We document properties of business cycles in ten countries over the last hundred years, contrasting the behavior of real quantities with that of the price level and the stock of money. Although the magnitude of output fluctuations has varied across countries and periods, relations among variables have been remarkably uniform. Consumption has generally been about as variable as output, and investment substantially more variable, and both have been strongly procyclical. The trade balance has generally been countercyclical. The exception to this regularity is government purchases, which exhibit no systematic cyclical tendency. With respect to the size of output fluctuations, standard deviations are largest between the two world wars. In some countries (notably Australia and Canada) they are substantially larger prior to World War I than after World War II, but in others (notably Japan and the United Kingdom) there is little difference between these periods. Properties of price levels, in contrast, exhibit striking differences between periods. Inflation rates are more persistent after World War II than before, and price level fluctuations are typically procyclical before World War II, countercyclical afterward. We find no general tendency toward increased persistence in money growth rates, but find that fluctuations in money are less highly correlated with output in the postwar period.

We consider a dynamic, stochastic equilibrium business cycle model which is augmented to reflect seasonal shifts in preferences, technology, and government purchases. Our estimated parameterization implies implausibly large seasonal variation in the state of technology: rising at an annual rate of 24% in the fourth quarter and falling at an annual rate of 28% in the first quarter. Furthermore, our findings indicate that variation in the state of technology of this magnitude is required if the model is to explain the main features of the seasonal cycle.

An economic experiment consists of the act of placing people in an environment desired by the experimenter, who then records the time paths of their economic behavior. Performing experiments that use actual people at the level of national economies is obviously not practical, but constructing a model economy and computing the economic behavior of the model’s people is. We refer to such experiments as computational experiments because the economic behavior of the model’s people is computed. In this essay, we specify the steps in designing a computational experiment to address some well posed quantitative question. We emphasize that the computational experiment is an econometric tool used in the task of deriving the quantitative implications of theory.

I argue that Farmer and Guo's one-sector real business cycle model with indeterminacy and sunspots fails empirically and that its failure is inherent in the logic of the model taken together with some simple labor market facts.

We study a one-sector growth model which is standard except for the presence of an externality in the production function. The set of competitive equilibria is large. It includes constant equilibria, sunspot equilibria, cyclical and chaotic equilibria, and equilibria with deterministic or stochastic regime switching. The efficient allocation is characterized by constant employment and a constant growth rate. We identify an income tax-subsidy schedule that supports the efficient allocation as the unique equilibrium outcome. That schedule has two properties: (i) it specifies the tax rate to be an increasing function of aggregate employment, and (ii) earnings are subsidized when aggregate employment is at its efficient level. The first feature eliminates inefficient, fluctuating equilibria, while the second induces agents to internalize the externality.

An overlapping generations model is developed that contains labor markets in which adverse selection problems arise. As a response to these problems, quantity rationing of labor occurs. In addition, the model is capable of generating (a) random employment and prices despite the absence of underlying uncertainty in equilibrium; (b) a statistical (nondegenerate) Phillips curve; (c) procyclical movements in productivity; (d) correlations between aggregate demand and unemployment (and output); (e) an absence of correlation between unemployment (employment) and real wages. In addition, the Phillips curve obtained typically has the "correct" slope. Finally, the model reconciles the theoretical importance and observed unimportance of intertemporal substitution effects, and explains why price level stability may be a poor policy objective.

A model of a "real" business cycle is produced in which labor market participants possess private information. A class of economies is considered in which interesting cycles cannot arise without private information. A methodology adapted from Kydland and Prescott (1982) is then employed to show that models based on private information can empirically confront salient features of postwar U.S. business cycles. Moreover, this can be done in a way which is consistent with existing microeconomic evidence on wages and labor supply. Finally, it is shown that the important features of the model related to private information are fairly general.

Unit root tests against trend break alternatives are based on the premise that the dating of the trend breaks coincides with major economic events with permanent effects on economic activity, such as wars and depressions. Standard economic theory, however, suggests that these events have large transitory, rather than permanent, effects on economic activity. Conventional unit root tests against trend break alternatives based on linear ARIMA models do not capture these transitory effects and can result in severely distorted inference. We quantify the size distortions for a simple model in which the effects of wars and depressions can reasonably be interpreted as transitory. Monte Carlo simulations show that in moderate samples, the widely used Zivot-Andrews (1992) test mistakes transitory dynamics for trend breaks with high probability. We conclude that these tests should be used only if there are no plausible economic explanations for apparent trend breaks in the data.

