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)

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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

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

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Database Compatibility

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Data Link Express

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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
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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

Session 1: Bootcamp Part 1

Visualization with GGPlot2 and data analysis

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Session 3: Univariate Models Part 1

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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

Session 5: Multivariate Models Part 1

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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

Is recent drop in sentiment signaling softer growth ahead?

Robert Brusca

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**Broad and severe weakness in European production**: industrial production data for the monetary union turned decidedly sour in January. All major production categories showed declines in January, including the headline series for production excluding construction and manufacturing output. There were also drops across the major manufacturing sectors—consumer goods, intermediate goods, and capital goods—as well as in both of the consumer sub categories of durable goods and nondurable goods. January was a really tough month for the industrial sector and the European monetary union.

**Sequential output weakness as well**: Output is not only falling in every category in January—and for two months in a row—but the sequential growth rates over 12 months, six months, and three months also show decelerations present for all of these categories of output except capital goods. That means the six-month growth rate is weaker than the 12-month growth rate, and the three-month growth rate is weaker than the six-month growth rate for six of seven of these categories—the exception is capital goods. And capital goods are a minor exception with the growth over three months only slightly stronger than over six months, and at that it's still a negative growth rate. It shows a decline in output, just a slower decline. There is no silver lining here, just clouds and rain.

**Quarter to date and more**: As if that's not enough, these are output data for January so we can calculate quarter-to-date growth rates in the first quarter. On that basis, all seven of these categories show output declining, and output is declining in all seven of these categories at a double-digit pace!  In addition, when we step back to compare growth rates over the last year with previous 12-month growth rates back to April 2006, a 20-year horizon, we find that all the growth rates in the table lie below their median rates of growth for this previous twenty-year span. Capital goods fare the best, with a percentile standing of its growth rate at its nearly 48th percentile, just slightly below its median, which lies at a ranking of 50%. The growth rates for consumer nondurables, for example, have had output growth weaker during this period, only 1.7% of the time. Consumer goods output has been weaker, only 3.8% of the time. Manufacturing output is in the bottom quartile among historically ranked growth rates. These are extremely bad and consistently poor rankings for industrial growth.

The table also offers up country-by-county data for January. Looking just at monetary union members, seven of twelve show output declines in January, but that compares to December, which was a strong month with only three of those members showing output declines. However, a month earlier, in November, eight monetary union members had shown output declines. There are sequential output declines reported by Germany, Spain, and Ireland over the last twelve-to-six-to-three months. Only Malta and Greece show output trends that are accelerating, and of course, these are two of the smaller monetary union countries. Seven monetary union countries show quarter-to-date output is declining early in this first quarter. Among the five countries showing output increasing, two of them showed double-digit growth rates in the new quarter and those two again are Malta and Greece. For the countries overall, only five of twelve have queue percentile standings of their earlier growth rates that are above their historic medians for the last 20 years. That list of five includes France, Malta, Greece, Portugal, and Austria.

The industrial data for Europe in January are decidedly downbeat and concerning. These numbers are being reported before hostilities in the Middle East began to ramp up and clearly before oil prices spurted higher. The European manufacturing sector is not digging itself out of the hole it fell into after COVID and the invasion of Ukraine. And after showing a hint of recovery, it now appears to be deep in the morass of economic weakness.

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Europe

EMU IP Trends Are Decidedly Negative

Sandy Batten

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The U.S. trade deficit in goods and services (BOP basis) narrowed to $54.5 billion in January from a revised $72.9 billion in December (previously $70.3 billion), according to the U.S. Census Bureau. The goods deficit declined to $81.8 billion from $99.3 billion while the services surplus widened slightly to $27.3 billion from $26.3 billion in December. The Action Economics Forecast Survey looked for a deficit of $67.9 billion.

The real (inflation-adjusted) trade deficit in goods narrowed to $83.9 billion (2017$) from $97.9 billion in December (previously $97.1 billion). However, the January figure was larger than the Q4 average, implying that the trade deficit is on course to subtract from overall GDP growth in Q1.

