{"title":"Hamilton Versus Hamilton: Spurious Nonlinearities","authors":"Luiggi Donayre","doi":"10.2139/ssrn.3874223","DOIUrl":"https://doi.org/10.2139/ssrn.3874223","url":null,"abstract":"Using Monte Carlo simulations, this paper evaluates the ability of the trend-cycle decomposition approach of Hamilton (2018) to adequately identify asymmetries in business cycles fluctuations. By considering different specifications of linear and asymmetric processes consistent with previous estimates, the results indicate that the approach of Hamilton (2018) is unable to preserve true asymmetric behavior nor reproduce U.S. business cycles features, especially in highly persistent or mildly asymmetric processes, or in small samples. The findings are robust to the presence of a time-varying drift, the complexity of the autoregressive dynamics and symmetric nonlinearity. Furthermore, the approach of Hamilton (2018) generates spurious expansionary periods when none exist in the data-generating process. Interestingly, they occur, exclusively, in the case of Markov-switching models of the type introduced by Hamilton (1989), but not for other nonlinear models. Meanwhile, the distortions are also present in the case of symmetric nonlinearity. Based on these findings, caution is called into question when the approach is applied to processes that are thought to behave nonlinearly.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124095478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Keynes and his Consequences; A Theory of Stagflation","authors":"Craig Duddy","doi":"10.2139/ssrn.3899765","DOIUrl":"https://doi.org/10.2139/ssrn.3899765","url":null,"abstract":"Keynes attempted, in the general theory to develop a theory of the business cycle. However, this attempt was rather underwhelming given the significance of the subject matter. In this paper, our primary course of concern is not to give a scathing review overall, but rather to detail the fundamental fallacy that Keynes advocated. There is, in reality, no way to 'keep the boom, but abolish the slump.' Monetary expansion is not a tool by which new goods and services can be directly created, and to predicate ones economics wholly on a view of demand and not of production can only lead to incorrect and fallacious conclusions. What I hope to show is that the Austrian tradition should not fall into the same errors both Keynes, and their own predecessors did. We should not be either exclusively supply-side, or demand-side, we should recognise the dual interdependence of both on the structure of production.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"574 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117061434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Unified Approach for Jointly Estimating the Business and Financial Cycle, and the Role of Financial Factors","authors":"Tino Berger, Julia Richter, Benjamin Wong","doi":"10.2139/ssrn.3805578","DOIUrl":"https://doi.org/10.2139/ssrn.3805578","url":null,"abstract":"We jointly estimate the U.S. business and financial cycle through a unified empirical approach while simultaneously accounting for the role of financial factors. Our approach uses the Beveridge-Nelson decomposition within a medium-scale Bayesian Vector Autoregression. First, we show, both in reduced form and when we identify a structural financial shock, that variation in financial factors had a larger role post-2000 and a more modest role pre-2000. Our results suggest that the financial sector did play a role in overheating the business cycle pre-Great Recession. Second, while we document a positive unconditional correlation between the credit cycle and the output gap, the correlation of the lagged credit cycle and the contemporaneous output gap turns negative when we condition on a financial shock. The sign-switch suggests that the nature of the underlying shocks may be important for understanding the relationship between the business and financial cycles.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130326726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic Industry Uncertainty Networks and the Business Cycle","authors":"Jozef Baruník, Mattia Bevilacqua, R. Faff","doi":"10.2139/ssrn.3768370","DOIUrl":"https://doi.org/10.2139/ssrn.3768370","url":null,"abstract":"We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles. Classifying U.S. industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not create strong linkages in the network. Moreover, we find that this ex-ante network of uncertainty is a useful predictor of business cycles, especially when it is based on uncertainty hubs. The industry uncertainty network behaves counter-cyclically in that a tighter network tends to associate with future business cycle contractions.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124724532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Media, Economic Activity and Macroeconomic Expectations","authors":"S. Baz, L. Cathcart, Alexander Michaelides","doi":"10.2139/ssrn.3378043","DOIUrl":"https://doi.org/10.2139/ssrn.3378043","url":null,"abstract":"We construct indices based on newspaper mentions of a simple and repeated message (the word ``recession'') and show that they are useful coincident and leading indicators of U.S. economic activity, both in-sample and out-of-sample. Finance-specialized newspapers perform better than nonspecialized ones in forecasting economic activity, indicating how narratives might spread. Importantly, media coverage can affect individual expectations and economic decisions in the Michigan Survey of Consumer Expectations, and is correlated with Google searches for the word ``recession''. Our results provide evidence on how economic narratives might spread and affect actual economic decisions and therefore be important in understanding economic activity.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115421812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Jointly Determining the State Dimension and Lag Order for Markov-Switching Vector Autoregressive Models","authors":"Nan Li, S. Kwok","doi":"10.2139/ssrn.3800535","DOIUrl":"https://doi.org/10.2139/ssrn.3800535","url":null,"abstract":"This paper studies the problem of joint identification of the state dimension and lag order for a class of Markov-switching vector autoregressive (MS-VAR) models, in which all parameters are presumed to be regime-dependent. To this end, three complexity-penalized criteria AIC^{MS}, HQC^{MS} and SIC^{MS} are considered, and a new criterion AIC_c^{MS} is derived by minimizing the Kullback-Leibler (KL) divergence. The efficacy of the procedure is evaluated by means of Monte Carlo experiments. We illustrate the usefulness of the joint model selection procedure with empirical applications to the modeling of business cycles in the U.S. and Australia.