Many economists have worried about changes in the demand for money, since money demand shocks can affect output variability and have implications for monetary policy. This paper studies the theoretical implications of changes in money demand for the nonneutrality of money in the limited participation (liquidity) model and the predetermined (sticky) price model. In the liquidity model, we find that an important connection exists between the nonneutrality of money and the relative money demands of households and firms. This model predicts that the real effect of a money shock rose by 100 percent between 1952 and 1980, and subsequently declined 65 percent. In contrast, we find that the nonneutrality of money in the sticky price model is invariant to changes in money demands or other monetary factors. Several researchers have concluded from VAR analyses that the effects of money shock over time are roughly stable. This view is consistent with the predictions of the sticky price model, but is harder to reconcile with the specific pattern of time variation predicted by the liquidity model.

The neoclassical growth model studied in Kydland and Prescott [1982] is modified to permit the capital utilization rate to vary. The effect of this modification is to increase the amplitude of the aggregate fluctuations predicted by theory as the equilibrium response to technological shocks. If following Solow [1957], the changes in output not accounted for by changes in the labor and tangible capital inputs are interpreted as being the technology shocks, the statistical properties of the fluctuations in the post-war United States economy are close in magintude and nature to those predicted by theory.

The neoclassical growth model studied in Kydland and Prescott [1982] is modified to permit the capital utilization rate to vary. The effect of this modification is to increase the amplitude of the aggregate fluctuations predicted by theory as the equilibrium response to technological shocks. If following Solow [1957], the changes in output not accounted for by changes in the labor and tangible capital inputs are interpreted as being the technology shocks, the statistical properties of the fluctuations in the post-war United States economy are close in magintude and nature to those predicted by theory.

We present a class of convex endogenous growth models and analyze their performance in terms of both growth and business cycle criteria. The models we study have close analogs in the real business cycle literature. We interpret the exogenous growth rate of productivity as an endogenous growth rate of human capital. This perspective allows us to compare the strengths of the two classes of models.

To highlight the mechanism that gives endogenous growth models the ability to improve upon their exogenous growth relatives, we study models that are symmetric in terms of human and physical capital formation—our two engines of growth. More precisely, we analyze models in which the technology used to produce human capital is identical to the technologies used to produce consumption and investment goods and in which the technology shocks in the two sectors are perfectly correlated.

We introduce two modifications into the standard real business cycle model: habit persistence preferences and limitations on intersectoral factor mobility. The resulting model is consistent with the observed mean equity premium, mean risk free rate and Sharpe ratio on equity. The model does roughly as well as the standard real business cycle model with respect to standard measures. On four other dimensions its business cycle implications represent a substantial improvement. It accounts for (i) persistence in output, (ii) the observation that employment across different sectors moves together over the business cycle, (iii) the evidence of ‘excess sensitivity’ of consumption growth to output growth, and (iv) the ‘inverted leading indicator property of interest rates,’ that high interest rates are negatively correlated with future output.

Between 1929 and 1933, real output per adult fell over 30 percent and total factor productivity fell 18 percent. This productivity decrease is much larger than expected from just extrapolating the productivity decrease that typically occurs during recessions. This paper evaluates what factors may have caused this large decrease, including unmeasured factor utilization, changes in the composition of production, and increasing returns. I find that these factors combined explain less than one-third of the 18 percent decrease, and I conclude that the productivity decrease during the Great Depression remains a puzzle.

Chile and Mexico experienced severe economic crises in the early 1980s. This paper analyzes four possible explanations for why Chile recovered much faster than did Mexico. Comparing data from the two countries allows us to rule out a monetarist explanation, an explanation based on falls in real wages and real exchange rates, and a debt overhang explanation. Using growth accounting, a calibrated growth model, and economic theory, we conclude that the crucial difference between the two countries was the earlier policy reforms in Chile that generated faster productivity growth. The most crucial of these reforms were in banking and bankruptcy procedures.

