Haver Analytics
Haver Analytics

Introducing

Peter D'Antonio

Peter started working for Haver Analytics in 2016. He worked for nearly 30 years as an Economist on Wall Street, most recently as the Head of US Economic Forecasting at Citigroup, where he advised the trading and sales businesses in the Capital Markets. He built an extensive Excel system, which he used to forecast all major high-frequency statistics and a longer-term macroeconomic outlook. Peter also advised key clients, including hedge funds, pension funds, asset managers, Fortune 500 corporations, governments, and central banks, on US economic developments and markets. He wrote over 1,000 articles for Citigroup publications.   In recent years, Peter shifted his career focus to teaching. He teaches Economics and Business at the Molloy College School of Business in Rockville Centre, NY. He developed Molloy’s Economics Major and Minor and created many of the courses. Peter has written numerous peer-reviewed journal articles that focus on the accuracy and interpretation of economic data. He has also taught at the NYU Stern School of Business.   Peter was awarded the New York Forecasters Club Forecast Prize for most accurate economic forecast in 2007, 2018, and 2020.   Peter D’Antonio earned his BA in Economics from Princeton University and his MA and PhD from the University of Pennsylvania, where he specialized in Macroeconomics and Finance.

Publications by Peter D'Antonio

  • The world has become more fragmented politically in the past decade, which has heightened global risk and uncertainty. The diminished sense of security has caused many countries to increase military spending. While this may be a rational response for individual countries, collectively, the rise in military spending has been alarming and seems to be leading the world toward even more risk and uncertainty. This in turn may feed the need for more security. In addition, the devotion of so much of the world’s resources to military spending may be damaging for the global economy.

    According to the Stockholm International Peace Research Institute (SIPRI), world annual military expenditure reached $2.8 trillion (in constant 2024 terms) in 2025. That figure represented a 41 percent increase in the past ten years. However, half of that rise occurred in the past three years. We looked at the SIPRI Military Expenditure dataset (available in Haver’s GLSECTOR database) to understand how and why military spending is changing across countries and regions.

    Worldwide gains in military spending The rise in military spending has been widespread. Between the years 2022 and 2025, 45 of the top 50 countries in terms of military spending posted increases, with an average gain among that group of 41.8 percent. NATO spending (excluding the US) jumped by 44.7 percent, while non-NATO military spending increased by 29.2 percent.

    Surprisingly, US military spending was essentially flat during this time. As a result, US military spending declined as a share of world spending by 6.6 percentage points to 33.5 percent. However, the Trump Administration has proposed a $1.5 trillion military budget for 2027, a roughly 60 percent increase from the 2025 spending listed in Figure 1. If that budget is enacted, then in 2027 the US's increase alone would be equivalent to 20 percent of 2025's entire world total. And we know that other countries both in NATO and Asia are ramping up spending as well.

  • Global| Aug 18 2025

    The Power of AI

    The global race in the field of Artificial Intelligence is becoming a priority for both nations and firms alike. However, we are concerned that the overwhelming energy needs of AI will force countries to compromise on the competing goal of environmental sustainability. In the second of his three-part Viewpoint series, The Age of Constraints, Andy Cates did an energy reality check. There he highlighted real energy prices and the ever-changing energy demands that are needed to power and cool the data centers supporting AI functionality. We further explore how leading economies have pursued energy generation over the past 20 years and deduce which directions they might take to power up AI.

    Specifically, we compare the forms of electricity generation across the three major players in the AI race – the United States, China, and Europe. This comparison shows the stark differences in total power needs as well as the contrasting compositions of power generation. These compositions reflect both physical capacities and societal goals across the three major economies.

  • The decline of US manufacturing and the rise of Chinese manufacturing has preoccupied policymakers over the past 25 years. It has resulted in the latest effort to use tariffs to try to drive domestic and foreign manufacturers back to the United States and limit trade disparities with China. This idea of bringing back manufacturing to the US is so ingrained in people’s thinking that it almost seems odd to question if that is a goal the US should pursue.

    The facts are clear: Employment in the US manufacturing sector from 1965 to 2000 was fairly stable in a range between 17 million and 19 million. However, there was an abrupt shift away from manufacturing in the early 2000s, to a new lower range of 11.5 million to 13 million, which was nearly a 6 million decline, or 33 percent (see chart 1).

  • The US current account deficit has nearly tripled over the past eight years, covering the previous two administrations. With the current account deficit now running at roughly $1.1 trillion per year or 3.7 percent of GDP, the new administration has announced across-the-board increases in tariffs in order to level the playing field on trade. We wondered how we got here and if the causes might highlight ways to solve the problem.

    In the April 3 Viewpoints article titled Liberating the Downside, Andy Cates and Kevin Gaynor discussed the prospects for narrowing the US current account deficit through tariffs in the context of the national accounts. One way to look at the national accounts is though the following identity

    (M – X) = (I – S) + (G – T)

    where (M – X) is the current account deficit, (I – S) is the private borrowing need, and (G – T) is the public borrowing need or the government budget deficit. This equation offers a valuable framework to identify the underlying causes of the undesirable rise in the US current account deficit.

    Based on a combination of Bureau of Economic Analysis NIPA Tables 3.1, 4.1 and 5.1 (all these data can be found in the Haver USNA database), it is clear that the interplay between saving and investment drives the current account, with some small adjustments for the statistical discrepancy.

    • Widespread job gains in December.
    • Jobless rate edges down.
    • Earnings pressures ease.