Exports of goods and services rebounded in January, rising 5.5% m/m (10.4% y/y) following a 1.6% monthly decline in December (previously -1.7% m/m). Goods exports (Census basis) jumped 8.2% m/m or $14.8 billion after a 3.0% m/m decline in December and a 5.2% monthly decline in November. However, 60% of the rebound in January was accounted for by an $8.8 billion increase in exports of nonmonetary gold and other precious metals. Without the surge in these metal exports, the remainder of exports rose 3.5% m/m in January. Exports of nonmonetary gold and other precious metals are not included in the tabulation of GDP. Services exports increased 1.2% m/m (+6.3% y/y) in January on top of a 0.8% m/m increase in December.

By end use, the January jump in goods exports was unsurprisingly led by 15.1% m/m surge in exports of industrial supplies and materials. However, 94% of this increase was accounted for by the jump in exports of nonmonetary gold and other precious metals. Capital goods exports rose 8.8% m/m on top of a 4.2% increase in December. Exports of “other” goods surged 37.1% m/m, more than offsetting a 14.5% monthly decline in December and their first increase in four months. By contrast, auto exports slumped 6.0% m/m, their third consecutive monthly decline, and nonfood consumer goods exports ex autos plummeted 12.1% m/m, their third monthly decline in the past four months. For exports of services, travel declined for the first time in four months. Solid gains were posted by financial services, use of intellectual property, and other business services.

Imports of goods and services slipped 0.7% m/m (-11.3% y/y) in January, their first monthly decline in three months, after a 3.5% m/m rise in December and a 4.4% monthly gain in November. Goods imports (Census basis) fell 1.1% m/m in January, their first monthly decline in three months. Auto imports slumped 8.3% m/m, their fourth monthly decline in the past five months. Imports of nonfood consumer goods ex autos dropped 5.8% m/m in January, their third monthly decline in the past four months. Imports of industrial supplies fell 2.7% m/m following a 15.9% m/m surge in December. By contrast, capital goods imports jumped 3.1% m/m, their fourth consecutive monthly gain, while imports of “other” goods surged 7.3% m/m. Imports of services edged up 0.3% m/m in January after a 2.7% monthly rise in December, Travel imports, construction service imports, imported intellectual property, and imported maintenance services fell while imports of other business services, insurance services, and imports of personal and recreational services posted solid gains.

By country, the goods trade deficit with China widened marginally to $12.5 billion in January from $12.4 billion in December. Exports to China jumped 11.5% m/m and imports from China rebounded, rising 5.3% m/m following monthly declines in both November and December. The trade deficit with the European Union narrowed markedly to $6.1 billion in January from $11.1 billion in December. Exports to the EU fell 3.2% m/m, their third monthly decline in the past four months, while imports from the EU plummeted 13.2% m/m, also their third monthly decline in the past four months. The deficit with Japan widened to $5.5 billion in January from $5.3 billion.

The international trade data can be found in Haver’s **USECON** database. Detailed figures on international trade are available in the **USINT** and **USTRADE** databases. The expectations figures are from the Action Economics Forecast Survey in **AS1REPNA**.

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- The deficit in goods and services narrowed to $54.5 billion in January from $72.9 billion in December
- Exports rebounded, rising 5.5% m/m in January after a 1.6% m/m decline in December.
- However, 60% of the exported goods rebound was in nonmonetary gold and other precious metals.
- Imports edged down 0.7% m/m following a 3.5% monthly jump in December.
- The goods deficit narrowed to $81.8 billion while the services surplus widened slightly to $27.3 billion.

U.S. Trade Deficit Narrowed More than Expected in January

Winnie Tapasanun

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Total housing starts unexpectedly rose 7.2% m/m in January to a seasonally adjusted annual rate of 1.487 million units following a downwardly revised 4.8% increase to 1.387 million in December (initially +6.2%; 1.404 mil.) and an upwardly revised 4.1% rise to 1.324 million in November (previously +3.9%; 1.322 mil.), data from the U.S. Census Bureau showed. The Action Economics Forecast Survey had expected 1.350 million starts for January. The latest figure marked the biggest of three consecutive m/m gains and the fourth in five months as well as the highest level since February 2025. The year-on-year rate strengthened to +9.5% in January, the strongest y/y pace since July, after -8.4% in December and -1.7% in January 2025. Overall, starts remained 18.3% below the April 2022 peak of 1.820 million.