Previous research has suggested that discrete and occasional plant-level capital adjustments have significant aggregate implications. In particular, it has been argued that changes in plants’ willingness to invest in response to aggregate shocks can at times generate large movements in total investment demand. In this study, I re-assess these predictions in a general equilibrium environment. Specifically, assuming nonconvex costs of capital adjustment, I derive generalized (S,s) adjustment rules yielding lumpy plant-level investment within an otherwise standard equilibrium business cycle model. In contrast to previous partial equilibrium analyses, model results reveal that the aggregate effects of lumpy investment are negligible. In general equilibrium, households’ preference for relatively smooth consumption profiles offsets changes in aggregate investment demand implied by the introduction of lumpy plant-level investment. As a result, adjustments in wages and interest rates yield quantity dynamics that are virtually indistinguishable from the standard model.

Recent empirical analysis has found nonlinearities to be important in understanding aggregated investment. Using an equilibrium business cycle model, we search for aggregate nonlinearities arising from the introduction of nonconvex capital adjustment costs. We find that, while such costs lead to nontrivial nonlinearities in aggregate investment demand, equilibrium investment is effectively unchanged. Our finding, based on a model in which aggregate fluctuations arise through exogenous changes in total factor productivity, is robust to the introduction of shocks to the relative price of investment goods.

We show how to decentralize constrained efficient allocations that arise from enforcement constraints between sovereign nations. In a pure exchange economy, these allocations can be decentralized with private agents acting competitively and taking as given government default decisions on foreign debt. In an economy with capital, these allocations can be decentralized if the government can tax capital income as well as default on foreign debt. The tax on capital income is needed to make private agents internalize a subtle externality. The decisions of the government can arise as an equilibrium of a dynamic game between governments.

Financial crises are widely argued to be due to herd behavior. Yet recently developed models of herd behavior have been subjected to two critiques which seem to make them inapplicable to financial crises. Herds disappear from these models if two of their unappealing assumptions are modified: if their zero-one investment decisions are made continuous and if their investors are allowed to trade assets with market-determined prices. However, both critiques are overturned—herds reappear in these models—once another of their unappealing assumptions is modified: if, instead of moving in a prespecified order, investors can move whenever they choose.

We examine deviations from trend of net exports and other components of GNP for the United States and attempt to build models consistent with their behavior. The most striking fact is that net exports have consistently been countercyclical. We show, first, that dynamic pure-exchange models can only produce a negative correlation between net exports and GNP if the variance of consumption exceeds that of output. In (he United Slates it does not, so this class of models cannot explain observed comovements between output and trade. We then examine government spending and nontraded goods as potential remedies, but show that their behavior is either inconsistent with the data or can be made consistent with any pattern of comovements. The most promising model introduces production and capital formation. Fluctuations are driven by country-specific productivity shocks, in which high productivity domestically leads to high domestic investment and a deficit in the balance of trade. This theory also receives support from the large negative covariance between net exports and investment in American data.

We examine deviations from trend of net exports and other components of GNP for the United States and attempt to build models consistent with their behavior. The most striking fact is that net exports have consistently been countercyclical. We show, first, that dynamic pure-exchange models can only produce a negative correlation between net exports and GNP if the variance of consumption exceeds that of output. In (he United Slates it does not, so this class of models cannot explain observed comovements between output and trade. We then examine government spending and nontraded goods as potential remedies, but show that their behavior is either inconsistent with the data or can be made consistent with any pattern of comovements. The most promising model introduces production and capital formation. Fluctuations are driven by country-specific productivity shocks, in which high productivity domestically leads to high domestic investment and a deficit in the balance of trade. This theory also receives support from the large negative covariance between net exports and investment in American data.

We develop an equilibrium business cycle model where producers of final goods pursue generalized (S,s) inventory policies with respect to intermediate goods due to nonconvex factor adjustment costs. When calibrated to reproduce the average inventory-to-sales ratio in postwar U.S. data, our model explains over half of the cyclical variability of inventory investment. Moreover, inventory accumulation is strongly procyclical, and production is more volatile than sales, as in the data.

