structure of the PPI began in 2010 (three other observations were close with increases of 1.1%; the largest increase was 1.3% during the inflation burst in 2022).

Goods prices other than energy items were tame compared with service prices, but they too were unsettling. This grouping posted an increase of 0.6%, a reading in the upper end of the range from the past few years. The increase, although pronounced, was not broadly based. In a list of 53 non-energy goods provided by the BLS, only 13 posted increases of 0.4% or more, although a handful were especially sharp (electronic components 8.1%, industrial chemicals 4.4%, household furniture 1.8%).

Food represented the only major grouping that was not troubling, registering an increase of 0.2%. 


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- The energy component led the sharp increase in the PPI, but it had support from many other areas
- Excluding energy, most service prices rose sharply; prices of non-energy goods also were under pressure
- The food component went against the grain with an increase of only 0.2%


April PPI: Broad-Based Pressure

Robert Brusca

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Industrial production in the European monetary area in March rose by 0.2%. Manufacturing output rose by 0.4%, marking two-months in a row of output increases. Output is still falling overall and in manufacturing over three months. Over three-months total manufacturing output excluding construction falls 2.7% annualized, over 6-months, it falls at a 0.4% annual rate, and over three-months the pace of decline steps back up again to -1.2% at an annual rate. The declines in manufacturing are more or less along the same lines.

**Sectors**
Output of consumer goods fell in March, driven by a decline in the output of nondurable goods that fell 4.5% month-to-month. Intermediate goods output rose by 0.9% in the month, increasing for the second month in a row. Capital goods output rose 1.1% after rising 0.8% in February.

**Sequential growth**
However sequential growth rates find headline growth negative over 12-months, six-months, and three-months- the same as for manufacturing. Consumer goods output declines at an accelerating pace dropping 11.6% over 12-months, at a 13.6% annual rate over six-months and at a 24.9% annual-rate over three-months. Those declines are led by reduction in consumer nondurables output. Intermediate goods output is mostly weak over the horizon, falling by 1.5% over 12-months and by 0.9% over 3 months annualized. The exception is capital goods sector where output rises by 2.2% over 12 months and accelerates to 4.6% over 6-months but then tails back, trimming growth to a 1.2% annual rate over three-months.

**Country Performance**
On a country basis declines occur in only two early-reporting members; those are Malta and Germany in March. Over three months output declines in the monetary area occurs in Ireland and Luxembourg and in Germany- with increases elsewhere. Output declines over 12-months, six-months, and three-months in the monetary area only for Germany, Luxembourg, and Ireland. There are consistent output increases in the monetary union in Austria, France, Finland, Italy, Greece, and Portugal. For most countries, increasing output is the rule despite the weak headlines, indicating that large economies are faring worse than smaller economies.

**Q1 Growth**
In the completed first quarter, we have manufacturing output falling by 1.8% at an annual rate and overall output falling at a 1.9% annual rate. Output declines in the quarter and in all major sectors. As for country reporters output falls in the quarter for Austria, Germany, Luxembourg, and Ireland.

**Growth rate rankings**
So, the percentile queue standings presented in the right-hand column are rankings of industrial production growth rates over 12-months. Compared to recent history, overall output has a 17-percentile standing which is relatively weak, in the lower one-fifth of its ranked results over the period (back to 2006). Only capital goods output at 52.5% has a standing above the 50% level which places it above its median result for the period. Among reporting countries seven have percentile standings above 50%, above their respective medians. The countries where output does not grow at a pace in excess of its median are Germany, Luxembourg, Malta, and Ireland.

On balance the smaller countries seem to be faring better in the European monetary union. The last two months have been relatively good months for output across the union; however, January had been so weak that the two months have not been able to recover from the weakness experienced in January. And the March data hardly reflect the hardships that are going to be visiting these economies because of the rise in oil prices and concerns about the situation in Iran and the strait of Hormuz. The future is unlikely to get better.





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