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124979367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unemployment, Firm Dynamics, and the Business Cycle","authors":"A. Colciago, Stefano Fasani, L. Rossi","doi":"10.2139/ssrn.3724244","DOIUrl":"https://doi.org/10.2139/ssrn.3724244","url":null,"abstract":"We formulate and estimate a business cycle model which can account for key business cycle properties of labor market variables and other aggregates. Three features distinguish our model from the standard model with Search And Matching (SAM) frictions in the labor market: frictional firm entry, endogenous product variety, and investment in two assets: stocks and physical capital. Our model with firm dynamics displays an endogenous form of wage moderation. Thanks to the latter, it outperforms the SAM framework augmented with exogenous real wage rigidities.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"87 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132658089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bewley Banks","authors":"Rustam Jamilov, Tommaso Monacelli","doi":"10.2139/ssrn.3732172","DOIUrl":"https://doi.org/10.2139/ssrn.3732172","url":null,"abstract":"We develop a non-linear, quantitative macroeconomic model with heterogeneous monopolistic financial intermediaries, incomplete markets, default risk, endogenous bank entry, and aggregate uncertainty. The model generates a bank net worth distribution fluctuation problem analogous to the canonical Bewley-Huggett-Aiyagari-Imrohoglu environment. Our framework nests Gertler and Kiyotaki (2010) and the standard Real Business Cycle model as special cases. We present four general results. First, relative to the GK benchmark, banks' balance sheet-driven recessions can be significantly amplified, depending on the interaction of endogenous credit margins, the cyclicality of a precautionary lending motive and the (counter-) cyclicality of intermediaries' idiosyncratic risk. Second, equilibrium responses to aggregate exogenous shocks depend explicitly on the conditional distributions of bank net worth and leverage, which are endogenous time-varying objects. Aggregate shocks to banks' balance sheets that hit a concentrated and fragile banking distribution cause significantly larger recessions. A persistent consolidation in the U.S. banking sector that matches the one observed over 1980-2020 generates a large economic contraction and an increase in financial instability. Third, we document, and match, novel stylized facts on both the cross-section of credit margins and the cyclical properties of the first three moments of the cross-sectional distributions of financial intermediary assets, net worth, leverage, loan margins, and default risk. We find that shocks to capital quality and to leverage constraint tightness (\"financial shocks'') can match fluctuations in the U.S. financial sector very well. Finally, we use the model to identify and characterize episodes of systemic banking crises. Such events are associated with large economic recessions, spikes in bank leverage, and large drops in the number of intermediaries.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122687908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Networks and Business Cycles","authors":"Wu Zhu, Yucheng Yang","doi":"10.2139/ssrn.3718826","DOIUrl":"https://doi.org/10.2139/ssrn.3718826","url":null,"abstract":"The speed at which the US economy has recovered from recessions ranges from months to years. We propose a model incorporating innovation network, production network, and cross-sectional shock and show that their interactions jointly explain large variations in the recovery speed across recessions in the US. \u0000 \u0000Besides the production linkages, firms learn insights on production from each other through the innovation network. We show that shock's sectoral distribution plays a crucial role in its amplification and persistence when the innovation network takes a low-rank structure. % Under a low-rank innovation network, the shock's impact on future growth is greatly amplified and persistent when the shock follows the sectors' importance vector in the innovation network. In contrast, the amplification becomes weak, and the shock's impact decreases exponentially when the shock follows other directions. \u0000 \u0000We estimate a state-space model of the cross-sectional technology shock and document a set of new stylized facts on the structure of the innovation network and sectoral distribution of the shock for the US. We show that the specific low-rank network structure and the time-varying sectoral distribution of the shock can well explain the large variation in the recovery speed across recessions in the US. Finally, to emphasize the prevalence of the channel, we explore the application of the theory in asset pricing.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115520011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Forecasting US Recessions: The Role of Economic Uncertainty","authors":"V. Ercolani, Filippo Natoli","doi":"10.2139/ssrn.3710134","DOIUrl":"https://doi.org/10.2139/ssrn.3710134","url":null,"abstract":"This paper highlights the role of macroeconomic and financial uncertainty in predicting US recessions. In-sample forecasts using probit models indicate that these two variables are the best predictors of recessions at short horizons. Macroeconomic uncertainty has the highest predictive power up to 7 months ahead and becomes the second best predictor --- after the yield curve slope --- at longer horizons. Using data up to end-2018, out-of-sample forecasts show that uncertainty contributed significantly to lowering the probability of a recession in 2019, which indeed did not occur.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130812574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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