The comovement between inventory investment and final sales is often interpreted as evidence that inventories amplify aggregate fluctuations. In contrast, our model economy exhibits a business cycle similar to that of a comparable benchmark without inventories, though we do observe somewhat higher variability in employment, and lower variability in consumption and investment. Thus, our equilibrium analysis reveals that the presence of inventories does not substantially raise the cyclical variability of production, because it dampens movements in final sales.

Are deflation and depression empirically linked? No, concludes a broad historical study of inflation and real output growth rates. Deflation and depression do seem to have been linked during the 1930s. But in the rest of the data for 17 countries and more than 100 years, there is virtually no evidence of such a link.

We find that in a sample of emerging economies business cycles are more volatile than in developed ones, real interest rates are countercyclical and lead the cycle, consumption is more volatile than output and net exports are strongly countercyclical. We present a model of a small open economy, where the real interest rate is decomposed in an international rate and a country risk component. Country risk is affected by fundamental shocks but, through the presence of working capital, also amplifies the effects of those shocks. The model generates business cycles consistent with Argentine data. Eliminating country risk lowers Argentine output volatility by 27% while stabilizing international rates lowers it by less than 3%.

We derive the empirical implications of a popular class of international macroeconomic models. The real economy is a stochastic exchange model with complete markets. A standard result is that cross-country risk sharing implies perfect correlation between consumption paths across countries. With mild restrictions on the endowment process ii also implies a positive correlation between net exports and output in every country. We introduce money using cash-in-advance constraints and show that the implications for real variables carry over into the monetary economy. These dichotomy and neutrality propositions generalize those in the literature to stochastic environments with heterogeneous agents, and do not require the cash-in-advance constraint to bind in every state. They imply that any correlation between the nominal exchange rate and the balance of trade can be made consistent with the theory.

We derive the empirical implications of a popular class of international macroeconomic models. The real economy is a stochastic exchange model with complete markets. A standard result is that cross-country risk sharing implies perfect correlation between consumption paths across countries. With mild restrictions on the endowment process ii also implies a positive correlation between net exports and output in every country. We introduce money using cash-in-advance constraints and show that the implications for real variables carry over into the monetary economy. These dichotomy and neutrality propositions generalize those in the literature to stochastic environments with heterogeneous agents, and do not require the cash-in-advance constraint to bind in every state. They imply that any correlation between the nominal exchange rate and the balance of trade can be made consistent with the theory.

We solve equilibrium models of lumpy investment wherein establishments face persistent shocks to common and plant-specific productivity. Nonconvex adjustment costs lead plants to pursue generalized (S, s) rules with respect to capital; thus, their investments are lumpy. In partial equilibrium, this yields substantial skewness and kurtosis in aggregate investment, though, with differences in plant-level productivity, these nonlinearities are far less pronounced. Moreover, nonconvex costs, like quadratic adjustment costs, increase the persistence of aggregate investment, yielding a better match with the data. In general equilibrium, aggregate nonlinearities disappear, and investment rates are very persistent, regardless of adjustment costs. While the aggregate implications of lumpy investment change substantially in equilibrium, the inclusion of fixed costs or idiosyncratic shocks makes the average distribution of plant investment rates largely invariant to market-clearing movements in real wages and interest rates. Nonetheless, we find that understanding the dynamics of plant-level investment requires general equilibrium analysis.

A two country overlapping generations model is constructed, in which financial intermediation arises endogenously as an incentive compatible means of economizing on monitoring costs. Because of international credit markets. The model is used to generate the existence of transaction costs, money markets in the two countries are segmented and investors have differential access to predictions concerning the role of international intermediation in economic development, and to examine the nature of business cycle phenomena across alternative exchange rate regimes. Disturbances are propagated by a credit allocation mechanism, which also lends a novel flavor to the model's long run properties.

The fiscal year and the calendar year coincide for a large fraction of firms traded in the New York and American Stock Exchanges. It is therefore possible that part of the large positive abnormal return earned by stocks as a group during the first week of trading in January may be due to temporal resolution of uncertainty accompanying the end of the fiscal year. We study this hypothesis by examining whether stocks of firms with fiscal years ending in months other than December also realize positive abnormal returns, following the end of their fiscal years. We find that there are no excess returns for such firms in the first five trading days following the end of the fiscal year.

