Ellen is a consultant at the Federal Reserve Bank of Minneapolis, a professor of economics at the University of Minnesota, and director of the Heller-Hurwicz Economics Institute. She is also a research associate at the National Bureau of Economic Research, a Fellow of the Econometric Society, a Fellow of the Society for the Advancement of Economic Theory, a member of the Bureau of Economic Analysis Advisory Committee, a member of the Minnesota Population Center Advisory Board, and President-elect of the Midwest Economics Association.
Ellen received her B.S. in economics and mathematics from Boston College and her Ph.D. from Stanford University. Prior to coming to Minnesota she taught at Duke University. She has also taught short courses at European University Institute, University of Pennsylvania, Stockholm School of Economics, UCLA, International Monetary Fund, Arizona State University, and Universidad do Minho.
Ellen’s research is concerned with the aggregate effects of monetary and fiscal policy—in particular, the effects on GDP, investment, the allocation of hours, the stock market, and international capital flows. Her recent work reexamines some business cycle puzzles in macroeconomics, considering the fact that some investments are unmeasured. Along with colleague Ed Prescott, she has also been analyzing policy reforms related to financing retirement in economies with aging populations.
Japan is facing the problem of how to finance retirement, health care, and long-term care expenditures as the population ages. This paper analyzes the impact of policy options intended to address this problem by employing a dynamic general equilibrium overlapping generations model, specifically parameterized to match both the macro- and microeconomic level data of Japan. We find that financing the costs of aging through gradual increases in the consumption tax rate delivers better macroeconomic performance and higher welfare for most individuals relative to other financing options, including raising social security contributions, debt financing, and a uniform increase in health care and long-term care copayments.
This paper examines the reliability of widely used surveys on U.S. businesses. We compare survey responses of business owners with administrative data and document large inconsistencies in business incomes, receipts, and the number of owners. We document problems due to nonrepresentative samples and measurement errors. Nonrepresentativeness is reflected in undersampling of owners with low incomes. Measurement errors arise because respondents do not refer to relevant documents and possibly because of framing issues. We discuss implications for statistics of interest, such as business valuations and returns. We conclude that predictions based on current survey data should be treated with caution.
In this paper, we first provide evidence that existing measures of business incomes and valuations based on widely used surveys such as the Survey of Consumer Finances are mismeasured. We then develop a theory disciplined by U.S. national accounts and business census data to measure net incomes and private business sweat equity—which is the value of time to build customer bases, client lists, and other intangible assets. We estimate an aggregate sweat equity value of 0.65 times GDP, with little cross-sectional dispersion in valuations when compared to business net incomes and large cross-sectional dispersion in rates of return. Our estimate of sweat equity is close to the estimate of marketable fixed assets used in production by private businesses, implying a high ratio of intangible to total assets. We use the model to evaluate the impact of greater tax compliance of private businesses and lower tax rates on the net income of both privately held and publicly traded businesses. We find larger sectoral and aggregate effects from the tax policy experiments relative to studies that abstract from private business and, in particular, the accumulation of sweat capital. Finally, we show that our results are robust to including nonpecuniary benefits of business ownership.
Because ﬁrms invest heavily in R&D, software, brands, and other intangible assets—at a rate close to that of tangible assets—changes in measured GDP, which does not include all intangible investments, understate the actual changes in total output. If changes in the labor input are more precisely measured, then it is possible to observe little change in measured total factor productivity (TFP) coincidentally with large changes in hours and investment. This mismeasurement leaves business cycle modelers with large and unexplained labor wedges accounting for most of the ﬂuctuations in aggregate data. To address this issue, I incorporate intangible investments into a multi-sector general equilibrium model and parameterize income and cost shares using data from an updated U.S. input and output table, with intangible investments reassigned from intermediate to ﬁnal uses. I employ maximum likelihood methods and quarterly observations on sectoral gross outputs for the United States over the period 1985–2014 to estimate processes for latent sectoral TFPs—that have common and sector-speciﬁc components. Aggregate hours are not used to estimate TFPs, but the model predicts changes in hours that compare well with the actual hours series and account for roughly two-thirds of its standard deviation. I ﬁnd that sector-speciﬁc shocks and industry linkages play an important role in accounting for ﬂuctuations and comovements in aggregate and industry-level U.S. data, and I ﬁnd that the model’s common component of TFP is not correlated at business cycle frequencies with the standard measures of aggregate TFP used in the macroeconomic literature.
In this paper, we estimate the impact of increasing costs on foreign producers following a withdrawal of the United Kingdom from the European Union (popularly known as Brexit). Our predictions are based on simulations of a multicountry neoclassical growth model that includes multinational firms investing in research and development (R&D), brands, and other intangible capital that is used nonrivalrously by their subsidiaries at home and abroad. We analyze several post-Brexit scenarios. First, we assume that the United Kingdom unilaterally imposes tighter restrictions on foreign direct investment (FDI) from other E.U. nations. With less E.U. technology deployed in the United Kingdom, U.K. firms increase investment in their own R&D and other intangibles, which is costly, and welfare for U.K. citizens is lower. If the European Union remains open, its citizens enjoy a modest gain from the increased U.K. investment since it can be costlessly deployed in subsidiaries throughout Europe. If instead we assume that the European Union imposes the same restrictions on U.K. FDI, then E.U. firms invest more in their own R&D, benefiting the United Kingdom. With costs higher on both U.K. and E.U. FDI, we predict a significant fall in foreign investment and production by U.K. firms. The United Kingdom increases international lending, which finances the production of others both domestically and abroad, and inward FDI rises. U.K. consumption falls and leisure rises, implying a negligible impact on welfare. In the European Union, declines in investment and production are modest, but the welfare of E.U. citizens is significantly lower. Finally, if, during the transition, the United Kingdom reduces current restrictions on other major foreign investors, such as the United States and Japan, U.K. inward FDI and welfare both rise significantly.
