Mark Thoma sends us to: Summer 2018 Journal of Economic Perspectives: "Symposium: Macroeconomics a Decade after the Great Recession...
..."What Happened: Financial Factors in the Great Recession," by Mark Gertler and Simon Gilchrist At the onset of the recent global financial crisis, the workhorse macroeconomic models assumed frictionless financial markets. These frameworks were thus not able to anticipate the crisis, nor to analyze how the disruption of credit markets changed what initially appeared like a mild downturn into the Great Recession. Since that time, an explosion of both theoretical and empirical research has investigated how the financial crisis emerged and how it was transmitted to the real sector. The goal of this paper is to describe what we have learned from this new research and how it can be used to understand what happened during the Great Recession. In the process, we also present some new empirical work. We argue that a complete description of the Great Recession must take account of the financial distress facing both households and banks and, as the crisis unfolded, nonfinancial firms as well. Exploiting both panel data and time series methods, we analyze the contribution of the house price decline, versus the banking distress indicator, to the overall decline in employment during the Great Recession. We confirm a common finding in the literature that the household balance sheet channel is important for regional variation in employment. However, we also find that the disruption in banking was central to the overall employment contraction. Full-Text Access | Supplementary Materials
"Finance and Business Cycles: The Credit-Driven Household Demand Channel," by Atif Mian and Amir Sufi What is the role of the financial sector in explaining business cycles? This question is as old as the field of macroeconomics, and an extensive body of research conducted since the Global Financial Crisis of 2008 has offered new answers. The specific idea put forward in this article is that expansions in credit supply, operating primarily through household demand, have been an important driver of business cycles. We call this the credit-driven household demand channel. While this channel helps explain the recent global recession, it also describes economic cycles in many countries over the past 40 years. Full-Text Access | Supplementary
"Identification in Macroeconomics," by Emi Nakamura and Jón Steinsson This paper discusses empirical approaches macroeconomists use to answer questions like: What does monetary policy do? How large are the effects of fiscal stimulus? What caused the Great Recession? Why do some countries grow faster than others? Identification of causal effects plays two roles in this process. In certain cases, progress can be made using the direct approach of identifying plausibly exogenous variation in a policy and using this variation to assess the effect of the policy. However, external validity concerns limit what can be learned in this way. Carefully identified causal effects estimates can also be used as moments in a structural moment matching exercise. We use the term "identified moments" as a short-hand for "estimates of responses to identified structural shocks," or what applied microeconomists would call "causal effects." We argue that such identified moments are often powerful diagnostic tools for distinguishing between important classes of models (and thereby learning about the effects of policy). To illustrate these notions we discuss the growing use of cross-sectional evidence in macroeconomics and consider what the best existing evidence is on the effects of monetary policy. Full-Text Access | Supplementary Materials
"The State of New Keynesian Economics: A Partial Assessment," by Jordi Galí In August 2007, when the first signs emerged of what would come to be the most damaging global financial crisis since the Great Depression, the New Keynesian paradigm was dominant in macroeconomics. Ten years later, tons of ammunition has been fired against modern macroeconomics in general, and against dynamic stochastic general equilibrium models that build on the New Keynesian framework in particular. Those criticisms notwithstanding, the New Keynesian model arguably remains the dominant framework in the classroom, in academic research, and in policy modeling. In fact, one can argue that over the past ten years the scope of New Keynesian economics has kept widening, by encompassing a growing number of phenomena that are analyzed using its basic framework, as well as by addressing some of the criticisms raised against it. The present paper takes stock of the state of New Keynesian economics by reviewing some of its main insights and by providing an overview of some recent developments. In particular, I discuss some recent work on two very active research programs: the implications of the zero lower bound on nominal interest rates and the interaction of monetary policy and household heterogeneity. Finally, I discuss what I view as some of the main shortcomings of the New Keynesian model and possible areas for future research. Full-Text Access | Supplementary Materials
"On DSGE Models," by Lawrence J. Christiano, Martin S. Eichenbaum and Mathias Trabandt The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks. Full-Text Access | Supplementary Materials
"Evolution of Modern Business Cycle Models: Accounting for the Great Recession," Patrick J. Kehoe, Virgiliu Midrigan and Elena Pastorino Modern business cycle theory focuses on the study of dynamic stochastic general equilibrium (DSGE) models that generate aggregate fluctuations similar to those experienced by actual economies. We discuss how these modern business cycle models have evolved across three generations, from their roots in the early real business cycle models of the late 1970s through the turmoil of the Great Recession four decades later. The first generation models were real (that is, without a monetary sector) business cycle models that primarily explored whether a small number of shocks, often one or two, could generate fluctuations similar to those observed in aggregate variables such as output, consumption, investment, and hours. These basic models disciplined their key parameters with micro evidence and were remarkably successful in matching these aggregate variables. A second generation of these models incorporated frictions such as sticky prices and wages; these models were primarily developed to be used in central banks for short-term forecasting purposes and for performing counterfactual policy experiments. A third generation of business cycle models incorporate the rich heterogeneity of patterns from the micro data. A defining characteristic of these models is not the heterogeneity among model agents they accommodate nor the micro-level evidence they rely on (although both are common), but rather the insistence that any new parameters or feature included be explicitly disciplined by direct evidence. We show how two versions of this latest generation of modern business cycle models, which are real business cycle models with frictions in labor and financial markets, can account, respectively, for the aggregate and the cross-regional fluctuations observed in the United States during the Great Recession. Full-Text Access | Supplementary Materials