Single-family starts fell 2.8% (-6.5% y/y) to 935,000 in January, the first m/m drop since September, after a 3.3% rise to 962,000 in December (981,000 initially). They hit a low of 795,000 in November 2022 and previously reached a high of 1.218 million in November 2021 and a peak of 1.273 million in December 2020. Multi-family starts advanced 29.9% (54.2% y/y) to 552,000, the largest of three successive m/m increases and the highest level since May 2023, on top of an 8.1% December gain to 425,000 (423,000 initially). They reached a peak of 629,000 units in November 2022 and a high of 616,000 units in April 2022.

By region, January housing starts showed a mixed performance. Starts in the Northeast surged 47.4% (108.5% y/y) to 196,000 in January after a 13.6% drop in December, registering the largest m/m gain since September and the highest level since December 2022. Starts in the South recovered 11.4% (16.0% y/y) to 810,000, the third m/m increase in four months and the highest level since July, after a 2.8% December decline. In contrast, starts in the Midwest decreased 10.8% (-2.8% y/y) to 174,000 in January following a 15.4% rebound in December. Starts in the West fell 7.5% (-20.7% y/y) to 307,000, the third m/m fall in four months, after a 31.2% December jump. Notably, the South continued to lead all regions, accounting for 54.5% of total U.S. housing starts; the region previously peaked at 1.044 million in April 2022.

Total building permits, single-family permits, and multi-family permits all declined for the third time in four months in January. Total building permits fell 5.4% (-5.8% y/y) to 1.376 million in January, the lowest level since August, after a 4.8% rebound to 1.455 million in December. They remained well below a peak of 1.920 million in January 2022 and a high of 1.855 million in January 2021. Single-family permits slid 0.9% (-11.6% y/y) to a five-month-low 873,000 following a 1.7% December slide to 881,000. They reached highs of 1.243 million in both January 2022 and January 2021. Multi-family permits dropped 12.4% (+6.6% y/y) to 503,000 after a 16.7% December gain to 574,000. They reached a peak of 817,000 units in February 2023 and a high of 787,000 units in June 2022. Regionally, permits fell m/m in the West (-15.7%; -1.9% y/y), Northeast (-9.6%; +13.5% y/y), and South (-3.5%; -13.2% y/y), but increased m/m in the Midwest (+9.0%; +4.1% y/y).

The housing starts and building permits figures can be found in Haver’s **USECON** database. The expectations figure is contained in the **AS1REPNA** database.

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- Housing starts +7.2% (+9.5% y/y) to 1.487 mil. in Jan.; largest of three straight m/m gains.
- Multi-family starts at highest level since May ’23; single-family starts down for the first time in four mths.
- Starts m/m up in the Northeast (+47.4%) and South (+11.4%), but down in the Midwest (-10.8%) and West (-7.5%).
- Building permits at a five-month low, w/ declines in both single-family and multi-family permits.

U.S. Housing Starts Jump in January to an 11-Month High

Kathleen Stephansen, CBE

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Initial claims for unemployment insurance declined by 1,000 to 213,000 in the week ending March 7, from 214,000 in the week ending February 28, revised from 213,000. The four-week average declined 4,000 to 212,000 in the March 7 week from 216,000 in the prior week, revised from 215,750. The Action Economics Forecast Survey looked for 215,000 claims to have been filed.

The total number of unemployment insurance beneficiaries—also known as “continuing claims”—declined by 21,000 to 1.850 million in the week ending February 28, from 1.871 million in the week ending February 21, revised from 1.868 million. The four-week moving average stood at 1.852 million, little changed from the previous week’s average of 1.852 million. The insured unemployment rate remained at 1.2% in the week of February 28. It has remained at that level since the week of November 29, 2025.

The insured unemployment rate varied greatly across individual states and territories. In the week ending February 21, the highest unemployment rates were in Rhode Island (3.33%), Massachusetts (2.91%), New Jersey (2.87%), Washington (2.51%), Minnesota (2.43%), California (2.32%), Montana (2.17%), Connecticut and Michigan (both 2.10%) and Oregon (2.03%). The lowest rates were in Florida (0.30%), Louisiana (0.35%), Arkansas (0.40%), and North Carolina and Alabama (both 0.42%). Rates in other notable states include New York (2.32%), Illinois (2.16%), Pennsylvania (1.92%), and Texas (1.13%). These state data are not seasonally adjusted.

