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.

icon-chart.png

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

icon-db.png

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

icon-time.png

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

products-dlx.svg

Data Link Express

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

products-haverview.svg

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

products-matlab.svg

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.

products-stata.svg

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.

products-sas.svg

[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.

products-rats.svg

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

products-r.svg

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

products-python.svg

Remote Training: Applied Time Series in Python

Michael J. Moran

260410L.jpg

260410M.jpg

The Consumer Price Index rose 0.9% in March, easily the sharpest monthly rise since the inflation burst in 2022. Although pronounced in magnitude, the increase was not surprising, as essentially all analysts had built in pressure from the energy sector. Energy prices jumped 10.9%, led by a surge of 21.2% in gasoline prices. Other energy components wiggled: charges for electricity services rose 0.8%, offsetting declines in the prior two months; a drop 0.9% in the price of natural gas services followed sharp increases in the prior three months.

The press report from the Bureau of Labor Statistics showed food prices as unchanged, but calculating the shift to more than one decimal point showed a marginal decline (-0.005%) The dip was almost imperceptible, but it nevertheless was a welcome rarity. The decline occurred in the food-at-home component (i.e. grocery store prices, -0.2%); prices of food away from home (i.e. at restaurants and bars) rose 0.2%.

Core prices rose 0.2 percent, softer than the expected increase of 0.3%. Only two areas posted high-side readings. Apparel prices increased 1.0% after a jump of 1.3% in February, perhaps reflecting hope for an active spring selling season. Airfares jumped 2.7%, hardly surprising in light of recent energy developments. Sharper increases are likely in coming months because of higher fuel prices. Most other core items were contained, including declines of 1.0% in medical-care commodities and 0.4% in the prices of used motor vehicles. Prices of medical-care commodities have been quiet since the middle of 2024; the latest year-over-year change totaled only 0.3%. Prices of used cars and trucks have declined for four consecutive months, leaving a year-over-year decline of 3.2%.

Although core prices were well contained in March, the outlook is uncertain because of potential passthrough from higher energy prices. At the same time, recent trends in the inflation rates for core goods and core services offer a reason to be optimistic, as both are decelerating. As shown in the left chart below, core goods prices in the past six months have been subdued, which has pulled the year-over-year change from 1.5% last fall (August to October) to 1.2% in March. Core service prices, shown in the right chart below, have registered changes of 0.3% or 0.4% in the three months before the 0.2% reading in March. However, results for October and November were restrained, and changes in the past six months in total show deceleration. The year-over-year change of 3.0% in core service prices in March reflects an advance of 3.3% in the first six months of this span (annual rate) and 2.7% in the past six months. The pattern is choppy, but it traces a decelerating trend.

The Consumer Price figures can be found in Haver's **USECON** database. The expectations figure is contained in the **AS1REPNA** database.

260410N.jpg

260410O.jpg

- Gasoline prices drove the energy component higher; electricity prices also contributed.
- Food prices provided a surprise by posting a fractional decline.
- Core prices rose less than expected; both goods and services components were contained.

March CPI: Pressure in the Energy Sector (as Expected); Tame Elsewhere (Surprisingly)

Winnie Tapasanun

260410F.jpg

260410G.jpg

Total factory orders were virtually unchanged m/m in February following a flat reading in January and a 0.4% decline in December, data from the U.S. Census Bureau showed. The Action Economics Forecast Survey had expected a 0.2% m/m February increase. The year-on-year growth rate eased to 3.7% in February, the lowest since October, from 4.2% in January (+3.0% in February 2025), remaining far below the April 2021 peak of 39.6%. Notably, orders for nondefense aircraft & parts plunged 28.6% m/m in February following decreases of 1.7% in January and 22.7% in December, while orders for defense aircraft & parts fell 2.1% after a 26.9% January slump and an 11.8% December jump. Factory orders excluding defense edged up 0.1% (3.6% y/y), the third m/m increase in four months, following a 0.4% January rebound. Factory orders excluding the transportation sector rose 1.2% (2.5% y/y), the strongest of four consecutive m/m gains, after a 0.5% January increase.

