Using data from a prominent online platform for launching new digital products, we document that the composition of the platform's 'beta testers' on the day a new product is launched has a systematic and persistent impact on the venture's success. Specifically, we use word embedding methods to...

We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining...

Youth employment has been near historic lows in recent years, and racial gaps persist. This paper tests whether information frictions limit young people's labor market success with a field experiment involving over 43,000 youth in New York City. We build software that allows employers to quickly...

In a pilot program during the 2016-17 admissions cycle, the University of California, Berkeley invited many applicants for freshman admission to submit letters of recommendation. This proved controversial within the university, with concerns that this change would further disadvantage applicants...

This paper develops a model of repeated innovation with knowledge spillovers. The model's novel feature is that firms compete on two dimensions: 1) product quality or cost, where one firm's innovation ultimately spills over to other firms; and 2) distribution costs, where there are no spillovers...

Tech clusters like Silicon Valley play a central role for modern innovation, business competitiveness, and economic performance. This paper reviews what constitutes a tech cluster, how they function internally, and the degree to which policy makers can purposefully foster them. We describe the...

We examine how exposure of Chinese firms to the Covid-19 shock varied with a cluster index (measuring spatial agglomeration of firms in related industries) at the county level. Two data sources are used: entry flows of newly registered firms in the entire country, and an entrepreneur survey...

We study the informational content of factor structures in discrete triangular systems. Factor structures have been employed in a variety of settings in cross sectional and panel data models, and in this paper we formally quantify their identifying power in a bivariate system often employed in...

It is standard practice in empirical work to allow for clustering in the error covariance matrix if the explanatory variables of interest vary at a more aggregate level than the units of observation. Often, however, the structure of the error covariance matrix is more complex, with correlations...

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but...