_**Note from DOL**: Calendar Year (CY) 2026 seasonal factors and revised seasonal factors for CY 2021-2025 for both initial claims and continued claims will be available at  [https://www.bls.gov/lau/seasonal-adjustment-for-weekly-unemployment-insurance-claims.htm](https://www.bls.gov/lau/seasonal-adjustment-for-weekly-unemployment-insurance-claims.htm) by 12:00 P.M. (Eastern) on Thursday, March 19, 2026. Revisions to the historical series for CY 2021-2025 for both initial claims and continued claims will be published on March 19, 2026, with the release of the Unemployment Insurance Weekly Claims News Release._

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 dipped by 1,000 to 213,000.
- Continuing claims declined by 21,000 to 1.850 million.
- The insured unemployment rate remained at 1.2%.


U.S. Initial Unemployment Claims Edged Down in the Week of March 7

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Japan's Ministry of Finance business outlook survey shows a slow but positive improvement in the outlook for employment among large firms, while the outlook for large manufacturing firms’ hiring continues to cycle and oscillate around zero (see Chart).

The assessment on current observations of the economy slipped to +4.4 for all large enterprises in the first quarter of 2026, compared to +4.9 in the fourth quarter of last year. For large manufacturing enterprises, the assessment slipped to 3.8 from 4.7. There were also slippages reported for medium-sized enterprises as well as for small enterprises; for both the total and manufacturing sectors, assessments were worse, the smaller the reporting unit (on both a net reading basis and a percentile standing basis).

The quarter-ahead assessment slipped to 3.7 from the 4.4 assessment of the first quarter for all large enterprises. For large manufacturing enterprises, the outlook slipped from plus 3.8 in the first quarter of this year to -1.1. The second quarter ahead outlook, however, improved to 4.7 from 3.7 for all large enterprises, and the manufacturing outlook for two quarters ahead picked up to 3.3 from -1.1 in the quarter ahead. However, that 3.3 outlook for large manufacturing enterprises is still below the first quarter assessment (of 3.8) as well as below the fourth quarter and the third quarter assessments of 2025.

The percentile standing of the quarter-ahead assessment for all large enterprises is 44.6. For manufacturing firms, the percentile standing is 38.4, and for nonmanufacturers it is 62.2. The percentile standing values compare the current observation with a history of observation readings back to 2007; values above the 50th percentile are above their historic medians. We can see for the quarter ahead for large enterprises all of their responses are above their medians, and the relative strength resides among nonmanufacturing enterprises; they report the highest standings.

For the second quarter ahead, the percentile standings slip for the total group of large enterprises as well as for manufacturing and nonmanufacturing, separately. This occurs even though the net assessments improve from the quarter ahead to two quarters ahead. You can get an inkling ‘why’ by looking at the ‘average’ and noting that the average two-quarter ahead reading has been higher than the average quarter-ahead reading. So, to rank higher than the quarter-ahead, the second-quarter ahead has a higher hurdle to go over. The standing for nonmanufacturing slips from a 62.2 percentile for the quarter ahead to a 58.1 percentile standing for the second quarter ahead. Large manufacturers take a relatively large step back to a 28.4 percentile standing two quarters ahead from the 38.4 percentile for one quarter ahead. These step backs are reflected in the headline which steps back to 37.8 for two quarters ahead from a 44.6 percentile standing for the first quarter ahead.

What is evident in this survey is that large enterprises that the MOF surveys are becoming increasingly pessimistic as we look farther into the future, since the current rankings for all large enterprises, large enterprise manufacturers, and large nonmanufacturers show the strongest percentile standings among this triad of readings for the current quarter, with the quarter-ahead standings weaker and two-quarter-ahead standings weaker still. This growing pessimism is not a good feature.

**Medium and small enterprises not as dismally inclined**
**Medium-sized firms:** The transit to greater pessimism that we see for large enterprises as we look further into the future does not carry over to medium enterprises. Medium enterprises do see lower readings for the quarter ahead compared to the current-quarter assessments, and generally the quarter ahead provides assessments that are below the 50% mark, making them below median expectations as well. However, for two quarters ahead, the percentile standings improve, and at least for medium-sized manufacturing enterprises, there is a reading above the 50-percentile mark for that category two-quarters ahead, putting it even above the 45.2 percentile reading posted for the current quarter.

