Dale Jorgenson has bestowed a great honor and no small challenge by inviting me to give this lecture: a great honor because of the distinguished list of economists who have preceded me; a challenge because of the standard they have set, and because there is no greater challenge for any economist than providing a coherent account of significant events to his scientific peers. I am sometimes asked by friends about the differences between academic life and life as a public official. There are many. Two stand out. First, as an academic, the gravest sin one can commit is to sign one’s name to something one did not write. As a public official it is a mark of effectiveness to do so as often as possible. Second, as an academic, if a problem is too hard and does not admit of a satisfactory solution, there is an obvious response: work on a different problem. That is not a luxury that one has in government. I have been reminded of this often in recent years as we have grappled with financial crises in a number of what had previously been considered emerging markets with unrestrained futures. Anyone who doubts the social importance of what economists do should consider the debates surrounding these crises. Hundreds of millions of people who expected rapidly rising standards of living have seen their living standards fall; hundreds of thousands if not millions of children have been forced to drop out of school and go to work; hundreds of billions of dollars of apparent wealth has been lost; the stability of large nations as nations has been called into question; and the United States has made its largest nonmilitary foreign-policyrelated financial commitments since the Marshall Plan. Almost all the issues involved in understanding, preventing, and mitigating these crises are the stuff of economics courses and research: fixed versus flexible exchange rates, moral hazard and multiple equilibria, speculation and liquidity, fiscal and monetary policies, regulation and competition. What economists think, say, and do has profound implications for the lives of literally billions of their fellow citizens. Whether it is discussing the role of derivatives in signaling exchange-rate commitments with Chinese Premier Zhu Rongji, or discussing an NBER working paper on inflation targeting with the Brazilian central bank governor Arminio Fraga, or discussing alternative approaches to bankruptcy law with Indonesia’s economic team, or optimal debt durations with the Mexican authorities, I am consistently struck by the impact of the kind of research discussed at the AEA meetings. The future well-being of the world’s people in large part will depend on how the ongoing process of global integration works out. This is a strong statement, but one that is supported by the global economy’s post-World War I failure and its post-World War II success. Central to global integration is financial integration: the flow of funds and of capital across international borders. And as the events of the late 1920’s and early 1930’s remind us, central to global disintegration can be international financial breakdowns. Today, I want to reflect on the issue of global financial integration in light of the dramatic and largely unpredicted events of recent years. It is perhaps a good time for reflection: there has been enough repair that priority can shift from * U.S. Department of the Treasury, 1500 Pennsylvania Avenue, Washington, DC 20005. This lecture reflects many things I have learned from experiences I have shared with colleagues in the United States government and governments around the world. I thank Brad DeLong, Marty Feldstein, Stephanie Flanders, Ken Rogoff, Andrei Shleifer, and Ted Truman for useful comments and suggestions. I am especially grateful to Nouriel Roubini and Stephanie Flanders for valuable discussions and assistance in the preparation of this lecture. The usual disclaimer applies

Charles R. Hulten's (1992) article suggested that very little of the productivity slowdown of the 1970's could be attributed to capital-embodied technical change. Hulten estimated that about 20 percent of total technical change (what he termed the residual growth of quality-adjusted output) in U.S. manufacturing over the period from 1949 to 1983 could be ascribed to embodied technical change in machinery and equipment. However, he found very little difference in the contribution of embodied technical change to total technical change between the periods 1949-1973 and 1974-1983, the slowdown period. In my paper (Wolff, 1991), I found a very significant vintage effect, estimated by the change in the average age of the capital stock. My data, drawn from Angus Maddison (1982), covered the G-7 countries over the period 1880-1979 and were based on figures for total capital (structures, machinery, and equipment) and for the entire economy. These results suggested that embodied technical change played a significant role in the productivity falloff of the 1970's. In this paper, I use more recent data for six OECD countries (France, Germany, Japan, the Netherlands, the United Kingdom, and the United States) compiled by Angus Maddison (1991, 1993a, b) and focus on the period from 1950 to 1989. I find here that the vintage effect is, indeed, a very strong determinant of the post-1973 productivity slowdown among OECD countries, explaining on average about two-fifths of the slowdown. The effect varies among countries, from a low of 23 percent in Japan to 69 percent in France. For the United States, the vintage effect appears to account for a little over half of its slowdown. Though it should be stressed that my results do not directly contradict those of Hulten, whose measure of technical change was confined to machinery and equipment within U.S. manufacturing, I will still attempt some reconciliation of my findings with those of Hulten at the end. The discrepancy in results suggests the possibility that the