This paper examines which macroeconomic signals shape household expectations and finds that unemployment shocks play a more influential role than inflation shocks. Using daily data, we identify which announcements prompt households to revise their expectations. We construct two shock series—assuming households are either sophisticated or naive—based on the surprise components of announcements. Labor market news strongly influences both general economic sentiment and inflation expectations. Even when inflation rises and unemployment falls, households respond more to unemployment shocks. Most changes in inflation expectations are driven by labor market shocks. During negative supply and demand shocks, unemployment remains the dominant driver.

This paper examines the real effects of monetary policy in India through the lens of household-level heterogeneity. Using detailed microdata on consumption and asset holdings, we show that monetary policy shocks have significant effects on household consumption. Importantly, these effects vary systematically with households' positions in the wealth distribution. Households facing tighter financial constraints—those with limited liquid assets—exhibit stronger consumption responses to monetary policy shocks. By linking consumption data with asset portfolio information, we highlight the role of financial heterogeneity in shaping the transmission of monetary policy. Our findings underscore the importance of accounting for household-level differences in wealth and liquidity when evaluating the effectiveness of monetary policy.

This paper identifies the share of poor and wealthy hand-to-mouth (HtM) households in India. Wealthy HtM households hold substantial illiquid assets—such as housing and gold jewelry—but have limited liquid wealth, including cash and checking accounts. In contrast, poor HtM households lack both liquid and illiquid assets. We combine consumption and income data from CMIE with asset portfolio data from AIDIS using machine learning techniques, and apply the classification methodology of Kaplan, Violante, and Weidner (2014) to categorize households. We find that 47% of Indian households are hand-to-mouth, out of which 85% are wealthy HtM and 15% are poor HtM. While wealthy HtM households resemble non-HtM households in demographics and asset holdings, they exhibit high marginal propensities to consume out of transitory income shocks, similar to poor HtM households.

The savings rate in the Indian economy has declined sharply since 2007 and approached a low of 29% of GDP in 2020. In this paper, we take a closer look at the historical evolution of aggregate savings in India, as well as its different components. We use a simple framework that seeks to explain the time variation in savings over the sample period. We find that increased prosperity more than explains the decline in savings of Indian households, while the decline in old age dependency was a major offset. Our baseline forecast implies a roughly 2 percentage point decline in household savings as a fraction of GDP over the next five years. We build some medium term scenarios to understand the trade-offs going forward.

The labor force participation rate in the United States has exhibited a sharp drop after the 2008 recession.  Using the Current Population Survey, this paper first disentangles the trends in the participation rate along various demographic groups using shift-share analysis. Next, using time series, cross-section and individual variation, it examines the determinants of an individual's participation decision. Finally, it concludes with a discussion of the plausibility of various theories explaining the decline in participation from a labor supply lens. We find that the decrease in labor force participation seems to be voluntary, suggesting that it isn't driven by demand side factors.

In developing countries, weak enforcement of labor and tax regulations creates an opportunity for employers to collude with employees and manipulate the unemployment insurance system. In particular, workers who are eligible for benefits have an incentive to agree with their employers to transition into informality and share the proceeds from unemployment checks. We study the importance of this mechanism for the design of optimal unemployment insurance policies in a quantitative Diamond-Mortensen-Pissarides model calibrated with Brazilian data.