Durable goods orders fell 1.3% (+7.4% y/y) in February after a 0.4% decline in January (in line with a 1.4% m/m decrease in the advance report on April 7), marking the fourth m/m decline in five months. The February m/m fall reflected a 5.3% orders drop (+10.2% y/y) in transportation equipment following a 1.9% January decrease, alongside m/m declines of 0.5% (+2.4% y/y) in furniture & related products and 0.3% (+4.9% y/y) in electrical equipment, appliances & components. Other major durable goods orders categories rose m/m in February, led by a 2.4% gain (10.5% y/y) in primary metals, followed by increases of 1.7% (9.5% y/y) in machinery, 0.5% (5.4% y/y) in fabricated metal products, and 0.2% (7.7% y/y) in computers & electronic products.

Nondurable goods orders, which equal nondurable goods shipments, advanced 1.5% (0.1% y/y) in February, the biggest of three successive m/m gains, after a 0.5% increase in January. The February m/m rise was led by a 6.2% jump (-6.4% y/y) in petroleum & coal products, followed by gains of 5.9% (-5.8% y/y) leather & allied products, 1.2% (-2.8% y/y) in textile mills, 1.0% (1.6% y/y) in paper products, 0.9% (1.2% y/y) in plastics & rubber products, 0.6% (3.7% y/y) in beverage & tobacco products, 0.5% (3.2% y/y) in chemical products, 0.4% (3.2% y/y) in apparel, and 0.2% (0.5% y/y) in food products. To the downside, nondurable goods shipments for textile products (-1.4%; -1.5% y/y) and printing (-0.4%; -0.9% y/y) fell m/m in February following their January increases.

Total shipments rose 1.4% (3.5% y/y) in February after gains of 0.7% in January and December, registering the fourth m/m rise in five months. Excluding transportation, shipments advanced 1.4% (2.3% y/y), the fifth m/m gain in six months, after a 0.5% January increase. Shipments of durable goods industries also rose 1.4% (6.9% y/y), up for the fifth time in six months, after a 0.9% January gain. This reflected m/m increases across nearly all durable goods shipments categories, led by a 2.5% rise (10.1% y/y) in primary metals, followed by gains of 1.7% (5.5% y/y) in electrical equipment, appliances & components, 1.7% (4.0% y/y) in furniture & related products, 1.6% (9.7% y/y) in transportation equipment, 1.4% (7.6% y/y) in machinery, 1.3% (3.8% y/y) in nonmetallic mineral products, 1.0% (6.1% y/y) in computers & electronic products, 1.0% (2.5% y/y) in miscellaneous durable goods, and 0.9% (5.4% y/y) in fabricated metal products. In contrast, durable goods shipments for wood products were the only category with a monthly decline in February, easing 0.1% (-2.9% y/y) following a flat January reading.

Unfilled orders edged up 0.1% (11.1% y/y) in February, the smallest of seven consecutive m/m increases, following a 0.6% rise in January. Excluding transportation, unfilled orders grew 0.2% (1.9% y/y), up for the seventh straight month, after a 0.3% January increase. Backlogs of durable goods ticked up 0.1% (11.1% y/y) in February, led by gains of 0.5% (2.0% y/y) in machinery and 0.2% (4.9% y/y) in electrical equipment, appliances & components, partially offset by declines of 0.7% (+1.5% y/y) in furniture & related products and 0.1% (+2.3% y/y) in primary metals.

Inventories inched up 0.1% (0.8% y/y) in February, the fourth successive m/m increase, following matching 0.1% gains in January and December. Excluding transportation, inventories edged up 0.1% (1.0% y/y) after no change in January. Durable goods inventories increased 0.1% (1.8% y/y) in February after rising 0.2% for four straight months, while nondurable goods inventories were virtually unchanged (-0.8% y/y) after declining 0.3% in January and December.

The factory sector data are available in Haver’s **USECON** database. The Action Economics Forecast Survey is in the **AS1REPNA** database.

260410H.jpg

260410I.jpg

- Factory orders virtually unchanged (+3.7% y/y) in Feb. for second straight month; still 7.6% above the Jan. ’24 low.
- Durable goods orders (-1.3%), fourth m/m fall in five mths.; nondurable goods orders (+1.5%), largest of three successive m/m gains; shipments (+1.4%), fourth m/m rise in five mths.
- Transportation orders -5.3% m/m, led by a 28.6% plunge in nondefense aircraft orders.
- Unfilled orders +0.1%, smallest of seven straight m/m increases.
- Inventories +0.1%, holding within a narrow 0.1%-0.2% range for four consecutive mths.