**Small firms**: For small enterprises, there is no real generalization across the various types of firms. Manufacturing firms’ percentile standing from the current quarter to the quarter ahead just about halve themselves, a sharp step back for manufacturers. However, for nonmanufacturers, there's an improvement from a 56.2 percentile standing in the current quarter to a 60.3 percentile standing in the quarter ahead. These two groups are moving in opposite directions for two quarters ahead. Manufacturers stop that deterioration and gain back just a small measure of what they lose in the quarter ahead with their two-quarter ahead standing, while nonmanufacturers lose some of their ebullience as the percentile standing drops to a 50.7 percentile reading from 60.3 but still sports an above-median value.

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**Summing up**
As a bellwether, the large enterprises and particularly manufacturing firms are the preferred gauges. On this basis, the results of the survey are disappointing. Although current assessments are quite fine, the outlook is certainly off-putting and that may be surprising with new Prime Minister, Takaichi, having just taken office and won a large majority in a snap election. Perhaps firms are more concerned about prospects for fiscal policy and whether there will be excessive stimulus and possibly they are also more concerned about the potential for the Bank of Japan to be held back from raising rates to contain growing inflationary pressures. But even with the new apparently very popular Prime Minister in office, it's surprising to see the MOF survey create such a weak set of readings.

Japan

MOF Japan Business Outlook Survey

Andrew Cates

**The Blue Chip Growth Consensus**
The first chart this week tracks the evolution of Blue Chip consensus forecasts for 2026 real GDP growth over the past six months for the United States, China and Taiwan. What stands out is the remarkable stability—and in some cases gradual improvement—in growth expectations, even as the geopolitical backdrop has become more unsettled. A backdrop of intense geopolitical instability in the Middle East historically tends to introduce downside risks to global activity through higher energy prices, shipping disruptions and financial market volatility. Yet the consensus outlook for the world economy has so far remained broadly resilient. One reason may lie in the continuing strength of investment tied to artificial intelligence. Taiwan’s growth outlook has been revised steadily higher in recent months, reflecting its pivotal role in the global semiconductor ecosystem and the infrastructure build-out associated with the AI boom. In that sense, the chart captures an interesting juxtaposition in the current global economy: rising geopolitical uncertainty on the one hand, and a powerful technology-driven investment cycle on the other.

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**Sentiment surveys**
The picture becomes somewhat less reassuring when we turn to global sentiment indicators. The latest Sentix global economic expectations index shows a sharp deterioration in March, interrupting what had been a gradual improvement in global economic sentiment over the past year. Notably, the survey period coincided with the early stages of the recent escalation in tensions in the Middle East, suggesting that rising geopolitical risks may already be weighing on investor and analyst expectations. While the current conditions index remains relatively firm—consistent with the still-resilient growth outlook seen in the Blue Chip forecasts—the sudden downward lurch in expectations is potentially more concerning. Historically, sharp declines in forward-looking sentiment indicators such as this have sometimes served as early warning signals of a softening global growth environment, particularly when they coincide with rising energy prices and heightened geopolitical uncertainty.

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**The Blue Chip Inflation Consensus**
Turning to inflation, the latest Blue Chip revisions suggest that forecasters have so far made only very modest adjustments to their outlook for 2026 consumer prices. As the chart shows, the largest upward revision this month was for India, while smaller increases were recorded for Australia, the euro area and South Korea. Elsewhere, forecasts were largely unchanged. What is notable is the absence of more widespread upward revisions, particularly given the sharp climb in oil prices in recent days following the escalation of tensions in the Middle East. For now, panelists appear to be assuming that the energy shock will prove either temporary or limited in scope. However, should higher oil prices persist—or begin to filter through more broadly into transportation and production costs—this relative stability in inflation forecasts could come under greater pressure in the months ahead.