Many countries are facing challenging fiscal financing issues as their populations age and the number of workers per retiree falls. Policymakers need transparent and robust analyses of alternative policies to deal with demographic changes. In this paper, we propose a simple framework that can easily be matched to aggregate data from the national accounts. We demonstrate the usefulness of our framework by comparing quantitative results for our aggregate model with those of a related model that includes within-age-cohort heterogeneity through productivity differences. When we assess proposals to switch from the current tax and transfer system in the United States to a mandatory saving-for-retirement system with no payroll taxation, we find that the aggregate predictions for the two models are close.
We elaborate on the business cycle accounting method proposed by Chari, Kehoe, and McGrattan (2007), clear up some misconceptions about the method, and then apply it to compare the Great Recession across OECD countries as well as to the recessions of the 1980s in these countries. We have four main findings. First, with the notable exception of the United States, Spain, Ireland, and Iceland, the Great Recession was driven primarily by the efficiency wedge. Second, in the Great Recession, the labor wedge plays a dominant role only in the United States, and the investment wedge plays a dominant role in Spain, Ireland, and Iceland. Third, in the recessions of the 1980s, the labor wedge played a dominant role only in France, the United Kingdom, Belgium, and New Zealand. Finally, overall in the Great Recession the efficiency wedge played a more important role and the investment wedge played a less important role than they did in the recessions of the 1980s.
Foreign investment into China has surged since the 1990s and become a topic of keen interest for both scholars and the media. While China has encouraged this investment with the goal of catching up technologically, close analysis reveals that only a small share of its foreign investment comes from the United States and other nations with the technology China seeks.
Instead, inward foreign direct investment (FDI) flows predominantly from Hong Kong and a few Caribbean nations. Two key factors behind this: China’s tax policy toward foreign investment and its “industrial” policies to encourage development and growth. Specifically, preferential tax treatment for foreign investment leads many Chinese businesses and households to “round-trip” investments; and policies requiring joint ventures between Chinese and foreign high-tech companies—while benefiting China enormously—discourage investment by multinationals from advanced countries.
A problem that faces many countries including the United States is how to finance retirement consumption as the population ages. Proposals for switching to a saving-for-retirement system that do not rely on high payroll taxes have been challenged on the grounds that welfare would fall for some groups such as retirees or the working poor. We show how to devise a transition path from the current U.S. system to a saving-for-retirement system that increases the welfare of all current and future generations, with estimates of future gains higher than those found in typically used macroeconomic models. The gains are large because there is more productive capital than commonly assumed. Furthermore, the gains are amplified if we lower capital income taxes in addition to payroll taxes, because the value of business equity increases relative to the capital stock. Our quantitative results depend importantly on accounting for differences between actual government tax revenues and what revenues would be if all income were taxed at the income-weighted average marginal tax rates used in our analysis.
In its “Statement on Longer-Run Goals and Monetary Policy Strategy,” the Federal Open Market Committee (Federal Reserve Board of Governors, 2014) summarizes its two main objectives: to mitigate (i) deviations of inflation from its longer-run goal and (ii) deviations of employment from the Federal Open Market Committee’s assessment of its maximum level. In the case of employment, the statement acknowledges that “the maximum level … is largely determined by nonmonetary factors,” which is why the FOMC sets no fixed goal for the employment level. It instead depends on the Committee’s “assessment.”
In this paper, I investigate the link between monetary policy and employment using predictions of current monetary theory. The results show that even with the extraordinary monetary accommodation provided by the Fed since 2008, theory predicts only a small impact of monetary policy on employment. Other research suggests that to understand what does impact employment levels and hours worked, economic theory should be modified to account for factors that impact labor-leisure decisions.
Some have proposed wealth taxation as a means of reducing economic inequality, but such proposals are premature. While economic theory and data measurement have solid grounding when analyzing other forms of taxation, such as income or sales taxes, this is not the case for wealth.
Total estimates of the two most widely used measures of wealth, fixed assets and net worth, vary widely over the six decades for which data are available. Trend lines in these two wealth measures are rarely correlated. In addition, the relationship between the two—and explanation of why they differ so radically—remains a theoretical puzzle for economists. Given this state of affairs, accurate predictions for the impact, and design, of wealth taxation policies are not yet possible.
By the 1970s, quid pro quo policy, which requires multinational firms to transfer technology in return for market access, had become a common practice in many developing countries. While many countries have subsequently liberalized quid pro quo requirements, China continues to follow the policy. In this paper, we incorporate quid pro quo policy into a multicountry dynamic general equilibrium model, using microevidence from Chinese patents to motivate key assumptions about the terms of the technology transfer deals and macroevidence on China’s inward foreign direct investment (FDI) to estimate key model parameters. We then use the model to quantify the impact of China’s quid pro quo policy and show that it has had a significant impact on global innovation and welfare.
To gain access to its markets, the Chinese government sometimes requires high-technology foreign firms to transfer partial property rights to their technology. Because the Chinese market is large and potentially lucrative, major multinationals typically agree to this quid pro quo policy, often through joint ventures with Chinese firms.