U.S. Factory Orders Flat in February on Weak Nondefense Aircraft Orders

Andrew Cates

**Positive Growth Surprises, Negative Inflation Surprises—For Now**
The global macro backdrop heading into the latest Middle East shock was, by recent standards, relatively constructive. As the chart shows, growth data had been consistently surprising to the upside, while inflation surprises have been in negative territory—an unusually benign combination suggesting resilient activity alongside easing price pressures. What is striking, however, is that—at least through March and into early April—this pattern has not yet been meaningfully dislodged. For now, the data flow still reflects a world that was stabilising rather than deteriorating. That said, this is almost certainly a lagging signal. Supply-side shocks of this nature—particularly those centred on energy—tend to work with a delay but can be highly disruptive once they feed through. The risk, therefore, is that the current “goldilocks” surprise dynamic proves short-lived as higher energy costs, supply chain frictions and rising uncertainty begin to reshape the incoming data in the weeks ahead.

260409Z1.jpg

**Monetary Policy Expectations Shift as Easing Bets Are Repriced**
How policymakers respond to the evolving situation in the Middle East will be critical in shaping both market dynamics and the broader global outlook. This chart, based on the latest April Blue Chip Financial Forecasts survey, suggests that expectations are already beginning to shift. Forecasters are now less inclined to anticipate policy easing in the period ahead—particularly in the euro area, where expectations for rate cuts have been scaled back. Similarly, some of the easing previously priced for the Federal Reserve and the Bank of England has been pared back over the next 12 months. While this is not yet a full pivot toward tightening, it does point to a more cautious policy backdrop, reflecting the risk that renewed energy-driven inflation pressures could constrain central banks’ ability to support growth.

260409Z2.jpg

**Delay, Don’t Tighten: Central Banks’ Likely Playbook**
If the previous chart highlights a shift in policy expectations, this one gives a clearer sense of the reaction function underpinning it. When asked how central banks would respond if energy-driven inflation proves more persistent, most panellists point not to renewed tightening, but to a more cautious delay in easing. In other words, the hurdle for rate cuts has risen, even if the bar for  hikes remains relatively high. This distinction matters. It suggests that policymakers are likely to treat the shock as a supply-driven inflation impulse—one that complicates the outlook but does not automatically warrant aggressive tightening. At the same time, the responses underscore a second important theme: divergence. A sizeable share of forecasters expect policy paths to vary significantly across regions, reflecting differences in energy exposure, inflation dynamics and domestic growth conditions. Taken together, the message is one of constrained flexibility. Central banks may want to support growth, but persistent energy pressures could keep them on hold for longer than previously anticipated—reinforcing the more cautious policy outlook already evident in market pricing.

260409Z3.jpg

**Markets Signal Fiscal Concern, Not Inflation Panic**
If central banks are likely to proceed cautiously, financial markets are already beginning to draw their own conclusions. This chart shows that the recent adjustment in US Treasury markets has been driven primarily by a rise in real yields rather than a meaningful increase in inflation expectations. In other words, markets are not yet pricing a loss of monetary policy credibility or a sharp unanchoring of inflation expectations. Instead, the move points more toward concerns around the broader policy mix—particularly the fiscal backdrop and the potential for increased borrowing needs in an environment of heightened geopolitical risk. This distinction is important. A rise in inflation expectations would suggest fears of central banks falling behind the curve. What we are seeing instead is a repricing of real rates, consistent with tighter financial conditions and a higher risk premium. For now, at least, markets appear to view the shock less as a classic inflation spiral and more as a development that complicates the growth outlook and places greater strain on policy frameworks—especially on the fiscal side.