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**Oil prices and short-dated yields**
The next chart highlights the close relationship that often emerges between energy prices and expectations for U.S. monetary policy. Over the past year, movements in the price of West Texas Intermediate crude have tended to be mirrored—albeit imperfectly—in shifts in the yield on two-year US Treasury notes, a market-based proxy for expectations about the Federal Reserve’s policy path. The correlation between the two series has been relatively strong, reflecting the fact that oil price swings can influence inflation expectations and therefore the outlook for interest rates. Yet despite the recent sharp rise in oil prices associated with the escalation of tensions in the Middle East, there has so far been no comparable move higher in two-year Treasury yields. This relative stability suggests that financial markets may be assuming that the latest oil shock will prove temporary or, at least, insufficient to materially alter the Federal Reserve’s policy trajectory.

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**Oil exposure**
Staying with the theme of Middle East instability, the next chart highlights the varying degree to which major economies remain exposed to fluctuations in global oil markets. Measured as a share of GDP, Japan, China and several major European economies remain significant net importers of crude oil, leaving them more vulnerable to sustained increases in energy prices. Germany, France and Italy all retain notable import dependencies, while the United Kingdom’s exposure is comparatively modest. By contrast, the United States is now close to balance in crude trade, reflecting the transformation brought about by the shale revolution, while Canada stands out as a substantial net exporter. These differences matter in the current environment. Should geopolitical tensions lead to a sustained rise in oil prices, the macroeconomic burden would likely fall most heavily on the large importing economies, particularly in Asia and parts of Europe, where higher energy costs could weigh on growth and complicate the inflation outlook.

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**Oil prices and inflation**
The final chart stays with the theme of Middle East instability by highlighting the extent to which oil price movements tend to feed through into inflation dynamics across Asia. The five-year correlations between Brent crude prices and energy-related CPI inflation are positive and, in several cases, quite strong. Thailand, China and Malaysia show particularly high sensitivities, suggesting that swings in global oil prices are quickly reflected in domestic energy costs. India and Japan also display meaningful correlations, while the relationship is somewhat weaker in Singapore and Taiwan and even slightly negative in South Korea over this period. The broader message is that oil shocks rarely remain confined to energy markets alone. In many Asian economies, they transmit relatively quickly into inflation, potentially complicating monetary policy decisions if geopolitical tensions were to drive a sustained rise in crude prices.

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The past few days have seen financial markets rattled by a sharp escalation of tensions in the Middle East, with oil prices rising, risk assets wobbling and investors reassessing the potential macroeconomic fallout from a possible energy shock. Yet, taken together, this week’s charts suggest that the global economic outlook has so far remained relatively resilient. Blue Chip consensus forecasts for 2026 growth have held steady in recent months, with Taiwan’s steadily improving outlook hinting at the ongoing influence of the global AI investment cycle. That said, forward-looking sentiment indicators are beginning to show some cracks: the latest Sentix expectations index registered a sharp deterioration in March, potentially reflecting rising geopolitical uncertainty. Inflation expectations, by contrast, have shifted only modestly, with forecasters making few meaningful revisions despite the recent surge in oil prices. Financial markets appear to share that view, as movements in two-year US Treasury yields—often a proxy for expectations of Federal Reserve policy—have not mirrored the sharp rise in crude prices, suggesting investors currently see the oil shock as temporary. The final charts highlight why energy markets nonetheless remain central to the outlook: many major economies remain significant net oil importers, and in much of Asia oil price movements feed quickly into consumer energy inflation. Should geopolitical tensions persist and keep crude prices elevated, these channels could yet transmit broader macroeconomic pressures in the months ahead.

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Charts of the Week: Geopolitics Meets the Global Economy

Michael J. Moran

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The consumer price index rose 0.3% in February, a touch above the average in the prior six months. (Measured with more precision, the latest change was 0.27%, up from an average of 0.23% in the prior six months.) The increase left the year-over year change at 2.4%, the same as in January.

The food and energy components account for the above-average increase In February, as both posted high-side readings (0.4% and 0.6%, respectively). The increase in energy prices was not especially troubling, as it followed a drop of 1.5 percent in January and did little damage to a tame underlying trend, although that friendly trend will begin to shift in response to the conflict in the Middle East. The increase in food prices, while not alarming, should not be downplayed, as it marked the second noticeable advance in the past three months (0.6% in December).