We use a quantitative macroeconomic model to analyze the effects of this policy on firm investment incentives, Chinese technology goals, and overall international technology and investment flows.
We study the large observed changes in labor supply by married women in the United States over the post–World War II period, a period that saw little change in the labor supply by single women. We investigate the effects of changes in the gender wage gap, the quantitative impact of technological improvements in the production of nonmarket goods, and the potential inferiority of nonmarket goods in explaining the dramatic change in labor supply. We find that small decreases in the gender wage gap can simultaneously explain the significant increases in the average hours worked by married women and the relative constancy in the hours worked by single women and by single and married men. We also find that the impact of technological improvements in the household on married female hours and on the relative wage of females to males is too small for realistic values. Some specifications of the inferiority of home goods match the hours patterns, but they have counterfactual predictions for wages and expenditure patterns.
During the downturn of 2008–2009, output and hours fell significantly while labor productivity rose. These facts have led many to conclude that there is a significant deviation between observations and current macrotheories that assume business cycles are driven, at least in part, by fluctuations in total factor productivities of firms. We show that once investment in intangible capital is included in the analysis, there is no inconsistency. Measured labor productivity rises if the fall in output is underestimated; this occurs when there are large unmeasured intangible investments. Microevidence suggests that these investments are large and cyclically important.
Prior to the mid-1980s, labor productivity growth was a useful barometer of the U.S. economy’s performance: it was low when the economy was depressed and high when it was booming. Since then, labor productivity has become significantly less procyclical. In the recent downturn of 2008–2009, labor productivity actually rose as GDP plummeted. These facts have motivated the development of new business cycle theories because the conventional view is that they are inconsistent with existing business cycle theory. In this paper, we analyze recent events with existing theory and find that the labor productivity puzzle is much less of a puzzle than previously thought. In light of these findings, we argue that policy agendas arising from new untested theories should be disregarded.
Empirical studies quantifying the economic effects of increased foreign direct investment (FDI) have not provided conclusive evidence that they are positive, as theory predicts. This paper shows that the lack of empirical evidence is consistent with theory if countries are in transition to FDI openness. Anticipated welfare gains lead to temporary declines in domestic investment and employment. Also, growth measures miss some intangible FDI, which is expensed from company profits. The reconciliation of theory and evidence is accomplished with a multicountry dynamic general equilibrium model parameterized with data from a sample of 104 countries during 1980–2005. Although no systematic benefits of FDI openness are found, the model demonstrates that the eventual gains in growth and welfare can be huge, especially for small countries.
Previous studies of the U.S. Great Depression find that increased government spending and taxation contributed little to either the dramatic downturn or the slow recovery. These studies include only one type of capital taxation: a business profits tax. The contribution is much greater when the analysis includes other types of capital taxes. A general equilibrium model extended to include taxes on dividends, property, capital stock, and excess and undistributed profits predicts patterns of output, investment, and hours worked that are more like those in the 1930s than found in earlier studies. The greatest effects come from the increased taxes on corporate dividends and undistributed profits.
A problem facing the United States and many other countries is how to finance retirement consumption as the number of their workers per retiree falls. The problem with a savings for retirement systems is that there is a shortage of good savings opportunities given the nature of most current tax systems and governments’ limited ability to honor the debt it issues. We find that eliminating capital income taxes will greatly increase saving opportunities and make a savings-for-retirement system feasible with only modest amount of government debt. The switch from a system close to the current U.S. retirement system, which relies heavily on taxing workers’ incomes and making lump-sum transfers to retirees, to one without income taxes will increase the welfare of all birth-year cohorts alive today and particularly the welfare of the yet unborn cohorts. The equilibrium paths for the current and alternative policies are computed.
It is widely believed that an important factor underlying the rapid growth in China is increased foreign direct investment (FDI) and the transfer of foreign technology capital, which is accumulated know-how from investment in research and development (R&D), brands, and organizations that is not specific to a plant. In this paper, we study two channels through which FDI can contribute to upgrading of the stock of technology capital: knowledge spillovers and appropriation. Knowledge spillovers lead to new ideas that do not directly compete or devalue the foreign affiliate’s stock. Appropriation, on the other hand, implies a redistribution of property rights over patents and trademarks; the gain to domestic companies comes at a loss to the multinational company (MNC). In this paper we build these sources of technology capital transfer into the framework developed by McGrattan and Prescott (2009, 2010) and introduce an endogenously-chosen intensity margin for operating technology capital in order to capture the trade-offs MNCs face when expanding their markets internationally. We first demonstrate that abstracting from technology capital transfers results in predicted bilateral FDI inflows to China that are grossly at odds with the data. We then use the bilateral inflows to parameterize the model with technology capital transfers and compute the global economic impact of Chinese policies that encouraged greater inflows of FDI and technology capital transfers. Microevidence on automobile patents is used to support our parameter choices and main findings.
For the 1990s, the basic neoclassical growth model predicts a depressed economy, when in fact the U.S. economy boomed. We extend the base model by introducing intangible investment and non-neutral technology change with respect to producing intangible investment goods and find that the 1990s are not puzzling in light of this new theory. There is micro and macro evidence motivating our extension, and the theory’s predictions are in conformity with U.S. national accounts and capital gains. We compare accounting measures with corresponding measures for our model economy. We find that standard accounting measures greatly understate the 1990s boom.