slowdown in investment in public infrastructure after 1973 may have played an important role in the post-1973 productivity slowdown. Moreover, since this is only a note, I will not review the rather extensive literature on the productivity slowdown of the 1970's (see, for example, Edward F. Denison's [1979] and my [Wolff, 1985] review articles), except to list a number of factors that have been examined. The main candidates have included the slowdown in the rate of capital formation, changes in the composition of the labor force, the role of energy price shocks, declines in R&D spending (and/ or the productivity of R&D), changes in the composition of output (mainly, the shift to services), and increased government regulation. Of these, the decline in investment appears to have played a major role, explaining about a fourth to a third of the slowdown in U.S. productivity growth after 1973. In Section I, I present the basic data for the analysis. The basic regression results are presented in Section II. In Section III, I consider other possible factors that may have played a role in the productivity slowdown of the 1970's. Section IV provides a decomposition of labor productivity growth into its various sources, including a vintage effect, estimated by changes in the average age of capital. Section V analyzes the relative importance of each component in the falloff of productivity growth observed among OECD countries after * Department of Economics, New York University, New York, NY 10003. The author would like to express appreciation to Moses Abramovitz, Charles Hulten, and two anonymous referees for their comments and to the Sloan Foundation and C.V. Starr Center for Applied Economics at New York University for financial support

During the past fifteen years, the United States has experienced a dramatic decline in productivity growth. In the two decades before the mid-1960's, real output per hour of labor input in the private nonfarm sector grew at an average rate of 2-1/2 percent a year, fueling a dramatic rise in both the amount of goods and services produced and the average real wage of American workers. Since then, productivity performance has been much poorer, falling to about 2 percent per year between 1965 and 1973, and then to less than two-thirds of a percent per year between 1973 and 1979. Recent experience is particularly discouraging: current estimates indicate that productivity in the private nonfarm sector is still lower than it was in 1977. While the productivity slowdown has rekindled interest in the sources of growth, none of the new research has yielded a satisfactory solution to the Great Productivity Mystery. Most growth accounting studies have indicated that less than half of the observed slowdown in the growth of output per unit of labor input can be explained by the capital intensity of production, the education and experience of workers, increased regulation, and the age of the capital stock. Some researchers claim that the increase in energy prices (and the resulting reduction in energy input) is responsible for much of the decline, but their case is far from proven. Little attention has been paid to the close correlation between slower productivity growth in the United States and the other major economic development since World War II: the shift from price stability before the mid-1960's to persistent inflation since then. The timing of reductions in productivity growth strongly suggest that the productivity slowdown is related to the inflationary process. Labor productivity started increasing more slowly in the mid1960's, just as the current inflationary spiral began to gain momentum. In the 1970's, as inflation increased, productivity performance deteriorated even further. The negative correlation between inflation and productivity growth is particularly striking when the cumulative deviation of the price level from its pre-1965 trend is compared to the cumulative deviation of productivity from its trend over the same period, as in Figure 1. Abstracting from cyclical wiggles in productivity, the increases in the inflation rate closely track the reductions in productivity growth that the economy has experienced. Over the past fifteen years, each increase of one percentage point in the annual inflation rate has been accompanied by a reduction in labor productivity growth of about one-fourth of a percentage point per year. A number of sound theoretical reasons suggest that this correlation is more than a statistical accident, and that inflation has been a major cause of the recent productivity slowdown. First, by increasing the variance of relative prices, inflation may have reduced the ability of the price system to transmit information and cut into real efficiency gains. Second, inflation may have created a downward bias in the measurement of real output, producing a fictitious reduction in productivity growth. Third, energy price increases may have generated significant reductions in productivity growth, either by causing a shift toward more labor-intensive means of production or by altering the environment in which technical progress takes place. Fourth, inflation has eroded tax deductions for depreciation and raised the rental price of capital services, which may have retarded the growth of capital per worker. In addition to these possibilities, which have causation running from higher inflation to lower productivity growth, the correlation between productivity and the price level may have been *Federal Reserve Board of Governors. The views expressed in this paper are my own, and do not necessarily represent those of the Board of Governors or the staff of the Federal Reserve System. A bibliography for this article is available from the author on request