Excluding food and energy, prices rose 0.2%, matching the average of the past six months and keeping the year-over-year change steady at 2.5%. The core component seemed uneventful at first blush, but in fact it showed two notable changes: apparel prices rose 1.3% and airfares jumped 1.4%. These areas often move erratically, with sharp increases typically followed by discounting within a few months. That pattern could well unfold again, but both areas also have shown hints of stirring in the past few months. Apparel prices have now increased for four consecutive months, with the latest change pulling the level of the index out of the range in place in the past two years. The increase of 1.4% in airfares followed jumps of 6.5% and 3.8% in the prior two months, and this index also jumped out of a tight range that had been in place. Given the volatile nature of these items, odds favor easing in coming months, but they bear watching.

Outside of apparel and airfares, the core CPI was well behaved, with most areas showing modest changes. The favorable performance is evident in the breakdown of core prices between goods and services. During 2024 and much of 2025, an acceleration in goods prices seemed an inflation threat, but this area has cooled recently. Service prices also raised questions about the inflation outlook last year, as the steady deceleration came to a halt in the spring and summer. However, core service prices again began to decelerate in the fall. The pace of deceleration has slowed in the past few months, influenced by airfares, which hopefully will shift gears soon.

The outlook for core service inflation also has improved because of an easing in rental inflation. As inflation cooled after the 2021-22 burst, rents joined the trend but moved much more slowly than other areas. However, the pace of deceleration picked up late last year, with October and November registering modest increases. High-side readings in December and January suggested renewed upward pressure on rents, but a modest increase in February (0.1%) raises the possibility that rents will be less problematic than in the prior few years.

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

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- Food and energy post above-average price increases.
- Ex food and energy, apparel and airfares misbehave...
- ...but most other areas showed modest price changes.

February CPI: Moderate Increase Despite Jumps in Volatile Areas

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Mortgage applications rose 3.2% w/w (44.7% y/y) in the week ending March 6 after rising 11.0% w/w (55.9% y/y) in the week ending February 27, according to the Mortgage Bankers Association’s (MBA) Weekly Mortgage Applications Survey. Applications for loans to purchase a house rose 7.8% w/w (10.8% y/y) in the latest week, after rising 6.1% w/w (10.0% y/y) in the prior week.  Applications for loan refinancing edged up 0.5% w/w (80.7% y/y) in the week ending March 6, after a jump of 14.3% w/w (108.8% y/y) in the February 27 week.

The effective interest rate on a 30-year fixed-rate loan rose 12bps to 6.36% in the week ending March 6 from 6.24% in the week ending February 27. The rate on 15-year fixed-rate mortgages rose 7bps to 5.71% in the latest week from 5.64% in the prior week. The 30-year Jumbo rate rose 10bps to 6.35% in the March 6 week from 6.25% in the February 27 week. The rate on a 5-year ARM was unchanged at 5.50% in the week ending March 6 from the February 27 week.

The share of applications for refinancing an existing loan dropped to 57.8% of total applications in the week of March 6 from 59.8% in the February 27 week. The adjustable-rate mortgage (ARM) share of activity edged up to 8.9% in the March 6  week from 8.8% in the February 27 week.

The average size of a mortgage loan declined 1.3% w/w (-0.4% y/y) to $418,100 in the week ending March 6, after rising 1.6% w/w (6.1% y/y) to $423,400 in the week ending February 27. The average size of a purchase loan declined 1.0% w/w (-3.1% y/y) to $446,400 in the latest week, after rising 1.8% w/w (0.6% y/y) to $450,900 in the week ending February 27. The average size of a loan to refinance a mortgage dropped 1.9% w/w (+7.2% y/y) to $397,400 in the week ending March 6, after rising 1.6% w/w (20.4% y/y) to $404,900 in the week ending February 27.

The Mortgage Bankers Association Survey covers 75% of all U.S. retail residential mortgage applications and has been conducted weekly since 1990. Respondents include mortgage bankers, commercial banks and thrifts. The base period and value for all indexes is March 16, 1990=100. The figures for weekly mortgage applications and interest rates are available in Haver’s **SURVEYS** database.

- Both applications for loans to purchase and for loan refinancing rose.
- Effective interest rate on 30-year fixed loans rose 12bps to 6.36%.
- Average loan size declined.