Applied macroeconomists interested in identifying the sources of business cycle fluctuations typically have no more than 40 or 50 years of data at a quarterly frequency. With sample sizes that small, identification may not be possible even with correctly specified representations of the data. In this article, I investigate whether small samples are indeed a problem for some commonly used statistical representations. I compare three—a vector autoregressive moving average (VARMA), an unrestricted state space, and a restricted state space—that are all consistent with the same prototype business cycle model. The statistical representations that I consider differ in the amount of a priori theory that is imposed, but all are correctly specified. I find that the identifying assumptions of VARMAs and unrestricted state space representations are too minimal: the range of estimates for statistics of interest for business cycle researchers is so large as to be uninformative.
Michael Christian’s paper presents a human capital account for the United States for the period 1994 to 2006. The main findings are twofold. First, the total human capital stock is about three-quarters of a quadrillion dollars in 2006. This estimate is roughly 55 times gross domestic product (GDP) and 16 times the net stock of fixed assets plus consumer durables. His second finding is that the measures of gross investment in human capital are sensitive to alternative assumptions about enrollment patterns. In my comments, I emphasize the need for greater interaction between human capital accountants and applied economists. To date, there remains a disconnect between those measuring human wealth and those investigating its economic impact.
The U.S. Bureau of Economic Analysis (BEA) estimates the return on investments of foreign subsidiaries of U.S. multinational companies over the period 1982–2006 averaged 9.4 percent annually after taxes; U.S. subsidiaries of foreign multinationals averaged only 3.2 percent. Two factors distort BEA returns: technology capital and plant-specific intangible capital. Technology capital is accumulated know-how from intangible investments in R&D, brands, and organizations that can be used in foreign and domestic locations. Used abroad, it generates profits for foreign subsidiaries with no foreign direct investment (FDI). Plant-specific intangible capital in foreign subsidiaries is expensed abroad, lowering current profits on FDI and increasing future profits. We develop a multicountry general equilibrium model with an essential role for FDI and apply the BEA’s methodology to construct economic statistics for the model economy. We estimate that mismeasurement of intangible investments accounts for over 60 percent of the difference in BEA returns.
There is much debate about the usefulness of the neoclassical growth model for assessing the macroeconomic impact of fiscal shocks. We test the theory using data from World War II, which is by far the largest fiscal shock in the history of the United States. We take observed changes in fiscal policy during the war as inputs into a parameterized, dynamic general equilibrium model and compare the values of all variables in the model to the actual values of these variables in the data. Our main finding is that the theory quantitatively accounts for macroeconomic activity during this big fiscal shock.
Macroeconomists have largely converged on method, model design, reduced-form shocks, and principles of policy advice. Our main disagreements today are about implementing the methodology. Some think New Keynesian models are ready to be used for quarter-to-quarter quantitative policy advice; we do not. Focusing on the state-of-the-art version of these models, we argue that some of its shocks and other features are not structural or consistent with microeconomic evidence. Since an accurate structural model is essential to reliably evaluate the effects of policies, we conclude that New Keynesian models are not yet useful for policy analysis.
In this paper, we extend the growth model to include firm-specific technology capital and use it to assess the gains from opening to foreign direct investment. A firm’s technology capital is its unique know-how from investing in research and development, brands, and organization capital. Technology capital is distinguished from other forms of capital in that a firm can use it simultaneously in multiple domestic and foreign locations. A country can exploit foreign technology capital by permitting direct investment by foreign multinationals. In both steady-state and transitional analyses, the extended growth model predicts large gains to being open.
Over the period 1982–2006, the U.S. Bureau of Economic Analysis (BEA) estimates the return on investments of foreign subsidiaries of U.S. multinational companies averaged 9.4 percent per year after taxes while U.S. subsidiaries of foreign multinationals earned on average only 3.2 percent. We estimate the importance of two factors that distort BEA returns: technology capital and plant-specific intangible capital. Technology capital is accumulated know-how from intangible investments in R&D, brands, and organizations that can be used in foreign and domestic locations. Technology capital used abroad generates profits for foreign subsidiaries with no foreign direct investment. Plant-specific intangible capital in foreign subsidiaries is expensed abroad, lowering current profits on foreign direct investment (FDI) and increasing future profits. We develop a multicountry general equilibrium model with an essential role for FDI and apply the same methodology as the BEA to construct economic statistics for the model economy. We estimate that mismeasurement of intangible investments accounts for over 60 percent of the difference in BEA returns.
A framework is developed with what we call technology capital. A country is a measure of locations. Absent policy constraints, a firm owning a unit of technology capital can produce the composite output good using the unit of technology capital at as many locations as it chooses. But it can operate only one operation at a given location, so the number of locations is what constrains the number of units it operates using this unit of technology capital. If it has two units of technology capital, it can operate twice as many operations at every location. In this paper, aggregation is carried out and the aggregate production functions for the countries are derived. Our framework interacts well with the national accounts in the same way as does the neoclassical growth model. It also interacts well with the international accounts. There are constant returns to scale, and therefore no monopoly rents. Yet there are gains to being economically integrated. In the framework, a country’s openness is measured by the effect of its policies on the productivity of foreign operations. Our analysis indicates that there are large gains to this openness.
The central finding of the recent structural vector autoregression (SVAR) literature with a differenced specification of hours is that technology shocks lead to a fall in hours. Researchers have used this finding to argue that real business cycle models are unpromising. We subject this SVAR specification to a natural economic test and show that when applied to data from a multiple-shock business cycle model, the procedure incorrectly concludes that the model could not have generated the data as long as demand shocks play a nontrivial role. We also test another popular specification, which uses the level of hours, and show that with nontrivial demand shocks, it cannot distinguish between real business cycle models and sticky price models. The crux of the problem for both SVAR specifications is that available data require a VAR with a small number of lags and such a VAR is a poor approximation to the model’s VAR.