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.

The common approach to evaluating a model in the structural VAR literature is to compare the impulse responses from structural VARs run on the data to the theoretical impulse responses from the model. The Sims-Cogley-Nason approach instead compares the structural VARs run on the data to identical structural VARs run on data from the model of the same length as the actual data. Chari, Kehoe, and McGrattan (2006) argue that the inappropriate comparison made by the common approach is the root of the problems in the SVAR literature. In practice, the problems can be solved simply. Switching from the common approach to the Sims-Cogley-Nason ap-proach basically involves changing a few lines of computer code and a few lines of text. This switch will vastly increase the value of the structural VAR literature for economic theory.

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 investigate the consequences of demographic change for business cycle analysis. We find that changes in the age composition of the labor force account for a significant fraction of the variation in business cycle volatility observed in the U.S. and other G7 economies. During the postwar period, these countries experienced dramatic demographic change, although details regarding extent and timing differ from place to place. Using panel-data methods, we exploit this variation to show that the age composition of the workforce has a large and statistically significant effect on cyclical volatility. We conclude by relating these findings to the recent decline in U.S. business cycle volatility. Using both simple accounting exercises and a quantitative general equilibrium model, we find that demographic change accounts for a significant part of this moderation.

Robert Solow has criticized our 2006 Journal of Economic Perspectives essay describing “Modern Macroeconomics in Practice.” Solow eloquently voices the commonly heard complaint that too much macroeconomic work today starts with a model with a single type of agent. We argue that modern macroeconomics may not end too far from where Solow prefers. He is also critical of how modern macroeconomists use data to construct models. Specifically, he seems to think that calibration is the only way that our models encounter data. To the contrary, we argue that modern macroeconomics uses a wide variety of empirical methods and that this big-tent approach has served macroeconomics well. Solow also questions our claim that modern macroeconomics is firmly grounded in economic theory. We disagree and explain why.

This paper is a primer on the great depressions methodology developed by Cole and Ohanian (1999, 2007) and Kehoe and Prescott (2002, 2007). We use growth accounting and simple dynamic general equilibrium models to study the depression that occurred in Finland in the early 1990s. We find that the sharp drop in real GDP over the period 1990–93 was driven by a combination of a drop in total factor productivity (TFP) during 1990–92 and of increases in taxes on labor and consumption and increases in government consumption during 1989–94, which drove down hours worked in Finland. We attempt to endogenize the drop in TFP in variants of the model with an investment sector and with terms-of-trade shocks but are unsuccessful.

Recent studies say prices change about every four months. Economists have interpreted this high frequency as evidence against the importance of sticky prices for the real effects of monetary policy. Theory implies that this interpretation is correct if most price changes are regular, but not if most are temporary, as in the data. Temporary changes have a striking feature: after such a change, the nominal price tends to return exactly to its preexisting level. We study versions of Calvo and menu cost models that replicate this feature. Both models predict that the degree of aggregate price stickiness is determined mostly by the frequency of regular price changes, not by the combined frequency of temporary and regular price changes. Since regular prices are sticky in the data, the models predict a substantial degree of aggregate price stickiness even though micro prices change frequently. In particular, the aggregate price level in our models is as sticky as in standard models in which micro prices change about once a year. In this sense, prices are sticky after all.

Three of the arguments made by Temin (2008) in his review of Great Depressions of the Twentieth Century are demonstrably wrong: that the treatment of the data in the volume is cursory; that the definition of great depressions is too general and, in particular, groups slow growth experiences in Latin America in the 1980s with far more severe great depressions in Europe in the 1930s; and that the book is an advertisement for the real business cycle methodology. Without these three arguments — which are the results of obvious conceptual and arithmetical errors, including copying the wrong column of data from a source — his review says little more than that he does not think it appropriate to apply our dynamic general equilibrium methodology to the study of great depressions, and he does not like the conclusion that we draw: that a successful model of a great depression needs to be able to account for the effects of government policy on productivity.

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.

