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Ozge Akinci, Gianluca Benigno, and Albert Queralto
The COVID-19 outbreak has triggered unusually fast outﬂows of dollar funding from emerging market economies (EMEs). These outflows are known as “sudden stop” episodes, and they are typically followed by economic contractions. In this post, we assess the macroeconomic eﬀects of the COVID-induced sudden stop of capital flows to EMEs, using our open-economy DSGE model. Unlike existing frameworks, such as the Federal Reserve Board’s SIGMA model, our model features both domestic and international ﬁnancial constraints, making it well-suited to capture the eﬀects of an outﬂow of dollar funding. The model predicts output losses in EMEs due in part to the adverse eﬀect of local currency depreciation on private-sector balance sheets with dollar debts. The ﬁnancial stresses in EMEs, in turn, spill back to the U.S. economy, through both trade and ﬁnancial channels. The model-predicted output losses are persistent (consistent with previous sudden stop episodes), with financial effects being a significant drag on the recovery. We stress that we are only tracing out the effects of one particular channel (the stop of capital flows and its associated effect on funding costs) and not the totality of COVID-related effects.
Since the outbreak of the COVID-19 pandemic in late January, oil prices have fallen sharply. In this post, we compare recent price declines with those seen in previous oil price collapses, focusing on the drivers of such episodes. In order to do that, we break oil price shocks down into demand and supply components, applying the methodology behind the New York Fed’s weekly Oil Price Dynamics Report.
People across the world have cut back sharply on travel due to the Covid-19 pandemic, working from home and cancelling vacations and other nonessential travel. Industrial activity is also off sharply. These forces are translating into an unprecedented collapse in global oil demand. The nature of the decline means that demand is unlikely to respond to the steep drop in oil prices, so supply will have to fall in tandem. The rapid increase in U.S. oil production of recent years was already looking difficult to sustain before the pandemic, as evidenced by the limited profitability of the sector. Now, U.S. producers may have to bear the brunt of the global supply adjustment needed over the near term.
4/27: Following strong reader interest, we began sharing the Weekly Economic Index on the New York Fed’s public website. Look for it twice weekly on Tuesday and Thursday at 11:30 a.m.
Economists are well-practiced at assessing real activity based on familiar aggregate time series, like the unemployment rate, industrial production, or GDP growth. However, these series represent monthly or quarterly averages of economic conditions, and are only available at a considerable lag, after the month or quarter ends. When the economy hits sudden headwinds, like the COVID-19 pandemic, conditions can evolve rapidly. How can we monitor the high-frequency evolution of the economy in “real time”?
In recent years there has been a lot of interest in the effect of income inequality (heterogeneity) on the economy, from both academics and policymakers. Researchers have developed Heterogeneous Agent New Keynesian (HANK) models that incorporate heterogeneity and uninsurable idiosyncratic risk into the New Keynesian models that have become a cornerstone of monetary policy analysis. This research has argued that heterogeneity and idiosyncratic risk change many features of New Keynesian models – the
transmission of conventional monetary policy, the forward guidance puzzle, fiscal multipliers, the efficacy of targeted transfers and automatic stabilizers, among others. However, the source of the difference between HANK and representative agent New Keynesian (RANK) models remains unclear. This is because HANK models are typically not analytically tractable, leaving it unclear what exactly is driving the results. To shed light on the macroeconomic consequences of heterogeneity, we develop a stylized HANK model that contains key features present in more complicated HANK models.
Large firms play an integral role in aggregate economic activity owing to their size and production linkages. Events specific to these large firms can thus have significant effects on the macroeconomy. Quantifying these effects is tricky, however, given the complexity of the production process and the difficulty in identifying firm-level events. The recent pause in Boeing’s 737 MAX production is a striking example of such an event or “shock” to a large firm. This post applies a basic framework that is grounded in economic theory to provide a back-of-the envelope calculation of how the “737 MAX shock” could impact U.S. GDP growth in the first quarter of 2020.
In our previous post, we presented evidence suggesting that labor market indicators provide the most reliable information for dating the U.S. business cycle. In this post, we further develop the case. In fact, the unemployment rate has provided an almost perfect record of distinguishing the beginning of recessions in the post-war U.S. economy. We also show that using more granular labor market data, such as by region or industry, also provides valuable information about the state of the business cycle.
The study of the business cycle—fluctuations in aggregate economic activity between times of widespread expansion and contraction—is one of the foremost pursuits in macroeconomics. But even distinguishing periods of expansion and recession can be challenging. In this post, we discuss different conceptual approaches to dating the business cycle, study their past performance for the U.S. economy, and highlight the informativeness of labor market indicators.
William Chen, Marco Del Negro, Ethan Matlin, Reca Sarfati, and Andrea Tambalotti
This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since September 2019. As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE model Q & A.
Matthew Higgins, Thomas Klitgaard, and Michael Nattinger
Tariffs are a form of taxation. Indeed, before the 1920s, tariffs (or customs duties) were typically the largest source of funding for the U.S. government. Of little interest for decades, tariffs are again becoming relevant, given the substantial increase in the rates charged on imports from China. U.S. businesses and consumers are shielded from the higher tariffs to the extent that Chinese firms lower the dollar prices they charge. U.S. import price data, however, indicate that prices on goods from China have so far not fallen. As a result, U.S. wholesalers, retailers, manufacturers, and consumers are left paying the tax.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.
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