We make three comparisons relevant for the business cycle accounting approach. We show that in theory, representing the investment wedge as a tax on investment is equivalent to representing this wedge as a tax on capital income as long as the probability distributions over this wedge in the two representations are the same. In practice, convenience dictates that the underlying probability distributions over the investment wedge are different in the two representations. Even so, the quantitative results under the two representations are essentially identical. We also compare our methodology, the CKM methodology, to an alternative one used in Christiano and Davis (2006) and by us in early incarnations of the business cycle accounting approach. We argue that the CKM methodology rests on more secure theoretical foundations. Finally, we show that the results from the VAR-style decomposition of Christiano and Davis reinforce the results of the business cycle decomposition of CKM.
We propose a simple method to help researchers develop quantitative models of economic fluctuations. The method rests on the insight that many models are equivalent to a prototype growth model with time-varying wedges which resemble productivity, labor and investment taxes, and government consumption. Wedges corresponding to these variables—efficiency, labor, investment, and government consumption wedges—are measured and then fed back into the model in order to assess the fraction of various fluctuations they account for. Applying this method to U.S. data for the Great Depression and the 1982 recession reveals that the efficiency and labor wedges together account for essentially all of the fluctuations; the investment wedge plays a decidedly tertiary role, and the government consumption wedge, none. Analyses of the entire postwar period and alternative model specifications support these results. Models with frictions manifested primarily as investment wedges are thus not promising for the study of business cycles. (See Additional Material for a response to Christiano and Davis (2006).)
Real business cycles are recurrent fluctuations in an economy’s incomes, products, and factor inputs—especially labor—that are due to nonmonetary sources. These sources include changes in technology, tax rates and government spending, tastes, government regulation, terms of trade, and energy prices. Most real business cycle (RBC) models are variants or extensions of a neoclassical growth model. One such prototype is introduced. It is then shown how RBC theorists, applying the methodology of Kydland and Prescott (Econometrica 1982), use theory to make predictions about actual time series. Extensions of the prototype model, current issues, and open questions are also discussed.
Expensed investments are expenditures financed by the owners of capital that increase future profits but, by national accounting rules, are treated as an operating expense rather than as a capital expenditure. Sweat investment is financed by worker-owners who allocate time to their business and receive compensation at less than their market rate. Such investments are made with the expectation of realizing capital gains when the business goes public or is sold. But these investments are not included in GDP. Taking into account hours spent building equity while ignoring the output introduces an error in measured productivity and distorts the picture of what is happening in the economy. In this paper, we incorporate expensed and sweat equity in an otherwise standard business cycle model. We use the model to analyze productivity in the United States during the 1990s boom. We find that expensed plus sweat investment was large during this period and critical for understanding the dramatic rise in hours and the modest growth in measured productivity.
We derive the quantitative implications of growth theory for U.S. corporate equity plus net debt over the period 1960–2001. There were large secular movements in corporate equity values relative to GDP, with dramatic declines in the 1970s and dramatic increases starting in the 1980s and continuing throughout the 1990s. During the same period, there was little change in the capital-output ratio or earnings share of output. We ask specifically whether the theory accounts for these observations. We find that it does, with the critical factor being changes in the U.S. tax and regulatory system. We find that the theory also accounts for the even larger movements in U.K. equity values relative to GDP in this period.
In this paper, we show that ignoring corporate intangible investments gives a distorted picture of the post-1990 U.S. economy. In particular, ignoring intangible investments in the late 1990s leads one to conclude that productivity growth was modest, corporate profits were low, and corporate investment was at moderate levels. In fact, the late 1990s was a boom period for productivity growth, corporate profits, and corporate investment.
The main substantive finding of the recent structural vector autoregression literature with a differenced specification of hours (DSVAR) is that technology shocks lead to a fall in hours. Researchers have used these results to argue that business cycle models in which technology shocks lead to a rise in hours should be discarded. We evaluate the DSVAR approach by asking, is the specification derived from this approach misspecified when the data are generated by the very model the literature is trying to discard? We find that it is misspecified. Moreover, this misspecification is so great that it leads to mistaken inferences that are quantitatively large. We show that the other popular specification that uses the level of hours (LSVAR) is also misspecified. We argue that alternative state space approaches, including the business cycle accounting approach, are more fruitful techniques for guiding the development of business cycle theory.
In recent financial crises and in recent theoretical studies of them, abrupt declines in capital inflows, or sudden stops, have been linked with large drops in output. Do sudden stops cause output drops? No, according to a standard equilibrium model in which sudden stops are generated by an abrupt tightening of a country’s collateral constraint on foreign borrowing. In this model, in fact, sudden stops lead to output increases, not decreases. An examination of the quantitative effects of a well-known sudden stop, in Mexico in the mid-1990s, confirms that a drop in output accompanying a sudden stop cannot be accounted for by the sudden stop alone. To generate an output drop during a financial crisis, as other studies have done, the model must include other economic frictions which have negative effects on output large enough to overwhelm the positive effect of the sudden stop.
Gali and Rabanal provide statistical evidence that, in their view, puts into question the real business-cycle paradigm in favor of the sticky-price paradigm. I demonstrate that their statistical procedure is easily misled in that they would reach the same conclusions even if their data had been simulated from an RBC model. I also demonstrate that sticky-price models do a poor job generating U.S.-like business cycles with only shocks to technology, the federal funds rate, and government consumption. This explains why Gali and Rabanal need large unobserved shocks to preferences and to the degree of monopoly power.