The U.S. Great Recession featured a large decline in output and labor, tighter financial conditions, and a large increase in firm growth dispersion. We build a model in which increased volatility at the firm level generates a downturn and worsened credit conditions. The key idea is that hiring inputs is risky because financial frictions limit firms' ability to insure against shocks. An increase in volatility induces firms to reduce their inputs to reduce such risk. Out model can generate most of the decline in output and labor in the Great Recession and the observed increase in firms' interest rate spreads.

This paper studies the nature of business cycle variation in individual earnings risk using a confidential dataset from the U.S. Social Security Administration, which contains (uncapped) earnings histories for millions of individuals. The base sample is a nationally representative panel containing 10 percent of all U.S. males from 1978 to 2010. We use these data to decompose individual earnings growth during recessions into “between-group” and “within-group” components. We begin with the behavior of within-group shocks. Contrary to past research, we do not find the variance of idiosyncratic earnings shocks to be countercyclical. Instead, it is the left-skewness of shocks that is strongly countercyclical. That is, during recessions, the upper end of the shock distribution collapses—large upward earnings movements become less likely—whereas the bottom end expands—large drops in earnings become more likely. Thus, while the dispersion of shocks does not increase, shocks become more left-skewed and, hence, risky during recessions. Second, to study between-group differences, we group individuals based on several observable characteristics at the time a recession hits. One of these characteristics—the average earnings of an individual at the beginning of a business cycle episode—proves to be an especially good predictor of fortunes during a recession: prime-age workers that enter a recession with high average earnings suffer substantially less compared with those who enter with low average earnings (which is not the case during expansions). Finally, we find that the cyclical nature of earnings risk is dramatically different for the top 1 percent compared with all other individuals—even relative to those in the top 2 to 5 percent.

This technical appendix supports "Liquidity Effects, Monetary Policy, and the Business Cycle" in Journal of Money, Credit and Banking (November 1995, Vol. 27, No. 4, Pt. 1, pp. 1113-1136), https://doi.org/10.2307/2077793.

We build a variation of the neoclassical growth model in which financial shocks to households or wealth shocks (in the sense of wealth destruction) generate recessions. Two standard ingredients that are necessary are (1) the existence of adjustment costs that make the expansion of the tradable goods sector difficult and (2) the existence of some frictions in the labor market that prevent enormous reductions in real wages (Nash bargaining in Mortensen-Pissarides labor markets is enough). We pose a new ingredient that greatly magnifies the recession: a reduction in consumption expenditures reduces measured productivity, while technology is unchanged due to reduced utilization of production capacity. Our model provides a novel, quantitative theory of the current recessions in southern Europe.

Building on the Merton (1974) and Leland (1994) structural models of credit risk, we develop a simple, transparent, and robust method for measuring the financial soundness of individual firms using data on their equity volatility. We use this method to retrace quantitatively the history of firms’ financial soundness during U.S. business cycles over most of the last century. We highlight three main findings. First, the three worst recessions between 1926 and 2012 coincided with insolvency crises, but other recessions did not. Second, fluctuations in asset volatility appear to drive variation in firms’ financial soundness. Finally, the financial soundness of financial firms largely resembles that of nonfinancial firms.

We build a variation of the neoclassical growth model in which both wealth shocks (in the sense of wealth destruction) and financial shocks to households generate recessions. The model features three mild departures from the standard model: (1) adjustment costs make it difficult to expand the tradable goods sector by reallocating factors of production from nontradables to tradables; (2) there is a mild form of labor market frictions (Nash bargaining wage setting with Mortensen-Pissarides labor markets); (3) goods markets for nontradables require active search from households wherein increases in consumption expenditures increase measured productivity. These departures provide a novel quantitative theory to explain recessions like those in southern Europe without relying on technology shocks.

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.

This paper investigates the macroeconomic effects of cyclical fluctuations in marginal tax rates. It finds that systematically including tax variables in a standard real business cycle model substantially improves the model's ability to reproduce basic facts about postwar U.S. business cycle fluctuations. In particular, modeling fluctuations in personal and corporate income tax rates increases the model's predicted relative variability of hours and decreases its predicted correlation between hours and average productivity. Fluctuations in tax rates produce large substitution effects that alter the leisure/labor supply decision.