Variable Annuities are the subject of considerable discussion by individuals who identify themselves with life insurance companies and security dealers. The paper by Mr. Albert Linton published in the May, 1956, issue of the Journal of Finance is a case in point. This comment does not attempt to marshall arguments for or against variable annuities, but is concerned only with the major factors determining the size of the payments to be made from a variable annuity fund during the payment period. In Mr. Linton's Table 2, the assumption is made that the variable annuity payment would follow Standard and Poor's index of stock prices.1 The other major factor influencing the size of the annuity payment, the cash dividends that will be received by and added to the annuity fund during the period of the annuity payments, is omitted. This is comparable to omitting interest on the standard annuity contract. The purpose of Table 2 was evidently to display the magnitude of the fluctuations in variable annuity payments in contrast to the absolute dollar stability of the payments made under the terms of a traditional annuity contract. Mr. Linton emphasizes that “irate and disillusioned policyholders” might write letters to insurance commissioners and even congressmen when payments fall under variable annuity contracts. Such pressure might have been (or may be) the opportunity for federal regulation of those life insurance companies that issue variable annuity contracts. Column 1, Table 1, in this comment sets forth the fixed payment of $100 per month specified by Mr. Linton, Column 2 reproduces the assumed monthly payment made under a variable annuity contract as shown by Mr. Linton in his. Table 2, and Column 3 presents a revised statement of the monthly payment under a variable annuity contract taking cognizance of the dividends received by the annuity fund during each year of the life of the annuity. The period 1926 to 1954 is the period selected by Mr. Linton. According to Mr. Linton's presentation, the payments made under the variable annuity were less than those under the traditional contract in twelve of the twenty-nine years. The revised variable annuity payments fall below the fixed monthly payments of $100 in only three years. Furthermore, the lowest payment under the revised computation is $83 per month as compared with $49 per month shown by Mr. Linton. Certainly the intensity of the remarks in the policyholders' letters would be different if the variable annuity payments fell 17 per cent rather than 51 per cent below a norm established by the payment of a fixed number of dollars under a fixed annuity contract. Fixed annuity policyholders may well complain about the opportunities missed when they compare their $100 with the more than $200 monthly income in 1954 that might have been possible under a variable annuity contract. In the computation of Column 3, Table 1, the advantages accruing to the variable annuitant during the accumulation period have been foregone. Mr. Linton recognizes this advantage in suggesting that the rate of growth of funds during the accumulation period invested in a well-selected, properly diversified group of stocks has been larger than the rate of interest achieved by the investment portfolios that are the basis for traditional annuity contracts. We believe that such higher yields on equities are not dependent on inflation given the maintenance of our long-run rate of economic growth and that this relationship is very likely to continue. This position, however, must be left undefended since the space that may be alloted to a comment is very limited. Let the case of the conservative be admitted, however. The holder of a variable annuity contract, the annuitant, would take more risk with respect to the number of dollars he will eventually receive. Life insurance companies, other financial institutions, and even the structure of the capital markets will be affected by any considerable growth in the use of variable annuities. Such changes are certain to follow whether the life insurance companies themselves or some newly developed type of financial institution handles variable valued annuities

Johannes Stroebel is the David S. Loeb Professor of Finance at New York University's Stern School of Business. Johannes joined Stern as an Assistant Professor of Finance in 2013 and received tenure in 2016. He started his career in 2012 as the Neubauer Family Assistant Professor of Economics at the University of Chicago Booth School of Business after earning a Ph.D. in Economics at Stanford University. Stroebel's prolific body of work, which looks more like that of somebody 20 rather than only 10 years out of the Ph.D., spans a broad range of topics and uses a variety of methods. He has made important contributions to at least four areas: household finance, asset pricing, climate risk, and social networks. Several papers forge connections between these areas. I highlight key contributions to each of these research agendas. The first strand of Johannes' work focuses on household finance. In two papers published in the Quarterly Journal of Economics (Agarwal et al. (2015, 2018)), Stroebel combines a large microlevel data set of credit card accounts with careful identification. The first paper finds that regulation that protected consumers by limiting fees was not undone by banks charging higher costs elsewhere, but rather resulted in higher consumer surplus. The second paper uses the cross-section of credit card accounts to show that the monetary pass-through via the bank lending channel is limited because the borrowers with a high marginal propensity to borrow and consume are those for which the banks have a low marginal willingness to lend. Another important paper in household finance is the American Economic Review paper (Giglio et al. (2021b)) that establishes a modest response of financial portfolio decisions to households' beliefs about expected returns. Johannes returns to the topic of consumer credit in a forthcoming Journal of Finance paper (Howell et al. (2023)) on lender