With a monetary union in place, many European countries are now debating if and how to coordinate their tax policies. Of particular interest to EU ministers is taxation of mobile factors like capital. Mendoza and Tesar (MT) use a game-theoretic approach to address the question, What is the outcome of tax competition and tax coordination when countries choose the tax on capital income and adjust other tax rates to keep revenues constant? MT predict very large welfare gains (losses) to tax competition for European countries that had high (low) tax rates prior to financial integration. In particular they predict a large gain for the United Kingdom and a large loss for countries in continental Europe. A second finding is that the welfare gains of tax coordination relative to that of tax competition are small. I discuss these findings in light of current policy debates and possible future extensions of this work.
This article describes changes in the number of average weekly hours of market work per person in the United States since World War II. Overall, this number has been roughly constant; for various groups, however, it has shifted dramatically—from males to females, from older people to younger people, and from single- to married-person households. The article provides a detailed look at how the lifetime pattern of work hours has changed since 1950 for different demographic groups. This article also documents several factors that lead to the reallocation of hours worked across groups: increases in relative wages of females to males; technological innovations that shift female labor from the home to the market; increases in Social Security benefits to retired workers; and changes in family structure. The data presented are based on those collected by the U.S. Bureau of the Census during the 1950–2000 decennial censuses.
Economists have offered many theories for the U.S. Great Depression, but no consensus has formed on the main forces behind it. Here we describe and demonstrate a simple methodology for determining which theories are the most promising. We show that a large class of models, including models with various frictions, are equivalent to a prototype growth model with time-varying efficiency, labor, and investment wedges that, at least on face value, look like time-varying productivity, labor taxes, and investment taxes. We use U.S. data to measure these wedges, feed them back into the prototype growth model, and assess the fraction of the fluctuations in 1929–39 that they account for. We find that the efficiency and labor wedges account for essentially all of the decline and subsequent recovery. Investment wedges play, at best, a minor role.
Many stock market analysts think that in 1929, at the time of the crash, stocks were overvalued. Irving Fisher argued just before the crash that fundamentals were strong and the stock market was undervalued. In this paper, we use growth theory to estimate the fundamental value of corporate equity and compare it to actual stock valuations. Our estimate is based on values of productive corporate capital, both tangible and intangible, and tax rates on corporate income and distributions. The evidence strongly suggests that Fisher was right. Even at the 1929 peak, stocks were undervalued relative to the prediction of theory.
Mehra and Prescott (1985) found the difference between average equity and debt returns puzzling because it was too large to be a premium for bearing nondiversifiable aggregate risk. Here, we re-examine this puzzle, taking into account some factors ignored by Mehra and Prescott—taxes, regulatory constraints, and diversification costs—and focusing on long-term rather than short-term savings instruments. Accounting for these factors, we find the difference between average equity and debt returns during peacetime in the last century is less than 1 percent, with the average real equity return somewhat under 5 percent, and the average real debt return almost 4 percent. As theory predicts, the real return on debt has been close to the 4 percent average after-tax real return on capital. Similarly, as theory predicts, the real return on equity is equal to the after-tax real return on capital plus a modest premium for bearing nondiversifiable aggregate risk.
The central puzzle in international business cycles is that fluctuations in real exchange rates are volatile and persistent. We quantity the popular story for real exchange rate fluctuations: they are generated by monetary shocks interacting with sticky goods prices. If prices are held fixed for at least one year, risk aversion is high, and preferences are separable in leisure, then real exchanage rates generated by the model are as volatile as in the data and quite persistent, but less so than in the data. The main discrepancy between the model and the data, the consumption—real exchange rate anomaly, is that the model generates a high correlation between real exchange rates and the ratio of consumption across countries, while the data show no clear pattern between these variables.
U.S. stock prices have increased much faster than gross domestic product GDP) in the postwar period. Between 1962 and 2000, corporate equity value relative to GDP nearly doubled. In this paper, we determine what standard growth theory says the equity value should be in 1962 and 2000, the two years for which our steady-state assumption is a reasonable one. We find that the actual valuations were close to the theoretical predictions in both years. The reason for the large run-up in equity value relative to GDP is that the average tax rate on dividends fell dramatically between 1962 and 2000. We also find that, given legal constraints that effectively prohibited the holding of stocks as reserves for pension plans, there is no equity premium puzzle in the postwar period. The average returns on debt and equity are as theory predicts.
The value of U.S. corporate equity in the first half of 2000 was close to 1.8 times U.S. gross national product (GNP). Some stock market analysts have argued that the market is overvalued at this level. We use a growth model with an explicit corporate sector and find that the market is correctly valued. In theory, the market value of equity plus debt liabilities should equal the value of productive assets plus debt assets. Since the net value of debt is currently low, the market value of equity should be approximately equal to the market value of productive assets. We find that the market value of productive assets, including both tangible and intangible assets and assets used outside the country by U.S. subsidiaries, is currently about 1.8 times GNP, the same as the market value of equity.