260409Z4.jpg

**Electricity Prices Reflect Energy Dependence**
The initial response in electricity markets since the Middle East disruption has followed a familiar pattern. Economies with greater domestic energy capacity—such as Scandinavia and, to a lesser extent, the US—have seen relatively contained electricity prices. By contrast, those more reliant on imported energy—most notably the UK and parts of Europe—continue to face significantly higher costs

260409Z5.jpg

**Generation Capacity Determines Energy Resilience**
These price dynamics are closely linked to underlying differences in electricity generation capacity. As the sixth chart shows, countries with higher per capita electricity production—again including Scandinavia and the US—are structurally better positioned to absorb external shocks. In contrast, economies with more limited domestic generation capacity, such as the UK and Germany, are inherently more exposed to fluctuations in global energy markets. This structural divide is likely to prove increasingly important in the period ahead, influencing not just near-term inflation outcomes but also the relative resilience of growth across economies as energy costs remain volatile.

260409Z6.jpg

Amid further tentative signs of de-escalation—most notably President Trump’s decision on April 7th to step back from further escalation—financial markets have stabilised somewhat, but the macroeconomic implications of the Middle East crisis remain highly uncertain. As our charts show, the global economy entered this shock from a position of relative strength, with positive growth surprises and easing inflation pressures still evident in the data (chart 1). However, that benign backdrop now looks vulnerable. Central banks are already reassessing the outlook, with expectations for policy easing being pared back (chart 2) and a growing consensus that any response to persistent energy-driven inflation will likely involve delaying cuts rather than tightening aggressively—albeit with significant regional divergence (chart 3). Financial markets, for their part, are not yet signalling a loss of inflation control, but the rise in real yields suggests increasing concern around the broader policy mix, particularly fiscal pressures (chart 4). Finally, the adjustment to the shock is unlikely to be uniform. Structural differences in domestic energy capacity are already driving wide divergences in electricity prices, leaving more import-dependent economies exposed to higher costs and sharper trade-offs between growth and inflation (charts 5 and 6). Taken together, the message is clear: even if geopolitical tensions ease, the economic aftershocks are likely to be uneven, persistent and increasingly shaped by structural constraints.

<iframe data-testid="embed-iframe" style="border-radius:12px" src="https://open.spotify.com/embed/episode/4qBjHX7OmdXmxVN2oRe1nB?utm_source=generator" width="100%" height="152" frameBorder="0" allowfullscreen="" allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture" loading="lazy"></iframe>

Charts of the Week: From Oil Shock to Policy Dilemma

260409A.jpg

260409B.jpg

This monthly report is always packed with information relating to the household sector. At this time, most observers will probably be most interested in price developments, and the results for February were a bit unsettling. The headline price index rose 0.4%, influenced by a jump of 0.8% in energy prices. This increase was largely anticipated and not especially troubling when viewed in isolation. Energy prices have shown little net change in the past two years, and the latest reading of the index was comfortably within the recent range of observations. However, given developments in the Middle East, energy prices undoubtedly will surge out of that recent range in the months ahead.

Core PCE prices also rose 0.4%, a touch firmer than the expected increase of 0.3%. An increase of 0.4% in core inflation is a quick pace even when viewed in Isolation, but this advance followed a similar increase in January, and the December reading almost rounded to 0.4%. These recent changes pulled the year-over-year increase in core prices to 3.0%, a full percentage point above the Federal Reserve’s target.

Nominal personal income dipped 0.1% in February, which translated to a decline of 0.4% after adjusting for inflation (almost rounding to -0.5%). The softness is striking, but a review of the detail suggests that special factors played a role. Much of the weakness reflected a decline of 1.7% in dividend income, which followed a jump of 1.9% in January. Dividend payments in the prior two years followed the same pattern, leaving one to suspect that seasonal adjustment has gone awry. Government transfer payments also declined, with the miscellaneous category accounting for most of the drop. Medicaid payments also fell, marking the fifth consecutive decline, most likely driven by the tightening of provisions included in the One Big Beautiful Bill Act.

Nominal consumer expenditures rose 0.5%, a seemingly strong result, but the change amounted to only 0.1% in real terms. The small increase followed a flat reading in January and increases of only 0.1% in November and December. Consumers spent actively in the second and third quarters of last year, but they have become cautious recently. The data in hand suggest real outlay growth of approximately 1.0% in the first quarter, slower than the average pace of 3.0% in the middle of last year and 1.9% in 2025-Q4.

The personal income and consumption figures are available in Haver’s **USECON** database with detail in the **USNA** database. The Action Economics forecasts are in **AS1REPNA**.