"Microeconomic Heterogeneity and Macroeconomic Shocks," by Greg Kaplan and Giovanni L. Violante In this essay, we discuss the emerging literature in macroeconomics that combines heterogeneous agent models, nominal rigidities, and aggregate shocks. This literature opens the door to the analysis of distributional issues, economic fluctuations, and stabilization policies—all within the same framework. In response to the limitations of the representative agent approach to economic fluctuations, a new framework has emerged that combines key features of heterogeneous agents (HA) and New Keynesian (NK) economies. These HANK models offer a much more accurate representation of household consumption behavior and can generate realistic distributions of income, wealth, and, albeit to a lesser degree, household balance sheets. At the same time, they can accommodate many sources of macroeconomic fluctuations, including those driven by aggregate demand. In sum, they provide a rich theoretical framework for quantitative analysis of the interaction between cross-sectional distributions and aggregate dynamics. In this article, we outline a state-of-the-art version of HANK together with its representative agent counterpart, and convey two broad messages about the role of household heterogeneity for the response of the macroeconomy to aggregate shocks: 1) the similarity between the Representative Agent New Keynesian (RANK) and HANK frameworks depends crucially on the shock being analyzed; and 2) certain important macroeconomic questions concerning economic fluctuations can only be addressed within heterogeneous agent models. Full-Text Access | Supplementary Materials
Symposium: Incentives in the Workplace
"Compensation and Incentives in the Workplace," by Edward P. Lazear Labor is supplied because most of us must work to live. Indeed, it is called "work" in part because without compensation, the overwhelming majority of workers would not otherwise perform the tasks. The theme of this essay is that incentives affect behavior and that economics as a science has made good progress in specifying how compensation and its form influences worker effort. This is a broad topic, and the purpose here is not a comprehensive literature review on each of many topics. Instead, a sample of some of the most applicable papers are discussed with the goal of demonstrating that compensation, incentives, and productivity are inseparably linked. Full-Text Access | Supplementary Materials
"Nonmonetary Incentives and the Implications of Work as a Source of Meaning," by Lea Cassar and Stephan Meier Empirical research in economics has begun to explore the idea that workers care about nonmonetary aspects of work. An increasing number of economic studies using survey and experimental methods have shown that nonmonetary incentives and nonpecuniary aspects of one's job have substantial impacts on job satisfaction, productivity, and labor supply. By drawing on this evidence and relating it to the literature in psychology, this paper argues that work represents much more than simply earning an income: for many people, work is a source of meaning. In the next section, we give an economic interpretation of meaningful work and emphasize how it is affected by the mission of the organization and the extent to which job design fulfills the three psychological needs at the basis of self-determination theory: autonomy, competence, and relatedness. We point to the evidence that not everyone cares about having a meaningful job and discuss potential sources of this heterogeneity. We sketch a theoretical framework to start to formalize work as a source of meaning and think about how to incorporate this idea into agency theory and labor supply models. We discuss how workers' search for meaning may affect the design of monetary and nonmonetary incentives. We conclude by suggesting some insights and open questions for future research. Full-Text Access | Supplementary Materials
"The Changing (Dis-)utility of Work," by Greg Kaplan and Sam Schulhofer-Wohl We study how changes in the distribution of occupations have affected the aggregate non-pecuniary costs and benefits of working. The physical toll of work is less now than in 1950, with workers shifting away from occupations in which people report experiencing tiredness and pain. The emotional consequences of the changing occupation distribution vary substantially across demographic groups. Work has become happier and more meaningful for women, but more stressful and less meaningful for men. These changes appear to be concentrated at lower education levels. Full-Text Access | Supplementary Materials
"Social Connectedness: Measurement, Determinants, and Effects," by Michael Bailey, Rachel Cao, Theresa Kuchler, Johannes Stroebel and Arlene Wong Social networks can shape many aspects of social and economic activity: migration and trade, job-seeking, innovation, consumer preferences and sentiment, public health, social mobility, and more. In turn, social networks themselves are associated with geographic proximity, historical ties, political boundaries, and other factors. Traditionally, the unavailability of large-scale and representative data on social connectedness between individuals or geographic regions has posed a challenge for empirical research on social networks. More recently, a body of such research has begun to emerge using data on social connectedness from online social networking services such as Facebook, LinkedIn, and Twitter. To date, most of these research projects have been built on anonymized administrative microdata from Facebook, typically by working with coauthor teams that include Facebook employees. However, there is an inherent limit to the number of researchers that will be able to work with social network data through such collaborations. In this paper, we therefore introduce a new measure of social connectedness at the US county level. Our Social Connectedness Index is based on friendship links on Facebook, the global online social networking service. Specifically, the Social Connectedness Index corresponds to the relative frequency of Facebook friendship links between every county-pair in the United States, and between every US county and every foreign country. Given Facebook's scale as well as the relative representativeness of Facebook's user body, these data provide the first comprehensive measure of friendship networks at a national level. Full-Text Access | Supplementary Materials...