Why Are China’s Households in the Doldrums?
A perennial challenge with China’s growth model has been overly high investment spending relative to GDP and unusually low consumer spending, something which China has long struggled to rebalance. As China attempts to move away from credit-intensive, investment-focused growth, the economy’s growth will have to rely on higher consumer spending. However, a prolonged household borrowing binge, COVID scarring and a deep slump in the property market in China have damaged household balance sheets and eroded consumer sentiment. In this post, we examine the impact of recent shocks on Chinese household behavior for clues around the outlook for reviving consumption and economic growth in China.
Who Uses “Buy Now, Pay Later”?
“Buy now, pay later” (BNPL) has become an increasingly popular form of payment among Americans in recent years. While BNPL provides shoppers with the flexibility to pay for goods and services over time, usually with zero interest, the Consumer Financial Protection Bureau (CFPB) has identified several areas of potential consumer harm associated with its growing use, including inconsistent consumer protections, and the risk of excessive debt accumulation and over-extension. BNPL proponents have argued that the service enables improved credit access and greater financial inclusion, with approval being quick and relatively easy. More research is needed to assess the overall risks and benefits of BNPL for consumers. As a first step, we draw on new survey data to examine the background and circumstances of consumers who receive and take up BNPL offers. We find both the availability and use of BNPL to be fairly widespread but see disproportionate take-up among consumers with unmet credit needs, limited credit access, and greater financial fragility. While BNPL expands financial inclusion, especially to those with low credit scores, there is a risk that these payment plans contribute to excessive debt accumulation and over-extension.
The New York Fed DSGE Model Forecast— September 2023
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 June 2023. 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.
Reintroducing the New York Fed Staff Nowcast
“Nowcasts” of GDP growth are designed to track the economy in real time by incorporating information from an array of indicators as they are released. In April 2016, the New York Fed’s Research Group launched the New York Fed Staff Nowcast, a dynamic factor model that generated estimates of current quarter GDP growth at a weekly frequency. The onset of the COVID-19 pandemic sparked widespread economic disruptions—and unprecedented fluctuations in the economic data that flow into the Staff Nowcast. This posed significant challenges to the model, leading to the suspension of publication in September 2021. Taking advantage of recent developments in time-series econometrics, we have since developed a more robust version of the Staff Nowcast model, one that better handles data volatility. In this post, we discuss the model’s new features, present estimates of current quarter GDP growth, and evaluate how the Staff Nowcast would have performed during the pandemic period. Today’s post marks the resumption of regular New York Fed Staff Nowcast releases, to be published each Friday.
How Large Are Inflation Revisions? The Difficulty of Monitoring Prices in Real Time
With prices quickly going up after the COVID-19 pandemic, inflation releases have rarely been as present in the public debate as in recent years. However, since inflation estimates are frequently revised, how precise are the real-time data releases? In this Liberty Street Economics post, we investigate the size and nature of revisions to inflation. We find that inflation estimates for a given month can change substantially as subsequent data vintages are released. As an example, consider March 2009. With the economy contracting amid the Global Financial Crisis, the twelve-month inflation rate for personal consumption expenditures (PCE) excluding food and energy dropped from an initial estimate of 1.8 percent to 0.8 percent in the current series. The difference is dramatic and points to the difficulty of monitoring inflation in real time. Our results suggest that there is significant uncertainty in measuring inflation, and the key features of the recent spike and subsequent moderation of inflation may look quite different in hindsight once further revisions have taken place.
Leader‑Follower Dynamics in Shareholder Activism
Activist shareholders play a central role in modern corporations, influencing the capital structure, business strategy, and governance of firms. Such “blockholders” range from investors who actively jawbone or break up firms to index funds that are largely passive in that they limit themselves to voting. In between, however, is a key group of blockholders that have historically focused on trading but have embraced activism as an established business strategy in the past few decades. Campaigns involving such “trading” blockholders have become ubiquitous, increasingly targeting large-capitalization firms; further, their attacks feature multiple activists, each with individual stakes that, in isolation, are unable to control targets. In this post, we ask three questions: (1) How do trading activists build stakes before an attack, while anticipating that other investors may have similar incentives? (2) Does the nature of strategic trading change relative to settings where activism is unlikely to occur? (3) Are there trade-offs between trading and the firm’s long-term value?