260409C.jpg

260409D.jpg

- The energy component contributed to a high-side reading on the price index for personal consumption expenditures; the core component was firm as well.
- Consumer spending showed signs of slowing.

Personal Income, Consumption, and Prices: Higher Prices Dampen Real Gains

Sandy Batten

260409N1.jpg

260409C1.jpg

The third estimate of Q4 2025 GDP showed that real GDP growth slowed to 0.5% q/q saar versus 0.7% in the second estimate and 1.4% in the advance estimate. GDP had grown 4.4% in Q3. The more than one-month long shutdown of the federal government continued to have been a notable restraint on GDP growth in Q4, subtracting 1.0%-point from overall growth, the same as in the second estimate.

Revisions were very small across major expenditure categories. Growth of personal consumption expenditures was revised down slightly to 1.9% q/q saar from 2.0% previously. Nonresidential fixed investment increased 2.4%, up slightly from the 2.2% reported in the second estimate. The 0.5% q/q decline previously reported for residential investment was revised to a larger decline of 1.7%, subtracting 0.1%-point from overall growth versus 0.0%-point in the previous estimate. Inventories declined more than previously estimated, reducing their contribution to growth from 0.3%-point in the second estimate to 0.1%-point in today’s estimate.

260409O1.jpg

260409P1.jpg

There were slight downward revisions to the declines previously reported for both exports and imports, leaving net exports essentially unrevised. As already noted, a 16.6% q/q saar plunge in federal government spending (revised down slightly from -16.7%) accounted for most of the weakness in Q4. This included a 24.3% q/q collapse in nondefense spending, the second largest quarterly decline in nearly forty years. By contrast, state and local government spending increased 1.5%, revised up from 1.2% in the previous estimate.

Private domestic demand growth (final sales to private domestic purchasers, a favored gauge of demand by the Federal Reserve) was revised slower to 1.8% q/q saar in Q4 from 1.9% in the second estimate and 2.4% in the advance report. However, even the revised pace of growth is respectable and close to the economy’s potential growth rate.

The GDP data can be found in Haver’s **USECON** and **USNA** databases. **USNA** contains virtually all of the Bureau of Economic Analysis detail in the national accounts. The Action Economics consensus estimates can be found in **AS1REPNA**.

260409Q1.jpg

260409S1.jpg

- Q4 GDP growth revised to 0.5% q/q saar from 0.7% in the first revision and 1.4% in the advance report.
- The shutdown of the federal government still played a critical role in the slowdown, subtracting 1.0%-point from Q4 growth.
- Domestic demand slowed further with final sales to private domestic purchasers revised down to 1.8% from 1.9% in the first revision and 2.4% in the advance report.

U.S. Q4 2025 Real GDP Growth Revised Slower

Our global data offering is unparalleled in terms of coverage, quality, and organization. We offer 290+ databases from 2500 government and private sources, a wealth of key survey and forecast data covering the world’s economies, and a robust offering of archive databases that drive machine learning for big data applications.

Optimized for precision analytics, our data is seamlessly integrated with Microsoft Office and all leading statistical packages through our DLX® software and platform independent HaverView™ website. We further offer direct database feeds, client server or cloud-based delivery, and RESTful API.


Privacy Policy

Disclaimer

Contact us

Service Health

A premier time series data platform for the global strategy, research, and quant communities. 

London

Singapore

Tokyo

New York

Economy in Brief

Viewpoints

Contact Us

Our Data

Our Products

What We Do

Our Authors

About Us

Data News

Featured Data Additions

Resources

Release Calendars

Training Center

Webinars

Newsletters

Download Software

For Clients

Live Updates

Mfrs' Shipments Inventories & Orders (Feb), CPI (Mar)

Financial Soundness Indicators (Feb), Industrial Turnover (Feb)

Trade by SITC (Mar), Mfg Enterprise Survey (Q4)

IP, Industrial Turnover (Feb), CPI, HICP and NPI (Mar)

PVI, GDP Indicator, Industrial Turnover & Orders, IP, Index of Services (Feb), Central Gov't Debt (Mar)

IP, Industrial Turnover (Feb), CPI & HICP (Mar)

Wholesale Trade (Feb), GDP (Q4-3rd), Personal Income (Feb)

BoE Bank Liabilities Survey, BoE Credit Conditions Survey (Q1)