This study demonstrates that the U.S. equity premium has declined significantly during the last three decades. The study calculates the equity premium using a variation of a formula in the classic Gordon stock valuation model. The calculation includes the bond yield, the stock dividend yield, and the expected dividend growth rate, which in this formulation can change over time. The study calculates the premium for several measures of the aggregate U.S. stock portfolio and several assumptions about bond yields and stock dividends and gets basically the same result. The premium averaged about 7 percentage points during 1926–70 and only about 0.7 of a percentage point after that. This result is shown to be reasonable by demonstrating the roughly equal returns that investments in stocks and consol bonds of the same duration would have earned between 1982 and 1999, years when the equity premium is estimated to have been zero.
In this paper, I characterize equilibria for a sticky-price model in which Federal Reserve policy is an interest-rate rule similar to that described in Taylor (1993). For standard preferences and technologies used in the literature, the model predicts that the nominal interest rate is negatively serially correlated, and that shocks to interest rates imply a potentially large but short-lived response in output. Shocks to government spending and technology lead to persistent changes in output but the percentage change in output is predicted to be smaller than the percentage changes in spending or technology. I compare the model’s predictions to data using innovations backed out from estimated processes for interest rates, government spending, and technology shocks. These comparisons confirm the theoretical findings. In response to observed changes in government spending and technology, the model predicts a path for output that is much smoother than the data and much smoother than that predicted by non-sticky price models.
Most models of aggregate economic activity, like the standard neoclassical growth model, ignore the fact that equipment and structures are maintained and repaired. Once physical capital is purchased in these models, there are typically no more decisions made regarding its use. The theme of this article is that there is evidence to suggest that incorporating expenditures on the maintenance and repair of physical capital into models of aggregate economic activity will change the quantitative answers to some key questions that have been addressed with these models. This evidence is primarily from a little-used economywide survey in Canada. The survey shows that the activity of maintaining and repairing equipment and structures is an activity that is generally both large relative to investment and a substitute for investment to some extent—and to a large extent during some episodes.
This article describes changes in the number of average weekly hours of market work per person in the United States since World War II. Overall, this number has been roughly constant; for various groups, however, it has shifted dramatically—from males to females, from older people to younger people, and from single- to married-person households. The article provides a unique look at how the lifetime pattern of work hours has changed since 1950 for different demographic groups. The article also documents several factors that may be related to the changes in hours worked: simultaneous changes in Social Security benefits, fertility rates, and family structure. The data presented are based on those collected by the U.S. Bureau of the Census during the 1950–90 decennial censuses.
The conventional wisdom is that monetary shocks interact with sticky goods prices to generate the observed volatility and persistence in real exchange rates. We investigate this conventional wisdom in a quantitative model with sticky prices. We find that with preferences as in the real business cycle literature, irrespective of the length of price stickiness, the model necessarily produces only a fraction of the volatility in exchange rates seen in the data. With preferences which are separable in leisure, the model can produce the observed volatility in exchange rates. We also show that long stickiness is necessary to generate the observed persistence. In addition, we show that making asset markets incomplete does not measurably increase either the volatility or persistence of real exchange rates.
AK growth models predict that permanent changes in government policies affecting investment rates should lead to permanent changes in a country’s GDP growth. Charles Jones (1995) sees no evidence for this prediction in data for 15 OECD countries after World War II: rates of investment, especially for equipment, have risen while GDP growth rates have not. This article provides evidence supporting the AK models’ prediction. Data back to the 19th century show a strong positive relationship between investment rates and growth rates and short-lived deviations from trends. A strong positive relationship also exists between average rates of investment and growth in postwar data for a large cross-section of countries. To account for the short-run deviations in rates that Jones highlights, the model he used is extended to allow policies to affect not only investment/output ratios but also capital/output ratios and labor/leisure decisions.
This chapter reviews the literature that tries to explain the disparity and variation of GDP per worker and GDP per capita across countries and across time. There are many potential explanations for the different patterns of development across countries, including differences in luck, raw materials, geography, preferences, and economic policies. We focus on differences in economic policies and ask to what extent can differences in policies across countries account for the observed variability in income levels and their growth rates. We review estimates for a wide range of policy variables. In many cases, the magnitude of the estimates is under debate. Estimates found by running cross-sectional growth regressions are sensitive to which variables are included as explanatory variables. Estimates found using quantitative theory depend in critical ways on values of parameters and measures of factor inputs for which there is little consensus. In this chapter, we review the ongoing debates of the literature and the progress that has been made thus far.
I argue that low-frequency movements in U.S. base velocity are well explained by standard models of money demand. The model of Gordon, Leeper, and Zha is not standard because they assume a very high interest elasticity. The positive conclusion that they reach about the model’s ability to mimic movements in velocity necessarily implies that predicted movements in interest rates are too smooth.
We construct a quantitative equilibrium model with price setting and use it to ask whether with staggered price setting monetary shocks can generate business cycle fluctuations. These fluctuations include persistent output fluctuations along with the other defining features of business cycles, like volatile investment and smooth consumption. We assume that prices are exogenously sticky for a short period of time. Persistent output fluctuations require endogenous price stickiness in the sense that firms choose not to change prices very much when they can do so. We find that for a wide range of parameter values the amount of endogenous stickiness is small. As a result, we find that in a standard quantitative business cycle model staggered price setting, by itself, does not generate business cycle fluctuations.
We find that the welfare gains to being at the optimum quantity of debt rather than the current U.S. level are small, and, therefore, concerns regarding the high level of debt in the U.S. economy may be misplaced. This finding is based on a model of a large number of infinitely-lived households whose saving behavior is influenced by precautionary saving motives and borrowing constraints. This model incorporates a different role for government debt than is found in standard models, and it captures different cost-benefit trade-offs. On the benefit side, government debt enhances the liquidity of households by providing an additional means of smoothing consumption and by effectively loosening borrowing constraints. On the cost side, the implied taxes have adverse wealth distribution and incentive effects. In addition, government debt crowds out capital via higher interest rates and lowers per capita consumption.