U.S. Mortgage Applications Rose Again in the March 6 Week

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Industrial production (IP) rose a slightly larger-than-expected 0.2% m/m in February following an unrevised 0.7% monthly jump in January and small upward revisions to November (0.2% m/m vs. 0.1% previously) and December (0.3% m/m versus 0.2% m/m previously), according to data released by the Federal Reserve Board. The Action Economics Survey looked for a 0.1% monthly gain. The y/y rate slowed to 1.4% in February from 2.3% in January. The annual rate in February was the slowest since last August. However, IP has trended up over the past several months, growing at a 4.2% annual rate since last October although it is still 1.4% below its November 2018 peak.

Manufacturing output increased 0.2% y/y (1.3% y/y) in February following an upwardly revised 0.8% monthly gain in January (previously +0.6% m/m). Mining production increased by a solid 0.8% m/m (1.4% y/y) in February with the previously reported 0.2% monthly decline in January revised up meaningfully to a 0.9% monthly gain. This was the third monthly increase in mining in the past four months. Utilities output slid 0.6% m/m (+2.5 y/y), the first monthly decline in three months, after a downwardly revised 0.1% m/m increase in January (previously 2.1% m/m). This reflected unchanged electricity production and a 4.7% m/m decline in natural gas distribution.

Within manufacturing, durable goods production edged up 0.1% m/m (2.4% y/y) in February following an upwardly revised 1.1% monthly jump in January (previously 0.8% m/m). Activity in February was volatile across sectors. For example, output of electrical equipment and appliances rose 1.1% m/m and output of motor vehicles and parts jumped 1.7% m/m. By contrast, machinery output fell 1.2% m/m while miscellaneous production declined 1.1% m/m. Output of nondurable manufactured goods increased 0.2% m/m (0.3% y/y) in February after a 0.5% monthly gain in January (revised up slightly from 0.4% m/m). Output of plastics and rubber products rose 0.5% m/m in February on top of a 1.8% monthly jump in January; chemical production increased 0.9% m/m following a solid 1.2% monthly gain in January. By contrast, output of textiles slumped 1.7% m/m, and petroleum production declined 1.6% m/m, its first monthly decline in four months.

By market groups, output of consumer goods was unchanged in February (-0.2% y/y) following a 0.3% monthly increase in January (revised down from 0.7% m/m). Production of business equipment edged up 0.2% m/m (6.4% y/y) in February after a 0.9% m/m increase in January. Output of construction supplies dropped 0.2% m/m (+0.3% y/y) following a 1.1% monthly jump in January. Output of materials increased 0.3% m/m (1.7% y/y) in February on top of an 0.8% monthly gain in January.

In special classifications, output of selected high-tech industries rose 0.7% m/m (8.6% y/y) following an upwardly revised 2.6% monthly jump in January (previously 1.9% m/m). Output of motor vehicles and parts rose a solid 1.7% m/m (-0.7% y/y) in February on top of an upwardly revised 2.4% m/m surge in January (previously 1.3% m/m). The February gain was led by a 2.2% monthly increase in motor vehicle production. Manufacturing output excluding selected high-tech industries was up 0.2% m/m (1.0% y/y) in February after a 0.7% monthly rise in January. Manufacturing output excluding selected high-tech industries and motor vehicles and parts was unchanged in February (+1.2% y/y) following a 0.6% monthly increase in January.

Capacity utilization was unchanged at 76.3% in February, 3.1%-points below its long-term (1972-2025) average, from an upwardly revised 76.3% in January (previously 76.2%). The January/February reading was the highest since last July. Manufacturing capacity utilization was also unchanged at 75.6% in February, 2.6%-points below its long-term (1972-2025) average.

Industrial production and capacity data are in Haver’s **USECON** database. Additional detail on production and capacity utilization can be found in the **IP** database. The expectations figures come from the **AS1REPNA** database.

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- Total industrial output increased 0.2% m/m in February, slightly larger than expected.
- There was no revision to January, but there were small upward revisions to November and December.
- Manufacturing output increased 0.2% m/m, mining rose 0.8%, while utilities production slid 0.6% m/m.
- The headline rate of capacity utilization was unchanged in February and remained well below its long-term average.

U.S. Industrial Production Edged Up in February

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