automation and racial disparities in credit access. Much of Johannes' work, some of which I describe below, touches on housing, the largest asset in households' portfolios. Stroebel's second main research pillar is asset pricing. In three connected papers, Giglio, Maggiori, and Stroebel infer the discount rates that investors apply to cash flows that accrue in the very far future. Such very long discount rates are important, for example, for analyses of greenhouse gas abatement investments that trade off the uncertain future benefits against current costs (Giglio et al. (2021a)). More on the climate implications below. In traditional financial markets, we have very few very long-lived assets from which to infer long-run discount rates. The authors turn to real estate markets. In Singapore and the United Kingdom, investors can buy houses either as freeholds, which grant perpetual ownership rights to land and structure, or as leaseholds, which grant tradeable temporary ownership rights ranging between 75 and 999 years. From the price difference between freeholds and leaseholds of different maturities, the authors back out a term structure of discount rates under reasonable assumptions on growth rates of rents. The observed price discounts imply low long-run discount rates of 2.6% per year for very far-out payoffs. Combined with the observation that the overall (maturity-weighted) return on housing is around 6% per year, they conclude that the term structure of discount rates is downward sloping (Giglio, Maggiori, and Stroebel (2015)). These discount rate estimates suggest that there was no bubble in these housing markets in the 2000s (Giglio, Maggiori, and Stroebel (2016)). Put differently, the risk premium applied to cash flows in the very far future is high enough to make its present discounted value equal to zero; the transversality condition for long-lived assets is likely to be satisfied. The third and most recent area Johannes has focused on is climate finance, as summarized in a recent review article (Giglio, Kelly, and Stroebel (2021)). A central issue in this literature is how to think of the uncertainty associated with future benefits of climate abatement investments. More economic activity creates larger climate damages as a by-product. But climate risk also directly affects the economy, think of a natural disaster. Under the first view, states of the world with lots of climate change are states of the world with high GDP (Nordhaus (2013)), whereas in the second view, they are states with low GDP (Barro (2015), Weitzman (2012)). Whether states of the world with rapid climate change are good or bad states has major quantitative implications for the discount rate to be used when calculating the benefits of climate mitigation and the social cost of carbon. Giglio et al. (2021a) argue that real estate markets are informative for which discount rate to use when evaluating climate abatement investments. It establishes that real estate returns are risky, performing poorly in low-growth and consumption disaster states. It also documents that real estate values are indeed exposed to climate risk by studying how coastal house prices change when the perception of climate risk increases. A disaster risk model, where economic activity increases the likelihood of a climate disaster and rebounds after a disaster, generates a downward-sloping discount rate curve, consistent with the aforementioned evidence from the real estate market. Since climate abatement investments hedge climate change risk, the appropriate discount rates are below the risk-free rate at all maturities and rising in maturity. Johannes has several more interesting papers in climate finance (Engle et al. (2020), Stroebel and Wurgler (2021), van Benthem et al. (2022), Alekseev et al. (2022)) that zoom in on risk measurement and management. The fourth, and maybe most well-known area of Johannes' research portfolio is his work on how social networks affect economic decision making, summarized in Bailey et al. (2018a) and Kuchler and Stroebel (2021). Together with Theresa Kuchler and other coauthors, Johannes uses Facebook (now Meta) data to construct a social graph of friendship links and shows that this network is important for the transmission of beliefs about all kinds of real outcomes. Their first and best-known paper in this agenda is in the Journal of Political Economy (Bailey et al. (2018b)). It shows that friends' experiences with house price growth shape the homeownership choices and the price paid for houses of their geographically distant Facebook friends. This influence occurs by changing their beliefs. In Bailey et al. (2019), the authors explore how variation in house price beliefs that is induced by the same type of social network variation affects mortgage leverage choice. Kuchler et al. (2022) shows that mutual fund investment decisions are in part determined by social networks. In more recent worth with Raj Chetty, Matt Jackson, Theresa Kuchler, and other coauthors (Chetty et al. (2022a, 2022b)), Johannes investigates that the effect friendship networks have on upward income mobility. They also study the factors that influence interactions across people of different socioeconomic backgrounds and suggest policy interventions that could increase such interactions. The Fischer Black Prize honors individual financial research. It is awarded for a body of work that best exemplifies the Fischer Black hallmark of developing original research that is relevant to finance practice. The winner should either be under age 40, or under age 45 for a winner who had not been awarded a Ph.D. (or equivalent) by age 35. The American Finance Association appreciates the generosity of the original donors who made this prize possible and the recent 2018 donors who helped to substantially increase the endowment. The names of the donors can be found at https://afajof.org/fischer-black-prize