We ask what fraction of the variation in incomes across countries can be accounted for by investment distortions. In our neoclassical growth model the relative price of investment to consumption is a good measure of the distortions. Using data on relative prices we estimate a stochastic process for distortions and compare the resulting variance of incomes in the model to that in the data. We find that the variation of incomes in the model is roughly 4/5 of the variability of incomes in the data. Our model does well in accounting for 6 key regularities on income and investment in the data.
The paper itself is followed by three appendices: Appendix 1 describing the log-likelihood function, Appendix 2 describing the construction of labor share of income associated with the production of consumption and investment goods, and the Data Appendix.
This article describes the academic debate about the usefulness of the capital asset pricing model (the CAPM) developed by Sharpe and Lintner. First the article describes the data the model is meant to explain—the historical average returns for various types of assets over long time periods. Then the article develops a version of the CAPM and describes how it measures the risk of investing in particular assets. Finally the article describes the results of competing studies of the model’s validity. Included are studies that support the CAPM (Black; Black, Jensen, and Scholes; Fama and MacBeth), studies that challenge it (Banz; Fama and French), and studies that challenge those challenges (Amihud, Christensen, and Mendelson; Black; Breen and Korajczyk; Jagannathan and Wang; Kothari, Shanken, and Sloan). The article concludes by suggesting that, while academic debate continues, the CAPM may still be useful for those interested in the long run.
This paper catalogues formulas that are useful for estimating dynamic linear economic models. We describe algorithms for computing equilibria of an economic model and for recursively computing a Gaussian likelihood function and its gradient with respect to parameters. We apply these methods to several example economies.
We estimate a dynamic general equilibrium model of the U.S. economy that includes an explicit household production sector and stochastic fiscal variables. We use our estimates to investigate two issues. First, we analyze how well the model accounts for aggregate fluctuations. We find that household production has a significant impact and reject a nested specification in which changes in the home production technology do not matter for market variables. Second, we study the effects of some simple fiscal policy experiments and show that the model generates different predictions for the effects of tax changes than similar models without home production.
We describe a model for calculating the optimal quantity of debt and then apply it to the U.S. economy. The model consists of a large number of infinitely-lived households whose saving behavior is influenced by precautionary saving motives and borrowing constraints. This model incorporates a different role for government debt than the standard representative agent growth model and captures different trade-offs between the benefits and costs of varying its level. Government debt enhances the liquidity of households by providing additional assets for smoothing consumption (in addition to claims to capital) and effectively loosening borrowing constraints. By raising the interest rate, government debt makes assets less costly to hold and more effective in smoothing consumption. However, the implied taxes have wealth distribution, incentive, and insurance effects. Further, government debt crowds out capital (via higher interest rates) and lowers per capita consumption. Our quantitative analysis suggests that the crowding out effect is decisive for welfare. We also describe variations of the model which permit endogenous growth. It turns out that even with lump sum taxes and inelastic labor, government debt as well as government consumption have growth rate effects, thereby implying large welfare gains from reducing the level of debt.
This article reports the recent progress made by researchers trying to build business cycle models that can reliably reproduce aggregate U.S. time series. The article first describes some features of the U.S. data that the models are meant to reproduce. Then it describes a version of the standard business cycle model, along with the indivisible labor extension of that model, both of which assume that fluctuations in economic activity are caused only by shocks to technology. Finally, it describes a version of recent other extensions which assume that shocks to fiscal variables also contribute to the fluctuations. Adding fiscal shocks to standard business cycle models is shown to significantly improve their ability to mimic some of the data.
This paper catalogues formulas that are useful for estimating dynamic linear economic models. We describe algorithms for computing equilibria of an economic model and for recursively computing a Gaussian likelihood function and its gradient with respect to parameters. We display an application to Rosen, Murphy, and Scheinkman’s (1994) model of cattle cycles.
We estimate a dynamic general equilibrium model of the U.S. economy that includes an explicit household production sector. We use these estimates to investigate two issues. First, we analyze how well the model accounts for aggregate fluctuations. Second, we use the model to study the effects of fiscal policy. We find household production has a significant impact, and reject a nested specification in which changes in the home production technology do not matter for market variables. The model generates very different predictions for the effects of tax changes than similar models without home production.
Since it is the dominant paradigm of the business cycle and growth literatures, the stochastic growth model has been used to test the performance of alternative numerical methods. This paper applies the finite element method to this example. I show that the method is easy to apply and, for examples such as the stochastic growth method, gives accurate solutions within a second or two on a desktop computer. I also show how inequality constraints can be handled by redefining the optimization problem with penalty functions.
This paper develops a model of competitive economy which is used to study the effect that distortionary taxes have on the business cycle and on agents’ welfare. In the presence of distortions, the equilibria are not Pareto optimal and standard computational techniques cannot be used. Instead, methods that take into account the presence of distorting taxes are applied. Maximum likelihood estimates of taste, technology and policy parameters from U.S. post-war time series are used to obtain several results. I find that a significant portion of the variance of the aggregate consumption, output, hours worked, capital stock, and investment can be attributed to the factor tax and government spending processes. Also, I compute the deadweight loss due to alternative tax changes and compare these estimates to others in the literature. Specification of taxes as constant versus state-contingent can have a significant effect on the results.